ArticleSpatial and spatio-temporal epidemiology2023
Spatial modeling and socioeconomic inequities of COVID-19 in the urban area of the city of Cali, Colombia.
Article in Spatial and spatio-temporal epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness.International journal of environmental research and public health · 2026Pooled it
- Understanding socioeconomic inequalities in COVID-19 vaccination: controlling endogenous selection in Cali, Colombia.International journal of health geographics · 2025Article
- Sociodemographic Inequalities in COVID-19 Booster Dose Vaccination Coverage: a Retrospective Study of 196 Provinces in Peru.Journal of racial and ethnic health disparities · 2025Article
- Bayesian Modeling and Estimation of Spatial Risk for Hospitalization and Mortality from Ischemic Heart Disease in Paraná, Brazil.Global heart · 2024Article
- Socioeconomic disparities and concentration of the spread of the COVID-19 pandemic in the province of Quebec, Canada.BMC public health · 2023Article
- An overview of urban analytical approaches to combating the Covid-19 pandemic.Environment and planning. B, urban analytics and city science · 2023Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 has spread worldwide with a high variability in cases and mortality between populations. This research aims to assess socioeconomic inequities of COVID-19 in the city of Cali, Colombia, during the first and second peaks of the pandemic in this city. An ecological study by neighborhoods was carried out, were COVID-19 cases were analyzed using a Bayesian hierarchical spatial model that includes potential risk factors such as the index of unsatisfied basic needs and socioeconomic variables as well as random effects to account for residual variation. Maps showing the geographic patterns of the estimated relative risks as well as exceedance probabilities were created. The results indicate that in the first wave, the neighborhoods with the greatest unsatisfied basic needs and low socioeconomic strata, were more likely to report positive cases for COVID-19. For the second wave, the disease begins to spread through different neighborhoods of the city and middle socioeconomic strata presents the highest risk followed by the lower strata. These findings indicate the importance of measuring social determinants in the study of the distribution of cases due to COVID-19 for its inclusion in the interventions and measures implemented to contain contagions and reduce impacts on the most vulnerable populations.
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