Socially Vulnerable Patients with Inflammatory Bowel Disease Are at Increased Risk for Vaccine Preventable Illness

INTRODUCTION: Inflammatory bowel disease (IBD) affects patients across diverse ethnic, minority, cultural, and socioeconomic backgrounds;however, the relationship between these social determinants of health (SDOH) and IBD outcomes is not well-studied. SDOH have a known impact on disparities in vaccination, but these effects may be more salient in the IBD population where patients are at greater risk for vaccine-preventable illness from immunosuppressive therapies. The social vulnerability index (SVI) is a tool provided by Centers for Disease Control that can identify individuals at risk for health care disparities by estimating neighborhood-level social need on a 0-1 scale (higher scores indicating greater social vulnerability). Utilizing census tract-level SVI data, we aimed to identify the relationship between the SDOH and vaccination rates in patients with IBD. METHOD(S): We used a retrospective cohort design of patients seen at a single IBD center between 01/01/2015 and 08/31/2022. Using the current address listed in the electronic medical record, we geocoded patients to individual census tracts and linked them to corresponding SVI and subscales (Figure 1). Controlling a priori for age, gender, race, ethnicity, marital status, English proficiency, electoral district, and religious affiliation, we used multivariable linear regression to examine the relationship between SVI and vaccination against influenza, Covid-19, pneumococcal pneumonia (conjugate and polysaccharide), and Zoster. RESULT(S): 15,245 patients with IBD were included and the percent of unvaccinated individuals was high across all vaccine types: flu (42.8%), Covid-19 (50.9%), pneumonia (62.4%), and Zoster (89.6%). High total levels of social vulnerability were associated with lower vaccination rates across all vaccine groups: flu (B -1.3, 95% CI -1.5, -1.2, p<0.001), Covid-19 (B -0.99, 95% CI -1.1, -0.88), p<0.001), pneumonia (B -0.21, 95% CI -0.27, -0.14, p<0.001), Zoster (B -0.23, 95% CI -0.27, -0.19, p<0.001). On SVI sub-scales, high scores in Socioeconomic Status, Household Composition, and Housing/Transportation were important predictors of vaccine uptake while Minority Status/Language was non-significant (Table 1). CONCLUSION(S): Living in a socially vulnerable community is associated with lower vaccination rates across all vaccine types. Higher scores on neighborhood level Socioeconomic Status, Household Composition, and Housing/Transportation were also associated with lower vaccine uptake. Many factors may affect why socially vulnerable patients are under-vaccinated, including a lack of patient and provider knowledge of routine vaccines, lack of access to care, and poor trust in vaccines and healthcare system. Further research is needed improve IBD health maintenance in gastroenterology clinics and ensure equitable distribution of vaccines to socially vulnerable patients. [Formula presented] [Formula presented]Copyright © 2023

Racial and Socioeconomic Disparities in Colorectal Cancer Screening During the COVID-19 Pandemic

INTRODUCTION: Colorectal cancer (CRC) screening has reduced CRC mortality. The COVID-19 pandemic led to a reduction in screening volume. We sought to evaluate whether specific populations or socioeconomic groups were disproportionately impacted by the reduced access to care. METHOD(S): Patients eligible for CRC screening in a large integrated healthcare system, who had a primary care visit between January 2016 and April 2022, were evaluated. Trends in CRC screening were assessed by age, race, gender, insurance type, and geographic delineation by state and classification of urban or rural areas. Multilevel logistic regression models evaluated region-level cluster effects of CRC screening by patient demographics, insurance, and social vulnerability index (SVI), including socioeconomic status, household composition and disability, minority status and language, and housing and transportation domains. The interaction between trend in CRC screening and race was also investigated. RESULT(S): A total of 654,386 patients were screeneligible between January 2016 and April 2022. The cohort screening rate peaked at 70% in 2019 with a subsequent downtrend to a nadir of 63.6% through the first part of 2022. Whereas the Native American population is consistently the least screened population, the Asian population demonstrated the most significant decrease in screening during and after the COVID-19 pandemic, falling from a peak at 69.1% in 2019 to 59.3% in 2021;this remains low in 2022 at 58.9%. Further, older patients, males, location in an urban area, White ethnicity and use of commercial insurance were significantly associated with higher odds of CRC screening (p< 0.001). Conversely, patients living in more vulnerable census tracts based on the SVI socioeconomic status and housing/transportation domain had lower odds of having CRC screening (p< 0.001). Finally, there was a significant interaction between trend in CRC screening and race. The CRC screening rate increased between 2016 and 2019 and then decreased for all races, but Asian patients had the most significant decrease in CRC screening between 2020 and 2021 (68.3% versus 60.2%, p< 0.001;Figure 1). CONCLUSION(S): This is the first study to demonstrate that the COVID-19 pandemic led to a population-wide decrease in CRC screening volume that disproportionately affected the Asian population and those of lower socioeconomic status. We are currently evaluating whether this impacted stage migration and mortality. (Figure Presented).

