Application of one-, three-, and seven-day forecasts during early onset on the COVID-19 epidemic dataset using moving average, autoregressive, autoregressive moving average, autoregressive integrated moving average, and naive forecasting methods.

ABSTRACT: The coronavirus disease 2019 (COVID-19) spread rapidly across the world since its appearance in December 2019. This data set creates one-, three-, and seven-day forecasts of the COVID-19 pandemic's cumulative case counts at the county, health district, and state geographic levels for the state of Virginia. Forecasts are created over the first 46 days of reported COVID-19 cases using the cumulative case count data provided by The New York Times as of April 22, 2020. From this historical data, one-, three-, seven, and all-days prior to the forecast start date are used to generate the forecasts. Forecasts are created using: (1) a Naïve approach; (2) Holt-Winters exponential smoothing (HW); (3) growth rate (Growth); (4) moving average (MA); (5) autoregressive (AR); (6) autoregressive mo

SUBMITTER: Lynch CJ 

PROVIDER: S-EPMC7834853 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature