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Geospatial joint modeling of vector and parasite serology to microstratify malaria transmission

Proc Natl Acad Sci U S A. 2024-06; 
Ellen A Kearney, Punam Amratia, Su Yun Kang, Paul A Agius, Kefyalew Addis Alene, Katherine O'Flaherty, Win Han Oo, Julia C Cutts, Win Htike, Daniela Da Silva Goncalves, Zahra Razook, Alyssa E Barry, Damien Drew, Aung Thi, Kyaw Zayar Aung, Htin Kyaw Thu, Myat Mon Thein, Nyi Nyi Zaw, Wai Yan Min Htay, Aung Paing Soe, James G Beeson, Julie A Simpson, Peter W Gething, Ewan Cameron, Freya J I Fowkes
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Abstract

The World Health Organization identifies a strong surveillance system for malaria and its mosquito vector as an essential pillar of the malaria elimination agenda. salivary antibodies are emerging biomarkers of exposure to mosquito bites that potentially overcome sensitivity and logistical constraints of traditional entomological surveys. Using samples collected by a village health volunteer network in 104 villages in Southeast Myanmar during routine surveillance, the present study employs a Bayesian geostatistical modeling framework, incorporating climatic and environmental variables together with salivary antigen serology, to generate spatially continuous predictive maps of biting exposure. Our maps quanti... More

Keywords

Anopheles salivary antibodies, disease mapping, geospatial, malaria