Socially Vulnerable Patients with Inflammatory Bowel Disease Are at Increased Risk for Vaccine Preventable Illness

INTRODUCTION: Inflammatory bowel disease (IBD) affects patients across diverse ethnic, minority, cultural, and socioeconomic backgrounds;however, the relationship between these social determinants of health (SDOH) and IBD outcomes is not well-studied. SDOH have a known impact on disparities in vaccination, but these effects may be more salient in the IBD population where patients are at greater risk for vaccine-preventable illness from immunosuppressive therapies. The social vulnerability index (SVI) is a tool provided by Centers for Disease Control that can identify individuals at risk for health care disparities by estimating neighborhood-level social need on a 0-1 scale (higher scores indicating greater social vulnerability). Utilizing census tract-level SVI data, we aimed to identify the relationship between the SDOH and vaccination rates in patients with IBD. METHOD(S): We used a retrospective cohort design of patients seen at a single IBD center between 01/01/2015 and 08/31/2022. Using the current address listed in the electronic medical record, we geocoded patients to individual census tracts and linked them to corresponding SVI and subscales (Figure 1). Controlling a priori for age, gender, race, ethnicity, marital status, English proficiency, electoral district, and religious affiliation, we used multivariable linear regression to examine the relationship between SVI and vaccination against influenza, Covid-19, pneumococcal pneumonia (conjugate and polysaccharide), and Zoster. RESULT(S): 15,245 patients with IBD were included and the percent of unvaccinated individuals was high across all vaccine types: flu (42.8%), Covid-19 (50.9%), pneumonia (62.4%), and Zoster (89.6%). High total levels of social vulnerability were associated with lower vaccination rates across all vaccine groups: flu (B -1.3, 95% CI -1.5, -1.2, p<0.001), Covid-19 (B -0.99, 95% CI -1.1, -0.88), p<0.001), pneumonia (B -0.21, 95% CI -0.27, -0.14, p<0.001), Zoster (B -0.23, 95% CI -0.27, -0.19, p<0.001). On SVI subscales, high scores in Socioeconomic Status, Household Composition, and Housing/ Transportation were important predictors of vaccine uptake while Minority Status/ Language was non-significant (Table 1). CONCLUSION(S): Living in a socially vulnerable community is associated with lower vaccination rates across all vaccine types. Higher scores on neighborhood level Socioeconomic Status, Household Composition, and Housing/Transportation were also associated with lower vaccine uptake. Many factors may affect why socially vulnerable patients are under-vaccinated, including a lack of patient and provider knowledge of routine vaccines, lack of access to care, and poor trust in vaccines and healthcare system. Further research is needed improve IBD health maintenance in gastroenterology clinics and ensure equitable distribution of vaccines to socially vulnerable patients. (Figure Presented).

