Medium-term Air Quality Benchmarking for Ecosystem Monitoring and Sustainability Planning: Case Study Dallas County (U.S.A.) 2015 to 2020

Medium-term air quality assessment, benchmarking it to recent past data can usefully complement short-term air quality index data for monitoring purposes. By using daily and monthly averaged data, medium-term air quality benchmarking provides a distinctive perspective with which to monitor air quality for sustainability planning and ecosystem perspectives. By normalizing the data for individual air pollutants to a standard scale they can be more easily integrated to generate a daily combined local area benchmark (CLAB). The objectives of the study are to demonstrate that medium-term air quality benchmarking can be tailored to reflect local conditions by selecting the most relevant pollutants to incorporate in the CLAB indicator. Such a benchmark can provide an overall air quality assessment for areas of interest. A case study is presented for Dallas County (U.S.A.) applying the proposed method by benchmarking 2020 data for air pollutants to their trends established for 2015 to 2019. Six air pollutants considered are: ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, benzene and particulate matter less than 2.5 micrometres. These pollutants are assessed individually and in terms of CLAB, and their 2020 variations for Dallas County compared to daily trends established for years 2015 to 2019. Reductions in benzene and carbon monoxide during much of 2020 are clearly discernible compared to preceding years. The CLAB indicator shows clear seasonal trends for air quality for 2015 to 2019 with high pollution in winter and spring compared to other seasons that is strongly influenced by climatic variations with some anthropogenic inputs. Conducting CLAB analysis on an ongoing basis, using a relevant nearpast time interval for benchmarking that covers several years, can reveal useful monthly, seasonal and annual trends in overall air quality. This type of medium-term, benchmarked air quality data analysis is well suited for ecosystem monitoring.

Age Differences in Preparedness for the Continuation of COVID-19: Important Roles of Social Support

This study examined the association between age and preparedness for the continuation of COVID-19. The moderation effects of three types of social support, namely, emotional, financial, and instrumental assistance were also tested. Using a sample of 443 adults in Dallas county which has the most confirmed cases in Texas, results of multiple linear regressions showed that compared to those aged between 18 and 64, older adults aged 65 and reported better preparedness for the continuation of COVID-19. Receiving emotional, financial, and instrumental assistance were respectively more important for older people to get better prepared than for younger adults, which is consistent with the socioemotional selectivity theory. Our findings directed attention to the strengths and resilience of older adults during COVID-19 from a life course perspective and highlighted the importance of social support and social relationship in their post-disaster recovery and ongoing preparedness.

190. Epidemiology of COVID-19 Breakthrough Infections in Dallas County, Texas, 2021

Background From March 2020 through May 2021, Dallas County reported a total of 304,056 cases of COVID-19, including 4,073 deaths. During the month of December 2020, a post-holiday surge of cases led to peak daily average case rates of over 50 cases per 100,000. COVID-19 cases and deaths have since declined substantially following the rollout of COVID-19 vaccine delivery. As of June 8, 2021, about 1,831,588 Dallas County residents have received at least one COVID-19 vaccine dose and 910,067 are fully vaccinated. Recent county integration of immunization and case databases enabled identification and analysis of COVID-19 breakthrough infections. Methods A COVID-19 breakthrough infection was defined as a positive test (PCR or antigen) collected from an individual ≥ 14 days after receiving the full series of an FDA-authorized COVID-19 vaccine. Nationally, 10,262 vaccine breakthrough infections had been reported from 46 US states and territories, through April 2021. Vaccine breakthrough cases were reviewed and medical records abstracted to collect demographic information, clinical characteristics, and medical conditions. Data analysis was performed using R, version 4.0.2 (2020). Results Of the 700 vaccine breakthrough cases reported in Dallas County residents as of June 8, 2021, 304 (43%) were male and 396 (57%) female, with an average age of 53 years. The majority of the vaccine breakthrough cases were White (42%); 25% were Hispanic/Latino; and 20% were Black. Almost all breakthrough cases were confirmed with PCR testing, with 451 (64%) cases receiving the Pfizer vaccine. Of breakthrough cases, 49% were symptomatic; 52% (358) had underlying conditions including: tobacco use, obesity, or immunocompromised state; 68 (10%) were hospitalized; and 11 (1.6%) died. Whole genome sequencing was performed on 51 cases, with 14 (27.5%) variants identified, including: eight B.1.1.7, two B.1.429 and one P.1 variants. Conclusion Despite the high levels of vaccine efficacy documented in US vaccine trials, COVID-19 breakthrough infections, though currently uncommon, do occur and are important to investigate. Ongoing close public health surveillance of variants is needed to discern changes in patterns of vaccine efficacy and characteristics of populations at greatest risk of severe disease from COVID-19. Disclosures All Authors: No reported disclosures

