After 2019 novel cornavirus disease (COVID-19) appeared in Wuhan in early December 2019, it broke out in mid-to-late January 2020 and quickly spread throughout the country. So far, it has spread in dozens of countries and regions, the scientific and efficient understanding of epidemic development is essential for prevention and control. The number of infected people is a key indicator for assessing the situation of the epidemic, helping decision-makers formulate policies in time. This paper uses the maximum likelihood estimation method to obtain estimators of the number of newly infected people across the country except Hubei province. Moreover, Bootstrap simulation enables us to obtain confidence intervals for the estimators. Based on these solutions of the model, we further calculate the number of existing infected but undiagnosed people and predict the trend of the newly diagnosed for the next few days, providing suggestions on returning to work.
DING Zhiwei, LIU Yanyun, KONG Jing, ZHANG Hong, ZHANG Yi, DAI Yuhong, YANG Zhouwang
. A probability model for estimating the expected number of the newly infected and predicting the trend of the diagnosed[J]. Operations Research Transactions, 2020
, 24(1)
: 1
-12
.
DOI: 10.15960/j.cnki.issn.1007-6093.2020.01.001
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