Pandemic effects on social capital and loneliness in residents and non-residents of Chinese immigrant enclaves in Philadelphia

The COVID-19 pandemic profoundly affected cancer prevention behaviors and cancer care. Social capital is also thought to affect cancer prevention and care, with some observed improvements in well being and survival among cancer patients. Residents of immigrant enclaves are thought to have more social capital than non-residents, potentially buffering against negative effects of the pandemic. We compared residents and non-residents of Chinese immigrant enclaves in Philadelphia with respect to their social capital and loneliness and change in these factors from before to during the pandemic. Participants were 520 Chinese immigrant men and women aged 3565 y. Baseline interviews conducted 9/18-01/20 included questions on residence and demographics, structural and cognitive social capital (short version of the Adapted Social Capital Assessment Tool (SASCAT)), and a validated 3-item loneliness scale. The SASCAT includes questions on membership in neighborhood groups, receiving support from specific individuals (e.g., family, neighbors, friends), and cognitive social capital representing perceived levels of trust and belonging in the neighborhood. In May-July 2020, 419 participants completed a follow-up interview that included the SASCAT and loneliness scales. Participants were categorized as residing in a traditional, emerging, or non-enclave neighborhood depending on the ethnic density of their census tract and adjacent tracts. At baseline there were no significant differences in social capital or loneliness across neighborhood types. During the pandemic, participants regardless of neighborhood type reported declines in group membership (18% baseline vs. 11% pandemic) and loneliness (25% vs. 12%), and increases in cognitive social capital (85% vs. 99%) and receiving support from individuals (35% vs. 69%) (all p<0.001). However, extent of change differed by neighborhood, resulting in significantly less loneliness among residents of traditional enclaves (5%) than in emerging (14%) and non-enclave (16%) residents (p=0.02) during the pandemic. Multivariate analyses using generalized estimating equation models indicated that residents of traditional enclaves experienced a larger decrease in loneliness than other participants (interaction p=0.009), and that residents of traditional and emerging enclaves experienced a larger increase in cognitive social capital than residents of non-enclaves (interaction p=0.03). Our findings provide evidence that while the pandemic may have effected declines in group membership in this sample of Chinese immigrants, it was associated with increases in other forms of social capital and with a decrease in loneliness, particularly among enclave residents. These findings suggest the importance of clarifying how social capital derived from interacting within an immigrant enclave might be leveraged to counter the effects of a community stressor such as the COVID-19 pandemic, and used towards positive cancer outcomes in these communities.

The impact of socioeconomic status on telemedicine utilization during the COVID-19 pandemic among surgical clinics at an academic tertiary care center.

BACKGROUND: The COVID-19 pandemic caused many surgical providers to conduct outpatient evaluations using remote audiovisual conferencing technology (i.e., telemedicine) for the first time in 2020. We describe our year-long institutional experience with telemedicine in several general surgery clinics at an academic tertiary care center and examine the relationship between area-based socioeconomic measures and the likelihood of telemedicine participation. METHODS: We performed a retrospective review of our outpatient telemedicine utilization among four subspecialty clinics (including two acute care and two elective surgery clinics). Geocoding was used to link patient visit data to area-based socioeconomic measures and a multivariable analysis was performed to examine the relationship between socioeconomic indicators and patient participation in telemedicine. RESULTS: While total outpatient visits per month reached a nadir in April 2020 (65% decrease in patient visits when compared to January 2020), there was a sharp increase in telemedicine utilization during the same month (38% of all visits compared to 0.8% of all visits in the month prior). Higher rates of telemedicine utilization were observed in the two elective surgery clinics (61% and 54%) compared to the two acute care surgery clinics (14% and 9%). A multivariable analysis demonstrated a borderline-significant linear trend (p = 0.07) between decreasing socioeconomic status and decreasing odds of telemedicine participation among elective surgery visits. A sensitivity analysis to examine the reliability of this trend showed similar results. CONCLUSION: Telemedicine has many patient-centered benefits, and this study demonstrates that for certain elective subspecialty clinics, telemedicine may be utilized as the preferred method for surgical consultations. However, to ensure the equitable adoption and advancement of telemedicine services, healthcare providers will need to focus on mitigating the socioeconomic barriers to telemedicine participation.

