Measles hotspots and epidemiological connectivity
Penn State University, Biology Department and Center for Infectious Disease Dynamics, University Park, PA, USA.Epidemiology and Infection (Impact Factor: 2.54). 09/2010; 138(9):1308-16. DOI: 10.1017/S0950268809991385
Though largely controlled in developed countries, measles remains a major global public health issue. Regional and local transmission patterns are rooted in human mixing behaviour across spatial scales. Identifying spatial interactions that contribute to recurring epidemics helps define and predict outbreak patterns. Using spatially explicit reported cases from measles outbreaks in Niger, we explored how regional variations in movement and contact patterns relate to patterns of measles incidence. Because we expected to see lower rates of re-introductions in small, compared to large, populations, we measured the population-size corrected proportion of weeks with zero cases across districts to understand relative rates of measles re-introductions. We found that critical elements of spatial disease dynamics in Niger are agricultural seasonality, transnational contact clusters, and roads networks that facilitate host movement and connectivity. These results highlight the need to understand local patterns of seasonality, demographic characteristics, and spatial heterogeneities to inform vaccination policy.
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- "And HIV-infected children may have prolonged shedding of measles virus increasing the period of infectivity and the spread of measles virus to secondary contacts . Clustering of measles in both space and time has been identified at the country and regional levels in South Africa and Niger [6,22,23], but no studies have examined clustering in an urban setting of sub-Saharan Africa. Spatial-temporal clustering of measles was investigated during the 2010 outbreak in Lusaka, Zambia, and specifically whether HIV-infected children with measles were spatially clustered during the outbreak. "
ABSTRACT: Measles cases may cluster in densely populated urban centers in sub-Saharan Africa as susceptible individuals share spatially dependent risk factors and may cluster among human immunodeficiency virus (HIV)-infected children despite high vaccination coverage. Children hospitalized with measles at the University Teaching Hospital (UTH) in Lusaka, Zambia were enrolled in the study. The township of residence was recorded on the questionnaire and mapped; SaTScan software was used for cluster detection. A spatial-temporal scan statistic was used to investigate clustering of measles in children hospitalized during an endemic period (1998 to 2002) and during the 2010 measles outbreak in Lusaka, Zambia. Three sequential and spatially contiguous clusters of measles cases were identified during the 2010 outbreak but no clustering among HIV-infected children was identified. In contrast, a space-time cluster among HIV-infected children was identified during the endemic period. This cluster occurred prior to the introduction of intensive measles control efforts and during a period between seasonal peaks in measles incidence. Prediction and early identification of spatial clusters of measles will be critical to achieving measles elimination. HIV infection may contribute to spatial clustering of measles cases in some epidemiological settings.
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- "Within a GIS, layers of different spatial information can be input and overlaid to obtain geographically specific, disease-relevant outputs and combining these with mathematical models can yield importation-relevant measures, such as the number of imported infections per 1,000 of the population per year . Figure 5 illustrates an example of a P. falciparum malaria-relevant HPM analysis of cross-border HPM data between country A and country B (country A has relatively higher transmission than country B), based on models previously outlined [15,87,88]. Pre-defined geographical boundaries can be overlaid onto PfPR endemicity  and population distribution maps  to estimate population-weighted PfPR per location. "
ABSTRACT: Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.
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ABSTRACT: Seasonally driven cycles of incidence have been consistently observed for a range of directly transmitted pathogens. Though frequently observed, the mechanism of seasonality for directly transmitted human pathogens is rarely well understood. Despite significant annual variation in magnitude, measles outbreaks in Niger consistently begin in the dry season and decline at the onset of the seasonal rains. We estimate the seasonal fluctuation in measles transmission rates for the 38 districts and urban centres of Niger, from 11 years of weekly incidence reports. We show that transmission rates are consistently in anti-phase to the rainfall patterns across the country. The strength of the seasonal forcing of transmission is not correlated with the latitudinal rainfall gradient, as would be expected if transmission rates were determined purely by environmental conditions. Rather, seasonal forcing is correlated with the population size, with larger seasonal fluctuation in more populous, urban areas. This pattern is consistent with seasonal variation in human density and contact rates due to agricultural cycles. The stronger seasonality in large cities drives deep inter-epidemic troughs and results in frequent local extinction of measles, which contrasts starkly to the conventional observation that large cities, by virtue of their size, act as reservoirs of measles.