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A Human Disease Indicator for the Effects of Recent Global Climate Change
Abstract
Connections between weather and disease are well established, with many diseases occurring during certain seasons or erupting from unseasonable flood or drought conditions. With new concerns about global warming, accompanied by greater climate variability, many recent studies have focused on disease fluctuations related to short-term or interannual climate oscillations (e.g., from weather extremes driven by El Nino). Yet, the nagging question remains as to whether or not there has been any documented change in human disease trends in response to long-term climate change, since warming has already occurred over the last century (1, 2).
This study likely represents the first piece of evidence that warming trends over the last century are affecting human disease.
... Vector-borne pathogens are particularly sensitive to climate 11 , a fact that has led to widespread and continued speculation that anthropogenic climate change will increase the incidence and intensity of their transmission [12][13][14] . There is, however, little evidence supporting such speculations 11,15,16 , while at the same time there is an increasing realization that other non-climatic abiotic and biotic factors can also affect disease distribution [17][18][19][20] . In this article, we discuss those features of the BTV-Culicoides system that make it exquisitely sensitive to changes in climate. ...
... closely to the criteria that has been set out by earlier researchers 11,15,16 . Several areas of research (for example, theoretical model systems, laboratory experiments and field manipulations and observations) have demonstrated the biological sensitivity of both Culicoides vectors and BTV to changes in processes to climate are considered together, it is likely that increases in temperature (particularly at night-time and in winter), as well as increases in precipitation (particularly in summer/autumn) will lead to an increased geographical and seasonal incidence of BTV transmission by increasing the range, abundance and seasonal activity of vectors, increasing the proportion of a vector species that is competent and by increasing the development rates of the virus within vectors, thereby extending transmission ability to further Culicoides species. ...
... Changes in the global temperature can generate a wide range of consequences for human health. Direct consequences are linked to the bioclimatic well-being of people, whereas indirect consequences are linked to the complex interactions between environmental conditions and the spread of infectious 17 and allergic diseases 18 . The positive effects of climate-related human well-being are many 19 : from the reduction of the risk of numerous chronic diseases in adulthood (such as diabetes and cardiovascular conditions, obesity, and asthma), to the acceleration of recovery after surgery, to the reduction of hospital admissions and premature mortality, up to better pregnancy outcomes and improved mental health 20 . ...
The population experiencing high temperatures in cities is rising due to anthropogenic climate change, settlement expansion, and population growth. Yet, efficient tools to evaluate potential intervention strategies to reduce population exposure to Land Surface Temperature (LST) extremes are still lacking. Here, we implement a spatial regression model based on remote sensing data that is able to assess the population exposure to LST extremes in urban environments across 200 cities based on surface properties like vegetation cover and distance to water bodies. We define exposure as the number of days per year where LST exceeds a given threshold multiplied by the total urban population exposed, in person ⋅ day. Our findings reveal that urban vegetation plays a considerable role in decreasing the exposure of the urban population to LST extremes. We show that targeting high-exposure areas reduces vegetation needed for the same decrease in exposure compared to uniform treatment.
... Diarrhea is estimated to reach 17% of all deaths among children aged <5 years and ranks 5 th as the biggest cause of death in the world (37) . Climate factors such as rainfall, relative humidity, and air pressure can contribute to changes in the incidence of diarrhea because it impacts on the level of replication of certain pathogenic bacteria and protozoa that cause diarrhea (38) . ...
Areas classified as Urban Heat Islands (UHI) have a higher health risk due to climate change. High population activity, increasing population density, and low vegetation cover cause this area to become warmer than its surroundings. From the detection of the spatial pattern, Padang City has nine sub-districts belonging to UHI. In this area, environmental problems often occur due to climate calamities and have an impact on health. Therefore, this study was to determine the classification of public health risks and community adaptation to climate change in urban heat island areas. This research was conducted on 141 households in Koto Tangah sub-district as the large UHI area and highly prone to climate problems. Data collected by questionnaires, observation, and literature study. The risk assessment matrix was used to identify health risk status. The results showed that water pollution, respiratory problems, and diarrheal diseases are classified as high risks. The community needs to adapt to climate change, mainly doing routine physical activities, to increase immunity from many diseases.
... The linkage between climatic variables and transmission (or spread) of vector-borne diseases, for example, malaria, dengue fever, lyme, and scrub typhus is well established. These diseases are either seasonspecific or erupt because of extreme events such as flood, drought etc. (Patz, 2002). Short-term changes in the climatic variables because of global warming has intensified the need of studying climate change and disease transmission concurrently (Rocklöv & Dubrow, 2020). ...
We propose a hybrid machine learning algorithm (i.e., P2CA−PSO−ANN) to model malaria outbreak in three districts (Barmer, Bikaner, and Jodhpur) of Rajasthan in the Western India. We have used different meteorological variables (i.e., relative humidity, temperature, and rainfall) as input features to predict malaria. We have also considered the combined impact of these variables through a linear data fusion. We then extract the uncorrelated information from the feature set by applying Probabilistic Principal Component Analysis (P2CA). We trained the fully connected feed-forward Artificial Neural Network (ANN) by optimising its hyperparameters iteratively through a bio-inspired optimisation algorithm (Particle Swarm Optimisation). We train and evaluate the performance of this algorithm using monthly meteorological variables from 2009 - 2012. This accurately predicts the malaria cases with the coefficient of correlation (R = 0.99), and Root Mean Square Error (RMSE = 1.76).
Finally, we compare our model with different benchmark algorithms (Generalised Regression Neural Network (GRNN), Gaussian Process Regression (GPR), Support Vector Regression (SVR), Random Forest, and Radial Basis Neural Networks (RBNN)) in terms of accuracy. We observed the performance of hybrid machine learning model relatively high. This study can be used as an early warning intelligent system to predict the malaria outbreaks solely from meteorological data.
... The linkage between climatic variables and transmission (or spread) of vector-borne diseases, for example, malaria, dengue fever, lyme, and scrub typhus is well established. These diseases are either seasonspecific or erupt because of extreme events such as flood, drought etc. (Patz, 2002). Short-term changes in the climatic variables because of global warming has intensified the need of studying climate change and disease transmission concurrently (Rocklöv & Dubrow, 2020). ...
We propose a hybrid machine learning algorithm to model malaria cases in three districts (Barmer, Bikaner, and Jodhpur) of Rajasthan in Western India. We have used different meteorological variables (i.e., relative humidity, temperature, and rainfall) as input features to predict malaria. We have also considered the combined impact of these variables through a linear data fusion. We then extract the uncorrelated information from the feature set by applying probabilistic principal component analysis. We trained the fully connected feed-forward ANN by optimising its hyperparameters iteratively through a bio-inspired optimisation algorithm (Particle Swarm Optimisation). We train and evaluate the performance of this algorithm using monthly meteorological variables from 2009 - 2012. This accurately predicts the malaria cases with the coefficient of correlation (R = 0.99) and RMSE = 1.76. Finally, we compare our model with different benchmark algorithms (GRNN, GPR, SVR, RF, and RBNN) in terms of accuracy. We observed the performance of the hybrid machine learning model to be relatively high. This study can be used as an early warning intelligent system to predict malaria outbreaks solely from meteorological data.
... Changes in the global temperature can generate a wide range of consequences for human health. Direct consequences are linked to the bioclimatic well-being of people, whereas indirect consequences are linked to the complex interactions between environmental conditions and the spread of infectious 17 and allergic diseases 18 . approach to the problem, the design and evaluation of urban adaptation plans should be city-specific and based on the detailed assessment of the city thermoscape 23 . ...
Extreme urban heat exposure due to anthropogenic climate change and population growth is rising. Yet, efficient tools to evaluate potential intervention strategies to reduce heat exposure are still lacking. Here we implement a spatial regression model that is able to predict with high accuracy the Land Surface Temperature (LST) of urban environments across 190 cities based on land surface properties like vegetation, built-up areas, and distance to water bodies, without any additional climate information. By coupling the model information with the population layer, we show that by increasing the overall urban vegetation by 3%, it would be possible to reduce by 50% the exposure of the urban population to extreme heat, while an increment of 11% could reduce LST over the most populated areas of the city by 1K. We finally discuss the challenges and the limitations of greening interventions in the context of available surfaces in urban areas
... Establishing temporal trends for zoonotic enteric diseases allows for the identification of potential risk factors (Lal 2014;Chen et al. 2015). Identifying seasonal trends also allows for the monitoring of changes in disease patterns, which is useful for understanding how environ-mentally sensitive diseases will respond under future scenarios of climate change or land use change (Patz 2002;Lal 2014). Therefore, this study seeks to review and describe spatial trends in dairy cattle density from 2000 to 2014 and to explore the temporal patterns of disease notifications from 1997 to 2015 across New Zealand. ...
Public health risks associated with the intensification of dairy farming are an emerging concern. Dairy cattle are a reservoir for a number of pathogens that can cause human illness. This study examined the spatial distribution of dairy cattle density and explored temporal patterns of human campylobacteriosis and cryptosporidiosis notifications in New Zealand from 1997 to 2015. Maps of dairy cattle density were produced, and temporal patterns of disease rates were assessed for urban versus rural areas and for areas with different dairy cattle densities using descriptive temporal analyses. Campylobacteriosis and cryptosporidiosis rates displayed strong seasonal patterns, with highest rates in spring in rural areas and, for campylobacteriosis, summer in urban areas. Increases in rural cases often preceded increases in urban cases. Furthermore, disease rates in areas with higher dairy cattle densities tended to peak before areas with low densities or no dairy cattle. Infected dairy calves may be a direct or indirect source of campylobacteriosis or cryptosporidiosis infection in humans through environmental or occupational exposure routes, including contact with animals or feces, recreational contact with contaminated waterways, and consumption of untreated drinking water. These results have public health implications for populations living, working, or recreating in proximity to dairy farms.
