Abstract
Malaria hotspots, defined as areas where transmission intensity exceeds the average level, become more pronounced as transmission declines. Targeting hotspots may accelerate reductions in transmission and could be pivotal for malaria elimination. Determinants of hotspot location, particularly of their movement, are poorly understood. We used spatial statistical methods to identify foci of incidence of self-reported malaria in a large census population of 64,000 people, in 8,290 compounds over a 2.5-year study period. Regression models examine stability of hotspots and identify static and dynamic correlates with their location. Hotspot location changed over short time-periods, rarely recurring in the same area. Hotspots identified in spring versus fall season differed in their stability. Households located in a hotspot in the fall were more likely to be located in a hotspot the following fall (RR = 1.77, 95% CI: 1.66–1.89), but the opposite was true for compounds in spring hotspots (RR = 0.15, 95% CI: 0.08–0.28). Location within a hotspot was related to environmental and static household characteristics such as distance to roads or rivers. Human migration into a household was correlated with risk of hotspot membership, but the direction of the association differed based on the origin of the migration event.
Highlights
A hotspot of malaria transmission is defined as ‘a geographical area within an endemic focus of malaria transmission where transmission intensity exceeds the average level’[1]
In the total population sample, we found that there was dependence between the outcome and the probability of missing household characteristics, when we adjusted regressions using IPW, we found no meaningful change in parameter estimates in the magnitude or direction of effect
We found significant lagged effects of hotspot membership which were modified by timing of the current interval
Summary
A hotspot of malaria transmission is defined as ‘a geographical area within an endemic focus of malaria transmission where transmission intensity exceeds the average level’[1]. Hotspots have been postulated to act as reservoirs of residual transmission in areas with otherwise effective control measures and may ‘fuel’ continual transmission within a larger area. If this is true, interventions directed at hotspots could reduce transmission outside of the targeted area. Hotspots identified in longitudinal cohort studies can be stable, usually related to fixed environmental risk factors, or may move from year to year and season to season[5,9,10,12,14,15,16,17,18]. Using data from a large, population based cohort in western Kenya, we first determine hotspot location, quantify the spatial and temporal stability of malaria hotspots and identify both static and dynamic correlates of hotspot location
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