Observational studyPLoS neglected tropical diseases2025
Designing a multidimensional vulnerability index for supervising dengue cases from 2015 to 2020 in a low/middle-income country: A spatial principal component analysis.
Observational study in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundDengue is one of the most prevalent infectious diseases worldwide, affecting around 390 million people each year. Previous studies have reported that social, climatic, and government-related conditions can increase the frequency of dengue events in some territories. This study aimed to design a multidimensional vulnerability index encompassing social, climatic, and government-related factors associated with dengue and correlate this index with dengue incidence in Colombia between 2015 and 2020.
methodsObservational, ecological, longitudinal study conducted from 2015 to 2020. Based on administrative data from state sources such as the Ministry of Health, the National Administrative Department of Statistics (DANE), the National Planning Department (DNP), and other sources, a principal component analysis was performed to design the multidimensional vulnerability index.
resultsData from 1099 municipalities over the six-year analysis period were included. The index comprised five main factors: climatic factors, basic service coverage, precipitation-related factors, municipal performance, and transparency in social development. The proposed index showed a mean vulnerability of 0.48 (median = 0.48; SD = 0.15; IQR: 0.36-0.59). Higher index values were found in the southwestern territories and the Amazon regions of Colombia, as well as some municipalities in the Caribbean region. These territories exhibited the highest levels of poverty, regional access to services, precipitation, and temperature. Spatial analyses confirmed this concordance. The nonlinear association between the MVI and dengue incidence suggests threshold effects, in which municipalities with MVI scores above 0.8 have higher levels of dengue morbidity.
conclusionsThe proposed index showed a suitable correlation with dengue case frequency at a regional level and could be extended to other countries for the development of dengue outbreak prevention campaigns.
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