... One positive feedback of higher temperatures is a reduction in the survival of some enteric pathogens in water (e.g., Campylobacter, E. coli, enteroviruses, when temperatures are comprised between 20°C to 37°C), with the exception of Vibrio cholerae (Hunter, 2003). It has been shown that increases in cholera incidences are strongly correlated with episodes of El Niñ o, the intensity of which is predicted to increase with climate change; however, the effect is transient, suggesting a threshold effect (Patz, 2002). Several studies have also found positive associations between air temperature and waterborne infections (Guzman-Herrador et al., 2015). ...
... In this work, it was found that the large-scale HFRS surveillance dataset collected at 127 cities in Eastern China during 2005-2016 and the global climate dynamics records available exhibit a strong synchronicity in multiannual cycles, including 1, 1.5 and 3 yrs periods (Fig 2, S4 and S5 Figs). This finding provides strong quantitative support to an earlier claim that HFRS infections are closely associated with global climate dynamics through complicated nonlinear dynamics, including multiannual and seasonal variational patterns of both climate dynamics and rodent population [20,[49][50][51]. ...
Background
Hemorrhagic fever with renal syndrome (HFRS) is a rodent-associated zoonosis caused by hantavirus. The HFRS was initially detected in northeast China in 1931, and since 1955 it has been detected in many regions of the country. Global climate dynamics influences HFRS spread in a complex nonlinear way. The quantitative assessment of the spatiotemporal variation of the “HFRS infections-global climate dynamics” association at a large geographical scale and during a long time period is still lacking.
Methods and findings
This work is the first study of a recently completed dataset of monthly HFRS cases in Eastern China during the period 2005–2016. A methodological synthesis that involves a time-frequency technique, a composite space-time model, hotspot analysis, and machine learning is implemented in the study of (a) the association between HFRS incidence spread and climate dynamics and (b) the geographic factors impacting this association over Eastern China during the period 2005–2016. The results showed that by assimilating core and city-specific knowledge bases the synthesis was able to depict quantitatively the space-time variation of periodic climate-HFRS associations at a large geographic scale and to assess numerically the strength of this association in the area and period of interest. It was found that the HFRS infections in Eastern China has a strong association with global climate dynamics, in particular, the 12, 18 and 36 mos periods were detected as the three main synchronous periods of climate dynamics and HFRS distribution. For the 36 mos period (which is the period with the strongest association), the space-time correlation pattern of the association strength indicated strong temporal but rather weak spatial dependencies. The generated space-time maps of association strength and association hotspots provided a clear picture of the geographic variation of the association strength that often-exhibited cluster characteristics (e.g., the south part of the study area displays a strong climate-HFRS association with non-point effects, whereas the middle-north part displays a weak climate-HFRS association). Another finding of this work is the upward climate-HFRS coherency trend for the past few years (2013–2015) indicating that the climate impacts on HFRS were becoming increasingly sensitive with time. Lastly, another finding of this work is that geographic factors affect the climate-HFRS association in an interrelated manner through local climate or by means of HFRS infections. In particular, location (latitude, distance to coastline and longitude), grassland and woodland are the geographic factors exerting the most noticeable effects on the climate-HFRS association (e.g., low latitude has a strong effect, whereas distance to coastline has a wave-like effect).
Conclusions
The proposed synthetic quantitative approach revealed important aspects of the spatiotemporal variation of the climate-HFRS association in Eastern China during a long time period, and identified the geographic factors having a major impact on this association. Both findings could improve public health policy in an HFRS-torn country like China. Furthermore, the synthetic approach developed in this work can be used to map the space-time variation of different climate-disease associations in other parts of China and the World.
... 4 Diarrhea, for example, is one of the conditions in children contributing to malnutrition, affecting both growth and cognitive development of infected individuals, among other complications. [5][6][7] The spread of infectious forms of intestinal parasites is a determining factor for the increased incidence of intestinal parasites in Brazil. The eggs, larvae, or cysts submit your manuscript | www.dovepress.com ...
Background
Intestinal parasites’ eggs, larvae, or cysts can be carried in public transport buses, and contribute to the increased incidence of diseases. This study aimed to detect biological forms of intestinal parasites in samples from public buses in the town of Diamantina, Minas Gerais, in order to know the local situation and propose interventions to improve public health.
Materials and methods
In November 2014, six samples were obtained in buses of the two stations by using Graham method, in duplicate, by affixing a 6×5 cm clear tape, six times on each collection site of the bus, in an area of ~30 cm². Then, each tape was positioned longitudinally on a slide microscope, and the identification of the biological forms of the parasites was performed with the aid of a 40× objective optical microscope.
Results
A total of 216 slides were analyzed, of which 86 (39.8%) were positive for at least one intestinal parasite. Cysts of Entamoeba coli were the most frequently found in this study (52.1%), followed by Endolimax nana cysts (30.7%), Iodamoeba butschlii (6.5%), helminth larvae (4.7%), Giardia lamblia cysts (3.6%), Hymenolepis nana eggs (1.2%), Enterobius vermicularis eggs (0.6%), and Entamoeba histolytica cysts (0.6%). Top right handrails and right stanchions had the highest occurrence of biological forms, with 18.3% and 14.8%, respectively.
Conclusion
The results indicated the need for better cleaning of the buses and better personal hygiene by users, since pathogenic and non-pathogenic intestinal parasites were found, suggesting fecal contamination of these sites, representing a risk to public health.
... Factors like open water storage increase Aedes population densities and the transmission of Aedes-borne diseases like dengue, especially in urban areas [15]. Outbreak of the disease is tied to seasonal patterns such as heavy rain and humidity [36]. Dengue control measures include environmental management and mosquito control with insecticides [15]. ...
Numerous virulent and widespread diseases are related to water. The transmission and outbreak of water-related diseases are closely coupled to their hydrological environment. Changes in this environment and the associated hydrological processes may affect the occurrence and virulence of water-related diseases. Environmental changes can be manifold, including e.g. climate and land use, agricultural management or urbanization. Water fluxes and storages play a dominant role in describing disease outbreak, transmission and transport. New land cover types often alter landscape scale water storages. If the effects of changes could be better understood, predictions about the distribution, emergence or outbreak of water-related diseases would be possible. Furthermore, the collaboration of experts from different disciplines is essential for accurate spatial and temporal prediction of water-related disease outbreaks. Here we review the current state of knowledge of water-related diseases and present a general classification of these diseases, followed by a discussion of their major drivers. This review focuses particularly on hydrologists and how they can contribute with their understanding of hydrological processes.
... Because recent field and laboratory studies indicate that corals on the GBR are significantly adapted to local thermal conditions [43,90], we based WSSTA on the local SST climatology created independently for each of the 48 reefs. Furthermore, our long-term, fine-grained measurements of SST and SST anomalies match the scale of the biological surveys, eliminating the usual mismatch between climate and health data that has plagued similar studies of human and wildlife disease dynamics [91]. ...
... geographical region, type of water supply, urban vs. rural setting, human behavior, age, host susceptibility, concurrent disease such as HIV) modify this relationship [34,45,[47][48][49][50][51][52]. Mitigating the burden of diarrheal diseases appears especially critical since global change, including climate change, global population increase and urbanization, may impact the ecology of infectious diseases and enhance the outbreak of waterborne diseases [5,[53][54][55][56], in particular in developing countries where the population is considered to be less resilient than in developed countries [57]. ...
Background
The global burden of diarrhea is a leading cause of morbidity and mortality worldwide. In montane areas of South-East Asia such as northern Laos, recent changes in land use have induced increased runoff, soil erosion and in-stream suspended sediment loads, and potential pathogen dissemination. To our knowledge, few studies have related diarrhea incidences to catchment scale hydrological factors such as river discharge, and loads of suspended sediment and of Fecal Indicator Bacteria (FIB) such as Escherichia coli, together with sociological factors such as hygiene practices. We hypothesized that climate factors combined with human behavior control diarrhea incidence, either because higher rainfall, leading to higher stream discharges, suspended sediment loads and FIB counts, are associated with higher numbers of reported diarrhea cases during the rainy season, or because water shortage leads to the use of less safe water sources during the dry season. Using E. coli as a FIB, the objectives of this study were thus (1) to characterize the epidemiological dynamics of diarrhea in Northern Laos, and (2) to identify which hydro-meteorological and sociological risk factors were associated with diarrhea epidemics.
Methods
Considering two unconnected river catchments of 22 and 7,448 km², respectively, we conducted a retrospective time series analysis of meteorological variables (rainfall, air temperature), hydrological variables (discharge, suspended sediments, FIB counts, water temperature), and the number of diarrheal disease cases reported at 6 health centers located in the 5 southern districts of the Luang Prabang Province, Lao PDR. We also examined the socio-demographic factors potentially affecting vulnerability to the effect of the climate factors, such as drinking water sources, hygiene habits, and recreational water exposure.
Results
Using thus a mixed methods approach, we found E. coli to be present all year long (100–1,000 Most Probable Number or MPN 100 mL⁻¹) indicating that fecal contamination is ubiquitous and constant. We found that populations switch their water supply from wells to surface water during drought periods, the latter of which appear to be at higher risk of bacterial contamination than municipal water fountains. We thus found that water shortage in the Luang Prabang area triggers diarrhea peaks during the dry and hot season and that rainfall and aquifer refill ends the epidemic during the wet season. The temporal trends of reported daily diarrhea cases were generally bimodal with hospital admissions peaking in February-March and later in May-July. Annual incidence rates were higher in more densely populated areas and mostly concerned the 0–4 age group and male patients.
Conclusions
We found that anthropogenic drivers, such as hygiene practices, were at least as important as environmental drivers in determining the seasonal pattern of a diarrhea epidemic. For diarrheal disease risk monitoring, discharge or groundwater level can be considered as relevant proxies. These variables should be monitored in the framework of an early warning system provided that a tradeoff is found between the size of the monitored catchment and the frequency of the measurement.
