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.

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.

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.

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.

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.

State-Level Social and Economic Policies and Their Association With Perinatal and Infant Outcomes.

Policy Points State-level social and economic policies that expand tax credits, increase paid parental leave, raise the minimum wage, and increase tobacco taxes have been demonstrated to reduce adverse perinatal and infant health outcomes. These findings can help prioritize evidence-based legislated policies to improve perinatal and infant outcomes in the United States. CONTEXT: Rates of preterm birth and infant mortality are alarmingly high in the United States. Legislated efforts may directly or indirectly reduce adverse perinatal and infant outcomes through the enactment of certain economic and social policies. METHODS: We conducted a narrative review to summarize the associations between perinatal and infant outcomes and four state-level US policies. We then used a latent profile analysis to create a social and economic policy profile for each state based on the observed policy indicators. FINDINGS: Of 27 articles identified, nine focused on tax credits, eight on paid parental leave, four on minimum wages, and six on tobacco taxes. In all but three studies, these policies were associated with improved perinatal or infant outcomes. Thirty-three states had tax credit laws, most commonly the earned income tax credit (n = 28, 56%). Eighteen states had parental leave laws. Two states had minimum wage laws lower than the federal minimum; 14 were equal to the federal minimum; 29 were above the federal minimum; and 5 did not have a state law. The average state tobacco tax was $1.76 (standard deviation = $1.08). The latent profile analysis revealed three policy profiles, with the most expansive policies in Western and Northeastern US states, and the least expansive policies in the US South. CONCLUSIONS: State-level social and economic policies have the potential to reduce adverse perinatal and infant health outcomes in the United States. Those states with the least expansive policies should therefore consider enacting these evidence-based policies, as they have shown a demonstratable benefit in other states.

Disparities of COVID-19 and HIV Occurrence Based on Neighborhood Infection Incidence in Philadelphia, Pennsylvania.

Objectives. To evaluate the occurrence of HIV and COVID-19 infections in Philadelphia, Pennsylvania, through July 2020 and identify ecological correlates driving racial disparities in infection incidence. Methods. For each zip code tabulation area, we created citywide comparison Z-score measures of COVID-19 cases, new cases of HIV, and the difference between the scores. Choropleth maps were used to identify areas that were similar or dissimilar in terms of disease patterning, and weighted linear regression models helped identify independent ecological predictors of these patterns. Results. Relative to COVID-19, HIV represented a greater burden in Center City Philadelphia, whereas COVID-19 was more apparent in Northeast Philadelphia. Areas with a greater proportion of Black or African American residents were overrepresented in terms of both diseases. Conclusions. Although race is a shared nominal upstream factor that conveys increased risk for both infections, an understanding of separate structural, demographic, and economic risk factors that drive the overrepresentation of COVID-19 cases in racial/ethnic communities across Philadelphia is critical. Public Health Implications. Difference-based measures are useful in identifying areas that are underrepresented or overrepresented with respect to disease occurrence and may be able to elucidate effective or ineffective mitigation strategies. (Am J Public Health. 2022;112(3):408-416. https://doi.org/10.2105/AJPH.2021.306538).

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).

Effect of Adjustment for Case Misclassification and Infection Date Uncertainty on Estimates of COVID-19 Effective Reproduction Number.

BACKGROUND: Surveillance data captured during the COVID-19 pandemic may not be optimal to inform a public health response, because it is biased by imperfect test accuracy, differential access to testing, and uncertainty in date of infection. METHODS: We downloaded COVID-19 time-series surveillance data from the Colorado Department of Public Health & Environment by report and illness onset dates for 9 March 2020 to 30 September 2020. We used existing Bayesian methods to first adjust for misclassification in testing and surveillance, followed by deconvolution of date of infection. We propagated forward uncertainty from each step corresponding to 10,000 posterior time-series of doubly adjusted epidemic curves. The effective reproduction number (Rt), a parameter of principal interest in tracking the pandemic, gauged the impact of the adjustment on inference. RESULTS: Observed period prevalence was 1.3%; median of the posterior of true (adjusted) prevalence was 1.7% (95% credible interval [CrI]: 1.4%, 1.8%). Sensitivity of surveillance declined over the course of the epidemic from a median of 88.8% (95% CrI: 86.3%, 89.8%) to a median of 60.8% (95% CrI: 60.1%, 62.6%). The mean (minimum, maximum) values of Rt were higher and more variable by report date, 1.12 (0.77, 4.13), compared to those following adjustment, 1.05 (0.89, 1.73). The epidemic curve by report date tended to overestimate Rt early on and be more susceptible to fluctuations in data. CONCLUSION: Adjusting for epidemic curves based on surveillance data is necessary if estimates of missed cases and the effective reproduction number play a role in management of the COVID-19 pandemic.

