Infectious diseases and human behavior are intertwined. On one side, our movements and interactions are the engines of transmission. On the other, the unfolding of viruses might induce changes to our ...daily activities. While intuitive, our understanding of such feedback loop is still limited. Before COVID-19 the literature on the subject was mainly theoretical and largely missed validation. The main issue was the lack of empirical data capturing behavioral change induced by diseases. Things have dramatically changed in 2020. Non-pharmaceutical interventions (NPIs) have been the key weapon against the SARS-CoV-2 virus and affected virtually any societal process. Travel bans, events cancellation, social distancing, curfews, and lockdowns have become unfortunately very familiar. The scale of the emergency, the ease of survey as well as crowdsourcing deployment guaranteed by the latest technology, several Data for Good programs developed by tech giants, major mobile phone providers, and other companies have allowed unprecedented access to data describing behavioral changes induced by the pandemic.
Here, I review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 348 articles written by more than 2518 authors in the first 12 months of the emergency. While the large majority of the sample was obtained by querying PubMed, it includes also a hand-curated list. Considering the focus, and methodology I have classified the sample into seven main categories: epidemic models, surveys, comments/perspectives, papers aiming to quantify the effects of NPIs, reviews, articles using data proxies to measure NPIs, and publicly available datasets describing NPIs. I summarize the methodology, data used, findings of the articles in each category and provide an outlook highlighting future challenges as well as opportunities.
Policymakers have implemented a wide range of non-pharmaceutical interventions to fight the spread of COVID-19. Variation in policies across jurisdictions and over time strongly suggests a ...difference-in-differences (DD) research design to estimate causal effects of counter-COVID measures. We discuss threats to the validity of these DD designs and make recommendations about how researchers can avoid bias, interpret results accurately, and provide sound guidance to policymakers seeking to protect public health and facilitate an eventual economic recovery.
•We investigate the relationship between policy responses to the COVID-19 pandemic and stock market volatility.•We explore several different non-pharmaceutical interventions in 67 ...countries.•Stringent policy responses increase return volatility in international stock markets.•The effect is independent from the role of the coronavirus pandemic itself and is robust to many considerations.•Information campaigns and public event cancellations are the major contributors to the growth of volatility.
Do government interventions aimed at curbing the spread of COVID-19 affect stock market volatility? To answer this question, we explore the stringency of policy responses to the novel coronavirus pandemic in 67 countries around the world. We demonstrate that non-pharmaceutical interventions significantly increase equity market volatility. The effect is independent from the role of the coronavirus pandemic itself and is robust to many considerations. Furthermore, two types of actions that are usually applied chronologically particularly early—information campaigns and public event cancellations—are the major contributors to the growth of volatility.
From March to June 2022, Shanghai was struck by a new coronavirus variant, Omicron, resulting in the infected cases of at least 600,000 people. Despite implementing a strict containment policy of ...city-wide silence (i.e., residents were not allowed to go out unless necessary), the outbreak cannot be effectively prevented within a short period of time. A significant academic and practical question is: how could we prevent and control outbreak of COVID-19 in large, densely populated cities like Shanghai? It is necessary to develop a rational epidemic spreading model for large cities, in order to accurately predict the trend of disease and quantitatively assess the impact of non-pharmaceutical interventions. In this paper, a multilayer commuter metapopulation network model is constructed to capture commuting flows and the size of epidemic outbreak during commuting between districts. The model accurately predicts epidemic spreading in each district of Shanghai. Assuming strict city-wide lockdowns, with each district locked down and limited inter-district commuting as social zones, simulations demonstrate significant suppression of outbreaks due to social-level interventions. For example, a 1-fold increase in PCR (Polymerase Chain Reaction) testing efficiency reduces the size of epidemic outbreak by approximately 70%. Larger districts require stricter controls to prevent exponential growth. Lockdowns effectively prevent epidemic outbreak at low disease rates but less so at high rates. Liberalized policies lead to varied outbreak trends, with economically developed regions peaking earlier due to higher population densities. This study provides a comprehensive framework for quantitatively evaluating the impact of social and regional controls on urban epidemics.
•Introduces a model that accurately captures commuting flows and predicts epidemic outbreaks in Shanghai.•Simulations show significant outbreak suppression through strict city-wide lockdowns with limited inter-district commuting.•Larger districts need stricter controls to prevent exponential epidemic growth, highlighting tailored interventions.•Lockdowns effectively prevent outbreaks at low disease rates but are less effective at high rates, stressing early intervention.•Liberalized policies result in varied outbreak trends, with economically developed regions peaking earlier due to higher population densities, suggesting nuanced strategies based on regional socio-economic factors.
