Self-Reported PrEP Use and Risk of Bacterial STIs Among Ontarian Men Who Are Gay or Bisexual or Have Sex With Men.

PURPOSE: HIV pre-exposure prophylaxis (PrEP) may increase rates of bacterial sexually transmitted infections (STIs) among gay, bisexual, and other men who have sex with men (GBM) through risk compensation (eg, an increase in condomless sex or number of partners); however, longitudinal studies exploring the time-dependent nature of PrEP uptake and bacterial STIs are limited. We used marginal structural models to estimate the effect of PrEP uptake on STI incidence. METHODS: We analyzed data from the iCruise study, an online longitudinal study of 535 Ontarian GBM from July 2017 to April 2018, to estimate the effects of PrEP uptake on incidence of self-reported bacterial STIs (chlamydia, gonorrhea, and syphilis) collected with 12 weekly diaries. The incidence rate was calculated as the number of infections per 100 person-months, with evaluation of the STIs overall and individually. We used marginal structural models to account for time-varying confounding and quantitative bias analysis to evaluate the sensitivity of estimates to nondifferential outcome misclassification. RESULTS: Participating GBM were followed up for a total of 1,623.5 person-months. Overall, 70 participants (13.1%) took PrEP during the study period. Relative to no uptake, PrEP uptake was associated with an increased incidence rate of gonorrhea (incidence rate ratio = 4.00; 95% CI, 1.67-9.58), but not of chlamydia or syphilis, and not of any bacterial STI overall. Accounting for misclassification, the median incidence rate ratio for gonorrhea was 2.36 (95% simulation interval, 1.08-5.06). CONCLUSIONS: We observed an increased incidence rate of gonorrhea associated with PrEP uptake among Ontarian GBM that was robust to misclassification. Although our findings support current guidelines for integrating gonorrhea screening with PrEP services, additional research should consider the long-term impact of PrEP among this population.

Contrasting methods to operationalize antibiotic exposure in clinical research: a real-world application on healthcare-associated Clostridioides difficile infection.

The goal of this article is to summarize common methods of antibiotic operationalization used in clinical research and demonstrate methods for exposure variable selection. We demonstrate three methods for modeling exposure, using data from a case-control study on Clostridioides difficile infection in hospitalized patients: 1) factor analysis, 2) logistic regression models, and 3) Least Absolute Shrinkage and Selection Operator (LASSO) regression. The factor analysis identified 8 variables contributing the most variation in the dataset: any antibiotic exposure; number of antibiotic classes; number of antibiotic courses; dose; and specific classes monobactam, 𝛽-lactam 𝛽-lactamase inhibitors, rifamycin, and cephalosporin. The logistic regression models resulting in the best model fit used predictors representing any antibiotic exposure and the proportion of a patient's hospitalization on antibiotics. The LASSO model selected 22 variables for inclusion in the predictive model, of which 10 were antibiotic exposure variables, including: any antibiotic exposure; classes 𝛽-lactam 𝛽-lactamase inhibitors, carbapenem, cephalosporin, fluoroquinolone, monobactam, rifamycin, sulfonamides, and miscellaneous; and proportion of hospitalization on antibiotics. Investigators studying antibiotic use should consider multiple characteristics of exposure informed by their research question and the theory on how antibiotics may impact the distribution of the outcome in their target population.

Inferring Population HIV Viral Load From a Single HIV Clinic's Electronic Health Record: Simulation Study With a Real-World Example.

