Data-based analysis, modelling and forecasting of the COVID-19 outbreak in Iran

Background: The rapid spread of COVID-19 virus from China to other countries andoutbreaks of disease require an epidemiological analysis of the disease in the shortest timeand an increased awareness of effective interventions. Thus, this study aimed to determinethe epidemic trend and prediction of COVID-19 in Iran, Based on joinpoint regressionmodel.Material and Methods: We collected the incidence and mortality of COVID-19 in 31.12.2019to 17.10.2020 in Iran from official websites. We used the joinpoint regression to report annualpercent change incidence and mortality. Also, we predicted the incidence and mortality ofCOVID-19 from 17.10.2020 to 31.12.2020 by formula and AAPC.Results: Between 31.12.2019 to 17.10.2020, the average annual percent change for Iran ofincidence COVID-19 1.38% (95% CI 1.11 to 1.65) and mortality 1.68% (95% CI 1.32 to 2.04).If no action is taken to control the disease, Incidence of COVID-19, to 31.12.2020 Reaches12724 person and mortality of COVID-19, 925 person.Conclusions: The most important point is to emphasize the timing of the epidemic peak,hospital readiness, government measures and public readiness to reduce social contact. In thisstudy, estimations (incidence and mortality rate) were made based on joinpoint regressionmodel. If enforcement and public behavior interventions continue with current trends, theCOVID-19 epidemic will be Enormous increase until December 31, 2020 in Iran.

کلیدواژه ها:

Forecasting ، COVID-19 ، Iran