The new identified virus COVID-19 has become one of the most contagious diseases in human history. The ongoing coronavirus has created severe threats to global mental health, which have resulted in ...crisis management challenges and international concerns related to health issues. As of September 9, 2021, there were over 223.4 million patients with COVID-19, including 4.6 million deaths and over 200 million recovered patients reported worldwide, which has made the COVID-19 outbreak one of the deadliest pandemics in human history. The aggressive public health implementations endorsed various precautionary safety and preventive strategies to suppress and minimize COVID-19 disease transmission. The second, third, and fourth waves of COVID-19 continue to pose global challenges to crisis management, as its evolution and implications are still unfolding. This study posits that examining the strategic ripostes and pandemic experiences sheds light on combatting this global emergency. This study recommends two model strategies that help reduce the adverse effects of the pandemic on the immune systems of the general population. This present paper recommends NPI interventions (non-pharmaceutical intervention) to combine various measures, such as the suppression strategy (lockdown and restrictions) and mitigation model to decrease the burden on health systems. The current COVID-19 health crisis has influenced all vital economic sectors and developed crisis management problems. The global supply of vaccines is still not sufficient to manage this global health emergency. In this crisis, NPIs are helpful to manage the spillover impacts of the pandemic. It articulates the prominence of resilience and economic and strategic agility to resume economic activities and resolve healthcare issues. This study primarily focuses on the role of social media to tackle challenges and crises posed by COVID-19 on economies, business activities, healthcare burdens, and government support for societies to resume businesses, and implications for global economic and healthcare provision disruptions. This study suggests that intervention strategies can control the rapid spread of COVID-19 with hands-on crisis management measures, and the healthcare system will resume normal conditions quickly. Global economies will revitalize scientific contributions and collaborations, including social science and business industries, through government support.
•Based on multi-source big data, we built a Bayesian inference model to examine the effectiveness of non-pharmaceutical interventions for mitigating the spread of COVID-19 across both multiple ...pandemic waves and geographic scales.•The synergistic effectiveness of NPIs for reducing COVID-19 infections declined along waves before vaccine rollout, from 95.4% in the first wave to 56.0% in the third wave at the global level, and similarly from 83.3% to 58.7% at national level in the USA.•NPIs effectiveness had fluctuating performance across waves on regional and subnational scales.•Regardless of geographical scale, gathering restrictions and facial coverings played significant roles to mitigate the early waves of COVID-19.
Governments worldwide have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic. However, the effect of these individual NPI measures across space and time has yet to be sufficiently assessed, especially with the increase of policy fatigue and the urge for NPI relaxation in the vaccination era. Using the decay ratio in the suppression of COVID-19 infections and multi-source big data, we investigated the changing performance of different NPIs across waves from global and regional levels (in 133 countries) to national and subnational (in the United States of America USA) scales before the implementation of mass vaccination. The synergistic effectiveness of all NPIs for reducing COVID-19 infections declined along waves, from 95.4% in the first wave to 56.0% in the third wave recently at the global level and similarly from 83.3% to 58.7% at the USA national level, while it had fluctuating performance across waves on regional and subnational scales. Regardless of geographical scale, gathering restrictions and facial coverings played significant roles in epidemic mitigation before the vaccine rollout. Our findings have important implications for continued tailoring and implementation of NPI strategies, together with vaccination, to mitigate future COVID-19 waves, caused by new variants, and other emerging respiratory infectious diseases.
•Nonpharmaceutical interventions were effective in reducing COVID-19 transmission.•Social distancing is more effective than the other NPIs in containing COVID-19.•Two or more synchronous NPIs are ...more effective than a single type of NPI.
To evaluate and compare the effectiveness of four types of non-pharmaceutical interventions (NPIs) to contain the time-varying effective reproduction number (Rt) of coronavirus disease-2019 (COVID-19).
This study included 1,908,197 confirmed COVID-19 cases from 190 countries between 23 January and 13 April 2020. The implemented NPIs were categorised into four types: mandatory face mask in public, isolation or quarantine, social distancing and traffic restriction (referred to as mandatory mask, quarantine, distancing and traffic hereafter, respectively).
The implementations of mandatory mask, quarantine, distancing and traffic were associated with changes (95% confidence interval, CI) of −15.14% (from −21.79% to −7.93%), −11.40% (from −13.66% to −9.07%), −42.94% (from −44.24% to −41.60%) and −9.26% (from −11.46% to −7.01%) in the Rt of COVID-19 when compared with those without the implementation of the corresponding measures. Distancing and the simultaneous implementation of two or more types of NPIs seemed to be associated with a greater decrease in the Rt of COVID-19.
