Association between social vulnerability and place of death during the first 2 years of COVID-19 in Massachusetts.

We investigated the relationship between individual-level social vulnerability and place of death during the infectious disease emergency of the COVID-19 pandemic in Massachusetts. Our research represents a unique contribution by matching individual-level death certificates with COVID-19 test data to analyse differences in distributions of place of death.

Sexual Networking and HIV/STI Prevention Among Men who have Sex with Men and Identify as Persons of Color in the Era of COVID-19 in Boston, MA: Qualitative Findings from the National HIV Behavioral Surveillance Project.

Men who have sex with men and identify as persons of color (MSM of color) are significantly impacted by HIV in the United States. The COVID-19 pandemic may have disproportionately exacerbated HIV-related disparities among MSM of color by affecting sexual networking behaviors and disrupting access to sexual health care. The current study explored the impact of COVID-19 on sexual networking and HIV/sexually transmitted infection (STI) prevention behaviors among MSM of color in Boston, MA. Eighteen semi-structured interviews were conducted via the 2020-2021 Boston sample of the National HIV Behavioral Surveillance (NHBS) project. Eligible participants were at least 18 years old, identified as a man or non-binary person assigned male at birth and as a person of color, and endorsed ever having sex with men. Interviews were coded using inductive and deductive approaches, and themes were extracted using thematic analysis. When participants were asked about the impact of COVID-19 on sexual networking and HIV/STI prevention, the following themes emerged: (1) differing interpretations of COVID-19 public health guidance, (2) behavior change to meet social and sexual needs, (3) limited or changed access to HIV/STI prevention services; and (4) avoidance of healthcare appointments. Overall, the pandemic affected sexual networking and HIV/STI prevention behaviors among MSM of color. Though changes in sexual networking varied, most participants decreased in-person networking, increased dating app use, and prioritized longer-term relationships. Despite loosening of restrictions, these impacts may persist and should inform the adaptation of sexual networking guidance and interventions to mitigate HIV-related disparities in communities of color.

Evaluating COVID-19 Risk to Essential Workers by Occupational Group: A Case Study in Massachusetts.

Occupational exposure to SARS-CoV-2 varies by profession, but "essential workers" are often considered in aggregate in COVID-19 models. This aggregation complicates efforts to understand risks to specific types of workers or industries and target interventions, specifically towards non-healthcare workers. We used census tract-resolution American Community Survey data to develop novel essential worker categories among the occupations designated as COVID-19 Essential Services in Massachusetts. Census tract-resolution COVID-19 cases and deaths were provided by the Massachusetts Department of Public Health. We evaluated the association between essential worker categories and cases and deaths over two phases of the pandemic from March 2020 to February 2021 using adjusted mixed-effects negative binomial regression, controlling for other sociodemographic risk factors. We observed elevated COVID-19 case incidence in census tracts in the highest tertile of workers in construction/transportation/buildings maintenance (Phase 1: IRR 1.32 [95% CI 1.22, 1.42]; Phase 2: IRR: 1.19 [1.13, 1.25]), production (Phase 1: IRR: 1.23 [1.15, 1.33]; Phase 2: 1.18 [1.12, 1.24]), and public-facing sales and services occupations (Phase 1: IRR: 1.14 [1.07, 1.21]; Phase 2: IRR: 1.10 [1.06, 1.15]). We found reduced case incidence associated with greater percentage of essential workers able to work from home (Phase 1: IRR: 0.85 [0.78, 0.94]; Phase 2: IRR: 0.83 [0.77, 0.88]). Similar trends exist in the associations between essential worker categories and deaths, though attenuated. Estimating industry-specific risk for essential workers is important in targeting interventions for COVID-19 and other diseases and our categories provide a reproducible and straightforward way to support such efforts.

Associations Between Health Insurance Coverage with HIV Detection and Prevention Behaviors Among Individuals with Undiagnosed HIV or at Increased Risk for HIV Infection in the USA.

BACKGROUND: Improving HIV detection and prevention remains a critical public health initiative that requires policy-based solutions. This study sought to compare HIV detection/prevention behaviors before and after healthcare reform in Massachusetts, USA, among heterosexually active persons - the group with the highest reported number of undiagnosed HIV cases. The current study sought to (1) characterize differences in insurance coverage and HIV detection/prevention behaviors between cycles 1 (2006) to 5 (2019); (2) evaluate socio-demographic disparities in insurance coverage accounting for cycle; and (3) evaluate associations between health insurance coverage and HIV detection/prevention behaviors accounting for cycle and socio-demographics. METHODS: This is a secondary analysis of the National HIV Behavioral Surveillance (NHBS) project: Boston HET cycle (i.e., made up of heterosexually active persons living in the Boston area) data. Descriptive, bivariate (e.g., chi-square), and multiple logistic and negative binomial loglink regression analyses were conducted. RESULTS: In chi-square analyses with post hoc Bonferroni tests, the proportion of participants with current health insurance significantly increased from cycle 1 (77%) to cycle 2 (95%), p < .001. In the regression models that controlled for NHBS cycle, 1-year change in age (adjusted odds ratio [aOR] = 1.03, 95% confidence interval [CI] = 1.02, 1.05), female gender (aOR = 3.41, 95% CI = 2.48, 4.69), and change in education category (aOR = 1.19, 95% CI = 1.02, 1.39) were associated with a higher likelihood of having health insurance. In regression models that controlled for cycle, age, gender, and education, participants with health insurance were more likely than those without insurance to report seeing a medical provider in the past year (aOR = 3.49, 95% CI = 2.32, 4.66), ever having an HIV test (aOR = 1.52, 95% CI = 0.35, 2.69) and more frequent HIV testing in the past 2 years (incidence rate ratio [IRR] = 1.44, 95% = 1.14, 1.82). Participants with health insurance did not differ from those without insurance in number of vaginal condomless sex partners (IRR = 1.16, 95% CI = 0.95, 1.41) but did report more condomless anal sex partners in the past year (IRR = 1.97, 95% CI = 1.46, 2.65). CONCLUSIONS: This study demonstrates how health insurance coverage is positively associated with HIV detection and prevention relevant to both US and international efforts to end the HIV epidemic.

Injection of Methamphetamine Has Increased in Boston, Massachusetts: 5 Waves of Centers for Disease Control and Prevention State Surveillance Data.

OBJECTIVES: In the United States, the number of overdose deaths related to opioids in combination with stimulants has increased; however, the Northeast has typically been less impacted by stimulant overdose. Injection drug use (IDU) results in high mortality from overdose and infectious disease and there are racial disparities observed in overdose death rates. We examined trends in stimulant and opioid IDU, including trends stratified by race, using 5 waves of cross-sectional state surveillance data. METHODS: Data came from the Centers for Disease Control and Prevention's National HIV Behavioral Surveillance system Boston, Massachusetts site, which includes 5 waves of data (2005-2018) among adults in the Boston metropolitan area reporting IDU (N = 2550). Outcome measures were type of substance injected in the past 12 months (heroin, prescription opioids, "speedball," cocaine, crack, and/or methamphetamine). RESULTS: Participants were 70% male, 58% non-Hispanic White, and injected a mean of 3 different drugs in the past 12 months. From 2015 to 2018, there was a more than 2-fold increase in injection of methamphetamine (15% vs 38%, P < 0.001), a pattern which held across racial groups. Combination heroin and methamphetamine injection increased from 2015 (15%) to 2018 (35%, P < 0.001). Multiple drug injection (injecting >1 drug) increased significantly across years compared with single drug injection ( P = 0.03). CONCLUSIONS: Findings suggest that increased use of methamphetamine and opioids extends to Boston. There is an urgent need for enhanced screening of methamphetamine use among those using opioids and increased access and payor coverage of efficacious treatments for stimulant and opioid use disorders (eg, contingency management and medication treatment for opioid use disorder).