Genetic and Metabolic Determinants of Plasma Levels of ANGPTL8

Context ANGPTL8 (A8) plays a key role in determining the tissue fate of circulating triglycerides (TGs). Plasma A8 levels are associated with several parameters of glucose and TG metabolism, but the causality of these relationships and the contribution of genetic variants to differences in A8 levels have not been explored. Objective To characterize the frequency distribution of plasma A8 levels in a diverse population using a newly-developed ELISA and to identify genetic factors contributing to differences in plasma A8 levels. Design and Setting Population-based sample of Dallas County. Participants Individuals in the Dallas Heart Study (DHS-1, n=3,538; DHS-2, n=3,283), including 2,131 individuals with repeated measurements 7-9 years apart (age 18-85 years; >55% female; 52% Black; 29% White; 17% Hispanic; and 2% other). Main Outcome Measure(s) Associations of A8 levels with body-mass index (BMI), plasma levels of glucose, insulin, lipids, hepatic TG and DNA variants identified by exome-wide sequencing. Results A8 levels varied over a 150-fold range (2.1 - 318 ng/mL; median, 13.3 ng/mL) and differed between racial/ethnic groups (Blacks > Hispanics > Whites). A8 levels correlated with BMI, fasting glucose, insulin and TG levels. A variant in A8, R59W, accounted for 17% of the inter-individual variation in A8 levels but was not associated with the metabolic parameters correlated with plasma A8 concentrations. Conclusions A8 levels were strongly associated with indices of glucose and TG metabolism, but the lack of association of genetic variants at the A8 locus that impact A8 levels with these parameters indicates that differences in A8 levels are not causally related to the associated metabolic phenotypes.

Reducing medical oncology infusion no-show rate by improving patient and intra-clinic communication.

47 Background: Parkland Health and Hospital System (PHHS) is the safety-net health system for Dallas County. In a resource-limited health care system, no-shows create waste and delay care. We sought to decrease the no-show rate (NSR) for patients scheduled for infusions, transfusions, and injections in the PHHS medical oncology infusion center by 33% in a 4-month period. Methods: A multidisciplinary team reviewed the NSR from January 2020 to May 2020. The reasons for missed appointments were investigated via chart review to better develop an intervention for meaningful change. A telephone follow-up protocol by the infusion nurses with standardized documentation and communication with the clinic and scheduling teams (intra-clinic communication) was implemented for each missed infusion appointment starting in February 2020. Results: The infusion center had a 16.4% NSR in January 2020. Of the 306 missed appointments, there was no documented reason for 44% (159). 19% (70) were related to change in plan-of-care; 19% (67) were in patients who had been admitted. Patient-related issues (transportation, illness, work/family obligations, etc.) were 13% of no-shows. Only 40 (11%) of the no-shows had a follow-up call. After implementation of follow-up telephone calls, the NSR was 11.2% by May 2020, a 32% decrease. 57.8% (204/1822) of patients who no-showed received a follow-up call to document reason for the missed appointment. Conclusions: We decreased the NSR in the PHHS medical oncology infusion center by 32% over a 4-month period, nearly reaching our goal, by implementing standardized post-no-show follow-up calls. Through our process, we discovered that communication, with the patient and intra-clinic, accounted for the most missed appointments rather than patient-related or other factors. Perhaps confounding our results were changes brought about by the COVID-19 pandemic, including mandatory telephone screening of patients prior to infusion appointments. Next steps include integrating pre-appointment calls into the workflow, standardizing change-in-plan communication, and cost analysis of interventions in our resource-limited setting.