Our study indicates that NPIs can significantly contain the COVID-19 pandemic. Distancing and the simultaneous implementation of two or more NPIs should be the strategic priorities for containing COVID-19.
•COVID-19 has had a massive impact on quality of life worldwide.•Mask-wearing is a widely accepted non-pharmaceutical intervention, but the effects of social distancing have not been thoroughly ...evaluated.•This study demonstrates a causal relationship between strictly implemented social distancing and the incidence and exacerbation of asthma.•Social distancing against COVID-19 may suppress asthma incidence and exacerbation.
Non-pharmaceutical interventions have been implemented globally to control the COVID-19 pandemic and have been shown to alleviate both allergies and respiratory infections. Although mask-wearing is an accepted non-pharmaceutical intervention, the effects of social distancing have not been thoroughly evaluated.
To evaluate the effects of social distancing on asthma trends in Seoul, South Korea.
This study included data from the National Health Insurance Service of South Korea, covering approximately 10 million people in Seoul. Daily and monthly data of patients with asthma from 2018 to 2021 were examined, and the degree of social distancing performance was measured using the number of subway users as an index. Pearson's correlation coefficient was used to determine the relationship between the two indices. The change-point detection technique, cross-correlation, and Granger causality method were used to assess the temporal causality between social distancing and asthma.
The number of patients with asthma decreased by 42.4 % from 2019 to 2020, while that of subway users decreased by 26.3 % during this period. Pearson's correlation analysis revealed significant positive correlations. Asthma and subway users showed a significant change in incidence following the implementation of social distancing; subway users showed a causal relationship with patients with asthma.
Our results showed that the number of subway users decreased after the implementation of strict social distancing, coinciding with a decrease in the number of patients with asthma. These findings suggest that social distancing measures implemented to control COVID-19 may reduce the incidence and exacerbation of asthma.
Background
Little RSV activity was observed during the first expected RSV season since the COVID‐19 pandemic. Multiple countries later experienced out‐of‐season RSV resurgences, yet their association ...with non‐pharmaceutical interventions (NPIs) is unclear. This study aimed to describe the changes in RSV epidemiology during the COVID‐19 pandemic and to estimate the association between individual NPIs and the RSV resurgences.
Methods
RSV activity from Week (W)12‐2020 to W44‐2021 was compared with three pre‐pandemic seasons using RSV surveillance data from Brazil, Canada, Chile, France, Israel, Japan, South Africa, South Korea, Taiwan, the Netherlands and the United States. Changes in nine NPIs within 10 weeks before RSV resurgences were described. Associations between NPIs and RSV activity were assessed with linear mixed models. Adherence to NPIs was not taken into account.
Results
Average delay of the first RSV season during the COVID‐19 pandemic was 39 weeks (range: 13–88 weeks). Although the delay was <40 weeks in six countries, a missed RSV season was observed in Brazil, Chile, Japan, Canada and South Korea. School closures, workplace closures, and stay‐at‐home requirements were most commonly downgraded before an RSV resurgence. Reopening schools and lifting stay‐at‐home requirements were associated with increases of 1.31% (p = 0.04) and 2.27% (p = 0.06) in the deviation from expected RSV activity.
Conclusion
The first RSV season during the COVID‐19 pandemic was delayed in the 11 countries included. Reopening of schools was consistently associated with increased RSV activity. As NPIs were often changed concomitantly, the association between RSV activity and school closures may be partly attributed to other NPIs.
Non-pharmaceutical interventions (NPIs) can effectively contain the spread of the coronavirus disease 2019 (COVID-19) when implemented promptly and decisively. However, legislative concerns on the ...economic repercussions of NPIs often delay their rollout. Utilizing proprietary transaction-level data from two major restaurant chains, we quantitatively assess the effects of stay-at-home (SAH) orders implemented during the COVID-19 pandemic. Our findings indicate a significant 17.5 % decrease in revenue for restaurants affected by these orders, with a more pronounced impact observed in densely populated areas. The study also reveals a notable decline in home delivery revenues, suggesting a comprehensive disruption in both dine-in and delivery services. However, post-lifting of the SAH orders, we document a rapid diminishment in the revenue disparity between affected and unaffected restaurants, followed by a robust rebound in overall performance within several weeks. Our study contributes to the broader discourse on the resilience and adaptability of small businesses in the face of public health crises, providing a foundation for future research and policy formulation in pandemic resilience planning.
•Unique data reveals a 17 % decrease in revenue for Beijing restaurant chains affected by stay-at-home orders.•Analysis shows more severe revenue losses in densely populated regions.•Significant downturn also observed in home delivery services during SAH orders.•Study underscores the need for targeted subsidies to bolster restaurant resilience.
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