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Environmental, socio-demographic and behavioural determinants of malaria risk in the western Kenyan highlands: A case-control study
Abstract
To identify risk factors for uncomplicated malaria in highland areas of East Africa at higher risk of malaria epidemics, in order to design appropriate interventions.
Prospective, population-based, case-control study in the Nandi Hills, a highland area of western Kenya, to identify environmental, sociodemographic and behavioural factors associated with clinical malaria. Data were collected using field observation, a structured questionnaire, and a global positioning system device.
We interviewed 488 cases of slide-confirmed malaria and 980 age-matched controls. Multivariate analyses associated higher malaria risk with living <250 m of a forest [OR = 3.3 (95% CI 1.5, 7.1)], <250 m of a swamp [2.8 (1.3, 5.9)], <200 m of maize fields [2.0 (1.2, 3.4)], in the absence of trees <200 m [1.6 (1.2, 2.2)], on flat land [1.6 (1.2, 2.2)], in houses without ceilings [1.5 (1.1, 2.2)], in houses with a separate kitchen building [1.8 (1.4, 2.3)] and in households where the female household head had no education [1.9 (1.1, 3.1)]. Travelling out of the study site [2.2 (1.2, 4.1)] was also associated with increased risk. CONCLUSIONS; In this East African highland area, risk of developing uncomplicated malaria was multifactorial with a risk factor profile similar to that in endemic regions. Households within close proximity to forest and swamp borders are at higher risk of malaria and should be included in indoor residual spraying campaigns.
... 13 This finding is also consistent with those of other studies conducted in the East African highlands. [23][24][25] Furthermore, study participants in the latter age groups are more likely to stay at home and probably travel less as they might be overburdened by home affairs (cultivation, harvesting, and caring for their family) and also may use mosquito netting and other precautions against exposure. ...
... This finding is compatible with the result of many other similar studies done in Ethiopia, Kenya, and Peru. 10,12,20,[25][26][27][28] This relationship might be due to a combination of different factors including the movement of nonimmune people from these relatively malaria-free high-altitude villages to areas such as Asgede Tsimbla, Tahtay Adiyabo, and Humara, which are low lands with intensive malaria-endemic areas. When populations move from low-transmission areas to high-transmission areas, they are more susceptible to malaria than the resident population if exposed to an infective mosquito. ...
... Although people might express interest in mosquito net, anecdotal evidence suggests that even those who owned mosquito net did not use them. 25 This finding is compatible with similar studies conducted in Ethiopia and elsewhere. 10,12,25,32 In this regard, these findings could arise from a combination of factors that might include primarily vector density and the associated perception that risk might be low, the belief that only those who travel outside of their home village were at risk of getting malaria, belief that who use a bed net at home might fail to do so when they travel, or simply due to limited sample size. ...
Key goal and targets of the Ethiopian national malaria control strategy are to achieve malaria elimination within specific geographical areas with historically low malaria transmission and to reach near-zero malaria transmission in the remaining malarious areas by 2020. However, back and forth population movement between high-transmission and low-transmission area imposes challenge on the success of national malaria control programs. Therefore, examining the effect of human movement and identification of at-risk populations is crucial in an elimination setting. A matched case-control study was conducted among 520 study participants at a community level in low malaria transmission settings in northern Ethiopia. Study participants who received a malaria test were interviewed regarding their recent travel history. Bivariate and multivariate analyses were carried out to determine if the reported travel was related to malaria infection. Younger age (adjusted odds ratio [AOR] = 3.20, 95% confidence interval [CI]: 1.73, 5.89) and travel in the previous month (AOR = 11.40, 95% CI: 6.91, 18.82) were statistically significant risk factors for malaria infection. Other statistically significant factors, including lower educational level (AOR = 2.21, 95% CI: 1.26, 3.86) and nonagricultural in occupation (AOR = 2.0, 95% CI: 1.02, 3.94), were also found as risk factors for malaria infection. Generally, travel history was found to be a strong predictor for malaria acquisition in the high-altitude villages. Therefore, besides the existing efforts in endemic areas, targeting those who frequently travel to malarious areas is crucial to reduce malaria infection risks and possibility of local transmissions in high-altitude areas of northern Ethiopia.
... Although a number of forms of environmental degradation or ecosystem alteration could affect mosquito populations, deforestation is an increasingly studied factor in several locales across Asia, Sub-Saharan Africa, and, most prominently, Latin America (e.g., [5][6][7][8]). While a number of case studies identify links between forest loss and malaria or mosquito prevalence [5][6][7][8][9], whether relationship exists across areas or regions remains insufficiently examined. ...
... Although a number of forms of environmental degradation or ecosystem alteration could affect mosquito populations, deforestation is an increasingly studied factor in several locales across Asia, Sub-Saharan Africa, and, most prominently, Latin America (e.g., [5][6][7][8]). While a number of case studies identify links between forest loss and malaria or mosquito prevalence [5][6][7][8][9], whether relationship exists across areas or regions remains insufficiently examined. We attempt to contribute to this line of inquiry by imparting a cross-national analysis of less-developed, non-desert nations to examine the potential association deforestation and malaria prevalence across countries. ...
... Prior examinations of deforestation and malaria tend to focus on the epidemiological aspects of ecosystem change and mosquito habitat proliferation [5,6,[8][9][10]. While these studies provide key evidence on the direct mechanisms that cause deforestation to lead to increased levels of larvae, parasite concentrations, mosquito populations, or actual malaria rates [5,6,[8][9][10], they fail also to consider fully the wider socio-economic context in which forest loss occurs. ...
Malaria represents an infectious disease keenly tied to environmental conditions, as mosquitoes represent the disease vector. Many studies are beginning to document that changes in environmental conditions, such as deforestation, can greatly alter the density and activity of mosquito populations and therefore malaria rates. While numerous epidemiological studies examine the links between forest loss and mosquito proliferation in distinct locales, comparative assessments across multiple sites are lacking. We attempt to address this gap by imparting a cross-national analysis of less-developed, non-desert, malaria endemic nations. Using a structural equation model of 67 nations, we find positive associations between deforestation rates and malaria prevalence across nations. Our results also suggest that rural population growth and specialization in agriculture are two key influences on forest loss in developing nations. Thus, anthropogenic drivers of environmental degradation are important to consider in explaining cross-national variation in malaria rates.
... Furthermore, studies focused on projected increases in malaria transmission as a result of changes in climate should take into account the global decline of the disease by 60% from 2000 to 2015 mainly as a result of aggressive human interventions and treatment [25][26][27]. Therefore, a robust vulnerability assessment should not only take into account the impact of the climate-induced hazard to the population, but also the heterogeneity of the population and for malaria transmission, the differences in topography and hydrological characteristics of the landscape and other biological and socio-economic influences of transmission [16,[28][29][30][31][32][33][34][35][36] in a holistic and integrated manner [4,6,7]. Such an approach can incorporate an understanding of how changes in climate will impact the current burden of the disease (biophysical vulnerability). ...
... Comprehensive reviews of climate change and malaria transmission have been covered in other papers [21,[46][47][48]. Some of these studies have developed suitable environmental, socio-demographic and behavioural indicators of malaria risk at regional, community and household levels [15,21,33,[48][49][50]. This previous knowledge and expert consultations were used to capture relevant knowledge about the system and to identify the relationships between key variables influencing risk of malaria infection in East Africa. ...
... Sensitivity analysis can reveal the relative significance or leverage of driving variables, providing an objective basis to identify a subset of variables for model formulation. [48,49,74] 19 Immune status Lowered immunity to malaria due to pregnancy or inexposure; acquired immunity to malaria from long term exposure [48,49,79,89,90] 20 Interactions Co-infections with other diseases such as HIV increase likelihood and severity of infection [15,50] 21 Drug resistance Resistance of the malaria parasite to drugs/parasite evolution [15,48,50] Socio-economic variables 22 Urbanisation Expansion of urban areas and overcrowding in cities [49] 23 Population migration/travel Movement of people from low risk areas to malaria-endemic or epidemicprone areas and vice versa [48,50] 24 Nutritional status Poor health as a result of undernutrition or malnutrition [48,49] 25 Gender Gender roles, expectations and cultural customs [48,49] 26 Poverty Socio-economic conditions; household income, food and household assets [15,48,49,74] 27 Religious beliefs Religion or superstitions in understanding or managing malaria and/or climate change impacts [15,49] 28 Perception Knowledge and understanding of disease [15,33,49] 29 Type of house House with grass-thatched roof and mud walls (semi-permanent) or Bbrick house with tiled or aluminium roof (permanent); house with separate kitchen, house with ceiling and house with open eaves [33,48,49] 30 Education level of household head Education level of male or female head of household [33] 31 Health-seeking behaviour Willingness to seek treatment for malaria; households with malaria medicine in stock, self-medication, tradition/cultural norms and practices in malaria management [48,49] 32 Net use Use of insecticide-treated bed nets to prevent malaria infection [15,33,74] 33 Environmental controls Keeping area around the houses cleared of shrubs and other overgrowth; safe disposal of plastics and other water-retaining containers [15,33] 34 Quality of health systems Health services and policy; availability of health facilities; access to healthcare; quality of healthcare and capacity for malaria treatment [15,47,48,50] ...
Background
Malaria is one of the key research concerns in climate change-health relationships. Numerous risk assessments and modelling studies provide evidence that the transmission range of malaria will expand with rising temperatures, adversely impacting on vulnerable communities in the East African highlands. While there exist multiple lines of evidence for the influence of climate change on malaria transmission, there is insufficient understanding of the complex and interdependent factors that determine the risk and vulnerability of human populations at the community level. Moreover, existing studies have had limited focus on the nature of the impacts on vulnerable communities or how well they are prepared to cope. In order to address these gaps, a systems approach was used to present an integrated risk and vulnerability assessment framework for studies of community level risk and vulnerability to malaria due to climate change.
Results
Drawing upon published literature on existing frameworks, a systems approach was applied to characterize the factors influencing the interactions between climate change and malaria transmission. This involved structural analysis to determine influential, relay, dependent and autonomous variables in order to construct a detailed causal loop conceptual model that illustrates the relationships among key variables. An integrated assessment framework that considers indicators of both biophysical and social vulnerability was proposed based on the conceptual model.
Conclusions
A major conclusion was that this integrated assessment framework can be implemented using Bayesian Belief Networks, and applied at a community level using both quantitative and qualitative methods with stakeholder engagement. The approach enables a robust assessment of community level risk and vulnerability to malaria, along with contextually relevant and targeted adaptation strategies for dealing with malaria transmission that incorporate both scientific and community perspectives.
... Overnight travel has been associated with higher malaria incidence in western Kenya in multiple studies [23][24][25] but prevention strategies used while traveling and changes in usual prevention behaviors have not been well explored as facilitators of this increased risk. We used data from an endemic lowland and an epidemic highland site in western Kenya to explore types of prevention strategies undertaken when traveling and how use of LLIN differs while sleeping at home vs. while traveling. ...
... Our results are consistent with several contemporary studies of travel-related Plasmodium infection in sub-Saharan Africa. Our previous work in the region demonstrates the risks of travel to highland travelers has been persistent for over a decade [25]. Maleded et al. (2018) found that having traveled to a highly-endemic lowland region of Ethiopia from a low-risk region had a confounding effect on infection in a matched case-control study [27]. ...
Background
Overnight travel predicts increased likelihood of Plasmodium infection and may introduce parasite strains to new areas, but deviations from routine at-home use of long-lasting insecticidal nets (LLINs) during travel are not well studied.
Methods
Cross-sectional data were taken in 2015 from the western Kenyan highlands and lowlands. Household surveys assessed individual travel activity during the previous month, LLIN use (at home and away), and current Plasmodium infection status. Crude and adjusted logistic regression was used to estimate the odds ratios (OR) of current malaria infection relative to travel within the last month.
Results
Highland residents who had traveled were more likely to have Plasmodium infection at the time of interview than highland residents who had not traveled (adjusted OR = 4.09 [1.60, 10.52]). Alternately, in the lowlands those who traveled overnight were significantly less likely to be infected vs non-travelers (adjusted OR = 0.56 [0.39,0.96]). Rates of LLIN use during travel were lower than reported rates while at home. Despite this, among travelers, LLIN use during travel was not associated with likelihood of Plasmodium infection for either region.
Conclusions
Travel had heterogeneous associations with infection status for the lowlands and highlands of western Kenya. Given the higher prevalence of malaria in the lowlands, travel is unlikely to increase likelihood of exposure. Conversely, travel from the lower-prevalence highlands may have taken respondents to higher prevalence areas. LLIN use while traveling differed from at-home habits and may depend on availability of LLINs where the traveler sleeps.
... These factors in uence risk status of malaria, level of susceptibility, social interaction as well as behaviours, thereby promoting the disease occurrence by creating favourable environment for the malaria vectors to thrive (Ernst et al., 2006). The concept of human ecology of disease has since been a principal constituent in geographic approach to study the predisposing factors towards disease in human society (Pascual et al., 2006;Ernst et al., 2009Peterson et al., 2009). The human ecology entails the various manners in which human behaviour in its sociodemographic and cultural perspectives interact with the environment to promote or hinder the occurrence of malaria among susceptible host. ...
... The socio-economic status, housing conditions, educational level have signi cant impact on the risk status of malaria. For instance, people living in close proximity, about 450m away from vector breeding sites, incessant or recent migration to malaria endemic regions, weedy surroundings, houses without ceilings, houses with a separate kitchen building, living within 200m of a maize eld and household in which the heads had no formal education are all at an increased risk of malaria infection in the highlands (Ernst et al., 2009;Peterson et al., over-emphasized (Jamison et al., 1993). ...
Studies highlighting the influence of sociodemographic, cultural and environmental factors on malaria incidence have been able to elucidate the risk status of malaria. The sociodemographic, cultural and environmental risk variables influencing malaria occurrence was evaluated.
Blood samples were collected from 360 multistage systematically selected household heads in Epe and Orimedu. Pretested and structured questionnaires were administered to the participants to obtain data related to their sociodemography, mosquito prevention practices and environmental factors of vulnerability to malaria. Potential risk factors for malaria infection occurrence was analyzed using binary logistic regression (Odds Ratio, O.R). Chisquare (X²) was used to analyze the relationship between malaria outcome and bednet ownership, standard mosquito prevention practices awareness, presence of surrounding stagnant pools and possession of window/door nets.
