The Covid-19 containment effects of public health measures: A spatial difference-in-differences approach.
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ABSTRACT:
SUBMITTER: Kosfeld R
PROVIDER: S-EPMC8250984 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: At the start of the coronavirus disease 2019 (COVID-19) pandemic, in the absence of pharmaceutical interventions, countries resorted to containment measures to stem the spread of the disease. In this paper, we have conducted a global study using a sample of 46 countries to evaluate whether these containment measures resulted in unemployment. Methods: We use a difference-in-differences (DID) specification with a heterogenous intervention to show the varying intensity effect of containment measures on unemployment, on a sample of 46 countries. We explain variations in unemployment from January-June 2020 using stringency of containment measures, controlling for gross domestic product (GDP) growth, inflation rate, exports, cases of COVID-19 per million, COVID-19-specific fiscal spending, time fixed effects, region fixed effects, and region trends. We conduct further subset analyses by COVID-cases quintiles and gross national income (GNI) per capita quintiles. Results: The median level of containment stringency in our sample was 43.7. Our model found that increasing stringency to this level would result in unemployment increasing by 1.87 percentage points (or 1.67 pp, after controlling for confounding). For countries with below median COVID-19 cases and below median GNI per capita, this effect is larger. Conclusion: Containment measures have a strong impact on unemployment. This effect is larger in poorer countries and countries with low COVID-19 cases. Given that unemployment has profound effects on mortality and morbidity, this consequence of containment measures may compound the adverse health effects of the pandemic for the most vulnerable groups. It is necessary for governments to consider this in future pandemic management, and to attempt to alleviate the impact of containment measures via effective fiscal spending.
| S-EPMC10125098 | biostudies-literature
Project description: Not available
| S-EPMC7833997 | biostudies-literature
Project description:Combining Spanish firm-level monthly trade data with country-level Covid-19 containment measures over February–July 2020, we show that the value of exports decreased more in destinations that introduced strict containment measures, whereas the value of imports remained unaffected. Strict containment measures in a partner country increased the probability of a firm ceasing to trade with it. Negative effects were concentrated between March and May 2020. The detrimental effect of containment on exports was larger in destinations where the share of jobs that could be done remotely was low, for goods consumed outside the household, for wholesalers and retailers, and for manufacturers not participating in global value chains.
| S-EPMC8923832 | biostudies-literature
Project description:Public health emergencies influence urban carbon emissions, yet an in-depth understanding of deviations between regional emissions under such emergencies and normal levels is lacking. Inspired by the concept of resilience, we introduce the concept of regional carbon resilience and propose four resilience indicators covering periods during and after emergencies. A synthetic difference-in-differences model is employed to compute these indicators, providing a more suitable approach than traditional methods assuming unchanged levels before and after emergencies. Using the COVID-19 pandemic in China as a case study, focusing on the power and industry sectors, we find that over 40% regions exhibit strong resilience (> 0.9). Average in-resilience (0.764 and 0.783) is higher than post-resilience (0.534 and 0.598) in both sectors, indicating lower resilience during than after emergencies. Significant differences in resilience performance exist across regions, with Hebei (0.93) and Hangzhou (0.92) as top performers, and Qinghai (0.29) and Guiyang (0.36) as the least resilient. Furthermore, a preliminary correlation analysis identifies 22 factors affecting carbon resilience; higher energy consumption, stronger industrial production, and a healthier regional economy positively contribute to resilience with coefficients over + 0.3, while pandemic severity negatively impacts resilience, with coefficients up to -0.58. These findings provide valuable references for policymaking to achieve carbon neutrality goals.
| S-EPMC11374798 | biostudies-literature
Project description:ImportanceThe effectiveness of public health measures implemented to mitigate the spread and impact of SARS-CoV-2 relies heavily on honesty and adherence from the general public.ObjectiveTo examine the frequency of, reasons for, and factors associated with misrepresentation and nonadherence regarding COVID-19 public health measures.Design, setting, and participantsThis survey study recruited a national, nonprobability sample of US adults to participate in an online survey using Qualtrics online panels (participation rate, 1811 of 2260 [80.1%]) from December 8 to 23, 2021. The survey contained screening questions to allow for a targeted sample of one-third who had had COVID-19, one-third who had not had COVID-19 and were vaccinated, and one-third who had not had COVID-19 and were unvaccinated.Main outcomes and measuresThe survey assessed 9 different types of misrepresentation and nonadherence related to COVID-19 public health measures and the reasons underlying such behaviors. Additional questions measured COVID-19-related beliefs and behaviors and demographic characteristics.ResultsThe final sample included 1733 participants. The mean (SD) participant age was 41 (15) years and the sample predominantly identified as female (1143 of 1732 [66.0%]) and non-Hispanic White (1151 of 1733 [66.4%]). Seven hundred twenty-one participants (41.6%) reported misrepresentation and/or nonadherence in at least 1 of the 9 items; telling someone they were with or about to be with in person that they were taking more COVID-19 preventive measures than they actually were (420 of 1726 [24.3%]) and breaking quarantine rules (190 of 845 [22.5%]) were the most common manifestations. The most commonly endorsed reasons included wanting life to feel normal and wanting to exercise personal freedom. All age groups younger than 60 years (eg, odds ratio for those aged 18-29 years, 4.87 [95% CI, 3.27-7.34]) and those who had greater distrust in science (odds ratio, 1.14 [95% CI, 1.05-1.23]) had significantly higher odds of misrepresentation and/or nonadherence for at least 1 of the 9 items.Conclusions and relevanceIn this survey study of US adults, nearly half of participants reported misrepresentation and/or nonadherence regarding public health measures against COVID-19. Future work is needed to examine strategies for communicating the consequences of misrepresentation and nonadherence and to address contributing factors.
