Distinct parasite populations infect individuals identified through passive and active case detection in a region of declining malaria transmission in southern Zambia

Abstract

BackgroundSubstantial reductions in the burden of malaria have been documented in parts of sub-Saharan Africa, with elimination strategies and goals being formulated in some regions. Within this context, understanding the epidemiology of low-level malaria transmission is crucial to achieving and sustaining elimination. A 24 single-nucleotide-polymorphism Plasmodium falciparum molecular barcode was used to characterize parasite populations from infected individuals identified through passive and active case detection in an area approaching malaria elimination in southern Zambia.MethodsThe study was conducted in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia, where the parasite prevalence declined over the past decade, from 9.2% in 2008 to less than 1% in 2013. Parasite haplotypes from actively detected, P. falciparum-infected participants enrolled in a serial cross-sectional, community-based cohort study from 2008 to 2013 and from passively detected, P. falciparum-infected individuals enrolled at five rural health centres from 2012 to 2015 were compared. Changes in P. falciparum genetic relatedness, diversity and complexity were analysed as malaria transmission declined.ResultsActively detected cases identified in the community were most commonly rapid diagnostic test negative, asymptomatic and had submicroscopic parasitaemia. Phylogenetic reconstruction using concatenated 24 SNP barcode revealed a separation of parasite haplotypes from passively and actively detected infections, consistent with two genetically distinct parasite populations. For passively detected infections identified at health centres, the proportion of detectable polyclonal infections was consistently low in all seasons, in contrast with actively detected infections in which the proportion of polyclonal infections was high. The mean genetic divergence for passively detected infections was 34.5% for the 2012–2013 transmission season, 37.8% for the 2013–2014 season, and 30.8% for the 2014–2015 season. The mean genetic divergence for actively detected infections was 22.3% in the 2008 season and 29.0% in the 2008–2009 season and 9.9% across the 2012–2014 seasons.ConclusionsDistinct parasite populations were identified among infected individuals identified through active and passive surveillance, suggesting that infected individuals detected through active surveillance may not have contributed substantially to ongoing transmission. As parasite prevalence and diversity within these individuals declined, resource-intensive efforts to identify the chronically infected reservoir may not be necessary to eliminate malaria in this setting.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-017-1810-3) contains supplementary material, which is available to authorized users.

The use of spatial and genetic tools to assess Plasmodium falciparum transmission in Lusaka, Zambia between 2011 and 2015

“…Infections were classified as polyclonal using a cutoff of ≥ 4 loci with a mixed infection call [33,50,51]. Genetic relatedness was calculated using a modified SNP π [52], which accounts for samples with missing…”

The geography of malaria elimination in Bangladesh: combining data layers to estimate the spatial spread of parasites

“…Our samples came from symptomatic patients who presented at a health facility, which would be the norm for routine reporting to the NMEP. We therefore did not include asymptomatic or subclinical infections, and it is unknown to what extent the parasite in symptomatic patients are representative of the entire parasite population in this area (35). Although we were able to enroll patients at 57 health facilities that covered a wide geographic area, these study sites represent 59% of all CHT health facilities which report data to the NMEP.…”

Improving the efficiency of reactive case detection for malaria elimination in southern Zambia: a cross-sectional study

“…Households were enrolled into the RCD study in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia between January 12, 2015 and July 26, 2017 [18,25,27,28]. The region has a tropical savannah climate with the rainy season occurring from December to April, followed by a cool dry season from May to August, and a hot dry season from September to November as previously described [18,22,15,26].…”

“…Samples were re-packed and stored at -20˚C until parasite DNA extraction was performed using the Chelex ® method [28,32]. qPCR was performed with the Applied Biosystems StepOnePlus™ Real-Time PCR System (Thermo Scientific, Waltham, MA, USA).…”