Malaria risk was relatively high among participants aged 60 years and above (O.R=1.35), secondary school leavers (O.R=2.51), pensioners (O.R=3.00), participants without previous episodes (1.33) and participants who are not aware of malaria (O.R=2.11). Low malaria risk was observed among participants: who sought treatment in health facilities (O.R=0.00) and who knew that malaria can be prevented (O.R=0.54). Malaria prevalence was high among participants who own bednet(s) (x̄²(3) = 1.81, P0.57>0.05), have windows/door nets (x̄²(3) = 2.33, P0.95>0.05) and who do not have surroundings stagnant pools (x̄²(3) = 1.17, P0.33>0.05).
Age, educational level, occupation, previous malaria episodes, treatment facility of choice, malaria awareness and knowledge about mosquito prevention practices influence malaria risk status. However, bed net ownership, possession of window/door nets and absence of surrounding puddles do not significantly reduce malaria incidence.
... 8 The study sites are located approximately 20 km apart and share similar ranges of altitudes (Kip: 1,941-2,108 m; Kap: 1,887-2,065 m). 8,9 The western edge of Kip borders the Nandi North forest, and the large Kimondi swamp borders the eastern edge of Kip and the western edge of Kap. 8,9 Both sites experience unstable highly seasonal malaria transmission patterns. ...
... 8,9 The western edge of Kip borders the Nandi North forest, and the large Kimondi swamp borders the eastern edge of Kip and the western edge of Kap. 8,9 Both sites experience unstable highly seasonal malaria transmission patterns. Figure 1 details the study area, including the locations of the households and health centers. ...
The use of spatial data in malaria elimination strategies is important to understand whether targeted interventions against malaria can be used, particularly in areas with limited resources. We previously documented consistent areas of increased malaria incidence in the epidemic-prone area of Kipsamoite in highland Kenya from 2001 to 2004. In this area and a neighboring subcounty (Kapsisiywa), malaria incidence decreased substantially in 2005, going from peak incidence of 31.7 per 1,000 persons in June 2004 to peak incidence of 7.4 per 1,000 persons in May 2005. Subsequently, the use of indoor residual spraying and artemisinin combination therapy malaria treatment led to a possible interruption of malaria transmission for a 13-month period from 2007 to 2008, after which the incidence returned to very low levels until an epidemic in April-July 2013. In the present study, we used novel kernel density estimation methods to determine whether areas of increased malaria incidence were consistent in six periods of peak incidence from 2003 to 2013, and to assess patterns of incidence in the period before versus. after the period of possible interruption. Areas of highest incidence differed during peak malaria transmission periods over the years 2003-2013, and differed before and after the potential malaria interruption. In this epidemic-prone region with very low malaria transmission, consistent malaria "hotspots" identified in a time of higher transmission are no longer present. Ongoing assessment of spatial malaria epidemiology to identify and target current areas of elevated malaria risk may be important in campaigns to control or eliminate malaria in epidemic-prone areas.
... 14,17,18 Within sub-Saharan Africa, previous studies have provided empirical evidence demonstrating a general association between travel and individual parasitemia, especially among individuals returning to lower prevalence areas. [19][20][21][22][23][24] Not all types of travel pose the same risk for infection nor does travel necessarily translate into a significant threat to lowprevalence areas. An individual's duration and frequency of travel, risk while traveling, and risk management behaviors contribute to the probability of acquiring parasites. ...
... 30 Previous studies on this topic have often been health facility based, using a case-control design to compare travel exposure and infection among patients. [19][20][21][22][23][24] That design, although providing insights into the role of travel on individual malaria infection, does not lend itself to estimates of the relative importance of importation to current malaria prevalence and has often been limited in its ability to consider differences in risk due to characteristics of travel. Not all travel impose a substantial risk to malaria infection, and consideration of risk at trip destination is important; movement between areas with little transmission or during times with low vector activity is unlikely to have a substantial impact on travelers and onward transmission compared with travel to highly endemic areas. ...
As Zambia continues to reduce its malaria incidence and target elimination in Southern Province, there is a need to identify factors that can reintroduce parasites and sustain malaria transmission. To examine the relative contributions of types of human mobility on malaria prevalence, this analysis quantifies the proportion of the population having recently traveled during both peak and nonpeak transmission seasons over the course of 2 years and assesses the relationship between short-term travel and malaria infection status. Among all residents targeted by mass drug administration in the Lake Kariba region of Southern Province, 602,620 rapid diagnostic tests and recent travel histories were collected during four campaign rounds occurring between December 2014 and February 2016. Rates of short-term travel in the previous 2 weeks fluctuated seasonally from 0.3% to 1.2%. Travel was significantly associated with prevalent malaria infection both seasonally and overall (adjusted odds ratio [AOR]: 2.55; 95% CI: 2.28-2.85). The strength of association between travel and malaria infection varied by travelers' origin and destination, with those recently traveling to high-prevalence areas from low-prevalence areas experiencing the highest odds of malaria infection (AOR: 7.38). Long-lasting insecticidal net usage while traveling was associated with a relative reduction in infections (AOR: 0.74) compared with travelers not using a net. Although travel was directly associated with only a small fraction of infections, importation of malaria via human movement may play an increasingly important role in this elimination setting as transmission rates continue to decline.
... Earthen roof as well as open eaves has been reported to be associated with increase in malaria risk [16]. However, in western Kenyan highlands, open eaves and uncovered windows did not appear to have an effect on the malaria incidence/ prevalence [17]. It was observed that, 396 (88%) people with separate kitchen were living in concrete houses, while the concrete houses were observed to have less malaria incidence/ prevalence. ...
... The presence of a separate kitchen was significantly associated with reduced malaria prevalence in the present study and similar results were also reported from Ethiopia where absence of separate kitchen was shown to be associated with increased malaria risk [18]. However, findings from western Kenyan highlands showed that separate kitchen had been reported to be related to higher risk of malaria incidence [7,17]. It is well known fact that presence of a separate kitchen is likely to reflect their sound financial status capable of constructing separate rooms with better personal protection methods from vectors. ...
Background
Household and environmental factors are reported to influence the malaria endemicity of a place. Hence, a careful assessment of these factors would, potentially help in locating the possible areas under risk to plan and adopt the most suitable and appropriate malaria control strategies. MethodsA cross-sectional household survey was carried out in the study site, Besant Nagar, Chennai, through random sampling method from February 2014 to February 2015. A structured interviewer-administered questionnaire was used to assess selected variables of demography, structural particulars of a household, usage of repellents, animals on site, presence of breeding habitats and any mosquito/vector breeding in the household, malaria/vector control measures undertaken by government in each houses. The data was collected through one to one personal interview method, statistically analysed overall and compared between the households/people infected with malaria within a period of 1 year and their non-infected counterparts of the same area. ResultsPresence of malaria was found to be significantly associated with the occupation, number of inhabitants, presence of a separate kitchen, availability of overhead tanks and cisterns, immatures of vector mosquitoes, presence of mosquito breeding and type of roof structures (p < 0.05). However, age, gender, usage of repellents, animals on site, number of breeding habitats or detection of vector breeding did not significantly associate with the malaria incidence/prevalence. Conclusions
The survey revealed various demographic, household and environmental factors likely to associate with the malaria incidence/prevalence in an urban slum of Chennai. The socio-demographic and household variables have revealed disparities in malaria infection from the present cross sectional study. The absence of significant association with many parameters indicates the probable role of other confounding factors which influence the malaria prevalence.
... were not hypothesised to be associated with SEP in this study population, since LLINs and all healthcare were provided free of charge. Other household-level risk factors for malaria include distance to larval habitats [26], distance to village periphery [27], urbanicity [28] and the density of livestock nearby [29]; which were outside the scope of this study. In turn, malaria imposes costs that can cause poverty, but this feedback loop was not analysed in this study [30,31]. ...
... Uganda [18] and SSA [19] have observed that well-built housing, with closed eaves and modern wall and roof materials, is associated with lower malaria risk through reduced house entry by mosquito vectors, and that measures of higher urbanicity in Uganda can be associated with lower HBR [28]. Second, we found that food security (access to sufficient food) may also mediate the association between poverty and malaria. ...
While malaria remains a major global public health problem, total annual incidence fell by 30% during 2000–2013, largely due to the scale–up of long–lasting insecticide–treated nets and indoor residual spraying. In the future, sustainable methods of control and elimination are needed to maintain this progress. Since malaria is associated with poverty, malaria control and economic development can be mutually supportive. This thesis tests specific hypotheses relating to the causal pathways between poverty and malaria, to identify potential routes to controlling malaria alongside development.
Two systematic reviews found that in sub-Saharan Africa: (1) parasite prevalence and clinical malaria incidence are on average halved in the wealthiest children, compared to the poorest within a community and (2) parasite prevalence and clinical malaria incidence are on average halved in residents of modern housing, compared to traditional housing. In-depth interviews and cross-sectional surveys collected socioeconomic information for all children aged six months to 10 years living in 100 households, who were followed for 36 months in Nagongera, an agrarian and highly endemic setting in rural Uganda. Analyses of the relationships between socioeconomic position (SEP), potential determinants of SEP and malaria found that: (3) relative success in smallholder agriculture was associated with higher SEP, (4) human biting rate (HBR) and parasite prevalence were approximately halved in children of highest SEP, compared to the poorest, (5) wealth indices, income and education were more sensitive indicators of socioeconomic inequalities in malaria risk than occupation, (6) HBR and parasite prevalence were halved in modern housing, compared to traditional housing and (7) house quality may partly explain the association between SEP and malaria.
Together, these studies indicate that housing improvements and agricultural development interventions to reduce poverty merit further investigation as ‘intersectoral’ interventions against malaria.
... • there is an inverse relationship between temperature (hence altitude and latitude) and the length of the plasmodium growth-cycle [4,30,36,37]; • the micro-climate of forests enhances anophelines breeding sites and prolongs their survival as adults [38,39]; ...
... This can be explained by the biology of the disease, as we have noted earlier. The literature suggests that these places provide not only a conducive environment for successful completion of the plasmodium growth-cycle [4,30,36,37] but also a suitable breeding site and feeding ground for the anopheles vector [29,[38][39][40]. Small increases in malaria risk are also associated with being male and with being over age 55. ...
Background
Despite being one of the world’s most affected regions, only little is known about the social and spatial distributions of malaria in Indonesian Papua. Existing studies tend to be descriptive in nature; their inferences are prone to confounding and selection biases. At the same time, there remains limited malaria-cartographic activity in the region. Analysing a subset (N = 22,643) of the National Basic Health Research 2007 dataset (N = 987,205), this paper aims to quantify the district-specific risk of malaria in Papua and to understand how socio-demographic/economic factors measured at individual and district levels are associated with individual’s probability of contracting the disease.
Methods
We adopt a Bayesian hierarchical logistic regression model that accommodates not only the nesting of individuals within the island’s 27 administrative units but also the spatial autocorrelation among these locations. Both individual and contextual characteristics are included as predictors in the model; a normal conditional autoregressive prior and an exchangeable one are assigned to the random effects. Robustness is then assessed through sensitivity analyses using alternative hyperpriors.
Results
We find that rural Papuans as well as those who live in poor, densely forested, lowland districts are at a higher risk of infection than their counterparts. We also find age and gender differentials in malaria prevalence, if only to a small degree. Nine districts are estimated to have higher-than-expected malaria risks; the extent of spatial variation on the island remains notable even after accounting for socio-demographic/economic risk factors.
Conclusions
Although we show that malaria is geography-dependent in Indonesian Papua, it is also a disease of poverty. This means that malaria eradication requires not only biological (proximal) interventions but also social (distal) ones.
... Mathematical modelling shows how human movement between low malaria-endemic areas and high malariaendemic areas resulted in regular importation of malaria parasites into areas that would otherwise be non-endemic and can become an epicentre for ongoing transmission [8][9][10][11][12]. Furthermore, studies from many countries aiming to eliminate malaria and are bordering higher burden neighbouring countries indicated that transmission persisted as a consequence of a high number of imported cases [13][14][15][16][17]. Churcher et al. [18] showed evidence that controlled non-endemic malaria areas (which indicates that malaria transmission with current control intervention cannot be self-sustained locally if importation ceased) has been reached once 32% to 48% of reported malaria cases are imported cases. ...
Background
Border malaria is a major obstacle for the malaria elimination in Saudi Arabia. Today, the southern border of Saudi Arabia is a region where malaria cases are resurging, and malaria control is dwindling mainly due to the humanitarian crisis and the conflict in Yemen. This study analyses the current border malaria epidemiology along the southern border of Saudi Arabia from 2015 to 2018.
Methods
All reported cases maintained by the malaria elimination centres in Aledabi and Baish, Jazan Province, Saudi Arabia, from 2015 to 2018 were analysed to examine the epidemiological changes over time. Pearson’s Chi-Square test of differences was utilized to assess differences between the characteristics of imported and local causes and between border cases. A logistic regression model was used to predict imported status was related to living along side of the border area.
Results
A total of 3210 malaria cases were reported in Baish and Aledabi malaria centres between 2015 and 2018, of which 170 were classified as local cases and 3040 were classified as imported cases. Reported malaria cases were mainly among males, within the imported cases 61.5% (1868/3039) were residents of the border areas.
Conclusions
Given the complexity of cross-border malaria, creating a malaria buffer zone that covers a certain margin from both sides of the border would allow for a joint force, cross-border malaria elimination programme. To initiate a malaria elimination activity and cases reported as belonging to this zone, rather than being pushed from one country to the other, would allow malaria elimination staff to work collaboratively with local borderland residents and other stakeholders to come up with innovative solutions to combat malaria and reach malaria-free borders.
... The Western Kenyan highlands is classified as mixed endemic and epidemic-prone malaria transmission area malaria (Division of National Malaria Programme (DNMP) [Kenya] ICF, 2021a). Several studies have investigated the associations between climate change and changes in malaria transmission in this region, with biophysical data showing an increased risk of malaria transmission under climate change (Githeko and Ndegwa, 2001;Zhou et al., 2004;Minakawa et al., 2005;Yanda et al., 2006;Cohen et al., 2008;Pascual et al., 2008;Ernst et al., 2009;Hashizume et al., 2009;Munga et al., 2009;Wandiga et al., 2009;Chaves et al., 2012;McCann et al., 2014;Sewe et al., 2015Sewe et al., , 2017Akpan et al., 2019;Matsushita et al., 2019). However, there is a lack of studies assessing climate change and malaria risk in the context of other biological, ecological, demographic, cultural and socio-economic factors which can mediate exposure, vulnerability and response to projected risks at a local level (Bates et al., 2004;Protopopoff et al., 2009;Onyango et al., 2016). ...