Sociodemographic Determinants of Missed Telehealth Appointments in Colorectal Surgery

INTRODUCTION: The COVID-19 pandemic facilitated telehealth adoption. Multiple barriers may impact accessibility to such services. We estimated the association between sociodemographic and clinical factors, with keeping telehealth appointments. METHOD(S): Single-center retrospective cohort study comprising consecutive telehealth appointments at the Division of Colorectal Surgery (March-December 2020). Demographics, appointment type, diagnosis, and distance to the hospital were collected. Federal Financial Institutions Examination Council's (FFIEC) website was used to obtain estimated family income and poverty levels based on home location. Multivariable clustered logistic regression estimated the association between sociodemographic characteristics and keeping telehealth appointments. RESULT(S): A total of 925 telehealth appointments were analyzed, of which 84.11% were kept. Non-White patients (odds ratio [OR] 0.59, 95% CI 0.39-0.90, p = 0.015), and those with follow-up appointments (OR 0.50, 95% CI 0.31-3.07, p = 0.006) had lower odds of keeping appointments when compared with White patients, and those having postoperative appointments, respectively. Patients who had attended college had higher odds of keeping appointments (OR 1.77, 95% CI 1.02-3.07, p = 0.044) when compared with those who declined to provide their education level (Figure 1). Age, sex, diagnosis, income level, and percentage of people living under poverty within census tracts per FFIEC were not predictors of keeping telehealth appointments. CONCLUSION(S): Patients self-identifying as non-White and presenting for non-postoperative follow-up visits were more likely to miss telehealth appointments. College education was associated with keeping appointments. Future studies could characterize barriers to telehealth programs implementation to optimize access among groups at high risk of non-compliance. (Figure Presented).

UNEQUAL DISTRIBUTION: ACCESS TO SARS-COV2 TESTING SITES IN COMPARISON TO SARS-COV2 POSITIVITY RATES IN MONROE COUNTY MARCH -OCTOBER 2020

BACKGROUND: Over the course of the 20th century, Monroe County NY, has developed into a community facing significant defacto segregation: a central crescent of the city has lower economic indicators and a predominantly minority community. We set out to analyze rates of SARS-COV2 as well as the distribution of SARS-COV2 testing sites across Monroe County during the first wave of the pandemic (March 2020-Sept 2020). Our hypothesis was that while disease rates would be higher in historical disadvantaged areas, the distribution of testing resources would be less accessible. This is a potentially novel methodology to demonstrate layers of unequal access to resources. METHODS: We extracted data on the total number of SARS-COV2 cases by zip code in Monroe County, NY from March 23 - October 21, 2020 and SARS-COV2 testing sites from the Monroe County Department of Health website. Sociodemographic factors were taken from the 2015 American Community Survey. We used geospatial analysis to assess the local spatial autocorrelation of SARS-COV2 rates. We adapted a definition based on the USDA's 4th definition for food deserts to create a measure of “SARS-COV2 testing site desert.” To overcome coordination of census tract level definitions with zip code level data, we assumed an equivalency factor where we divided the total zip code population by 4000 (average census tract size). We then tested whether SARS-COV2 testing sites were accessible using this definition. RESULTS: There were statistically significant differences in local spatial autocorrelation which allowed us to separate the county into “SARS-COV2 hot zones” and “SARS-COV2 cold zones.” The hot zones had a statistically significant lower median income and a higher percentage of Black and Hispanic residents. The cold zones along the perimeter had a higher median income and higher percentage of white residents (Mann Whitney p values < 0.05). Using the definition for SARS-COV2 testing site deserts, the hot zones had less access to testing sites than the cold zones. CONCLUSIONS: SARS-COV2 case rates were differentially distributed in the first wave of the pandemic in Monroe County. There were significantly higher positivity rates in areas with predominately black residents, lower median incomes, and limited car access. These areas with higher SARSCOV2 positivity rates also had lower initial access to SARS-COV2 testing sites, creating an example of compounded inequity. Creating specific definitions surrounding healthcare access that consider transportation and can be rapidly analyzed may allow for more effective future resource allocation. An early version of this analysis allowed healthcare systems and community organizations to create pilot SARS-COV2 testing sites in areas with higher rates of disease in real time. Using geospatial data analyses provides an exciting potential way to model and impact change in equitable healthcare delivery.

Racial disparity in COVID-19 severity after adjusting for chronic illnesses and sociodemographic factors

Background. Research has reported that African American (AA) cancer patients with COVID-19 had a higher hospitalization rate than their white counterparts. Because the severity of COVID-19 is partly related to existing chronic diseases, one of the speculations is that racial differences in COVID-19 severity are attributable to AA cancer patients having a higher prevalence of chronic illnesses. Our study aimed to assess the impact of existing chronic diseases on the racial differences in hospitalization and length of hospitalization in COVID-19 cancer patients in Louisiana. Methods. We linked cancer cases diagnosed in 2015-2019 from the Louisiana Tumor Registry (LTR) with the statewide COVID-19 data to identify COVID-19 patients who had been previously diagnosed with cancer. We also identified chronic illnesses (i.e., heart disease, peripheral vascular and cerebrovascular diseases, pulmonary disease, renal disease, liver disease, diabetes, and others) from 2012-2020 hospital discharge data and LTR data. Age and census tract level poverty were at the time of COVID-19 diagnosis. Bivariate and multivariable logistic regressions were used to exam the association of race with hospitalization after adjusting for socio-demographic and chronic illnesses. The multivariable Poisson model was used to assess the racial disparity in length (in days) of hospitalization. Results. Of 6,518 COVID-19 cancer patients, there were 30.8% AA, 68.4% whites, and 0.8% other races. AA, male, older, residing in high poverty, and patients with chronic illnesses were more likely (P<0.05) to be hospitalized. The odds of hospitalization was 87.2% higher among AA patients than white patients in bivariate analysis. After adjusting for age, gender, poverty, obesity, smoking status, and chronic illnesses, the odds of hospitalization was still higher for AA than white patients (OR=1.81;95% CI: 1.55-2.09). The length of hospital stay for AA was more (P<0.05) than whites After adjusting for the same covariates. Conclusion. Sociodemographic factors and chronic illnesses are associated with the severity of COVID-19 among cancer patients. However, AA COVID-19 cancer patients have significantly higher odds of hospitalization and longer hospital stays even when controlling these factors. More research is warranted to determine underlying factors of the observed racial disparities.

COVID-19 Vaccine Uptake among US Adults According to Standard Occupational Groups.

This cross-sectional ecological study examined the relationship between neighborhood-level standard occupational groups in the USA and COVID-19 vaccine uptake using 774 census tract data, each consisting of approximately 1600 housing units. The neighborhood-level COVID-19 vaccination uptake data were retrieved from Harris County Public Health, Harris County, Texas. The standard occupational group data were from the US Census Bureau. We calculated the incidence rate ratios (IRRs) for vaccine uptake using bivariate and multivariable Poisson regression models. In the adjusted models, we found that the healthcare practitioner/technician (IRR: 1.008; 95% CI: 1.003-1.014; p = 0.001), business/management/legal (IRR: 1.011; 95% CI: 1.008-1.013; p < 0.001), computer/engineering/life/physical/social science (IRR: 1.018; 95% CI: 1.013-1.023; p < 0.001), and arts/design/entertainment/sports/media (IRR: 1.031; 95% CI: 1.018-1.044; p < 0.001) occupational groups were more likely to have received the full regimen of a COVID-19 vaccine. On the contrary, the building/installation/maintenance/repair (IRR: 0.991; 95% CI: 0.987-0.995; p < 0.001), construction/extraction/production (IRR: 0.991; 95% CI: 0.988-0.995; p < 0.001), transportation/material moving (IRR: 0.992; 95% CI: 0.987-0.997; p = 0.002), food preparation/serving related (IRR: 0.995; 95% CI: 0.990-0.999; p = 0.023), and personal care/services (IRR: 0.991; 95% CI: 0.985-0.998; p = 0.017) groups were less likely to have received the complete dose of a COVID-19 vaccine. White-collar workers were more likely to be vaccinated than blue-collar workers. We adjusted for age, sex, and race/ethnicity in the multivariable analysis. The low vaccine uptake among certain occupational groups remains a barrier to pandemic control. Engaging labor-centered stakeholders in the development of vaccination interventions may increase uptake.