BACKGROUND: Population viral load (VL), the most comprehensive measure of the HIV transmission potential, cannot be directly measured due to lack of complete sampling of all people with HIV. OBJECTIVE: A given HIV clinic's electronic health record (EHR), a biased sample of this population, may be used to attempt to impute this measure. METHODS: We simulated a population of 10,000 individuals with VL calibrated to surveillance data with a geometric mean of 4449 copies/mL. We sampled 3 hypothetical EHRs from (A) the source population, (B) those diagnosed, and (C) those retained in care. Our analysis imputed population VL from each EHR using sampling weights followed by Bayesian adjustment. These methods were then tested using EHR data from an HIV clinic in Delaware. RESULTS: Following weighting, the estimates moved in the direction of the population value with correspondingly wider 95% intervals as follows: clinic A: 4364 (95% interval 1963-11,132) copies/mL; clinic B: 4420 (95% interval 1913-10,199) copies/mL; and clinic C: 242 (95% interval 113-563) copies/mL. Bayesian-adjusted weighting further improved the estimate. CONCLUSIONS: These findings suggest that methodological adjustments are ineffective for estimating population VL from a single clinic's EHR without the resource-intensive elucidation of an informative prior.

A Qualitative Study of Physicians' Views on the Reuse of Electronic Health Record Data for Secondary Analysis.

Electronic health records (EHRs) have become ubiquitous in clinical practice. Given the rich biomedical data captured for a large panel of patients, secondary analysis of these data for health research is also commonplace. Yet, there are many caveats to EHR data that the researchers must be aware of, such as the accuracy of and motive for documentation, and the reason for patients' visits to the clinic. The clinician-the author of the documentation-is thus central to the correct interpretation of EHR data for research purposes. In this study, I interviewed 11 physicians in various clinical specialties to bring attention to their view on the validity of research using EHR data. Qualitative, in-depth, one-on-one interviews were conducted with practicing physicians in inpatient and outpatient medicine. Content analysis using a data-driven, inductive approach to identify themes related to challenges and opportunities in the reuse of EHR data for secondary analysis generated seven themes. Themes that reflected challenges of EHRs for research included (1) audience, (2) accuracy of data, (3) availability of data, (4) documentation practices, and (5) representativeness. Themes that reflected opportunities of EHRs for research included (6) endorsement and (7) enablers. The greatest perceived barriers reflected the intended audience of the EHR, the interpretation and meaning of the data, and the quality of the data for research purposes. Physicians generally expressed more perceived challenges than opportunities in the reuse of EHR data for research purposes; however, they remained optimistic.

Geospatial Disparities in Youth Sexually Transmitted Infections During COVID-19.

INTRODUCTION: Early in the COVID-19 pandemic, routine sexually transmitted infection (STI) screenings decreased, and test positivity rates increased due to limited screening appointments, national-level STI testing supply shortages, and social distancing mandates. It is unclear if adolescent preventive STI screening has returned to pre-pandemic levels and if pre-existing disparities worsened in late-pandemic. METHODS: This cross-sectional study examined 22,974 primary care visits by 13-19-year-olds in the Philadelphia metropolitan area undergoing screening for gonorrhea and chlamydia in a 31-clinic pediatric primary care network during 2018-2022. Using interrupted-time-series analysis and logistic regression, pandemic-related changes in the asymptomatic STI screening rate and test positivity were tracked across patient demographics. Neighborhood moderation was investigated by census-tract-level Child Opportunity Index in 2023. RESULTS: The asymptomatic STI screening rate dropped by 27.8 percentage points (pp) and 13.5pp when the pandemic and national STI test supply shortage began, respectively, but returned to pre-pandemic levels after supply availability was restored in early 2021. Non-Hispanic-Black adolescents had a significant pandemic drop in STI screening rate, and it did not return to prep-andemic levels (-3.6 pp in the late-pandemic period, p<0.01). This decrease was more pronounced in socioeconomically and educationally disadvantaged neighborhoods (7.5 pp and 9.9 pp lower, respectively) than in advantaged neighborhoods (both p<0.001), controlling for sex, age, insurance type and clinic characteristics. CONCLUSIONS: Neighborhood socioeconomic and educational disadvantage amplified racial-ethnic disparities in STI screening during the pandemic. Future interventions should focus on improving primary care utilization of non-Hispanic-Black adolescents to increase routine STI screening and preventive care utilization.

Measuring variation in infant mortality and deaths of despair by US congressional district in Pennsylvania: a methodological case study.