Climate change has been linked to increasing rates of malaria infection in Western Kenya. Projections show an increased risk of malaria infection under climate change scenarios, impacting vulnerable populations and placing millions of people at risk. Developing suitable risk management strategies requires understanding the hazard, exposure, vulnerability and response to climate change and malaria risk in the context of other local environmental, socio-economic and socio-cultural factors (including gender) that influence exposure, vulnerability and capacity to cope. This paper draws upon two analytical frameworks, using data gathered from focus group discussions with small-scale farmers in Western Kenya: The Intergovernmental Panel on Climate Change (IPCC) Risk Assessment Framework; and Feminist Political Ecology (FPE) to analyze social constructions underpinning farming responsibilities and decision-making power and how these influence the gendered dimensions of exposure, vulnerability and response to climate change and malaria risk in the community. This paper finds that gender influences the risk of malaria through feminization of agricultural activities in the region, socially constructed gendered responsibilities for care and farm work, which increases exposure and vulnerability to mosquito bites and malaria infection, and socially constructed rights of women to make farming decisions and manage farm income, which influences their capacity to manage risk and cope in the long term. Drawing on these findings, this paper proposes that an intersectional gender lens needs to be incorporated into climate and malaria adaptation policy and programming. It concludes with recommendations for implementing the UNFCCC Enhanced Lima Work Program on Gender at the country levels and the development of gender-responsive climate change and malaria risk management.
... It is important to consider this modification because less than half of houses in a typical urban area in a LMIC have ceilings [53], implying an even lower proportion in rural areas. Four studies conducted in East and West Africa showed that ceilings reduced mosquito entry, and this led to reduced risk of acquiring malaria [40,[53][54][55]. The strength of ceilings is that it is associated with other desirable properties, such as cooler indoor temperatures and modern aesthetics [56,57]. ...
Background
Significant progress in malaria prevention during the past two decades has prompted increasing global dialogue on malaria elimination. Recent reviews on malaria strategies have focused mainly on long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS), with little emphasis on other prevention methods. This article is a scoping review of literature on malaria prevention methods beyond LLINs and IRS in low- and middle-income countries (LMICs).
Methods
This scoping review found articles published between from 1994 to 2020. Studies were obtained from a search of the PubMed, the Cochrane Library and Social Science abstracts. Grey literature and manual search of secondary references was also done. The search strategy included all study designs but limited only to English. Three independent reviewers performed the selection and characterization of articles, and the data collected were synthesized qualitatively.
Results
A total of 10,112 studies were identified among which 31 met the inclusion criteria. The results were grouped by the 3 emerging themes of: housing design; mosquito repellents; and integrated vector control. Housing design strategies included closing eves, screening of houses including windows, doors and ceilings, while mosquito repellents were mainly spatial repellents, use of repellent plants, and use of plant-based oils. Integrated vector control included larvae source management. Evidence consistently shows that improving housing design reduced mosquito entry and malaria prevalence. Spatial repellents also showed promising results in field experiments, while evidence on repellent plants is limited and still emerging. Recent literature shows that IVM has been largely ignored in recent years in many LMICs. Some malaria prevention methods such as spatial repellents and IVM are shown to have the potential to target both indoor and outdoor transmission of malaria, which are both important aspects to consider to achieve malaria elimination in LMICs.
Conclusion
The scoping review shows that other malaria prevention strategies beyond LLINs and IRS have increasingly become important in LMICs. These methods have a significant role in contributing to malaria elimination in endemic countries if they are adequately promoted alongside other conventional approaches.
... Malaria is considered to be a disease of the poor [45][46][47], and several studies have shown significant association between poverty and malaria [48,49]. There are also studies that have shown no significant association between malaria and SES of the household [17,[50][51][52]. Interestingly, even though prevalence of malaria is higher in poorest, after adjusting the other socio-economic variables, richest were found to have slightly higher risk of malaria than the other economic categories. ...
Background
Even though malaria cases have drastically come down in the last decade, malaria remains a serious public health concern in many parts of India. National Framework for Malaria Elimination in India (2016–2030) has been launched with the goal to eliminate malaria by 2030. Understanding the socio-economic and household determinants of malaria at the national level will greatly aid India’s malaria elimination efforts.
Methods
The data from Longitudinal Ageing Survey of India (LASI) Wave 1 (2017–2018) survey comprising 70,671 respondents ≥ 45 years across all the States and Union Territories were used for the analysis. Simple and multiple logistic regressions were used to obtain the unadjusted and adjusted odds ratio respectively of the socio-economic and household variables.
Results
The major socio-economic variables that increase the likelihood of malaria are caste (‘scheduled tribes’), low education levels and rural residence. The scheduled tribes have 1.8 times higher odds of malaria than the scheduled castes (AOR: 1.8; 95% CI: 1.5–2.1). Respondents with high school education (6–12 grade) (AOR: 0.7; 95% CI: 0.6–0.8) and college education (AOR: 0.5; 95% CI: 0.4–0.6) had a very low risk of malaria than those with no school years. Rural residence and occupation (agriculture and allied jobs) also increases the odds of malaria. The major housing determinants are household size (≥ 6), housing type (kutcha), use of unclean fuel, outside water source, improper sanitation (toilet facilities) and damp wall/ceiling.
Conclusions
The study has identified the major socio-economic and housing factors associated with malaria in adults aged 45 and above. In addition to vector and parasite control strategies in the tribal dominated regions of India, improving literacy and housing conditions may help India’s malaria elimination efforts.
... Despite their lack of association in this study, many studies have also indicated that environmental risk factors are also predictors of malaria. For instance, the presence of forests near house and plants used for fencing [41], and living in areas where stagnant water or irrigation existed [16,[43][44][45] were all shown to be associated with greater odds of the disease in other studies. Lack of association of these factors in the present study could be attributed due to factors like the presence of stagnant water, forests near home, intermittent rivers and living together with livestock's were lower both among the cases and controls. ...
Abstract Background Malaria is a major health problem in Ethiopia. Sleeping under long-lasting insecticidal nets (LLINs) is its major control strategy. Despite high LLINs use (84%) in Ziway-Dugda District, malaria remained a public health problem, raising concern on its effectiveness. Understanding the effectiveness of malaria control interventions is vital. This study evaluated the effectiveness of LLINs and determinants of malaria in Ziway-Dugda District, Arsi Zone Ethiopia. Methods A matched case–control study was conducted among 284 study participants (71 cases and 213 controls) in Ziway-Dugda District, Arsi Zone, Ethiopia from March to May, 2017. Three health centers were selected randomly, and enrolled individuals newly diagnosed for malaria proportionally. Cases and controls were individuals testing positive and negative for malaria using rapid diagnostic tests. Each case was matched to three controls using the age of (5 years), gender and village of residence. The information was collected using pre-tested structured questionnaires through face to face interviews and observation. Data were entered into Epi-Info version 3.5, and analysed using Stata version-12. Conditional logistic regression was performed, and odds of LLINs use were compared using matched Adjusted Odds Ratio (AOR), 95% confidence interval (CI) and p-value of
... The wealth index lost its significance in the presence of other variables, and could not be included in final model. This is similar to findings to studies carried out in Tanzania [60] Ethiopia [32] and Kenya [61], which shows that SES had no association with malaria infection. Worrall et al. in a systematic review of nine studies, revealed that two studies found a significant positive relationship between poverty and malaria, four studies found no significant relationship and three studies demonstrated mixed results [55]. ...
Background
Malaria is known as a disease of poverty because of its dominance in poverty-stricken areas. Madhya Pradesh state in central India is one of the most vulnerable states for malaria morbidity and mortality. Socio-economic, environmental and demographic factors present challenges in malaria control and elimination. As part of the Malaria Elimination Demonstration Project in the tribal district of Mandla in Madhya Pradesh, this study was undertaken to assess the role of different social-economic factors contributing to malaria incidence.
Methods
The study was conducted in the 1233 villages of district Mandla, where 87% population resides in rural areas. The data was collected using the android based mobile application—SOCH for a period of 2 years (September 2017 to August 2019). A wealth index was computed along with analysis of the socio-economic characteristics of houses with malaria cases. Variables with significant variation in malaria cases were used in logistic regression.
Results
More than 70% of houses in Mandla are Kuccha (made of thatched roof or mud), 20% do not have any toilet facilities, and only 11% had an annual income of more than 50,000 INR, which converts to about $700 per year. Households with younger heads, male heads, more number of family members were more likely to have malaria cases. Kuccha construction, improper water supply, low household income houses were also more likely to have a malaria case and the odds doubled in houses with no toilet facilities.
Conclusion
Based on the results of the study, it has been found that there is an association between the odds of having malaria cases and different household variables such as age, gender, number of members, number of rooms, caste, type of house, toilet facilities, water supply, cattle sheds, agricultural land, income, and vector control interventions. Therefore, a better understanding of the association of various risk factors that influence the incidence of malaria is required to design and/or deploy effective policies and strategies for malaria elimination. The results of this study suggest that appropriate economic and environmental interventions even in low-income and poverty-stricken tribal areas could have huge impact on the success of the national malaria elimination goals.
... During final model selection, we considered the potential confounding effects of household elevation; treatment by indoor residual spraying; roof material; number of rooms; distances to the nearest forest, swamp, and health clinic; individual bed net use; and travel, identified a priori. 21 To determine the final adjusted models, we used the purposeful selection of covariates method; used fractional polynomials to evaluate the linearity in the logit of each continuous variable; tested for statistical interaction of both antibody response with age and bed net use with age; calculated diagnostic statistics of leverage, lack of fit (change in Pearson's chi-square), and influence (Cook's distance) for the matched data; and evaluated the sensitivity of the model fits when excluding data for the matched groups that were potentially poorly fit or influential. 22,23 To evaluate whether antibodies in combination predicted clinical malaria more accurately than antibodies alone, we used the predicted probability generated from the adjusted conditional logistic regression models for single antibodies as well as antibodies in combination and compared their respective areas under the receiver operating characteristic curve (AUROC). ...
Prevalence and levels of antibodies to multiple Plasmodium falciparum antigens show promise as tools for estimating malaria exposure. In a highland area of Kenya with unstable transmission, we assessed the presence and levels of antibodies to 12 pre-erythrocytic and blood-stage P. falciparum antigens by multiplex cytometric bead assay or ELISA in 604 individuals in August 2007, with follow-up testing in this cohort in April 2008, April 2009, and May 2010. Four hundred individuals were tested at all four time points. During this period, the only substantial malaria incidence occurred from April to August 2009. Antibody prevalence in adults was high at all time points (> 70%) for apical membrane antigen 1, erythrocyte-binding antigen 175, erythrocyte-binding protein-2, glutamate rich protein (GLURP)-R2, merozoite surface protein (MSP) 1 (19), MSP-1 (42), and liver-stage antigen-1; moderate (30-70%) for GLURP-R0, MSP-3, and thrombospondin-related adhesive protein; and low (< 30%) for SE and circumsporozoite protein (CSP). Changes in community-wide malaria exposure were best reflected in decreasing antibody levels overtime for highly immunogenic antigens, and in antibody seroprevalence overtime for the less-immunogenic antigens. Over the 3 years, antibody levels to all antigens except CSP and schizont extract (SE) decreased in an age-dependent manner. Prevalence and levels of antibodies to all antigens except CSP and SE increased with age. Increases in antibody prevalence and levels to CSP and SE coincided with increases in community-wide malaria incidence. Antibody levels to multiple P. falciparum antigens decrease in the absence of consistent transmission. Multiplex assays that assess both the presence and level of antibodies to multiple pre-erythrocytic and blood-stage P. falciparum antigens may provide the most useful estimates of past and recent malaria transmission in areas of unstable transmission and could be useful tools in malaria control and elimination campaigns.
... With prospective data collected on the study population before, during, and after the implementation of the MOH interventions, we were well positioned to evaluate and provide feedback on the effectiveness of these efforts specific to this epidemic-prone highland Kenya setting. 15,16 Both sites are in Kenya's "epidemic-prone areas of the western highlands" epidemiologic zone, experience unstable highly seasonal malaria transmission patterns, and are at risk for malaria epidemics. Two MOH dispensaries, Kip Health Center and Kap Health Center, are the only healthcare facilities in the study area; community health workers do not operate in this area. ...
In epidemic-prone areas of the western highlands, the Kenya Ministry of Health conducted campaigns of indoor residual spraying (IRS) of households, followed by mass distribution of insecticide-treated bed nets (ITNs), as part of the National Malaria Strategy. We previously reported that in the highland areas of Kipsamoite and Kapsisiywa, widespread IRS coverage in 2007, after lower but substantial coverage in 2005 and 2006, contributed to possible local interruption of malaria transmission between 2007 and 2008. Indoor residual spraying campaigns in the area ended in 2010, succeeded by a mass ITN distribution campaign in 2011 and 2012 targeting universal coverage. Insecticide-treated bed net use in the area increased from 17.1% pre-campaign in 2011 to 51.7% post-campaign in 2012, but decreased to 35.8% in 2013. The ITN campaign did not reduce malaria incidence in the population as a whole (odds ratio [OR] after ITN distribution versus before, 1.29, 95% CI: 1.00-1.66, P = 0.049). However, in 2011-2013, individuals who stated that they slept under ITNs as compared with those who did not had a decrease in malaria incidence that approached statistical significance (OR 0.74, 95% CI: 0.52-1.04, P = 0.08). Mass ITN distribution after previous annual IRS campaigns was insufficient to further reduce malaria transmission in this area of low and highly seasonal transmission possibly because of low ITN use despite the mass campaign.
... During final model selection, we considered the potential confounding effects of household elevation; treatment by indoor residual spraying; roof material; number of rooms; distances to the nearest forest, swamp, and health clinic; individual bed net use; and travel, identified a priori. 21 To determine the final adjusted models, we used the purposeful selection of covariates method; used fractional polynomials to evaluate the linearity in the logit of each continuous variable; tested for statistical interaction of both antibody response with age and bed net use with age; calculated diagnostic statistics of leverage, lack of fit (change in Pearson's chi-square), and influence (Cook's distance) for the matched data; and evaluated the sensitivity of the model fits when excluding data for the matched groups that were potentially poorly fit or influential. 22,23 To evaluate whether antibodies in combination predicted clinical malaria more accurately than antibodies alone, we used the predicted probability generated from the adjusted conditional logistic regression models for single antibodies as well as antibodies in combination and compared their respective areas under the receiver operating characteristic curve (AUROC). ...
