Epidemiology of Plasmodium falciparum Infections in a Semi-Arid Rural African Setting: Evidence from Reactive Case Detection in Northwestern Kenya

Abstract

In northwestern Kenya, Turkana County has been historically considered unsuitable for stable malaria transmission because of its unfavorable climate and predominantly semi-nomadic population; consequently, it is overlooked during malaria control planning. However, the area is changing, with substantial development, an upsurge in travel associated with resource extraction, and more populated settlements forming. Recently, numerous malaria outbreaks have highlighted the need to characterize malaria transmission and its associated risk factors in the region to inform control strategies. Reactive case detection of confirmed malaria cases at six health facilities across central Turkana was conducted from 2018 to 2019. Infections in household members of index cases were detected by malaria rapid diagnostic tests (RDTs) and PCR tests, and they were grouped according household and individual characteristics. The relationships between putative risk factors and infection were quantified by multilevel logistic regression models. Of the 3,189 household members analyzed, 33.6% had positive RDT results and/or PCR test results. RDT-detected infections were more prevalent in children; however, PCR-detected infections were similarly prevalent across age groups. Recent travel was rarely reported and not significantly associated with infection. Bed net coverage was low and net crowding was associated with increased risks of household infections. Infections were present year-round, and fluctuations in prevalence were not associated with rainfall. These findings indicate year-round, endemic transmission with moderate population immunity. This is in stark contrast to recent estimates in this area. Therefore, further investigations to design effective intervention approaches to address malaria in this rapidly changing region and other similar settings across the Horn of Africa are warranted.

Figure 1.

The study area, enrollment, and positivity for household members based on the results of rapid diagnostic test (RDTs) and/or PCR tests. (A) The study was performed in central Turkana, which is a county in northwestern Kenya. Index patients from health facilities and their households were enrolled (Map data from Google Earth, Maxar, CNES/Airbus, and Landsat/Copernicus). (B) Spatial distribution of the proportion of household members with positive results for malaria according to RDTs or PCR tests (*household members who were inaccessible for mapping because of seasonal flooding). (C) The percent of household members with positive results for malaria according to RDTs or PCR tests are compared for each month and based on the total monthly rainfall (mm).

Figure 2.

Plasmodium falciparum infections in index patients and household members. (A) Parasite density distributions of index patients and household members with infections detectable by rapid diagnostic tests (RDTs) or PCR tests alone. Vertical line indicates the mean parasite density for each group. The proportion of household members was stratified by different test outcomes for age (B) and urban and rural catchment areas (C).