A multi-level spatial analysis of clinical malaria and subclinical Plasmodium infections in Pailin Province, Cambodia
Parker, Daniel M.
Peto, Thomas J.
von Seidlein, Lorenz
White, Nicholas J.
Dondorp, Arjen M.Note: Order does not necessarily reflect citation order of authors.
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CitationParker, D. M., R. Tripura, T. J. Peto, R. J. Maude, C. Nguon, J. Chalk, P. Sirithiranont, et al. 2017. “A multi-level spatial analysis of clinical malaria and subclinical Plasmodium infections in Pailin Province, Cambodia.” Heliyon 3 (11): e00447. doi:10.1016/j.heliyon.2017.e00447. http://dx.doi.org/10.1016/j.heliyon.2017.e00447.
AbstractBackground: The malaria burden is decreasing throughout the Greater Mekong Subregion, however transmission persists in some areas. Human movement, subclinical infections and complicated transmission patterns contribute to the persistence of malaria. This research describes the micro-geographical epidemiology of both clinical malaria and subclinical Plasmodium infections in three villages in Western Cambodia. Methods: Three villages in Western Cambodia were selected for the study based on high reported Plasmodium falciparum incidence. A census was conducted at the beginning of the study, including demographic information and travel history. The total population was 1766. Cross-sectional surveys were conducted every three months from June 2013 to June 2014. Plasmodium infections were detected using an ultra-sensitive, high-volume, quantitative polymerase chain reaction (uPCR) technique. Clinical episodes were recorded by village health workers. The geographic coordinates (latitude and longitude) were collected for all houses and all participants were linked to their respective houses using a demographic surveillance system. Written informed consent was obtained from all participants. Results: Most clinical episodes and subclinical infections occurred within a single study village. Clinical Plasmodium vivax episodes clustered spatially in each village but only lasted for a month. In one study village subclinical infections clustered in geographic proximity to clusters of clinical episodes. The largest risk factor for clinical P. falciparum episodes was living in a house where another clinical P. falciparum episode occurred (model adjusted odds ratio (AOR): 6.9; CI: 2.3–19. 8). Subclinical infections of both P. vivax and P. falciparum were associated with clinical episodes of the same species (AOR: 5.8; CI: 1.5–19.7 for P. falciparum and AOR: 14.6; CI: 8.6–25.2 for P. vivax) and self-reported overnight visits to forested areas (AOR = 3.8; CI: 1.8–7. 7 for P. falciparum and AOR = 2.9; CI: 1.7–4.8 for P. vivax). Discussion Spatial clustering within the villages was transient, making the prediction of spatial clusters difficult. Interventions that are dependent on predicting spatial clusters (such as reactive case detection) would only have detected a small proportion of cases unless the entire village was screened within a limited time frame and with a highly sensitive diagnostic test. Subclinical infections may be acquired outside of the village (particularly in forested areas) and may play an important role in transmission.
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