Yongli Cai

Bio: Yongli Cai is an academic researcher. The author has contributed to research in topics: Computer science & Biology. The author has an hindex of 11, co-authored 18 publications receiving 1196 citations.

Estimating the Serial Interval of the Novel Coronavirus Disease (COVID-19): A Statistical Analysis Using the Public Data in Hong Kong From January 16 to February 15, 2020

Abstract: Background: The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a large outbreak of novel coronavirus disease (COVID-19) since the end of 2019 As of February 15, there were 56 COVID-19 cases confirmed in Hong Kong since the first case with symptom onset on January 23, 2020 Methods: Based on the publicly available surveillance data in Hong Kong, we identified 21 transmission events as of February 15, 2020 An interval censored likelihood framework is adopted to fit three different distributions including Gamma, Weibull, and lognormal, that govern the serial interval (SI) of COVID-19 We selected the distribution according to the Akaike information criterion corrected for small sample size (AICc) Findings: We found the lognormal distribution performed slightly better than the other two distributions in terms of the AICc Assuming a lognormal distribution model, we estimated the mean of SI at 4 9 days (95% CI: 3 6–6 2) and SD of SI at 4 4 days (95% CI: 2 9–8 3) by using the information of all 21 transmission events Conclusion: The SI of COVID-19 may be shorter than the preliminary estimates in previous works Given the likelihood that SI could be shorter than the incubation period, pre-symptomatic transmission may occur, and extra efforts on timely contact tracing and quarantine are crucially needed in combating the COVID-19 outbreak © Copyright © 2020 Zhao, Gao, Zhuang, Chong, Cai, Ran, Cao, Wang, Lou, Wang, Yang, He and Wang

Quantifying the association between domestic travel and the exportation of novel coronavirus (2019-nCoV) cases from Wuhan, China in 2020: a correlational analysis.

Abstract: Quantifying the association between domestic travel and the exportation of novel coronavirus (2019-nCoV) cases from Wuhan, China in 2020: a correlational analysis Shi Zhao1,2, Zian Zhuang3, Peihua Cao4, Jinjun Ran5, Daozhou Gao6, Yijun Lou3, Lin Yang7, Yongli Cai8, Weiming Wang8, Daihai He3,*, and Maggie H. Wang1,2 JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China, Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China, Department of AppliedMathematics, Hong Kong Polytechnic University, Hong Kong, China, Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, China, School of Public Health, Li Ka Shing Faculty ofMedicine, University of Hong Kong, Hong Kong, China, Mathematics and Science College, Shanghai Normal University, Shanghai, China, School of Nursing, Hong Kong Polytechnic University, Hong Kong, China and Department of Mathematics, Huaiyin Normal University, Huai’an, China

The effect of the fear factor on the dynamics of a predator-prey model incorporating the prey refuge

Abstract: In this paper, we investigate the dynamics of an improved Leslie-Gower predator-prey model which is characterized by the reduction of the prey growth rate due to fear of the predator (i.e., antipredator behavior). The value of this study lies in two aspects: mathematically, (i) it provides the existence and the stability of the positive equilibrium; (ii) it gives the existence of the Hopf bifurcation and limit cycle; and (iii) it shows the mechanisms of the fear factor and the prey refuge on the level of the positive equilibrium. Biologically, we find that the influence of the fear factor is complex: (i) increasing the level of fear can cause the level of the population density to decrease and the prey to become extinct; (ii) the effect of the cost of fear on the stability of the positive equilibrium is rich and complex: it can either destabilize the stability and benefit the emergency of the periodic behavior or stabilize the system by excluding the existence of periodic solutions; (iii) with a fixed level of fear, the prey refuge is beneficial to the coexistence of the prey and the predator, and with the increase of the level of the prey refuge, the positive equilibrium may change from stable spiral sink to unstable spiral source to stable spiral sink. These results may enrich the dynamics of the predator-prey systems.

The effect of human mobility and control measures on the COVID-19 epidemic in China.

Abstract: The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.

Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy.

