Households or Hotspots? Defining Intervention Targets for Malaria Elimination in Ratanakiri Province, Eastern Cambodia

被引:8
作者
Bannister-Tyrrell, Melanie [1 ]
Krit, Meryam [1 ]
Sluydts, Vincent [1 ,2 ]
Tho, Sochantha [3 ]
Sokny, Mao [3 ]
Mean, Vanna [4 ]
Kim, Saorin [5 ]
Menard, Didier [5 ]
Grietens, Koen Peeters [1 ]
Abrams, Steven [2 ,6 ]
Hens, Niel [2 ,6 ]
Coosemans, Marc [1 ]
Bassat, Quique [7 ,8 ,9 ]
van Hensbroek, Michael Boele [10 ,11 ]
Durnez, Lies [1 ,2 ]
Van Bortel, Wim [1 ]
机构
[1] Inst Trop Med, Natl Str 155, B-2000 Antwerp, Belgium
[2] Univ Antwerp, Antwerp, Belgium
[3] Natl Ctr Parasitol Entomol & Malaria Control, Phnom Penh, Cambodia
[4] Ratanakiri Prov Hlth Dept, Banlung, Cambodia
[5] Pasteur Inst, Phnom Penh, Cambodia
[6] Univ Hasselt, Hasselt, Belgium
[7] Univ Barcelona, Hosp Clinic, ISGlobal, Barcelona, Spain
[8] Ctr Invest Saude Manh, Maputo, Mozambique
[9] Catalan Inst Res & Adv Studies, Barcelona, Spain
[10] Acad Med Ctr, Amsterdam, Netherlands
[11] Amsterdam Inst Global Hlth & Dev, Amsterdam, Netherlands
关键词
malaria; hotspot; malaria elimination; Greater Mekong Subregion; epidemiology; EPIDEMIOLOGY; TRANSMISSION; PARASITEMIA; INFECTIONS; STRATEGIES; RISK;
D O I
10.1093/infdis/jiz211
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
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.
引用
收藏
页码:1034 / 1043
页数:10
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