An evaluation of the impact of mitigation policies on health and the economy by managing social distancing during outbreaks

The COVID-19 pandemic has necessitated various unavoidable social restrictions, leading to questions about the effectiveness of public emergency interventions and their impact economic growth. Block et al. (2020) conducted a notably study using an agent-based model to evaluate policies for reducing contact and demonstrated how choices in contact behavior can influence the rate and spread of the virus. However, their approach did not consider the economic consequences of these social restrictions. In response, we propose a set of strategies for governments to plan and evaluate policies during emergencies, aiming to contain infections while minimizing negative economic consequences. Our results indicate that there is no trade-off between containment strategies and economic output loss, making containment measures necessary policy instruments. However, potential trade-offs do emerge when selecting the most effective strategy. In this context, we propose and evaluate various policy alternatives to extreme "social distancing" measures, which can partially restore essential social interactions while preventing economic disasters induced by productivity losses.

COVID Protection Behaviors, Mental Health, Risk Perceptions, and Control Beliefs: A Dynamic Temporal Network Analysis of Daily Diary Data

BACKGROUND

To control infections, behavioral non-pharmaceutical interventions (NPIs) such as social distancing and hygiene measures (masking, hand hygiene) were implemented widely during the COVID-19 pandemic. At the same time, adherence to NPIs has also been implied in an increase in mental health problems. However, the designs of many existing studies are often poorly suited to disentangle complex relationships between NPI adherence, mental health symptoms, and health-related cognitions (risk perceptions, control beliefs).

PURPOSE

To separate between- and temporal within-person associations between mental health, health-related cognitions, and NPI adherence.

METHODS

Six-month ecological momentary assessment (EMA) study with six 4-day assessment bouts in 397 German adults. Daily measurement of adherence, mental health symptoms, and cognitions during bouts. We used dynamic temporal network analysis to estimate between-person, as well as contemporaneous and lagged within-person effects for distancing and hygiene NPIs.

RESULTS

Distinct network clusters of mental health, health cognitions, and adherence emerged. Participants with higher control beliefs and higher susceptibility were also more adherent (between-person perspective). Within-person, similar findings emerged, additionally, distancing and loneliness were associated. Lagged findings suggest that better adherence to NPIs was associated with better mental health on subsequent days, whereas higher loneliness was associated with better subsequent hygiene adherence.

CONCLUSIONS

Findings suggest no negative impact of NPI adherence on mental health or vice versa, but instead suggest that adherence might improve mental health symptoms. Control beliefs and risk perceptions are important covariates of adherence-both on between-person and within-person level.

The effects of policy changes and human mobility on the COVID-19 epidemic in the Dominican Republic, 2020-2021

Recent advances in technology can be leveraged to enhance public health research and practice. This study aimed to assess the effects of mobility and policy changes on COVID-19 case growth and the effects of policy changes on mobility using data from Google Mobility Reports, information on public health policy, and COVID-19 testing results. Multiple bivariate regression analyses were conducted to address the study objectives. Policies designed to limit mobility led to decreases in mobility in public areas. These policies also decreased COVID-19 case growth. Conversely, policies that did not restrict mobility led to increases in mobility in public areas and led to increases in COVID-19 case growth. Mobility increases in public areas corresponded to increases in COVID-19 case growth, while concentration of mobility in residential areas corresponded to decreases in COVID-19 case growth. Overall, restrictive policies were effective in decreasing COVID-19 incidence in the Dominican Republic, while permissive policies led to increases in COVID-19 incidence.

Do more stringent policies reduce daily COVID-19 case counts? Evidence from Canadian provinces

The enactment of COVID-19 policies in Canada falls under provincial jurisdiction. This study exploits time-series variation across four Canadian provinces to evaluate the effects of stricter COVID-19 policies on daily case counts. Employing data from this time-period allows an evaluation of the efficacy of policies independent of vaccine impacts. While both OLS and IV results offer evidence that more stringent Non-Pharmaceutical Interventions (NPIs) can reduce daily case counts within a short time-period, IV estimates are larger in magnitude. Hence, studies that fail to control for simultaneity bias might produce confounded estimates of the efficacy of NPIs. However, IV estimates should be treated as correlations given the possibility of other unobserved determinants of COVID-19 spread and mismeasurement of daily cases. With respect to specific policies, mandatory mask usage in indoor spaces and restrictions on business operations are significantly associated with lower daily cases. We also test the efficacy of different forecasting models. Our results suggest that Gradient Boosted Regression Trees (GBRT) and Seasonal Autoregressive-Integrated Moving Average (SARIMA) models produce more accurate short-run forecasts relative to Vector Auto Regressive (VAR), and Susceptible-Infected-Removed (SIR) epidemiology models. Forecasts from SIR models are also inferior to results from basic OLS regressions. However, predictions from models that are unable to correct for endogeneity bias should be treated with caution.

Analyzing Social Media Messaging on Masks and Vaccines: A Case Study on Misinformation During the COVID-19 Pandemic

Misinformation and disinformation during infectious disease outbreaks can hinder public health responses. This analysis examines comments about masks and COVID-19 vaccines on Twitter during the first six months of the COVID-19 pandemic. We conducted a content analysis of 6,600 randomly selected English-language tweets, examining tweets for health, political, of societal frames; inclusion of true information, false information, partially true/misleading information, and/or opinion; political components; risk frames; and use of specific types of rumor. We found false and partially false information in 22% of tweets in which we were able to assess veracity. Tweets with misinformation were more likely to mention vaccines, be political in nature, and promote risk elevating messages (p<0.5). We also found false information about vaccines as early as January 2020, nearly a year before COVID-19 vaccines became widely available. These findings highlight a need for new policies and strategies aimed to counter harmful and misleading messaging.

