Best selected forecasting models for COVID-19 pandemic

Abstract This study sought to identify the most accurate forecasting models for COVID-19-confirmed cases, deaths, and recovered patients in Pakistan. For COVID-19, time series data are available from 16 April 15 August 2021 Ministry of National Health Services Regulation Coordination’s health advice portal. Descriptive as well models, autoregressive integrated moving average, exponential smoothing (Brown, Holt, Winters), neural networks, Error, Trend, Seasonal (ETS) were applied. The analysis was carried out using R coding language. descriptive shows that average number confirmed COVID-19-related reported each day 2,916, 69.43, 2,772, respectively. highest COVID-19 cases fatalities per day, however, recorded on 17, 27, 2021, ETS (M, N, M), network, nonlinear (NNAR) (3, 1, 2), NNAR (8, 4) found be best among all other competing patients, outbreaks, predicted rise by around 0.75, 5.08, 19.11% daily. These statistical results will serve a guide disease management control.