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The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study

BACKGROUND: Traditionally, dengue prevention and control rely on vector control programs and reporting of symptomatic cases to a central health agency. However, case reporting is often delayed, and the true burden of dengue disease is often underestimated. Moreover, some countries do not have routin...

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Autores principales: Sylvestre, Emmanuelle, Cécilia-Joseph, Elsa, Bouzillé, Guillaume, Najioullah, Fatiha, Etienne, Manuel, Malouines, Fabrice, Rosine, Jacques, Julié, Sandrine, Cabié, André, Cuggia, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816958/
https://www.ncbi.nlm.nih.gov/pubmed/36548023
http://dx.doi.org/10.2196/37122
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author Sylvestre, Emmanuelle
Cécilia-Joseph, Elsa
Bouzillé, Guillaume
Najioullah, Fatiha
Etienne, Manuel
Malouines, Fabrice
Rosine, Jacques
Julié, Sandrine
Cabié, André
Cuggia, Marc
author_facet Sylvestre, Emmanuelle
Cécilia-Joseph, Elsa
Bouzillé, Guillaume
Najioullah, Fatiha
Etienne, Manuel
Malouines, Fabrice
Rosine, Jacques
Julié, Sandrine
Cabié, André
Cuggia, Marc
author_sort Sylvestre, Emmanuelle
collection PubMed
description BACKGROUND: Traditionally, dengue prevention and control rely on vector control programs and reporting of symptomatic cases to a central health agency. However, case reporting is often delayed, and the true burden of dengue disease is often underestimated. Moreover, some countries do not have routine control measures for vector control. Therefore, researchers are constantly assessing novel data sources to improve traditional surveillance systems. These studies are mostly carried out in big territories and rarely in smaller endemic regions, such as Martinique and the Lesser Antilles. OBJECTIVE: The aim of this study was to determine whether heterogeneous real-world data sources could help reduce reporting delays and improve dengue monitoring in Martinique island, a small endemic region. METHODS: Heterogenous data sources (hospitalization data, entomological data, and Google Trends) and dengue surveillance reports for the last 14 years (January 2007 to February 2021) were analyzed to identify associations with dengue outbreaks and their time lags. RESULTS: The dengue hospitalization rate was the variable most strongly correlated with the increase in dengue positivity rate by real-time reverse transcription polymerase chain reaction (Pearson correlation coefficient=0.70) with a time lag of −3 weeks. Weekly entomological interventions were also correlated with the increase in dengue positivity rate by real-time reverse transcription polymerase chain reaction (Pearson correlation coefficient=0.59) with a time lag of −2 weeks. The most correlated query from Google Trends was the “Dengue” topic restricted to the Martinique region (Pearson correlation coefficient=0.637) with a time lag of −3 weeks. CONCLUSIONS: Real-word data are valuable data sources for dengue surveillance in smaller territories. Many of these sources precede the increase in dengue cases by several weeks, and therefore can help to improve the ability of traditional surveillance systems to provide an early response in dengue outbreaks. All these sources should be better integrated to improve the early response to dengue outbreaks and vector-borne diseases in smaller endemic territories.
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spelling pubmed-98169582023-01-07 The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study Sylvestre, Emmanuelle Cécilia-Joseph, Elsa Bouzillé, Guillaume Najioullah, Fatiha Etienne, Manuel Malouines, Fabrice Rosine, Jacques Julié, Sandrine Cabié, André Cuggia, Marc JMIR Public Health Surveill Original Paper BACKGROUND: Traditionally, dengue prevention and control rely on vector control programs and reporting of symptomatic cases to a central health agency. However, case reporting is often delayed, and the true burden of dengue disease is often underestimated. Moreover, some countries do not have routine control measures for vector control. Therefore, researchers are constantly assessing novel data sources to improve traditional surveillance systems. These studies are mostly carried out in big territories and rarely in smaller endemic regions, such as Martinique and the Lesser Antilles. OBJECTIVE: The aim of this study was to determine whether heterogeneous real-world data sources could help reduce reporting delays and improve dengue monitoring in Martinique island, a small endemic region. METHODS: Heterogenous data sources (hospitalization data, entomological data, and Google Trends) and dengue surveillance reports for the last 14 years (January 2007 to February 2021) were analyzed to identify associations with dengue outbreaks and their time lags. RESULTS: The dengue hospitalization rate was the variable most strongly correlated with the increase in dengue positivity rate by real-time reverse transcription polymerase chain reaction (Pearson correlation coefficient=0.70) with a time lag of −3 weeks. Weekly entomological interventions were also correlated with the increase in dengue positivity rate by real-time reverse transcription polymerase chain reaction (Pearson correlation coefficient=0.59) with a time lag of −2 weeks. The most correlated query from Google Trends was the “Dengue” topic restricted to the Martinique region (Pearson correlation coefficient=0.637) with a time lag of −3 weeks. CONCLUSIONS: Real-word data are valuable data sources for dengue surveillance in smaller territories. Many of these sources precede the increase in dengue cases by several weeks, and therefore can help to improve the ability of traditional surveillance systems to provide an early response in dengue outbreaks. All these sources should be better integrated to improve the early response to dengue outbreaks and vector-borne diseases in smaller endemic territories. JMIR Publications 2022-12-22 /pmc/articles/PMC9816958/ /pubmed/36548023 http://dx.doi.org/10.2196/37122 Text en ©Emmanuelle Sylvestre, Elsa Cécilia-Joseph, Guillaume Bouzillé, Fatiha Najioullah, Manuel Etienne, Fabrice Malouines, Jacques Rosine, Sandrine Julié, André Cabié, Marc Cuggia. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 22.12.2022. 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 https://publichealth.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Sylvestre, Emmanuelle
Cécilia-Joseph, Elsa
Bouzillé, Guillaume
Najioullah, Fatiha
Etienne, Manuel
Malouines, Fabrice
Rosine, Jacques
Julié, Sandrine
Cabié, André
Cuggia, Marc
The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study
title The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study
title_full The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study
title_fullStr The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study
title_full_unstemmed The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study
title_short The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study
title_sort role of heterogenous real-world data for dengue surveillance in martinique: observational retrospective study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816958/
https://www.ncbi.nlm.nih.gov/pubmed/36548023
http://dx.doi.org/10.2196/37122
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