Analysis of the Transmissibility Change of 2019-Novel Coronavirus Pneumonia and Its Potential Factors in China from 2019 to 2020

Abstract

Background. Recently, a large-scale novel coronavirus pneumonia (NCP) outbreak swept China. As of Feb. 9, 2020, a total of 40,260 patients have been diagnosed with NCP, and 23,589 patients were suspected to have infected by the 2019 novel coronavirus (COVID-19), which puts forward a great challenge for public health and clinical treatment in China. Until now, we are in the high-incidence season of NCP. Thus, the analysis of the transmissibility change of NCP and its potential factors may provide a reliable reference for establishing effective prevention and control strategies. Method. By means of the method of calculating the instantaneous basic reproduction number R0t proposed by Cori et al. (2013), we use R0t to describe the transmissibility change of COVID-19 in China, 2019-2020. In addition, the Baidu Index (BDI) and Baidu Migration Scale (BMS) were selected to measure the public awareness and the effect of Wuhan lockdown (restricted persons in Wuhan outflow from the epidemic area) strategy, respectively. The Granger causality test (GCT) was carried out to explore the association between public awareness, the effect of the Wuhan lockdown strategy, and the transmissibility of COVID-19. Results. The estimated averaged basic reproduction number of NCP in China was 3.44 with 95% CI (2.87, 4.0) during Dec. 8, 2019, to Feb. 9, 2020. The instantaneous basic reproduction numbers (R0t) have two waves and reaching peaks on Jan. 8 and Jan. 27, respectively. After reaching a peak on Jan. 27, R0t showed a continuous decline trend. On Feb. 9, R0t has fallen to 1.68 (95% CI: 1.66, 1.7), but it is still larger than 1. We find a significantly negative association between public awareness and the transmissibility change of COVID-19, with one unit increase in cumulative BDI leading to a decrease of 0.0295% (95% CI: 0.0077, 0.051) R0t. We also find a significantly negative association between the effect of the Wuhan lockdown strategy and the transmissibility change of COVID-19, and a one unit decrease in BMS may lead to a drop of 2.7% (95% CI: 0.382, 4.97) R0t. Conclusion. The current prevention and control measures have effectively reduced the transmissibility of COVID-19; however, R0t is still larger than the threshold 1. The results show that the government adopting the Wuhan lockdown strategy plays an important role in restricting the potential infected persons in Wuhan outflow from the epidemic area and avoiding a nationwide spread by quickly controlling the potential infection in Wuhan. Meanwhile, since Jan. 18, 2020, the people successively accessed COVID-19-related information via the Internet, which may help to effectively implement the government’s prevention and control strategy and contribute to reducing the transmissibility of NCP. Therefore, ongoing travel restriction and public health awareness remain essential to provide a foundation for controlling the outbreak of COVID-19.

Could the ambient higher temperature decrease the transmissibility of COVID-19 in China?

“…In China, quarantine measures are the most stringent in the world, as well as earliest, the whole city of Wuhan was lockdown on January 23 [25], followed by Hubei and the other provinces. During policy implementation period, most people stay at home during the outbreak and maintain social distance outside, which could effectively reduce the spread of COVID-19 [26]. Thus, the rising temperature from January to February accordingly in China may form a false conclusion of the temperature-morbidity relationship.…”

Could the Ambient Higher Temperature Decrease the Transmissibility of COVID-19 in China?

“…In China, quarantine measures are the most stringent in the world, as well as earliest, the whole city of Wuhan was lockdown on January 23 [25], followed by Hubei and the other provinces. During policy implementation period, most people stay at home during the outbreak and maintain social distance outside, which could effectively reduce the spread of COVID-19 [26]. Thus, the rising temperature from January to February accordingly in China may form a false conclusion of the temperature-morbidity relationship.…”

An AHP-based regional COVID-19 vulnerability model and its application in China

“…As regards the determination of the R0 value, there is a big difference between the different prevention measures and the different medical treatment levels for the same infectious disease, which means that the R0 value in the same region will change as the epidemic develops and the local prevention and control measures are implemented, accordingly (Wu et al 2020b ; Li et al 2020 ; Yadav et al 2020 ; Zhao et al 2020c ; Yue et al 2020 ; Stedman et al 2020 ; Peng et al 2020 ). Hence, the present work refers mainly to the data provided by WHO when a relevant decision needs to be made.…”