Many ecological studies examine health outcomes and disparities using administrative boundaries such as census tracts, counties, or states. These boundaries help us to understand the patterning of health by place, along with impacts of policies implemented at these levels. However, additional geopolitical units (units with both geographic and political meaning), such as congressional districts (CDs), present further opportunities to connect research with public policy. Here we provide a step-by-step guide on how to conduct disparities-focused analysis at the CD level. As an applied case study, we use geocoded vital statistics data from 2010-2015 to examine levels of and disparities in infant mortality and deaths of despair in the 19 US CDs of Pennsylvania for the 111th-112th (2009-2012) Congresses and 18 CDs for the 113th-114th (2013-2016) Congresses. We also provide recommendations for extending CD-level analysis to other outcomes, states, and geopolitical boundaries, such as state legislative districts. Increased surveillance of health outcomes at the CD level can help prompt policy action and advocacy and, hopefully, reduce rates of and disparities in adverse health outcomes.

A catchment and location-allocation analysis of mammography access in Delaware, US: implications for disparities in geographic access to breast cancer screening.

BACKGROUND: Despite a 40% reduction in breast cancer mortality over the last 30 years, not all groups have benefited equally from these gains. A consistent link between later stage of diagnosis and disparities in breast cancer mortality has been observed by race, socioeconomic status, and rurality. Therefore, ensuring equitable geographic access to screening mammography represents an important priority for reducing breast cancer disparities. Access to breast cancer screening was evaluated in Delaware, a state that experiences an elevated burden from breast cancer but is otherwise representative of the US in terms of race and urban-rural characteristics. We first conducted a catchment analysis of mammography facilities. Finding evidence of disparities by race and rurality, we next conducted a location-allocation analysis to identify candidate locations for the establishment of new mammography facilities to optimize equitable access. METHODS: A catchment analysis using the ArcGIS Pro Service Area analytic tool characterized the geographic distribution of mammography sites and Breast Imaging Centers of Excellence (BICOEs). Poisson regression analyses identified census tract-level correlates of access. Next, the ArcGIS Pro Location-Allocation analytic tool identified candidate locations for the placement of additional mammography sites in Delaware according to several sets of breast cancer screening guidelines. RESULTS: The catchment analysis showed that for each standard deviation increase in the number of Black women in a census tract, there were 68% (95% CI 38-85%) fewer mammography units and 89% (95% CI 60-98%) fewer BICOEs. The more rural counties in the state accounted for 41% of the population but only 22% of the BICOEs. The results of the location-allocation analysis depended on which set of screening guidelines were adopted, which included increasing mammography sites in communities with a greater proportion of younger Black women and in rural areas. CONCLUSIONS: The results of this study illustrate how catchment and location-allocation analytic tools can be leveraged to guide the equitable selection of new mammography facility locations as part of a larger strategy to close breast cancer disparities.

Alignment of Ending the HIV Epidemic Priority Jurisdictions With Availability of HIV Service Organizations: An Ecological Study.

We sought to describe and quantify the association between HIV service organization availability, HIV burden, and HIV awareness and prevention in the 57 priority jurisdictions selected as part of the U.S. Ending the HIV Epidemic initiative. On average, jurisdictions with more per capita organizations had more people living with HIV, more individuals aware of their positive status, and more individuals prescribed PrEP (b = 0.3; 95% CI [0.2, 0.5] for each additional case per 1,000 people in the first metric, and b = 0.3; 95% CI [0.2, 0.4] and b = 0.1; 95% CI [< 0.1, 0.1], respectively, for each percentage point change in the second two metrics), accounting for jurisdiction size. Several jurisdictions were outliers in the modeled associations and may reflect comparatively better, or worse, performance than similar jurisdictions. This information can assist in evaluating resource allocation and determining whether availability translates to accessibility.

Modeling the impact of xenointoxication in dogs to halt Trypanosoma cruzi transmission.

