Protective policies for all? An analysis of Covid-19 deaths and protective policies among low-, medium-, and high-vulnerability groups

Did the COVID-19 quarantine policies applied in Cochabamba, Bolivia mitigated cases successfully? an interrupted time series analysis

BACKGROUND

The COVID-19 pandemic prompted varied policy responses globally, with Latin America facing unique challenges. A detailed examination of these policies' impacts on health systems is crucial, particularly in Bolivia, where information about policy implementation and outcomes is limited.

OBJECTIVE

To describe the COVID-19 testing trends and evaluate the effects of quarantine measures on these trends in Cochabamba, Bolivia.

METHODS

Utilizing COVID-19 testing data from the Cochabamba Department Health Service for the 2020-2022 period. Stratified testing rates in the health system sectors were first estimated followed by an interrupted time series analysis using a quasi-Poisson regression model for assessing the quarantine effects on the mitigation of cases during surge periods.

RESULTS

The public sector reported the larger percentage of tests (65%), followed by the private sector (23%) with almost double as many tests as the public-social security sector (11%). In the time series analysis, a correlation between the implementation of quarantine policies and a decrease in the slope of positive rates of COVID-19 cases was observed compared to periods without or with reduced quarantine policies.

CONCLUSION

This research underscores the local health system disparities and the effectiveness of stringent quarantine measures in curbing COVID-19 transmission in the Cochabamba region. The findings stress the importance of the measures' intensity and duration, providing valuable lessons for Bolivia and beyond. As the global community learns from the pandemic, these insights are critical for shaping resilient and effective health policy responses.

Considering collaborative incident management: A study of the COVID-19 response and initial recovery in a rural West Virginia community

Hierarchical command-style structures are commonplace in the management of disasters, though researchers have begun to recommend the exploration of networked approaches to incident management. Furthermore, few studies are explicitly looking at the rural context of disaster management. This study seeks to contribute to both topics by examining the motivations for emergent collaboration in the direction of the response and initial recovery to the coronavirus disease 2019 pandemic in a rural West Virginia community. Between March 2020 and March 2022, the primary investigator moderated regular briefings of a community task force convened to coordinate the pandemic response and recovery. As regular operations concluded, members completed a survey, and 10 randomly selected members participated in semistructured interviews regarding their experiences in the task force. Survey responses suggest that common motivations for collaboration in nondisaster contexts (as they appear in the scholarly literature) and potential benefits of networked approaches highlighted in the incident management literature could also serve as motivators within the disaster context. Qualitative interview data extend that discussion and identify the need to gain clear information regarding the concerned authorities and specific local information to better inform the expenditure of limited resources as two additional motivators for collaboration.

Differential associations of mask mandates on COVID-19 infection and mortality by community social vulnerability

BACKGROUND

The COVID-19 pandemic in the United States has disproportionately impacted communities deemed vulnerable to disease outbreaks. Our objectives were to test (1) whether infection and mortality decreased in counties in the most vulnerable (highest) tercile of the Social Vulnerability Index (SVI), and (2) whether disparities between terciles of SVI were reduced, as the length of mask mandates increased.

METHODS

Using the New York Times COVID-19 and the Centers for Disease Control and Prevention SVI and mask mandate datasets, we conducted negative binomial regression analyses of county-level COVID-19 cases and deaths from 1/2020-11/2021 on interactions of SVI and mask mandate durations.

RESULTS

Mask mandates were associated with decreases in mid-SVI cases (IRR: 0.79) and deaths (IRR: 0.90) and high-SVI cases (IRR: 0.89) and deaths (IRR: 0.88). Mandates were associated with the mitigation of infection disparities (Change in IRR: 0.92) and mortality disparities (Change in IRR: 0.85) between low and mid-SVI counties and mortality disparities between low and high-SVI counties (Change in IRR: 0.84).

DISCUSSION

Mask mandates were associated with reductions in COVID-19 infection and mortality and mitigation of disparities for mid and high-vulnerability communities.

CONCLUSIONS

Ongoing COVID-19 response efforts may benefit from longer-standing infection control policies, particularly in the most vulnerable communities.

Open data for COVID-19 policy analysis and mapping

As the COVID-19 pandemic unfolded in the spring of 2020, governments around the world began to implement policies to mitigate and manage the outbreak. Significant research efforts were deployed to track and analyse these policies in real-time to better inform the response. While much of the policy analysis focused narrowly on social distancing measures designed to slow the spread of disease, here, we present a dataset focused on capturing the breadth of policy types implemented by jurisdictions globally across the whole-of-government. COVID Analysis and Mapping of Policies (COVID AMP) includes nearly 50,000 policy measures from 150 countries, 124 intermediate areas, and 235 local areas between January 2020 and June 2022. With up to 40 structured and unstructured characteristics encoded per policy, as well as the original source and policy text, this dataset provides a uniquely broad capture of the governance strategies for pandemic response, serving as a critical data source for future work in legal epidemiology and political science.

