Stresman, Gillian and Sepúlveda, Nuno and Fornace, Kimberly and Grignard, Lynn and Mwesigwa, Julia and Achan, Jane and Miller, John and Bridges, Daniel J. and Eisele, Thomas P. and Mosha, Jacklin and Lorenzo, Pauline Joy and Macalinao, Maria Lourdes and Espino, Fe Esperanza and Tadesse, Fitsum and Stevenson, Jennifer C. and Quispe, Antonio M. and Siqueira, André and Lacerda, Marcus and Yeung, Shunmay and Sovannaroth, Siv and Pothin, Emilie and Gallay, Joanna and Hamre, Karen E. and Young, Alyssa and Lemoine, Jean Frantz and Chang, Michelle A. and Phommasone, Koukeo and Mayxay, Mayfong and Landier, Jordi and Parker, Daniel M. and Von Seidlein, Lorenz and Nosten, Francois and Delmas, Gilles and Dondorp, Arjen and Cameron, Ewan and Battle, Katherine and Bousema, Teun and Gething, Peter and D'Alessandro, Umberto and Drakeley, Chris.
(2020)
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, 20 (8).
pp. 953-963.
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Official URL: https://edoc.unibas.ch/78507/
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Abstract
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.; 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.; 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.; 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.; Wellcome Trust.
Faculties and Departments: | 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Former Units within Swiss TPH > Clinical Epidemiology (Genton) 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Former Units within Swiss TPH > Infectious Disease Modelling > Epidemiology and Transmission Dynamics (Smith) |
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UniBasel Contributors: | Pothin, Emilie and Gallay, Joanna |
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Item Type: | Article, refereed |
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Article Subtype: | Research Article |
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ISSN: | 1473-3099 |
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Note: | Publication type according to Uni Basel Research Database: Journal article |
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Language: | English |
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Identification Number: | |
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edoc DOI: | |
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Last Modified: | 19 Dec 2022 08:03 |
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Deposited On: | 19 Dec 2022 08:03 |
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