BACKGROUND: Chagas disease, a vector-borne parasitic disease caused by Trypanosoma cruzi, affects millions in the Americas. Dogs are important reservoirs of the parasite. Under laboratory conditions, canine treatment with the systemic insecticide fluralaner demonstrated efficacy in killing Triatoma infestans and T. brasiliensis, T. cruzi vectors, when they feed on dogs. This form of pest control is called xenointoxication. However, T. cruzi can also be transmitted orally when mammals ingest infected bugs, so there is potential for dogs to become infected upon consuming infected bugs killed by the treatment. Xenointoxication thereby has two contrasting effects on dogs: decreasing the number of insects feeding on the dogs but increasing opportunities for exposure to T. cruzi via oral transmission to dogs ingesting infected insects. OBJECTIVE: Examine the potential for increased infection rates of T. cruzi in dogs following xenointoxication. DESIGN/METHODS: We built a deterministic mathematical model, based on the Ross-MacDonald malaria model, to investigate the net effect of fluralaner treatment on the prevalence of T. cruzi infection in dogs in different epidemiologic scenarios. We drew upon published data on the change in percentage of bugs killed that fed on treated dogs over days post treatment. Parameters were adjusted to mimic three scenarios of T. cruzi transmission: high and low disease prevalence and domestic vectors, and low disease prevalence and sylvatic vectors. RESULTS: In regions with high endemic disease prevalence in dogs and domestic vectors, prevalence of infected dogs initially increases but subsequently declines before eventually rising back to the initial equilibrium following one fluralaner treatment. In regions of low prevalence and domestic or sylvatic vectors, however, treatment seems to be detrimental. In these regions our models suggest a potential for a rise in dog prevalence, due to oral transmission from dead infected bugs. CONCLUSION: Xenointoxication could be a beneficial and novel One Health intervention in regions with high prevalence of T. cruzi and domestic vectors. In regions with low prevalence and domestic or sylvatic vectors, there is potential harm. Field trials should be carefully designed to closely follow treated dogs and include early stopping rules if incidence among treated dogs exceeds that of controls.

Geolocation to Identify Online Study-Eligible Gay, Bisexual, and Men who have Sex with Men in Philadelphia, Pennsylvania.

BACKGROUND: Data collection and cleaning procedures to exclude bot-generated responses are used to maintain the data integrity of samples from online surveys. However, these procedures may be time-consuming and difficult to implement. Thus, we aim to evaluate the validity of a single-step geolocation algorithm for recruiting eligible gay, bisexual, and men who have sex with men in Philadelphia for an online study. METHODS: We used a 4-step approach, based on common practices for evaluating bot-generated and fraudulent responses, to assess the validity of participants' Qualtrics survey data as our referent standard. We then compared it to Qualtrics' single-step geolocation algorithm that used the MaxMind commercial database to map participants' Internet protocol address to their approximate location. We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the single-step geolocation approach relative to the 4-step approach. RESULTS: There were 826 respondents who completed the survey and 440 (53%) were eligible for enrollment based on the 4-step approach. The single-step geolocation approach yielded a sensitivity of 91% (95% CI = 88%, 93%), specificity of 79% (95% CI = 74%, 83%), PPV of 83% (95% CI = 80%, 86%), and NPV of 88% (95% CI = 85%, 91%). CONCLUSIONS: Geolocation alone provided a moderately high level of agreement with the 4-step approach for identifying geographically eligible participants in the online sample, but both approaches may be subject to additional misclassification. Researchers may want to consider multiple procedures to ensure data integrity in online samples.

A Catchment and Location-Allocation Analysis of Mammography Access in Delaware, US: Implications for disparities in geographic access to breast cancer screening.