A narrative review on the validity of electronic health record-based research in epidemiology.

Electronic health records (EHRs) are widely used in epidemiological research, but the validity of the results is dependent upon the assumptions made about the healthcare system, the patient, and the provider. In this review, we identify four overarching challenges in using EHR-based data for epidemiological analysis, with a particular emphasis on threats to validity. These challenges include representativeness of the EHR to a target population, the availability and interpretability of clinical and non-clinical data, and missing data at both the variable and observation levels. Each challenge reveals layers of assumptions that the epidemiologist is required to make, from the point of patient entry into the healthcare system, to the provider documenting the results of the clinical exam and follow-up of the patient longitudinally; all with the potential to bias the results of analysis of these data. Understanding the extent of as well as remediating potential biases requires a variety of methodological approaches, from traditional sensitivity analyses and validation studies, to newer techniques such as natural language processing. Beyond methods to address these challenges, it will remain crucial for epidemiologists to engage with clinicians and informaticians at their institutions to ensure data quality and accessibility by forming multidisciplinary teams around specific research projects.

Preoperative Gabapentin for Minimally Invasive Hysterectomy: A Randomized Controlled Trial.

STUDY OBJECTIVE: To evaluate whether a single dose of gabapentin given preoperatively reduces narcotic use 24 hours after minimally invasive hysterectomy (MIH). DESIGN: Randomized controlled trial. SETTING: Single academic-affiliated community hospital. PATIENTS: Women undergoing MIH for benign indications between June 2016 and June 2017. INTERVENTIONS: Subjects were randomized to receive a preoperative regimen of acetaminophen, celecoxib, and gabapentin versus acetaminophen and celecoxib alone. MEASUREMENTS AND MAIN RESULTS: The primary outcome assessed was the total amount of narcotics used at 24 hours after surgery. Secondary outcomes included adverse effects from gabapentin use, total narcotics used, and pain scores at 2 weeks after surgery. A total of 129 women were randomized and eligible for analysis in the gabapentin study arm (n = 68) or the control arm (n = 61). Demographic characteristics and surgical details were similar between groups. Narcotics used at 24 hours after surgery totaling 168 versus 161 oral morphine milligram equivalents in the gabapentin and control groups, respectively, did not significantly differ between groups (p = .60). Total narcotics used and pain scores at 2 weeks after surgery and the rates of adverse effects from gabapentin were also similar between study arms. CONCLUSION: Single-dose, preoperative gabapentin for women undergoing benign MIH does not reduce total opioid use 24 hours after surgery.

Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA.

BACKGROUND: Despite widespread use, the accuracy of the diagnostic test for SARS-CoV-2 infection is poorly understood. The aim of our work was to better quantify misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves using publicly available surveillance data from Alberta, Canada and Philadelphia, USA. METHODS: We examined time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, the sensitivity and specificity of the diagnostic test. RESULTS: Our analysis revealed that the data were compatible with near-perfect specificity, but it was challenging to gain information about sensitivity. We applied these insights to uncertainty/bias analysis of epidemic curves under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the adjusted epidemic curves likely falls within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60-70% range. In the extreme scenario, hundreds of undiagnosed cases, even among the tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate. CONCLUSION: The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves.

Trends and Characteristics of Proposed and Enacted State Legislation on Childhood Vaccination Exemption, 2011-2017.

Objectives. To examine trends and characteristics of proposed and enacted state legislation that would directly affect states' immunization exemption laws.Methods. We performed content analysis of proposed bills in state legislatures from 2011 to 2017. We classified bills as provaccination or antivaccination.Results. State legislators proposed 175 bills, with the volume increasing over time: 92 (53%) bills expanded access to exemptions, and 83 (47%) limited the ability to exempt. Of the 13 bills signed into law, 12 (92%) limited the ability to exempt. Bills that expanded access to exemptions were more likely to come from Republican legislators and Northeastern and Southern states.Conclusions. Although most proposed legislation would have expanded access to exemptions, bills that limited exemptions were more likely to be enacted into law. Legal barriers to exempt one's children from vaccination persist despite vaccine hesitancy, which is encouraging for public health.Public Health Implications. Most vaccine exemption laws introduced in state legislatures would pose threats to the public's health. There is a need for constituents to engage their elected legislators and advocate provaccination policies.

The Joint Effects of Antenatal Steroids and Gestational Age on Improved Outcomes in Neonates.

