key: cord-0682950-ft397bbz
authors: Wang, Ligui; Chen, Hui; Qiu, Shaofu; Song, Hongbin
title: Evaluation of control measures for COVID-19 in Wuhan, China
date: 2020-04-10
journal: J Infect
DOI: 10.1016/j.jinf.2020.03.043
sha: 0db2f215fcb66b6d4fb6fe039b2878ee8affd740
doc_id: 682950
cord_uid: ft397bbz

nan

Letter to the Editor

Recent article in this Journal has reported trend of the coronavirus disease in China. 1 The outbreak of COVID-19 was first reported from Wuhan, China, had spread to more than 100 countries. 2 Recent studies had forecasted COVID-19 incidence in China and worldwide based on mathematical models, 3 , 4 but they did not take into account the control measures adopted by the Chinese government; the forecast results were appreciably higher than actual numbers. For instance, the article forecasted that the number of infections in Wuhan would reach 75,815 on January 25, 2020, but the actual number was simply 618. 3 Therefore, it is indispensable to establish a new dynamic model of the epidemic to evaluate the effectiveness of control measures in Wuhan ( Fig. 1 ) .

In our study, we used data released by the National Health Commission. 5 Since the data were not updated from January 1 to January 17, we used data from January 18 to February 13 to establish our model. Epidemic prevention and control in Wuhan can be divided into three stages: the first stage was the natural occurrence and spread of the epidemic from January 18 to January 23; the second stage was the blockade of Wuhan and the advocacy of residents going out less from January 23 to February 5; and the third stage was cabin hospitals put into use from February 6 to February 13 to ensure that all cases are admitted to hospitals and close contacts are under intensive medical observation. We used the susceptible-exposed-infected-removed (SEIR) dynamic model 6 to simulate the spread of the epidemic and Simulated Annealing (SA) algorithm to identify optimal parameters. 7 The formula of SEIR model is as follows: 

The susceptible, exposed, infected, and r removed populations at time t were set as S (t), E (t), I (t), and R (t), respectively, and the total population in Wuhan was set as N. The number of the susceptible infected by each infected person per unit time (d) was set as α1, and by each exposed person, α2. Moreover, according to the literature, the incubation period was 1/ β = 4 d, 8 and the infection period was 1/ γ = 3.5 d. 9 After adopting control measures, the number of susceptible infected by each infected person per unit time (d) was set as C * α1, and by each exposed person, C * α2. The optimal parameters of the model found out through SA algorithm.

The goodness of fit between the forecast value and the actual incidence was 81.98%, suggesting that our model can reflect the actual incidence and spread of the epidemic. Based on this model, we calculated the basic reproduction number in Wuhan, R 0 = 3.31, the effective reproduction number of the second stage, R T = 1.12, and the effective reproduction number of the second stage, R T = 0.71 (R T < 1, the inflection point of the epidemic appeared and the incidence began to decline).

In this article, the effectiveness of control measures at different stages of COVID-19 in Wuhan was evaluated for the first time. The results showed that the effective reproduction number after blockade of the city was R T = 1.12, showing that blockade reduced transmission of infection by 66.16%. Although the adopted prevention and control measureswere effective, the effective reproduction number remained greater than 1, indicating that the epidemic continues to spread. This could be attributable to medical limitations: not all patients could be admitted to hospitals, and close contacts were mainly isolated at home, resulting in family outbreaks. Since February 6, cabin hospitalshave been put into use to ensure that all cases are admitted to hospitals and close contacts are under intensive medical observation. Consequently, the effective reproduction number has decreased to less than 1 (R T = 0 • 71), indicating the inflection point of the epidemic; thus, the incidence of the disease will gradually decrease until its disappearance.

The authors declare that they have no competing interests.

This work was financially supported by grants from the China Mega-Project on Infectious Disease Prevention (No. 2017ZX10303401).

Trend and forecasting of the COVID-19 outbreak in China

World Health Organization. Coronavirus disease (COVID-2019) situation reports -50

Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study

Estimating the unreported number of novel coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A data-driven Modelling analysis of the early outbreak

National Health Commission of the People's Republic of China

Extension and verification of the SEIR model on the 2009 influenza A (H1N1) pandemic in Japan

Optimization by simulated annealing

Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China:retrospective case series

Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia

Hongbin Song * Center for Disease Control and Prevention of Chinese People's Liberation Army, 20 Dong-Da-Jie Street