Three potential challenges in studying COVID-19 pandemic data: Chinese statistics social media and preprint servers

摘要

Coronavirus (COVID-19), which started in Wuhan, China, in early December 2019, has now become the biggest challenge to health for almost all countries in the world. On January 31, 2020, the WHO declared COVID-19 a public health emergency, and then on March 11, COVID-19 was officially declared a pandemic. To overcome this worldwide outbreak, scientists and health policy makers around the world have tried to implement prevention strategies (e.g., home isolation, travel restrictions, social distancing, etc.) or have begun research projects for the development of a vaccine and new drugs against this novel coronavirus. Many studies are already focusing on the epidemic, the mechanism of the novel coronavirus, the medication, the epidemiology of infection, etc., and most scientific journals have begun fast-tracking manuscripts regarding COVID-19; many papers have been published since the epidemic began. However, there are some challenges (despite financial resources or the complexity and unknown nature of the virus) which could potentially lead to misleading and incorrect results and decisions. The first challenge is the Chinese statistics; the first report of COVID-19, the statistics of infected persons and mortality, fatality rates, and then the first published manuscripts all came from China and is being used as the basic information on the epidemiology of the novel coronavirus. Now, however, new criticism has been raised against the Chinese reports. The Chinese information (specifically, numbers of infected and death cases) is clouded by a fog of skewed data, political imperatives, and unreported cases and possibly deaths. The underestimation of Chinese statistics is not just a claim; at the start of the epidemic in Wuhan, it was predicted that the most plausible number of infected cases was in the thousands (rather than the hundreds reported by Chinese authorities), and even this is likely an underestimate (1). Therefore, this skeptical data put other nations at risk in adequately understanding and preparing for the disease and caused researchers and policymakers to underestimate the fatality and severity of the epidemic.