It's not all about residual confounding: a plea for QBA for epidemiologic researchers and educators.

We spend a great deal of time on confounding in our teaching, in our methods development and in our assessment of study results. This may give the impression that uncontrolled confounding is the biggest problem that observational epidemiology faces, when in fact, other sources of bias such as selection bias, measurement error, missing data, and misalignment of zero time may often (especially if they are all present in a single study) lead to a stronger deviation from the truth. Compared to the amount of time we spend teaching how to address confounding in a data analysis, we spend relatively little time teaching methods for simulating confounding (and other sources of bias) to learn their impact and develop plans to mitigate or quantify the bias. We review a paper by Desai et al that uses simulation methods to quantify the impact of an unmeasured confounder when it is completely missing or when a proxy of the confounder is measured. We use this article to discuss how we can use simulations of sources of bias to ensure we generate better and more valid study estimates, and we discuss the importance of simulating realistic datasets with plausible bias structures to guide data collection. If an advanced life form exists outside of our current universe and they came to earth with the goal of scouring the published epidemiologic literature to understand what the biggest problem epidemiologists have, they would quickly discover that the limitations section of publications would provide them with all the information they needed. And most likely what they would conclude is that the biggest problem that we face is uncontrolled confounding. It seems to be an obsession of ours.

Does Engagement in HIV Care Affect Screening, Diagnosis, and Control of Noncommunicable Diseases in Sub-Saharan Africa? A Systematic Review and Meta-analysis.

Low- and middle-income countries are facing a growing burden of noncommunicable diseases (NCDs). Providing HIV treatment may provide opportunities to increase access to NCD services in under-resourced environments. We conducted a systematic review and meta-analysis to evaluate whether use of antiretroviral therapy (ART) was associated with increased screening, diagnosis, treatment, and control of diabetes, hypertension, chronic kidney disease, or cardiovascular disease among people living with HIV in sub-Saharan Africa (SSA). A comprehensive search of electronic literature databases for studies published between 01 January 2011 and 31 December 2022 yielded 26 studies, describing 13,570 PLWH in SSA, 61% of whom were receiving ART. Random effects models were used to calculate summary odds ratios (ORs) of the risk of diagnosis by ART status and corresponding 95% confidence intervals (95% CIs), where appropriate. ART use was associated with a small but imprecise increase in the odds of diabetes diagnosis (OR 1.07; 95% CI 0.71, 1.60) and an increase in the odds of hypertension diagnosis (OR 2.10, 95% CI 1.42, 3.09). We found minimal data on the association between ART use and screening, treatment, or control of NCDs. Despite a potentially higher NCD risk among PLWH and regional efforts to integrate NCD and HIV care, evidence to support effective care integration models is lacking.

Use of quantitative bias analysis to evaluate single-arm trials with real-world data external controls.

PURPOSE: Use of real-world data (RWD) for external controls added to single-arm trials (SAT) is increasingly prevalent in regulatory submissions. Due to inherent differences in the data-generating mechanisms, biases can arise. This paper aims to illustrate how to use quantitative bias analysis (QBA). METHODS: Advanced non-small cell lung cancer (NSCLC) serves as an example, where many small subsets of patients with molecular tumor subtypes exist. First, some sources of bias that may occur in oncology when comparing RWD to SAT are described. Second, using a hypothetical immunotherapy agent, a dataset is simulated based on expert input for survival analysis of advanced NSCLC. Finally, we illustrate the impact of three biases: missing confounder, misclassification of exposure, and outcome evaluation. RESULTS: For each simulated scenario, bias was induced by removing or adding data; hazard ratios (HRs) were estimated applying conventional analyses. Estimating the bias-adjusted treatment effect and uncertainty required carefully selecting the bias model and bias factors. Although the magnitude of each biased and bias-adjusted HR appeared moderate in all three hypothetical scenarios, the direction of bias was variable. CONCLUSION: These findings suggest that QBA can provide an intuitive framework for bias analysis, providing a key means of challenging assumptions about the evidence. However, the accuracy of bias analysis is itself dependent on correct specification of the bias model and bias factors. Ultimately, study design should reduce bias, but QBA allows us to evaluate the impact of unavoidable bias to assess the quality of the evidence.

