BACKGROUND: Variation in the risk of malaria within populations is a frequently described but poorly understood phenomenon. This heterogeneity creates opportunities for targeted interventions but only if hot spots of malaria transmission can be easily identified. METHODS: We determined spatial patterns in malaria transmission in a district in northeastern Tanzania, using malaria incidence data from a cohort study involving infants and household-level mosquito sampling data. The parasite prevalence rates and age-specific seroconversion rates (SCRs) of antibodies against Plasmodium falciparum antigens were determined in samples obtained from people attending health care facilities. RESULTS: Five clusters of higher malaria incidence were detected and interpreted as hot spots of transmission. These hot spots partially overlapped with clusters of higher mosquito exposure but could not be satisfactorily predicted by a probability model based on environmental factors. Small-scale local variation in malaria exposure was detected by parasite prevalence rates and SCR estimates for samples of health care facility attendees. SCR estimates were strongly associated with local malaria incidence rates and predicted hot spots of malaria transmission with 95% sensitivity and 85% specificity. CONCLUSIONS: Serological markers were able to detect spatial variation in malaria transmission at the microepidemiological level, and they have the potential to form an effective method for spatial targeting of malaria control efforts.
BACKGROUND: Variation in the risk of malaria within populations is a frequently described but poorly understood phenomenon. This heterogeneity creates opportunities for targeted interventions but only if hot spots of malaria transmission can be easily identified. METHODS: We determined spatial patterns in malaria transmission in a district in northeastern Tanzania, using malaria incidence data from a cohort study involving infants and household-level mosquito sampling data. The parasite prevalence rates and age-specific seroconversion rates (SCRs) of antibodies against Plasmodium falciparum antigens were determined in samples obtained from people attending health care facilities. RESULTS: Five clusters of higher malaria incidence were detected and interpreted as hot spots of transmission. These hot spots partially overlapped with clusters of higher mosquito exposure but could not be satisfactorily predicted by a probability model based on environmental factors. Small-scale local variation in malaria exposure was detected by parasite prevalence rates and SCR estimates for samples of health care facility attendees. SCR estimates were strongly associated with local malaria incidence rates and predicted hot spots of malaria transmission with 95% sensitivity and 85% specificity. CONCLUSIONS: Serological markers were able to detect spatial variation in malaria transmission at the microepidemiological level, and they have the potential to form an effective method for spatial targeting of malaria control efforts.
Authors: Molly Deutsch-Feldman; Harry Hamapumbu; Jailos Lubinda; Michael Musonda; Ben Katowa; Kelly M Searle; Tamaki Kobayashi; Timothy M Shields; Jennifer C Stevenson; Philip E Thuma; William J Moss Journal: Am J Trop Med Hyg Date: 2018-03-15 Impact factor: 2.345
Authors: Christian P Nixon; Christina E Nixon; Dian Sidik Arsyad; Krisin Chand; Frilasita A Yudhaputri; Wajiyo Sumarto; Suradi Wangsamuda; Puji B Asih; Sylvia S Marantina; Isra Wahid; Gang Han; Jennifer F Friedman; Michael J Bangs; Din Syafruddin; J Kevin Baird Journal: Pathog Glob Health Date: 2014-12-10 Impact factor: 2.894
Authors: Philip Bejon; Thomas N Williams; Anne Liljander; Abdisalan M Noor; Juliana Wambua; Edna Ogada; Ally Olotu; Faith H A Osier; Simon I Hay; Anna Färnert; Kevin Marsh Journal: PLoS Med Date: 2010-07-06 Impact factor: 11.069
Authors: Jamie T Griffin; T Deirdre Hollingsworth; Lucy C Okell; Thomas S Churcher; Michael White; Wes Hinsley; Teun Bousema; Chris J Drakeley; Neil M Ferguson; María-Gloria Basáñez; Azra C Ghani Journal: PLoS Med Date: 2010-08-10 Impact factor: 11.069