COVID-19 Mitigation Policies Research Articles

Parents' Perceptions of Schools' COVID-19 Mitigation Strategies: A Phenomenological Study.

At the onset of the COVID-19 pandemic, schools closed across the United States. Given the impact of virtual learning and lost access to school resources, schools eventually reopened with COVID-19 mitigation protocols in place. This qualitative study sought to understand parental perceptions of school-based COVID-19 mitigation strategies. Using a phenomenology approach, nine focus groups were completed with 40 parents of children in grades K-8 representing eight Maryland counties. Based on acceptance of masking policies (as indicated on a survey), parents were sorted into 2 groups-lower and higher masking acceptance. A thematic analysis was conducted for each group and themes were compared between the 2 groups. The main themes were related to parents' general sentiments regarding COVID-19, compliance, pandemic-related changes over time, changes in personal opinions, and in-person learning. Both groups described challenges related to inconsistent COVID-19 mitigation policies and practices, the challenges of rapid and frequent changes in guidelines during the pandemic, and the benefits of in-person learning. Parents of elementary and middle school children, regardless of general acceptance of masking policies, shared concerns about implementation and guidance regarding school-based mitigation strategies.

Assessing the Role of Surabaya City Government's Responsiveness Toward Public Acceptance of COVID-19 Mitigation Policies

Public acceptance, involving community awareness and support, is crucial for successful policy implementation. Despite challenges faced during the performance of the COVID-19 mitigation policy in Surabaya, the city government has shown responsiveness in addressing the issue. This study investigates the influence of the Surabaya City Government's responsiveness on public acceptance of the COVID-19 mitigation policy. Employing the Policy Acceptance Model and government responsiveness theory, a quantitative survey was conducted with 400 purposively sampled respondents. Results indicate a significant positive effect, indicating that higher government responsiveness leads to greater public acceptance of the COVID-19 mitigation policy. These findings support existing theories and validate the importance of community support in policy implementation

Auditory Learner

Auditory Learner

Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning

Infectious disease outbreaks can have a disruptive impact on public health and societal processes. As decision-making in the context of epidemic mitigation is multi-dimensional hence complex, reinforcement learning in combination with complex epidemic models provides a methodology to design refined prevention strategies. Current research focuses on optimizing policies with respect to a single objective, such as the pathogen’s attack rate. However, as the mitigation of epidemics involves distinct, and possibly conflicting, criteria (i.a., mortality, morbidity, economic cost, well-being), a multi-objective decision approach is warranted to obtain balanced policies. To enhance future decision-making, we propose a deep multi-objective reinforcement learning approach by building upon a state-of-the-art algorithm called Pareto Conditioned Networks (PCN) to obtain a set of solutions for distinct outcomes of the decision problem. We consider different deconfinement strategies after the first Belgian lockdown within the COVID-19 pandemic and aim to minimize both COVID-19 cases (i.e., infections and hospitalizations) and the societal burden induced by the mitigation measures. As such, we connected a multi-objective Markov decision process with a stochastic compartment model designed to approximate the Belgian COVID-19 waves and explore reactive strategies. As these social mitigation measures are implemented in a continuous action space that modulates the contact matrix of the age-structured epidemic model, we extend PCN to this setting. We evaluate the solution set that PCN returns, and observe that it explored the whole range of possible social restrictions, leading to high-quality trade-offs, as it captured the problem dynamics. In this work, we demonstrate that multi-objective reinforcement learning adds value to epidemiological modeling and provides essential insights to balance mitigation policies.

Crisis Leadership in the Time of Covid: Effects of Personality Traits on Response Speed

Abstract Why were some countries faster than others at introducing COVID-19 mitigation policies? Existing research shows that leaders are central to defining and making sense of crises, which then shapes their governments’ crisis response. I argue that crisis-sense-making depends on leaders’ personality traits pertaining to how they perceive their power status, collect and process information, and interact with their environment, subsequently influencing their governments’ crisis response speed. I test this argument in the context of the European experience with COVID-19, combining an original Leadership Traits Analysis dataset of thirty-two leaders with the Oxford COVID-19 Government Response Tracker data. I show that leaders who were highly self-confident or exhibited a tendency to challenge constraints were significantly slower at introducing pandemic mitigation policies. Leaders who were open to information were significantly faster to do so. I also show that policy emulation between countries over time dissipated the slowing effects of the leaders’ need for power and conceptual complexity on response speed. The results present new and systematic evidence on how leader personality shaped pandemic policy-making, contributing to the literature on crisis policy-making and political leadership. They also offer science advisors food for thought on how to communicate with leaders.

Emerging Adult Mental Health During COVID: Exploring Relationships Between Discrete and Cumulative Individual and Contextual Stressors and Well-Being

PurposeIndicators of poor mental health increased during the COVID-19 pandemic among emerging adults aged 18–24 years, a group already at elevated risk. This study explores associations between contextual and personal stressors with symptoms of emerging adults’ anxiety and depression, assessing both multidimensional and distinct measures of stress. MethodsUsing Census Household Pulse Surveys from emerging adults aged 18 to 24 years (N = 71,885) and administrative data from April 23, 2020 to March 29, 2021, we estimated logistic regression models adjusted for state and wave fixed effects. ResultsRates of elevated anxiety and depressive symptoms rose dramatically among emerging adults during the first year of the COVID-19 pandemic. Results indicate that potential contextual stressors—state COVID-19 rates and state COVID-19 mitigation policies limiting social interactions (stay-at-home orders, restaurant closures, large gathering restrictions, and mask mandates)—were not significantly associated with symptoms. In contrast, personal economic stressors (nonemployment, household income loss, food insecurity, housing insecurity, lacking health insurance) and disruptions to education were associated significantly with elevated anxiety and depressive symptoms, with greater numbers of stressors associated with worse well-being. DiscussionEmerging adults reported persistently high levels of elevated anxiety and depressive symptoms during the first year of the pandemic, outcomes associated not with COVID-19 rates or mitigation policies, but with economic inequities, and other personal stressors heightened by the pandemic. Providing targeted support for young adults, including ensuring access to mental health supports, health care, and economic relief, is critical.

BUILDING ADMINISTRATIVE CAPACITY: TACKLING DOMESTIC VIOLENCE AMIDST THE COVID-19 PANDEMIC

The implementation of Covid-19 mitigation policies has hindered the effective functioning of public services. During the Covid-19 pandemic, domestic violence cases remained hidden due to victims' limited access to reporting channels, despite the government's efforts in establishing P2TP2A and SEJIWA psychological services. The persistently high incidence of domestic violence prompted Farazmand (2009) to advocate for increasing the state's administrative capacity to confront unforeseen challenges. This article examines Indonesia's approach to addressing domestic violence during the pandemic through Farazmand's Administrative Capacity Building recipe, utilizing a descriptive qualitative methodology with a literature study. The analysis reveals a pressing need for preventive services in Indonesia, such as social marketing and the implementation of artificial intelligence (AI) technology in creating applications that can proactively combat domestic violence, aligning with Farazmand's notion of "anticipatory" administrative capacity.

Studying the impact of COVID-19 mitigation policies on childhood obesity, health behaviors, and disparities in an observational cohort: Protocol for the COVID-19 Family Study

BackgroundCOVID-19 pandemic control policies, including school closures, suspended extra-curricular activities, and social distancing, were introduced to prevent viral transmission, and disrupted children's daily routines, health behaviors, and wellness. This observational cohort study among 697 families with children or adolescents, based on the Family Stress Model, aims to: 1) evaluate pre- to during-pandemic changes in child health behaviors (diet, physical activity, sleep) and weight gain, 2) identify mechanisms explaining the changes, and 3) determine projected healthcare costs on weight gain and obesity. Each aim includes an examination by racial and ethnic, socioeconomic, and geographic disparities. MethodsThe study employs a mixed methods design, recruiting children and their caregivers from two obesity prevention trials halted in 2020. Enrolled participants complete annual surveys to assess child health behaviors, family resources, routines, and demographics, and home environment in 2020–2022. Height and weight are measured annually in 2021–2022. Annual semi-structured interviews are conducted within a subsample to understand mechanisms of observed changes. Multilevel mixed models and mediation analyses are used to examine changes in child health behaviors and weight gain and mechanisms underlying the changes. Qualitative data are analyzed within and across time points and integrated with quantitative findings to further explain mechanisms. Markov models are used to determine healthcare costs for unhealthy child behaviors and weight gain. ConclusionFindings from this study will aid in understanding pandemic-related changes in child health behaviors and weight status and will provide insights for the implementation of future programs and policies to improve child and family wellness.

Lessons Learned From Applying a Monitoring and Evaluation Framework to Economic, Social, and Other Health Impacts of the COVID-19 Pandemic.

Individual and community-level COVID-19 mitigation policies can have effects beyond direct COVID-19 health outcomes, including social, behavioral, and economic outcomes. These social, behavioral, and economic outcomes can extend beyond the pandemic period and have disparate effects on populations. Public Health-Seattle & King County (PHSKC) built on the Centers for Disease Control and Prevention's community mitigation strategy framework to create a local project tracking near-real-time data to understand factors affected by mitigation approaches, inform decision-making, and monitor and evaluate community-level disparities during the pandemic. This case study describes the framework and lessons learned from PHSKC's collation, use, and dissemination of local data from 20 data sources to guide community and public health decision-making. Social, behavioral, economic, and health indicators were regularly updated and disseminated through interactive dashboards and products that examined data in the context of applicable policies. Data disaggregated by demographic characteristics and geography highlighted inequities, but not all datasets contained the same details; local surveys or qualitative data were used to fill gaps. Project outcomes included informing city and county emergency response planning related to implementation of financial and food assistance programs. Key lessons learned included the need to (1) build on existing processes and use automated processes and (2) partner with other sectors to use nontraditional public health data for active dissemination and data disaggregation and for real-time data contextualized by policy changes. This project provided programs and communities with timely, reliable data to understand where to invest recovery funding. A similar framework could position other health departments to examine social and economic effects during future public health emergencies.

Development of a community-informed communication toolkit to prevent spread of viral illness in schools, including SARS-COV-2.

Schools were uniquely impacted during the COVID-19 (SARS-COV-2) pandemic. We sought to elucidate how parents/guardians of elementary and middle school students in Maryland navigated the return to in-person school following remote instruction. We also sought to understand how they perceived communication about school-based COVID-19 mitigation strategies and their preferences for the content and format of public health communication about COVID-19 mitigation in schools. We engaged a community advisory board comprised of key partners and implemented a survey and focus groups. Results indicated that parents/guardians wanted clearer communication about COVID-19 mitigation policies in schools and were experiencing fatigue and confusion. These insights informed the development of a tailorable communication toolkit. The toolkit was designed to (1) inform parents/guardians about the importance and effectiveness of mitigation strategies for preventing viral spread to keep children in school, (2) promote a sense of community and support, and (3) help school communication teams effectively communicate information about mitigation strategies being implemented. We describe a process for leveraging schools as a trusted messenger, engaging school communities in the development of communication messages, and utilizing a tailorable communication toolkit in the context of shifting public health guidance and local needs. The toolkit development and dissemination process offers a model for targeting public health messaging to parents/guardians in school settings.

Population-Level Disparities in Exposure to COVID-19 Mitigation Policies, April 2020-April 2021.

Studies have found that COVID-19 stay-at-home orders (SHOs) and face mask policies (FMPs) were associated with reduced COVID-19 transmission and deaths. But it is unknown whether exposure to these policies varied by sociodemographic characteristics across the US population. The goal of this study was to quantify and characterize the sociodemographic characteristics and geographic distribution of populations exposed to evidence-based COVID-19 mitigation policies. We obtained statewide SHOs and FMPs for all US counties from April 10, 2020, to April 10, 2021, calculated median policy lengths, and categorized counties into 4 groups based on length of policy exposure: low SHO-low FMP, high SHO-low FMP, low SHO-high FMP, and high SHO-high FMP. We described exposure groups by COVID-19 cumulative case/death and vaccination rates and county sociodemographic characteristics. In total, 3142 counties from all 50 states and Washington, District of Columbia, were included in the analysis. County-level sociodemographic factors and county cumulative rates for COVID-19 cases, deaths, and vaccinations. The largest percentage of the US population lived in counties with high exposure to SHOs and FMPs. However, populations living in high SHO-high FMP counties had the lowest percent non-Hispanic Black (NHB) and highest percent non-Hispanic White (NHW) populations. Populations living in high SHO-low FMP counties had the highest percent NHB and Hispanic populations and the lowest percent NHW population. This study identified county-level racial, ethnic, and sociodemographic disparities in exposure to evidence-based statewide COVID-19 mitigation policies. Exposure to evidence-based policies is an important consideration for studies evaluating the root causes of health inequities.

Partisan self-identification predicts attitudes of South Dakota nurses toward COVID-19 vaccine mandate for healthcare workers

ObjectivesNurses are at greater risk of infection from COVID-19. However, mistrust of the vaccine exists even among this group. In the United States, the government implemented a vaccine mandate for health care workers to increase vaccination rates. This study investigated the drivers of nurses’ attitudes toward the mandate. MethodsWe fielded a survey to study the attitudes of nurses toward COVID-19 vaccine mandate for HCWs. We contacted nurses in South Dakota, United States, based on the information from the South Dakota Board of Nursing. The survey was open in June and July 2022. We conducted a multivariate regression analysis to identify the factors that predict attitudes toward this regulation. ResultsWe received 1,084 responses. Results of regression analysis showed statistically significant relationships between partisan self-identification, evangelical identity, gender, and COVID-19 vaccination status and support for COVID-19 vaccine mandate for healthcare workers. Age, time with patients, positive COIVD-19 test in the last year, education, and nurse classification variables were not statistically significant. ConclusionsThe same factors that drive people's attitudes toward COVID-19 mitigation policies also explain nurses’ attitudes toward a vaccine mandate for healthcare workers. The politicization of the COVID-19 pandemic is present also among nurses. Health care officials should be mindful of the influence of these biases as they evaluate the vaccine mandate and develop new regulations.

Digital Communications Technology Use and Feelings of Anxiety, Depression, and Loneliness Among Older Adults During the COVID-19 Pandemic.

Some have touted technology as a panacea for overcoming the isolation associated with COVID-19 mitigation policies; yet, these tools are not widely adopted by older adults. With data from the COVID-19 supplement to the National Health and Aging Trends Survey, we conduct adjusted Poisson regression modeling to examine digital communications use during COVID-19 and feelings of anxiety, depression, and loneliness during the COVID-19 pandemic among older adults (65+ years of age). Adjusted Poisson regression revealed that those who reported frequent use of video calls with friends and family (aPR = 1.22, 95% CI:1.06-1.41) and with healthcare providers (aPR = 1.22, 95% CI:1.03-1.45) were more likely to report feelings of anxiety than those not using these platforms; yet, reports of in-person visits with friends and family (aPR = 0.79, 95% CI: 0.66-0.93) and with healthcare providers (aPR = 0.88, 95% CI: 0.77-1.01) were associated with fewer feelings of depression and loneliness, respectively. Future research is needed to tailor digital technology to support older adults.

Surveillance of SARS-CoV-2 in sewage from buildings housing residents with different vulnerability levels

During the last three years, various restrictions have been set up to limit the transmission of the Coronavirus Disease (COVID-19). While these rules apply at a large scale (e.g., country-wide level) human-to-human transmission of the virus that causes COVID-19, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), occurs at a small scale. Different preventive policies and testing protocols were implemented in buildings where COVID-19 poses a threat (e.g., elderly residences) or constitutes a disruptive force (e.g., schools). In this study, we sampled sewage from different buildings (a school, a university campus, a university residence, and an elderly residence) that host residents of different levels of vulnerability. Our main goal was to assess the agreement between the SARS-CoV-2 concentration in wastewater and the policies applied in these buildings. All buildings were sampled using passive samplers while 24 h composite samples were also collected from the elderly residence. Results showed that passive samplers performed comparably well to composite samples while being cost-effective to keep track of COVID-19 prevalence. In the elderly residence, the comparison of sampling protocols (passive vs. active) combined with the strict clinical testing allowed us to compare the sensitivities of the two methods. Active sampling was more sensitive than passive sampling, as the former was able to detect a COVID-19 prevalence of 0.4 %, compared to a prevalence of 2.2 % for passive sampling. The number of COVID-19-positive individuals was tracked clinically in all the monitored buildings. More frequent detection of SARS-CoV-2 in wastewater was observed in residential buildings than in non-residential buildings using passive samplers. In all buildings, sewage surveillance can be used to complement COVID-19 clinical testing regimes, as the detection of SARS-CoV-2 in wastewater remained positive even when no COVID-19-positive individuals were reported. Passive sampling is useful for building managers to adapt their COVID-19 mitigation policies.

The benefit of vaccination after previous SARS-CoV-2 infection in the omicron era

The benefit of vaccination after previous SARS-CoV-2 infection in the omicron era

UNPARTNERED AND CHILDLESS OLDER ADULTS' RISK OF LONELINESS DURING COVID-19 BY COUNTRY CONTEXT

Abstract Older adults with non-traditional family structures (unpartnered and childless) may be at higher risk for loneliness. Yet, experiences of loneliness during COVID-19 can vary depending on a country’s context (e.g., culture, demography, COVID-19 mitigation policies, severity of the pandemic). We explore associations between older Europeans’ family structure and loneliness to assess risks for those with non-traditional family structures (e.g., unpartnered vs partnered, childless vs parents) during the pandemic across a variety of country contexts. We analyze data from the Survey of Health, Ageing and Retirement in Europe (SHARE) collected before (2019/2020) and twice during (2020, 2021) the pandemic to examine if unpartnered and childless older adults are at higher risk of loneliness, and compare results by multiple indicators of country context (fertility and partnership rates, stringency of COVID mitigation policies, population age composition, and COVID fatality rates). Results of this study can potentially inform current and future pandemic mitigation strategies.

COVID-19 ambassadors: Recognizing Kampus Mengajar at the Merdeka Belajar Kampus Merdeka program humanitarian projects in the tertiary education curriculum

As of April 2022, various countries around the world have shown their success in tackling the COVID-19 pandemic, including Indonesia. One of the COVID-19 mitigation policies in Indonesia is the involvement of students as COVID-19 ambassadors through a program called Kampus Mengajar, which carries 12 credits. However, the COVID-19 ambassador experienced academic injustice because the participating study programs and faculties did not recognize the program. The purpose of this research is to analyze the recognition of COVID-19 ambassadors who participate in the program. This research uses a case study-type qualitative research. The research setting is Universitas Ahmad Dahlan involving 70 students of the program and seven heads of faculties and study programs. Observation and in-depth interviews were administered with the head of the faculty and study programs. The results showed that study programs and faculties at universities could only recognize the activities of COVID-19 ambassador students in the program that have relevance to certain subjects. Thus, the higher education unit bureaucracy has lost its human dimension and is unfair to the student ambassadors of COVID-19. The implications of the findings of this study become a scathing critique of the fading of human values in higher education.

Analyzing the Effectiveness of COVID-19 Mitigation Policies Using ARIMA Forecasting

The SARS-CoV-2 virus has triggered a worldwide pandemic situation which countries are desperately trying to adapt to. In order to halt the transmission of this virus, these countries have implemented COVID-19 mitigation policies, which are designed to suppress the spread and deadliness of the virus. However, there has not been much research into the effectiveness of these COVID-19 mitigation policies. Using data from the Kaggle Platform as well as the European Centre for Disease Prevention and Control, we hope to use an ARIMA time series forecasting model in order to identify effective COVID-19 mitigation polices. This will be done by analyzing the cases time series before the mitigation policy was implemented in a certain country and generating a predicted forecast curve during the time range of the mitigation policy. By comparing this generated curve with the actual curve, deviations will be able to be identified, indicating the significance of the mitigation policy during its implementation. Although most forecasting was relatively inaccurate due to a shortage in training data, one social distancing mitigation policy in South Korea had a clear deviation between the forecast curve without the influence of the mitigation policy and the actual curve. Overall, the ARIMA model has its merits and may prove to be useful with the collection of more data. By analyzing the effectiveness of these policies, future research into this topic may lead to a greater understanding about the transmission of COVID-19 and ways to suppress it.

Information Environments and Support for COVID-19 Mitigation Policies

This research assesses how the environment for coronavirus disease (COVID) information contributed to the public’s willingness to support measures intended to mitigate the spread and transmission of the virus in the early stages of the pandemic. A representative sample of 600 Floridians was surveyed in April 2020. After controlling for sociodemographic factors, COVID anxiety, and knowledge about the virus, we find that components of the information environment mattered for public opinion related to mitigation policies. Television news sources, including local and national network news, center-left cable news (i.e., CNN, MSNBC), and Fox News, contributed to shaping policy support. The results highlight the importance of televised news coverage in shaping public opinion toward healthcare-related policies.

Determinants of voluntary compliance: COVID-19 mitigation

During the pre-vaccine period, the success of containing the spread of COVID-19 depends upon how communities respond to non-pharmaceutical mitigation policies such as social distancing, wearing of masks, retail and dining constraints, crowd limitation, and shelter-in-place orders. Of these policies, shelter-in-place and social distancing are of central importance. By using county-level mobility data as a measure of a community's voluntary compliance with social distancing policies, this study found that counties who received strong state social distancing policy directives and who had a high pro-social character showed lower mobility on retail and recreation mobility and grocery and pharmacy mobility (better social distancing) after states reopened from shelter-in-place orders. Counties that experienced a longer duration of shelter-in-place orders showed higher mobility (less social distancing), implying that the duration of the shelter-in-place order deteriorated social distancing response after reopening. This may be because reopening sent a “safe” signal to these counties or resulted in a response to the pent-up demand inducing higher mobility. The results indicate that implementing shelter-in-place and social distancing policies to slow down the transmission of COVID-19 were not necessarily effective in motivating a county to reduce mobility voluntarily. A county's pro-social character and the duration of shelter-in-place order should be considered when designing COVID-19 mitigation policies.