Patterns of Infectious Disease Associated With Injection Drug Use in Massachusetts.

BACKGROUND: Since 2014, multiple outbreaks of human immunodeficiency virus (HIV) among people who inject drugs have occurred across the United States along with hepatitis C virus (HCV), skin and soft tissue infections (SSTIs), and infective endocarditis (IE), creating a converging public health crisis. METHODS: We analyzed the temporal patterns of infectious disease and overdose using a hierarchical Bayesian distributed lag logistic regression model examining the probability that a given geographic area experienced at least 1 HIV case in a given month as a function of the counts/rates of overdose, HCV, SSTI, and IE and associated medical procedures at different lagged time periods. RESULTS: Current-month HIV is associated with increasing HCV cases, abscess incision and drainage, and SSTI cases, in distinct temporal patterns. For example, 1 additional HCV case occurring 5 and 7 months previously is associated with a 4% increase in the odds of observing at least 1 current-month HIV case in a given locale (odds ratios, 1.04 [90% credible interval {CrI}: 1.01-1.10] and 1.04 [90% CrI: 1.00-1.09]). No such associations were observed for echocardiograms, IE, or overdose. CONCLUSIONS: Lagged associations in other infections preceding rises in current-month HIV counts cannot be described as predictive of HIV outbreaks but may point toward newly discovered epidemics of injection drug use and associated clinical sequalae, prompting clinicians to screen patients more carefully for substance use disorder and associated infections.

Influence of geospatial resolution on sociodemographic predictors of COVID-19 in Massachusetts.

PURPOSE: When studying health risks across a large geographic region such as a state or province, researchers often assume that finer-resolution data on health outcomes and risk factors will improve inferences by avoiding ecological bias and other issues associated with geographic aggregation. However, coarser-resolution data (e.g., at the town or county-level) are more commonly publicly available and packaged for easier access, allowing for rapid analyses. The advantages and limitations of using finer-resolution data, which may improve precision at the cost of time spent gaining access and processing data, have not been considered in detail to date. METHODS: We systematically examine the implications of conducting town-level mixed-effect regression analyses versus census-tract-level analyses to study sociodemographic predictors of COVID-19 in Massachusetts. In a series of negative binomial regressions, we vary the spatial resolution of the outcome, the resolution of variable selection, and the resolution of the random effect to allow for more direct comparison across models. RESULTS: We find stability in some estimates across scenarios, changes in magnitude, direction, and significance in others, and tighter confidence intervals on the census-tract level. Conclusions regarding sociodemographic predictors are robust when regions of high concentration remain consistent across town and census-tract resolutions. CONCLUSIONS: Inferences about high-risk populations may be misleading if derived from town- or county-resolution data, especially for covariates that capture small subgroups (e.g., small racial minority populations) or are geographically concentrated or skewed (e.g., % college students). Our analysis can help inform more rapid and efficient use of public health data by identifying when finer-resolution data are truly most informative, or when coarser-resolution data may be misleading.

Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts.

Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities. Greater awareness of this issue has occurred due to the COVID-19 pandemic, during which inequities in cases, hospitalizations, and deaths were reported but with evidence of substantial missing demographic details. Although the problem of missing race and ethnicity data in COVID-19 cases has been well documented, neither its spatiotemporal variation nor its particular drivers have been characterized. Using individual-level data on confirmed COVID-19 cases in Massachusetts from March 2020 to February 2021, we show how missing race and ethnicity data: (1) varied over time, appearing to increase sharply during two different periods of rapid case growth; (2) differed substantially between towns, indicating a nonrandom distribution; and (3) was associated significantly with several individual- and town-level characteristics in a mixed-effects regression model, suggesting a combination of personal and infrastructural drivers of missing data that persisted despite state and federal data-collection mandates. We discuss how a variety of factors may contribute to persistent missing data but could potentially be mitigated in future contexts.

Massachusetts flu vaccination and application for COVID-19 routine vaccination planning.

Background: SARS-CoV-2 has affected communities of color at disproportionate rates. In particular, Black Americans have higher COVID-19 mortality rates, rooted in health disparities and institutionalized racism. We describe Massachusetts (MA) influenza (flu) vaccination data by race and vaccination location to inform yearly COVID-19 vaccination plans. Methods: We analyzed self-reported, pooled data from the 2017, 2018, and 2019 Massachusetts Behavioral Risk Factor Surveillance System (MA-BRFSS) of adults. Using the questions around race and ethnicity and flu vaccination, we calculated location types most visited as a percent of people receiving flu vaccine, stratified by race. Results: The 3 years combined yielded 6031 completed surveys. Compared to White non-Hispanics, Black non-Hispanics, Hispanics, and other non-White adults combined reported flu vaccination less frequently (p < 0.01). Doctor's office or a health maintenance organization (HMO) were the primary flu vaccination locations among all race subcategories. Within each race category, the top three locations covered 82.7 % of White respondents, while covering only 75.9 % of Hispanic respondents, and 71.0 % of Black respondents. Fewer Hispanic (16.1 %) and Black respondents (13.8 %) were vaccinated at supermarkets or drug stores compared to White respondents (25.2 %). Conclusion: As COVID-19 vaccination will likely be a yearly occurrence, the above findings can help support future COVID-19 vaccination plans. Since the frequency and location of receipt of flu vaccination varied by race/ethnicity in Massachusetts, the state should ensure specific COVID-19 vaccination locations are available going forward.

Gaps in HIV Preexposure Prophylaxis Continuum of Care Following State Partner Services for Massachusetts Primary and Secondary Syphilis Cases, 2017 to 2018.

BACKGROUND: Human immunodeficiency virus (HIV) preexposure prophylaxis (PrEP) reduces HIV acquisition. We used a PrEP continuum of care to measure impact of field epidemiologist-facilitated referrals for PrEP-naive infectious syphilis cases across multiple clinical and pharmacy sites of care. METHODS: Retrospective analysis of 2017 to 2018 primary and secondary syphilis cases, medical charts, and pharmacy data to identify PrEP education, referral offer, referral acceptance, first visit, prescription pickup (PrEP initiation) and 2 to 3 months (PrEP persistence). The HIV seroconversion was determined using database match at syphilis diagnosis date and at 12 months. χ 2 or Fisher's exact tests were used to compare demographic characteristics associated with steps with lower progression rates. RESULTS: Of 1077 syphilis cases, partner services engaged 662 of 787 (84%) HIV-negative cases; 490 were PrEP-naive, 266 received education, 166 were offered referral, 67 accepted referral, 30 attended an initial appointment, and 22 were prescribed PrEP. Of 16 with pharmacy data, 14 obtained medication, and 8 persisted on PrEP at 2 to 3 months. Continuum progression was lowest from (1) PrEP-naïve to receiving PrEP education, (2) offered referral to referral acceptance, and (3) referral acceptance to initial PrEP appointment. Men with male partners were more likely to receive PrEP education or accept a referral. Higher social vulnerability was associated with increased PrEP referral acceptance. CONCLUSIONS: Few individuals accepted PrEP referrals and persisted on PrEP. Field and clinic data capture were inconsistent, possibly underestimating referral volume and impact of field engagement. Efforts aimed at increasing referral acceptance and clinic attendance may improve PrEP uptake especially among women and heterosexual men with syphilis.

Application of an Existing Syndromic Surveillance System to Quantify Possible Cases of Opioid-associated Amnestic Syndrome in Massachusetts.

OBJECTIVES: In recent years, an opioid-associated amnestic syndrome (OAS) was identified in Massachusetts through elicited reporting by health care providers (traditional surveillance, TS). Whether OAS occurs more frequently and with a wider spatiotemporal distribution in Massachusetts remains unclear. We compared the frequency and spatiotemporal characteristics of emergency department (ED) visits for possible OAS (pOAS) using a pre-existing syndromic surveillance system (SyS) with OAS cases captured through TS. METHODS: SyS was queried for Massachusetts ED visits in 15- to 55- year-olds with a chief complaint text and discharge codes for memory loss in association with codes for opioid use (pOAS). SyS data were extracted for 2016-2020, whereas TS was conducted for 2012-2018. Cases identified by SyS and TS were stratified by demographic and spatiotemporal variables. RESULTS: TS ascertained 22 reported cases of OAS (18 males) between 2012 and 2018, ranging from 0 to 5 annually. No identified OAS patients presented between January and March or in western Massachusetts. Between 2016 and 2020, SyS identified 82 ED visits (49 males) with pOAS, ranging from 13 to 22 per year. Over the 5-year period, at least 2 ED visits for pOAS occurred during each month of the year (24 total during January, February, or March) and at least 1 visit occurred in each county except 2, with the second largest number (11) in Berkshire County (at the western border of Massachusetts), where no cases were ascertained through TS. CONCLUSIONS: Although OAS is a relatively rare condition, use of SyS in Massachusetts suggests a broader and more frequent spatiotemporal distribution than previously indicated from TS.

Trends in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Seroprevalence in Massachusetts Estimated from Newborn Screening Specimens.

BACKGROUND: Estimating the cumulative incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for setting public health policies. We leveraged deidentified Massachusetts newborn screening specimens as an accessible, retrospective source of maternal antibodies for estimating statewide seroprevalence in a nontest-seeking population. METHODS: We analyzed 72 117 newborn specimens collected from November 2019 through December 2020, representing 337 towns and cities across Massachusetts. Seroprevalence was estimated for the Massachusetts population after correcting for imperfect test specificity and nonrepresentative sampling using Bayesian multilevel regression and poststratification. RESULTS: Statewide seroprevalence was estimated to be 0.03% (90% credible interval [CI], 0.00-0.11) in November 2019 and rose to 1.47% (90% CI: 1.00-2.13) by May 2020, following sustained SARS-CoV-2 transmission in the spring. Seroprevalence plateaued from May onward, reaching 2.15% (90% CI: 1.56-2.98) in December 2020. Seroprevalence varied substantially by community and was particularly associated with community percent non-Hispanic Black (ß = .024; 90% CI: 0.004-0.044); i.e., a 10% increase in community percent non-Hispanic Black was associated with 27% higher odds of seropositivity. Seroprevalence estimates had good concordance with reported case counts and wastewater surveillance for most of 2020, prior to the resurgence of transmission in winter. CONCLUSIONS: Cumulative incidence of SARS-CoV-2 protective antibody in Massachusetts was low as of December 2020, indicating that a substantial fraction of the population was still susceptible. Maternal seroprevalence data from newborn screening can inform longitudinal trends and identify cities and towns at highest risk, particularly in settings where widespread diagnostic testing is unavailable.

What we know about antibiotics prescribed by dentists in a Brazilian southeastern state.

The objective of this study was to analyze possible associations between antibiotic dental prescriptions in the public health service, health service characteristics, and social characteristics of the municipalities. Using the register of dispensing in the public health service of a state in the Southeast region of Brazil, in 2017 we analyzed patterns of antibiotic prescriptions by dentists. Data were obtained from the Integrated Pharmaceutical Services Management System (SIGAF, in Portuguese). The outcome variable was the number of Daily Defined Doses (DDD) per 1,000 residents/year in each municipality. CART (Classification and Regression Tree) technique was used to determine the influence of the following variables: populational social characteristics (Human Development Index, Gini Index, the proportion of rural population and proportion of families benefiting from the Bolsa Família Program) and oral health services characteristics (access to individual dental care, number of dentists and oral health teams per 1,000 residents, and percentage of preventive and restorative individual dental procedures. Data analysis was performed using IBM SPSS Statistics 21.0. Antibiotics were the medications most prescribed by dentists in the public health service, with penicillin being the most frequently prescribed class. The average DDD/1,000 residents/year for the 421 municipalities surveyed was 96.54 (range 0.008 and 619.660). Select factors were associated with antibiotic prescriptions including access to individual dental care (Adjusted p-value ≤0.001), a number of oral health teams/1,000 inhabitants (Adjusted p-value=0.001), and Gini Index (Adjusted p-value = 0.046). Access to oral health services and inequality were associated with the use of antibiotics.

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.

What we know about antibiotics prescribed by dentists in a Brazilian southeastern state

Abstract The objective of this study was to analyze possible associations between antibiotic dental prescriptions in the public health service, health service characteristics, and social characteristics of the municipalities. Using the register of dispensing in the public health service of a state in the Southeast region of Brazil, in 2017 we analyzed patterns of antibiotic prescriptions by dentists. Data were obtained from the Integrated Pharmaceutical Services Management System (SIGAF, in Portuguese). The outcome variable was the number of Daily Defined Doses (DDD) per 1,000 residents/year in each municipality. CART (Classification and Regression Tree) technique was used to determine the influence of the following variables: populational social characteristics (Human Development Index, Gini Index, the proportion of rural population and proportion of families benefiting from the Bolsa Família Program) and oral health services characteristics (access to individual dental care, number of dentists and oral health teams per 1,000 residents, and percentage of preventive and restorative individual dental procedures. Data analysis was performed using IBM SPSS Statistics 21.0. Antibiotics were the medications most prescribed by dentists in the public health service, with penicillin being the most frequently prescribed class. The average DDD/1,000 residents/year for the 421 municipalities surveyed was 96.54 (range 0.008 and 619.660). Select factors were associated with antibiotic prescriptions including access to individual dental care (Adjusted p-value ≤0.001), a number of oral health teams/1,000 inhabitants (Adjusted p-value=0.001), and Gini Index (Adjusted p-value = 0.046). Access to oral health services and inequality were associated with the use of antibiotics.

Geographic Associations Between Social Factors and SARS-CoV-2 Testing Early in the COVID-19 Pandemic, February-June 2020, Massachusetts.

OBJECTIVES: Widespread SARS-CoV-2 testing is critical to identify infected people and implement public health action to interrupt transmission. With SARS-CoV-2 testing supplies and laboratory capacity now widely available in the United States, understanding the spatial heterogeneity of associations between social determinants and the use of SARS-CoV-2 testing is essential to improve testing availability in populations disproportionately affected by SARS-CoV-2. METHODS: We assessed positive and negative results of SARS-CoV-2 molecular tests conducted from February 1 through June 17, 2020, from the Massachusetts Virtual Epidemiologic Network, an integrated web-based surveillance and case management system in Massachusetts. Using geographically weighted regression and Moran's I spatial autocorrelation tests, we quantified the associations between SARS-CoV-2 testing rates and 11 metrics of the Social Vulnerability Index in all 351 towns in Massachusetts. RESULTS: Median SARS-CoV-2 testing rates decreased with increasing percentages of residents with limited English proficiency (median relative risk [interquartile range] = 0.96 [0.95-0.99]), residents aged ≥65 (0.97 [0.87-0.98]), residents without health insurance (0.96 [0.95-1.04], and people residing in crowded housing conditions (0.89 [0.80-0.94]). These associations differed spatially across Massachusetts, and localized models improved the explainable variation in SARS-CoV-2 testing rates by 8% to 12%. CONCLUSION: Indicators of social vulnerability are associated with variations in SARS-CoV-2 testing rates. Accounting for the spatial heterogeneity in these associations may improve the ability to explain and address the SARS-CoV-2 pandemic at substate levels.

A qualitative study of injection and sexual risk behavior among unstably housed people who inject drugs in the context of an HIV outbreak in Northeast Massachusetts, 2018.

BACKGROUND: To investigate the underlying causes of a sudden increase in HIV among people who inject drugs (PWID) and initiate an appropriate response to the outbreak, we engaged in in-depth qualitative interviews with members of the PWID community in Lawrence and Lowell, Massachusetts. METHODS: We interviewed 34 PWID who were currently or recently unstably housed, then transcribed interviews and coded transcripts, grouping codes into categories from which we identified key themes. RESULTS: Participants described a heightened threat of overdose prompting PWID to inject together, increasing opportunities for sharing injection equipment. There were misunderstandings about safe injection practices to prevent HIV transmission and a low threshold for injection-related risk taking. Stigma regarding HIV prevented conversations about HIV status. Less thought was given to sexual risks than injection-related risks for HIV transmission. CONCLUSIONS: We found multiple facilitators of HIV transmission. Additional HIV education and prevention interventions focusing on both injection and sexual risk practices would benefit this population, in addition to structural interventions such as increased access and availability of syringe service programs.

Emergency department visits for infectious oral conditions in Massachusetts, 2014 through 2018.

BACKGROUND: The authors aimed to measure population-based preventable emergency department (ED) visits related to infectious oral conditions (IOCs) in Massachusetts and to examine the associated sociodemographic factors to support prevention efforts. METHODS: A statewide retrospective analysis of ED visits related to IOCs in Massachusetts from 2014 through 2018 was conducted using a Center for Health Information and Analysis database. The authors described patients' characteristics, dental diagnoses frequencies, emergency severity, lengths of stay, associated treatment, and costs. Multilevel logistic regression was used to assess factors associated with IOC visits. RESULTS: IOC visits in 2014 through 2018 were 1.2% (149,777) of the total ED visits, with an estimated cost of $159.7 million. There was an annual decline in the prevalence of IOC visits from 2014 through 2018. After adjusting for sociodemographic factors, odds of IOC were higher among males (adjusted odd ratio [AOR], 1.26; 95% CI, 1.24 to 1.27), non-Hispanic Blacks compared with non-Hispanic Whites (AOR, 1.03; 95% CI, 1.02 to 1.06), people residing in dental health care professional shortage areas (AOR, 1.06; 95% CI, 1.04 to 1.07), public insurance beneficiaries (AOR, 1.90; 95% CI, 1.87 to 1.93), or uninsured (AOR, 2.60; 95% CI, 2.54 to 2.66) compared with privately insured. CONCLUSIONS: There was an annual decline in the prevalence of IOC visits from 2014 through 2018. Higher odds of IOC visits were associated with young adults, Black patients, uninsured people, public insurance beneficiaries, and people who reside in dental health care professional shortage areas. PRACTICAL IMPLICATIONS: The authors provided statewide data to support proposed policies to improve oral health care in Massachusetts. IOCs are mostly preventable, but well-coordinated care between medicine and dentistry is integral for prevention.

Childhood Respiratory Outpatient Visits Correlate With Socioeconomic Status and Drive Geographic Patterns in Antibiotic Prescribing.

BACKGROUND: Reducing geographic disparities in antibiotic prescribing is a central public health priority to combat antibiotic resistance, but drivers of this variation have been unclear. METHODS: We measured how variation in outpatient visit rates (observed disease) and antibiotic prescribing rates per visit (prescribing practices) contributed to geographic variation in per capita antibiotic prescribing in Massachusetts residents younger than 65 years between 2011 and 2015. RESULTS: Of the difference in per capita antibiotic prescribing between high- and low-prescribing census tracts in Massachusetts, 45.2% was attributable to variation in outpatient visit rates, while 25.8% was explained by prescribing practices. Outpatient visits for sinusitis, pharyngitis, and suppurative otitis media accounted for 30.3% of the gap in prescribing, with most of the variation in visit rates concentrated in children younger than 10 years. Outpatient visits for these conditions were less frequent in census tracts with high social deprivation index. CONCLUSIONS: Interventions aimed at reducing geographic disparities in antibiotic prescribing should target the drivers of outpatient visits for respiratory illness and should account for possible underutilization of health services in areas with the lowest antibiotic consumption. Our findings challenge the conventional wisdom that prescribing practices are the main driver of geographic disparities in antibiotic use.