TY - JOUR
T1 - Households or hotspots? Defining intervention targets for malaria elimination in Ratanakiri Province, eastern Cambodia
AU - Bannister-Tyrrell, Melanie
AU - Krit, Meryam
AU - Sluydts, Vincent
AU - Tho, Sochantha
AU - Sokny, Mao
AU - Mean, Vanna
AU - Kim, Saorin
AU - Menard, Didier
AU - Grietens, Koen Peeters
AU - Abrams, Steven
AU - Hens, Niel
AU - Coosemans, Marc
AU - Bassat, Quique
AU - van Hensbroek, Michael Boele
AU - Durnez, Lies
AU - Van Bortel, Wim
N1 - FTX; (CC BY-NC-ND 4.0); © The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America.
PY - 2019
Y1 - 2019
N2 - Background: Malaria "hotspots" have been proposed as potential intervention units for targeted malaria elimination. Little is known about hotspot formation and stability in settings outside sub-Saharan Africa.Methods: Clustering of Plasmodium infections at the household and hotspot level was assessed over 2 years in 3 villages in eastern Cambodia. Social and spatial autocorrelation statistics were calculated to assess clustering of malaria risk, and logistic regression was used to assess the effect of living in a malaria hotspot compared to living in a malaria-positive household in the first year of the study on risk of malaria infection in the second year.Results: The crude prevalence of Plasmodium infection was 8.4% in 2016 and 3.6% in 2017. Living in a hotspot in 2016 did not predict Plasmodium risk at the individual or household level in 2017 overall, but living in a Plasmodium-positive household in 2016 strongly predicted living in a Plasmodium-positive household in 2017 (Risk Ratio, 5.00 [95% confidence interval, 2.09-11.96], P < .0001). There was no consistent evidence that malaria risk clustered in groups of socially connected individuals from different households.Conclusions: Malaria risk clustered more clearly in households than in hotspots over 2 years. Household-based strategies should be prioritized in malaria elimination programs in this region.
AB - Background: Malaria "hotspots" have been proposed as potential intervention units for targeted malaria elimination. Little is known about hotspot formation and stability in settings outside sub-Saharan Africa.Methods: Clustering of Plasmodium infections at the household and hotspot level was assessed over 2 years in 3 villages in eastern Cambodia. Social and spatial autocorrelation statistics were calculated to assess clustering of malaria risk, and logistic regression was used to assess the effect of living in a malaria hotspot compared to living in a malaria-positive household in the first year of the study on risk of malaria infection in the second year.Results: The crude prevalence of Plasmodium infection was 8.4% in 2016 and 3.6% in 2017. Living in a hotspot in 2016 did not predict Plasmodium risk at the individual or household level in 2017 overall, but living in a Plasmodium-positive household in 2016 strongly predicted living in a Plasmodium-positive household in 2017 (Risk Ratio, 5.00 [95% confidence interval, 2.09-11.96], P < .0001). There was no consistent evidence that malaria risk clustered in groups of socially connected individuals from different households.Conclusions: Malaria risk clustered more clearly in households than in hotspots over 2 years. Household-based strategies should be prioritized in malaria elimination programs in this region.
U2 - 10.1093/infdis/jiz211
DO - 10.1093/infdis/jiz211
M3 - A1: Web of Science-article
C2 - 31028393
SN - 0022-1899
VL - 220
SP - 1034
EP - 1043
JO - Journal of Infectious Diseases
JF - Journal of Infectious Diseases
IS - 6
ER -