Toward Open and Reproducible Epidemiology.

Starting in the 2010s, researchers in the experimental social sciences rapidly began to adopt increasingly open and reproducible scientific practices. These practices include publicly sharing deidentified data when possible, sharing analytical code, and preregistering study protocols. Empirical evidence from the social sciences suggests such practices are feasible, can improve analytical reproducibility, and can reduce selective reporting. In academic epidemiology, adoption of open-science practices has been slower than in the social sciences (with some notable exceptions, such as registering clinical trials). Epidemiologic studies are often large, complex, conceived after data have already been collected, and difficult to replicate directly by collecting new data. These characteristics make it especially important to ensure their integrity and analytical reproducibility. Open-science practices can also pay immediate dividends to researchers' own work by clarifying scientific reasoning and encouraging well-documented, organized workflows. We consider how established epidemiologists and early-career researchers alike can help midwife a culture of open science in epidemiology through their research practices, mentorship, and editorial activities.

Burden of Chronic Obstructive Pulmonary Disease Attributable to Tuberculosis: A Microsimulation Study.

Tuberculosis (TB) is a risk factor for chronic obstructive pulmonary disease (COPD), but COPD is also a predictor of TB. The excess life-years lost to COPD caused by TB can potentially be saved by screening for and treating TB infection. We examined the number of life-years that could be saved by preventing TB and TB-attributable COPD. We compared the observed (no intervention) and counterfactual microsimulation models constructed from observed rates in the Danish National Patient Registry (covering all Danish hospitals between 1995 and 2014). In the Danish population of TB and COPD-naive individuals (n = 5,206,922), 27,783 persons (0.5%) developed TB. Among those who developed TB, 14,438 (52.0%) developed TB with COPD. Preventing TB saved 186,469 life-years overall. The excess number of life-years lost to TB alone was 7.07 years per person, and the additional number of life-years lost among persons who developed COPD after TB was 4.86 years per person. The life-years lost to TB-associated COPD are substantial, even in regions where TB can be expected to be identified and treated promptly. Prevention of TB could prevent a substantial amount of COPD-related morbidity; the benefit of screening and treatment for TB infection is underestimated by considering morbidity from TB alone.

Preconception Periodontitis and Risk of Spontaneous Abortion in a Prospective Cohort Study.

Few studies have evaluated the association between periodontitis and spontaneous abortion (SAB), and all had limitations. We used data from the Pregnancy Study Online (PRESTO), a prospective preconception cohort study of 3,444 pregnancy planners in the United States and Canada (2019-2022), to address this question. Participants provided self-reported data on periodontitis diagnosis, treatment, and symptoms of severity (i.e., loose teeth) via the enrollment questionnaire. SAB (pregnancy loss at <20 weeks' gestation) was assessed via bimonthly follow-up questionnaires. Participants contributed person-time from the date of a positive pregnancy test to the gestational week of SAB, loss to follow-up, or 20 weeks' gestation, whichever came first. We fitted Cox regression models with weeks of gestation as the time scale to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs), and we used inverse probability of treatment weighting to account for differential loss to follow-up. We used probabilistic quantitative bias analysis to estimate the magnitude and direction of the effect of exposure misclassification bias on results. In weighted multivariable models, we saw no appreciable association between preconception periodontitis diagnosis (HR = 0.97, 95% CI: 0.76, 1.23) or treatment (HR = 1.01, 95% CI: 0.79, 1.27) and SAB. A history of loose teeth was positively associated with SAB (HR = 1.38, 95% CI: 0.88, 2.14). Quantitative bias analysis indicated that our findings were biased towards the null but with considerable uncertainty in the bias-adjusted results.