COVID-19 Infection Experiences and Social Determinants of Health in North Carolina: A Qualitative Analysis

Study Objectives: Social determinants of health (SDOH) influence the health outcomes of COVID-19 patients;yet, little is known about how patients at risk of significant disease burden view this relationship. Our study sought to explore patient perceptions of the influence of SDOH on their COVID-19 infection experience and COVID-19 transmission within their communities. Methods: We conducted a qualitative study of patients in a North Carolina health care system’s registry who tested positive for COVID-19 from March 2020 through February 2021. All patients’ addresses across six counties served were geo-referenced and analyzed by Kernel Density Estimation (KDE) to identify population-dense outbreaks of COVID-19 (hotspots). Spatial autocorrelation analysis was performed to identify census area clusters of white, Black and Hispanic populations, based on the 2019 American Community Survey dataset. Patients were identified by a randomized computer-generated sampling method. After informed consent, patients participated in semi-structured phone interviews in English or Spanish based on patient preference by trained bilingual researchers. Each interview was evaluated using a combination of deductive and inductive content analysis to determine prevalent themes related to COVID-19 knowledge and diagnosis, disease experience, and the impact of SDOH. Results: The 10 patients interviewed from our COVID-19 hotspots were of equal distribution by sex, and predominantly Black (70%), ages 22-70 years (IQR 45-62 years), and presented to the ED for evaluation (70%). The respondents were more frequently publicly insured (50% medicaid/medicare;vs 30% uninsured;vs 20% private). The interviews demonstrated themes surrounding the experience and impact of COVID-19. The perceived risk of contracting COVID-19 and knowledge of how to prevent infection varied greatly among our sample, and could be in part explained by SDOH such as their occupation, living conditions and mode of transportation. The experiences of COVID-19 testing, diagnosis, isolation and medical treatment were most influenced by the timing of infection in relation to the study period. For example, in the early months of the pandemic, the knowledge of isolation requirements and available support systems seemed to have negatively impacted the ability to isolate and follow public health guidance, as well as the support mechanisms provided by employers during this period. Communication of infection status once diagnosed varied greatly, with some voicing feelings of shame, and others advocating for sharing of infection experiences to change community behaviors. Suggestions for how to improve the COVID-19 response included improving communication and enforcing public health guidelines, including raising awareness for vulnerable populations on topics like expected symptoms, financial support, increasing testing, and vaccination delivery. Conclusion: Further exploration of important themes and related SDOH that influenced how the participants experienced the COVID-19 pandemic will be necessary to decrease the negative impacts of SDOH in communities that are high-risk for COVID-19 spread.

Disparities in SARS-CoV-2 Antibody Prevalence: Findings from a Citywide Serosurvey in Holyoke, Massachusetts, November 2020-January 2021

Background. Seroprevalence studies are important tools to estimate the prevalence of prior or recent SARS-CoV-2 infections. This information is critical for identifying hotspots and high-risk groups and informing public health responses to the COVID-19 pandemic. We conducted a city-level seroprevalence study in Holyoke, Massachusetts to estimate the seroprevalence of SARS-CoV-2 antibodies and risk factors for seropositivity. Methods. We invited inhabitants of 2,000 randomly sampled addresses to participate between November 5 and December 31, 2020. Participants completed questionnaires measuring sociodemographic and health characteristics, and COVID-19 exposure history, and provided dried blood spots for measurement of SARS-CoV-2 IgG and IgM antibodies. To calculate total and group seroprevalence estimates, inverse probability of response weights were constructed based on age, gender, race/ethnicity and census tract to ensure estimates represented the city's population. Results. We enrolled 280 households including 472 individuals. 328 underwent antibody testing. The citywide weighted seroprevalence of SARS-CoV-2 IgG or IgM was 13.9% (95%CI 7.8 - 21.8) compared to 9.8% based on publicly reported case counts. Seroprevalence was 16.8% (95%CI 5.7 - 28.0) among individuals identifying as Hispanic compared to 8.9% (95%CI 3.0 - 14.7) among those identifying as White. Seroprevalence was 20.7% (95%CI 2.2 - 39.2) for ages 0-19;13.8% (95%CI 5.6 - 22) for ages 20 - 44;9.6% (95%CI 0 - 20.5) for ages 45 - 59;4.8% (95%CI 0 - 10.2) for ages 60 - 84;and 42.9% (95%CI 0 - 100) for ages >85. 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 SARSCoV-2 pandemic.

High Acceptance and Rapid Implementation of COVID-19 Vaccine in a Public HIV Clinic in Northern California: An Initial Analysis of Social Determinants

Background. Safety net HIV providers face operational challenges during the COVID pandemic with services often transformed to telehealth. HIV infected persons are a priority population for SARS CoV-2 vaccination. Medical mistrust of COVID vaccines has been cited as a contributor to vaccine hesitancy. Data on efficient and successful vaccination efforts of HIV infected persons in safety net health systems is needed. In San Mateo County, Latino persons comprised 42% of all COVID cases, Whites 16%, and African Americans 2%. Methods. SARS CoV2 vaccination with BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna) or Ad26.COV2.S (Janssen) vaccine were offered beginning February 2, 2021 through May 28, 2021 in a northern California public County HIV clinic. Clinic patients were contacted by bilingual English/Spanish speaking HIV clinic staff and appointments scheduled at County affiliated vaccination sites. Clinic staff followed up by phone with patients who did not initially accept vaccine. We calculate the percentage of patients who completed vaccine series and use multivariable logistic regression analysis to estimate the odds of series completion by patient race/ethnicity, gender and age. Results. Virtually all, 95% (349/365) of HIV patients in our County HIV clinic were offered vaccine during a 17 week period. Among those, 86% (313/365) accepted and received at least one dose and 80% completed the series (292/365) at time of this analysis. Janssen vaccine was given to only 2% (7/313) patients. Series completion was highest among Latinos and Asians. Latinos had the highest odds of vaccine series completion (OR = 4.12;95% CI 1.71 - 9.93). COVID-19 Vaccine Series Completion in a California Public HIV Clinic by Race/ Ethnicity, Age and Sexual Orientation, n=364 Conclusion. HIV patients offered SARS CoV2 vaccine by County HIV clinic staff with established patient care relationships had high vaccine acceptance (80%), comparable to 68% series completion in the county overall and 56% in the health equity quartile county census tracts. Latino HIV infected persons were most likely to complete the COVID vaccine series. Ryan White funded HIV clinics are ideal hubs to coordinate HIV patient COVID vaccination efforts. Adding COVID vaccine completion to HIV clinic performance measures would likely be beneficial.

Household Transmission of Febrile Illness Measured by Smartphone-Connected Thermometers, United States, 2016-2021

Background. Understanding household transmission dynamics of infectious diseases can help develop mitigation strategies. Traditional methods of population-level disease surveillance do not capture household transmission. Data collected from smartphone-connected thermometers that can differentiate among individuals in a household can be used to study these characteristics. Using this technology, we estimated the household secondary attack rate (SAR) of febrile illness, assessed its correlation with CDC-reported influenza-like illness (ILI) and COVID-19 case incidence, and identified risk factors for secondary transmission. Methods. We conducted a retrospective cohort study among 596,096 febrile illness index cases recorded from August 1, 2016 to January 20, 2021 in households with two or more individuals in all 50 states. Fevers were measured using the Kinsa Smart Thermometer and mobile device app. Secondary cases were defined as household members who recorded a fever 1-10 days after an index case. We calculated SAR prior to and during the COVID-19 pandemic within the study period, and assessed correlation to ILI and COVID-19 case incidence using Spearman's rank correlation coefficient. Bivariate and multivariable mixed logistic regression models were used to identify risk factors for secondary transmission. Results. SAR in the pre-COVID-19 period was 5.9% (95% CI: 5.8%-6.0%) during flu season (November to April), and 3.7% (95% CI: 3.6%-3.7%) in flu off-season, and weekly SAR was significantly correlated with ILI reported from CDC (ρ=0.84, p< 0.001). Secondary transmission was 40% more likely to occur in households where the index case's initial temperature was ≥ 39.1°C. During the COVID-19 period, SAR was 3.3% (95% CI: 3.3%-3.4%), and daily SAR was significantly correlated with national daily COVID-19 incidence rates (ρ=0.86, p< 0.001). Households in census tracts with >50% essential workforce were 50% more likely to experience secondary transmission. Conclusion. Household SAR was highly correlated with ILI and COVID-19 cases. Capturing household transmission of febrile illness through routine public health surveillance may identify risk factors for infectious disease transmission, allowing for more targeted interventions.