Immune correlates of protection against clinical malaria are difficult to ascertain in low-transmission areas because of the limited number of malaria cases. We collected blood samples from 5,753 individuals in a Kenyan highland area, ascertained malaria incidence in this population over the next 6 years, and then compared antibody responses to 11 Plasmodium falciparum vaccine candidate antigens in individuals who did versus did not develop clinical malaria in a nested case-control study (154 cases and 462 controls). Individuals were matched by age and village. Antigens tested included circumsporozoite protein (CSP), liver-stage antigen (LSA)-1, apical membrane antigen-1 FVO and 3D7 strains, erythrocyte-binding antigen-175, erythrocyte-binding protein-2, merozoite surface protein (MSP)-1 FVO and 3D7 strains, MSP-3, and glutamate-rich protein (GLURP) N-terminal non-repetitive (R0) and C-terminal repetitive (R2) regions. After adjustment for potential confounding factors, the presence of antibodies to LSA-1, GLURP-R2, or GLURP-R0 was associated with decreased odds of developing clinical malaria (odds ratio [OR], [95% CI] 0.56 [0.36-0.89], 0.56 [0.36-0.87], and 0.77 [0.43-1.02], respectively). Levels of antibodies to LSA-1, GLURP-R2, and CSP were associated with decreased odds of developing clinical malaria (OR [95% CI]; 0.61 [0.41-0.89], 0.60 [0.43-0.84], and 0.49 [0.24-0.99], for every 10-fold increase in antibody levels, respectively). The presence of antibodies to CSP, GLURP-R0, GLURP-R2, and LSA-1 combined best-predicted protection from clinical malaria. Antibodies to CSP, GLURP-R0, GLURP-R2, and LSA-1 are associated with protection against clinical malaria in a low-transmission setting. Vaccines containing these antigens should be evaluated in low malaria transmission areas.
... A study in Krogwe, Tanzania, showed that children living in high-quality housing had only a third of the malaria infections compared to those living in poor quality housing [49]. In addition, location is important with households that are very close to the border of forests and swamps being at high risk for malaria [4,50]. To sum up, unimproved conditions of housing structure were associated with higher malaria prevalence. ...
Background
Malaria is an increasing concern in Indonesia. Socio-demographic factors were found to strongly influence malaria prevalence. This research aimed to explore the associations between socio-demographic factors and malaria prevalence in Indonesia.
Methods
The study used a cross-sectional design and analysed relationships among the explanatory variables of malaria prevalence in five endemic provinces using multivariable logistic regression.
Results
The analysis of baseline socio-demographic data revealed the following independent risk variables related to malaria prevalence: gender, age, occupation, knowledge of the availability of healthcare services, measures taken to protect from mosquito bites, and housing condition of study participants. Multivariable analysis showed that participants who were unaware of the availability of health facilities were 4.2 times more likely to have malaria than those who were aware of the health facilities (adjusted odds ratio = 4.18; 95% CI 1.52–11.45; P = 0.005).
Conclusions
Factors that can be managed and would favour malaria elimination include a range of prevention behaviours at the individual level and using the networks at the community level of primary healthcare centres. This study suggests that improving the availability of a variety of health facilities in endemic areas, information about their services, and access to these is essential.
Electronic supplementary material
The online version of this article (10.1186/s12936-019-2760-8) contains supplementary material, which is available to authorized users.
... Age, wealth and educational status, religion, region, place of residence (rural), and sleeping under ITN were found to significantly influence reproductive-age women's knowledge levels regarding causes, signs/symptoms, prevention, and care-seeking practices for malaria. The study finding reflects existing evidence in Ghana [27,28], other African countries [29,30], and developing countries [31] of the role of individual, social, environmental, and health system determinants of malaria among varied population groups. Nonuse of ITN was found to be statistically significant and associated with poor knowledge related to care seeking among reproductive-age women in Ghana. ...
Introduction:
Malaria is a major cause of morbidity and mortality worldwide, requiring individual and environmental level controls to prevent its adverse morbidity effects. This study examined reproductive-aged women's knowledge and care-seeking practices for malaria prevention and control in Ghana.
Methods:
The 2016 Ghana Malaria Indicator Survey data for reproductive-age women was analysed (n=5,150). Multilevel mixed-effects logistic regression model was used to determine factors associated with reproductive-aged women's knowledge and care-seeking practices for malaria.
Results:
62.3%, 81.3%, and 64.6% knowledge levels on causes, signs/symptoms, and prevention of malaria were found, respectively, among respondents. Age, wealth and educational status, religion, region, and place of residence (rural) were found to significantly influence respondents' knowledge of causes, signs/symptoms, and care-seeking practices for malaria. A 15% differential among Insecticide Treated Nets (ITNs) awareness and use was found. Increasing age (≥35 years) was associated with increasing knowledge of malaria. Regional variations were observed to significantly influence knowledge of malaria treatment.
Conclusion:
Though ownership of ITNs and knowledge of malaria prevention were high, it did not necessarily translate into use of ITNs. Thus, there is a need to intensify education on the importance and the role of ITNs use in the prevention of malaria.
... In Indonesia, the optimum temperature for malaria mosquitoes ranges between 25 and 27 °C [3]. For the vectorhost relationship, factors such as the distance of people's houses from a river, lakes, pond, distance to the regional urban centre [16][17][18] distance to forest [19,20] were shown to be significant predictors. ...
Background:
Malaria, a parasitic infection, is a life-threatening disease in South Sumatra Province, Indonesia. This study aimed to investigate the spatial association between malaria occurrence and environmental risk factors.
Methods:
The number of confirmed malaria cases was analysed for the year 2013 from the routine reporting of the Provincial Health Office of South Sumatra. The cases were spread over 436 out of 1613 villages. Six potential ecological predictors of malaria cases were analysed in the different regions using ordinary least square (OLS) and geographically weighted regression (GWR). The global pattern and spatial variability of associations between malaria cases and the selected potential ecological predictors was explored.
Results:
The importance of different environmental and geographic parameters for malaria was shown at global and village-level in South Sumatra, Indonesia. The independent variables altitude, distance from forest, and rainfall in global OLS were significantly associated with malaria cases. However, as shown by GWR model and in line with recent reviews, the relationship between malaria and environmental factors in South Sumatra strongly varied spatially in different regions.
Conclusions:
A more in-depth understanding of local ecological factors influencing malaria disease as shown in present study may not only be useful for developing sustainable regional malaria control programmes, but can also benefit malaria elimination efforts at village level.
... Furthermore, we observed that high parasite density significantly correlates with reduction in PCV as in other localities [21,29,34]. The association between malaria risk and environmental, socio-demographic, as well as behavioural variables has been variously explored [35][36][37][38]. We observed on the contrary that educational status of the subjects was not positively associated with malaria occurrence as a significantly higher prevalence was observed among those who completed secondary school (27.2%), compared to those who completed primary school (14.7%) and illiterates (22%), however, it contradicts other findings (39,40). ...
Malaria-related morbidity is a common occurrence in sub-Saharan Africa culminating in low productivity, and waste of valuable manpower. A cross-sectional study of a suburban community in Ilorin, north-central, Nigeria, was conducted. Malaria parasite detection and quantification was established using Giemsa-stained thick and thin blood films. Packed cell volume (PCV) was determined with hematocrit centrifuge and micro-hematocrit reader. Bio-data, socio-environmental and socio-demographic factors were obtained with pretested questionnaire. One thousand, one hundred and four (44.8% males and 55.2% females) inhabitants enrolled for the study with 63.86% harbouring varying degrees of Plasmodium falciparum parasitaemia. Specific point prevalence with respect to age groups were only significant (p<0.05) with age 6-10 and 26-30 respectively. 42.1% of the population were anaemic following established guidelines. More subjects concealed light infections with slightly higher mean anaemia in comparison to other groups. Education level, farming, proximity to stagnant water and sleeping outdoor was highly correlated with degree of infections (p<0.001). Five epidemiological factors predicted future malaria infections viz; outdoor sleepers (OR: 0.003, 95% CI: 0.001-0.006, p<0.001), domiciling within 50 metres of bushes (OR: 10.807, 95% CI: 8.067-14.479, p<0.001), use of insecticides (OR: 0.003, 95% CI: 0.001-0.004, p<0.001), proximity to stagnant water (OR: 0.516, 95% CI: 0.400-0.666, p<0.001) and drug efficacy (OR: 0.457, 95% CI: 0.354-0.590, p<0.001). Malaria still remains a public health debacle in Nigeria. Transmission largely depends on a complex interaction of the vector, physical, socioeconomic , demographic and environmental factors, human biology and behaviour with malnutrition promoting anaemic outcomes.
... Relationship between deforestation caused by a small-scale farming and Anopheles mosquito breeding was evidently proven in Amazon region. [60,64,65,[134][135][136][137][138][139][140][141][142][143][144] In a structural equation model across 67 (developing) nations, positive association was observed between deforestation rates and malaria prevalence. In Sub-Saharan countries, living in the land without trees led to the increased risk of malaria infection. ...
Malaria, one of the deadliest diseases in human history, still infects many people worldwide. Among the species of the genus Plasmodium , P. vivax is commonly found in temperate-zone countries including South Korea. In this article, we first review the history of malarial infection in Korea by means of studies on Joseon documents and the related scientific data on the evolutionary history of P. vivax in Asia. According to the historical records, malarial infection was not unusual in pre-20th-century Korean society. We also found that certain behaviors of the Joseon people might have affected the host-vector-pathogen relationship, which could explain why malarial infection prevalence was so high in Korea at that time. In our review of genetic studies on P. vivax , we identified substantial geographic differentiation among continents and even between neighboring countries. Based on these, we were able to formulate a strategy for future analysis of ancient Plasmodium strains in Korea.
... The sample size was calculated using Open Epi statistical software for unmatched case control design with the assumption of the proportion of exposure among control (P=0.43), 95% confidence interval, 80% power, odds ratio of 2.31 and case to control ratio of 1:4 [16]. The calculated sample size yields 315 subjects (i.e., 63 cases and 252 controls). ...
Background: To date malaria prevention mainly focuses on reduction of human and mosquito contact through insecticide treated bed net. In spite of 100% bed net coverage and marked reduction in malaria mortality in southern region of Ethiopia, malaria is still the leading cause of under-five morbidity. The aim of this study was to identify predictors of malaria among under-five children living in households having insecticide treated bed net. Methods: A community based case control study was conducted in Shashego district, Hadiya zone, Southern Ethiopia. Cases were under five children diagnosed with malaria, and controls were healthy under five children. A total of 310 under-five children paired with their mothers/care taker were selected from the community. Malaria status was determined using rapid diagnostic test. Structured questionnaire and anthropometric measurements were employed to collect data. Bivariate and multivariable logistic regression analysis was performed using SPSS version 20 software. P-value<0.05 and 95% CI was used to declare significant association. Results: Nearly seven among ten 44 (69.8%) cases had Plasmodium vivax malaria. Three in five (60%) cases and controls used insecticide treated nets regularly. Having rectangular bed net (AOR=11.89, 95% CI: 5.57, 25.37), low wealth index quintile (AOR=3.21, 95% CI: 1.31, 7.86), household surrounded with maize/enset plant (AOR 5.89, 95% CI: 2.16, 13.98), moderate (AOR=13.23, 95% CI: 2.41, 72.54) and severe stunting (AOR=8.29, 95% CI: 1.80, 38.19) were independent predictors of malaria. Conclusion: Prior to bed net distribution, the local community bed net shape preference should be considered for effective utilization and to reduce malaria cases. The finding also indicates poverty alleviation and reduction of chronic malnutrition plays significant role to avert malaria morbidity. Presence of enset plant around households and malaria risk needs further investigation.
... The sample size was calculated using Open Epi statistical software for unmatched case control design with the assumption of the proportion of exposure among control (P=0.43), 95% confidence interval, 80% power, odds ratio of 2.31 and case to control ratio of 1:4 [16]. The calculated sample size yields 315 subjects (i.e., 63 cases and 252 controls). ...
... Based on the result found from our study, education level is found to be significantly associated with malaria. A study done in Kenya also found that greater malaria risk is associated with lower level of education of individuals [14]. This study also showed that marital status is significantly associated with malaria. ...
Malaria and anemia are public health problems that have an impact on social and economic development. Malaria causes 70,000 deaths each year and accounts for 17% of outpatient visits to health institutions. It is one of the causes of anemia. Therefore, knowing the relation between malaria and anemia could have a great contribution to the development of prevention strategies. This study is intended to jointly model the prevalence of malaria and anemia by employing a bivariate probit model and show their relationship. The data was obtained from 384 patients visiting Alaba health center. The results of the bivariate probit model shows that sex, age, education level and marital status are significantly associated with malaria and sex and education level are significantly associated with anemia. The results of the seemingly unrelated bivariate probit model shows that sex, education level, age and marital status are significantly determining the prevalence of malaria, and malaria, sex and education level are significantly determining the prevalence of anemia.
... It is clear that household socio-economic status plays an important role in malaria prevention because people with higher income have more resources to access personal protective measures against malaria. However, in the present study it could not be determined whether households in the lower wealth category were at increased risk of malaria, consistent with other studies that reported lack of association between household wealth and malaria risk [14,39]. In contrast, a casecontrol study undertaken in South Africa showed that households in the higher wealth categories had a lower risk of malaria than households in the poorer categories [37]. ...
Background
A recent considerable decline in malaria morbidity and mortality in Ethiopia is likely to be followed by changes in the practice of effective preventive measures and malaria risk factors. This study aimed to identify determinants of long-lasting insecticidal nets (LLINs) ownership and risk of malaria infection.
Methods
A matched case–control study of 191 case and 377 control households was conducted between October 2014 and November 2015 in Adami Tullu district in south-central Ethiopia. Cases were microscopy or rapid diagnostic test confirmed malaria patients identified at three health centers and nine health posts, and matched on age with two neighbourhood controls. Information was collected on socio-demographic factors, house structure, knowledge on malaria and ownership of LLINs. The logistic regression model was used to determine predictors of LLINs ownership and malaria infection.
Results
All cases were infections due to either Plasmodium falciparum (71.2%) or Plasmodium vivax (28.8%). About 31% of the study households had at least one LLINs. Significant determinants of LLINs ownership were household’s head malaria knowledge [adjusted odds ratio (AOR) = 2.47, 95% confidence interval (CI) 1.44–4.22], educational status [read and write (AOR = 6.88, 95% CI 2.30–20.55), primary education or higher (AOR = 5.40, 95% CI 1.57–18.55)], farmer respondent (AOR = 0.35, 95% CI 0.17–0.76), having ≥ 3 sleeping areas (AOR = 6.71, 95% CI 2.40–18.77) and corrugated roof type (AOR = 2.49, 95% CI 1.36–4.58). This study was unable to identify important risk factors of malaria infection with regard to sex, household wealth index, house structure, ownership of LLINs, keeping livestock inside house, staying overnight outdoor or having malaria during the last 6 months.
