Effects of Physical Distancing to Control COVID-19 on Public Health, the Economy, and the Environment

Adherence to Physical Distancing and Health Beliefs About COVID-19 Among Patients With Cancer

BACKGROUND

This study aimed to validate questionnaires on adherence to physical distancing and health beliefs about coronavirus disease 2019 (COVID-19) among patients with cancer and explore their interaction with depression or viral anxiety among them.

METHODS

Through an online survey, data from 154 cancer patients (female: 82.5%, breast cancer: 66.2%, current cancer treatment, presence: 65.6%) were collected from March to June 2022. The survey gathered responses to questionnaires on adherence to physical distancing, health beliefs about COVID-19, perceived social norms, Stress and Anxiety to Viral Epidemics-6 items, and Patient Health Questionnaire-2. Confirmatory factor analysis (CFA) for construct validity and structural equation model (SEM) were performed.

RESULTS

The CFA showed a good model fit for adherence to physical distancing (comparative fit index [CFI] = 1.000, Tucker-Lewis index [TLI] = 0.930, root-mean-square-error of approximation [RMSEA] = 0.000, and standardized root-mean-square residual [SRMR] = 0.050) and a satisfactory model fit for health beliefs about COVID-19 (CFI = 0.978, TLI = 0.971, RMSEA = 0.061, and SRMR = 0.089). Through SEM, we found that personal injunctive norms were the main mediators linking health beliefs with physical distancing in patients with cancer. Depression also mediated the effects of viral anxiety and perceived severity on physical distancing (χ² = 20.073, df = 15, P = 0.169; CFI = 0.984; RMSEA = 0.047).

CONCLUSION

The questionnaires are reliable and valid. Patients with cancer may be able to adhere to physical distancing by addressing perceived severity, viral anxiety, perceived benefits, self-efficacy, perceived barriers, as well as personal injunctive norms.

Physical distancing versus testing with self-isolation for controlling an emerging epidemic

Two distinct strategies for controlling an emerging epidemic are physical distancing and regular testing with self-isolation. These strategies are especially important before effective vaccines or treatments become widely available. The testing strategy has been promoted frequently but used less often than physical distancing to mitigate COVID-19. We compared the performance of these strategies in an integrated epidemiological and economic model that includes a simple representation of transmission by "superspreading," wherein a relatively small fraction of infected individuals cause a large share of infections. We examined the economic benefits of distancing and testing over a wide range of conditions, including variations in the transmissibility and lethality of the disease meant to encompass the most prominent variants of COVID-19 encountered so far. In a head-to-head comparison using our primary parameter values, both with and without superspreading and a declining marginal value of mortality risk reductions, an optimized testing strategy outperformed an optimized distancing strategy. In a Monte Carlo uncertainty analysis, an optimized policy that combined the two strategies performed better than either one alone in more than 25% of random parameter draws. Insofar as diagnostic tests are sensitive to viral loads, and individuals with high viral loads are more likely to contribute to superspreading events, superspreading enhances the relative performance of testing over distancing in our model. Both strategies performed best at moderate levels of transmissibility, somewhat lower than the transmissibility of the ancestral strain of SARS-CoV-2.

Exploring Future Signals of COVID-19 and Response to Information Diffusion Using Social Media Big Data

COVID-19 is a respiratory infectious disease that first reported in Wuhan, China, in December 2019. With COVID-19 spreading to patients worldwide, the WHO declared it a pandemic on 11 March 2020. This study collected 1,746,347 tweets from the Korean-language version of Twitter between February and May 2020 to explore future signals of COVID-19 and present response strategies for information diffusion. To explore future signals, we analyzed the term frequency and document frequency of key factors occurring in the tweets, analyzing the degree of visibility and degree of diffusion. Depression, digestive symptoms, inspection, diagnosis kits, and stay home obesity had high frequencies. The increase in the degree of visibility was higher than the median value, indicating that the signal became stronger with time. The degree of visibility of the mean word frequency was high for disinfectant, healthcare, and mask. However, the increase in the degree of visibility was lower than the median value, indicating that the signal grew weaker with time. Infodemic had a higher degree of diffusion mean word frequency. However, the mean degree of diffusion increase rate was lower than the median value, indicating that the signal grew weaker over time. As the general flow of signal progression is latent signal → weak signal → strong signal → strong signal with lower increase rate, it is necessary to obtain active response strategies for stay home, inspection, obesity, digestive symptoms, online shopping, and asymptomatic.