Attrition from Care Among Men Initiating ART in Male-Only Clinics Compared with Men in General Primary Healthcare Clinics in Khayelitsha, South Africa: A Matched Propensity Score Analysis.

Men have higher rates of attrition from antiretroviral therapy (ART) programs than women. In Khayelitsha, a high HIV prevalence area in South Africa, two public sector primary healthcare clinics offer services, including HIV testing and treatment, exclusively to men. We compared attrition from ART care among men initiating ART at these clinics with male attrition in six general primary healthcare clinics in Khayelitsha. We described baseline characteristics of patients initiating ART at the male and general clinics from 1 January 2014 to 31 March 2018. We used exposure propensity scores (generated based on baseline health and age) to match male clinic patients 1:1 to males at other clinics. The association between attrition (death or loss to follow-up, defined as no visits for nine months) and clinic type was estimated using Cox proportional hazards regression. Follow-up time began at ART initiation and ended at attrition, clinic transfer, or dataset closure. Before matching, patients from male clinics (n = 784) were younger than males from general clinics (n = 2726), median age: 31.2 vs 35.5 years. Those initiating at male clinics had higher median CD4 counts at ART initiation [Male Clinic 1: 329 (IQR 210-431), Male Clinic 2: 364 (IQR 260-536), general clinics 258 (IQR 145-398), cells/mm3]. In the matched analysis (1451 person-years, 1568 patients) patients initiating ART at male clinics had lower attrition (HR 0.71; 95% CI 0.60-0.85). In separate analyses for each of the two male clinics, only the more established male clinic showed a protective effect. Male-only clinics reached younger, healthier men, and had lower ART attrition than general services. These findings support clinic-specific adaptations to create more male-friendly environments.

Associations of inter-annual rainfall decreases with subsequent HIV outcomes for persons with HIV on antiretroviral therapy in Southern Africa: a collaborative analysis of cohort studies.

BACKGROUND: Periods of droughts can lead to decreased food security, and altered behaviours, potentially affecting outcomes on antiretroviral therapy (ART) among persons with HIV (PWH). We investigated whether decreased rainfall is associated with adverse outcomes among PWH on ART in Southern Africa. METHODS: Data were combined from 11 clinical cohorts of PWH in Lesotho, Malawi, Mozambique, South Africa, Zambia, and Zimbabwe, participating in the International epidemiology Databases to Evaluate AIDS Southern Africa (IeDEA-SA) collaboration. Adult PWH who had started ART prior to 01/06/2016 and were in follow-up in the year prior to 01/06/2016 were included. Two-year rainfall from June 2014 to May 2016 at the location of each HIV centre was summed and ranked against historical 2-year rainfall amounts (1981-2016) to give an empirical relative percentile rainfall estimate. The IeDEA-SA and rainfall data were combined using each HIV centre's latitude/longitude. In individual-level analyses, multivariable Cox or generalized estimating equation regression models (GEEs) assessed associations between decreased rainfall versus historical levels and four separate outcomes (mortality, CD4 counts < 200 cells/mm3, viral loads > 400 copies/mL, and > 12-month gaps in follow-up) in the two years following the rainfall period. GEEs were used to investigate the association between relative rainfall and monthly numbers of unique visitors per HIV centre. RESULTS: Among 270,708 PWH across 386 HIV centres (67% female, median age 39 [IQR: 32-46]), lower rainfall than usual was associated with higher mortality (adjusted Hazard Ratio: 1.18 [95%CI: 1.07-1.32] per 10 percentile rainfall rank decrease) and unsuppressed viral loads (adjusted Odds Ratio: 1.05 [1.01-1.09]). Levels of rainfall were not strongly associated with CD4 counts < 200 cell/mm3 or > 12-month gaps in care. HIV centres in areas with less rainfall than usual had lower numbers of PWH visiting them (adjusted Rate Ratio: 0.80 [0.66-0.98] per 10 percentile rainfall rank decrease). CONCLUSIONS: Decreased rainfall could negatively impact on HIV treatment behaviours and outcomes. Further research is needed to explore the reasons for these effects. Interventions to mitigate the health impact of severe weather events are required.

