Synchronized nonpharmaceutical interventions for the control of COVID-19

Abstract

The world is experiencing an ongoing pandemic of coronavirus disease-2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In attempts to control the pandemic, a range of nonpharmaceutical interventions (NPIs) has been implemented worldwide. However, the effect of synchronized NPIs for the control of COVID-19 at temporal and spatial scales has not been well studied. Therefore, a meta-population model that incorporates essential nonlinear processes was constructed to uncover the transmission characteristics of SARS-CoV-2 and then assess the effectiveness of synchronized NPIs on COVID-19 dynamics in China. Regional synchronization of NPIs was observed in China, and it was found that a combination of synchronized NPIs (the travel restrictions, the social distancing and the infection isolation) prevented 93.7% of SARS-CoV-2 infections. The use of synchronized NPIs at the time of the Wuhan lockdown may have prevented as much as 38% of SARS-CoV-2 infections, compared with the unsynchronized scenario. The interconnectivity of the epicenter, the implementation time of synchronized NPIs, and the number of regions considered all affected the performance of synchronized NPIs. The results highlight the importance of using synchronized NPIs in high-risk regions for the control of COVID-19 and shed light on effective strategies for future pandemic responses.

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

“…Third, the role of human mobility in COVID-19 transmission is further clarified. Similarly to previous studies [13,21,32], it is verified that human mobility (by travel) can spark new infections in virgin areas and high frequency of human mobility in reality has driven COVID-19 diffusion across the 31 provinces of China. The present paper further indicates that the effects of human mobility in the spatiotemporal transmission of COVID-19 are more prominent in two cases: early stage of infection and when R 0 is a little bigger than one.…”

“…In this case, more than 92.3% population in China would be infected clinically/subclinically by COVID-19 virus. The estimated effects of interventions are much more significant than previous results, which claimed that (1) if without nonpharmaceutical interventions in China, the number of cases was predicted to be 7.6 million by February 29, 2020 [16], or 37 million by March 5, 2020 [31], or increase the total infections by 93.7% [32]. The reason for the severity of our estimation could be that this study highlights the intrinsic spatiotemporal transmission dynamics and the total infection process.…”

Metapopulations, the inflationary effect, and consequences for public health

“…Ruktanonchai et al (2020) illustrated that if different countries in the EU came out of lockdown at different times (thereby generating spatiotemporal heterogeneity – as in fact was the case), then there would be many more infections and hospitalizations from COVID-19 than if states came out of lockdown in a coordinated manner. Others have modeled the timing of application of NPIs in light of this phenomenon and found it to be quite general (Berestycki et al, 2023; Eksin et al, 2021; Wang and Wu, 2022; Zhang et al, 2021). A general conclusion is that optimal local public health strategies locally depend on the public health decisions made by nearby localities.…”

Preface

“…In [21] it is suggested that patient's symptoms (clinical symptoms and features) can be helpful to distinguish infected COVID-19 cases by using the non-dominated sorting genetic algorithm (NSGA-II) within the proposed predictive model. In [22] it is confirmed that a combination of synchronized NPIs (the travel restrictions, the social distancing and the infection isolation) prevented 93.7% of SARS-CoV-2 infections. In [23] the first and second waves of COVID-19 are discussed based on data from four countries, and a potential scheme is suggested to control the pandemic.…”