Lockdown as an intervention measure to mitigate the spread of COVID-19: a modeling study
Keywords:Epidemiology, Social Isolation, COVID-19, Coronavirus infections
Introduction: This work aims to develop a biomathematical model of transmission of COVID-19, in the State of Sergipe, Brazil, to estimate the distribution of cases over time and to project the impact on the spread of the epidemic outbreak due to interventions and control measures on the local population. Methods: Epidemiological mathematical modeling study, carried out to analyze the dynamics of accumulated cases of COVID-19, which used a logistic growth model that adds a term of withdrawal of individuals as a control measure. Three possible scenarios of COVID-19 propagation based on three different withdrawal rates of individuals were simulated. Each of the rates is adjusted with actual data on the number of infected and control measures on the population. Results: The extreme measure of total isolation, or lockdown, would be the best scenario, presenting a lower incidence of infected, when compared to the other measures. The number of infected would grow slowly over the months and the number of symptomatic individuals in this scenario would be 40,265 cases. It was noticed that the State of Sergipe is still in the initial phase of the disease, in any of the scenarios. It was possible to observe that the peak of cases and balance, in the current scenario of social isolation, will take place when the new support capacity is reached, at the end of August in approximately 1,171,353 infected individuals. Conclusion: It was noticed that lockdown is the intervention with greater capacity to mitigate the spread of the virus by the population.
Keywords: COVID-19, Coronavirus Infection, Social Isolation, Epidemiology.
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Copyright (c) 2020 Eduesley Santana-Santos, Aédson Nascimento Gois, Estêvão Esmi Laureano, David da Silva Santos, Luiz Fernando Souza Santos, Daniel Eduardo Sánchez, Rita de Cássia Almeida Vieira, Jussiely Cunha Oliveira
This work is licensed under a Creative Commons Attribution 4.0 International License.