Background: Despite a 40% reduction in breast cancer mortality over the last 30 years, not all groups have benefited equally from these gains. A consistent link between later stage of diagnosis and disparities in breast cancer mortality has been observed by race, socioeconomic status, and rurality. Therefore, ensuring equitable geographic access to screening mammography represents an important priority for reducing breast cancer disparities. This study conducted a catchment and location-allocation analysis of mammography access in Delaware, a state that is representative of the US in terms of race and urban-rural characteristics and experiences an elevated burden from breast cancer. Methods: A catchment analysis using the ArcGIS Pro Service Area analytic tool characterized the geographic distribution of mammography sites and Breast Imaging Centers of Excellence (BICOEs). Poisson regression analyses identified census tract-level correlates of access. Next, the ArcGIS Pro Location-Allocation analytic tool identified candidate locations for the placement of additional mammography sites in Delaware according to several sets of breast cancer screening guidelines. Results: The catchment analysis showed that for each standard deviation increase in the number of Black women in a census tract, there were 64% (95% CI, 0.18-0.66) fewer mammography units and 85% (95% CI, 0.04-0.48) fewer BICOEs. The more rural counties in the state accounted for 41 % of the population but only 22% of the BICOEs. The results of the location-allocation analysis depended on which set of screening guidelines were adopted, which included increasing mammography sites in communities with a greater proportion of younger Black women and in rural areas. Conclusions: The results of this study illustrate how catchment and location-allocation analytic tools can be leveraged to guide the equitable selection of new mammography facility locations as part of a larger strategy to close breast cancer disparities.

Modeling the impact of xenointoxication in dogs to halt Trypanosoma cruzi transmission.

Background: Chagas disease, a vector-borne parasitic disease caused by Trypanosoma cruzi , affects millions in the Americas. Dogs are important reservoirs of the parasite. Under laboratory conditions, canine treatment with the systemic insecticide fluralaner demonstrated efficacy in killing Triatoma infestans and T. brasiliensis, T. cruzi vectors, when they feed on dogs. This form of pest control is called xenointoxication. However, T. cruzi can also be transmitted orally when mammals ingest infected bugs, so there is potential for dogs to become infected upon consuming infected bugs killed by the treatment. Xenointoxication thereby has two contrasting effects on dogs: decreasing the number of insects feeding on the dogs but increasing opportunities for exposure to T. cruzi via oral transmission to dogs ingesting infected insects. Objective: Examine the potential for increased infection rates of T. cruzi in dogs following xenointoxication. Design/Methods: We built a deterministic mathematical model, based on the Ross-MacDonald malaria model, to investigate the net effect of fluralaner treatment on the prevalence of T. cruzi infection in dogs in different epidemiologic scenarios. We drew upon published data on the change in percentage of bugs killed that fed on treated dogs over days post treatment. Parameters were adjusted to mimic three scenarios of T. cruzi transmission: high and low disease prevalence and domestic vectors, and low disease prevalence and sylvatic vectors. Results: In regions with high endemic disease prevalence in dogs and domestic vectors, prevalence of infected dogs initially increases but subsequently declines before eventually rising back to the initial equilibrium following one fluralaner treatment. In regions of low prevalence and domestic or sylvatic vectors, however, treatment seems to be detrimental. In these regions our models suggest a potential for a rise in dog prevalence, due to oral transmission from dead infected bugs. Conclusion: Xenointoxication could be a beneficial and novel One Health intervention in regions with high prevalence of T. cruzi and domestic vectors. In regions with low prevalence and domestic or sylvatic vectors, there is potential harm. Field trials should be carefully designed to closely follow treated dogs and include early stopping rules if incidence among treated dogs exceeds that of controls. Author summary: Chagas disease, caused by the parasite Trypanosoma cruzi , is transmitted via triatomine insect vectors. In Latin America, dogs are a common feeding source for triatomine vectors and subsequently an important reservoir of T. cruzi . One proposed intervention to reduce T. cruzi transmission is xenointoxication: treating dogs with oral insecticide to kill triatomine vectors in order to decrease overall T. cruzi transmission. Fluralaner, commonly administered to prevent ectoparasites such as fleas and ticks, is effective under laboratory conditions against the triatomine vectors. One concern with fluralaner treatment is that rapid death of the insect vectors may make the insects more available to oral ingestion by dogs; a more effective transmission pathway than stercorarian, the usual route for T. cruzi transmission. Using a mathematical model, we explored 3 different epidemiologic scenarios: high prevalence endemic disease within a domestic T. cruzi cycle, low prevalence endemic disease within a domestic T. cruzi cycle, and low prevalence endemic disease within a semi-sylvatic T. cruzi cycle. We found a range of beneficial to detrimental effects of fluralaner xenointoxication depending on the epidemiologic scenario. Our results suggest that careful field trials should be designed and carried out before wide scale implementation of fluralaner xenointoxication to reduce T. cruzi transmission.