... Although future impacts of climate change on human health have received considerable and increasing amounts of attention since the mid-1990s, few studies have documented human health impacts already evident. A study of the El Niño -Southern Oscillation and cholera in Bangladesh from around 1900 to 2001 may provide the first evidence that warming trends over the last century are already affecting human health 58,59 . The World Health Organization (WHO) has identified climate change as a major environmental risk to health 60 . ...
The increase in asthma incidence, prevalence, and morbidity over recent decades presents a significant challenge to public health. Pollen is an important trigger of some types of asthma, and both pollen quantity and season depend on climatic and meteorological variables. Over the same period as the global rise in asthma, there have been considerable increases in atmospheric carbon dioxide concentration and global average surface temperature. We hypothesize anthropogenic climate change as a plausible contributor to the rise in asthma. Greater concentrations of carbon dioxide and higher temperatures may increase pollen quantity and induce longer pollen seasons. Pollen allergenicity can also increase as a result of these changes in climate. Exposure in early life to a more allergenic environment may also provoke the development of other atopic conditions, such as eczema and allergic rhinitis. Although the etiology of asthma is complex, the recent global rise in asthma could be an early health effect of anthropogenic climate change.
... Global warming may also promote changes in the general pattern of fecal-oral infections and foodborne illness. It is hoped that the wide geographic distribution (by both the altitude and latitude) of organisms that transmit disease (vectors) not only increase the potential for transmission, but also change the dynamics of the life cycle (e g, reproduction, survival and potential of infection) of vectors of parasitic infectious organisms [23,25,26,29]. ...
... Vector-borne diseases are one of the most studied health challenges pertaining to climate change. 32 Although variation has been observed for specific diseases, according to the UN Food and Agriculture Organization (FAO), 33 some regions reported expansion of vector range due to rising temperaturesdthis has been noted with latitudinal and longitudinal shifts of tickborne encephalitis in Europe 34 in addition to mosquito-borne malaria in eastern Africa associated with a warming trend beginning in the 1970s. 17 Similar increases in malaria in southern Africa and South America 35 have been associated with the heavy rainfall of the El Niño Southern Oscillation cycle (ENSO). ...
Background:
Climate change has myriad implications for the health of humans, our ecosystems, and the ecological processes that sustain them. Projections of rising greenhouse gas emissions suggest increasing direct and indirect burden of infectious and noninfectious disease, effects on food and water security, and other societal disruptions. As the effects of climate change cannot be isolated from social and ecological determinants of disease that will mitigate or exacerbate forecasted health outcomes, multidisciplinary collaboration is critically needed.
Objectives:
The aim of this article was to review the links between climate change and its upstream drivers (ie, processes leading to greenhouse gas emissions) and health outcomes, and identify existing opportunities to leverage more integrated global health and climate actions to prevent, prepare for, and respond to anthropogenic pressures.
Methods:
We conducted a literature review of current and projected health outcomes associated with climate change, drawing on findings and our collective expertise to review opportunities for adaptation and mitigation across disciplines.
Findings:
Health outcomes related to climate change affect a wide range of stakeholders, providing ready collaborative opportunities for interventions, which can be differentiated by addressing the upstream drivers leading to climate change or the downstream effects of climate change itself.
Conclusions:
Although health professionals are challenged with risks from climate change and its drivers, the adverse health outcomes cannot be resolved by the public health community alone. A phase change in global health is needed to move from a passive responder in partnership with other societal sectors to drive innovative alternatives. It is essential for global health to step outside of its traditional boundaries to engage with other stakeholders to develop policy and practical solutions to mitigate disease burden of climate change and its drivers; this will also yield compound benefits that help address other health, environmental, and societal challenges.
... In this way, there are studies that have focused on the role of the tropical Pacific on vegetation, crop yields and the economic consequences resulting from these impacts (Hansen et al., 1998(Hansen et al., , 2001Adams et al., 1999;Legler et al., 1999;Li and Kafatos, 2000;Naylor et al., 2001;Tao et al., 2004;Deng et al., 2010;Phillips et al., 1998;Verdin et al., 1999;Podestá et al., 1999;Travasso et al., 2009). Regarding human health, tropical SST patterns have been widely linked to the development and propagation of diseases (Linthicum et al., 2010), where El Niño-Southern Oscillation (ENSO)-related variability plays a crucial role mainly affecting tropical and subtropical regions around the world (Kovats, 2000;Patz, 2002;Kovats et al., 2003;Patz et al., 2005;McMichael et al., 2006). ...
Sea Surface Temperature is the key variable when tackling seasonal to decadal climate forecast. Dynamical models are unable to properly reproduce tropical climate variability, introducing biases that prevent a skillful predictability. Statistical methodologies emerge as an alternative to improve the predictability and reduce these biases. Recent studies have put forward the non-stationary behavior of the teleconnections between tropical oceans, showing how the same tropical mode has different impacts depending on the considered sequence of decades. To improve the predictability, the Sea Surface Temperature based Statistical Seasonal foreCAST model (S4CAST) introduces the novelty of considering the non-stationary links between the predictor and predictand fields. This paper describes the development of S4CAST model whose operation is focused on the study of the predictability of any variable related to sea surface temperature. An application focused on West African rainfall predictability has been implemented as a benchmark example.
... Here, we develop a simple criterion for tick activity based on surface temperature and humidity at the ground level and, hence, neglect other impacts like (man-made) changes in landscape and ecosystems, including interim hosts like rodents, as well as changing exposure due to modern human behaviour [Randolph, 2001]. Therefore, the trend patterns of tick activity presented here are only arising from changing climate conditions and do not necessarily coincide with the future trend patterns of TBE and LB, as has been shown for the 20 th century by Patz [2002], Randolph [2004] and Sumilo et al. [2006]. In particular, Sumilo et al. [2007] have demonstrated that the political and socio-economic transition has been predominantly responsible for the tremendous increase of TBE cases in the Baltic States after 1990. ...
Among the consequences of climate change, latitudinal and altitudinal shifts in the occurrence of vector-borne infectious diseases represent a potential threat for human society. In Europe tick-borne infections like encephalitis (TBE) and Lyme borreliosis (LB) already play a major role
with increasing risk as various studies have shown. Beside biological and landscape-related factors as well as human behaviour, climate conditions affect the vectors' life cycle and activity. Here, we present results from a very high-resolution regional climate change simulation centered over
Germany and derive a multi-variate climate-related measure of tick activity, including temperature and humidity variables. With increasing temperature and decreasing humidity near the ground a pattern of enhanced tick activity in central and southern Germany and reduced tick activity in parts
of northern Germany and along the pre-Alps may occur. In terms of the interannual variations of tick activity, a stabilization around a higher mean value occurs after 2050 in Southeast Germany, whereas enhanced variability prevails in the coastal region of Germany and in the Alps. This study
shows that the implications of climate change may be quite complex in space although a simple approach is used and other factors of tick activity besides climate have been disregarded.
... In the case of neighboring Bangladesh -Link between stronger El Nino events and cholera prevalence was shown; and a strong case for the climate-health link by providing evidence for biological sensitivity to climate, meteorological evidence of climate change, and evidence of epidemiological change with global warming is shown. The study likely represents the first piece of evidence that warming trends over the last century are affecting human disease (Patz, 2002). ...
The global warming has substantial direct and indirect impact on us, on the health of ecosystems and food and water sources. Warming has been rapid due to economic development with little care on the consequences toward mother earth's atmosphere, land and water systems. Lessons to Nepal include warming of snowy peaks, their quick melting and sooner depletion of snow stocks; increased probability of sudden floods and desertification, changing crop zones; productivity regimes, patterns, maturity days, ecology; insects, predators, diseases their degree of occurrence, types or characteristics etc., so that concerns and priorities to research would be changed. Planting a tree in the backyard, practicing better urban disposals systems, encouraging individual choices such as un plugging a freezer, replacing incandescent bulbs with more efficient ones, sealing and insulating heating and cooling devices and food boxes, using solar, wind or geo-thermal resources whenever possible, joining a group of bicyclists, or mass transit; or resistance to an extreme weather, fuel use for cooking or warming food all can make a difference. It was felt that a single country can do little, but even the little would be of great value. Nepal can help reduce global warming by taking steps such as harnessing river systems soon for clean energy and offer benefits to the global community through safeguarded bio-diversity to maintain genetic system. Nepal should adapt to the bio-secure initiatives for meeting food needs locally and needs to let policymakers and leaders know and win confidence to this concern with support on study on Glaciers in Nepal and monitor the global warming situation and contribute by further seeking realistic small ways to reduce global warming. We can control hazards by raising awareness and exploring smaller and practical approaches at grass root level. The Journal of AGRICULTURE AND ENVIRONMENT Vol. 8, 2007, pp. 133-144
... Such an analysis offers insights into potential adaptation options for climate change related health impacts in New Zealand. By analysing historical disease patterns, such investigations can enhance disease prediction models [90], identify diseases that are potentially useful markers of changes in global climate or local weather [91] and contribute to the development of climate based, early warning systems. ...
Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases.
To examine the associations between regional climate variability and enteric disease incidence in New Zealand.
Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models.
No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β = 0.130, SE = 0.060, p <0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β = -0.008, SE = 0.004, p <0.05). By contrast, salmonellosis was positively associated with temperature (β = 0.110, SE = 0.020, p<0.001) of the current month and SOI of the current (β = 0.005, SE = 0.002, p<0.050) and previous month (β = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher.
Although spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.
... The consequences of climate variation at different temporal scales have attracted a great deal of scholarly attention (Patz 2002, Parmesan & Yohe 2003, Ludwig et al. 2006). Both short-and long-term climate variations can bring unwanted disasters to the world. ...
