MOVING AVERAGE AS A SIMPLE INDICATOR TO PREVISE THE TREND OF PANDEMIC CASES TO EVALUATE CONTROL INTERVENTION: STUDY FROM -ONE-YEAR COVID-19 IN INDONESIA

Abstract

The cases of Coronavirus disease 2019 (COVID-19) in Indonesia increased exponentially and spread rapidly. The Indonesian government has made various efforts to control the spread. Several methods and mathematical models are also proposed to predict and demonstrate how COVID-19 cases will develop. This study proposes an evaluation method by utilizing the movement of the moving average (MA) around the real-time growth of case data so that it can further detect which interventions and control efforts require immediate improvement. This study employed data on daily COVID-19 cases in Indonesia from the beginning of the case until the case on 7 July 2021. Adjusted case data were employed as the main data to produce MA data and as an indicator to project future case growth. The COVID-19 cases in Indonesia occur in several phases: the delayed phase (very slow case development), the flattened phase of the curve (flat case), the exponential phase until the end of October 2020, the decline phase (downwards in all MA lines), and the return to the exponential phase with a more progressive increase from the previous phase. However, the direction of the decline case reoccurred after the first vaccination. The results of the decomposition analysis show an increasing trend and no influence of the seasonal factor on the fluctuating number of cases. The moving average can strongly detect the movement direction of cases during the COVID-19 pandemic and is applicable as an indicator to evaluate case-control efforts and other pandemic cases.