scholarly journals The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

2020 ◽  
Author(s):  
Yang Liu ◽  
Christian Morgenstern ◽  
James Kelly ◽  
Rachel Lowe ◽  
Mark Jit ◽  
...  
Keyword(s):  
Empirical Evidence ◽  
Strong Evidence ◽  
International Travel ◽  
School Closure ◽  
Contact Tracing ◽  
Temporal Association ◽  
Time Varying ◽  
Temporal Clustering ◽  
The Impact ◽  
Pharmaceutical Interventions

Introduction: Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories. Methods: We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission with data from January - June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g., restrictions on 1000+ people gathering were not effective, restrictions on <10 people gathering was). Evidence supporting the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Conclusion: Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications taking into account these effects, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many although not all the actions policy-makers are taking to respond to the COVID-19 pandemic.

scholarly journals The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang Liu ◽  
◽  
Christian Morgenstern ◽  
James Kelly ◽  
Rachel Lowe ◽  
...  
Keyword(s):  
Empirical Evidence ◽  
Strong Evidence ◽  
International Travel ◽  
School Closure ◽  
Contact Tracing ◽  
Temporal Association ◽  
Time Varying ◽  
Temporal Clustering ◽  
The Impact ◽  
Pharmaceutical Interventions

Abstract Background Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories. Methods We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission using data from January to June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect, and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support, and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g. restrictions on 1000+ people gathering were not effective, restrictions on < 10 people gathering were). Evidence about the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Effect sizes varied depending on whether or not we included data after peak NPI intensity. Conclusion Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects, and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many, although not all, actions policy-makers are taking to respond to the COVID-19 pandemic.

scholarly journals The impact of lockdown measures on COVID-19: a worldwide comparison

2020 ◽  
Author(s):  
DI Papadopoulos ◽  
I Donkov ◽  
K Charitopoulos ◽  
S Bishara
Keyword(s):  
Public Information ◽  
Reproductive Rate ◽  
International Travel ◽  
School Closure ◽  
Contact Tracing ◽  
Economic Implications ◽  
Information Campaigns ◽  
Early Introduction ◽  
Travel Restrictions ◽  
The Impact

AbstractObjectiveWe aimed to determine which aspects of the COVID-19 national response are independent predictors of COVID-19 mortality and case numbers.DesignComparative observational study between nations using publicly available data.SettingWorldwide Participants Covid-19 patientsInterventionsStringency of 11 lockdown policies recorded by the Blavatnik School of Government database and earliness of each policy relative to first recorded national casesMain outcome measuresAssociation with log10 National deaths (LogD) and log10 National cases (LogC) on the 29th April 2020 corrected for predictive demographic variablesResultsEarly introduction was associated with reduced mortality (n=137) and case numbers (n=150) for every policy aside from testing policy, contact tracing and workplace closure. Maximum policy stringency was only found to be associated with reduced mortality (p=0·003) or case numbers (p=0·010) for international travel restrictions. A multivariate model, generated using demographic parameters (r2=0·72 for LogD and r2=0·74 for LogC), was used to assess the timing of each policy. Early introduction of first measure (significance p=0·048, regression coefficient β=-0·004, 95% confidence interval 0 to -0·008), early international travel restrictions (p=0·042, β=-0·005, -0·001 to - 0·009) and early public information (p=0·021, β=-0·005, -0·001 to -0·009) were associated with reduced LogC. Early introduction of first measure (p=0·003, β=-0·007, -0·003 to -0·011), early international travel restrictions (p=0·003, β=-0·008, -0·004 to-0·012), early public information (p=0·003, β=-0·007, 0·003 to -0·011), early generalised workplace closure (p=0·031, β=-0·012, -0·002 to -0·022) and early generalised school closure (p=0·050, β=-0·012, 0 to -0·024) were associated with reduced LogC.ConclusionsAt this stage in the pandemic, early institution of public information, international travel restrictions, and workplace closure are associated with reduced COVID-19 mortality and maintaining these policies may help control the pandemic.What is already known on this topicThe COVID-19 pandemic has spread rapidly throughout the world and presented vast healthcare, economic and political challenges. Many nations have recently passed the peak of their infection rate, and are weighing up relaxation of lockdown strategies. Though the effect of individual lockdown policies can be estimated by modelling, little is known about the impact of individual policies on population case numbers or mortality through comparison of differing strategies between nations. A PubMed search was carried out on the 14/5/20 using keywords including “novel coronavirus-infected pneumonia”, “2019-nCoV”, “Sars-Cov-2”, “Covid-19”, “lockdown”,” policy”, “social distancing”, “isolation”, “quarantine” and “contact tracing” returned 258 studies in total. Following scanning of the above results, we found 19 studies that have examined the effect of lockdown within a region, which have demonstrated a reduction in case numbers after the introduction of a lockdown. There are no previous studies that have compared the effectiveness of government lockdowns between nations to determine the effectiveness of specific policies.What this study addsThis study examines the corollary between government policy and COVID-19 case numbers and mortality, correct as of the 29th of April 2020, for every nation that there is available date within the Blavatnik School of Government database on COVID-19 policy. The study demonstrates that early generalised school closure, early generalised workplace closure, early restriction of international travel and early public information campaigns are independently associated with reduced national COVID-19 mortality. The maximum stringency of individual lockdown policies were not associated with reduced case numbers or mortality. Early reintroduction of these policies may be most effective in a relapse of the pandemic, though, school closure, workplace closure and restriction of international travel carry heavy politico-economic implications. There was no measurable effect of maximum stringency of lockdown policy on outcome at this point in time, indicating that early timing of lockdown introduction is of greater importance than its stringency, provided that the resultant viral reproductive rate is less than 1.