Conclusions
Household socio-economic status, educational status and knowledge on malaria were important predictors of LLINs ownership. Households with farmer respondents were less likely to own LLINs. Addressing these factors could improve household’s ownership of LLINs. The importance of factors associated with malaria infection was less evident in the current low transmission setting, and necessitates further epidemiological study.
... Malaria transmission is strongly associated with environmental parameters, which control mosquito breeding and parasite growth [33] [34]. Consequently parameters such as wetness index, forest cover, rainfall, aspect, elevation, slope, distance to stream (drainage buffer), breeding sites (water buffer) were considered in order of importance based upon findings of various research outputs and accordingly weights and respective ranks were provided for different thematic map and its significance towards malaria hotspot identification (Table 1 and Figure 4). ...
Introduction: Despite serious interventions worldwide, malaria remains a
significant cause of global morbidity and mortality. Malaria endemic zones
are predominant in the poorest tropical regions of the world, especially in
continental Africa and South-Asia. Major Indian population reside in malaria
endemic zones which are tribal dominated and inaccessible. Lack of suitable
data, reporting and medical facilities in malaria vulnerable regions handicaps
the decision makers in taking adequate steps. Natural resources were mapped
to establish their possible linkage with malaria incidence and to delineate malaria
hotspots using geo-spatial tools. Methods: Remote sensing data along
with various ancillary data such as socio-economic (population in general,
child population, tribal population, literacy), epidemiology (Malaria API and
Pf cases) and environmental parameters (wetness, forest cover, rainfall, aspect,
elevation, slope, drainage buffer, and breeding sites) were integrated on GIS
platform using a designed weight matrix. Multi criteria evaluation was done to
generate hotspot for effective monitoring of malaria incidences. Results: Various
thematic layers were utilized for integrated mapping, and the final map
depicted 59.1% of the study area is vulnerable to high to very high risk of malaria
occurrence. Manoharpur Administrative Block consisted of 89% of its
area under high to very high probability of malaria incidence and it needs to
be prioritized first for preventing epidemic outbreak. Various village pockets
were revealed for prioritizing it for focused intervention of malaria control
measures. Conclusions: Geospatial technology can be potentially used to map
in the field of vector-borne diseases including malaria. The maps produced
enable easy update of information both spatially and temporally provide effortless
accessibility of geo-referenced data to the policy makers to produce
cost-effective measures for malaria control in the endemic regions.
... Analysing routine case data using case-control methods provides an epidemiological tool in low malaria transmission settings where cross-sectional surveys are inappropriate. Casecontrol studies have been used to identify risk factors for malaria in a number of settings, including Peru [12], Columbia [13], Gambia [14] and the Kenyan Highlands [15]. More focused case-control studies have been conducted to examine associations between malaria risk and travel [16][17][18], risk factors for severe malaria [19,20] as well as the relationship between malaria and bacteraemia [21]. ...
Background:
A key component of malaria elimination campaigns is the identification and targeting of high risk populations. To characterize high risk populations in north central Namibia, a prospective health facility-based case-control study was conducted from December 2012-July 2014. Cases (n = 107) were all patients presenting to any of the 46 health clinics located in the study districts with a confirmed Plasmodium infection by multi-species rapid diagnostic test (RDT). Population controls (n = 679) for each district were RDT negative individuals residing within a household that was randomly selected from a census listing using a two-stage sampling procedure. Demographic, travel, socio-economic, behavioural, climate and vegetation data were also collected. Spatial patterns of malaria risk were analysed. Multivariate logistic regression was used to identify risk factors for malaria.
Results:
Malaria risk was observed to cluster along the border with Angola, and travel patterns among cases were comparatively restricted to northern Namibia and Angola. Travel to Angola was associated with excessive risk of malaria in males (OR 43.58 95% CI 2.12-896), but there was no corresponding risk associated with travel by females. This is the first study to reveal that gender can modify the effect of travel on risk of malaria. Amongst non-travellers, male gender was also associated with a higher risk of malaria compared with females (OR 1.95 95% CI 1.25-3.04). Other strong risk factors were sleeping away from the household the previous night, lower socioeconomic status, living in an area with moderate vegetation around their house, experiencing moderate rainfall in the month prior to diagnosis and living <15 km from the Angolan border.
Conclusions:
These findings highlight the critical need to target malaria interventions to young male travellers, who have a disproportionate risk of malaria in northern Namibia, to coordinate cross-border regional malaria prevention initiatives and to scale up coverage of prevention measures such as indoor residual spraying and long-lasting insecticide nets in high risk areas if malaria elimination is to be realized.
... The global burden of malaria has declined considerably in the last two decades, with a 47% reduction in malaria mortality rates worldwide since 2000 and 54% reduction in the WHO Africa Region (1). While globally the decline has been attributed to economic development and public health interventions (2), local-scale changes in malaria risk have been attributed to changes in environmental factors that are important for enabling and sustaining malaria transmission (3)(4)(5). The local impacts of environmental change are particularly evident in the East African highlands, one of the most densely populated regions of Africa (6). ...
Introduction: Malaria prevalence has declined in the Kilimanjaro region of Tanzania over the past 10 years, particularly at lower altitudes. While this decline has been related to the scale-up of long-lasting insecticidal nets to achieve universal coverage targets, it has also been attributed to changes in environmental factors that are important for enabling and sustaining malaria transmission.
Objectives: Herein, we apply spatial analytical approaches to investigate the impact of environmental and demographic changes, including changes in temperature, precipitation, land cover, and population density, on the range of the major malaria vector species Anopheles arabiensis in two districts of Tanzania, situated on the southern slope of Mount Kilimanjaro. These models are used to identify environmental changes that have occurred over a 10-year period and highlight the implications for malaria transmission in this highland region.
Methods: Entomological data were collected from the Hai and Lower Moshi districts of Tanzania in 2001–2004 and 2014–2015. Vector occurrence data were applied alongside satellite remote sensing indices of climate and land cover, and gridded population data, to develop species distribution models for An. arabiensis for the 2004 and 2014 periods using maximum entropy. Models were compared to assess the relative contribution of different environmental and demographic factors to observed trends in vector species distribution in lowland and highland areas.
Results: Changes in land cover were observed in addition to increased population densities, increased warm season temperature, and decreased wetness at low altitudes. The predicted area and extent of suitable habitat for An. arabiensis declined across the study area over the 10-year period, with notable contraction at lower altitudes, while species range in higher altitude zones expanded. Importantly, deforestation and warmer temperatures at higher altitudes may have created stable areas of suitable vector habitat in the highlands capable of sustaining malaria transmission.
Conclusion: We show that environmental changes have had an important influence on the distribution of malaria vector species in a highland area of northern Tanzania. Highland areas may be at continued risk for sporadic malaria outbreaks despite the overall range contraction of principal vector species at lower altitudes, where malaria transmission remains at low intensity.
... The adverse impact of socioeconomic conditions on health is particularly seen in vector-borne disease like malaria, dengue, Japanese encephalitis and congenital diseases like tuberculosis, cancer and coronary heart diseases [1][2][3][4][5][6][7] . By understanding the socioeconomic conditions of the community, the disease spectrum can be analysed very accurately. ...
Background & objectives: Lymphatic filariasis (LF) is a major public health problem in India. The objective of the study was to assess the impact of socioeconomic conditions on LF in Chittoor district of Andhra Pradesh, India.
Methods: A survey was carried out from 2004 to 2007 during which, an epidemiological and socioeconomic data were collected and analysed. The microfilaria (mf) positive samples were taken as cases and matched with control group by sex and age (1:1) for case-control study. Bivariate and multivariate logistic regression was used to identify the potential risk factors for filariasis. Using principal component analysis (PCA), a socioeconomic index was developed and the data/scores were classified into low, medium and high categories.
Results: In total 5,133 blood smears were collected, of which 77 samples were found positive for microfilaria (1.52%). Multivariate analysis showed that the risk of filariasis was higher in groups of people with income < ₹1000 per month [OR = 2.752 (95%CI, 0.435-17.429)]; ₹ 1000-3000 per month [3.079 (0.923-0.275)]; people living in tiled house structure [1.641 (0.534-5.048)], with kutcha (uncemented) drainage system [19.427 (2.985- 126.410)], respondents who did not implemented mosquito avoidance measures [1.737 (0.563-5.358)]; and in people who were not aware about prevention and control of filariasis [1.042 (0.368-2.956)]. PCA showed that respondents with low (41.6%) and medium (33.8%) socioeconomic status are more prone to filariasis (p=0.036).
Interpretation & conclusion: The cross sectional study showed that the population with low and medium socioeconomic status are at higher risk of filariasis. The identified socioeconomic risk factors can be used as a guideline for improving the conditions for effective management of filariasis.
... These arguments have to be specified, similarly to the previous spodt classification of the observed data set. . This local heterogeneity is driven by a variety of factors including distance to breeding sites, housing constructions and socio-behavioral characteristics (Koram, Bennett, Adiamah, and Greenwood 1995;Coleman, Mabuza, Kok, Coetzee, and Durrheim 2009;Ernst et al. 2009). The study was conducted in Bandiagara, Mali, following a cohort of 300 children, at 168 locations. ...
Spatial cluster detection is a classical question in epidemiology : are cases located near other cases ? In order to classify a study area into zones of different risks and determine their boundaries, we have developed a spatial partitioning method based on oblique decision trees, which is called spatial oblique decision tree (SpODT). This non-parametric method is based on the classification and regression tree (CART) approach introduced by Leo Breiman. Applied to epidemiological spatial data, the algorithm recursively searches among the coordinates for a threshold or a boundary between zones, so that the risks estimated in these zones are as different as possible. While the CART algorithm leads to rectangular zones, providing perpendicular splits of longitudes and latitudes, the SpODT algorithm provides oblique splitting of the study area, which is more appropriate and accurate for spatial epidemiology. Oblique decision trees can be considered as non-parametric regression models. Beyond the basic function, we have developed a set of functions that enable extended analyses of spatial data, providing: inference, graphical representations, spatio-temporal analysis, adjustments on covariates, spatial weighted partition, and the gathering of similar adjacent final classes. In this paper, we propose a new R package, SPODT, which provides an extensible set of functions for partitioning spatial and spatio-temporal data. The implementation and extensions of the algorithm are described. Function usage examples are proposed, looking for clustering malaria episodes in Bandiagara, Mali, and samples showing three different cluster shapes.
... Comprehensive reviews of climate change and malaria transmission have been covered in other papers (Martens and Thomas, 2004;Protopopoff et al., 2009;Sutherst, 2004). Other studies have developed suitable environmental, socio-demographic and behavioural indicators of malaria risk at regional, community and household levels (Bates et al., 2004a(Bates et al., , 2004bErnst et al., 2009;Protopopoff et al., 2009;Sutherst, 2004;Wandiga et al., 2009). The experts selected were three key academics well versed in climate change, malaria transmission and climate change-malaria research in East Africa. ...
Malaria is one of the key research concerns in climate change-health relationships. Numerous risk assessments and modelling studies providing evidence that the transmission range of malaria will expand with rising temperatures resulting in adverse impacts on vulnerable communities. This risk is significant in East Africa whereby current research shows an expansion of malaria into the highland areas due to changes in temperature and rainfall. While there exist multiple lines of evidence for the influence of climate change on malaria and the risk posed to vulnerable communities, there is insufficient understanding of the complexity of factors influencing the spread of the disease at the community level. This paper considers assessment of risk of malaria infection due to climate change, from systems perspective. Drawing upon published literature, we apply systems approach to propose a detailed conceptual model that illustrates causal relationships between the multiple drivers of malaria transmission in line with the current Intergovernmental Panel on Climate Change recommendations for risk and vulnerability assessments. We suggest that this framework can be applied at a community level using both quantitative and qualitative methods with stakeholder engagement and in conjunction with Bayesian Belief Network to models to: explore how policy and management interventions can reduce the risk of malaria infection and; provide targeted adaptation strategies that incorporates both the scientific and the community perspectives.
... Overall, and for the 5 years, malaria incidence has increased between 7 and 26 % in the bairros situated in the central eastern part of the municipality (suburbs) and decreased between 4 and 15 % in the other areas (rural and urban). [20]. This increase in the Chimoio results is probably due to the 3.5 % annual increase in population, reduced efforts to combat malaria and persistent poverty. ...
Background
In Africa, urban malaria is a major concern, since the towns and especially their suburbs are growing quickly. In Mozambique, malaria represents 45 % of all cases of outpatient visits and 56 % of inpatient visits at paediatric clinics. Malaria is a major public health burden in Chimoio Mozambique and few studies on malaria exist.
Methods
The study was carried out to establish the spatiality and temporality of malaria and describe socio-demographic characteristics of malaria patients in Chimoio. Weekly malaria data for 9 years (2006–2014) were collected from the district Epidemiological Bulletin and incidence by season, age, gender, and residence was calculated. SPSS version 20 was used for statistical analysis and ArcGis 10.1 was used to produce maps.
Results
The annual overall average of malaria incidence was 20.1 % and the attributable fraction (AF) of malaria was 16 %. There were differences in weekly and yearly malaria occurrences throughout the period. There was no difference in malaria cases between male and female patients. Children under 5 years of age are three times more prone to malaria than adults (p < 0.05). Three temporal clusters of malaria were identified: cluster 1, weeks 25–47 with average weekly cases of 618 (sd = 251.9), cluster 2, weeks 18–24 and 48–51 with average weekly cases of 1066 (sd = 317.4). cluster 3, weeks 1–17 and 52 with average weekly cases of 1587 (sd = 722.4). Similarly, three different clusters were identified according to residential areas: cluster 1 (10 %) mostly urban, cluster 2 (22 %) mostly suburbs, cluster 3 (28 %) mostly rural areas.
Conclusion
Malaria is increasing in the suburbs, and rural areas present more cases of malaria compared to urban areas. This article is an initial step to understand the dynamics of malaria in Chimoio. Results suggest that malaria varies in time and space, and that precision public health strategy should be used to control malaria occurrence. Studies on weather factors affecting malaria cases, bed net usage, and others should be undertaken.
... The presence of other variables might have accounted for this finding. Similar results were obtained in Kenya (Ernst et al., 2009). ...
