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Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016

BACKGROUND: Reliable measures of disease burden over time are necessary to evaluate the impact of interventions and assess sub-national trends in the distribution of infection. Three Malaria Indicator Surveys (MISs) have been conducted in Madagascar since 2011. They provide a valuable resource to as...

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Autores principales: Kang, Su Yun, Battle, Katherine E., Gibson, Harry S., Ratsimbasoa, Arsène, Randrianarivelojosia, Milijaona, Ramboarina, Stéphanie, Zimmerman, Peter A., Weiss, Daniel J., Cameron, Ewan, Gething, Peter W., Howes, Rosalind E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5964908/
https://www.ncbi.nlm.nih.gov/pubmed/29788968
http://dx.doi.org/10.1186/s12916-018-1060-4
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author Kang, Su Yun
Battle, Katherine E.
Gibson, Harry S.
Ratsimbasoa, Arsène
Randrianarivelojosia, Milijaona
Ramboarina, Stéphanie
Zimmerman, Peter A.
Weiss, Daniel J.
Cameron, Ewan
Gething, Peter W.
Howes, Rosalind E.
author_facet Kang, Su Yun
Battle, Katherine E.
Gibson, Harry S.
Ratsimbasoa, Arsène
Randrianarivelojosia, Milijaona
Ramboarina, Stéphanie
Zimmerman, Peter A.
Weiss, Daniel J.
Cameron, Ewan
Gething, Peter W.
Howes, Rosalind E.
author_sort Kang, Su Yun
collection PubMed
description BACKGROUND: Reliable measures of disease burden over time are necessary to evaluate the impact of interventions and assess sub-national trends in the distribution of infection. Three Malaria Indicator Surveys (MISs) have been conducted in Madagascar since 2011. They provide a valuable resource to assess changes in burden that is complementary to the country’s routine case reporting system. METHODS: A Bayesian geostatistical spatio-temporal model was developed in an integrated nested Laplace approximation framework to map the prevalence of Plasmodium falciparum malaria infection among children from 6 to 59 months in age across Madagascar for 2011, 2013 and 2016 based on the MIS datasets. The model was informed by a suite of environmental and socio-demographic covariates known to influence infection prevalence. Spatio-temporal trends were quantified across the country. RESULTS: Despite a relatively small decrease between 2013 and 2016, the prevalence of malaria infection has increased substantially in all areas of Madagascar since 2011. In 2011, almost half (42.3%) of the country’s population lived in areas of very low malaria risk (<1% parasite prevalence), but by 2016, this had dropped to only 26.7% of the population. Meanwhile, the population in high transmission areas (prevalence >20%) increased from only 2.2% in 2011 to 9.2% in 2016. A comparison of the model-based estimates with the raw MIS results indicates there was an underestimation of the situation in 2016, since the raw figures likely associated with survey timings were delayed until after the peak transmission season. CONCLUSIONS: Malaria remains an important health problem in Madagascar. The monthly and annual prevalence maps developed here provide a way to evaluate the magnitude of change over time, taking into account variability in survey input data. These methods can contribute to monitoring sub-national trends of malaria prevalence in Madagascar as the country aims for geographically progressive elimination. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12916-018-1060-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-59649082018-05-24 Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016 Kang, Su Yun Battle, Katherine E. Gibson, Harry S. Ratsimbasoa, Arsène Randrianarivelojosia, Milijaona Ramboarina, Stéphanie Zimmerman, Peter A. Weiss, Daniel J. Cameron, Ewan Gething, Peter W. Howes, Rosalind E. BMC Med Research Article BACKGROUND: Reliable measures of disease burden over time are necessary to evaluate the impact of interventions and assess sub-national trends in the distribution of infection. Three Malaria Indicator Surveys (MISs) have been conducted in Madagascar since 2011. They provide a valuable resource to assess changes in burden that is complementary to the country’s routine case reporting system. METHODS: A Bayesian geostatistical spatio-temporal model was developed in an integrated nested Laplace approximation framework to map the prevalence of Plasmodium falciparum malaria infection among children from 6 to 59 months in age across Madagascar for 2011, 2013 and 2016 based on the MIS datasets. The model was informed by a suite of environmental and socio-demographic covariates known to influence infection prevalence. Spatio-temporal trends were quantified across the country. RESULTS: Despite a relatively small decrease between 2013 and 2016, the prevalence of malaria infection has increased substantially in all areas of Madagascar since 2011. In 2011, almost half (42.3%) of the country’s population lived in areas of very low malaria risk (<1% parasite prevalence), but by 2016, this had dropped to only 26.7% of the population. Meanwhile, the population in high transmission areas (prevalence >20%) increased from only 2.2% in 2011 to 9.2% in 2016. A comparison of the model-based estimates with the raw MIS results indicates there was an underestimation of the situation in 2016, since the raw figures likely associated with survey timings were delayed until after the peak transmission season. CONCLUSIONS: Malaria remains an important health problem in Madagascar. The monthly and annual prevalence maps developed here provide a way to evaluate the magnitude of change over time, taking into account variability in survey input data. These methods can contribute to monitoring sub-national trends of malaria prevalence in Madagascar as the country aims for geographically progressive elimination. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12916-018-1060-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-05-23 /pmc/articles/PMC5964908/ /pubmed/29788968 http://dx.doi.org/10.1186/s12916-018-1060-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Kang, Su Yun
Battle, Katherine E.
Gibson, Harry S.
Ratsimbasoa, Arsène
Randrianarivelojosia, Milijaona
Ramboarina, Stéphanie
Zimmerman, Peter A.
Weiss, Daniel J.
Cameron, Ewan
Gething, Peter W.
Howes, Rosalind E.
Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016
title Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016
title_full Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016
title_fullStr Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016
title_full_unstemmed Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016
title_short Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016
title_sort spatio-temporal mapping of madagascar’s malaria indicator survey results to assess plasmodium falciparum endemicity trends between 2011 and 2016
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5964908/
https://www.ncbi.nlm.nih.gov/pubmed/29788968
http://dx.doi.org/10.1186/s12916-018-1060-4
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