Epidemics, Lockdown Measures and Vulnerable Populations: A Mixed-Methods Systematic Review of the Evidence of Impacts on Mother and Child Health in Low-and Lower-Middle-Income Countries

BACKGROUND

The aim of this research was to synthetise the existing evidence on the impact of epidemic-related lockdown measures on women and children's health in low- and lower-middle-income countries (LLMICs).

METHODS

A mixed-methods systematic review was conducted of qualitative, quantitative and mixed-methods evidence. Between 1st and 10th of November 2021, seven scientific databases were searched. The inclusion criteria were that the paper provided evidence on the impact of lockdown and related measures, focused on LLMICs, addressed impacts on women and child's health, addressed epidemics from 2000-2020, was peer-reviewed, provided original evidence, and was published in English. The Joanne Briggs Institute's critical appraisal tools were used to assess the quality of the studies, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reporting. The evidence from the papers was grouped by type of lockdown measure and categories of impact, using a narrative data-based convergent synthesis design.

RESULTS

The review process identified 46 papers meeting the inclusion criteria from 17 countries that focussed on the coronavirus disease 2019 (COVID-19) and Ebola epidemics. The evidence on the decrease of utilisation of health services showed plummeting immunisation rates and faltering use of maternal and perinatal services, which was linked to a growth of premature deaths. Impacts on the mental health of children and women were convincingly established, with lockdowns associated with surges in depression, anxiety and low life satisfaction. Vulnerability may be compounded by lockdowns, as livelihoods were disrupted, and poverty levels increased.

CONCLUSION

Limitations included that searches were conducted in late-2020 as new research was being published, and that some evidence not published in English may have been excluded. Epidemic-related lockdown measures carry consequences for the health of women and children in lower-income settings. Governments will need to weigh the trade-offs of introducing such measures and consider policies to mitigate their impacts on the most vulnerable.

Perceptions of the ethical permissibility of strict travel restrictions to mitigate transmission of SARS-CoV-2

Although there has been extensive exploration of public opinion surrounding many non-pharmaceutical interventions (NPIs) aimed at mitigating transmission of SARS-CoV-2 (e.g. mask-wearing and social distancing), there has been less discussion of the public's perception of the ethical appropriateness other NPIs. This paper presents the results of a survey of U.S. adults' opinions of the ethical permissibility of both state-to-state and international travel restrictions to mitigate transmission of SARS-CoV-2. Our research revealed overall high agreement with the ethical permissibility of both state-to-state and international travel restrictions, though we saw significant difference across political party affiliation and conservative/liberal ideologies. Other factors associated with agreement with state-to-state travel restrictions included increasing education, increasing income, and both high and low commitment altruism. When considering international travel restrictions, income, education, and low commitment altruism were associated with increased agreement with the ethical permissibility of international travel restrictions. Ethical analysis and implications are explored.

Non-Pharmaceutical Interventions as Controls to mitigate the spread of epidemics: An analysis using a spatiotemporal PDE model and COVID-19 data

We investigate the spatiotemporal dynamics and control of an epidemic using a partial differential equation (PDE) based Susceptible-Latent-Infected-Recovered (SLIR) model. We first validate the model using empirical COVID-19 data corresponding to a period of 45 days from the state of Ohio, United States. Upon optimizing the model parameters in the learning phase of the analysis using actual infection data from a period of the first 30 days, we then find that the model output closely tracks the actual data for the next 15 days. Next, we introduce a control input into the model to represent the Non-Pharmaceutical Intervention of social distancing. Implementing the control using two distinct schemes, we find that in both cases the control input is able to significantly mitigate the infection spread. In addition to opening a novel pathway towards the characterization, analysis and implementation of Non-Pharmaceutical Interventions across multiple geographical scales using Control frameworks, our results highlight the importance of first-principles based PDE models in understanding the spatiotemporal dynamics of epidemics triggered by novel pathogens.

Effects of weather-related social distancing on city-scale transmission of respiratory viruses: a retrospective cohort study

Background

Unusually high snowfall in western Washington State in February 2019 led to widespread school and workplace closures. We assessed the impact of social distancing caused by this extreme weather event on the transmission of respiratory viruses.

Methods

Residual specimens from patients evaluated for acute respiratory illness at hospitals in the Seattle metropolitan area were screened for a panel of respiratory viruses. Transmission models were fit to each virus to estimate the magnitude reduction in transmission due to weather-related disruptions. Changes in contact rates and care-seeking were informed by data on local traffic volumes and hospital visits.

Results

Disruption in contact patterns reduced effective contact rates during the intervention period by 16 to 95%, and cumulative disease incidence through the remainder of the season by 3 to 9%. Incidence reductions were greatest for viruses that were peaking when the disruption occurred and least for viruses in an early epidemic phase.

Conclusion

High-intensity, short-duration social distancing measures may substantially reduce total incidence in a respiratory virus epidemic if implemented near the epidemic peak. For SARS-CoV-2, this suggests that, even when SARS-CoV-2 spread is out of control, implementing short-term disruptions can prevent COVID-19 deaths.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06028-4.