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Transmissibility of COVID-19 in 11 Major Cities in China and Its Guo et al. Infectious Diseases of Poverty (2020) 9:87 https://doi.org/10.1186/s40249-020-00708-0 RESEARCH ARTICLE Open Access Transmissibility of COVID-19 in 11 major cities in China and its association with temperature and humidity in Beijing, Shanghai, Guangzhou, and Chengdu Xiao-Jing Guo, Hui Zhang* and Yi-Ping Zeng Abstract Background: The new coronavirus disease COVID-19 began in December 2019 and has spread rapidly by human-to-human transmission. This study evaluated the transmissibility of the infectious disease and analyzed its association with temperature and humidity to study the propagation pattern of COVID-19. Methods: In this study, we revised the reported data in Wuhan based on several assumptions to estimate the actual number of confirmed cases considering that perhaps not all cases could be detected and reported in the complex situation there. Then we used the equation derived from the Susceptible-Exposed-Infectious-Recovered (SEIR) model to calculate R0 from January 24, 2020 to February 13, 2020 in 11 major cities in China for comparison. With the calculation results, we conducted correlation analysis and regression analysis between R0 and temperature and humidity for four major cities in China to see the association between the transmissibility of COVID-19 and the weather variables. Results: It was estimated that the cumulative number of confirmed cases had exceeded 45 000 by February 13, 2020 in Wuhan. The average R0 in Wuhan was 2.7, significantly higher than those in other cities ranging from 1.8 to 2.4. The inflection points in the cities outside Hubei Province were between January 30, 2020 and February 3, 2020, while there had not been an obvious downward trend of R0 in Wuhan. R0 negatively correlated with both temperature and humidity, which was significant at the 0.01 level. Conclusions: The transmissibility of COVID-19 was strong and importance should be attached to the intervention of its transmission especially in Wuhan. According to the correlation between R0 and weather, the spread of disease will be suppressed as the weather warms. Keywords: COVID-19, Transmissibility, Basic reproduction number, Temperature, Humidity *Correspondence: [email protected] Institute of Public Safety Research, Tsinghua University, 100084 Beijing, People’s Republic of China © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/)appliestothedatamade available in this article, unless otherwise stated in a credit line to the data. Guo et al. Infectious Diseases of Poverty (2020) 9:87 Page 2 of 13 Background [24]; and a regression equation was derived to show how On December 8, 2019, the first case of unexplained pneu- temperature, relative humidity, and wind velocity affected monia was officially reported in Wuhan, the capital of the transmission of SARS [25]. Thus we wonder if the Hubei Province in China [1]. There have been reports of spread of COVID-19 follows a similar pattern. Consid- the new coronavirus disease (coronavirus disease 2019, ering that R0 is useful for measuring the transmission COVID-19,namedbytheWorldHealthOrganizationon ability of infectious diseases, we conducted association February 11, 2020) since December 2019 [1, 2]. As was analyses between R0 and temperature, relative humidity, reported by the National Health Commission of the Peo- and absolute humidity respectively. Statistical methods ple’s Republic of China, the number of confirmed cases such as correlation and regression were adopted for the had reached 63 851 by February 13, 2020 in China, includ- analysis. ing 1380 deaths. On the same day, Hubei Province alone This paper measured the transmissibility of COVID- totally had 51 986 confirmed cases including 1318 deaths, 19 with R0 and analyzed its correlation with temperature accounting for 81.4% and 95.5% of the whole country and humidity. First, we revised the epidemiological data respectively. Among them there were 35 991 confirmed in Wuhan to make R0 more accurate. Second, we calcu- cases and 1016 deaths in Wuhan, accounting for 69.2% lated R0 and compared the average value and developing and 77.1% of the number in Hubei Province respectively trend of R0 in 11 cities including Wuhan. Third, we con- [3]. The cumulative number of confirmed cases keeps ris- ducted correlation and regression analysis between R0 and ing, indicating the strong transmissibility of COVID-19, temperature and humidity to see the association between especially in Wuhan, Hubei Province. Therefore, it is of R0 and weather. great importance to adopt reasonable indicators to assess the transmission ability of the