Abstract
Despite the recent malaria burden reduction in the Americas, focal transmission persists across the Amazon Basin. Timely analysis of surveillance data is crucial to characterize high-risk individuals and households for better targeting of regional elimination efforts. Here we analyzed 5,480 records of laboratory-confirmed clinical malaria episodes combined with demographic and socioeconomic information to identify risk factors for elevated malaria incidence in Mâncio Lima, the main urban transmission hotspot of Brazil. Overdispersed malaria count data clustered into households were fitted with random-effects zero-inflated negative binomial regression models. Random-effect predictors were used to characterize the spatial heterogeneity in malaria risk at the household level. Adult males were identified as the population stratum at greatest risk, likely due to increased occupational exposure away of the town. However, poor housing and residence in the less urbanized periphery of the town were also found to be key predictors of malaria risk, consistent with a substantial local transmission. Two thirds of the 8,878 urban residents remained uninfected after 23,975 person-years of follow-up. Importantly, we estimated that nearly 14% of them, mostly children and older adults living in the central urban hub, were free of malaria risk, being either unexposed, naturally unsusceptible, or immune to infection. We conclude that statistical modeling of routinely collected, but often neglected, malaria surveillance data can be explored to characterize drivers of transmission heterogeneity at the community level and provide evidence for the rational deployment of control interventions.
Highlights
Malaria continues to be a major cause of morbidity and mortality in sub-Saharan Africa, South and Southeast Asia, Oceania, and Latin America, with 219 million cases and 435,000 deaths worldwide in 2017 [1]
The study comprised 8,878 subjects with ages ranging between
Plasmodium vivax accounted for 84.2% of the episodes; 14.4% of the infections were due to P. falciparum, and 1.4% due to both species
Summary
Malaria continues to be a major cause of morbidity and mortality in sub-Saharan Africa, South and Southeast Asia, Oceania, and Latin America, with 219 million cases and 435,000 deaths worldwide in 2017 [1]. The disease typically affects the rural poor, since urbanization tends to reduce malaria risk through improved housing, greater access to health services, and environmental changes that may limit vector abundance [2]. Statistical modeling of urban malaria risk (grant 2016/18740-9), and by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, (https://www.niaid.nih.gov/), United States of America (grant U19 AI089681). RMC receives a doctoral fellowship from the Conselho Nacional de Desenvolvimento Cientıfico e Tecnologico (CNPq; http://cnpq.br/), which provides senior research scholarships to GAP and MUF. FAPESP (2018/18557-5) provides a doctoral fellowship to AP. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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