| S-EPMC9552890 | biostudies-literature
Project description:Responses to the COVID-19 outbreak resulted in one of the largest short-term decreases in anthropogenic emissions in modern history. To date, there has been no comprehensive assessment of the impact of lockdowns on air quality and human health. Using global satellite observations and ground measurements from 36 countries in Europe, North America, and East Asia, we find that lockdowns led to reductions in NO2 concentrations globally, resulting in ~32,000 avoided premature mortalities, including ~21,000 in China. However, we do not find corresponding reductions in PM2.5 and ozone globally. Using satellite measurements, we show that the disconnect between NO2 and ozone changes stems from local chemical regimes. The COVID-related lockdowns demonstrate the need for targeted air quality policies to reduce the global burden of air pollution, especially related to secondary pollutants.
| S-EPMC8139585 | biostudies-literature
Project description:Countries worldwide have implemented measures to contain the spread of COVID-19, and it is vital to understand which factors influence compliance to these measures. This study investigated whether psychopathic traits predict adherence to containment measures imposed by the UK government. 156 university students (Mage=21 years) completed an online survey measuring psychopathic traits (the Triarchic Psychopathy Measure), demographic variables, and participants’ living situations, underlying health risks, contact with vulnerable people and fear of COVID-19. Hierarchical multiple regression indicated that higher psychopathic traits (particularly disinhibition) predicted lower adherence to containment measures when controlling for other variables. A mixed-model ANOVA analysing longitudinal data, collected during the second (n=156) and third (n=118) lockdowns, showed that this relationship was stable over time. Additionally, fear of COVID-19 predicted adherence and mediated the relationship between psychopathic traits and adherence. These findings highlight the relevance of psychopathic traits for understanding COVID-19-related behaviours, with implications for public health communication.
| S-EPMC9365514 | biostudies-literature
Project description:BackgroundWe hypothesize that comprehensive surveillance of COVID-19 in Singapore has facilitated early case detection and prompt contact tracing and, with community-based measures, contained spread. We assessed the effectiveness of containment measures by estimating transmissibility (effective reproduction number, (Equation is included in full-text article.)) over the course of the outbreak.MethodsWe used a Bayesian data augmentation framework to allocate infectors to infectees with no known infectors and determine serial interval distribution parameters via Markov chain Monte Carlo sampling. We fitted a smoothing spline to the number of secondary cases generated by each infector by respective onset dates to estimate (Equation is included in full-text article.)and evaluated increase in mean number of secondary cases per individual for each day's delay in starting isolation or quarantine.ResultsAs of April 1, 2020, 1000 COVID-19 cases were reported in Singapore. We estimated a mean serial interval of 4.6 days [95% credible interval (CI) = 4.2, 5.1] with a SD of 3.5 days (95% CI = 3.1, 4.0). The posterior mean (Equation is included in full-text article.)was below one for most of the time, peaking at 1.1 (95% CI = 1.0, 1.3) on week 9 of 2020 due to a spreading event in one of the clusters. Eight hundred twenty-seven (82.7%) of cases infected less than one person on average. Over an interval of 7 days, the incremental mean number of cases generated per individual for each day's delay in starting isolation or quarantine was 0.03 cases (95% CI = 0.02, 0.05).ConclusionsWe estimate that robust surveillance, active case detection, prompt contact tracing, and quarantine of close contacts kept (Equation is included in full-text article.)below one.
| S-EPMC7707159 | biostudies-literature
Project description: Not available
| S-EPMC7543445 | biostudies-literature
Project description:Environmental factors are well known to affect spatio-temporal patterns of infectious disease outbreaks, but whether the rapid spread of COVID-19 across the globe is related to local environmental conditions is highly debated. We assessed the impact of environmental factors (temperature, humidity and air pollution) on the global patterns of COVID-19 early outbreak dynamics during January-May 2020, controlling for several key socio-economic factors and airport connections. We showed that during the earliest phase of the global outbreak (January-March), COVID-19 growth rates were non-linearly related to climate, with fastest spread in regions with a mean temperature of ca. 5 °C, and in the most polluted regions. However, environmental effects faded almost completely when considering later outbreaks, in keeping with the progressive enforcement of containment actions. Accordingly, COVID-19 growth rates consistently decreased with stringent containment actions during both early and late outbreaks. Our findings indicate that environmental drivers may have played a role in explaining the early variation among regions in disease spread. With limited policy interventions, seasonal patterns of disease spread might emerge, with temperate regions of both hemispheres being most at risk of severe outbreaks during colder months. Nevertheless, containment measures play a much stronger role and overwhelm impacts of environmental variation, highlighting the key role for policy interventions in curbing COVID-19 diffusion within a given region. If the disease will become seasonal in the next years, information on environmental drivers of COVID-19 can be integrated with epidemiological models to inform forecasting of future outbreak risks and improve management plans.
| S-EPMC7744010 | biostudies-literature