Political Economy of the COVID-19 Pandemic: How State Policies Shape County-Level Disparities in COVID-19 Deaths

The authors examine how two state-level coronavirus disease 2019 (COVID-19) policy indices (one capturing economic support and one capturing stringency measures such as stay-at-home orders) were associated with county-level COVID-19 mortality from April through December 2020 and whether the policies were more beneficial for certain counties. Using multilevel negative binominal regression models, the authors found that high scores on both policy indices were associated with lower county-level COVID-19 mortality. However, the policies appeared to be most beneficial for counties with fewer physicians and larger shares of older adults, low-educated residents, and Trump voters. They appeared to be less effective in counties with larger shares of non-Hispanic Black and Hispanic residents. These findings underscore the importance of examining how state and local factors jointly shape COVID-19 mortality and indicate that the unequal benefits of pandemic policies may have contributed to county-level disparities in COVID-19 mortality.

Comparison of State-Level Regulations for Cannabis Contaminants and Implications for Public Health

BACKGROUND

The presence of contaminants in cannabis presents a potential health hazard to recreational users and susceptible patients with medical conditions. Because of the federally illegal status of cannabis, there are no unified regulatory guidelines mitigating the public health risk of cannabis contaminants.

OBJECTIVE

To inform further research and provide solutions to the public health risk of cannabis contaminants at a national level, we examined the current landscape of state-level contaminant regulations, and cannabis contaminants of concern, as well as patient populations susceptible to contaminants.

METHODS

We examined the regulatory documents for medical and recreational cannabis in all legalized U.S. jurisdictions and compiled a complete list of regulated contaminants, namely, pesticides, inorganics, solvents, microbes, and mycotoxins. We data mined the compliance testing records of 5,654 cured flower and 3,760 extract samples that accounted for ∼6% of California's legal cannabis production in 2020-2021. We also reviewed the publicly available medical cannabis use reports to tabulate the susceptible patient populations.

RESULTS

As of 18 May 2022, 36 states and the District of Columbia listed a total of 679 cannabis contaminants as regulated in medical or recreational cannabis, including 551 pesticides, 74 solvents, 12 inorganics, 21 microbes, 5 mycotoxins, and 16 other contaminants. Different jurisdictions showed significant variations in regulated contaminants and action levels ranging up to four orders of magnitude. A failure rate of 2.3% was identified for flowers and 9.2% for extracts in the California samples. Insecticides and fungicides were the most prevalent categories of detected contaminants, with boscalid and chlorpyrifos being the most common. The contaminant concentrations fell below the regulatory action levels in many legalized jurisdictions, indicating a higher risk of contaminant exposure. Cannabis use reports indicated usage in several patient populations susceptible to contamination toxicity, including cancer (44,318) and seizure (21,195) patients.

DISCUSSION

Although individual jurisdictions can implement their policies and regulations for legalized cannabis, this study demonstrates the urgent need to mitigate the public health risk of cannabis contamination by introducing national-level guidelines based on conventional risk assessment methodologies and knowledge of patients' susceptibility in medical use. https://doi.org/10.1289/EHP11206.

What Makes Urban Communities More Resilient to COVID-19? A Systematic Review of Current Evidence

It has been more than two years since the outbreak of the COVID-19 epidemic at the end of 2019. Many scholars have introduced the "resilience" concept into COVID-19 prevention and control to make up for the deficiencies in traditional community governance. This study analyzed the progress in research on social resilience, which is an important component of community resilience, focusing on the current literature on the impact of social resilience on COVID-19, and proposed a generalized dimension to integrated previous relevant literature. Then, VOSviewer was used to visualize and analyze the current progress of research on social resilience. The PRISMA method was used to collate studies on social resilience to the pandemic. The result showed that many current policies are effective in controlling COVID-19, but some key factors, such as vulnerable groups, social assistance, and socioeconomics, affect proper social functioning. Some scholars have proposed effective solutions to improve social resilience, such as establishing an assessment framework, identifying priority inoculation groups, and improving access to technology and cultural communication. Social resilience to COVID-19 can be enhanced by both external interventions and internal regulation. Social resilience requires these two aspects to be coordinated to strengthen community and urban pandemic resilience.

Social capital's impact on COVID-19 outcomes at local levels

Over the past thirty years, disaster scholars have highlighted that communities with stronger social infrastructure—including social ties that enable trust, mutual aid, and collective action—tend to respond to and recover better from crises. However, comprehensive measurements of social capital across communities have been rare. This study adapts Kyne and Aldrich’s (Risk Hazards Crisis Public Policy11, 61–86, 2020) county-level social capital index to the census-tract level, generating social capital indices from 2011 to 2018 at the census-tract, zipcode, and county subdivision levels. To demonstrate their usefulness to disaster planners, public health experts, and local officials, we paired these with the CDC’s Social Vulnerability Index to predict the incidence of COVID-19 in case studies in Massachusetts, Wisconsin, Illinois, and New York City. We found that social capital predicted 41–49% of the variation in COVID-19 outbreaks, and up to 90% with controls in specific cases, highlighting its power as diagnostic and predictive tools for combating the spread of COVID.