OBJECTIVES: Antenatal corticosteroids are standard of care for women at risk of a preterm birth and demonstrated to be protective against poor outcomes in neonates including respiratory disorders, mortality and intraventricular hemorrhage (IVH). Its benefits may vary by gestational age, and accurate estimation is needed in a single-center population to account for practice variation. METHODS: A retrospective cohort of infants admitted to the hospital's neonatal intensive care unit, 1997-2015. Using Poisson regression, we separately modeled the incidence rate ratio of death, grade III or IV intraventricular hemorrhage (IVH), and moderate to severe bronchopulmonary dysplasia (BPD) testing the moderating effects of gestation on antenatal steroids, controlling for potential confounding. RESULTS: Among 5314 infants admitted, death occurred in 298 (6%), severe IVH in 244 (5%), and BPD in 527 (10%). Antenatal steroids were protective of death and BPD in the adjusted analysis, and there was multiplicative interaction where each week increase in gestational age combined with steroid therapy resulted in 13% reduced incidence for each outcome. CONCLUSIONS FOR PRACTICE: Antenatal steroids are protective against severe IVH and moderate to severe BPD, and when combined with gestational age, steroids are associated with greater protective benefits in older neonates. There is likely an ideal window to maximize the benefits of antenatal steroids, and future etiologic research should consider the joint effects with gestational age.

Bayesian Approaches to Racial Disparities in HIV Risk Estimation Among Men Who Have Sex with Men.

BACKGROUND: Men who have sex with men (MSM) continue to be overrepresented for new HIV infections compared with non-MSM. This disparity becomes even more alarming when considering racial groups. We describe the race-specific effects in HIV prevalence among MSM relative to non-MSM and explore the causes of disagreement among estimates. METHODS: We used data from the National Epidemiologic Survey on Alcohol and Related Conditions, a nationally representative longitudinal survey conducted in the US Bayesian learning corrected for potential misclassification of MSM status and adjusted for residual confounding, hypothesized to explain the MSM racial disparity in HIV. We articulated the structure and strength of the latent confounders that would make race-specific risk gradients equivalent. RESULTS: Compared with non-MSM, the adjusted prevalence odds ratio (POR) and 95% credible interval for black MSM having self-reported HIV infection was 5.8 (2.0, 16), while the POR for white MSM was 12 (4.2, 31). For all MSM, the POR for HIV infection was 9.3 (3.6, 23) with black men having 2.6 times the odds of prevalent infection compared with white men. CONCLUSIONS: The observed race-specific associations in MSM are likely not due to misclassification alone, but represent a constellation of factors that differ between racial groups. We recommend specific risk factors in surveys needed to further identify the behavioral characteristics that lead to the observed differences when the estimates are stratified by race.

Bayesian Correction of Misclassification of Pertussis in Vaccine Effectiveness Studies: How Much Does Underreporting Matter?

Diagnosis of pertussis remains a challenge, and consequently research on the risk of disease might be biased because of misclassification. We quantified this misclassification and corrected for it in a case-control study of children in Philadelphia, Pennsylvania, who were 3 months to 6 years of age and diagnosed with pertussis between 2011 and 2013. Vaccine effectiveness (VE; calculated as (1 - odds ratio) × 100) was used to describe the average reduction in reported pertussis incidence resulting from persons being up to date on pertussis-antigen containing vaccines. Bayesian techniques were used to correct for purported nondifferential misclassification by reclassifying the cases per the 2014 Council of State and Territorial Epidemiologists pertussis case definition. Naïve VE was 50% (95% confidence interval: 16%, 69%). After correcting for misclassification, VE ranged from 57% (95% credible interval: 30, 73) to 82% (95% credible interval: 43, 95), depending on the amount of underreporting of pertussis that was assumed to have occurred in the study period. Meaningful misclassification was observed in terms of false negatives detected after the incorporation of infant apnea to the 2014 case definition. Although specificity was nearly perfect, sensitivity of the case definition varied from 90% to 20%, depending on the assumption about missed cases. Knowing the degree of the underreporting is essential to the accurate evaluation of VE.

The impact of psychosocial stressors on postpartum weight retention.

Excessive gestational weight gain and postpartum weight retention are implicated in future morbidity in women. To understand whether psychosocial stressors contribute to weight retention, we used data collected in a cohort of postpartum women and analyzed measures of stress, depression, social support, and health-related quality of life. Depressive symptoms at delivery and worse health-related quality of life and lower stress at 3 months postpartum were associated with 3-month weight retention. Interventions targeting depression and improving quality of life may further reduce weight retained.