The time-series ages distribution of the reported COVID-2019 infected people suggests the undetected local spreading of COVID-2019 in Hubei and Guangdong provinces before 19th Jan 2020 [article]

CHAO WU, min zheng
2020 medRxiv   pre-print
COVID-2019 is broken out in China. It becomes a severe public health disaster in one month. Find the period in which the spreading of COVID-2019 was overlooked, and understand the epidemiological characteristics of COVID-2019 in the period will provide valuable information for the countries facing the threats of COVID-2019. The most extensive epidemiological analysis of COVID-2019 shows that older people have lower infection rates compared to middle-aged persons. Common sense is that older
more » ... e prefer to report their illness and get treatment from the hospital compared to middle-aged persons. We propose a hypothesis that when the spreading of COVID-2019 was overlooked, we will find more older cases than the middle-aged cases. At first, we tested the hypothesis with 4597 COVID-2019 infected samples reported from 26th Nov 2019 to 17th Feb 2020 across the mainland of China. We found that 19th Jan 2020 is a critical time point. Few samples were reported before that day, and most of them were older ones. Then samples were explosively increased after that day, and many of them were middle-aged people. We have demonstrated the hypothesis to this step. Then, we grouped samples by their residences(provinces). We found that, in the provinces of Hubei and Guangdong, the ages of samples reported before 19th Jan 2020 are significantly higher than the ages of samples reported after that day. It suggests the COVID-2019 may be spreading in Hubei and Guangdong provinces before 19th Jan 2020 while people were unconscious of it. At last, we proposed that the ages distribution of each-day-reported samples could serve as a warning indicator of whether all potential COVID-2019 infected people are found. We think the power of our analysis is limit because 1. the work is data-driven, and 2. only ~5% of the COVID-2019 infected people in China are included in the study. However, we believe it still shows some value for its ability to estimate the possible unfound COVID-2019 infected people.
doi:10.1101/2020.03.28.20040204 fatcat:yksulfxknrcaxandqdxv62kxxq