397. Impact of School Opening Model on Cases of SARS-CoV-2 in Surrounding Communities: A Nationwide, Retrospective Cohort Study

Abstract Background Early in the COVID-19 pandemic, elementary and secondary schools were closed. There was variation in school opening mode (traditional, hybrid, remote) in fall 2020.The aim of this national, retrospective cohort study is to evaluate the impact of in-person learning on community incidence of SARS-CoV-2 and COVID-19-related deaths. Methods Data were extracted from several data sources. School opening mode was collected from the Burbio school tracker, which tracks school openings in a sample of school districts across the US. Incidence of SARS-CoV-2 and COVID-19 related deaths were obtained from the CDC. Data on community-level SARS-CoV-2 mitigation measures were obtained from the Oxford University COVID-19 Government Response Tracker. The effect of school mode on SARS-CoV-2 cases and deaths/100,000 during the 12-weeks following the start of school was estimated using a log-linear model with state, week, and state-week fixed effects. Models were stratified by 9 US Census divisions and adjusted for variables determined a priori to be potentially associated with the outcome. Results 519 US counties were included (Figure 1); mean cases of COVID-19 were increasing across all regions during the weeks following the start of school, regardless of school mode. Adjusted absolute differences in COVID-19 cases in counties with hybrid and traditional school opening modes relative to fully remote learning models are presented in Figure 2. In the Northeast and Midwest regions of the country, COVID-19 case rates were not statistically different between different school modes. However, in the South and West regions, there was a statistically significant increase in cases per week among counties that opened in an in-person relative to remote learning model, ranging from 17.1 (95% CI: 0.3-33.8) to 24.4 (95% CI: 7.3-41.5) in the South and from 19.0 (95% CI: 8.8-29.3) to 109.2 (95% CI: 50.4-168.0) in the West. There was no impact of school opening mode on COVID-19-related deaths. Figure 1. Map with distribution of counties and school opening mode across the United States Figure 2. Impact of school opening mode on subsequent cases of SARS-CoV-2, stratified by region. Conclusion Impact of school mode on community case-rates of SARS-CoV-2 varied across the US. In some areas of the country, traditional school mode was associated with increases in case rates relative to virtual while there were no differences in other regions. Disclosures All Authors: No reported disclosures

. Seroprevalence by antibody positivity profile Table 2. Unweighted and weighted seroprevalence by sociodemographic characteristics Conclusion. The measured SARS-CoV-2 seroprevalence in Holyoke was only 13.9% during the second surge of SARS-CoV-2 in this region, far from accepted thresholds for "herd immunity" and highlighting the need for expanding vaccination. Individuals identifying as Hispanic were at high risk of prior infection. Subsequent community-level serosurveys are necessary to guide local responses to the SARS-CoV-2 pandemic.
Disclosures. All Authors: No reported disclosures Background. Early in the COVID-19 pandemic, elementary and secondary schools were closed. There was variation in school opening mode (traditional, hybrid, remote) in fall 2020.The aim of this national, retrospective cohort study is to evaluate the impact of in-person learning on community incidence of SARS-CoV-2 and COVID-19-related deaths.

Impact of School Opening Model on Cases of SARS-CoV-2 in
Methods. Data were extracted from several data sources. School opening mode was collected from the Burbio school tracker, which tracks school openings in a sample of school districts across the US. Incidence of SARS-CoV-2 and COVID-19 related deaths were obtained from the CDC. Data on community-level SARS-CoV-2 mitigation measures were obtained from the Oxford University COVID-19 Government Response Tracker. The effect of school mode on SARS-CoV-2 cases and deaths/100,000 during the 12-weeks following the start of school was estimated using a log-linear model with state, week, and state-week fixed effects. Models were stratified by 9 US Census divisions and adjusted for variables determined a priori to be potentially associated with the outcome.
Results. 519 US counties were included ( Figure 1); mean cases of COVID-19 were increasing across all regions during the weeks following the start of school, regardless of school mode. Adjusted absolute differences in COVID-19 cases in counties with hybrid and traditional school opening modes relative to fully remote learning models are presented in Figure 2. In the Northeast and Midwest regions of the country, COVID-19 case rates were not statistically different between different school modes. However, in the South and West regions, there was a statistically significant increase in cases per week among counties that opened in an in-person relative to remote learning model, ranging from 17.1 (95% CI: 0.3-33.8) to 24.4 (95% CI: 7.3-41.5) in the South and from 19.0 (95% CI: 8.8-29.3) to 109.2 (95% CI: 50.4-168.0) in the West. There was no impact of school opening mode on COVID-19-related deaths. Conclusion. Impact of school mode on community case-rates of SARS-CoV-2 varied across the US. In some areas of the country, traditional school mode was associated with increases in case rates relative to virtual while there were no differences in other regions.
Disclosures. Background. The SARS-CoV-2 pandemic has revealed socioeconomic and healthcare inequities in the US. With approximately 20% of the population living in rural areas, there are limitations to healthcare access due to economic constraints, geographical distances, and provider shortages. There is limited data evaluating outcomes associated with SARS-CoV-2 positive patients treated at rural vs. urban hospitals. The aim of the study was to evaluate characteristics and outcomes of SARS-CoV-2 positive patients treated at rural vs. urban hospitals in the US.
Methods. This was a multicenter, retrospective cohort analysis of adult (≥ 18 years) hospitalized patients from 241 US acute care facilities with >1 day inpatient admission with a discharge or death between 3/6/20-5/15/21 (BD Insights Research Database [Becton, Dickinson & Company, Franklin Lakes, NJ]), which includes both small and large hospitals in rural and urban areas. SARS-CoV-2 infection was identified by a positive PCR or antigen during or < 7 days prior to hospital admission. Descriptive statistics were completed. P value of ≤0.05 was considered statistically significant.
Results. Overall,42 (17.4%) and 199 (82.6%) of hospitals were classified as rural and urban, respectively. A total of 304,073 patients were admitted to a rural hospital with 12,644 (4.2%) SARS-CoV-2 positive. In comparison, a total of 2,844,100 patients were treated at an urban hospital with 132,678 (4.7%) SARS-CoV-2 positive. Patients admitted to rural hospitals were older compared to those treated at an urban hospital (65.2 ± 17.3 vs. 61.5 ± 18.7, P=0.001) ( Table 1). Patients treated at an urban facility had significantly higher rates of ICU admission, severe sepsis, and mechanical ventilation. ICU length of stay was significantly longer for patients admitted to an urban hospital compared to a rural hospital (8.1 ± 9.9 vs. 6.1 ±7.2 days, P=0.001) ( Table 2). No difference in mortality was observed.

Conclusion.
In this large multicenter evaluation of hospitalized patients positive for SARS-CoV-2, there were significant differences in patient characteristics. There was no observed difference in mortality. These findings are important in evaluating the pandemic's impact on patients in rural and urban healthcare settings.
Disclosures Background. Laboratory identification (Lab-ID) of late-onset SARS-CoV-2 positive tests during a hospital stay is a potential public health surveillance approach for hospital-acquired COVID-19. However, prolonged RNA fragment shedding and intermittent detection of SARS-CoV-2 virus via PCR testing among infected patients may hamper interpretation of laboratory-identified events. We aimed to describe the epidemiology of late-onset SARS-CoV-2 laboratory events using clinical criteria, to evaluate the feasibility of a Lab-ID approach to detection of nosocomial SARS-COV-2 infection.