1064. Hepatitis C Epidemiology at the Dallas County Jail: A Changing Demographic

Background Nearly 1 in 3 people living with HCV pass through the CJ system each year. As a result, the CJ system is a crucial location for Hepatitis C screening, education and linkage to care. We aim to 1) identify the prevalence and incidence of HCV and 2) evaluate HCV demographic trends at a large urban jail. Methods Universal opt-out HCV testing was offered in four separate testing cycles from 2015 to 2019 to any individual undergoing a routine blood draw at the Dallas County Jail (N=14490; Figure 1). HCV antibody (Ab) assay (LabCorp) was used with reflex RNA testing added on in 2017. Demographic variables were extracted from the electronic medical record for all tested, with risk factors collected from those who tested positive for HCV Ab (HCV Ab+). Multivariate logistic regression was performed. Figure 1. HCV Ab and HCV RNA positivity among people screened for HCV in the Dallas County Jail from 2015 to 2019 (N=14490). Results The prevalence of HCV Ab+ was 16.7% in the Dallas County Jail; 75.3% of those who tested HCV Ab+ were also HCV RNA+ (Figure 1). The HCV Ab+ incidence rate was 13.5 cases per 1000 person-years. People who were HCV Ab+ were more frequently (adjusted odds ratio [95% confidence interval], p-value): older (1.07 (1.06-1.07), p< 0.001), female (1.24 [1.07-1.44], p=0.004), white (2.12 [1.83-2.45], p< 0.001), and in the birth cohort 1945-65 (1.79 [1.44-2.23], p< 0.001; Table 1). In earlier birth cohorts (1940s), black men were more often HCV Ab+; in more recent birth cohorts (1990s), white and Hispanic females were more often HCV Ab+ (Figure 2). Among individuals who tested HCV Ab+, IDU was more frequently reported by white individuals, particularly women, compared to black individuals (p< 0.001; Figure 3). Table 1. Demographic predictors of Hepatitis C Antibody positivity among those undergoing routine blood draws from 2015-19 at the Dallas County Jail (AIC 7041; BIC 7048; df 10; p<0.001). Figure 2. Trends of Hepatitis C Antibody prevalence and demographic prevalence ratios by birth year (prevalence ratio= proportion with disease/proportion with exposure) among people at the Dallas County Jail screened from 2017-2019 (N=10183). Demographic prevalence ratios were categorized by race (White, Hispanic, Black) and gender (Male, Female) into six categories. Gray bars represent the overall prevalence of HCV Ab+ by birth year. Figure 3. The racial demographics of injection drug use by gender among those who tested HCV Ab positive at the Dallas County Jail in 2017-2018 (n=672; total population p<0.001; male p=0.004; female p=0.008). Conclusion The high prevalence and incidence of HCV at the Dallas County Jail argues for routine, universal testing and linkage to treatment. Additionally, demographic trends mirror the IDU epidemic and have valuable implications for risk reduction and treatment interventions. Disclosures Ank E. Nijhawan, MD, MPH, Gilead (Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support)

1615. Influenza Outbreaks in Long-Term Care Facilities, 2017–2018 Influenza Season, Dallas, Texas

Background High rates of influenza-related hospitalizations and deaths occurred in the United States during the 2017–2018 influenza season. A record number of influenza outbreaks were reported in long-term care facilities (LTCF) in Dallas County. Public health surveillance of influenza-related intensive care unit (ICU) admissions and deaths in acute care hospitals improved early identification of outbreaks in LTCFs. Methods A confirmed LTCF influenza outbreak was defined as at least 1 lab-confirmed influenza case plus at least 1 case of influenza-like illness among residents or staff within 72 hours. Outbreaks were self-reported by facilities or identified by the health department during investigations of ICU hospitalizations and deaths. CDC guidance for influenza outbreak management was provided and daily active surveillance was continued for at least 1 week after the last case was identified. Data collected included: numbers of ill residents and staff, vaccination rates, dates of illness and chemoprophylaxis initiation, hospitalizations and deaths. Fisher exact tests and Chi-square were performed using SAS 9.4. Results During this influenza season, 32 confirmed influenza outbreaks were identified in Dallas County LTCFs: 17 in skilled nursing facilities (SNF), 13 in assisted-living facilities (ALF) and 2 in hybrid SNF/ALF. The average attack rate in residents was 9.8% (range: 1–35%). Influenza hospitalization rates were higher in ALF compared with SNF outbreaks (OR: 2.2). Influenza-associated mortality rates were higher in ALF compared with SNF (OR: 3.1). Of the 32 outbreaks, 20 (63%) were self-reported by facilities to public health and 12 (38%) were identified through health department review of influenza-associated ICU hospitalizations. Facilities where outbreak cases were identified through public health surveillance of ICU admissions had significantly lower overall attack rates (5.9% vs. 12.1%, P = 0.01) and shorter time to initiation of facility-wide chemoprophylaxis (0.4 vs. 2.4 days, P = 0.05). Conclusion Active surveillance of influenza-associated ICU admissions in acute-care hospitals facilitated the early identification of influenza outbreaks in LTCFs, which was associated with lower overall attack rates and shorter time to initiation of facility-wide chemoprophylaxis. Disclosures All authors: No reported disclosures.