Only a small number of quantitative studies have investigated the short- and long-term impacts of climate variations on society during Europe’s pre-industrial era. Accordingly, there is a lack of research clearly comparing the consequences of climate variation (short-term) and climate change (long-term). This study focuses on the close relationship between climate variations and the dynamics of the agrarian economy in Europe during the period of 1500 to 1800 AD. ARX modeling was applied to analyze the relationship between climate and past agrarian economies, on large spatial and long temporal scales. Both short- and long-term findings are provided, based on statistical analysis, as well as the empirical study of the 17th century economic crisis as a case analysis. The negative climatic variations in the short-term caused grain prices to increase. Grain prices were affected for up to 25 yr by a period of climatic variation due to the price stickiness. The immediate and long-term effects of climate variations over the study period can add up to significantly influence agrarian economies. Climate change occurs when climate variations last for more than 30 yr. The accumulated effect of climate change on the agrarian economy ultimately resulted in an economic crisis in pre-industrial Europe.
... To properly model the random interactions occurring in populations, the study of disease extinction requires a stochastic modeling approach. There are numerous studies from time series analysis and epidemic modeling supporting stochastic fluctuations due to random interactions [16,17,18,19]. The fluctuations may act as an effective force that drives the disease to vanish [20]. ...
Disease control is of paramount importance in public health, with infectious disease extinction as the ultimate goal. Although diseases may go extinct due to random loss of effective contacts where the infection is transmitted to new susceptible individuals, the time to extinction in the absence of control may be prohibitively long. Intervention controls are typically defined on a deterministic schedule. In reality, however, such policies are administered as a random process, while still possessing a mean period. Here, we consider the effect of randomly distributed intervention as disease control on large finite populations. We show explicitly how intervention control, based on mean period and treatment fraction, modulates the average extinction times as a function of population size and rate of infection spread. In particular, our results show an exponential improvement in extinction times even though the controls are implemented using a random Poisson distribution. Finally, we discover those parameter regimes where random treatment yields an exponential improvement in extinction times over the application of strictly periodic intervention. The implication of our results is discussed in light of the availability of limited resources for control.
... See XavierRodo et al, 2002, J. Patz, 2002 5 Nagasaki 1960, Zhou et al, 2002, Yang et al 2005, Steinmann et al 2006, Guo-Jing Yang et al 2007 ...
... There is growing recognition that we need to focus on possible synergisms among these and other stressors [Hughes and Connell, 1999;Lenihan et al., 1999]. In the last several years, the relationship between climate conditions and disease has received more attention as researchers have connected factors such as temperature and precipitation with increases in human and wildlife diseases [Pascual et al., 2000;Patz, 2002;Kutz et al., 2005;Pounds et al., 2006]. Yet, few studies have focused on the effects of climate change on diseases in the ocean, particularly at broad spatial scales. ...
Ocean warming due to climate change could increase the frequency and severity of infectious coral disease outbreaks by increasing pathogen virulence or host susceptibility. However, little is known about how temperature anomalies may affect disease severity over broad spatial scales. We hypothesized that the frequency of warm temperature anomalies increased the frequency of white syndrome, a common scleractinian disease in the Indo-Pacific. We created a novel 4 km satellite temperature anomaly dataset using data from NOAA's Pathfinder program and developed four different temperature anomaly metrics, which we correlated with white syndrome frequency at 47 reefs spread across 1500 km of the Great Barrier Reef. This cross-sectional epidemiological analysis used data from disease field surveys conducted by the Australian Institute of Marine Science six to twelve months after the summer of 2002, a year of extensive coral bleaching. We found a highly significant positive relationship between the frequency of warm temperature anomalies and the frequency of white syndrome. There was also a highly significant, nearly exponential relationship between total coral cover and the number of disease cases. Further, coral cover modified the effect of temperature on disease frequency. Both high coral cover (>50%) and anomalously warm water appear to be necessary for white syndrome outbreaks to occur and these two risk factors explained nearly 75% of the variance in disease cases. These results suggest that rising ocean temperatures could exacerbate the effects of infectious diseases on coral reef ecosystems.
... The strong altitudinal gradients within tropical mountain ranges particularly in the Andes of Colombia and Venezuela, and the Cordillera of Costa Rica are important in controlling climatic variability over space. This synthesis of the principal mechanisms and phenomena which control climate variability over the study region at annual and inter-annual timescales provides important insights into variability at longer (paleoclimatic) timescales, and permits the evaluation of climatic evidence of climate and global change (IPCC, 2001), including the accelerated retreat of tropical glaciers (Kaser and Osmaston, 2002), outbreaks of tropical diseases (Patz, 2002), and the most rapid loss of biodiversity in the world (Myers et al., 2000). Besides, the region possesses urgent basic and applied research needs prompted by large scale deforestation, erosion and land degradation, vulnerability and risk of human populations and settlements, and water pollution. ...
Continuing the tropical Pacific multivariate air‐sea coupler proposed by us before, we design the Global spatial‐temporal Teleconnection Coupler (GTC), which is modeled to discover the latent teleconnections among global sea surface temperature (SST). To this end, Pacific, Indian, and Atlantic oceans are divided into small ocean patches that compose a dynamics graph, in which the adjacent relationships are artificially constructed by prior knowledge and the non‐adjacent relationships are learned from the data by deep learning methods. Based on GTC, an El Niño‐Southern Oscillation (ENSO) deep learning forecast model (ENSO‐GTC) is established, where probability graph convolution layers are designed to learn spatial‐temporal teleconnection, that is, non‐adjacent relationships in the dynamics graph. A loss function with a graph total variations penalty term is remarkably proposed to maintain physical consistency. We tune ENSO‐GTC to the optimal, which has Niño3.4 index correlation skills of 0.79/0.66/0.51 at 6‐/12‐/18‐month forecasts with iterative strategy, and above 0.6 within 20‐month forecasts with direct strategy, outperforming the other state‐of‐the‐art models. We explore the forecast skill of ENSO‐GTC on the effective forecast lead time, improvements of persistence barrier, and analysis of forecast errors. Moreover, we find that what GTC has learned exactly matches multiple ENSO theories. The oscillations of Kelvin and Rossby waves make a 6‐month lagged correlation on Pacific SST. The north and south Pacific meridional modes (NPMM and SPMM) are strongly linked to the evolutions of ENSO and should be monitored more. The teleconnections between equatorial Indian/Atlantic and Pacific are very important and usually have 2‐month/8‐month lagged correlations before ENSO.
As climate change threatens human life and health by causing severe storms, floods, temperature fluctuations and droughts, it is predicted that in the coming decades, most of the global population will be impacted and the lives of millions will be at risk. In this context, the article investigates the existence of a symmetric and asymmetric causality between climate change and health between 1990 and 2015 for European countries, including EU, EFTA member and EU candidate states. In the first stage of the analysis, health scores are estimated by cluster and discriminant analyses; in the second stage, the relationships among these scores and climate variables are examined. The country-specific findings are obtained for the health effects of climate change variables according to factors such as geographical structure and seasonal characteristics. According to the results, while the health effects of changes in temperature and greenhouse emissions differ from country to country, the reduction in precipitation for nearly half of the countries is found to have a negative effect on health.
Changes in climate have caused impacts on natural and human systems. These impacts affect poor people's lives through impacts on livelihoods and the destruction of homes. In Delta State, Nigeria, the impacts of climate change are real. Adaptation has been identified as the key to reducing the impacts of climate change. However, successful adaptation depends on use of climate services. While climate services are essential to adaptation, the services do not always reach the users who need it most. This chapter analyzes factors influencing access and utilization of climate services in Delta State. The chapter utilizes the survey research while data were analyzed using both descriptive and inferential statistics. Findings show a low utilization of climate service. The determinants of access and utilization of climate services include income, educational attainments, access to ICT facilities, extension agents, and the level of local climate variability. The chapter calls for awareness creation on the importance of climate services.
This report presents a conceptual framework in the conduct of a vulnerability assessment and impact modeling for the Public Health Sector, a climate change vulnerability assessment framework, a climate change monitoring and evaluation framework, and documents innovative climate change adaptation practices applicable to the Philippine health sector. It also recommends that governments should engage more actively with the scientific community, who in turn must be supported to provide easily accessible climate risk information.
Changes in climate have caused impacts on natural and human systems. These impacts affect poor people's lives through impacts on livelihoods and the destruction of homes. In Delta State, Nigeria, the impacts of climate change are real. Adaptation has been identified as the key to reducing the impacts of climate change. However, successful adaptation depends on use of climate services. While climate services are essential to adaptation, the services do not always reach the users who need it most. This chapter analyzes factors influencing access and utilization of climate services in Delta State. The chapter utilizes the survey research while data were analyzed using both descriptive and inferential statistics. Findings show a low utilization of climate service. The determinants of access and utilization of climate services include income, educational attainments, access to ICT facilities, extension agents, and the level of local climate variability. The chapter calls for awareness creation on the importance of climate services.
As climate change threatens human life and health by causing severe storms, floods, temperature fluctuations and droughts, it is predicted that in the coming decades, most of the global population will be impacted and the lives of millions will be at risk. In this context, the article investigates the existence of a symmetric and asymmetric causality between climate change and health between 1990 and 2015 for European countries, including EU, EFTA member and EU candidate states. In the first stage of the analysis, health scores are estimated by cluster and discriminant analyses; in the second stage, the relationships among these scores and climate variables are examined. The country-specific findings are obtained for the health effects of climate change variables according to factors such as geographical structure and seasonal characteristics. According to the results, while the health effects of changes in temperature and greenhouse emissions differ from country to country, the reduction in precipitation for nearly half of the countries is found to have a negative effect on health.
Climate change currently contributes to the global burden of disease and premature deaths (very high confidence).
Human beings are exposed to climate change through changing weather patterns (temperature, precipitation, sea-level rise and more frequent extreme events) and indirectly through changes in water, air and food quality and changes in ecosystems, agriculture, industry and settlements and the economy. At this early stage the effects are small but are projected to progressively increase in all countries and regions. [8.4.1]
Emerging evidence of climate change effects on human health shows that climate change has:
altered the distribution of some infectious disease vectors (medium confidence) [8.2.8];
altered the seasonal distribution of some allergenic pollen species (high confidence) [8.2.7];
increased heatwave-related deaths (medium confidence) [8.2.1].
