摘要：Each country has been racing to contain the spread of COVID-19. The published data of daily infection and death cases can be used to measure the effectiveness of the control interventions. We focus our study in two Southeast Asia countries: Indonesia and Malaysia during period between March and November 2020. Newcomb-Benford law has been commonly used to analyze the probabilities of the first significant digits in natural occurrences since the late 19th century. It is a prominent statistical tool for its capability to detect frauds in datasets. A chi-squared test was recruited to quantify the closeness of the data and Newcomb-Benford law distributions. The results revealed that the distributions of daily infection and death cases in Indonesia followed Newcomb-Benford law while the opposite results were obtained for Malaysia. We have done the analysis of verifying the daily COVID-19 infection and death cases in Indonesia and Malaysia using Newcomb-Benford law. It can be inferred that, between March and November 2020, the control interventions in Indonesia was less effective compared to Malaysia.