Long-term aircraft noise exposure and risk of hypertension in postmenopausal women.

BACKGROUND: Studies of the association between aircraft noise and hypertension are complicated by inadequate control for potential confounders and a lack of longitudinal assessments, and existing evidence is inconclusive. OBJECTIVES: We evaluated the association between long-term aircraft noise exposure and risk of hypertension among post-menopausal women in the Women's Health Initiative Clinical Trials, an ongoing prospective U.S. METHODS: Day-night average (DNL) and night equivalent sound levels (Lnight) were modeled for 90 U.S. airports from 1995 to 2010 in 5-year intervals using the Aviation Environmental Design Tool and linked to participant geocoded addresses from 1993 to 2010. Participants with modeled exposures ≥45 A-weighted decibels (dB [A]) were considered exposed, and those outside of 45 dB(A) who also did not live in close proximity to unmodeled airports were considered unexposed. Hypertension was defined as systolic/diastolic blood pressure ≥140/90 mmHg or inventoried/self-reported antihypertensive medication use. Using time-varying Cox proportional hazards models, we estimated hazard ratios (HRs) for incident hypertension when exposed to DNL or Lnight ≥45 versus <45 dB(A), controlling for sociodemographic, behavioral, and environmental/contextual factors. RESULTS/DISCUSSION: There were 18,783 participants with non-missing DNL exposure and 14,443 with non-missing Lnight exposure at risk of hypertension. In adjusted models, DNL and Lnight ≥45 db(A) were associated with HRs of 1.00 (95% confidence interval [CI]: 0.93, 1.08) and 1.06 (95%CI: 0.91, 1.24), respectively. There was no evidence supporting a positive exposure-response relationship, and findings were robust in sensitivity analyses. Indications of elevated risk were seen among certain subgroups, such as those living in areas with lower population density (HRinteraction: 0.84; 95%CI: 0.72, 0.98) or nitrogen dioxide concentrations (HRinteraction: 0.82; 95%CI: 0.71, 0.95), which may indicate lower ambient/road traffic noise. Our findings do not suggest a relationship between aircraft noise and incident hypertension among older women in the U.S., though associations in lower ambient noise settings merit further investigation.

Moderate alcohol consumption on the risk of stroke in the Million Veteran Program.

BACKGROUND: There is inconsistent evidence on the association of moderate alcohol consumption and stroke risk in the general population and is not well studied among U.S. Veterans. Furthermore, it is unclear whether primarily drinking beer, wine, or liquor is associated with a difference in stroke risk. METHODS: The study included 185,323 Million Veteran Program participants who self-reported alcohol consumption on the Lifestyle Survey. Moderate consumption was defined as 1-2 drinks/day and beverage preference of beer, wine or liquor was defined if ≥ 50% of total drinks consumed were from a single type of beverage. Strokes were defined using ICD-9 and ICD-10 codes from the participants' electronic health record. RESULTS: The mean (sd) age of the sample was 64 (13) years and 11% were women. We observed 4,339 (94% ischemic; 6% hemorrhagic) strokes over a median follow-up of 5.2 years. In Cox models adjusted for age, sex, race, education, income, body mass index, smoking, exercise, diet, cholesterol, prevalent diabetes, prevalent hypertension, lipid-lowering medication, antihypertensive medication, and diabetes medication, moderate alcohol consumption (1-2 drinks/day) was associated with a 22% lower risk of total stroke compared with never drinking [Hazards ratio (HR) 95% confidence interval (CI): 0.78 (0.67, 0.92)]. When stratifying by stroke type, we observed a similar protective association with moderate consumption and ischemic stroke [HR (95% CI): 0.76 (0.65, 0.90)], but a non-statistically significant higher risk of hemorrhagic stroke [HR (95% CI): 1.29 (0.64, 2.61)]. We did not observe a difference in ischemic or hemorrhagic stroke risk among those who preferred beer, liquor or wine vs. no beverage preference. When stratifying by prior number of hospital visits (≤ 15, 16-33, 34-64, ≥ 65) as a proxy for health status, we observed attenuation of the protective association with greater number of visits [HR (95% CI): 0.87 (0.63, 1.19) for ≥ 65 visits vs. 0.80 (0.59, 1.08) for ≤ 15 visits]. CONCLUSIONS: We observed a lower risk of ischemic stroke, but not hemorrhagic stroke with moderate alcohol consumption and did not observe substantial differences in risk by beverage preference among a sample of U.S. Veterans. Healthy user bias of moderate alcohol consumption may be driving some of the observed protective association.

