Spatio-temporal variation of malaria hotspots in central Senegal, 2008-2012

Abstract

Background In malaria endemic areas, identifying spatio-temporal hotspots is becoming an important element of innovative control strategies targeting transmission bottlenecks. The aim of this work was to describe the spatio-temporal variation of malaria hotspots in central Senegal, and to identify the meteorological, environmental, and preventive factors that influence this variation. Methods The weekly incidence of malaria cases recorded from 2008 to 2012 in 575 villages of central Senegal (total population 523,908) during a trial of Seasonal Malaria Chemoprevention (SMC), were analysed. Data on weekly rainfall and annual vegetation types were obtained for each village from remote sensing data. The time series of weekly cumulative malaria incidence for the entire study area was divided into periods of high and low transmission using change-point analysis. Malaria hotspots were detected for each period with the SaTScan method. The effects of rainfall, vegetation type, and SMC intervention on the spatio-temporal variation of malaria hotspots were assessed using a General Additive Mixed Model. Results The cumulative malaria incidence rate for the entire area ranged from 0 to 115.34 cases/100,000 person weeks during the study period. During high transmission periods, the cumulative malaria incidence rate varied between 7.53 and 38.1 cases/100,000 person-weeks, and the number of hotspot villages varied between 62 and 147. During low transmission periods, the cumulative malaria incidence rate varied between 0.83 and 2.73 cases/100,000 person-weeks, and the number of hotspot villages varied between 10 and 43. Villages with SMC were less likely to be hotspots (OR=0.48, IC95%: 0.33-0.68). According to the spatial interpolation, 2 zones located in the south of the study area had the highest risk of being a hotspot (ORmin=1.90, 95%CI: 1.02-3.56; ORmax=60.65, 95%CI: 26.86-136.95). The association between rainfall and hotspot status was non-linear and depended on vegetation type and the amount of rainfall. Conclusion In our study, malaria hotspots varied over space and time according to a combination of meteorological, environmental, and preventive factors. Our analysis shows also the importance of adapting control strategies to the local context and dynamic patterns. Moreover, the issue of spatial hotspots and foci of malaria persistence during LTPs needs to be further addressed.

Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering

“…An alternative could be the importation of diverse genotypes due to human or mosquito mobility 21,[27][28][29][30] . A similar study of malaria incidence and prevalence has demonstrated the existence of malaria transmission hotspots at the village level in Senegal 7,8 . In such villages, human density, human behavior, lax malaria bed-net use, substandard housing construction, and a favorable ecological environment for mosquito proliferation (presence of mosquito breeding sites) have all been identified as risk factors for a household to be in a hotspot 31 .…”

“…Targeting and eliminating malaria hotspots can play an important role in malaria elimination 3,6 . Different studies using conventional malaria epidemiologic tools such as malaria incidence and prevalence rates, malaria morbidity and mortality rates, and entomological inoculation rates (EIR) have identified hotspots of malaria transmission; however, some of these metrics are better suited for more highly endemic regions [7][8][9] and may become less useful as malaria transmission declines. As some regions strive for malaria elimination, along with the decline of the disease incidence some of these conventional malaria metrics may become less informative 10 .…”