Projected trends in climate-change-related exposures of importance to human health will:
increase malnutrition and consequent disorders, including those relating to child growth and development (high confidence) [8.2.3, 8.4.1];
increase the number of people suffering from death, disease and injury from heatwaves, floods, storms, fires and droughts (high confidence) [8.2.2, 8.4.1];
continue to change the range of some infectious disease vectors (high confidence) [8.2, 8.4];
have mixed effects on malaria; in some places the geographical range will contract, elsewhere the geographical range will expand and the transmission season may be changed (very high confidence) [8.4.1.2];
increase the burden of diarrhoeal diseases (medium confidence) [8.2, 8.4];
increase cardio-respiratory morbidity and mortality associated with ground-level ozone (high confidence) [8.2.6, 8.4.1.4];
increase the number of people at risk of dengue (low confidence) [8.2.8, 8.4.1];
bring some benefits to health, including fewer deaths from cold, although it is expected that these will be outweighed by the negative effects of rising temperatures worldwide, especially in developing countries (high confidence) [8.2.1, 8.4.1].
Adaptive capacity needs to be improved everywhere; impacts of recent hurricanes and heatwaves show that even high-income countries are not well prepared to cope with extreme weather events (high confidence). [8.2.1, 8.2.2]
Adverse health impacts will be greatest in low-income countries. Those at greater risk include, in all countries, the urban poor, the elderly and children, traditional societies, subsistence farmers, and coastal populations (high confidence). [8.1.1, 8.4.2, 8.6.1.3, 8.7]
Economic development is an important component of adaptation, but on its own will not insulate the world’s population from disease and injury due to climate change (very high confidence).
Critically important will be the manner in which economic growth occurs, the distribution of the benefits of growth, and factors that directly shape the health of populations, such as education, health care, and public-health infrastructure. [8.3.2]
This training course' objectives are to improve the knowledge of health professionals on the associations and implications of climate change on human health and to enhance stronger and more efficient participation of the health sector in addressing climate change challenges. The training course is designed for public health professionals who are actively involved in the management and decision-making process related to health programmes. The course will also give a good foundation for non-medical professionals involved in addressing the health challenges posed by climate change. In 2015 this course was updated and is available at http://www.searo.who.int/entity/water_sanitation/documents/CCH_Training_Modules/en/
This training course' objectives are to improve the knowledge of health professionals on the associations and implications of climate change on human health and to enhance stronger and more efficient participation of the health sector in addressing climate change challenges. The training course is designed for public health professionals who are actively involved in the management and decision-making process related to health programmes. The course will also give a good foundation for non-medical professionals involved in addressing the health challenges posed by climate change. In 2015 this course was updated and is available at http://www.searo.who.int/entity/water_sanitation/documents/CCH_Training_Modules/en/
The World Health Organization Ottawa Charter for Health Promotion emphasized that health is not just a state or the object of living but should be considered as a vital resource for everyday life on which numerous services and deliverables depend. Without good health very little is achievable in the life of an individual or collectively in the context of a community.
In this chapter, we provide a physical understanding based on the regional large-scale environmental and hydroclimatic processes of how the first outbreaks of cholera may be related to low flow discharge of the Ganges, Brahmaputra, and Meghna rivers and subsequent and salinity intrusion during spring. Cholera incidence values in this season are inversely related to streamflow volumes, that is, bigger spring cholera peaks are seen in strong drought years. On the other hand, autumn cholera outbreaks are positively correlated to peak streamflow volumes, that is, bigger autumn peaks are seen in high flood years. Evidence points to large-scale population vulnerability to biannual cholera transmission mechanisms that provide ecological and environmental "conditions" for cholera outbreaks in the Bengal Delta floodplains.
Purpose – This chapter discusses and compares the climate change policies of Argentina and Canada at the international, national, and local level. Starting with a discussion of both Argentina and Canada’s positions in the UNFCCC, the chapter then explains the positions and policies that have been implemented in the national and then local level of each country.
Methodology/approach – This chapter is an analysis and comparison of laws, policies, and practices through not only a discursive analysis of their official positive legal meaning but also through an analysis of their actual applied impact. A multilevel institutional analysis is utilized such that the climate change policies of Argentina and Canada are analyzed at the international, national, and local level.
Findings – At the international level, a discourse surrounds Argentina and Canada in terms of developing and developed country and global justice. At the national level, each country has different official laws and discourses surrounding climate change; however, at the regional level in both countries, many similarities exist in respect of climate change mitigation and adaptation in both positivistic legal meaning and actual applied reality. This chapter hypothesizes that a problematic gap exists between the climate change institutional framework and the “real” climate change being experienced by local people.
Practical implications – The similarities in the actual applied experience of climate change mitigation and adaptation in Argentina (a developing country) and Canada (a developed country) at the regional level, contrasted with the different characteristics at the national and international level, offer insights into the challenge of effective implementation of climate change mitigation and adaptation.
Originality/value – The multilevel institutional analysis and comparison of Argentina and Canada in respect of climate change mitigation and adaptation reveal significant structural governance challenges for the effective implementation of climate change mitigation and adaptation goals of the UNFCCC. Overcoming these challenges may facilitate implementation of climate change mitigation and adaptation goals.
This chapter examines the relationship of climate change, health, and gender in the Pacific region; identifies gaps in research, capacity, and support; and proposes a framework illustrating the practical adaptation measures to be applied in strengthening the Papua New Guinea’s (PNG) public health sector capacity and policy. Using literature review as the research method, the study found that although other countries in the pacific are mostly affected by the climate change impacts, PNG remains highly affected by the climate-induced health impacts. Hence, a case study on Papua New Guinea was prepared. The chapter provides a practical understanding and knowledge on emerging health threats, gender issues, and adaptation measures to strengthen the Pacific and PNG’s public health system. The framework presented in this chapter could be highly beneficial not only for PNG but also for the whole Pacific region.
The first objective of this chapter is to review how climate change and climate variability may affect livestock diseases’ occurrences while emphasizing how little the knowledge on the links between livestock diseases and climate change is. The review of the literature shows that most of the investigated diseases are zoonotic ones with few specifi c to livestock and, moreover, these diseases appeared to be dramatically affected by climate variability rather than by ongoing climate change. A second objective of this chapter is to introduce some new modelling tools that can help predict diseases’ occurrences in space and in time in relation to climate variability and change, namely, environmental niche modelling, epidemiological modelling using R0map and teleconnection modelling. A working example on cattle trypanosomiasis in China is given to illustrate teleconnection modelling by using data from the World Organization for Animal Health (OIE). The conclusion of this chapter stresses three points: the need to consider the entangled linkages between ecosystems, society and health of animals and humans; the need of elaborated scenarios of livestock diseases linked to climate change and variability, which necessitates to develop and improve the recording of livestock diseases; and the need to incorporate climate-mediated physiological responses into the programs that manage breeding genetic diversity.
This chapter describes the shifted pattern of Bluetongue (BT) epidemics in Europe and summarizes the strands of evidence that link this emergence to climate change. The biological mechanisms underlying this response to climate change may include increased virus persistence over winter, the northward expansion of the primary Old World vector—Culicoides imicola—and, beyond this vector's range, transmission by indigenous European Culicoides species. This chapter considers these potential mechanisms in more detail, focusing on questions that remain to be answered and their consequences for the spread of BT in Europe. Vector-borne pathogens are particularly sensitive to climate because they are transmitted between vertebrate hosts by small, poikilothermic, blood-sucking insects or ticks. This has led to widespread and continued speculation that anthropogenic climate change will increase the incidence and intensity of their transmission. Bluetongue virus (BTV) replicates in all ruminant species but severe disease is mostly restricted to certain breeds of sheep and some species of deer. In cattle, BTV causes long-lived sub-clinical infections making these ruminants the main reservoir host. Bluetongue virus is transmitted between its ruminant hosts, primarily by certain species of Culicoides biting midges. Finally, this chapter speculates on the features of the European BTV–Culicoides ‘episystem’ that made it particularly sensitive to climate change.
Periodic epidemics of malaria occur every five to seven years in West Bengal. According to IPCC (Intergovernmental Panel on climate change), the vector borne diseases will be increased day by day due to global climate change. Ambient temperature, relative humidity, rainfall and wind speed are the major influencing factors of the dynamics of vector borne diseases. The breeding activity of Anopheles mosquitoes in association with meteorological parameters may be considered as one of the m environmental causes of malaria transmission. Our study addresses the malaria transmission probability in an urban and rural site of West Bengal. Kolkata (22.57 0 N, 88.37 0 E) and Digha (22.38 urban and a rural site in this study. Meteorological Parameters for the period 1997 to 2007 of these sites are analyzed to find the probability of malaria transmission windows throughout the year along with the malaria incidences. It is observed that broad transmission window (Temp: 16 40 0 C, RH: 55% – 80%) extends eight months in a year. The two sites have equal probability of transmission but malaria incidences in Digha are too small. Hence other environmental parameters such as slum area, drainage, population density, agricultural practices and health services are to be considered for monitoring malaria transmission. Periodic epidemics of malaria occur every five to seven years in West Bengal. According to IPCC (Intergovernmental Panel on climate change), the vector borne diseases will be increased day by day due to global emperature, relative humidity, rainfall and wind speed are the major influencing factors of the dynamics of vector borne diseases. The breeding activity of Anopheles mosquitoes in association with meteorological parameters may be considered as one of the major environmental causes of malaria transmission. Our study addresses the malaria transmission probability in an urban and rural site of West Bengal. E) and Digha (22.38 0 N, 87.32 0 E) are selected as an study. Meteorological Parameters for the period 1997 to 2007 of these sites are analyzed to find the probability of malaria transmission windows throughout the year along with the malaria incidences. It is observed that broad transmission window (Temp: 160 – 80%) extends eight months in a year. The two sites have equal probability of transmission but malaria incidences in Digha are too small. Hence other environmental parameters such as slum area, drainage, practices and health services are to be considered for monitoring malaria transmission.
