Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study

Abstract

<jats:p>Abstract: The COVID-19 death rate in Northeast Brazil is much higher when compared to the national average, demanding a study into the prognosis of the region for planning control measures and preventing the collapse of the health care system. We estimated the potential total cumulative cases of COVID-19 in the region for the next three months. Our study included all confirmed cases, from March 8 until April 28, 2020, collected from the official website that reports the situation of COVID-19 infections in Brazil. The Boltzmann function was applied to a data simulation for each set of data regarding different states. The model data were well fitted, with R2 values close to 0.999. Up to April 28, 20,665 cases were confirmed in the region. The state of Ceará has the highest rate of accumulated cases per 100,000 inhabitants (75.75), followed by Pernambuco. We estimated that the states of Ceará, Sergipe and Paraíba will experience a dramatic increase in the rate of cumulative cases until July 31. Maranhão, Pernambuco, Rio Grande do Norte and Piauí showed a more discreet increase in the model. For Bahia and Alagoas, a 4.7 and 6.6-fold increase in the rate was estimated, respectively. We estimate a substantial increase in the rate of cumulative cases per 100,000 inhabitants in the region within three months, especially for Ceará, Sergipe and Paraíba. The Boltzmann function proved to be a simple tool for epidemiological forecasting that can help planning the measures to contain COVID-19.</jats:p>

Evolução inicial da covid-19 em três estados da região nordeste do Brasil / Initial evolution of covid-19 in three states of the northeast region of Brazil

“…Só a partir da segunda quinzena de abril de 2020 que a região Nordeste brasileira começou a oferecer testes rápidos para o diagnóstico sorológico da Covid-19, mas eles geralmente estavam restritos a população com sintomas respiratórios e gripais, principalmente os casos graves e internados, não adotando a estratégia de testes em A constante ameaça de redução do isolamento social por parte da população e a estrutura urbana que favorece a aglomeração em comunidades, se mostrou um grande desafio para a manutenção das taxas de isolamento ideais para evitar a superlotação de leitos, exposição dos profissionais de saúde e mortes. É comprovado que o isolamento social, somado ao uso de máscaras e medidas higiênico-sanitárias contribuem para uma mais rápida diminuição dos impactos econômicos e psicossociais que essa pandemia causou (11) .…”

Prediction of cumulative rate of COVID-19 deaths in Brazil: a modeling study

“…Data were organized in Microsoft Excel (Windows version 2016, Microsoft Corporation; Redmond, WA, USA) and incorporated into Microcal Origin software version 6.0. The Boltzmann function [8][9][10]12 was applied to the data simulation for each set of data regarding different geographical regions in the northeast of Brazil. We obtained the parameters of each function, with the potential total number of confirmed cases being directly given by the parameter A 2 .…”

“…Even considering the possibility of a certain level of uncertainty, like any scientific result, the discoveries made from mathematical models are considered of paramount importance for the planning of public policies 7 . A simpler model in terms of understanding and application, which has already been used in studies carried out in China, is Boltzmann's model [8][9][10] . Thus, the objective of this study was to estimate the total potential number of deaths by COVID-19 for Brazil in the next two months, using Boltzmann's function -based on regression analysis.…”

A diffusive SEIR model for community transmission of Covid-19 epidemics: application to Brazil

“…Mathematical treatments of the spatial spread of COVID-19 have used probabilistic methods [10,17], neural networks methods [27,38], data analysis methods [5,12,33,21], and differential equations methods [4,7,14,15,20,40,41,44,47]. Reaction-diffusion equations have been used extensively to model the spatial spread of epidemic diseases (see, for example, [1,2,6,13,19,18,29,32,37,49,50,53]).…”