disease, based on which Methods effective intervention and control measures could be put Data acquisition and preprocessing forward [4, 5]. The daily accumulative number of confirmed cases and The basic reproduction number (R0) refers to the new additions are reported by the National Health Com- expected number of cases generated from a single case mission of the People’s Republic of China as well as the when all people are susceptible to infection [6]. It is widely health commission of each province on the official web- used to evaluate the transmission ability of an emerging site. An R package has been developed to access the infectious disease and determine what degree of control epidemiological data directly [26]. The R package was measures should be taken to eradicate the disease [7– used by us to acquire the number of total cases and 10]. When R0 > 1, the disease starts to spread; and new additions from January 18, 2020 to February 13, when R0 < 1, the disease is effectively controlled [11]. 2020 in Wuhan, Hubei Province considering that the sit- R0 is influenced by many other factors except for the uation there was complex and needed much attention. characteristics of the disease itself, such as conditions Besides, we also collected the daily-reported accumula- of the environment, policies of the government, peo- tive number of confirmed cases from January 24, 2020 ple’s awareness of infectious diseases, and social behavior. to February 13, 2020 in 10 Chinese major cities outside Therefore, we can use R0 to measure the transmissibility Hubei Province including Beijing, Chengdu, Chongqing, of COVID-19 and analyze its influencing factors, which Guangzhou, Hangzhou, Hefei, Nanjing, Shanghai, Shen- provides data support for suggestion-proposing and zhen, and Zhengzhou (listed by initials) for further calcu- decision-making. lation, estimation, and analysis. The reasons for selecting Research on transmissible diseases like influenza [12], those 10 cities were that they were first-tier cities or capi- severe acute respiratory syndrome (SARS) [13] and Mid- tal cities in China with the top number of cases. Certainly, dle East respiratory syndrome (MERS) [14]hasfoundthat Wuhan also met the criteria. Those cities could well rep- disease transmission is associated with temperature and resent the process status of the disease based on which humidity of the environment [15–20]. In terms of bio- disposal measures could be put forward. logical methods, influenza virus spread was found to be As for Wuhan, it was estimated by Imperial College promoted by cold temperature and low relative humid- London, UK that the total number of confirmed diagnoses ity with the guinea pig as a model host [21]; besides, an had reached 4000 by January 18, 2020 [27], which was experiment on the SARS coronavirus indicated that high much higher than the officially reported number. So we temperature and high humidity suppressed the spread attempted to revise the data in Wuhan to infer the actual of the virus [22]; similarly, MERS coronavirus was more transmissibility of the new coronavirus. With the substan- stable when temperature or humidity was lower [23]. In tial enhancement of case detection and reporting, the dif- terms of statistical methods, case studies of SARS in four ferences between the official numbers and the estimates major cities in China suggested that the transmissibility are predicted to be fewer and fewer. There are several had a close relationship with temperature and its variation assumptions for the data-preprocessing procedure: Guo et al. Infectious Diseases of Poverty (2020) 9:87 Page 3 of 13 1) The first case appeared on December 8, 2019 in Calculation of the basic reproduction number Wuhan and transmission started from that day on The basic reproduction number indicates the average [1, 28]. number of people infected by a patient during the infec- 2) The cumulative number of cases Y(t) by day t since tious period in the absence of control interventions [6]. the first single case followed the exponential function It is also denoted R0, which measures the transmissibility Y(t) = eλt in early development [29]. of infectious diseases. There are several ways to esti- 3) The cumulative number of cases on January 18, 2020 mate R0, including formula derivation [30, 31] and model was 4000, that was, Y(41) = 4000 [27]. fitting [32–34]. 4) From February 13, 2020 on, all cases in Wuhan can We describe the transmission pattern of COVID- be confirmed and the number of daily new cases is 19 with the Susceptible-Exposed-Infectious-Recovered correct, given that the number of newly confirmed (SEIR) model.
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