The purpose of this article is to examine the relationship between environmental changes and infectious diseases and their impact on health in environmental justice (EJ) communities. The evolution of EJ science and research is contingent upon an integrated approach that takes into account social processes and environmental changes to address the burden of infectious diseases in EJ communities. We recognize that infectious disease and environmental justice is novel and calls for more research in this area, especially as the focus of public health shifts towards an ecologic and social approach to disease prevention. We attempt to explore in further detail how environmental changes such as urbanization, agriculture, and climate variability could potentially influence pathogen dynamics, vector transmission, host susceptibility, and disease outcomes among environmental justice populations.
The third volume in the Institute of Animal Health (IAH) Biology of Animal Infections Series, Bluetongue discusses one of the most economically important diseases of domesticated livestock. Affecting primarily sheep particularly the improved mutton and wool breeds, it is now endemic in Africa, India, the Middle and Far East, Australia and the Americas, and over the last six years has caused a series of outbreaks throughout the Mediterranean region and central Europe. Bluetongue represent a paradigm not only for the other orbiviruses (such as African horse sickness virus, which shares the same vector species) but also for other insect transmitted diseases, including those of humans. * The only single definitive work that provides both historical and up to date data on the disease * Describes the latest developments in epidemiological modelling, molecular epidemiology and vaccine development, as well as explaining the current global epidemiology of the disease * Outlines the importance and possible mechanisms of overwintering, and the impact of global warming on the vectors and virus distribution Bluetongue is the third volume in Biology of Animal Infections, a series devoted to major animal infections. Written by acknowledged international experts in the field this book provides a wealth of information on Bluetongue ranging from the atomic structure of the virus particle, through diagnostics and control to transmission, distribution and clinical signs. The book also focuses on recent and dramatic changes in the regions affected by bluetongue virus that are linked compellingly to on-going climate-change and which have confirmed Bluetongue as one of the most important emerging diseases of the 21st century.
We address the problem of developing new and improved stochastic control
methods that enhance extinction in disease models. In finite
populations, extinction occurs when fluctuations owing to random
transitions act as an effective force that drives one or more components
or species to vanish. Using large deviation theory, we identify the
location of the optimal path to extinction in epidemic models with
stochastic vaccine controls. These models not only capture internal
noise from random transitions, but also external fluctuations, such as
stochastic vaccination scheduling. We quantify the effectiveness of the
randomly applied vaccine over all possible distributions by using the
location of the optimal path, and we identify the most efficient control
algorithms. We also discuss how mean extinction times scale with
epidemiological and social parameters.
Decisions for climate policy will need to take place in advance of climate science resolving all relevant uncertainties. Further, if the concern of policy is to reduce risk, then the best-estimate of climate change impacts may not be so important as the currently understood uncertainty associated with realizable conditions having high consequence. This study focuses on one of the most uncertain aspects of future climate change - precipitation - to understand the implications of uncertainty on risk and the near-term justification for interventions to mitigate the course of climate change. We show that the mean risk of damage to the economy from climate change, at the national level, is on the order of one trillion dollars over the next 40 years, with employment impacts of nearly 7 million labor-years. At a 1% exceedance-probability, the impact is over twice the mean-risk value. Impacts at the level of individual U.S. states are then typically in the multiple tens of billions dollar range with employment losses exceeding hundreds of thousands of labor-years. We used results of the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) climate-model ensemble as the referent for climate uncertainty over the next 40 years, mapped the simulated weather hydrologically to the county level for determining the physical consequence to economic activity at the state level, and then performed a detailed, seventy-industry, analysis of economic impact among the interacting lower-48 states. We determined industry GDP and employment impacts at the state level, as well as interstate population migration, effect on personal income, and the consequences for the U.S. trade balance.
Lack of birth and death registries in most of developing countries, particularly those in sub-Saharan Africa led to the establishment of Demographic Surveillance Systems (DSS) sites which monitor large population cohorts within defined geographical areas. DSS collects longitudinal data on migration, births, deaths and their causes via verbal autopsies. DSS data provide an opportunity to monitor many health indicators including mortality trends. Mortality rates in Sub-Sahara Africa show seasonal patterns due to high infant and child malaria-related mortality which is influenced by seasonal features present in environmental and climatic factors. However, it is unclear whether seasonal patterns differ by age in the first few months of life. This study provides an overview of approaches to assess, capture and detect seasonality peaks and patterns in mortality using the infant mortality data from the Rufiji DSS, Tanzania. Seasonality was best captured using Bayesian negative binomial models with time and cycle dependent seasonal parameters and autoregressive temporal error terms. Seasonal patterns are similar among different age groups during infancy and timing of their mortality peaks do not differ. Seasonality in mortality rates with two peaks per year is pronounced which corresponds to rainy seasons. Understanding of these trends is important for public health preparedness.
Analysis of the global mean surface air temperature has shown that its increase is due, at least in part, to differential
changes in daily maximum and minimum temperatures, resulting in a narrowing of the diurnal temperature range (DTR). The analysis,
using station metadata and improved areal coverage for much of the Southern Hemisphere landmass, indicates that the DTR is
continuing to decrease in most parts of the world, that urban effects on globally and hemispherically averaged time series
are negligible, and that circulation variations in parts of the Northern Hemisphere appear to be related to the DTR. Atmospheric
aerosol loading in the Southern Hemisphere is much less than that in the Northern Hemisphere, suggesting that there are likely
a number of factors, such as increases in cloudiness, contributing to the decreases in DTR.
Climate Change 2001: The Scientific Basis is the most comprehensive and up-to-date scientific assessment of past, present and future climate change. The report: • Analyses an enormous body of observations of all parts of the climate system. • Catalogues increasing concentrations of atmospheric greenhouse gases. • Assesses our understanding of the processes and feedbacks which govern the climate system. • Projects scenarios of future climate change using a wide range of models of future emissions of greenhouse gases and aerosols. • Makes a detailed study of whether a human influence on climate can be identified. • Suggests gaps in information and understanding that remain in our knowledge of climate change and how these might be addressed. Simply put, this latest assessment of the IPCC will again form the standard scientific reference for all those concerned with climate change and its consequences, including students and researchers in environmental science, meteorology, climatology, biology, ecology and atmospheric chemistry, and policymakers in governments and industry worldwide.
The origin of cholera has been elusive, even though scientific evidence clearly shows it is a waterborne disease. However, standard bacteriological procedures for isolation of the cholera vibrio from environmental samples, including water, between epidemics generally were unsuccessful. Vibrio cholerae, a marine vibrio, requiring salt for growth, enters into a dormant, viable but nonculturable stage when conditions are unfavorable for growth and reproduction. The association of Vibrio cholerae with plankton, notably copepods, provides further evidence for the environmental origin of cholera, as well as an explanation for the sporadic and erratic occurrence of cholera epidemics. On a global scale, cholera epidemics can now be related to climate and climatic events, such as El Niño, as well as the global distribution of the plankton host. Remote sensing, with the use of satellite imagery, offers the potential for predicting conditions conducive to cholera outbreaks or epidemics.
It has long been known that cholera outbreaks can be initiated when Vibrio cholerae, the bacterium that causes cholera, is present in drinking water in sufficient numbers to constitute an infective dose, if ingested by humans. Outbreaks associated with drinking or bathing in unpurified river or brackish water may directly or indirectly depend on such conditions as water temperature, nutrient concentration, and plankton production that may be favorable for growth and reproduction of the bacterium. Although these environmental parameters have routinely been measured by using water samples collected aboard research ships, the available data sets are sparse and infrequent. Furthermore, shipboard data acquisition is both expensive and time-consuming. Interpolation to regional scales can also be problematic. Although the bacterium, V. cholerae, cannot be sensed directly, remotely sensed data can be used to infer its presence. In the study reported here, satellite data were used to monitor the timing and spread of cholera. Public domain remote sensing data for the Bay of Bengal were compared directly with cholera case data collected in Bangladesh from 1992-1995. The remote sensing data included sea surface temperature and sea surface height. It was discovered that sea surface temperature shows an annual cycle similar to the cholera case data. Sea surface height may be an indicator of incursion of plankton-laden water inland, e.g., tidal rivers, because it was also found to be correlated with cholera outbreaks. The extensive studies accomplished during the past 25 years, confirming the hypothesis that V. cholerae is autochthonous to the aquatic environment and is a commensal of zooplankton, i.e., copepods, when combined with the findings of the satellite data analyses, provide strong evidence that cholera epidemics are climate-linked.
We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change.
Many diseases are influenced by weather conditions or display strong seasonality, suggestive of a possible climatic contribution. Projections of future climate change have, therefore, compelled health scientists to re-examine weather/disease relationships. There are three projected physical consequences of climate change: temperature rise, sea level rise, and extremes in the hydrologic cycle. This century, the Earth has warmed by about 0.5 degrees centigrade, and the mid-range estimates of future temperature change and sea level rise are 2.0 degrees centigrade and 49 centimeters, respectively, by the year 2100. Extreme weather variability associated with climate change may especially add an important new stress to developing nations that are already vulnerable as a result of environmental degradation, resource depletion, overpopulation, or location (e.g. low-lying coastal deltas). The regional impacts of climate change will vary widely depending on existing population vulnerability. Health outcomes of climate change can be grouped into those of: (a) direct physical consequences, e.g. heat mortality or drowning; (b) physical/chemical sequelae, e.g. atmospheric transport and formation of air pollutants; (c) physical/biological consequences, e.g. response of vector- and waterborne diseases, and food production; and (d) sociodemographic impacts, e.g. climate or environmentally induced migration or population dislocation. Better understanding of the linkages between climate variability as a determinant of disease will be important, among other key factors, in constructing predictive models to guide public health prevention.
Analysis of a monthly 18-year cholera time series from Bangladesh shows that the temporal variability of cholera exhibits
an interannual component at the dominant frequency of El Niño–Southern Oscillation (ENSO). Results from nonlinear time series
analysis support a role for both ENSO and previous disease levels in the dynamics of cholera. Cholera patterns are linked
to the previously described changes in the atmospheric circulation of south Asia and, consistent with these changes, to regional
temperature anomalies.