Contact times in professional football before and during the SARS-CoV-2 pandemic: Tracking data from the German Bundesliga

The global SARS-CoV-2 pandemic led to a lockdown in team sports in March 2020. Because the risk of virus transmission seems to correlate with the duration of close contacts, data on contact times are necessary to assess the risk of virus transmission in sports. In this study, an optical tracking system was used to determine contact times between players of the two highest men's professional football leagues in Germany in the 2019-20 season and in the first half of the 2020-21 season. Contacts between players were defined as being within a two-metre radius during matches and were differentiated as either match-specific or non-match-specific. In total, 918 matches with 197,087 contacts were analysed. The mean overall contact time of one-to-one situations of 36 s (SD: ± 66) before the lockdown was reduced to 30 s after the lockdown (SD: ± 60) (p < 0.0001). In professional football, contacts between two players infrequently occur within a two-metre radius, averaging less than 35 s. Only 36 player pair contacts lasted for more than 15 min (0.00018%). The mean accumulated contact time per player with all others was 10.6 ± 6.9 min per match, with a decrease from 11.6 ± 7.0 min before the lockdown to 10.0 ± 6.6 min (p < 0.0001) after lockdown in the season 2019-20. The SARS-CoV-2 pandemic has resulted in a reduction in match-specific contacts of 25%. It seems questionable if such short contacts in open-air sports may lead to considerable virus transmission.

The implications of globalization on COVID-19 vaccination in Europe

Although globalization has left its mark on economic dynamism, causing conditionalities among various aspects (market openness, production networks, technological and information developments, migratory flows, international cooperation, humanitarian support, etc.), the less pleasant side of it should not be omitted, i.e. the emergence of the framework for the faster diffusion of epidemiological diseases. Thus, with the onset of the SARS-CoV-2 virus, its widespread circulation is a serious challenge for the provision of efficient solutions to combat it, especially in countries with fragile health systems, poor institutional quality and lack of resources. In this paper we aim to investigate the implications of globalization on the COVID-19 vaccination of the population. The period under analysis is January 1, 2021-January 1, 2022, using montly data, and the object of our study are 48 European states. To capture the relationship between globalization and the vaccination rate, we applied regression models, including a number of factors that may influence the progress of vaccination. In order to test the robustness of the results, the two-stage least squares (2SLS) regressions was used. The regression models developed underlined that globalization impacts the degree of vaccination. More globalized economies are more competitive in COVID-19 management, and the significance of this effect comes from better interconnection in global markets and easier access to medical discoveries. At the same time, countries with a higher vaccination rate are associated with higher levels of development. Based on the results obtained, we proposed some policy recommendations to increase the propensity to vaccinate, ensure equity in the distribution of vaccines and provide financial support to developing countries.

Optimal health and economic impact of non-pharmaceutical intervention measures prior and post vaccination in England: a mathematical modelling study

Background. Even with good progress on vaccination, SARS-CoV-2 infections in the UK may continue to impose a high burden of disease and therefore pose substantial challenges for health policy decision makers. Stringent government-mandated physical distancing measures (lockdown) have been demonstrated to be epidemiologically effective, but can have both positive and negative economic consequences. The duration and frequency of any intervention policy could, in theory, be optimized to maximize economic benefits while achieving substantial reductions in disease. Methods. Here, we use a pre-existing SARS-CoV-2 transmission model to assess the health and economic implications of different strengths of control through time in order to identify optimal approaches to non-pharmaceutical intervention stringency in the UK, considering the role of vaccination in reducing the need for future physical distancing measures. The model is calibrated to the COVID-19 epidemic in England and we carry out retrospective analysis of the optimal timing of precautionary breaks in 2020 and the optimal relaxation policy from the January 2021 lockdown, considering the willingness to pay (WTP) for health improvement. Results. We find that the precise timing and intensity of interventions is highly dependent upon the objective of control. As intervention measures are relaxed, we predict a resurgence in cases, but the optimal intervention policy can be established dependent upon the WTP per quality adjusted life year loss avoided. Our results show that establishing an optimal level of control can result in a reduction in net monetary loss of billions of pounds, dependent upon the precise WTP value. Conclusion. It is vital, as the UK emerges from lockdown, but continues to face an on-going pandemic, to accurately establish the overall health and economic costs when making policy decisions. We demonstrate how some of these can be quantified, employing mechanistic infectious disease transmission models to establish optimal levels of control for the ongoing COVID-19 pandemic.

A modeling study of the effect of social distancing policies on the early spread of coronavirus disease 2019: a case of South Korea

The social distancing policy is an effective way to prevent the spread of infectious diseases in the initial phase of their outbreak when medical evidence to support a particular course of treatment is deficient. While studies on the coronavirus disease 2019 (COVID-19) have mainly focused on the effects of specific measures (e.g., school and workplace closures and restrictions on movement), few investigated the characteristics of epidemic trends in response to the intensity of the policy and the amount of time required for policy measures to take effect. This study employs the SIRD (susceptible, infected, recovered, and deceased) model to analyze the COVID-19 epidemic trend according to the intensity of the social distancing policy in South Korea. The model reveals that the reproduction number began at 5.58 and fluctuated between 0.14 and 1.72 during the study period in accordance with different policy intensities. At the beginning of the social distancing policy, restrictions on public facility use were likely to have been effective in preventing the spread of COVID-19. When the intervention was relaxed, the transmission potential increased significantly. According to the reproduction number, social distancing policies prove to be effective after 13-19 days of implementation; however, as the pandemic progressed, this period extended from 13-14 to 18-19 days for the same effect. This suggests that governments need to consider not only the intensity of the social distancing policy, but also people's low responsiveness as the pandemic remains prevalent over time. It is also recommended they take preemptive action to ensure sufficient time for the policy to achieve its stated goal.