Malaria and anaemia which jointly account for high proportion of morbidity and mortality among young children in developing countries have been individually studied using binary regression model. We adopt geoadditive latent variable model for binary/ordinal indicators to analyze the influence of variables of different types on the morbidity among young children in Nigeria. Latent variable models allow for the analysis of multidimensional response variables that reveal the indicator's underlying relationship that are caused by the latent variables. We extend the structural model to a semi-parametric geoadditive model in order to quantify the joint spatial structure of morbidity from malaria and anaemia. Findings revealed substantial geographical variations and the generated maps can guide policy makers and donors on how to prudently utilize the scarce resources for designing more cost-effective interventions.
... It is possible that individuals are aware that they should use their bed nets every night and thus report that they have used them, subsequently deflating estimates of disuse in these communities. In addition, there was no information collected on factors associated with malaria risk, which could include housing construction, use of other prevention factors (except IRS), proximity to high-risk areas, such as swamps or forest boundaries [34] which may be associated with an individual's willingness to obtain and use a bed net. In addition, the lack of use of available bed nets analyses was limited by the rarity of the event, and this precluded using multivariable models to adjust for potentially confounding variables other than the limited set of sociodemographic variables used. ...
Background
Challenges persist in ensuring access to and optimal use of long-lasting, insecticidal bed nets (LLINs). Factors associated with ownership and use may differ depending on the history of malaria and prevention control efforts in a specific region. Understanding how the cultural and social-environmental context of bed net use may differ between high- and low-risk regions is important when identifying solutions to improve uptake and appropriate use.
Methods
Community forums and a household, cross-sectional survey were used to collect information on factors related to bed net ownership and use in western Kenya. Sites with disparate levels of transmission were selected, including an endemic lowland area, Miwani, and a highland epidemic-prone area, Kapkangani. Analysis of ownership was stratified by site. A combined site analysis was conducted to examine factors associated with use of all available bed nets. Logistic regression modelling was used to determine factors associated with ownership and use of owned bed nets.
Results
Access to bed nets as the leading barrier to their use was identified in community forums and cross-sectional surveys. While disuse of available bed nets was discussed in the forums, it was a relatively rare occurrence in both sites. Factors associated with ownership varied by site. Education, perceived risk of malaria and knowledge of individuals who had died of malaria were associated with higher bed net ownership in the highlands, while in the lowlands individuals reporting it was easy to get a bed net were more likely to own one. A combined site analysis indicated that not using an available bed net was associated with the attitudes that taking malaria drugs is easier than using a bed net and that use of a bed net will not prevent malaria. In addition, individuals with an unused bed net in the household were more likely to indicate that bed nets are difficult to use, that purchased bed nets are better than freely distributed ones, and that bed nets should only be used during the rainy season.
Conclusion
Variations in factors associated with ownership should be acknowledged when constructing messaging and distribution campaigns. Despite reports of bed nets being used for other purposes, those in the home were rarely unused in these communities. Disuse seemed to be related to beliefs that can be addressed through education programmes. As mass distributions continue to take place, additional research is needed to determine if factors associated with LLIN ownership and use change with increasing availability of LLIN.
Background
Livelihood activities and human movements participate in the epidemiology of vector-borne diseases and influence malaria risk in elimination settings. In Saudi Arabia, where malaria transmission intensity varies geographically, it is vital to understand the components driving transmission within specific areas. In addition, shared social, behavioural, and occupational characteristics within communities may provoke the risk of malaria infection. This study aims to understand the relationship between human mobility, livelihood activities, and the risk of malaria infection in the border region of Jazan to facilitate further strategic malaria interventions. In addition, the study will complement and reinforce the existing efforts to eliminate malaria on the Saudi and Yemen border by providing a deeper understanding of human movement and livelihood activities.
Methods
An unmatched case–control study was conducted. A total of 261 participants were recruited for the study, including 81 cases of confirmed malaria through rapid diagnostic tests (RDTs) and microscopy and 180 controls in the Baish Governorate in Jazan Provinces, Saudi Arabia. Individuals who received malaria tests were interviewed regarding their livelihood activities and recent movement (travel history). A questionnaire was administered, and the data was captured electronically. STATA software version 16 was used to analyse the data. Bivariate and multivariate analyses were conducted to determine if engaging in agricultural activities such as farming and animal husbandry, recent travel history outside of the home village within the last 30 days and participating in spiritual gatherings were related to malaria infection status.
Results
A logistical regression model was used to investigate components associated with malaria infection. After adjusting several confounding factors, individuals who reported travelling away from their home village in the last 30 days OR 11.5 (95% CI 4.43–29.9), and those who attended a seasonal night spiritual gathering OR 3.04 (95% CI 1.10–8.42), involved in animal husbandry OR 2.52 (95% CI 1.10–5.82), and identified as male OR 4.57 (95% CI 1.43–14.7), were more likely to test positive for malaria infection.
Conclusion
Human movement and livelihood activities, especially at nighttime, should be considered malaria risk factors in malaria elimination settings, mainly when the targeted area is limited to a confined borderland area.
Background : Malaria is still one of the leading causes of mortality and morbidity in Mozambique with little progress in malaria control over the past 20 years. Sussundenga is one of most affected areas. Malaria transmission has a strong association with environmental and sociodemographic factors. The knowledge of sociodemographic factors that affects malaria, may be used to improve the strategic planning for its control. Currently such studies have not been performed in Sussundenga. Thus, the objective of this study is to model the relationship between malaria and sociodemographic factors in Sussundenga, Mozambique.
Methods: Houses in the study area were digitalized and enumerated using Google Earth Pro version 7.3. In this study 100 houses were randomly selected to conduct a community survey of Plasmodium falciparum parasite prevalence using rapid diagnostic test (RDT). During the survey, a questionnaire was conducted to assess the sociodemographic factors of the participants. Descriptive statistics were analyzed and backward stepwise logistic regression was performed establishing a relationship between positive cases and the factors. The analysis was carried out using SPSS version 20 package.
Results: The overall P. falciparum prevalence was 31.6%. Half of the malaria positive cases occurred in age group 5 to 14 years. Previous malaria treatment, population density and age group were significant predictors for the model. The model explained 13.5% of the variance in malaria positive cases and sensitivity of the final model was 73.3%.
Conclusion: In this area the highest burden of P. falciparum infection was among those aged 5–14 years old. Malaria infection was related to sociodemographic factors. Targeting malaria control at community level can combat the disease more effectively than waiting for cases at health centers. These finding can be used to guide more effective interventions in this region.
Background : Malaria is still one of the leading causes of mortality and morbidity in Mozambique with little progress in malaria control over the past 20 years. Sussundenga is one of most affected areas. Malaria transmission has a strong association with environmental and sociodemographic factors. The knowledge of sociodemographic factors that affects malaria, may be used to improve the strategic planning for its control. Currently such studies have not been performed in Sussundenga. Thus, the objective of this study is to model the relationship between malaria and sociodemographic factors in Sussundenga, Mozambique.
Methods: Houses in the study area were digitalized and enumerated using Google Earth Pro version 7.3. In this study 100 houses were randomly selected to conduct a community survey of Plasmodium falciparum parasite prevalence using rapid diagnostic test (RDT). During the survey, a questionnaire was conducted to assess the sociodemographic factors of the participants. Descriptive statistics were analyzed and backward stepwise logistic regression was performed establishing a relationship between positive cases and the factors. The analysis was carried out using SPSS version 20 package.
Results: The overall P. falciparum prevalence was 31.6%. Half of the malaria positive cases occurred in age group 5 to 14 years. Previous malaria treatment, population density and age group were significant predictors for the model. The model explained 13.5% of the variance in malaria positive cases and sensitivity of the final model was 73.3%.
Conclusion: In this area the highest burden of P. falciparum infection was among those aged 5–14 years old. Malaria infection was related to sociodemographic factors. Targeting malaria control at community level can combat the disease more effectively than waiting for cases at health centers. These finding can be used to guide more effective interventions in this region.
Malaria remains one of the leading causes of morbidity and mortality in many tropical countries with potential adverse effects on economic growth and development. Recognizing these negative effects, several mosquito control measures including bednets and household insecticide products (such as coil and repellent) have been promoted to reduce malaria. However, there is little evidence on the effects of combined measures on malaria reduction. This study examines the interaction effects of household use of bednets and insecticide products on self-reported malaria prevalence in Southern Ghana using panel data collected from two administrative districts and a doubly robust estimation technique. The study finds that the use of bednets is associated with lower malaria among household members. Household use of insecticide products singly shows no statistically significant negative relationship with malaria. The study finds some evidence that adopting the two measures jointly increases the efficacy of insecticide products and this signifies the importance of combining various measures to prevent malaria. The results also suggest that combining bednets and household insecticide products reduce malaria for all individuals, females and children under five years. The main policy implications are that single interventions on malaria prevention should focus on bednets, and the use of insecticide products should be combined with other measures in order to improve its efficacy to prevent malaria in developing countries.
Background
Even though malaria cases have drastically come down in the last decade, malaria remains a serious public health concern in many parts of India. National Framework for Malaria Elimination in India (2016-30) has been launched with the goal to eliminate malaria by 2030. Understanding the socio-economic and household determinants of malaria at the national level will greatly aid in India’s malaria elimination efforts.
Methods
The data from Longitudinal Ageing Survey of India (LASI) Wave 1 (2017-2019) survey comprising 70671 respondents ≥45 years across all the States and Union Territories were used for analysis.Simple and multiple logistic regressions were used to obtain the unadjusted and adjusted odds ratio respectively of the socio-economic and household variables.
Results
The major socio-economic variables that increase the likelihood of malaria are caste (Schedule Tribes), rural residence and low education levels.The scheduled tribes have 1.8 times higher odds of malaria than the scheduled castes (AOR: 1.8; 95% CI: 1.5-2.1). Respondents withhigh school education (6-12 grade) (AOR: 0.7; 95% CI: 0.6-0.8) and college education (AOR: 0.5; 95% CI: 0.4-0.6) had a very low risk of malaria than those with no school years. Rural residence and occupation (agriculture and allied jobs) also increases the odds of malaria. The major housing determinants are household size (≥6), housing type (kutcha), use of unclean fuel, outside water source, improper sanitation (toilet facilities) and damp wall/ceiling.
Conclusions
In addition to vector and parasite control strategies, improving literacy and housing conditions, especially in tribal dominated regions will greatly aid in India’s malaria elimination efforts.
Malaria is still one of the leading causes of mortality and morbidity in Mozambique with the 5 th highest prevalence in the world, with little progress in malaria control over the past 20 years. Sussundenga village is one of most affected areas, and lies along the Zimbabwe border, making evaluation of malaria transmission and control policies integral for regional efforts. The objective of this study was to map and quantify malaria parasite prevalence and model its relationship with sociodemographic and economic traits in Sussundenga Village. Houses in the study area were digitalized and enumerated using GoogleEarth Pro TM . A sample of 125 houses was drawn to conduct a community survey of P. falciparum parasite prevalence using rapid diagnostic test (RDT). During the survey, a questionnaire was conducted to assess the socio-demographic and economic traits of the participants. Descriptive statistics were analyzed and logistic regression was performed to establish the relationship between positive cases and the traits. Using GIS a map the prevalence of malaria was produced. The analysis was carried out using SPSS version 20 package and ArcGis 10.7.1. 358 participants were enrolled, completed the survey, and were tested for malaria. The overall P. falciparum prevalence was 31.6 % and spatiality identified. Half of the malaria positive cases occurred in age group 5 to 14, 40 % more than expected and age group over 24 accounted for 17.6 % the cases, around 50 % less than expected. The model explained 15 % of the variance in malaria positive cases and sensitivity of the final model was 91.8 %. The increase in malaria treated cases, having paid employment, education level and age category, will decrease the probability of malaria positive cases in Sussundenga Village. Conclusion In this area the highest burden of P. falciparum infection was among those 5-14 years old. Malaria infection was related to socio-demographic and economic traits. Targeting malaria control at community level can contributed better than waiting for cases at health centers. These finding can be used to guide more effective interventions in this region.
Objective
This study aims to understand the characteristics of houses and the behavior of residents in malaria endemic areas carried out on the islands of Jampea, Selayar Islands.
Methods
The method study used the observational method using an observation sheet.
Results
The results showed that there are still many people who less concerned with malaria problems than being supported by home environment that is fully related to water inundation and the dwelling population that dense.
Conclusion
Therefore, it is important to improve the strategy for optimizing the implementation of supervision in the region by the local government.
BACKGROUND:A clear understanding of the effects of housing structure, education, occupation, income, and wealth on malaria can help to better design socioeconomic interventions to control the disease. This literature review summarizes the relationship of housing structure, educational level, occupation, income, and wealth with the epidemiology of malaria in sub-Saharan Africa (SSA). METHODS:A systematic review and meta-analysis was conducted following the preferred reporting items for systematic reviews and meta-analyses guidelines. The protocol for this study is registered in PROSPERO (ID=CRD42017056070), an international database of prospectively registered systematic reviews. On January 16, 2016, available literature was searched in PubMed, Embase, CINAHL, and Cochrane Library. All but case studies, which reported prevalence or incidence of Plasmodium infection stratified by socioeconomic status among individuals living in SSA, were included without any limits. Odds Ratio (OR) and Relative Risk (RR), together with 95% CI and p-values were used as effect measures. Heterogeneity was assessed using chi-square, Moran's I2, and tau2 tests. Fixed (I2
Approximately 3.3 billion, or half of the world's population, are at risk from malaria and this number is projected to rise under climate change scenarios. While climate change does influence the global distribution of malaria, the spatial extent within regions will be determined by local land use factors and by other non-climatic factors. The latter include biological, social, demographic and cultural factors, along with human behaviour, drug resistance and public health interventions. At a local level, these factors can influence malaria transmission independently or by modifying the effects of climate change therefore, quantifying and understanding the impact of climate change needs consideration of the interactions between these other factors, climate change and malaria transmission. Using East Africa region as a case study, this paper suggests a participatory process of identification and ranking of key variables influencing malaria transmission known as structural analysis. In this process, we used systems thinking, literature review and expert consultations to identify a candidate set of influencing variables, describe the relationships between them and further, rank these identified variables in the order of their influence on the system. From our results, we determined that ElNino, average rainfall, malaria vector control, quality of information and agriculture were the five most influential variables of the system. Ranking of variables in order of influence is important in the context of decision-making as it identifies the most effective adaptation pathways for risk reduction.
Background
Thanks to a considerable increase in funding, malaria control interventions (MCI) whose efficacy had been demonstrated by controlled trials have been largely scaled up during the last decade. Nevertheless, it was not systematically investigated whether this efficacy had been preserved once deployed on the field. Therefore, we sought the literature to assess the disparities between efficacy and effectiveness and the effort to measure the protective effectiveness (PE) of MCI.