Gaps in the type 2 diabetes care cascade: a national perspective using South Africa's National Health Laboratory Service (NHLS) database.

BACKGROUND: Research out of South Africa estimates the total unmet need for care for those with type 2 diabetes mellitus (diabetes) at 80%. We evaluated the care cascade using South Africa's National Health Laboratory Service (NHLS) database and assessed if HIV infection impacts progression through its stages. METHODS: The cohort includes patients from government facilities with their first glycated hemoglobin A1c (HbA1c) or plasma glucose (fasting (FPG); random (RPG)) measured between January 2012 to March 2015 in the NHLS. Lab-diagnosed diabetes was defined as HbA1c ≥ 6.5%, FPG ≥ 7.0mmol/l, or RPG ≥ 11.1mmol/l. Cascade stages post diagnosis were retention-in-care and glycaemic control (defined as an HbA1c < 7.0% or FPG < 8.0mmol/l or RPG < 10.0mmol/l) over 24-months. We estimated gaps at each stage nationally and by people living with HIV (PLWH) and without (PLWOH). RESULTS: Of the 373,889 patients tested for diabetes, 43.2% had an HbA1c or blood glucose measure indicating a diabetes diagnosis. Amongst those with lab-diagnosed diabetes, 30.9% were retained-in-care (based on diabetes labs) and 8.7% reached glycaemic control by 24-months. Prevalence of lab-diagnosed diabetes in PLWH was 28.6% versus 47.3% in PLWOH. Among those with lab-diagnosed diabetes, 34.3% of PLWH were retained-in-care versus 30.3% PLWOH. Among people retained-in-care, 33.8% of PLWH reached glycaemic control over 24-months versus 28.6% of PLWOH. CONCLUSIONS: In our analysis of South Africa's NHLS database, we observed that 70% of patients diagnosed with diabetes did not maintain in consistent diabetes care, with fewer than 10% reaching glycemic control within 24 months. We noted a disparity in diabetes prevalence between PLWH and PLWOH, potentially linked to different screening methods. These differences underscore the intricacies in care but also emphasize how HIV care practices could guide better management of chronic diseases like diabetes. Our results underscore the imperative for specialized strategies to bolster diabetes care in South Africa.

Tracing People Living With Human Immunodeficiency Virus Who Are Lost to Follow-up at Antiretroviral Therapy Programs in Southern Africa: A Sampling-Based Cohort Study in 6 Countries.

