ArticleScientific reports2021
Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Risk Factors of COVID-19 Severity and Related Death in Children in the Post-Pandemic Era.Microorganisms · 2026Article
- Analysis of Models to Estimate Morbidity Rates of Respiratory Diseases Through Deep Learning.Tropical medicine & international health : TM & IH · 2026Article
- Effectiveness of COVID-19 Vaccines Against Hospitalization and Severe Disease in Children with Diabetes Mellitus During Pandemic and Post-Pandemic Eras.Microorganisms · 2026Article
- Social inequalities in the misbelief of chloroquine's protective effect against COVID-19: results from the EPICOVID-19 study in Brazil.PloS one · 2026Article
- Impacts of the COVID-19 pandemic on Brazilian families: a countrywide population-based survey.International journal of epidemiology · 2026Article
- COVID-19 Vaccine Effectiveness and Risk Factors of Booster Failure in 480,000 Patients with Diabetes Mellitus: A Population-Based Cohort Study.Microorganisms · 2025Article
- Agenda setting for health equity assessment through the lenses of social determinants of health using machine learning approach: a framework and preliminary pilot study.BioData mining · 2025Article
- Comparative performance of twelve machine learning models in predicting COVID-19 mortality risk in children: a population-based retrospective cohort study in Brazil.PeerJ. Computer science · 2025Article
- Epidemiology of cardiometabolic health in Latin America and strategies to address disparities.Nature reviews. Cardiology · 2024Review
- At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.Scientific reports · 2024Article
- Towards Improved XAI-Based Epidemiological Research into the Next Potential Pandemic.Life (Basel, Switzerland) · 2024Review
- Article
- Epidemiological profile of patients hospitalized with Crohn's disease due to severe acute respiratory infection during the COVID-19 pandemic: a 2-year report from Brazil.Frontiers in medicine · 2024Article
- Synthesizing Electronic Health Records for Predictive Models in Low-Middle-Income Countries (LMICs).Biomedicines · 2023Article
- Frailty, Comorbidity, and Associations With In-Hospital Mortality in Older COVID-19 Patients: Exploratory Study of Administrative Data.Interactive journal of medical research · 2022Article
- Machine learning and comorbidity network analysis for hospitalized patients with COVID-19 in a city in Southern Brazil.Smart health (Amsterdam, Netherlands) · 2022Article
- Clinical characteristics and comorbidities of COVID-19 in unvaccinated patients with Down syndrome: first year report in Brazil.Human genetics · 2022Article
- Being Physically Active Leads to Better Recovery Prognosis for People Diagnosed with COVID-19: A Cross-Sectional Study.International journal of environmental research and public health · 2022Article
- Influence of Population Size, the Human Development Index and the Gross Domestic Product on Mortality by COVID-19 in the Southeast Region of Brazil.International journal of environmental research and public health · 2022Article
- Risk Factors Associated with Mortality in Hospitalized Patients with COVID-19 during the Omicron Wave in Brazil.Bioengineering (Basel, Switzerland) · 2022Article
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Authors and funding
6 authors.
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Abstract
The COVID-19 pandemic continues to have a devastating impact on Brazil. Brazil's social, health and economic crises are aggravated by strong societal inequities and persisting political disarray. This complex scenario motivates careful study of the clinical, socioeconomic, demographic and structural factors contributing to increased risk of mortality from SARS-CoV-2 in Brazil specifically. We consider the Brazilian SIVEP-Gripe catalog, a very rich respiratory infection dataset which allows us to estimate the importance of several non-laboratorial and socio-geographic factors on COVID-19 mortality. We analyze the catalog using machine learning algorithms to account for likely complex interdependence between metrics. The XGBoost algorithm achieved excellent performance, producing an AUC-ROC of 0.813 (95% CI 0.810-0.817), and outperforming logistic regression. Using our model we found that, in Brazil, socioeconomic, geographical and structural factors are more important than individual comorbidities. Particularly important factors were: The state of residence and its development index; the distance to the hospital (especially for rural and less developed areas); the level of education; hospital funding model and strain. Ethnicity is also confirmed to be more important than comorbidities but less than the aforementioned factors. In conclusion, socioeconomic and structural factors are as important as biological factors in determining the outcome of COVID-19. This has important consequences for policy making, especially on vaccination/non-pharmacological preventative measures, hospital management and healthcare network organization.
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