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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Feb 8, 2022
Date Accepted: Oct 22, 2022

The final, peer-reviewed published version of this preprint can be found here:

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

Sylvestre E, Cécilia-Joseph E, Bouzillé G, Najioullah F, Etienne M, Etienne M, Malouines F, Rosine J, Julié S, Cabié A, Cuggia M

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

JMIR Public Health Surveill 2022;8(12):e37122

DOI: 10.2196/37122

PMID: 36548023

PMCID: 9816958

The role of heterogenous real-world data for dengue surveillance in Martinique: an observational retrospective study

  • Emmanuelle Sylvestre; 
  • Elsa Cécilia-Joseph; 
  • Guillaume Bouzillé; 
  • Fatiha Najioullah; 
  • Manuel Etienne; 
  • Manuel Etienne; 
  • Fabrice Malouines; 
  • Jacques Rosine; 
  • Sandrine Julié; 
  • André Cabié; 
  • Marc Cuggia

ABSTRACT

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 in place for vector control. Therefore, researchers are constantly assessing novel sources of data 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 heterogenous real-world data sources could help to 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:

Dengue hospitalization rate was the variable most strongly correlated with the increase in dengue positivity rate by RT-PCR (Pearson’s correlation coefficient = 0.70) with a time lag of -3 weeks. Weekly entomological interventions also were correlated with the increase in dengue positivity rate by RT-PCR (Pearson’s 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’s 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 of dengue cases of 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 general, in smaller endemic territories.


 Citation

Please cite as:

Sylvestre E, Cécilia-Joseph E, Bouzillé G, Najioullah F, Etienne M, Etienne M, Malouines F, Rosine J, Julié S, Cabié A, Cuggia M

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

JMIR Public Health Surveill 2022;8(12):e37122

DOI: 10.2196/37122

PMID: 36548023

PMCID: 9816958

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