Mathematical modeling of COVID-19 in 14.8 million individuals in Bahia, Brazil.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 33436608.
- Also identified by DOI 10.1038/s41467-020-19798-3 and PMC identifier 7803757.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
COVID-19 is affecting healthcare resources worldwide, with lower and middle-income countries being particularly disadvantaged to mitigate the challenges imposed by the disease, including the availability of a sufficient number of infirmary/ICU hospital beds, ventilators, and medical supplies. Here, we use mathematical modelling to study the dynamics of COVID-19 in Bahia, a state in northeastern Brazil, considering the influences of asymptomatic/non-detected cases, hospitalizations, and mortality. The impacts of policies on the transmission rate were also examined. Our results underscore the difficulties in maintaining a fully operational health infrastructure amidst the pandemic. Lowering the transmission rate is paramount to this objective, but current local efforts, leading to a 36% decrease, remain insufficient to prevent systemic collapse at peak demand, which could be accomplished using periodic interventions. Non-detected cases contribute to a ∽55% increase in R<sub>0</sub>. Finally, we discuss our results in light of epidemiological data that became available after the initial analyses.
Medical subject headings
- COVID-19
- Models, Theoretical
- Pandemics
- SARS-CoV-2