Predictive analysis of confirmed COVID-19 cases in Peru based on the Gompertz non-linear regression model using fatality cases data - Pérez Paredes, Marina Gabriela Sadith (2021)
This study aims to evaluate the future of confirmed cases of Covid-19 in Peru, using the Gompertz nonlinear regression model. The data were obtained from official reports of the Peru Ministry of Health (MINSA). The accumulated value of fatal cases was subjected to iterative analysis by the non-linear least-squares method to achieve a model. Given the first-order derivative of the predictive model was obtained the daily fatal cases curve. Using the fatality rate as the proportion between infected and fatal cases, both of them would also provide days average lag to estimate the epidemic curve. For the moment, the predictive model suggests that Peru would be in a slow descent in the epidemic curve, moving away from the peak of contagions per day. The trend of reaching about 550 thousand infected and 19 thousand deaths until the end of the year 2020. The predictions of the mathematical models may vary according to the periodic updating of data, updated predictions will be published on www.yupay-dynamic.com