Mechanisms of recurrent outbreak of COVID-19: a model-based study

Abstract

Recurrent outbreaks of the coronavirus disease 2019 (COVID-19) have occurred in many countries around the world. We developed a twofold framework in this study, which is composed by one novel descriptive model to depict the recurrent global outbreaks of COVID-19 and one dynamic model to understand the intrinsic mechanisms of recurrent outbreaks. We used publicly available data of cumulative infected cases from 1 January 2020 to 2 January 2021 in 30 provinces in China and 43 other countries around the world for model validation and further analyses. These time series data could be well fitted by the new descriptive model. Through this quantitative approach, we discovered two main mechanisms that strongly correlate with the extent of the recurrent outbreak: the sudden increase in cases imported from overseas and the relaxation of local government epidemic prevention policies. The compartmental dynamical model (Susceptible, Exposed, Infectious, Dead and Recovered (SEIDR) Model) could reproduce the obvious recurrent outbreak of the epidemics and showed that both imported infected cases and the relaxation of government policies have a causal effect on the emergence of a new wave of outbreak, along with variations in the temperature index. Meanwhile, recurrent outbreaks affect consumer confidence and have a significant influence on GDP. These results support the necessity of policies such as travel bans, testing of people upon entry, and consistency of government prevention and control policies in avoiding future waves of epidemics and protecting economy.

Enlightenment on oscillatory properties of 23 class B notifiable infectious diseases in the mainland of China from 2004 to 2020

“…Examples of these are the seasonal pertussis patterns such as measles [17] in Europe [18][19][20][21][22], influenza [23] in Japan, and measles [23] and rabies [24][25][26] in China. This oscillation may be driven by natural factors, such as seasonal temperature, rainfall [27,28], natural disasters [29], or human factors, such as school terms [30,31], economic migration [32,33], or vaccination coverage [34]. It is essential to forecast the recurrent outbreaks of these infectious diseases due to their global reach, impact on individual livelihoods, as well as on the economy [35,36] and public mental health systems [37,38].…”

Synchronized nonpharmaceutical interventions for the control of COVID-19

“…A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a global pandemic of coronavirus disease-2019 (COVID-19) [1,2]. The government of China implemented combinations of nonpharmaceutical interventions (NPIs) to attempt to contain the pandemic [3][4][5].…”

Using Evolutionary Game Dynamics to Reproduce Phase Portrait Diversity in a Pandemic Scenario

“…In pandemics such as the current COVID-19 one and in the absence of pharmaceutical interventions, recurrent waves of infections can be caused by several distinct factors, namely: (i) vital dynamics and the birth of new susceptible individuals; (ii) seasonality in infections caused by respiratory virus; (iii) appearance of new pathogenic strains capable of partial reinfection; (iv) waning immunity; (v) governmental NPI measures and dynamic social adhesion to preventive NPI recommendations [33][34][35]. In this work, we explore the possibility of explaining important qualitative and quantitative features of the nonlinear dynamics of a multiplewave pandemic based solely on the latter ingredient, i. e., item (v).…”