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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Statistical modeling of surveillance data to identify correlates of urban malaria risk: A population-based study in the Amazon Basin

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Author(s):
Corder, Rodrigo M. [1] ; Paula, Gilberto A. [2] ; Pincelli, Anaclara [1] ; Ferreira, Marcelo U. [1]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, Inst Biomed Sci, Dept Parasitol, Sao Paulo - Brazil
[2] Univ Sao Paulo, Inst Math & Stat, Dept Stat, Sao Paulo - Brazil
Total Affiliations: 2
Document type: Journal article
Source: PLoS One; v. 14, n. 8 AUG 9 2019.
Web of Science Citations: 0
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 Mancio 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. (AU)

FAPESP's process: 16/18740-9 - Scientific bases for residual malaria elimination in the Brazilian Amazon
Grantee:Marcelo Urbano Ferreira
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 18/18557-5 - Maternal IgG antibodies and protection against clinical Vivax Malaria in the first year of life
Grantee:Anaclara Pincelli Cintra
Support Opportunities: Scholarships in Brazil - Doctorate