scholarly journals Modeling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil

2021 ◽  
Author(s):  
Marcelo Eduardo Borges ◽  
Leonardo Souto Ferreira ◽  
Silas Poloni ◽  
Ângela Maria Bagattini ◽  
Caroline Franco ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Transmission Rate ◽  
Disease Incidence ◽  
Demographic Data ◽  
School Closure ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
School Closures ◽  
Infection Transmission ◽  
The Impact

Among the various non–pharmaceutical interventions implemented in response to the Covid–19 pandemic during 2020, school closures have been in place in several countries to reduce infection transmission. Nonetheless, the significant short and long–term impacts of prolonged suspension of in–person classes is a major concern. There is still considerable debate around the best timing for school closure and reopening, its impact on the dynamics of disease transmission, and its effectiveness when considered in association with other mitigation measures. Despite the erratic implementation of mitigation measures in Brazil, school closures were among the first measures taken early in the pandemic in most of the 27 states in the country. Further, Brazil delayed the reopening of schools and stands among the countries in which schools remained closed for the most prolonged period in 2020. To assess the impact of school reopening and the effect of contact tracing strategies in rates of Covid–19 cases and deaths, we model the epidemiological dynamics of disease transmission in 3 large urban centers in Brazil under different epidemiological contexts. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and elsewhere, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening. Our model shows that reopening schools results in a non–linear increase of reported Covid-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. While low rates of within[&ndash]school transmission resulted in small effects on disease incidence (cases/100,000 pop), intermediate or high rates can severely impact disease trends resulting in escalating rates of new cases even if other interventions remain unchanged. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects of reducing the total number of hospitalizations and deaths. Our results suggest that policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. Also, although contact tracing strategies are essential to prevent new infections and outbreaks within school environments, our data suggest that they are alone not sufficient to avoid significant impacts on community transmission in the context of school reopening in settings with high and sustained transmission rates.

scholarly journals Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China

Science ◽  
2020 ◽  
Vol 368 (6498) ◽  
pp. 1481-1486 ◽  
Author(s):  
Juanjuan Zhang ◽  
Maria Litvinova ◽  
Yuxia Liang ◽  
Yan Wang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Odds Ratio ◽  
School Closure ◽  
Hunan Province ◽  
Contact Tracing ◽  
Transmission Model ◽  
Social Distancing ◽  
Susceptibility To Infection ◽  
Contact Patterns ◽  
The Impact

Intense nonpharmaceutical interventions were put in place in China to stop transmission of the novel coronavirus disease 2019 (COVID-19). As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact survey data for Wuhan and Shanghai before and during the outbreak and contact-tracing information from Hunan province. Daily contacts were reduced seven- to eightfold during the COVID-19 social distancing period, with most interactions restricted to the household. We find that children 0 to 14 years of age are less susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than adults 15 to 64 years of age (odds ratio 0.34, 95% confidence interval 0.24 to 0.49), whereas individuals more than 65 years of age are more susceptible to infection (odds ratio 1.47, 95% confidence interval 1.12 to 1.92). Based on these data, we built a transmission model to study the impact of social distancing and school closure on transmission. We find that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. Although proactive school closures cannot interrupt transmission on their own, they can reduce peak incidence by 40 to 60% and delay the epidemic.