BACKGROUND: Attrition threatens the success of antiretroviral therapy (ART). In this cohort study, we examined outcomes of people living with human immunodeficiency virus (PLHIV) who were lost to follow-up (LTFU) during 2014-2017 at ART programs in Southern Africa. METHODS: We confirmed LTFU (missed appointment for ≥60 or ≥90 days, according to local guidelines) by checking medical records and used a standardized protocol to trace a weighted random sample of PLHIV who were LTFU in 8 ART programs in Lesotho, Malawi, Mozambique, South Africa, Zambia, and Zimbabwe, 2017-2019. We ascertained vital status and identified predictors of mortality using logistic regression, adjusted for sex, age, time on ART, time since LTFU, travel time, and urban or rural setting. RESULTS: Among 3256 PLHIV, 385 (12%) were wrongly categorized as LTFU and 577 (17%) had missing contact details. We traced 2294 PLHIV (71%) by phone calls, home visits, or both: 768 (34% of 2294) were alive and in care, including 385 (17%) silent transfers to another clinic; 528 (23%) were alive without care or unknown care; 252 (11%) had died. Overall, the status of 1323 (41% of 3256) PLHIV remained unknown. Mortality was higher in men than women, higher in children than in young people or adults, and higher in PLHIV who had been on ART <1 year or LTFU ≥1 year and those living farther from the clinic or in rural areas. Results were heterogeneous across sites. CONCLUSIONS: Our study highlights the urgent need for better medical record systems at HIV clinics and rapid tracing of PLHIV who are LTFU.

A Framework for Descriptive Epidemiology.

In this paper, we propose a framework for thinking through the design and conduct of descriptive epidemiologic studies. A well-defined descriptive question aims to quantify and characterize some feature of the health of a population and must clearly state: 1) the target population, characterized by person and place, and anchored in time; 2) the outcome, event, or health state or characteristic; and 3) the measure of occurrence that will be used to summarize the outcome (e.g., incidence, prevalence, average time to event, etc.). Additionally, 4) any auxiliary variables will be prespecified and their roles as stratification factors (to characterize the outcome distribution) or nuisance variables (to be standardized over) will be stated. We illustrate application of this framework to describe the prevalence of viral suppression on December 31, 2019, among people living with human immunodeficiency virus (HIV) who had been linked to HIV care in the United States. Application of this framework highlights biases that may arise from missing data, especially 1) differences between the target population and the analytical sample; 2) measurement error; 3) competing events, late entries, loss to follow-up, and inappropriate interpretation of the chosen measure of outcome occurrence; and 4) inappropriate adjustment.

Misconceptions About the Direction of Bias From Nondifferential Misclassification.

Measurement error is pervasive in epidemiologic research. Epidemiologists often assume that mismeasurement of study variables is nondifferential with respect to other analytical variables and then rely on the heuristic that "nondifferential misclassification will bias estimates towards the null." However, there are many exceptions to the heuristic for which bias towards the null cannot be assumed. In this paper, we compile and characterize 7 exceptions to this rule and encourage analysts to take a more critical and nuanced approach to evaluating and discussing bias from nondifferential mismeasurement.

On the Need to Revitalize Descriptive Epidemiology.

Nearly every introductory epidemiology course begins with a focus on person, place, and time, the key components of descriptive epidemiology. And yet in our experience, introductory epidemiology courses were the last time we spent any significant amount of training time focused on descriptive epidemiology. This gave us the impression that descriptive epidemiology does not suffer from bias and is less impactful than causal epidemiology. Descriptive epidemiology may also suffer from a lack of prestige in academia and may be more difficult to fund. We believe this does a disservice to the field and slows progress towards goals of improving population health and ensuring equity in health. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak and subsequent coronavirus disease 2019 pandemic have highlighted the importance of descriptive epidemiology in responding to serious public health crises. In this commentary, we make the case for renewed focus on the importance of descriptive epidemiology in the epidemiology curriculum using SARS-CoV-2 as a motivating example. The framework for error we use in etiological research can be applied in descriptive research to focus on both systematic and random error. We use the current pandemic to illustrate differences between causal and descriptive epidemiology and areas where descriptive epidemiology can have an important impact.

Illustrating How to Simulate Data From Directed Acyclic Graphs to Understand Epidemiologic Concepts.

Simulation methods are a powerful set of tools that can allow researchers to better characterize phenomena from the real world. As such, the ability to simulate data represents a critical set of skills that epidemiologists should use to better understand epidemiologic concepts and ensure that they have the tools to continue to self-teach even when their formal instruction ends. Simulation methods are not always taught in epidemiology methods courses, whereas causal directed acyclic graphs (DAGs) often are. Therefore, this paper details an approach to building simulations from DAGs and provides examples and code for learning to perform simulations. We recommend using very simple DAGs to learn the procedures and code necessary to set up a simulation that builds on key concepts frequently of interest to epidemiologists (e.g., mediation, confounding bias, M bias). We believe that following this approach will allow epidemiologists to gain confidence with a critical skill set that may in turn have a positive impact on how they conduct future epidemiologic studies.