COVID-19 pandemic: What can we learn for better air quality and human health?

The COVID-19 lockdown resulted in improved air quality in many cities across the world. With the objective of what could be the new learning from the COVID-19 pandemic and subsequent lockdowns for better air quality and human health, a critical synthesis of the available evidence concerning air pollution reduction, the population at risk and natural versus anthropogenic emissions was conducted. Can the new societal norms adopted during pandemics, such as the use of face cover, awareness regarding respiratory hand hygiene, and physical distancing, help in reducing disease burden in the future? The use of masks will be more socially acceptable during the high air pollution episodes in lower and middle-income countries, which could help to reduce air pollution exposure. Although post-pandemic, some air pollution reduction strategies may be affected, such as car-pooling and the use of mass transit systems for commuting to avoid exposure to airborne infections like coronavirus. However, promoting non-motorized modes of transportation such as cycling and walking within cities as currently being enabled in Europe and other countries could overshadow such losses. This demand focus on increasing walkability in a town for all ages and populations, including for a differently-abled community. The study highlighted that for better health and sustainability there. is also a need to promote other measures such as work-from-home, technological infrastructure, the extension of smart cities, and the use of information technology.

Older Seniors during the COVID-19 Pandemic-Social Support and Oral Health-Related Quality of Life

The coronavirus disease (COVID-19) has greatly affected all parts of private life and led to social distancing and self-isolation. Limited social support for older or frail people might have led to decreased oral health and its related quality of life. The current study aimed to investigate the social support of older seniors and self-perceived oral health-related quality of life (OHRQoL) over the course of the COVID-19 pandemic. Questionnaires were sent to all patients of the Dental Clinic of the University of Leipzig (Germany) aged 75, 80, or 85 years (n = 1228) at the end of February 2021. Besides demographic characteristics and care level, an adapted German version of the ENRICHD Social Support Inventory (ESSI-D) and the German Oral Health Impact Profile-14 (OHIP-14) were included. The response rate was 35.7% (n = 439). Twelve replies were not included in the data analysis as participants had either no interest, were cognitively impaired, or did not match the required age group. Analysis of ESSI-D revealed low social support for 13.2% (n = 53/403) of the seniors. No statistically significant impact of assigned care level on low social support was identified. Seniors with an assigned care level (CLyes) presented higher OHIP-14 sum scores (CLno/CLyes 6.43/10.12; p < 0.001). This was also true for six of the seven OHIP-14 domains, except for functional limitation. Regarding seniors with an assigned care level, a weak positive correlation was identified for sum scores of the ESSI-D and the OHIP-14 (r = 0.29). Despite the COVID-19 pandemic, older seniors reported high self-perceived social support. As seniors with an assigned care level revealed more impaired OHRQoL and a correlation with lower social support, special attention should be given to this vulnerable and frail group in times of a pandemic. When restrictions may minimize access to dental treatment and might negatively influence the oral health of older seniors, health care programs should offer more individual options for dental/medical appointments.

Stay-at-home orders and the willingness to stay home during the COVID-19 pandemic: A stated-preference discrete choice experiment

The spread of COVID-19 in the Spring of 2020 prompted state and local governments to implement a variety of policies, including stay-at-home (SAH) orders and mandatory mask requirements, aimed at reducing the infection rate and the severity of the pandemic’s impact. We implement a discrete choice experiment survey in three major U.S. States—California, Georgia, and Illinois—to empirically quantify individuals’ willingness to stay (WTS) home, measured as the number of weeks of a potential new SAH order, to prevent the spread of the COVID-19 disease and explore factors leading to their heterogeneous WTS. Our results demonstrate broad support for statewide mask mandates. In addition, the estimate of WTS to lower new positive cases is quite large, approximately five and half weeks, even though staying home lowers utility. We also find that individuals recognize the trade-offs between case reduction and economic slowdown stemming from SAH orders when they decide to stay home or not. Finally, pandemic related factors such as age, ability to work from home, and unemployment status are the main drivers of the heterogeneity in individuals’ WTS.

Adaptive Policies to Balance Health Benefits and Economic Costs of Physical Distancing Interventions during the COVID-19 Pandemic

Policy makers need decision tools to determine when to use physical distancing interventions to maximize the control of COVID-19 while minimizing the economic and social costs of these interventions. We describe a pragmatic decision tool to characterize adaptive policies that combine real-time surveillance data with clear decision rules to guide when to trigger, continue, or stop physical distancing interventions during the current pandemic. In model-based experiments, we find that adaptive policies characterized by our proposed approach prevent more deaths and require a shorter overall duration of physical distancing than alternative physical distancing policies. Our proposed approach can readily be extended to more complex models and interventions.

Suggestions for a Covid-19 Post-Pandemic Research Agenda in Environmental Economics

In this article we draw upon early lessons from the 2020 Covid-19 crisis and discuss how these may relate to a future research agenda in environmental economics. In particular, we describe how the events surrounding the Covid-19 crisis may inform environmental research related to globalization and cooperation, the green transition, pricing carbon externalities, as well as the role of uncertainty and timing of policy inventions. We also discuss the implications for future empirical research in this area.