Assessing and Validating a Model of Study Completion for a Prospective Cohort of Healthy Newborns.

OBJECTIVES: To identify potentially modifiable or actionable factors related to study completion among healthy mother-infant dyads participating in prospective research. PATIENTS/METHODS: We conducted a secondary analysis of completion data from a prospective study on newborn jaundice in the first week of life at a tertiary-care hospital in Philadelphia, PA, from 2015 to 2019. Participation in the original study involved enrollment before newborn discharge and subsequent follow-up for a jaundice assessment between 2 and 6 days of life. For this study, our primary outcome was completion of all study procedures. Associations between predictor variables and the outcome were assessed using bivariate and multivariable analyses. We fit a predictive model of study completion using logistic regression and validated the model using 5-fold cross-validation. RESULTS: Of 501 mother-infant dyads enrolled in the original study, 304 completed the study. Median maternal age was 28 years and 81.8% of mothers delivered via vaginal birth. Study completion was associated with colocation of the study visit with the initial well-child visit (adjusted odds ratio [aOR], 2.99, 95% confidence interval [CI], 2.01-4.46) and provision of an alternate phone number by the participant (aOR, 1.99; 95% CI, 1.34-2.96). The cross-validated model performed similarly to our final predictive model and had an average area under the receiver operating characteristic curve of 0.67 (range, 0.59-0.72), with a sensitivity of 68% and specificity of 60%. CONCLUSIONS: Findings demonstrate the importance of communication and patient-centric approaches for recruitment and retention in newborn research. Future work should incorporate these approaches while continuing to evaluate study retention strategies.

Data Quality in Electronic Health Record Research: An Approach for Validation and Quantitative Bias Analysis for Imperfectly Ascertained Health Outcomes Via Diagnostic Codes.

It is incumbent upon all researchers who use the electronic health record (EHR), including data scientists, to understand the quality of such data. EHR data may be subject to measurement error or misclassification that have the potential to bias results, unless one applies the available computational techniques specifically created for this problem. In this article, we begin with a discussion of data-quality issues in the EHR focusing on health outcomes. We review the concepts of sensitivity, specificity, positive and negative predictive values, and demonstrate how the imperfect classification of a dichotomous outcome variable can bias an analysis, both in terms of prevalence of the outcome, and relative risk of the outcome under one treatment regime (aka exposure) compared to another. This is then followed by a description of a generalizable approach to probabilistic (quantitative) bias analysis using a combination of regression estimation of the parameters that relate the true and observed data and application of these estimates to adjust the prevalence and relative risk that may have existed if there was no misclassification. We describe bias analysis that accounts for both random and systematic errors and highlight its limitations. We then motivate a case study with the goal of validating the accuracy of a health outcome, chronic infection with hepatitis C virus, derived from a diagnostic code in the EHR. Finally, we demonstrate our approaches on the case study and conclude by summarizing the literature on outcome misclassification and quantitative bias analysis.

Perceived Barriers to and Facilitators of Long-Acting Injectable HIV PrEP Use Among Black, Hispanic/Latino, and White Gay, Bisexual, and Other Men Who Have Sex With Men.

Long-acting injectable pre-exposure prophylaxis (LAI-PrEP) was recently approved for HIV prevention as an alternative to daily oral PrEP. We explored preferences and attitudes toward LAI-PrEP among Black, Hispanic/Latino, and White gay, bisexual, and other men who have sex with men (GBM) using focus groups (n = 13) and in-depth interviews (n = 17). Participants expressed differing levels of interest in LAI-PrEP. While important benefits of LAI-PrEP included convenience, provider-facilitated PrEP discussion, and expansion of PrEP options, participants raised concerns about treatment efficacy and side effects, discomfort with needles/injections, cost, and frequency of clinic visits. Our findings highlight ongoing challenges with accessing HIV-prevention tools and provide guidance for developing strategies to enhance LAI-PrEP uptake among GBM.