Relationship Between Level of American Football Playing and Diagnosis of Chronic Traumatic Encephalopathy in a Selection Bias Analysis.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts such as those from American football. Our understanding of this association is based on research in autopsied brains, since CTE can only be diagnosed postmortem. Such studies are susceptible to selection bias, which needs to be accounted for to ensure a generalizable estimate of the association between repetitive head impacts and CTE. We evaluated the relationship between level of American football playing and CTE diagnosis after adjusting for selection bias. The sample included 290 deceased male former American football players who donated their brains to the Veterans Affairs-Boston University-Concussion Legacy Foundation (VA-BU-CLF) Brain Bank between 2008 and 2019. After adjustment for selection bias, college-level and professional football players had 2.38 (95% simulation interval (SI): 1.16, 5.94) and 2.47 (95% SI: 1.46, 4.79) times the risk of being diagnosed with CTE as high-school-level players, respectively; these estimates are larger than estimates with no selection bias adjustment. Since CTE is currently diagnosed only postmortem, we additionally provide plausible scenarios for CTE risk ratios for each level of play during the former players' lifetime. This study provides further evidence to support a dose-response relationship between American football playing and CTE.

One Pill, Once a Day: Simplified Treatment Regimens and Retention in HIV Care.

Simplified drug regimens may improve retention in care for persons with chronic diseases. In April 2013, South Africa adopted a once-daily single-pill human immunodeficiency virus (HIV) treatment regimen as the standard of care, replacing a multiple-pill regimen. Because the regimens had similar biological efficacy, the shift to single-pill therapy offered a real-world test of the impact of simplified drug-delivery mechanisms on patient behavior. Using a quasi-experimental regression discontinuity design, we assessed retention in care among patients starting HIV treatment just before and just after the guideline change. The study included 4,484 patients starting treatment at a large public sector clinic in Johannesburg, South Africa. The share of patients prescribed a single-pill regimen increased by over 40 percentage points between March and April 2013. Initiating treatment after the policy change was associated with 11.7-percentage-points' higher retention at 12 months (95% confidence interval: -2.2, 29.4). Findings were robust to different measures of retention, different bandwidths, and different statistical models. Patients starting treatment early in HIV infection-a key population in the test-and-treat era-experienced the greatest improvements in retention from single-pill regimens.

The Expert Next Door: Interactions With Friends and Family During the COVID-19 Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic thrust the field of public health into the spotlight. For many epidemiologists, biostatisticians, and other public health professionals, this caused the professional aspects of our lives to collide with the personal, as friends and family reached out with concerns and questions. Learning how to navigate this space was new for many of us and required refining our communication style depending on context, setting, and audience. Some of us took to social media, utilizing our existing personal accounts to share information after sorting through and summarizing the rapidly emerging literature to keep loved ones safe. However, those in our lives sometimes asked unanswerable questions, or began distancing themselves when we suggested more stringent guidance than they had hoped for, causing additional stress during an already traumatic time. We often had to remind ourselves that we were also individuals experiencing this pandemic and that our time-intensive efforts were meaningful, relevant, and impactful. As this pandemic and other public health crises continue, we encourage members of our discipline to consider how we can best use shared lessons from this period and to recognize that our professional knowledge, when used in our personal lives, can promote, protect, and bolster confidence in public health.

Causal and Associational Language in Observational Health Research: A Systematic Evaluation.

We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, 3 reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was "associate" (45.7%). Reviewers' ratings of linking word roots were highly heterogeneous; over half of reviewers rated "association" as having at least some causal implication. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.