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Mathematical modeling of COVID-19 in 14.8 million individuals in Bahia, Brazil
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Nivea B. da Silva,
Rosemeire L. Fiaccone,
Luciana L. Cardim,
Felipe A. C. Pereira,
Caio P. de Castro,
Aureliano S. S. Paiva,
Alan Amad ,
Ernesto A. B. F. Lima,
Diego S. Souza,
Suani T. R. Pinho,
Pablo Ivan P. Ramos,
Roberto F. S. Andrade
Nature Communications, Volume: 12, Issue: 1
Swansea University Authors:
Matheus Torquato , Alan Amad
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DOI (Published version): 10.1038/s41467-020-19798-3
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,...
| Published in: | Nature Communications |
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| ISSN: | 2041-1723 |
| Published: |
Springer Science and Business Media LLC
2021
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa56082 |
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| 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 R0. Finally, we discuss our results in light of epidemiological data that became available after the initial analyses. |
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| College: |
Faculty of Science and Engineering |
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This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Finance Code 001. STRP was supported by an International Cooperation grant (process number INT0002/2016) from Bahia Research Foundation (FAPESB). STRP and RFSA were supported by the National Institute of Science and Technology—Complex Systems from CNPq, Brazil. JFO was supported by the Center of Data and Knowledge Integration for Health (CIDACS) through the Zika Platform—a long-term surveillance platform for Zika virus and microcephaly (Unified Health System (SUS), Brazilian Ministry of Health). AASA gratefully acknowledges the financial support received from the Engineering and Physical Sciences Research Council (EPSRC) in the form of grant EP/R002134/1. The authors acknowledge the helpful suggestions from members of the CoVida Network (http://www.redecovida.org), in special to contributors to the Rede CoVida Modelling Task-force (See Supplementary Note 1). Andris K. Walter is gratefully acknowledged for English language revision and manuscript copy-editing assistance. |
| Issue: |
1 |