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Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System
BACKGROUND: Cross-border malaria is a significant obstacle to achieving malaria control and elimination worldwide. OBJECTIVE: This study aimed to build a cross-border surveillance system that can make comparable and qualified data available to all parties involved in malaria control between French G...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492983/ https://www.ncbi.nlm.nih.gov/pubmed/32663141 http://dx.doi.org/10.2196/15409 |
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author | Saldanha, Raphael Mosnier, Émilie Barcellos, Christovam Carbunar, Aurel Charron, Christophe Desconnets, Jean-Christophe Guarmit, Basma Gomes, Margarete Do Socorro Mendonça Mandon, Théophile Mendes, Anapaula Martins Peiter, Paulo César Musset, Lise Sanna, Alice Van Gastel, Benoît Roux, Emmanuel |
author_facet | Saldanha, Raphael Mosnier, Émilie Barcellos, Christovam Carbunar, Aurel Charron, Christophe Desconnets, Jean-Christophe Guarmit, Basma Gomes, Margarete Do Socorro Mendonça Mandon, Théophile Mendes, Anapaula Martins Peiter, Paulo César Musset, Lise Sanna, Alice Van Gastel, Benoît Roux, Emmanuel |
author_sort | Saldanha, Raphael |
collection | PubMed |
description | BACKGROUND: Cross-border malaria is a significant obstacle to achieving malaria control and elimination worldwide. OBJECTIVE: This study aimed to build a cross-border surveillance system that can make comparable and qualified data available to all parties involved in malaria control between French Guiana and Brazil. METHODS: Data reconciliation rules based on expert knowledge were defined and applied to the heterogeneous data provided by the existing malaria surveillance systems of both countries. Visualization dashboards were designed to facilitate progressive data exploration, analysis, and interpretation. Dedicated advanced open source and robust software solutions were chosen to facilitate solution sharing and reuse. RESULTS: A database gathering the harmonized data on cross-border malaria epidemiology is updated monthly with new individual malaria cases from both countries. Online dashboards permit a progressive and user-friendly visualization of raw data and epidemiological indicators, in the form of time series, maps, and data quality indexes. The monitoring system was shown to be able to identify changes in time series that are related to control actions, as well as differentiated changes according to space and to population subgroups. CONCLUSIONS: This cross-border monitoring tool could help produce new scientific evidence on cross-border malaria dynamics, implementing cross-border cooperation for malaria control and elimination, and can be quickly adapted to other cross-border contexts. |
format | Online Article Text |
id | pubmed-7492983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-74929832020-10-01 Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System Saldanha, Raphael Mosnier, Émilie Barcellos, Christovam Carbunar, Aurel Charron, Christophe Desconnets, Jean-Christophe Guarmit, Basma Gomes, Margarete Do Socorro Mendonça Mandon, Théophile Mendes, Anapaula Martins Peiter, Paulo César Musset, Lise Sanna, Alice Van Gastel, Benoît Roux, Emmanuel JMIR Public Health Surveill Original Paper BACKGROUND: Cross-border malaria is a significant obstacle to achieving malaria control and elimination worldwide. OBJECTIVE: This study aimed to build a cross-border surveillance system that can make comparable and qualified data available to all parties involved in malaria control between French Guiana and Brazil. METHODS: Data reconciliation rules based on expert knowledge were defined and applied to the heterogeneous data provided by the existing malaria surveillance systems of both countries. Visualization dashboards were designed to facilitate progressive data exploration, analysis, and interpretation. Dedicated advanced open source and robust software solutions were chosen to facilitate solution sharing and reuse. RESULTS: A database gathering the harmonized data on cross-border malaria epidemiology is updated monthly with new individual malaria cases from both countries. Online dashboards permit a progressive and user-friendly visualization of raw data and epidemiological indicators, in the form of time series, maps, and data quality indexes. The monitoring system was shown to be able to identify changes in time series that are related to control actions, as well as differentiated changes according to space and to population subgroups. CONCLUSIONS: This cross-border monitoring tool could help produce new scientific evidence on cross-border malaria dynamics, implementing cross-border cooperation for malaria control and elimination, and can be quickly adapted to other cross-border contexts. JMIR Publications 2020-09-01 /pmc/articles/PMC7492983/ /pubmed/32663141 http://dx.doi.org/10.2196/15409 Text en ©Raphael Saldanha, Émilie Mosnier, Christovam Barcellos, Aurel Carbunar, Christophe Charron, Jean-Christophe Desconnets, Basma Guarmit, Margarete Do Socorro Mendonça Gomes, Théophile Mandon, Anapaula Martins Mendes, Paulo César Peiter, Lise Musset, Alice Sanna, Benoît Van Gastel, Emmanuel Roux. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 01.09.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Saldanha, Raphael Mosnier, Émilie Barcellos, Christovam Carbunar, Aurel Charron, Christophe Desconnets, Jean-Christophe Guarmit, Basma Gomes, Margarete Do Socorro Mendonça Mandon, Théophile Mendes, Anapaula Martins Peiter, Paulo César Musset, Lise Sanna, Alice Van Gastel, Benoît Roux, Emmanuel Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System |
title | Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System |
title_full | Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System |
title_fullStr | Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System |
title_full_unstemmed | Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System |
title_short | Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System |
title_sort | contributing to elimination of cross-border malaria through a standardized solution for case surveillance, data sharing, and data interpretation: development of a cross-border monitoring system |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492983/ https://www.ncbi.nlm.nih.gov/pubmed/32663141 http://dx.doi.org/10.2196/15409 |
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