Methods
The PubMed database was searched for references with keywords related to malaria, to control interventions for prevention and to study designs that allow for the measure of the PE against parasitemia or against clinical outcomes.
Results
Our search retrieved 1423 references, and 162 articles were included in the review. Publications were scarce before the year 2000 but dramatically increased afterwards. Bed nets was the MCI most studied (82.1%). The study design most used was a cross-sectional study (65.4%). Two thirds (67.3%) were conducted at the district level or below, and the majority (56.8%) included only children even if the MCI didn’t target only children. Not all studies demonstrated a significant PE from exposure to MCI: 60.6% of studies evaluating bed nets, 50.0% of those evaluating indoor residual spraying, and 4/8 showed an added PE of using both interventions as compared with one only; this proportion was 62.5% for intermittent preventive treatment of pregnant women, and 20.0% for domestic use of insecticides.
Conclusions
This review identified numerous local findings of low, non-significant PE –or even the absence of a protective effect provided by these MCIs. The identification of such failures in the effectiveness of MCIs advocates for the investigation of the causes of the problem found. Ideal evaluations of the PE of MCIs should incorporate both a large representativeness and an evaluation of the PE stratified by subpopulations.
House structure may influence the risk of malaria by affecting mosquito entry and indoor resting. Identification of construction features associated with protective benefits could inform vector control approaches, even in low-transmission settings. We examined the association between house structure and malaria prevalence in a cross-sectional analysis of 2,788 children and adults residing in 866 houses in a low-transmission area of Southern Province, Zambia, over the period 2008-2012. Houses were categorized according to wall (brick/cement block or mud/grass) and roof (metal or grass) material. Malaria was assessed by point-of-care rapid diagnostic test (RDT) for Plasmodium falciparum. We identified 52 RDT-positive individuals residing in 41 houses, indicating an overall prevalence of parasitemia in the sample of 1.9%, ranging from 1.4% to 8.8% among the different house types. Occupants of higher quality houses had reduced odds of P. falciparum malaria compared with those in the lowest quality houses after controlling for bed net use, indoor insecticide spraying, clustering by house, cohabitation with another RDT-positive individual, ecologic risk defined as nearest distance to a Strahler-classified third-order stream, education, age, and gender (adjusted odds ratio [OR]: 0.26, 95% confidence interval [CI]: 0.09-0.73, P = 0.01 for houses with brick/cement block walls and metal roof; OR: 0.22, 95% CI: 0.09-0.52, P < 0.01 for houses with brick/cement block walls and grass roof). Housing improvements offer a promising approach to vector control in low-transmission settings that circumvents the threat posed by insecticide resistance, and may confer a protective benefit of similar magnitude to current vector control strategies.
Kabupaten Lahat adalah salah satu wilayah endemis malaria di Sumatera Selatan dengan prevalensi 16,4% dan Annual Malaria Incidence 22,08. Tujuan penelitian ini untuk mengetahui faktor risiko lingkungan dengan kejadian malaria. Faktor risiko lingkungan genangan air (breeding place) berhubungan dengan kejadian malaria dengan nilai p= 0,000. Analisis multivariat menemukan determinan utama kejadian malaria adalah breeding place di sekitar rumah responden dengan odds ratio (OR) = 5,034 dan 95% CI = 2,65 _ 9,56. Responden yang tinggal di sekitar breeding place berisiko 5,03 kali lebih besar untuk menderita malaria dibandingkan dengan responden yang di sekitar rumah tidak terdapat breeding place setelah dikontrol variabel jarak rumah ke breeding place, ventilasi rumah, penggunaan kelambu, penggunaan obat anti nyamuk, dan kebiasaan keluar rumah pada malam hari.
Lahat district is one of the malaria endemic area in South Sumatra Province with a prevalence of 16.4% and Annual Malaria Incidence of 22.08. The case control reports were carried out of 240 respondents. This study aimed to understand the relationship among of environmental risk factors with the incidence of malaria. After primary data collection followed by processing and data analysis in a multimedia laboratory. There was association between breeding place and malaria cases (p value= 0.000). The results of multivariate analysis of variables revealed the determinant risk was breeding place, with OR = 5.034 and CI 95%= 2.65 _ 9.56. Respondents who live around the breeding place has 5.034 times chance of affected malaria compared with respondents around the house there are no breeding place after the controlled distance to the breeding place house, use of mosquito nets, use of anti-mosquito, and habits out of the house at night variables.
Abstract
Background
Transmission of Plasmodium falciparum generally decreases with increasing elevation, in part because lower temperature slows the development of both parasites and mosquitoes. However, other aspects of the terrain, such as the shape of the land, may affect habitat suitability for Anopheles breeding and thus risk of malaria transmission. Understanding these local topographic effects may permit prediction of regions at high risk of malaria within the highlands at small spatial scales.
Methods
Hydrologic modelling techniques were adapted to predict the flow of water across the landscape surrounding households in two communities in the western Kenyan highlands. These surface analyses were used to generate indices describing predicted water accumulation in regions surrounding the study area. Households with and without malaria were compared for their proximity to regions of high and low predicted wetness. Predicted wetness and elevation variables were entered into bivariate and multivariate regression models to examine whether significant associations with malaria were observable at small spatial scales.
Results
On average, malaria case households (n = 423) were located 280 m closer to regions with very high wetness indices than non-malaria "control" households (n = 895) (t = 10.35, p < 0.0001). Distance to high wetness indices remained an independent predictor of risk after controlling for household elevation in multivariate regression (OR = 0.93 [95% confidence interval = 0.89–0.96] for a 100 m increase in distance). For every 10 m increase in household elevation, there was a 12% decrease in the odds of the house having a malaria case (OR = 0.88 [0.85–0.90]). However, after controlling for distance to regions of high predicted wetness and the community in which the house was located, this reduction in malaria risk was not statistically significant (OR = 0.98 [0.94–1.03]).
Conclusion
Proximity to terrain with high predicted water accumulation was significantly and consistently associated with increased household-level malaria incidence, even at small spatial scales with little variation in elevation variables. These results suggest that high wetness indices are not merely proxies for valley bottoms, and hydrologic flow models may prove valuable for predicting areas of high malaria risk in highland regions. Application in areas where malaria surveillance is limited could identify households at higher risk and help focus interventions.
Global warming may affect the future pattern of many arthropod-borne diseases, yet the relationship between temperature and development has been poorly described for many key vectors. Here the development of the aquatic stages of Africa's principal malaria vector, Anopheles gambiae s.s. Giles, is described at different temperatures. Development time from egg to adult was measured under laboratory conditions at constant temperatures between 10 and 40 degrees C. Rate of development from one immature stage to the next increased at higher temperatures to a peak around 28 degrees C and then declined. Adult development rate was greatest between 28 and 32 degrees C, although adult emergence was highest between 22 and 26 degrees C. No adults emerged below 18 degrees C or above 34 degrees C. Non-linear models were used to describe the relationship between developmental rate and temperature, which could be used for developing process-based models of malaria transmission. The utility of these findings is demonstrated by showing that a map where the climate is suitable for the development of aquatic stages of A. gambiae s.s. corresponded closely with the best map of malaria risk currently available for Africa.
In the 1980s, highland malaria returned to the tea estates of western Kenya after an absence of nearly a generation. In order to determine the importance of travel for the spread of malaria in this region, we prospectively collected blood films and travel, demographic and geographic information on well persons and outpatients on tea estates near the western rim of the Rift Valley. Risk factors for malaria asexual parasitaemia included: tribal/ethnic group, home province and home district malaria endemicity. Travel away from the Kericho tea estates within the previous two months showed an odds ratio (OR) for parasitaemia of 1.59 for well persons and 2.38 for outpatients. Sexual stages of malaria parasites (gametocytes) had an OR of 3.14 (well persons) and 2.22 (outpatients) for those who had travelled. Increased risk of malaria parasitaemia with travel was concentrated in children aged <5 years. An increase in population gametocytaemia is possibly due to increased chloroquine resistance and suppressed infections contracted outside of the tea estates.
The current study examined temporal and spatial distribution patterns of anopheline malaria vectors in a highland site and determined the number of houses to be sampled to achieve the targeted precision level. Adult mosquito sampling was conducted seasonally in May and August 2002 in a 3 by 3-km2 area, and in November 2002 and February 2003 in an expanded 4 by 4-km2 area in Kakamega District, western Kenya. Anopheles gambiae Giles was the predominant malaria vector species, constituting 84.6% of the specimens, whereas Anopheles funestus Giles constituted 15.4% of the vector populations. An. gambiae abundance increased by six- to eight-fold in the long rainy season over the dry seasons, but An. funestus abundance peaked 3 mo after the long rainy season. For both species, the coefficient of variation was larger than 1, suggesting that the distribution of mosquito adults was aggregated. Mosquito clustering occurred in houses <400 m from a valley bottom. The negative binomial distribution was accepted in one sample period (August 2002) for An. gambiae and in two sampling periods (May and August 2002) for An. funestus. Taylor's power law analyses indicated that An. gambiae distribution was more aggregated in the wet seasons than in the dry seasons, whereas the degree of aggregation of An. funestus was similar in all four seasons. The minimum number of houses required to estimate anopheline female abundance within the commonly acceptable precision level (0.2) should be 17 houses per km2 for An. gambiae and 42 houses per km2 for An. funestus. The potential factors causing aggregated anopheline mosquito distribution are discussed.
A geographically stratified cross-sectional survey was conducted in 2002 to investigate household-level factors associated with use of mosquito control measures and self-reported malaria in Malindi, Kenya. A total of 629 households were surveyed. Logistic regressions were used to analyse the data. Half of all households (51%) reported all occupants using an insecticide-treated bed net and at least one additional mosquito control measure such as insecticides or removal of standing water. Forty-nine per cent reported a history of malaria in the household. Of the thirteen household factors analysed, low (OR=0.23, CI 0.11, 0.48) and medium (OR=0.50, CI 0.29, 0.86) education, mud--wood--coral (OR=0.0.39, CI 0.24, 0.66) and mud block--plaster (OR=0.47, CI 0.25, 0.87) wall types, farming (OR=1.38, CI 1.01, 1.90) and travel to rural areas (OR=0.48, CI 0.26, 0.91) were significantly associated with the use of mosquito control, while controlling for other covariates in the model. History of reported malaria was not associated with the use of mosquito control (OR=1.22, CI 0.79, 1.88). Of the thirteen covariates analysed in the second model, only two household factors were associated with history of malaria: being located in the well-drained stratum (OR=0.49, CI 0.26, 0.96) and being bitten while in the house (OR=1.22, CI 0.19, 0.49). These results suggest that high socioeconomic status is associated with increased household-level mosquito control use, although household-level control may not be enough, as many people are exposed to biting mosquitoes while away from the house and in areas that are more likely to harbour mosquitoes.
Although maize pollen is known to provide nutrition for larval anopheline mosquitoes, the epidemiologic relationship between maize agriculture and malaria transmission has never been defined. To determine whether recent changes in malaria transmission in Ethiopia might be linked to the spread of maize as a commercial crop, we compared malaria transmission and maize cultivation intensity in 21 villages in the Bure District of northwestern Ethiopia where maize cultivation has recently expanded. The cumulative incidence in high maize cultivation areas was 9.5 times higher than in areas with less maize. A chi-square goodness-of-fit test results showed that malaria cases were not distributed evenly among categories of maize cultivation intensity, (chi2 = 1,578, P < 0.001). A Poisson regression suggested that the intensity of maize cultivation, controlled for differences in elevation between sites, was positively and significantly correlated with malaria incidence. Thus, the intensity of maize cultivation was associated with exacerbated human risk of malaria in Bure.
Insecticide-treated bed nets (ITN) provide real hope for the reduction of the malaria burden across Africa. Understanding factors that determine access to ITN is crucial to debates surrounding the optimal delivery systems. The influence of homestead wealth on use of nets purchased from the retail sector is well documented, however, the competing influence of mother's education and physical access to net providers is less well understood.
Between December 2004 and January 2005, a random sample of 72 rural communities was selected across four Kenyan districts. Demographic, assets, education and net use data were collected at homestead, mother and child (aged < 5 years) levels. An assets-based wealth index was developed using principal components analysis, travel time to net sources was modelled using geographic information systems, and factors influencing the use of retail sector nets explored using a multivariable logistic regression model.
Homestead heads and guardians of 3,755 children < 5 years of age were interviewed. Approximately 15% (562) of children slept under a net the night before the interview; 58% (327) of the nets used were purchased from the retail sector. Homestead wealth (adjusted OR = 10.17, 95% CI = 5.45-18.98), travel time to nearest market centres (adjusted OR = 0.51, 95% CI = 0.37-0.72) and mother's education (adjusted OR = 2.92, 95% CI = 1.93-4.41) were significantly associated with use of retail sector nets by children aged less than 5 years.
Approaches to promoting access to nets through the retail sector disadvantage poor and remote communities where mothers are less well educated.
Malaria epidemics in highland areas of East Africa have caused considerable morbidity and mortality in the past two decades. Knowledge of "hotspot" areas of high malaria incidence would allow for focused preventive interventions in resource-poor areas, particularly if the hotspot areas can be discerned during non-epidemic periods and predicted by ecological factors.
To address this issue, spatial distribution of malaria incidence and the relationship of ecological factors to malaria incidence were assessed in the highland area of Kipsamoite, Kenya, from 2001-2004.
Clustering of disease in a single geographic "hotspot" area occurred in epidemic and non-epidemic years, with a 2.6 to 3.2-fold increased risk of malaria inside the hotspot, as compared to outside the area (P < 0.001, all 4 years). Altitude and proximity to the forest were independently associated with increased malaria risk in all years, including epidemic and non-epidemic years.
In this highland area, areas of high malaria risk are consistent in epidemic and non-epidemic years and are associated with specific ecological risk factors. Ongoing interventions in areas of ecological risk factors could be a cost-effective method of significantly reducing malaria incidence and blunting or preventing epidemics, even in the absence of malaria early warning systems. Further studies should be conducted to see if these findings hold true in varied highland settings.
Recent resurgence of malaria in the highlands of Western Kenya has called for a more comprehensive understanding of the previously neglected complex highland vector ecology. Besides other drivers of malaria epidemiology, topography is likely to have a major effect on spatial vector and parasite distribution. The aim of this study was to determine the effects of topography on malaria spatial vector distribution and parasite prevalence.
Indoor resting adult malaria vectors and blood parasites were collected in three villages along a 4 km transect originating from the valley bottom and ending at the hilltop for 13 months. Members of the Anopheles gambiae complex were identified by PCR. Blood parasites were collected from children 6-13 years old and densities categorized by site of home location and age of the children.