Community predictors of COVID-19 cases and deaths in Massachusetts: Evaluating changes over time using geospatially refined data.

BACKGROUND: The COVID-19 pandemic has highlighted the need for targeted local interventions given substantial heterogeneity within cities and counties. Publicly available case data are typically aggregated to the city or county level to protect patient privacy, but more granular data are necessary to identify and act upon community-level risk factors that can change over time. METHODS: Individual COVID-19 case and mortality data from Massachusetts were geocoded to residential addresses and aggregated into two time periods: "Phase 1" (March-June 2020) and "Phase 2" (September 2020 to February 2021). Institutional cases associated with long-term care facilities, prisons, or homeless shelters were identified using address data and modeled separately. Census tract sociodemographic and occupational predictors were drawn from the 2015-2019 American Community Survey. We used mixed-effects negative binomial regression to estimate incidence rate ratios (IRRs), accounting for town-level spatial autocorrelation. RESULTS: Case incidence was elevated in census tracts with higher proportions of Black and Latinx residents, with larger associations in Phase 1 than Phase 2. Case incidence associated with proportion of essential workers was similarly elevated in both Phases. Mortality IRRs had differing patterns from case IRRs, decreasing less substantially between Phases for Black and Latinx populations and increasing between Phases for proportion of essential workers. Mortality models excluding institutional cases yielded stronger associations for age, race/ethnicity, and essential worker status. CONCLUSIONS: Geocoded home address data can allow for nuanced analyses of community disease patterns, identification of high-risk subgroups, and exclusion of institutional cases to comprehensively reflect community risk.

Turning over a new leaf: Vape shop closings, openings and transitions in six U.S. Metropolitan statistical areas.

This study characterizes vape shop closings, openings, and changes in product mix in six U.S. metropolitan statistical areas with different tobacco and marijuana policies. With concern for higher rates of marijuana use among those who vape nicotine, the presence of marijuana-related terms in store names was also assessed. A census of stores that were classified online as vape shops/stores or vaporizer stores were telephoned in April-May 2018 (n = 739) and July-September 2019 (n = 919) to verify whether vape products and other tobacco products (OTP) were sold. We computed the percent of stores that closed, opened, and started/stopped selling OTP. Multilevel models tested whether these events varied by store type and by neighborhood demographics. Within 16 months, 11.5% of 739 stores had closed and 29.8% of 919 stores at follow-up had opened. Closings were more likely among vape-only than vape + OTP stores (AOR = 2.51, 95% CI = 1.47,4.29); vape-only stores were less likely to open (AOR = 0.46, 95% CI = 0.34,0.62). Regardless of store type, the odds of a store opening increased as the proportion of non-Hispanic/Latino White residents in the census tract increased (AOR = 1.47, 95% CI = 1.18,1.85). Overall, 2.0% of stores (vape-only and vape + OTP) had marijuana-related names at baseline and 3.5% at follow-up. The observed change (1.6% to 5.8%) was greatest in Oklahoma City, where the state legalized medical marijuana between baseline and follow-up. More stores were opening than closing in six U.S. metropolitan statistical areas before statewide sales restrictions on flavored tobacco and COVID-19. Uniform licensing is recommended to define vape shops and track their location and sales practices.