Abstract: In Italy, 128,948 confirmed cases and 15,887 deaths of people who tested positive for SARS-CoV-2 were registered as of 5 April 2020. Ending the global SARS-CoV-2 pandemic requires implementation of multiple population-wide strategies, including social distancing, testing and contact tracing. We propose a new model that predicts the course of the epidemic to help plan an effective control strategy. The model considers eight stages of infection: susceptible (S), infected (I), diagnosed (D), ailing (A), recognized (R), threatened (T), healed (H) and extinct (E), collectively termed SIDARTHE. Our SIDARTHE model discriminates between infected individuals depending on whether they have been diagnosed and on the severity of their symptoms. The distinction between diagnosed and non-diagnosed individuals is important because the former are typically isolated and hence less likely to spread the infection. This delineation also helps to explain misperceptions of the case fatality rate and of the epidemic spread. We compare simulation results with real data on the COVID-19 epidemic in Italy, and we model possible scenarios of implementation of countermeasures. Our results demonstrate that restrictive social-distancing measures will need to be combined with widespread testing and contact tracing to end the ongoing COVID-19 pandemic.

The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China

Abstract: BACKGROUND With its epicenter in Wuhan, China, the COVID-19 outbreak was declared a Public Health Emergency of International Concern by the World Health Organization (WHO). Consequently, many countries have implemented flight restrictions to China. China itself has imposed a lockdown of the population of Wuhan as well as the entire Hubei province. However, whether these two enormous measures have led to significant changes in the spread of COVID-19 cases remains unclear. METHODS We analyzed the available data on the development of confirmed domestic and international COVID-19 cases before and after lockdown measures. We evaluated the correlation of domestic air traffic to the number of confirmed COVID-19 cases and determined the growth curves of COVID-19 cases within China before and after lockdown as well as after changes in COVID-19 diagnostic criteria. RESULTS Our findings indicate a significant increase in doubling time from 2 days (95% CI: 1.9-2.6) to 4 days (95% CI: 3.5-4.3), after imposing lockdown. A further increase is detected after changing diagnostic and testing methodology to 19.3 (95% CI: 15.1-26.3), respectively. Moreover, the correlation between domestic air traffic and COVID-19 spread became weaker following lockdown (before lockdown: r = 0.98, P < 0.05 vs after lockdown: r = 0.91, P = NS). CONCLUSIONS A significantly decreased growth rate and increased doubling time of cases was observed, which is most likely due to Chinese lockdown measures. A more stringent confinement of people in high risk areas seems to have a potential to slow down the spread of COVID-19.

Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures.

Abstract: The spread of coronavirus disease 2019 (COVID-19) in Italy prompted drastic measures for transmission containment. We examine the effects of these interventions, based on modeling of the unfolding epidemic. We test modeling options of the spatially explicit type, suggested by the wave of infections spreading from the initial foci to the rest of Italy. We estimate parameters of a metacommunity Susceptible-Exposed-Infected-Recovered (SEIR)-like transmission model that includes a network of 107 provinces connected by mobility at high resolution, and the critical contribution of presymptomatic and asymptomatic transmission. We estimate a generalized reproduction number ([Formula: see text] = 3.60 [3.49 to 3.84]), the spectral radius of a suitable next-generation matrix that measures the potential spread in the absence of containment interventions. The model includes the implementation of progressive restrictions after the first case confirmed in Italy (February 21, 2020) and runs until March 25, 2020. We account for uncertainty in epidemiological reporting, and time dependence of human mobility matrices and awareness-dependent exposure probabilities. We draw scenarios of different containment measures and their impact. Results suggest that the sequence of restrictions posed to mobility and human-to-human interactions have reduced transmission by 45% (42 to 49%). Averted hospitalizations are measured by running scenarios obtained by selectively relaxing the imposed restrictions and total about 200,000 individuals (as of March 25, 2020). Although a number of assumptions need to be reexamined, like age structure in social mixing patterns and in the distribution of mobility, hospitalization, and fatality, we conclude that verifiable evidence exists to support the planning of emergency measures.