Adaptive behaviors and vaccination on curbing COVID-19 transmission: Modeling simulations in eight countries.

Current persistent outbreak of COVID-19 is triggering a series of collective responses to avoid infection. To further clarify the impact mechanism of adaptive protection behavior and vaccination, we developed a new transmission model via a delay differential system, which parameterized the roles of adaptive behaviors and vaccination, and allowed to simulate the dynamic infection process among people. By validating the model with surveillance data during March 2020 and October 2021 in America, India, South Africa, Philippines, Brazil, UK, Spain and Germany, we quantified the protection effect of adaptive behaviors by different forms of activity function. The modeling results indicated that (1) the adaptive activity function can be used as a good indicator for fitting the intervention outcome, which exhibited short-term awareness in these countries, and it could reduce the total human infections by 3.68, 26.16, 15.23, 4.23, 7.26, 1.65, 5.51 and 7.07 times, compared with the reporting; (2) for complete prevention, the average proportions of people with immunity should be larger than 90%, 92%, 86%, 71%, 92%, 84%, 82% and 76% with adaptive protection behaviors, or 91%, 97%, 94%, 77%, 92%, 88%, 85% and 90% without protection behaviors; and (3) the required proportion of humans being vaccinated is a sub-linear decreasing function of vaccine efficiency, with small heterogeneity in different countries. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination.

We developed a mechanism model which allows for simulating the novel coronavirus (COVID-19) transmission dynamics with the combined effects of human adaptive behaviours and vaccination, aiming at predicting the end time of COVID-19 infection in global scale. Based on the surveillance information (reported cases and vaccination data) between 22 January 2020 and 18 July 2022, we validated the model by Markov Chain Monte Carlo (MCMC) fitting method. We found that (1) if without adaptive behaviours, the epidemic could sweep the world in 2022 and 2023, causing 3.098 billion of human infections, which is 5.39 times of current number; (2) 645 million people could be avoided from infection due to vaccination; and (3) in current scenarios of protective behaviours and vaccination, infection cases would increase slowly, levelling off around 2023, and it would end completely in June 2025, causing 1.024 billion infections, with 12.5 million death. Our findings suggest that vaccination and the collective protection behaviour remain the key determinants against the global process of COVID-19 transmission.

The spatiotemporal transmission dynamics of COVID-19 among multiple regions: a modeling study in Chinese provinces.

Current explosive outbreak of COVID-19 around the world is a complex spatiotemporal process with hidden interactions between viruses and humans. This study aims at clarifying the transmission patterns and the driving mechanism that contributed to the COVID-19 prevalence across the provinces of China. Thus, a new dynamical transmission model is established by an ordinary differential system. The model takes into account the hidden circulation of COVID-19 virus among/within humans, which incorporates the spatial diffusion of infection by parameterizing human mobility. Theoretical analysis indicates that the basic reproduction number is a unique epidemic threshold, which can unite infectivity in each region by human mobility and can totally determine whether COVID-19 proceeds among multiple regions. By validating the model with real epidemic data in China, it is found that (1) if without any intervention, COVID-19 would overrun China within three months, resulting in more than 1.1 billion clinical infections and 0.2 billion subclinical infections; (2) high frequency of human mobility can trigger COVID-19 diffusion across each province in China, no matter where the initial infection locates; (3) travel restrictions and other non-pharmaceutical interventions must be implemented simultaneously for disease control; and (4) infection sites in central and east (rather than west and northeast) of China would easily stimulate quick diffusion of COVID-19 in the whole country. Supplementary Information: The online version supplementary material available at 10.1007/s11071-021-07001-1.

The spatiotemporal transmission dynamics of COVID-19 among multiple regions: a modeling study in Chinese provinces

Current explosive outbreak of COVID-19 around the world is a complex spatiotemporal process with hidden interactions between viruses and humans. This study aims at clarifying the transmission patterns and the driving mechanism that contributed to the COVID-19 prevalence across the provinces of China. Thus, a new dynamical transmission model is established by an ordinary differential system. The model takes into account the hidden circulation of COVID-19 virus among/within humans, which incorporates the spatial diffusion of infection by parameterizing human mobility. Theoretical analysis indicates that the basic reproduction number is a unique epidemic threshold, which can unite infectivity in each region by human mobility and can totally determine whether COVID-19 proceeds among multiple regions. By validating the model with real epidemic data in China, it is found that (1) if without any intervention, COVID-19 would overrun China within three months, resulting in more than 1.1 billion clinical infections and 0.2 billion subclinical infections;(2) high frequency of human mobility can trigger COVID-19 diffusion across each province in China, no matter where the initial infection locates;(3) travel restrictions and other non-pharmaceutical interventions must be implemented simultaneously for disease control;and (4) infection sites in central and east (rather than west and northeast) of China would easily stimulate quick diffusion of COVID-19 in the whole country. Supplementary Information The online version supplementary material available at 10.1007/s11071-021-07001-1.

Modeling coupling dynamics between the transmission, intervention of COVID-19 and economic development.

Current explosive outbreak of the novel coronavirus (COVID-19) pandemic is posing serious threats to public health and economics around the world. To clarify the coupling mechanism between this disease and economic development, a new dynamical system is established by ordinary differential equations (ODEs). It is theoretically proved that the basic reproduction number is a nonlinear combination of parameters regarding disease transmission, intervention and economy effect, which totally determines the stability of the disease-free and endemic equilibria. Further analyses indicate the existence of interaction and mutual restraint among transmissibility, quarantine and economics, in which (1) COVID-19 would cause a long-term impact on halting economic progress; (2) strong coupling of COVID-19 and economics would easily trigger disease outbreak, cause more human infections and alleviate the intervention effects of quarantine; and (3) there exists optimal strategy of time-varying quarantine for disease control and economic development. It is highlighted that adaptive isolation (rather than constant isolation) of at-risk population (rather than random individuals) is highly effective in reducing morbidity at the cost of least economic loss.

Population Movement, City Closure in Wuhan, and Geographical Expansion of the COVID-19 Infection in China in January 2020.

BACKGROUND: The unprecedented outbreak of corona virus disease 2019 (COVID-19) infection in Wuhan City has caused global concern; the outflow of the population from Wuhan was believed to be a main reason for the rapid and large-scale spread of the disease, so the government implemented a city-closure measure to prevent its transmission considering the large amount of travel before the Chinese New Year. METHODS: Based on the daily reported new cases and the population-movement data between 1 and 31 January, we examined the effects of population outflow from Wuhan on the geographical expansion of the infection in other provinces and cities of China, as well as the impacts of the city closure in Wuhan using different closing-date scenarios. RESULTS: We observed a significantly positive association between population movement and the number of the COVID-19 cases. The spatial distribution of cases per unit of outflow population indicated that the infection in some areas with a large outflow of population might have been underestimated, such as Henan and Hunan provinces. Further analysis revealed that if the city-closure policy had been implemented 2 days earlier, 1420 (95% confidence interval, 1059-1833) cases could have been prevented, and if 2 days later, 1462 (1090-1886) more cases would have been possible. CONCLUSIONS: Our findings suggest that population movement might be one important trigger for the transmission of COVID-19 infection in China, and the policy of city closure is effective in controlling the epidemic.