To Procrastinate or Not to Procrastinate: A Retrospective Study of the Optimal Timing of Containing the Global Spread of the COVID-19 Pandemic.

As global public health is under threat by the 2019-nCoV and a potential new wave of large-scale epidemic outbreak and spread is looming, an imminent question to ask is what the optimal strategy of epidemic prevention and control (P&C) measures would be, especially in terms of the timing of enforcing aggressive policy response so as to maximize health efficacy and to contain pandemic spread. Based on the current global pandemic statistic data, here we developed a logistic probability function configured SEIR model to analyse the COVID-19 outbreak and estimate its transmission pattern under different "anticipate- or delay-to-activate" policy response scenarios in containing the pandemic. We found that the potential positive effects of stringent pandemic P&C measures would be almost canceled out in case of significantly delayed action, whereas a partially procrastinatory wait-and-see control policy may still be able to contribute to containing the degree of epidemic spread although its effectiveness may be significantly compromised compared to a scenario of early intervention coupled with stringent P&C measures. A laissez-faire policy adopted by the government and health authority to tackling the uncertainly of COVID19-type pandemic development during the early stage of the outbreak turns out to be a high risk strategy from optimal control perspective, as significant damages would be produced as a consequence.

Retrospect: The Outbreak Evaluation of COVID-19 in Wuhan District of China.

There were 27 novel coronavirus pneumonia cases found in Wuhan, China in December 2019, named as 2019-nCoV temporarily and COVID-19 formally by the World Health Organization (WHO) on the 11 February 2020. In December 2019 and January 2020, COVID-19 has spread on a large scale among the population, which brought terrible disaster to the life and property of the Chinese people. In this paper, we analyze the features and pattern of the virus transmission. Considering the influence of indirect transmission, a conscious-based Susceptible-Exposed-Infective-Recovered (SEIR) (C-SEIR) model is proposed, and the difference equation is used to establish the model. We simulated the C-SEIR model and key important parameters. The results show that (1) increasing people's awareness of the virus can effectively reduce the spread of the virus; (2) as the capability and possibility of indirect infection increases, the proportion of people being infected will also increase; (3) the increased cure rate can effectively reduce the number of infected people. Then, the virus transmission can be modelled and used for the inflexion and extinction period of pandemic development so as to provide theoretical support for the Chinese government in the decision-making of pandemic prevention and recovery of economic production. Further, this study has demonstrated the effectiveness of the prevention measures taken by the Chinese government such as multi-level administrative district isolation and public health awareness.

Random Network Transmission and Countermeasures in Containing Global Spread of COVID-19-Alike Pandemic: A Hybrid Modelling Approach

Since the outbreak of the novel coronavirus disease (COVID-19) at the beginning of December 2019, there have been more than 28.69 million cumulative confirmed cases worldwide as of 12th September 2020, affecting over 200 countries and regions with more than 920,463 deaths. The COVID-19 pandemic has been sweeping worldwide with unexpected rapidity. In this paper, a hybrid modelling strategy based on tessellation structure- (TS-) configured SEIR model is adopted to estimate the scale of the pandemic spread. Building on the data pertaining to the global pandemic transmission over the last six months around the world, key impact factors in the transmission and control procedure have been analysed, including isolation rate, number of the infected cases before taking prevention measures, degree of contact scope, and medical level, so as to capture the fundamental factor influencing the pandemic. The quantitative evaluation allowed us to illustrate the magnitude of risks of pandemic and to recommend appropriate national health policy of prevention measures for effectively controlling both intra- and interregional pandemic spread. Our modelling results clearly indicate that the early-stage preventive measures are the most effective action to be taken to contain the pandemic spread of the highly contagious nature of the COVID-19.

The global COVID-19 pandemic at a crossroads: relevant countermeasures and ways ahead.

BACKGROUND: Since the outbreak of novel coronavirus disease (COVID-19) in Wuhan, China at the beginning of December 2019, there have been over 11,200,000 confirmed cases in the world as of the 3rd July 2020, affecting over 213 countries and regions with nearly 530,000 deaths. The pandemic has been sweeping all continents, North America, Latin America, Europe, Middle East and South Asia among others at an alarming rapidity. Here, we provide an estimate of the scale of the pandemic spread under different scenarios of variation in key influencing parameters with a hybrid model. METHODS: We developed a new hybrid model of infectious disease transmission based on Cellular Automata (CA)-configured SEIR to analyse the COVID-19 outbreak and estimate its transmission pattern. A probabilistic contamination network is embedded in the pandemic transmission model to capture the randomness feature of person-to-person spread of the novel virus. We used the improved SEIR model to quantify the population contact state with isolation measures under different continuous time series contact probability via CA. We adjusted the modelling parameters to verify the model performance in accordance to the data from the reports published by the Chinese Center for Disease Control and Prevention. We simulated several scenarios by varying such key parameters as number of isolation rate, average contact times of the population, number of infected people before taking prevention and control measures, medical level and number of imported cases. RESULTS: In the baseline model, we identified that the isolation control as the most influencing factor that had the largest impact on decreasing the speed of the reproductive number, accelerating the arrival of the "inflection point" of pandemic prevention and control, and the death rate reduction. We estimated that the probability of people contacts and the number of the onset infected cases before prevention measures also had significant effect on the infection rate reduction with appropriate prevention measures adoption, which partly reflects the impact of timely measure on the severity of the outbreak. We found that imported cases will risk the domestic prevention. CONCLUSIONS: Our modelling results clearly indicate that early-stage preventive measures are the most effective way to contain the pandemic spread and a strong interventionist approach needs to be adopted by policymakers vis-à-vis of the highly contagious nature of the COVID-19. Human resources, intensified isolation and confinement as well as special hospital buildings should be prioritised in countries with large number of infections to constrain the global transmission of the virulent infection. To do so, internationally coordinated actions require to be taken to replicate good practices to less infected countries and regions immediately.