A Two-wave Epidemiological model of COVID-19 outbreaks using MS-Excel® - Junior, Agenor De Noni; Silva, Bernardo Araldi da; Dal-Pizzol, Felipe; Porto, Luismar Marques (Archives of Clinical and Biomedical Research, 2021)
The emergence of the coronavirus SARS-CoV-2 has raised a global issue and a pandemic disease outbreak, COVID-19, was declared by the World Health Organization on March 12th, 2020. Health authority advisors and governments need to quickly manage and deal with growing epidemiological data on a daily basis. In this work, current available data from reported cases and deaths were analyzed and treated. Lethality has been calculated by finding linearization of death cases against reported ones, using a time-delayed data transposition. A two-wave statistical model, 2WM, based on the superposition of normal distributions was used to fit current data and to estimate the evolution of infections and deaths, using Microsoft® Excel. A gamma distribution was used as a risk function to estimate death probability from patient admission to reported death. Evolution of fatality cases over time can then be estimated from the model with reasonable accuracy. Data from South Korea, China, Australia, Germany, Italy, Spain, United States, United Kingdom and Brazil were used. Constant lethality can be determined from the initial stage of the pandemic wave, even for places with low testing. Values ranged from 1.7% to 15.3%. The two-wave model can be fine-tuned to properly adjust the data. The second wave pattern was estimated according to the first wave parameter. The accuracy for estimating COVID-19 evolution was compared to the classic SIR model with good agreement. According to the model, approximately 10,000,000 cases and 860,000 deaths will be recorded worldwide.