Accessibility of HIV Services in Philadelphia: Location-Allocation Analysis.

INTRODUCTION: As the first step in the HIV care continuum, timely diagnosis is central to reducing transmission of the virus and ending the HIV epidemic. Studies have shown that distance from a testing site is essential for ease of access to services and educational material. This study shows how location-allocation analysis can be used to improve allocation of HIV testing services utilizing existing publicly available data from 2015 to 2019 on HIV prevalence, testing site location, and factors related to HIV in Philadelphia, Pennsylvania. METHODS: The ArcGIS Location-Allocation analytic tool was used to calculate locations for HIV testing sites using a method that minimizes the distance between demand-point locations and service facilities. ZIP code level demand was initially specified on the basis of the percentage of late HIV diagnoses and in a sensitivity analysis on the basis of a composite of multiple factors. Travel time and distance from demand to facilities determined the facility location allocation. This analysis was conducted from 2021 to 2022. RESULTS: Compared with the 37 facilities located in 20 (43%) Philadelphia ZIP codes, the model proposed reallocating testing facilities to 37 (79%) ZIP codes using percent late diagnoses to define demand. On average, this would reduce distance to the facilities by 65% and travel time to the facilities by 56%. Results using the sensitivity analysis were similar. CONCLUSIONS: A wider distribution of HIV testing services across the city of Philadelphia may reduce distance and travel time to facilities, improve accessibility of testing, and in turn increase the percentage of people with knowledge of their status.

Partisan Polarization of Childhood Vaccination Policies, 1995‒2020.

Objectives. To examine trends in partisan polarization of childhood vaccine bills and the impact of polarization on bill passage in the United States. Methods. We performed content analysis on 1497 US state bills (1995-2020) and obtained voting returns for 228 legislative votes (2011‒2020). We performed descriptive and statistical analyses using 2 measures of polarization. Results. Vote polarization rose more rapidly for immunization than abortion or veterans' affairs bills. Bills in 2019-2020 were more than 7 times more likely to be polarized than in 1995-1996 (odds ratio [OR] = 7.04; 95% confidence interval [CI] = 3.54, 13.99). Bills related to public health emergencies were more polarized (OR = 1.76; 95% CI = 1.13, 2.75). Sponsor polarization was associated with 34% lower odds of passage (OR = 0.66; 95% CI = 0.42, 1.03). Conclusions. State lawmakers were more divided on vaccine policy, but partisan bills were less likely to pass. Bill characteristics associated with lower polarization could signal opportunities for future bipartisanship. Public Health Implications. Increasing partisan polarization could alter state-level vaccine policies in ways that jeopardize childhood immunization rates or weaken responsiveness during public health emergencies. Authorities should look for areas of bipartisan agreement on how to maintain vaccination rates. (Am J Public Health. 2022;112(10):1471-1479. https://doi.org/10.2105/AJPH.2022.306964).

Towards Eliminating Nonmedical Vaccination Exemptions Among School-Age Children.

The increase in childhood vaccine hesitancy and corresponding use of nonmedical exemptions to abstain from vaccination has deleteriously impacted the public's health. This has many in the field calling for widespread elimination of nonmedical school-entry exemptions, as has been done in six states to date: West Virginia, Mississippi, California, New York, Maine, and Connecticut. By eliminating nonmedical exemptions, vaccination rates can be improved, with the corresponding decline in vaccine-preventable disease incidence. Yet the path towards widespread adoption of these policies presents legislative and judicial implications which evolve with the changing political landscape. In this this article, we discuss legislative actions concerning the expansion of exemptions, whether the widespread elimination of nonmedical exemptions would be effective from a practical and legal end, and how the COVID-19 pandemic has influenced such legislation, with specific focus on Delaware.