Forecasting the 2020 COVID-19 Epidemic: A Multivariate Quasi-Poisson Regression to Model the Evolution of New Cases in Chile.

ABSTRACT: Objectives: To understand and forecast the evolution of COVID-19 (Coronavirus disease 2019) in Chile, and analyze alternative simulated scenarios to better predict alternative paths, in order to implement policy solutions to stop the spread and minimize damage. Methods: We have specified a novel multi-parameter generalized logistic growth model, which does not only look at the trend of the data, but also includes explanatory covariates, using a quasi-Poisson regression specification to account for overdispersion of the count data. We fitted our model to data from the onset of the disease (February 28) until September 15. Estimating the parameters from our model, we predicted the growth of the epidemic for the evolution of the disease until the end of October 2020. We also eva

SUBMITTER: Vicuna MI 

PROVIDER: S-EPMC8102770 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature