COVID-19 dynamics in an Ohio prison.

Incarcerated individuals are a highly vulnerable population for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding the transmission of respiratory infections within prisons and between prisons and surrounding communities is a crucial component of pandemic preparedness and response. Here, we use mathematical and statistical models to analyze publicly available data on the spread of SARS-CoV-2 reported by the Ohio Department of Rehabilitation and Corrections (ODRC). Results from mass testing conducted on April 16, 2020 were analyzed together with time of first reported SARS-CoV-2 infection among Marion Correctional Institution (MCI) inmates. Extremely rapid, widespread infection of MCI inmates was reported, with nearly 80% of inmates infected within 3 weeks of the first reported inmate case. The dynamical survival analysis (DSA) framework that we use allows the derivation of explicit likelihoods based on mathematical models of transmission. We find that these data are consistent with three non-exclusive possibilities: (i) a basic reproduction number >14 with a single initially infected inmate, (ii) an initial superspreading event resulting in several hundred initially infected inmates with a reproduction number of approximately three, or (iii) earlier undetected circulation of virus among inmates prior to April. All three scenarios attest to the vulnerabilities of prisoners to COVID-19, and the inability to distinguish among these possibilities highlights the need for improved infection surveillance and reporting in prisons.

Intention to vaccinate against COVID-19 and potential outreach strategies for a residential research university in Northeastern Ohio.

INTRODUCTION: A university's understanding of student, faculty, and staff members' intention to vaccinate against COVID-19 has been vital in returning safely to in-person education, research, and engagement with communities and professions. We employed a novel survey to describe intentions across subpopulations of one campus and consider key issues in their rationales for intentions and hesitancies. MATERIALS AND METHODS: 1,077 surveys based on Theory of Planned Behavior were completed from randomly selected pools of undergraduate students, graduate students, part-time faculty, full-time faculty, and staff. Chi-Squared Automated Interaction Detection algorithm analysis provided paths for evaluation. RESULTS AND DISCUSSION: 83 percent of respondents said they would receive the vaccine at their first opportunity, while 5 percent said they would never get the vaccine; the remaining 12 percent wanted more evidence before getting the vaccine. Findings included negative health perceptions of the vaccine, misinformation on the process, as well as negative rhetorical responses differentiated between political partisanship and membership within the campus community, eg, faculty, staff, or student. IMPLICATIONS: Universities seeking to raise campus vaccination rates should concentrate limited resources on the largest populations with the most opportunity to vaccinate. In this study, newer students, with conservative political views, represented a population of opportunity. Their formative beliefs may be influenced by messaging and in collaboration with students' personal physician and/or friend groups. A theory-based approach leads to focused efforts for safer campuses and resumption/continuation of face-to-face interactions for students, faculty, and staff.

Attitudes towards social distancing in response to COVID-19.

OBJECTIVES: COVID-19 has highlighted differences in our engagement in health prevention behaviors. The Health Belief Model (HBM), personality traits (conscientiousness, extraversion, and neuroticism), and sociodemographic variables were used to evaluate social distancing during the first month of a state-mandated Stay At Home (SAH) order. DESIGN: A web-based convenience sample of 645 Ohioans was surveyed. Hierarchical linear regression and mediation analysis were used to examine predictors of social distancing attitudes and behaviors and whether health beliefs mediated the relationship between personality and social distancing. RESULTS: Most respondents agreed with and adhered to social distancing guidelines. HBM constructs were strong predictors of SAH attitudes, while personality accounted for little additional variance. Anxiety was indirectly related to overall social distancing attitudes and behavior through its relationship with health beliefs. However, violations of social distancing were best explained by situational factors (e.g., being an essential worker). CONCLUSION: The results demonstrate the power of components of the HBM to explain attitudes and behaviors regarding the SAH order beyond any contribution from personality. By examining the role of personality and health beliefs on social distancing attitudes and behaviors, this research will benefit public health nurses and others tasked with communicating and promoting preventative health behavior.

Estimates of the value of life lost from COVID-19 in Ohio.

The economic burden of mortality due to the novel coronavirus (COVID-19) extends beyond the lives lost. Data from the Ohio Department of Public Health and Social Security Administration was used to estimate the years of potential life lost, 72,274 and economic value of those lost lives, US$17.39 billion. These estimates may be used to assess the risk-trade off of COVID-19 mitigation strategies in Ohio.

Improving Surveillance and Epidemic Response in Ohio Childcare Settings.

At the start of the Coronavirus Disease of 2019 (COVID-19) pandemic, the risk of cases in childcare programs was unknown. Thus, a rapid-response research approach was launched in Ohio childcare settings. Passive surveillance data from a state-operated incident reporting system were evaluated to estimate the number of COVID-19 cases from 15 August 2020 to 1 January 2021. Additionally, active surveillance with self-administered reverse transcriptase-polymerase chain reaction (RT-PCR) tests were conducted among staff at 46 childcare programs. Finally, six zoom-based focus groups with program administrators were used to gain feedback. Staff and children in childcare settings contributed 0.38% and 0.15% of the COVID-19 cases in Ohio during this timeframe, respectively. RT-PCR testing identified 3 unrecognized cases (0.88% of tests), and all occurred when the statewide positivity rate was >5%. Focus groups revealed that access to affordable cleaning supplies, masks, and reliable staffing were critical. Perhaps most importantly, we conclude that expanding the incident reporting system to include a childcare census would allow for the tracking of future health problems with highly valuable incidence rate estimations.

Individual and Work-Related Characteristics Associated with COVID-19 Vaccination Status among Ohio Nurses.

Uptake of the COVID-19 vaccine by nurses lags behind that of other health care professionals with minimal empirical evidence to understand this phenomenon. In this secondary analysis, we examined nurses' individual and work-related characteristics and their association with COVID-19 vaccination status. Alumni of three Ohio nursing colleges and members of a professional organization were invited to complete questionnaires from June through August 2021. Logistic regression models were used to evaluate associations between nurse characteristics and vaccination status. Among 844 respondents, 754 (80.30%) had received at least one dose of the vaccine. Older age, having a bachelor's degree or higher, and working in critical care were associated with vaccination. Providing direct care for COVID-19 patients in the last 7 days and a higher perception of one's work being affected by COVID-19 were significantly associated with being vaccinated, whereas prior COVID-19 infection was inversely associated with vaccination status. Our findings suggest that COVID-19 vaccine uptake among nurses is influenced by a host of factors related to virus knowledge, beliefs, and risk perceptions. Awareness of these factors can aid the development of interventions to increase nurses' acceptance of vaccines.

The Ohio Maternal Safety Quality Improvement Project: initial results of a statewide perinatal hypertension quality improvement initiative implemented during the COVID-19 pandemic.

BACKGROUND: Hypertensive disorders of pregnancy are a leading cause of severe maternal morbidity and mortality, and studies have shown that more than 60% of cases are preventable. As part of a statewide quality Maternal Safety Quality Improvement Project, we adapted the Alliance for Innovation on Maternal Health Severe Hypertension in Pregnancy bundle in a consortium of maternity hospitals in Ohio to improve care processes and outcomes for patients with a severe hypertensive event during pregnancy or the postpartum period. OBJECTIVE: This study aimed to report the first year of data from this Maternal Safety Quality Improvement Project, including an assessment of the process measures by hospital level of maternal care designation, and provide perspective on the unique challenges of implementing a large-scale Maternal Safety Quality Improvement Project during a global pandemic. STUDY DESIGN: This Maternal Safety Quality Improvement Project engaged Ohio level 1 to 4 maternity hospitals and provided multimodal quality improvement support. Participating hospitals submitted monthly patient-level data, which included all cases of new-onset sustained severe hypertension. The primary process measure was the proportion of birthing people in Ohio with sustained severe hypertension who received treatment with appropriate acute antihypertensive therapy within 60 minutes. The secondary process measures included receipt of a follow-up appointment after hospital discharge within 72 hours (if discharged on medication) or 10 days (if discharged without medication), a blood pressure cuff on hospital discharge, and education about urgent maternal warning signs. Data for primary and secondary process measures were plotted on a biweekly basis, and statistical process control methods were used to identify special cause variation over time. Data were stratified by various demographic variables, including race or ethnicity, insurance status, and maternal level of care. To assess the effect of the COVID-19 pandemic on this Maternal Safety Quality Improvement Project, process measure data were compared with COVID-19 case volume in Ohio across the study epoch. RESULTS: A total of 29 hospitals participated in the project from July 2020 to September 2021. Data were collected on 4948 hypertensive events representing 4678 unique patients. In aggregate, the primary process measure (timely and appropriate treatment) demonstrated a 19.3% increase (from a baseline of 56.5% to 67.4%; P<.001). The secondary process measures demonstrated significant increases ranging from 26.1% to 166.8% (all P<.001). Both non-Hispanic Black and White pregnant or postpartum people demonstrated shifts and sustained improvements in the treatment of severe hypertension, which did not differ by race across the study period. Process measure improvements were achieved and sustained across peaks in the COVID-19 pandemic. CONCLUSION: This Ohio Maternal Safety Quality Improvement Project demonstrated meaningful changes in project process measures in the identification and treatment of severe hypertension in pregnancy and the postpartum period. Process measures improvements were achieved across all hospital levels of maternal care, and differences were not observed by race or ethnicity. Our findings suggest that a robust and comprehensive quality improvement initiative with appropriate support and resources can achieve meaningful gains in the setting of a global pandemic.

SARS-CoV-2 Reinfection With Different SARS-CoV-2 Variants in Children, Ohio, United States.

BACKGROUND: Beginning in late 2021, we observed a significant increase in SARS-CoV-2 reinfections in pediatric patients evaluated at our institution. We aimed to characterize the children with SARS-CoV-2 reinfection, determine the number of SARS-CoV-2 reinfections, and characterize the intervals between two infections in our patient population. METHODS: From March 2020 to September 2022, we identified children ≤21 years old who had ≥2 SARS-CoV-2 infections using laboratory reports. We then defined the type of SARS-CoV-2 variant in the first and subsequent infections by mutation-specific typing or local epidemiology data. Clinical outcomes and the intervals between SARS-CoV-2 infections were assessed. RESULTS: We identified 541 children with ≥2 SARS-CoV-2 infections. The median interval between two infections was 229 days. The hospitalization rate was lower in the second infection. Reinfection counts were higher during the periods that Omicron variants predominated. Reinfection occurred more rapidly when Omicron variants were circulating with some occurring in less than 90 days. CONCLUSIONS: As SARS-CoV-2 continues to evolve, there is a need for ongoing surveillance to identify the frequency and time interval between reinfections and to re-evaluate the definition of SARS-CoV-2 reinfections.

SARS-CoV-2 Seroprevalence Among First Responders in Northeastern Ohio, 2020.

OBJECTIVES: First responders, including firefighters, emergency medical technicians (EMTs), paramedics, and law enforcement officers, are working on the front lines to fight the COVID-19 pandemic and facing an increased risk of infection. This study assessed the seroprevalence of SARS-CoV-2 infection among first responders in northeastern Ohio. METHODS: A survey and immunoglobulin G antibody test against SARS-CoV-2 nucleocapsid protein were offered to University Hospitals Health System-affiliated first-responder departments during May to September 2020. The survey contained questions about demographic characteristics and history of SARS-CoV-2 infection. A total of 3080 first responders with diverse job assignments from more than 400 fire and police departments participated in the study. RESULTS: Of 3080 participants, 73 (2.4%) were seropositive and 26 (0.8%) had previously positive real-time polymerase chain reaction results. Asymptomatic infection accounted for 46.6% (34 of 73) of seropositivity. By occupation, rates of seropositivity were highest among administration/support staff (3.8%), followed by paramedics (3.0%), EMTs (2.6%), firefighters (2.2%), and law enforcement officers (0.8%). Work-associated exposure rates to COVID-19 patients were: paramedics (48.2%), firefighters (37.1%), EMTs (32.3%), law enforcement officers (7.7%), and administration/support staff (4.4%). Self-reported community exposure was positively correlated with self-reported work-associated exposure rate (correlation coefficient = 0.99). Neither self-reported community nor work-associated exposure was correlated with SARS-CoV-2 seroprevalence. We found no significant difference in seroprevalence among sex/gender or age groups; however, Black participants had a higher positivity rate than participants of other racial groups despite reporting lower exposure. CONCLUSIONS: Despite the high work-associated exposure rate to SARS-CoV-2 infection, first responders with various roles demonstrated seroprevalence no higher than their administrative/supportive colleagues, which suggests infection control measures are effective in preventing work-related infection.

Projecting COVID-19 cases and hospital burden in Ohio.

As the Coronavirus 2019 disease (COVID-19) started to spread rapidly in the state of Ohio, the Ecology, Epidemiology and Population Health (EEPH) program within the Infectious Diseases Institute (IDI) at The Ohio State University (OSU) took the initiative to offer epidemic modeling and decision analytics support to the Ohio Department of Health (ODH). This paper describes the methodology used by the OSU/IDI response modeling team to predict statewide cases of new infections as well as potential hospital burden in the state. The methodology has two components: (1) A Dynamical Survival Analysis (DSA)-based statistical method to perform parameter inference, statewide prediction and uncertainty quantification. (2) A geographic component that down-projects statewide predicted counts to potential hospital burden across the state. We demonstrate the overall methodology with publicly available data. A Python implementation of the methodology is also made publicly available. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

SARS-CoV-2 Antibody Responses to the Ancestral SARS-CoV-2 Strain and Omicron BA.1 and BA.4/BA.5 Variants in Nursing Home Residents After Receipt of Bivalent COVID-19 Vaccine - Ohio and Rhode Island, September-November 2022.

Introduction of monovalent COVID-19 mRNA vaccines in late 2020 helped to mitigate disproportionate COVID-19-related morbidity and mortality in U.S. nursing homes (1); however, reduced effectiveness of monovalent vaccines during the period of Omicron variant predominance led to recommendations for booster doses with bivalent COVID-19 mRNA vaccines that include an Omicron BA.4/BA.5 spike protein component to broaden immune response and improve vaccine effectiveness against circulating Omicron variants (2). Recent studies suggest that bivalent booster doses provide substantial additional protection against SARS-CoV-2 infection and severe COVID-19-associated disease among immunocompetent adults who previously received only monovalent vaccines (3).* The immunologic response after receipt of bivalent boosters among nursing home residents, who often mount poor immunologic responses to vaccines, remains unknown. Serial testing of anti-spike protein antibody binding and neutralizing antibody titers in serum collected from 233 long-stay nursing home residents from the time of their primary vaccination series and including any subsequent booster doses, including the bivalent vaccine, was performed. The bivalent COVID-19 mRNA vaccine substantially increased anti-spike and neutralizing antibody titers against Omicron sublineages, including BA.1 and BA.4/BA.5, irrespective of previous SARS-CoV-2 infection or previous receipt of 1 or 2 booster doses. These data, in combination with evidence of low uptake of bivalent booster vaccination among residents and staff members in nursing homes (4), support the recommendation that nursing home residents and staff members receive a bivalent COVID-19 booster dose to reduce associated morbidity and mortality (2).

Likelihood-Free Dynamical Survival Analysis applied to the COVID-19 epidemic in Ohio.

The Dynamical Survival Analysis (DSA) is a framework for modeling epidemics based on mean field dynamics applied to individual (agent) level history of infection and recovery. Recently, the Dynamical Survival Analysis (DSA) method has been shown to be an effective tool in analyzing complex non-Markovian epidemic processes that are otherwise difficult to handle using standard methods. One of the advantages of Dynamical Survival Analysis (DSA) is its representation of typical epidemic data in a simple although not explicit form that involves solutions of certain differential equations. In this work we describe how a complex non-Markovian Dynamical Survival Analysis (DSA) model may be applied to a specific data set with the help of appropriate numerical and statistical schemes. The ideas are illustrated with a data example of the COVID-19 epidemic in Ohio.

Amid Ohio Measles Outbreak, New Global Report Warns of Decreased Vaccination During COVID-19 Pandemic.

This Medical News article discusses an annual report on measles from the World Health Organization and the US Centers for Disease Control and Prevention.

Ironic effects of political ideology and increased risk-taking in Ohio drivers during COVID-19 shutdown.

In March 2020, Ohio, along with many other states, enacted a stay-at-home order (i.e., "shutdown") to limit the spread of COVID-19. As a result of lower traffic, crashes should also have declined. We investigated whether crash rates declined in Ohio during the stay-at-home order and explore possible predictors for the decrease, such as reduced travel in compliance with the order, along with speeding, alcohol, and drug use. In addition, we examined whether support for President Trump would relate to greater travel and greater crashes (particularly during the stay-at-home order, when greater travel indicated lower compliance). The overall rate of crashes fell as people stayed home, mainly due to a decline in minor crashes. In contrast, the rate of serious crashes did not fall. Instead, percentage of alcohol-related crashes increased during the stay-at-home order, and the reduction in travel was associated with greater speeding-related crashes. Because alcohol and speeding tend to increase crash severity, these two factors may explain why severe crash rates were not reduced by lower traffic. Instead, it appears that those drivers remaining on the roads during the shutdown may have been more prone to risky behaviors, evidenced by a greater percentage of alcohol-related crashes across the state during the shutdown and greater speed-related crashes in counties with less traffic. In addition, county-level support for President Trump indirectly predicted greater rates of crashes (of all types) via increased travel (i.e., lower compliance with the shutdown), even while controlling for county-level income, rurality, and Appalachian region. Importantly, this mediated effect was stronger during the weeks of the shutdown, when greater travel indicated lower compliance. Thus, lower compliance with the stay-at-home order and increased risky driving behaviors by remaining drivers may explain why lower traffic did not lead to lower serious crashes.

Stress and Depression in Ohio Social Workers during the COVID-19 Pandemic: The Buffering Role of Social Connectedness.

Although social workers have an elevated risk of infection with COVID-19, no previous studies have investigated the virus's impact on practitioners. Using survey data (N = 441), this study identified associations between stress, depression, and COVID-related factors and explored the role of social connectedness as a moderator for mental health among Ohio social workers. The results of the study showed that among social workers with a positive COVID-19 diagnosis, 70 percent experienced moderate/high levels of stress, and 37 percent met the criteria for clinical depressive symptoms. Results from the multiple regression analyses showed that perceived stress was positively associated with a positive COVID-19 diagnosis for social workers, and depression was positively associated with working with a client with a positive COVID-19 diagnosis. An interaction effect was also identified between social connectedness and social workers' mental health. These findings suggest that the provision of individual or organizational interventions that emphasize social connectedness can help to protect social workers' mental health.

Child welfare workers satisfaction and wellbeing during the COVID-19 pandemic: Perspectives of agency staff in Ohio.

BACKGROUND: The COVID-19 pandemic has impacted the lives of children and families, created additional stressors, and increased risks for maltreatment. The pandemic has changed the way child welfare agencies operate, requiring changes to policies and practice. Minimal research has considered the effects of the COVID-19 pandemic on child welfare workers wellbeing and job satisfaction. OBJECTIVE: This mixed-methods research study seeks to understand CPS staff satisfaction, variables impacting satisfaction, and challenges that increased since the pandemic began for child welfare workers in Ohio. PARTICIPANTS AND SETTING: A sample of staff members (n = 267) from 50 CPS agencies across Ohio participated in the study. METHODS: This mixed-methods study used logistic regression, chi square analyses, and thematic analysis to analyze the data from a survey sent to child welfare agencies in Ohio. RESULTS: Caring for minor children, primary role at work, and years in child welfare were significantly associated with job satisfaction. Those working in foster care/placement, adoption/permanency, family support/visitation, kinship were 7.57 times more likely than those doing intake/investigation work to be satisfied with their job (p = .007). Thematic analysis of staff issues that increased during the pandemic resulted in six themes: Stress and Anxiety, Feeling Overwhelmed, Burnout, All, Motivation, and Isolation and Disconnection. CONCLUSIONS: The COVID-19 pandemic has created additional stressors for child welfare staff. Practice implications are discussed to help increase job satisfaction, staff wellbeing, and mitigate turnover.

Changes in Sexual Behavior Over the COVID-19 Pandemic Among a Community-Based Cohort of Men Who Have Sex With Men in Columbus, Ohio.

BACKGROUND: The purpose was to assess COVID-19 beliefs and attitudes and examine COVID-19-related changes in sexual behavior of men who have sex with men during 3 time periods: April-July 2020 (T1), August-December 2020 (T2), January-May 2021 (T3). METHODS: Data were analyzed from 157 men who have sex with men in Ohio recruited to participate in a longitudinal multisite network study of syphilis epidemiology in 3 US cities: Columbus, Ohio; Baltimore, Maryland; and Chicago, Illinois. In April 2020, a COVID-19 module was appended to existing baseline and follow-up surveys to assess beliefs, attitudes, and changes in sexual behavior. Sample characteristics were summarized. Correlations between demographic variables (age, racial identity) and COVID-19 outcomes were examined. RESULTS: In response to COVID-19 social distancing restrictions and self-reported anxiety, some men limited sexual activity at T1, but the majority (n = 105 [67%]) continued to engage in sex. The number of men engaging in sex increased over time (T2: n = 124 [79%]; T3: n = 121 [77%]). At T1, men not in a relationship more frequently reported having less sex compared with prepandemic (n = 39 [57%]). By T3, men in a relationship more frequently reported less sex (n = 32 [54%]). Increased anxiety about sex and condom use was positively correlated with identifying as a man of color (P < 0.001). Most of the sample reported either starting or increasing online sexual activity during each time period. CONCLUSIONS: Future efforts to target sexual health during a pandemic or other health emergencies should prioritize men of color and address the unique perspective of both single and partnered men.

Addressing Health Equity Goals for COVID-19 Vaccination Using Integrated Data and Mapping Tools: A Collaboration Between Academia, Public Health, and Health Care Systems in Columbus and Franklin County, Ohio.

CONTEXT: Data sharing between local health departments and health care systems is challenging during public health crises. In early 2021, the supply of COVID-19 vaccine was limited, vaccine appointments were difficult to schedule, and state health departments were using a phased approach to determine who was eligible to get the vaccine. PROGRAM: Multiple local health departments and health care systems with the capacity for mobile and pop-up vaccine clinics came together in Columbus and Franklin County, Ohio, with a common objective to coordinate where, when, and how to set up mobile/pop-up COVID-19 vaccine clinics. To support this objective, the Equity Mapping Tool, which is a set of integrated tools, workflows, and processes, was developed, implemented, and deployed in partnership with an academic institution. IMPLEMENTATION: The Equity Mapping Tool was designed after a rapid community engagement phase. Our analytical approaches were informed by community engagement activities, and we translated the Equity Mapping Tool for stakeholders, who typically do not share timely and granular data, to build capacity for data-enabled decision making. DISCUSSION: We discuss our observations related to the sustainability of the Equity Mapping Tool, lessons learned for public health scientists/practitioners, and future directions for extending the Equity Mapping Tool to other jurisdictions and public health crises.

Maintaining School Foodservice Operations in Ohio during COVID-19: "This [Was] Not the Time to Sit Back and Watch".

The COVID-19-related lockdowns led to school closures across the United States, cutting off critical resources for nutritious food. Foodservice employees emerged as frontline workers; understanding their experiences is critical to generate innovations for program operations and viability. The purpose of this cross-sectional study was to characterize COVID-19-related foodservice adaptations for summer and school year meal provision. Public school district foodservice administrators across Ohio were surveyed in December 2020. Questions related to meal provision before, during, and after COVID-19-related school closures. Results indicate the majority of districts continued providing meals upon their closure in Spring 2020 (n = 182, 87.1%); fewer did so in Summer (n = 88, 42.1%) and Fall (n = 32, 15.3%). In Spring and Summer, most districts that offered meals functioned as 'open sites' (67.0% and 87.5%, respectively), not limiting food receipt to district-affiliated students. Most districts employed a pick-up system for food distribution (76-84% across seasons), though some used a combination of approaches or changed their approach within-season. Qualitatively, districts reported both "successes" (e.g., supporting students) and "challenges" (e.g., supply chain). Despite being ill-prepared, districts responded quickly and flexibly to demands of the pandemic. This analysis provides insight for future practice (e.g., establishing community partnerships) and policy (e.g., bolstering local food systems).