Publication: 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
Issued Date
2020-08-01
Resource Type
ISSN
14744457
14733099
14733099
Other identifier(s)
2-s2.0-85088640560
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Mahidol University
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SCOPUS
Bibliographic Citation
The Lancet Infectious Diseases. Vol.20, No.8 (2020), 953-963
Suggested Citation
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 Sovannaroth, Emilie 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 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. The Lancet Infectious Diseases. Vol.20, No.8 (2020), 953-963. doi:10.1016/S1473-3099(20)30059-1 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/58054
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Title
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
Author(s)
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 Sovannaroth
Emilie 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
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 Sovannaroth
Emilie 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
Other Contributor(s)
Institute for Disease Modeling
Perth Children's Hospital
Clinton Health Access Initiative, Inc.
Universidad Continental, Huancayo
Sciences Economiques et Sociales de la Santé et Traitement de l'Information Médicale
CDC Foundation
Universidade de Lisboa
Zambian Ministry of Health
National Institute for Medical Research Tanga
Gokila
Shoklo Malaria Research Unit
London School of Hygiene & Tropical Medicine
Curtin University
Fundacao Oswaldo Cruz
Universitat Basel
Centers for Disease Control and Prevention
Tulane University School of Public Health and Tropical Medicine
Mahosot Hospital, Lao
Universiteit Antwerpen
Mahidol University
Nuffield Department of Medicine
University of California, Irvine
Johns Hopkins Bloomberg School of Public Health
Radboud University Nijmegen Medical Centre
Universidade do Estado do Amazonas
Instituto Elimina
University of Health Sciences
Fundação de Medicina Tropical Dr. Heitor Vieira Dourado
Ministère de la Santé Publique et de la Population
National Center for Parasitology, Entomology and Malaria Control
Macha Research Trust
Perth Children's Hospital
Clinton Health Access Initiative, Inc.
Universidad Continental, Huancayo
Sciences Economiques et Sociales de la Santé et Traitement de l'Information Médicale
CDC Foundation
Universidade de Lisboa
Zambian Ministry of Health
National Institute for Medical Research Tanga
Gokila
Shoklo Malaria Research Unit
London School of Hygiene & Tropical Medicine
Curtin University
Fundacao Oswaldo Cruz
Universitat Basel
Centers for Disease Control and Prevention
Tulane University School of Public Health and Tropical Medicine
Mahosot Hospital, Lao
Universiteit Antwerpen
Mahidol University
Nuffield Department of Medicine
University of California, Irvine
Johns Hopkins Bloomberg School of Public Health
Radboud University Nijmegen Medical Centre
Universidade do Estado do Amazonas
Instituto Elimina
University of Health Sciences
Fundação de Medicina Tropical Dr. Heitor Vieira Dourado
Ministère de la Santé Publique et de la Population
National Center for Parasitology, Entomology and Malaria Control
Macha Research Trust
Abstract
© 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license 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.