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Estimating Plasmodium falciparum Transmission Rates in Low-Endemic Settings Using a Combination of Community Prevalence and Health Facility Data
As some malaria control programs shift focus from disease control to transmission reduction, there is a need for transmission data to monitor progress. At lower levels of transmission, it becomes increasingly more difficult to measure precisely, for example through entomological studies. Many progra...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3425560/ https://www.ncbi.nlm.nih.gov/pubmed/22936995 http://dx.doi.org/10.1371/journal.pone.0042861 |
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author | Yukich, Joshua Briët, Olivier Bretscher, Michael T. Bennett, Adam Lemma, Seblewengel Berhane, Yemane Eisele, Thomas P. Keating, Joseph Smith, Thomas |
author_facet | Yukich, Joshua Briët, Olivier Bretscher, Michael T. Bennett, Adam Lemma, Seblewengel Berhane, Yemane Eisele, Thomas P. Keating, Joseph Smith, Thomas |
author_sort | Yukich, Joshua |
collection | PubMed |
description | As some malaria control programs shift focus from disease control to transmission reduction, there is a need for transmission data to monitor progress. At lower levels of transmission, it becomes increasingly more difficult to measure precisely, for example through entomological studies. Many programs conduct regular cross sectional parasite prevalence surveys, and have access to malaria treatment data routinely collected by ministries of health, often in health management information systems. However, by themselves, these data are poor measures of transmission. In this paper, we propose an approach for combining annual parasite incidence and treatment data with cross-sectional parasite prevalence and treatment seeking survey data to estimate the incidence of new infections in the human population, also known as the force of infection. The approach is based on extension of a reversible catalytic model. The accuracy of the estimates from this model appears to be highly dependent on levels of detectability and treatment in the community, indicating the importance of information on private sector treatment seeking and access to effective and appropriate treatment. |
format | Online Article Text |
id | pubmed-3425560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34255602012-08-30 Estimating Plasmodium falciparum Transmission Rates in Low-Endemic Settings Using a Combination of Community Prevalence and Health Facility Data Yukich, Joshua Briët, Olivier Bretscher, Michael T. Bennett, Adam Lemma, Seblewengel Berhane, Yemane Eisele, Thomas P. Keating, Joseph Smith, Thomas PLoS One Research Article As some malaria control programs shift focus from disease control to transmission reduction, there is a need for transmission data to monitor progress. At lower levels of transmission, it becomes increasingly more difficult to measure precisely, for example through entomological studies. Many programs conduct regular cross sectional parasite prevalence surveys, and have access to malaria treatment data routinely collected by ministries of health, often in health management information systems. However, by themselves, these data are poor measures of transmission. In this paper, we propose an approach for combining annual parasite incidence and treatment data with cross-sectional parasite prevalence and treatment seeking survey data to estimate the incidence of new infections in the human population, also known as the force of infection. The approach is based on extension of a reversible catalytic model. The accuracy of the estimates from this model appears to be highly dependent on levels of detectability and treatment in the community, indicating the importance of information on private sector treatment seeking and access to effective and appropriate treatment. Public Library of Science 2012-08-22 /pmc/articles/PMC3425560/ /pubmed/22936995 http://dx.doi.org/10.1371/journal.pone.0042861 Text en © 2012 Yukich et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Yukich, Joshua Briët, Olivier Bretscher, Michael T. Bennett, Adam Lemma, Seblewengel Berhane, Yemane Eisele, Thomas P. Keating, Joseph Smith, Thomas Estimating Plasmodium falciparum Transmission Rates in Low-Endemic Settings Using a Combination of Community Prevalence and Health Facility Data |
title | Estimating Plasmodium falciparum Transmission Rates in Low-Endemic Settings Using a Combination of Community Prevalence and Health Facility Data |
title_full | Estimating Plasmodium falciparum Transmission Rates in Low-Endemic Settings Using a Combination of Community Prevalence and Health Facility Data |
title_fullStr | Estimating Plasmodium falciparum Transmission Rates in Low-Endemic Settings Using a Combination of Community Prevalence and Health Facility Data |
title_full_unstemmed | Estimating Plasmodium falciparum Transmission Rates in Low-Endemic Settings Using a Combination of Community Prevalence and Health Facility Data |
title_short | Estimating Plasmodium falciparum Transmission Rates in Low-Endemic Settings Using a Combination of Community Prevalence and Health Facility Data |
title_sort | estimating plasmodium falciparum transmission rates in low-endemic settings using a combination of community prevalence and health facility data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3425560/ https://www.ncbi.nlm.nih.gov/pubmed/22936995 http://dx.doi.org/10.1371/journal.pone.0042861 |
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