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Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times

BACKGROUND: As controlling malaria transmission remains a public-health challenge in the Brazilian Amazon basin, the National Surveillance System for Malaria (SIVEP-MALARIA) has registered malaria notifications for over fifteen years helping in the decision-making on control and elimination. As a su...

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Autores principales: Ayala, Mario J. C., Valiati, Naiara C. M., Bastos, Leonardo S., Villela, Daniel A. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913006/
https://www.ncbi.nlm.nih.gov/pubmed/36765345
http://dx.doi.org/10.1186/s12936-023-04464-y
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author Ayala, Mario J. C.
Valiati, Naiara C. M.
Bastos, Leonardo S.
Villela, Daniel A. M.
author_facet Ayala, Mario J. C.
Valiati, Naiara C. M.
Bastos, Leonardo S.
Villela, Daniel A. M.
author_sort Ayala, Mario J. C.
collection PubMed
description BACKGROUND: As controlling malaria transmission remains a public-health challenge in the Brazilian Amazon basin, the National Surveillance System for Malaria (SIVEP-MALARIA) has registered malaria notifications for over fifteen years helping in the decision-making on control and elimination. As a surveillance database, the system is prone to reporting delays, and knowledge about reporting patterns is essential in decisions. METHODS: This study contains an analysis of temporal and state trends of reporting times in a total of 1,580,617 individual malaria reports from January 2010 to December 2020, applying procedures for statistical distribution fitting. A nowcasting technique was applied to show an estimation of number of cases using a statistical model of reporting delays. RESULTS: Reporting delays increased over time for the states of Amazonas, Rondônia, Roraima, and Pará. Amapá has maintained a similar reporting delay pattern, while Acre decreased reporting delay between 2010 and 2020. Predictions were more accurate in states with lower reporting delays. The temporal evolution of reporting delays only showed a decrease in malaria reports in Acre from 2010 to 2020. CONCLUSION: Malaria notifications may take days or weeks to enter the national surveillance database. The reporting times are likely to impact incidence estimation over periods when data is incomplete, whilst the impact of delays becomes smaller for retrospective analysis. Short-term assessments for the estimation of malaria incidence from the malaria control programme must deal with reporting delays.
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spelling pubmed-99130062023-02-12 Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times Ayala, Mario J. C. Valiati, Naiara C. M. Bastos, Leonardo S. Villela, Daniel A. M. Malar J Research BACKGROUND: As controlling malaria transmission remains a public-health challenge in the Brazilian Amazon basin, the National Surveillance System for Malaria (SIVEP-MALARIA) has registered malaria notifications for over fifteen years helping in the decision-making on control and elimination. As a surveillance database, the system is prone to reporting delays, and knowledge about reporting patterns is essential in decisions. METHODS: This study contains an analysis of temporal and state trends of reporting times in a total of 1,580,617 individual malaria reports from January 2010 to December 2020, applying procedures for statistical distribution fitting. A nowcasting technique was applied to show an estimation of number of cases using a statistical model of reporting delays. RESULTS: Reporting delays increased over time for the states of Amazonas, Rondônia, Roraima, and Pará. Amapá has maintained a similar reporting delay pattern, while Acre decreased reporting delay between 2010 and 2020. Predictions were more accurate in states with lower reporting delays. The temporal evolution of reporting delays only showed a decrease in malaria reports in Acre from 2010 to 2020. CONCLUSION: Malaria notifications may take days or weeks to enter the national surveillance database. The reporting times are likely to impact incidence estimation over periods when data is incomplete, whilst the impact of delays becomes smaller for retrospective analysis. Short-term assessments for the estimation of malaria incidence from the malaria control programme must deal with reporting delays. BioMed Central 2023-02-10 /pmc/articles/PMC9913006/ /pubmed/36765345 http://dx.doi.org/10.1186/s12936-023-04464-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ayala, Mario J. C.
Valiati, Naiara C. M.
Bastos, Leonardo S.
Villela, Daniel A. M.
Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times
title Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times
title_full Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times
title_fullStr Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times
title_full_unstemmed Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times
title_short Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times
title_sort notification of malaria cases in the brazilian amazon basin from 2010 to 2020: an analysis of the reporting times
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913006/
https://www.ncbi.nlm.nih.gov/pubmed/36765345
http://dx.doi.org/10.1186/s12936-023-04464-y
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