The two major vector-borne diseases of northern temperate regions, tick-borne encephalitis (TBE) and Lyme borreliosis (LB), show very different epidemiological patterns, but both have increased significantly in incidence since the 1980s. Insight into the temporal dynamics of TBE, gained from statistical analysis of spatial patterns integrated with biological explanation, suggests that the recent increases in TBE cases in Central Europe and the Baltic States may have arisen largely from changes in human behaviour that have brought more people into contact with infected ticks. Under forecast climate change scenarios, it is predicted that enzootic cycles of TBE virus may not survive along the southern edge of their present range, e.g. in Slovenia, Croatia and Hungary, where case numbers are indeed decreasing. New foci, however, are predicted and have been observed in Scandinavia. At the same time, human impact on the landscape, increasing both the habitat and wildlife hosts of ticks, has allowed tick populations to multiply significantly. This probably accounts for a genuine emergence of LB, with its high potential transmission rate, in both the USA and Europe, although the rate of emergence has been exaggerated by improved surveillance and diagnosis.
The public health and economic consequences of Plasmodium falciparum malaria are once again regarded as priorities for global development. There has been much speculation on whether anthropogenic climate change is exacerbating the malaria problem, especially in areas of high altitude where P. falciparum transmission is limited by low temperature. The International Panel on Climate Change has concluded that there is likely to be a net extension in the distribution of malaria and an increase in incidence within this range. We investigated long-term meteorological trends in four high-altitude sites in East Africa, where increases in malaria have been reported in the past two decades. Here we show that temperature, rainfall, vapour pressure and the number of months suitable for P. falciparum transmission have not changed significantly during the past century or during the period of reported malaria resurgence. A high degree of temporal and spatial variation in the climate of East Africa suggests further that claimed associations between local malaria resurgences and regional changes in climate are overly simplistic.
We present here quantitative evidence for an increased role of interannual climate variability on the temporal dynamics of an infectious disease. The evidence is based on time-series analyses of the relationship between El Niño/Southern Oscillation (ENSO) and cholera prevalence in Bangladesh (formerly Bengal) during two different time periods. A strong and consistent signature of ENSO is apparent in the last two decades (1980-2001), while it is weaker and eventually uncorrelated during the first parts of the last century (1893-1920 and 1920-1940, respectively). Concomitant with these changes, the Southern Oscillation Index (SOI) undergoes shifts in its frequency spectrum. These changes include an intensification of the approximately 4-yr cycle during the recent interval as a response to the well documented Pacific basin regime shift of 1976. This change in remote ENSO modulation alone can only partially serve to substantiate the differences observed in cholera. Regional or basin-wide changes possibly linked to global warming must be invoked that seem to facilitate ENSO transmission. For the recent cholera series and during specific time intervals corresponding to local maxima in ENSO, this climate phenomenon accounts for over 70% of disease variance. This strong association is discontinuous in time and can only be captured with a technique designed to isolate transient couplings.
The El Niño/Southern Oscillation (ENSO) phenomenon is the
strongest natural interannual climate fluctuation. ENSO originates in
the tropical Pacific Ocean and has large effects on the ecology of the
region, but it also influences the entire global climate system and
affects the societies and economies of manycountries. ENSO can be
understood as an irregular low-frequency oscillation between a warm (El
Niño) and a cold (La Niña) state. The strong El
Niños of 1982/1983 and 1997/1998, along with the more frequent
occurrences of El Niños during the past few decades, raise the
question of whether human-induced `greenhouse' warming affects, or will
affect, ENSO. Several global climate models have been applied to
transient greenhouse-gas-induced warming simulations to address this
question, but the results have been debated owing to the inability of
the models to fully simulate ENSO (because of their coarse equatorial
resolution). Here we present results from a global climate model with
sufficient resolution in the tropics to adequately represent the narrow
equatorial upwelling and low-frequency waves. When the model is forced
by a realistic future scenario of increasing greenhouse-gas
concentrations, more frequent El-Niño-like conditions and
stronger cold events in the tropical Pacific Ocean result.
We quantify the interannual-to-decadal variability of the heat content (mean temperature) of the world ocean from the surface
through 3000-meter depth for the period 1948 to 1998. The heat content of the world ocean increased by ∼2 × 1023 joules between the mid-1950s and mid-1990s, representing a volume mean warming of 0.06°C. This corresponds to a warming rate
of 0.3 watt per meter squared (per unit area of Earth's surface). Substantial changes in heat content occurred in the 300-
to 1000-meter layers of each ocean and in depths greater than 1000 meters of the North Atlantic. The global volume mean temperature
increase for the 0- to 300-meter layer was 0.31°C, corresponding to an increase in heat content for this layer of ∼1023 joules between the mid-1950s and mid-1990s. The Atlantic and Pacific Oceans have undergone a net warming since the 1950s
and the Indian Ocean has warmed since the mid-1960s, although the warming is not monotonic.
In the United States of America, seafood ranked third on the list of products which caused foodborne disease between 1983 and 1992. Outbreaks connected with fish vectors were caused by scombroid, ciguatoxin, bacteria and unknown agents; in shellfish, unknown agents, paralytic shellfish poisoning, Vibrio spp. and other bacteria, followed by hepatitis A virus, were responsible for the outbreaks. At least ten genera of bacterial pathogens have been implicated in seafood-borne diseases. Over the past twenty-five years, bacterial pathogens associated with faecal contamination have represented only 4% of the shellfish-associated outbreaks, while naturally-occurring bacteria accounted for 20% of shellfish-related illnesses and 99% of the deaths. Most of these indigenous bacteria fall into the family Vibrionaceae which includes the genera Vibrio, Aeromonas and Plesiomonas. In general, Vibrio spp. are not associated with faecal contamination and therefore faecal indicators do not correlate with the presence of Vibrio. Viruses are the most significant cause of shellfish-associated disease: in New York State, for example, 33% and 62% of 196 outbreaks between 1981 and 1992 were caused by Norwalk virus and gastrointestinal viruses (small round structured viruses), respectively. In addition, several illnesses are a result of toxic algal blooms, the growth of naturally occurring bacteria and diatoms causing neurotoxic shellfish poisoning, paralytic shellfish poisoning, diarrhoetic shellfish poisoning, amnesic shellfish poisoning and ciguatera. Current estimates place the annual number of ciguatera cases at 20,000 world-wide. Scombroid poisoning is the most significant cause of illness associated with seafood. Scombrotoxin is of bacterial origin and halophilic Vibrio spp. causing high histamine levels are implicated as the source. Scombroid poisoning is geographically diverse and many species have been implicated, namely: tuna, mahi-mahi, bluefish, sardines, mackerel, amberjack and abalone. Temperature abuse has been cited as a major cause of scombroid poisoning. For routine work, the use of faecal indicators to predict the relative level of faecal contamination should not be disposed of. However, the main source of seafood illness is due to species which are not predicted by these organisms. In order to protect public health, routine surveillance using new pathogen-specific techniques such as polymerase chain reaction should be used. This, in combination with risk assessment methods and hazard analysis and critical control points, will begin to address the need for improvement in the safety of seafood.
Epidemic group A meningococcal meningitis follows a unique and distinctive pattern in sub-Saharan Africa. Advances in molecular
and field epidemiology have begun to elucidate the mechanisms of meningococcal meningitis epidemics. Epidemics result from
a complex combination of host, organism, and environmental risk factors. Recent studies suggest that “antigenic shifts” in
group A meningococcal clones may trigger an outbreak of disease by suddenly decreasing herd immunity within a population.
Although the introduction of new group A meningococcal strains into a susceptible population contributes to the likelihood
of an epidemic, the presence of additional environmental factors, such as low humidity and coincident respiratory tract infections,
are also necessary for an epidemic to occur. Despite the unique behavior of group A meningococcal disease in sub-Saharan Africa,
the application of similar methods of epidemiological analysis may be useful for determining epidemic processes for other
diseases.
The recurrent great malaria epidemics which occurred in the Punjab province of former British India and Ceylon before the introduction of residual insecticides have been related to excessive and failing monsoon rains respectively. In the arid Punjab, rainfall facilitated breeding and increased the lifespan of the mosquito vector and, in the wet part of Ceylon, failing monsoon rains caused rivers to pool, creating more favourable breeding conditions. The periodic fluctuations in monsoon rainfall and epidemic malaria are here explained in relation to the El Niño Southern Oscillation. In the Punjab, epidemic malaria between 1868 and 1943 correlates significantly (r = 0.34, P < 0.005) with the sea surface temperature anomalies in the Eastern Equatorial Pacific, a parameter of the oscillation, and epidemics were significantly more prevalent in a year with a wet monsoon following a dry El Niño year than in other years. In Ceylon, epidemics were significantly more prevalent during El Niño years, when the same south-west monsoon tends to fail. With the reduced reliance on residual insecticides and the recurrence of epidemic malaria on the Indian subcontinent, advances made in predicting El Niño events may be used to forecast high and low risk years for future malaria epidemics.
Cyclospora cayetanensis was detected in fecal specimens from 63 (1.1%) of 5,836 Peruvian children studied over 2 years; the protozoan was detected
by modified acid-fast staining and autofluorescence under ultraviolet light. The highest prevalence occurred among children
between 2 and 4 years of age. Thirty-two percent (20) of the 63 C. cayetanensis—infected children were symptomatic. Nineteen infected children were enrolled in a double-blind, placebo-controlled trial
of a 3-day course of trimethoprim-sulfamethoxazole (TMP-SMZ; 5/25 mg/[kg • d]). Children were followed up with daily stool
examinations (mean number of samples examined per child ± SE, 19 ± 4). The mean duration of oocyst excretion ± SE was 4.8
± 1.2 days for TMP-SMZ recipients compared with 12.1 ±6.1 days for placebo recipients (P < .02). The prevalence of C. cayetanensis infection decreases during winter months and as children age; it decreases precipitously by adulthood. In children in areas
of endemicity, C. cayetanensis usually causes mild disease that is often asymptomatic. TMP-SMZ therapy significantly decreases the duration of oocyst excretion.