scholarly journals IMPACT OF IMF LENDING ANNOUNCEMENTS ON THE PERFORMANCE OF STOCK MARKET: EMPIRICAL EVIDENCE FROM PAKISTAN

2021 ◽  
Vol 9 (3) ◽  
pp. 467-476
Author(s):  
Muhammad Azeem ◽  
Nisar Ahmad ◽  
Sarfraz Hussain ◽  
Muzammil Khurshid ◽  
Safyan Majid
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Empirical Evidence ◽  
Economic Performance ◽  
Economic Conditions ◽  
The Political ◽  
Time Varying ◽  
Negative Effect ◽  
Multiple Challenges ◽  
The Impact

Purpose of the study: Stock markets have demonstrated varying reactions to IMF lending announcements across various economies. Announcements offered by IMF often be perceived negatively by the participants of the stock market, because of stringent conditions accompanied with the loan that may oppose the political and economic agenda of a borrowing nation. Thus, this study intends to investigate the impact of IMF’s announcements about extending loans to Pakistan on the performance of the Stock market in the debt-ridden economy. Methodology: For regular returns from 1997 to 2017, the benchmarking indexes of KSE-100 and 30 were used. Meanwhile, IMF lending arrangements are categorized into three respective dummies (standby, extended credit facility, and extended fund facility). The Generalized Autoregressive Conditional Heteroscedastic (GARCH) model was used to investigate the effect of IMF’s lending news on the regular stock returns. Main findings: The results show a statistically significant effect of the IMF’s News about lending arrangements on the performance of the stock market in Pakistan. Surprisingly, the negative effect of IMF lending announcements on the performance of the stock market in Pakistan implies that the loans extended by IMF are not professed by speculators as good for the economic performance of the economy. Application of this study: The findings of this study imply that simply extending loans is not a panacea for politically unstable and financially ruined nations. Lending strategies of IMF need to be favourable for the political and economic conditions of a borrowing country. Originality/ Novelty: As for as the novelty is concerned, the study has highlighted the time-varying impact of IMF lending announcements on the performance of the stock market in a financially fragile country where a newborn government facing multiple challenges has made its best effort to avoid borrowing from IMF.

scholarly journals Preparing for a future COVID-19 wave: insights and limitations from a data-driven evaluation of non-pharmaceutical interventions in Germany

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ashwin Aravindakshan ◽  
Jörn Boehnke ◽  
Ehsan Gholami ◽  
Ashutosh Nayak
Keyword(s):  
Public Space ◽  
Temporal Variations ◽  
International Travel ◽  
Disease Spread ◽  
Educational Institutions ◽  
Disease Propagation ◽  
Accurate Forecast ◽  
Spatio Temporal ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractTo contain the COVID-19 pandemic, governments introduced strict Non-Pharmaceutical Interventions (NPI) that restricted movement, public gatherings, national and international travel, and shut down large parts of the economy. Yet, the impact of the enforcement and subsequent loosening of these policies on the spread of COVID-19 is not well understood. Accordingly, we measure the impact of NPIs on mitigating disease spread by exploiting the spatio-temporal variations in policy measures across the 16 states of Germany. While this quasi-experiment does not allow for causal identification, each policy’s effect on reducing disease spread provides meaningful insights. We adapt the Susceptible–Exposed–Infected–Recovered model for disease propagation to include data on daily confirmed cases, interstate movement, and social distancing. By combining the model with measures of policy contributions on mobility reduction, we forecast scenarios for relaxing various types of NPIs. Our model finds that in Germany policies that mandated contact restrictions (e.g., movement in public space limited to two persons or people co-living), closure of educational institutions (e.g., schools), and retail outlet closures are associated with the sharpest drops in movement within and across states. Contact restrictions appear to be most effective at lowering COVID-19 cases, while border closures appear to have only minimal effects at mitigating the spread of the disease, even though cross-border travel might have played a role in seeding the disease in the population. We believe that a deeper understanding of the policy effects on mitigating the spread of COVID-19 allows a more accurate forecast of disease spread when NPIs are partially loosened and gives policymakers better data for making informed decisions.

scholarly journals Effect of COVID-19 Non-Pharmaceutical Interventions and the Implications for Human Rights

2020 ◽  
Vol 18 (1) ◽  
pp. 217
Author(s):  
Seung-Hun Hong ◽  
Ha Hwang ◽  
Min-Hye Park
Keyword(s):  
Human Rights ◽  
Linear Regression ◽  
School Closure ◽  
Contact Tracing ◽  
Limited Evidence ◽  
School Closures ◽  
Human Rights Abuses ◽  
Full Contact ◽  
Complete Contact ◽  
Pharmaceutical Interventions