Ninety eight percent (98%) of An. gambiae s.s. and (99%) Anopheles funestus were collected in houses located at the edge of the valley bottom, whereas 1% of An. gambiae s.s. were collected at mid hill and at the hilltop respectively. No An. funestus were collected at the hilltop. Malaria prevalence was 68% at the valley bottom, 40.2% at mid hill and 26.7% at the hilltop. Children aged six years and living at the edge of the valley bottom had an annual geometric mean number of 66.1 trophozoites for every 200 white blood cells, while those living at mid-hill had a mean of 84.8, and those living at hilltop had 199.5 trophozoites.
Malaria transmission in this area is mainly confined to the valley bottom. Effective vector control could be targeted at the foci. However, the few vectors observed at mid-hill maintained a relatively high prevalence rate. The higher variability in blood parasite densities and their low correlation with age in children living at the hilltop suggests a lower stability of transmission than at the mid-hill and valley bottom.
To determine whether proximity to flowering maize enhances the development of larval anopheline mosquitoes breeding in turbid water and when crowded, we evaluated the development of larval Anopheles arabiensis under various conditions of turbidity, larval density, and proximity to pollen-shedding maize in simulated breeding puddles in a malaria-endemic site. In naturally formed puddles, water turbidity, as well as larval density, increased as the rainy season progressed. In sites remote from flowering maize, more pupae developed and the resulting adults were larger in relatively clear water than in turbid water, and larval crowding inhibited development. In close proximity to flowering maize, however, larval development was little affected by water turbidity and larval crowding. Larvae of this member of the African An. gambiae complex of mosquitoes develop readily in turbid water and when crowded, provided that their breeding sites are located where maize pollen is abundant.
Information on the spatial relationships between disease vectors and environmental factors is fundamental to vector-borne disease control. Although it is well known that mosquito abundance is associated with the amount of rainfall and thus the number of larval breeding sites, the spatial relationship between larval habitat availability and adult mosquito abundance is not clear. We investigated the impact of environmental heterogeneity and larval habitats on the spatial distribution of Anopheles gambiae s. s. and An. funestus adult mosquitoes, the most important malaria vectors in the highlands of western Kenya. Mosquito sampling was conducted in May, August, and November 2002, and February 2003. Geographic information system layers of larval habitats, land use type, human population distribution, house structure, and hydrologic schemes were overlaid with adult mosquito abundance. Correlography was used to determine the spatial autocorrelation in adult mosquito abundance among houses and the cross-correlation between adult mosquito abundance and environmental factors. Getis' G(i)(*)(d) index was used to define focal adult mosquito abundance clusters. We found a significant autocorrelation in the vector population and a significant cross-correlation between the vector population and larval habitat availability. The threshold distances of both autocorrelation and cross-correlation were significantly varied among seasons. Focal clustering analysis revealed that the adult vector population was concentrated along the Yala River Valley where most larval habitats were found. Regression analysis found that distance of a house to the Yala River, age of the house, elevation, house structure, and tree canopy coverage significantly affected adult mosquito abundance. Our results suggest that vector control targeted at malaria transmission hotspots and supplemented by larval control may be an effective approach for epidemic malaria control in the western Kenya highlands.
Transmission of Plasmodium falciparum generally decreases with increasing elevation, in part because lower temperature slows the development of both parasites and mosquitoes. However, other aspects of the terrain, such as the shape of the land, may affect habitat suitability for Anopheles breeding and thus risk of malaria transmission. Understanding these local topographic effects may permit prediction of regions at high risk of malaria within the highlands at small spatial scales.
Hydrologic modelling techniques were adapted to predict the flow of water across the landscape surrounding households in two communities in the western Kenyan highlands. These surface analyses were used to generate indices describing predicted water accumulation in regions surrounding the study area. Households with and without malaria were compared for their proximity to regions of high and low predicted wetness. Predicted wetness and elevation variables were entered into bivariate and multivariate regression models to examine whether significant associations with malaria were observable at small spatial scales.
On average, malaria case households (n = 423) were located 280 m closer to regions with very high wetness indices than non-malaria "control" households (n = 895) (t = 10.35, p < 0.0001). Distance to high wetness indices remained an independent predictor of risk after controlling for household elevation in multivariate regression (OR = 0.93 [95% confidence interval = 0.89-0.96] for a 100 m increase in distance). For every 10 m increase in household elevation, there was a 12% decrease in the odds of the house having a malaria case (OR = 0.88 [0.85-0.90]). However, after controlling for distance to regions of high predicted wetness and the community in which the house was located, this reduction in malaria risk was not statistically significant (OR = 0.98 [0.94-1.03]).
Proximity to terrain with high predicted water accumulation was significantly and consistently associated with increased household-level malaria incidence, even at small spatial scales with little variation in elevation variables. These results suggest that high wetness indices are not merely proxies for valley bottoms, and hydrologic flow models may prove valuable for predicting areas of high malaria risk in highland regions. Application in areas where malaria surveillance is limited could identify households at higher risk and help focus interventions.
Summary As highland regions of Africa historically have been considered free of malaria, recent epidemics in these areas have raised concerns that high elevation malaria transmission may be increasing. Hypotheses about the reasons for this include changes in climate, land use and demographic patterns. We investigated the effect of land use change on malaria transmission in the south-western highlands of Uganda. From December 1997 to July 1998, we compared mosquito density, biting rates, sporozoite rates and entomological inoculation rates between 8 villages located along natural papyrus swamps and 8 villages located along swamps that have been drained and cultivated. Since vegetation changes affect evapotranspiration patterns and, thus, local climate, we also investigated differences in temperature, humidity and saturation deficit between natural and cultivated swamps. We found that on average all malaria indices were higher near cultivated swamps, although differences between cultivated and natural swamps were not statistically significant. However, maximum and minimum temperature were significantly higher in communities bordering cultivated swamps. In multivariate analysis using a generalized estimating equation approach to Poisson regression, the average minimum temperature of a village was significantly associated with the number of Anopheles gambiae s.l. per house after adjustment for potential confounding variables. It appears that replacement of natural swamp vegetation with agricultural crops has led to increased temperatures, which may be responsible for elevated malaria transmission risk in cultivated areas.
To obtain information on adult populations of Afrotropical malaria vector mosquitoes, mark-release-recapture experiments were performed with Anopheles females collected from indoor resting-sites in a savanna area near Ouagadougou, Burkina Faso, during September 1991 and 1992. Results were used to estimate the absolute population densities, daily survival rates, and dispersal parameters of malaria vectors in that area. In 1991 a total of 7260 female Anopheles were marked and released, of which 106 were recaptured in the release village and 6 in the neighbouring villages, a total recapture rate of 1.5%. The following year 13,854 female Anopheles were released and 116 recaptured in Goundri and 8 in the neighbouring villages, a total recapture rate of 0.9%. Recaptures were found in three of eight villages near Goundri. Nearly all of the recaptured mosquitoes were An gambiae s.l. Of these, molecular determination revealed that An.gambiae s.s. and An.arabiensis were present in a ratio of approximately 2:3. Two simple random models of dispersal were simulated and the parameters of the models determined by searching for the least-squared fit between simulated and observed distributions. The mean distance moved by individual mosquitoes, estimated in this way, ranged 350-650 m day-1, depending on the model and the year considered. Population densities were estimated using the Lincoln Index, Fisher-Ford and Jolly's methods. The estimates of population size had high standard errors and were not particularly consistent A "consensus' value of 150,000-350,000 mosquitoes is believed to apply for the An.gambiae s.l. female population. Survival was estimated to be 80-88% per day.
Malaria transmission varies from village to village and even from family to family in the same village. The current study was conducted in northern Ethiopia to identify risk factors responsible for such variations in a hypoendemic highland malaria setting: 2114 children aged < 10 years living in 6 villages situated close to small dams at altitudes from 1775 to 2175 m were monitored. Monthly malaria incidence was determined 4 times over a 1-year period during 1997. Incidence results were then analysed by 14 individual and household factors using Poisson multivariate regression. Among 14 factors analysed, use of irrigated land (rate ratio[RR] = 2.68, 95% CI 1.64-4.38), earth roof (RR = 2.15, 95% CI 1.31-3.52), animals sleeping in the house (RR = 1.92, 95% CI 1.29-2.85), windows (RR = 1.84, 95% CI 1.30-2.63), open eaves (RR = 1.85, 95% CI 1.19-2.88), no separate kitchen (RR = 1.57, 95% CI 1.10-2.23), and 1 sleeping room (RR = 1.52, 95% CI 1.05-2.20), were significantly associated with malaria. The proportion of infection among children exposed to one or no risk factor was 2.1%, increasing with the number of risk factors and reaching 29.4% with 5 or more. Further studies are needed to confirm the importance of particular risk factors, possibly leading to simple health education and control measures that could become part of routine control programmes, implemented with inter-sectoral collaboration.
Using data from India, we estimate the relationship between household wealth and children's school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children's enrollment across Indian states. On average a "rich" child is 31 percentage points more likely to be enrolled than a "poor" child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.
The impact of geography on incidence of clinical episodes of malaria was investigated in a cohort of children enrolled in a longitudinal clinical trial of antimalarial therapy in Kampala, Uganda. Participant households and the boundaries of local swamps and streams were mapped and incidence of clinical malaria episodes was measured prospectively using passive surveillance during one year of follow-up. Of 316 cohort participants, 305 from 219 households were followed for at least six weeks and were included in the analysis. Incidence of clinical malaria was highly variable, with no episodes occurring in 131 participants, and 367 new episodes of malaria diagnosed in the remaining 174 children. A gradient in incidence of clinical episodes of malaria was observed with distance of residence from a swamp (0.41 episodes per person year for residence > 100 meters from a swamp increasing to 2.22 episodes per person year for residence within a swamp), or a stream (0.61 episodes per person year for residence > or = 500 meters from a stream versus 1.76 episodes per person year for residence <500 meters from a stream). Multivariate analysis showed that distances of residence from a swamp or from a stream were independent predictors of malaria incidence, controlling for age, use of preventative measures, and primary source of water. Distance from a swamp was the strongest predictor, with an incidence rate ratio of 4.3 (95% confidence interval = 2.6-6.9, P < 0.001) between residence within a swamp and >100 meters from a swamp. In this urban setting, incidence of clinical episodes of malaria was strongly associated with proximity of residence to potential mosquito breeding sites.
The epidemiology of malaria over small areas remains poorly understood, and this is particularly true for malaria during epidemics in highland areas of Africa, where transmission intensity is low and characterized by acute within and between year variations. We report an analysis of the spatial distribution of clinical malaria during an epidemic and investigate putative risk factors. Active case surveillance was undertaken in three schools in Nandi District, Western Kenya for 10 weeks during a malaria outbreak in May-July 2002. Household surveys of cases and age-matched controls were conducted to collect information on household construction, exposure factors and socio-economic status. Household geographical location and altitude were determined using a hand-held geographical positioning system and landcover types were determined using high spatial resolution satellite sensor data. Among 129 cases identified during the surveillance, which were matched to 155 controls, we identified significant spatial clusters of malaria cases as determined using the spatial scan statistic. Conditional multiple logistic regression analysis showed that the risk of malaria was higher in children who were underweight, who lived at lower altitudes, and who lived in households where drugs were not kept at home.
Anopheline larval habitats associated with a swamp, were examined in a highland area (1910 m elevation) of western Kenya. A significant association was found between occurrence of Anopheles gambiae Giles s.s. (Diptera: Culicidae) larvae and two factors, habitat size and vegetation type. Over 80% of An. gambiae s.s. larvae were found in small isolated pools, characterized by short plants, occurring in both swamp margins and roadside ditches. However, Anopheles gambiae s.s. was not found in habitats marked by papyrus and floating plants. The larval habitat of An. gambiae s.s. was characterized by warmer daytime temperatures of water, which were significantly affected by habitat size and plant size. The density of indoor resting An. gambiae s.s. was 0.22 per house and negatively associated with distance from the swamp. These results indicate that the practice of swamp cultivation, in populated areas of the African highlands, increases availability and enhances habitat conditions for the malaria vector.
In areas of highly seasonal Plasmodium falciparum transmission, the presence of a large reservoir of persistently infected but asymptomatic individuals in the dry season leads to predictable increases in the incidence of clinical malaria in the rainy season. Highland areas, by contrast, are prone to unpredictable epidemics of malaria. To determine the importance of persistent asymptomatic infection in highland areas, we assessed asymptomatic individuals in the highland area of Kipsamoite, Kenya for the presence of P. falciparum blood-stage infection by microscopy and PCR. Five sample collections were performed during rainy and dry seasons over a 31-month period. The final collection was obtained at the start of a rainy season epidemic. Asymptomatic parasitemia was infrequent, ranging from 1.3 to 8.1% by microscopy and 5.9 to 14.5% by PCR testing. Microscopy had low sensitivity (22.2-54.8%) but excellent specificity (95.4-100%) in comparison to PCR testing. Frequency of asymptomatic parasitemia did not differ by age. Gametocyte prevalence was <1% in all periods, except at the start of the epidemic, when it increased to 5.3%. In this epidemic-prone highland area, inter-epidemic periods are characterized by low frequencies of asymptomatically infected individuals. Increases in gametocyte prevalence may be an early indicator of impending outbreaks.
Wealth, mother's education and physical access as determinants of retail sector net use in rural Kenya Travel as a risk factor for uncomplicated Plasmodium falciparum malaria in the highlands of western Kenya
- Noor Am
- Ja Omumbo
- Aa Amin
- D Zurovac
- Snow Rw Shanks Gd
- K Biomndo
- Hl Guyatt
- Snow
Noor AM, Omumbo JA, Amin AA, Zurovac D & Snow RW (2006) Wealth, mother's education and physical access as determinants of retail sector net use in rural Kenya. Malaria Journal 5, 5. Shanks GD, Biomndo K, Guyatt HL & Snow RW (2005) Travel as a risk factor for uncomplicated Plasmodium falciparum malaria in the highlands of western Kenya. Transactions of the Royal Society of Tropical Medicine and Hygiene 99(1), 71–74.
Malaria risk factors in highland western Kenya
- C Ernst
C. Ernst et al. Malaria risk factors in highland western Kenya
E-mail: kernst@email.arizona.edu Tropical Medicine and International Health
- N Martin Ave
Corresponding Author Kacey C. Ernst, Division of Epidemiology and Biostatistics, University of Arizona, 1295 N Martin Ave.,
Tucson, AZ 85724-5183, USA. E-mail: kernst@email.arizona.edu
Tropical Medicine and International Health
volume 14 no 10 pp 1258–1265 october 2009