TVISARS-CoV-2: a multicriteria index and urban dynamics in Minas Gerais, Brazil.
Abstract
OBJECTIVE: To develop a municipal-level vulnerability index to COVID-19 transmission that integrates socioeconomic factors, urban infrastructure, mobility, and composite indicators of social vulnerability and leisure for Minas Gerais. This study found factors associated with the spatial distribution of COVID-19 and classified the 853 municipalities in the state by vulnerability levels. METHODS: Data on COVID-19 cases from February 2022 were combined with nine variables in three domains: (i) socioeconomic factors (trade, service, construction, and manufacturing jobs); (ii) urban infrastructure and mobility (urban area, road connectivity, and vehicle density); and (iii) composite indicators (index of social vulnerability and access to culture, sports, and leisure). A multicriteria analysis model with Pearson's correlations was elaborated and validated by cross-validation. RESULTS: The vulnerability index ranged from 1 to 8. The municipality of Belo Horizonte showed the highest value (8), followed by Uberlândia (6) and other medium to large municipalities with high urban dynamism. Urban area (22.92%), road connectivity (17.54%), and vehicle density (12.86%) constituted the most influential variables in the model. Spatial distribution indicated greater vulnerability in metropolitan regions and regional hubs. CONCLUSIONS: The proposed index highlighted the role of structural and occupational characteristics in territorial vulnerability to COVID-19. Limitations such as the time lag of some variables, source heterogeneity, and case underreporting-especially in municipalities with lower testing capacity-may have influenced the results. Incorporating emerging technologies and sustainable practices can mitigate the risks of future pandemics and improve quality of life. The index offered a useful tool for health planning (which may be adapted to other communicable diseases).
Fields of Study & Subjects
COVID-19 epidemiological studies
Education during COVID-19 pandemic
Data-Driven Disease Surveillance
Publication details
- Journal / source
- PubMed
- Volume
- 59
- Pages
- e49–e49
- Publication date
- 1 January 2026
- Language
- EN