A data capture model and its associate study on the public web published COVID-19 data

Abstract

Background and Objective: The Coronavirus Disease 2019 pandemic situation is remaining severe worldwide. A single outbreak data source is not adequate for comprehensive analyses of the response to the pandemic. Such analyses need to seek proper integration of epidemic data for subsequent statistical analyses. Methods: 1) Considering reputations of publishers, activities, public users' accessibility, and retrievable historical data among several platforms, the World Health Organization (WHO), the US Centers for Disease Control (CDC), and Baidu's Real-time Epidemics (BRE) websites were selected as our data sources. 2) Data for 32 weeks until August 15th, 2020, were followed, including the US cumulative confirmed cases (CCCs), cumulative death cases (CDCs), cumulative discharged or cured cases (CD\vert CCs), daily new infective confirmed cases (DNCCs), and daily new death cases (DNDCs). 3) Estimators for the weekly current active infected confirm cases (CACs) and the weekly COVID19 fatal rate in the US hospitals (WFRUSH) were derived. Graphic display modules demonstrated the risks associated with demographic data. Results: 1) CCCs reached 5,285,546 cases in the US on August 15th, 2020, which initially climbed from the 9th-11th week; the CDCs were 167,546. The fatality rate initially climbed from the 12th-13th week, but fast turned over to decrease from the 18th week, then gradually flattened out near 3.17% till the mid of August 2020. 2) The WFRUSH first rose sharply at the 10th-11th week and started to decline in the 12th week, although there was a repeated smaller fluctuation in the 13th-14th week, during the generally downward process. 3) The US demographic characteristics and CDCs showed that the proportion of fatal cases in the senior Americans (age group over 65) accounted was 78.8%, about 4 (3.83) times the proportions of the other age groups. Supposed the death cases of seniors, directly caused by the COVID-19 rather than caused by the fundamental diseases, the \gamma value of the seniors, a ratio between the senior CDCs proportion over the senior population proportion was 4.81. Such a \gamma value for seniors, indicated a much higher fatality risk than other age groups. Conclusion: Integrative capture data from the publicly web-published COVID-19 statistics helps extend analyzable data and estimate or derive new-useful indicators CACs, WFRUSH, and \gamma value for the demographic group. As of the including the working population age of over 45, would have a much higher fatality rate than younger ages. It seemed necessary to study further if these death were caused directly by the COVID-19. Additionally, the African Americans, and male Americans, had relatively higher fatality rates. These high risks require more attention to strengthening health prevention; including the working-age population, even although the WFRUSH as a more appropriate and vital indication becomes stable to a low level after July 2020, meaning the clinical interventions and treatments were improved, or the virus fatality power was declined.