In response to the COVID-19 pandemic, many governments swiftly decided to order nationwide lockdowns based on limited evidence that such extreme measures were effective in containing the epidemic. A growing concern is that governments were given little time to adopt effective and proportional interventions protecting citizens’ lives while observing their freedom and rights. This paper examines the effectiveness of non-pharmaceutical interventions (NPIs) in containing COVID-19, by conducting a linear regression over 108 countries, and the implication for human rights. The regression results are supported by evidence that shows the change in 10 selected countries’ responding strategies and their effects as the confirmed cases increase. We found that school closures are effective in containing COVID-19 only when they are implemented along with complete contact tracing. Our findings imply that to contain COVID-19 effectively and minimize the risk of human rights abuses, governments should consider implementing prudently designed full contact tracing and school closure policies, among others. Minimizing the risk of human rights abuses should be a principle even when full contact tracing is implemented.

scholarly journals Effects of worldwide interventions and vaccination on COVID-19 between waves and countries

2021 ◽  
Author(s):  
Yong Ge ◽  
Wenbin Zhang ◽  
Haiyan Liu ◽  
Corrine W Ruktanonchai ◽  
Maogui Hu ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Large Scale ◽  
International Travel ◽  
Spatiotemporal Variations ◽  
School Closures ◽  
Vaccination Strategies ◽  
Travel Restrictions ◽  
The Impact ◽  
Second Wave ◽  
Pharmaceutical Interventions

Abstract Worldwide governments have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic, together with the large-scale rollout of vaccines since late 2020. However, the effect of these individual NPI and vaccination measures across space and time has not been sufficiently explored. By the decay ratio in the suppression of COVID-19 infections, we investigated the performance of different NPIs across waves in 133 countries, and their integration with vaccine rollouts in 63 countries as of 25 March 2021. The most effective NPIs were gathering restrictions (contributing 27.83% in the infection rate reductions), facial coverings (16.79%) and school closures (10.08%) in the first wave, and changed to facial coverings (30.04%), gathering restrictions (17.51%) and international travel restrictions (9.22%) in the second wave. The impact of NPIs had obvious spatiotemporal variations across countries by waves before vaccine rollouts, with facial coverings being one of the most effective measures consistently. Vaccinations had gradually contributed to the suppression of COVID-19 transmission, from 0.71% and 0.86% within 15 days and 30 days since Day 12 after vaccination, to 1.23% as of 25 March 2021, while NPIs still dominated the pandemic mitigation. Our findings have important implications for continued tailoring of integrated NPI or NPI-vaccination strategies against future COVID-19 waves or similar infectious diseases.

scholarly journals Correcting for Non-stationarity in BOLD-fMRI Connectivity Analyses

2021 ◽  
Vol 15 ◽  
Author(s):  
Catherine E. Davey ◽  
David B. Grayden ◽  
Leigh A. Johnston
Keyword(s):  
Empirical Evidence ◽  
Upper Bound ◽  
Signal Intensity ◽  
Time Varying ◽  
Signal Power ◽  
Inverse Gamma ◽  
Sample Correlation ◽  
Non Stationary Signal ◽  
The Impact ◽  
Theoretical Results

In this work fMRI BOLD datasets are shown to contain slice-dependent non-stationarities. A model containing slice-dependent, non-stationary signal power is proposed to address time-varying signal power during BOLD data acquisition. The impact of non-stationary power on functional MRI connectivity is analytically derived, establishing that pairwise connectivity estimates are scaled by a function of the time-varying signal power, with magnitude upper bound by 1, and that the variance of sample correlation is increased, thereby inducing spurious connectivity. Consequently, we make the observation that time-varying power during acquisition of BOLD timeseries has the propensity to diminish connectivity estimates. To ameliorate the impact of non-stationary signal power, a simple correction for slice-dependent non-stationarity is proposed. Our correction is analytically shown to restore both signal stationarity and, subsequently, the integrity of connectivity estimates. Theoretical results are corroborated with empirical evidence demonstrating the utility of our correction. In addition, slice-dependent non-stationary variance is experimentally determined to be optimally characterized by an inverse Gamma distribution. The resulting distribution of a voxel's signal intensity is analytically derived to be a generalized Student's-t distribution, providing support for the Gaussianity assumption typically imposed by fMRI connectivity methods.

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