Identifying drivers of dengue fever outbreaks in Mauritius using Geographic Information System

Abstract

Mosquito-borne diseases can cause public health disasters. Climatic and environmental conditions, urbanisation, changes in land use, and the increased movement of people and goods worldwide are causing their increased transmission. Mauritius is especially at risk being situated in a vulnerable geographical region. In this study, we used geographical tools to identify potential drivers and vulnerability areas related to dengue fever in the island. Dengue cases were identified by municipal ward (MW) and village council area (VCA). Meteorological data consisted of rainfall and temperature data. The Relative Development Index (RDI) was used as a proxy for socioeconomic factors. The population density and the number of houses in close proximity to rivers were determined per VCA and MW. Maps were generated on the software QGIS 3.12. Statistical tests consisted of multiple regression analysis with dengue incidence as the dependent variable and potential drivers as the independent variables. The results showed that the close proximity of houses to rivers had a significant positive effect on dengue incidence (p = 0.03) while the RDI had a significant negative effect (p = 0.01). Vulnerability areas in the island can hence be determined based on the findings.

Contribution: The findings of this study allow preemptive measures to be taken in identified vulnerability areas to prevent mosquito-borne disease outbreaks.