Analysis of the 140-year historical record suggests that the inverse relationship between the El Niño–Southern Oscillation
(ENSO) and the Indian summer monsoon (weak monsoon arising from warm ENSO event) has broken down in recent decades. Two possible
reasons emerge from the analyses. A southeastward shift in the Walker circulation anomalies associated with ENSO events may
lead to a reduced subsidence over the Indian region, thus favoring normal monsoon conditions. Additionally, increased surface
temperatures over Eurasia in winter and spring, which are a part of the midlatitude continental warming trend, may favor the
enhanced land-ocean thermal gradient conducive to a strong monsoon. These observations raise the possibility that the Eurasian
warming in recent decades helps to sustain the monsoon rainfall at a normal level despite strong ENSO events.
All known Rift Valley fever virus outbreaks in East Africa from 1950 to May 1998, and probably earlier, followed periods of abnormally high rainfall. Analysis of this record and Pacific and Indian Ocean sea surface temperature anomalies, coupled with satellite normalized difference vegetation index data, shows that prediction of Rift Valley fever outbreaks may be made up to 5 months in advance of outbreaks in East Africa. Concurrent near-real-time monitoring with satellite normalized difference vegetation data may identify actual affected areas.
To investigate whether the El Niño phenomenon and ambient temperature had an effect on the epidemiology of childhood diarrhoea, we analysed data on daily number of admissions of children with diarrhoea to the Oral Rehydration Unit of the Instituto de Salud del Niño in Lima, Peru, between January, 1993, and November, 1998.
We obtained daily data on hospital admissions from the Oral Rehydration Unit, and meteorological data from the Peruvian Weather Service, and used time-series linear regression models to assess the effects of the 1997-98 El Niño event on admissions for diarrhoea.
57,331 children under 10 years old were admitted to the unit during the study. During the 1997-98 El Niño episode, mean ambient temperature in Lima increased up to 5 degrees C above normal, and the number of daily admissions for diarrhoea increased to 200% of the previous rate. 6225 excess admissions were attributable to El Niño, and these cost US$277,000. During the period before the El Niño episode, admissions for diarrhoea increased by 8% per 1 degree C increase in mean ambient temperature. The effects of El Niño and ambient temperature on the number of admissions for diarrhoea were greatest during the winter months.
El Niño had an effect on hospital admissions greater than that explained by the regular seasonal variability in ambient temperature. The excess increase in ambient temperature was the main environmental variable affecting admissions. If our findings are reproducible in other regions, diarrhoeal diseases may increase by millions of cases worldwide with each degree of increase in ambient temperature above normal.
The incidence of tick-borne encephalitis (TBE) in Sweden has substantially increased since the mid-1980s. During the same period the climate has become milder and ticks have become more abundant. We investigated whether there is a link between the change in climate and the increase in incidence of TBE.
Since the late 1950s all cases of encephalitis admitted in Stockholm County have been serologically tested for TBE. We analysed the period 1960-98 with multiple regressions. The number of days per season with temperatures of known importance for tick prevalence and pathogen transmission were studied. 2 years of temperature data were related to each TBE incidence rate to account for the tick's long life-span.
Increases in disease incidence was significantly related (R(2)=0.58; p<0.0001) to a combination of two consecutive mild winters, temperatures favouring spring development (8-10 degrees C) and extended autumn activity (5-8 degrees C) in the year prior to the incidence year, and temperatures allowing tick activity (5-8 degrees C) early in the incidence year.
The findings indicate that the increase in TBE incidence since the mid-1980s is related to the period's change towards milder winters and early arrival of spring. Other factors may have influenced TBE incidence such as more people in endemic locations, and increases in host animal populations; factors which are partly climate related. Access to TBE vaccination since 1986 and increased awareness of ticks might have caused an underestimation of the links found. Our findings also suggest that the incidence of other tick-borne zoonoses might have been affected by the milder climate.
The world's climate appears now to be changing at an unprecedented rate. Shifts in the distribution and behaviour of insect and bird species indicate that biological systems are already responding to this change. It is well established that climate is an important determinant of the spatial and temporal distribution of vectors and pathogens. In theory, a change in climate would be expected to cause changes in the geographical range, seasonality (intra-annual variability), and in the incidence rate (with or without changes in geographical or seasonal patterns). The detection and then attribution of such changes to climate change is an emerging task for scientists. We discuss the evidence required to attribute changes in disease and vectors to the early effects of anthropogenic climate change. The literature to date indicates that there is a lack of strong evidence of the impact of climate change on vector-borne diseases (i.e. malaria, dengue, leishmaniasis, tick-borne diseases). New approaches to monitoring, such as frequent and long-term sampling along transects to monitor the full latitudinal and altitudinal range of specific vector species, are necessary in order to provide convincing direct evidence of climate change effects. There is a need to reassess the appropriate levels of evidence, including dealing with the uncertainties attached to detecting the health impacts of global change.
The Scientific Basis
- C K Folland
- T R Karl
Folland, C. K., Karl, T. R. (2001) in Climate Change 2001: The Scientific Basis, eds. Houghton, J., Ding, Y., Griggs, M., Noguer, M., van der Linden, P. & Dai, X. (Cambridge Univ. Press, Cambridge, U.K.), p. 881.
Climate, Infectious Disease and Human Health: An Interdisciplinary Perspective
- R R Colwell
- J A Patz
Colwell, R. R. & Patz, J. A. (1998) Climate,
Infectious Disease and Human Health: An Interdisciplinary Perspective (Am. Soc. Microbiol., Washington, DC).
- S Levitus
- J I Antonov
- T P Boyer
Levitus, S., Antonov, J. I. & Boyer, T. P. (2000)
Science 287, 2225-2229.
- M J Bouma
- H J Van Der Kaay
Bouma, M. J. & van der Kaay, H. J. (1994) Lancet
344, 1638-1639.
- J A Patz
- M A Mcgeehin
- S M Bernard
- K L Ebi
- P R Epstein
- A Grambsch
- D J Gubler
- P Reiter
- I Romieu
- J B Rose
Patz, J. A., McGeehin, M. A., Bernard, S. M., Ebi,
K. L., Epstein, P. R., Grambsch, A., Gubler, D. J.,
Reiter, P., Romieu, I., Rose, J. B., et al. (2000)
Environ. Health Perspect. 108, 367-376.
- J A Patz
- M Hulme
- C Rosenzweig
- T D Mitchell
- R A Goldberg
- A K Githeko
- S Lele
- A J Mcmichael
- D Le Sueur
Patz, J. A., Hulme, M., Rosenzweig, C., Mitchell,
T. D., Goldberg, R. A., Githeko, A. K., Lele, S.,
McMichael, A. J. & Le Sueur, D. (2002) Nature, in
press.
- E Lindgren
- R Gustafson
Lindgren, E. & Gustafson, R. (2001) Lancet 358,
16–18.
- G Madico
- J Mcdonald
- R H Gilman
- L Cabrera
- C R Sterling
Madico, G., McDonald, J., Gilman, R. H.,
Cabrera, L. & Sterling, C. R. (1997) Clin. Infect.
Dis. 24, 977–981.
- D R Easterling
- B Horton
- P D Jones
- T C Peterson
- T R Karl
- D E Parker
- M J Salinger
- V Razuvayev
- N Plummer
- P Jamason
- Folland
Easterling, D. R., Horton, B., Jones, P. D., Peterson, T. C., Karl, T. R., Parker, D. E., Salinger,
M. J., Razuvayev, V., Plummer, N., Jamason, P. &
Folland, C. K. (1997) Science 277, 364–367.
- M Bouma
- H Van Der Kaay
Bouma, M. & van der Kaay, H. (1996) Trop. Med.
Int. Health 1, 86-96.
- J A Patz
- D Engelberg
- J Last
Patz, J. A., Engelberg, D. & Last, J. (2000) Annu.
Rev. Public Health 21, 271-307.
- R R Colwell
Colwell, R. R. (1996) Science 274, 2025-2031.
- E K Lipp
- J B Rose
Lipp, E. K. & Rose, J. B. (1997) Rev. Sci. Tech. 16,
620-640.
- S E Randolph
Randolph, S. E. (2001) Philos. Trans. R. Soc.
London B 356, 1045-1056.
- R S Kovats
- D H Campbell-Lendrum
- A J Mcmichael
- A Woodward
- Cox
Kovats, R. S., Campbell-Lendrum, D. H., McMichael, A. J., Woodward, A. & Cox, J. S.
(2001) Philos. Trans. R. Soc. London B 356,
1057-1068.
- K J Linthicum
- A Anyamba
- C J Tucker
- P W Kelley
- M F Myers
- C J Peters
Linthicum, K. J., Anyamba, A., Tucker, C. J.,
Kelley, P. W., Myers, M. F. & Peters, C. J. (1999)
Science 285, 397-400.
Intergovernmental Panel on Climate Change (2001) in Climate Change 2001: Impacts, Adaptation and Vulnerability
- Acad
- Sci
- Usa
Acad. Sci. USA 97, 1438-1443.
19. Intergovernmental Panel on Climate Change (2001)
in Climate Change 2001: Impacts, Adaptation and
Vulnerability, eds. Canziani, O. & McCarthy, J.
(Cambridge Univ. Press, Cambridge, U.K.).
- K K Kumar
- B Rajagopalan
- M A Cane
Kumar, K. K., Rajagopalan, B. & Cane, M. A.
(1999) Science 284, 2156-2159.
- M Pascual
- X Rodo
- S P Ellner
- R Colwell
- M J Bouma
Pascual, M., Rodo, X., Ellner, S. P., Colwell, R. &
Bouma, M. J. (2000) Science 289, 1766-1769.
- Kovats
- Checkley
Infectious Disease and Human Health: An Interdisciplinary Perspective
- J A Patz R R Colwell
- Climate
- Colwell R R