Association between the proportion of Plasmodium falciparum and Plasmodium vivax infections detected by passive surveillance and the magnitude of the asymptomatic reservoir in the community: a pooled analysis of paired health facility and community data

Gillian Stresman, Nuno Sepúlveda, Kimberly Fornace, Lynn Grignard, Julia Mwesigwa, Jane Achan, John Miller, Daniel J. Bridges, Thomas P. Eisele, Jacklin Mosha, Pauline Joy Lorenzo, Maria Lourdes Macalinao, Fe Esperanza Espino, Fitsum Tadesse, Jennifer C. Stevenson, Antonio M. Quispe, André Siqueira, Marcus Lacerda, Shunmay Yeung, Siv SovannarothEmilie Pothin, Joanna Gallay, Karen E. Hamre, Alyssa Young, Jean Frantz Lemoine, Michelle A. Chang, Koukeo Phommasone, Mayfong Mayxay, Jordi Landier, Daniel M. Parker, Lorenz Von Seidlein, Francois Nosten, Gilles Delmas, Arjen Dondorp, Ewan Cameron, Katherine Battle, Teun Bousema, Peter Gething, Umberto D'Alessandro, Chris Drakeley

Resultado de la investigación: Artículo CientíficoArtículo originalrevisión exhaustiva

9 Citas (Scopus)

Resumen

Background: Passively collected malaria case data are the foundation for public health decision making. However, because of population-level immunity, infections might not always be sufficiently symptomatic to prompt individuals to seek care. Understanding the proportion of all Plasmodium spp infections expected to be detected by the health system becomes particularly paramount in elimination settings. The aim of this study was to determine the association between the proportion of infections detected and transmission intensity for Plasmodium falciparum and Plasmodium vivax in several global endemic settings. Methods: The proportion of infections detected in routine malaria data, P(Detect), was derived from paired household cross-sectional survey and routinely collected malaria data within health facilities. P(Detect) was estimated using a Bayesian model in 431 clusters spanning the Americas, Africa, and Asia. The association between P(Detect) and malaria prevalence was assessed using log-linear regression models. Changes in P(Detect) over time were evaluated using data from 13 timepoints over 2 years from The Gambia. Findings: The median estimated P(Detect) across all clusters was 12·5% (IQR 5·3–25·0) for P falciparum and 10·1% (5·0–18·3) for P vivax and decreased as the estimated log-PCR community prevalence increased (adjusted odds ratio [OR] for P falciparum 0·63, 95% CI 0·57–0·69; adjusted OR for P vivax 0·52, 0·47–0·57). Factors associated with increasing P(Detect) included smaller catchment population size, high transmission season, improved care-seeking behaviour by infected individuals, and recent increases (within the previous year) in transmission intensity. Interpretation: The proportion of all infections detected within health systems increases once transmission intensity is sufficiently low. The likely explanation for P falciparum is that reduced exposure to infection leads to lower levels of protective immunity in the population, increasing the likelihood that infected individuals will become symptomatic and seek care. These factors might also be true for P vivax but a better understanding of the transmission biology is needed to attribute likely reasons for the observed trend. In low transmission and pre-elimination settings, enhancing access to care and improvements in care-seeking behaviour of infected individuals will lead to an increased proportion of infections detected in the community and might contribute to accelerating the interruption of transmission. Funding: Wellcome Trust.

Idioma originalInglés estadounidense
Páginas (desde-hasta)953-963
-11
PublicaciónThe Lancet Infectious Diseases
Volumen20
N.º8
DOI
EstadoIndizado - ago. 2020

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Publisher Copyright:
© 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license

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