The Evolution of Selection Bias in the Recent Epidemiologic Literature-A Selective Overview.

Selection bias has long been central in methodological discussions across epidemiology and other fields. In epidemiology, the concept of selection bias has been continually evolving over time. In this issue of the Journal, Mathur and Shpitser (Am J Epidemiol.

Comparing frequency of booster vaccination to prevent severe COVID-19 by risk group in the United States.

There is a public health need to understand how different frequencies of COVID-19 booster vaccines may mitigate the risk of severe COVID-19, while accounting for waning of protection and differential risk by age and immune status. By analyzing United States COVID-19 surveillance and seroprevalence data in a microsimulation model, here we show that more frequent COVID-19 booster vaccination (every 6-12 months) in older age groups and the immunocompromised population would effectively reduce the burden of severe COVID-19, while frequent boosters in the younger population may only provide modest benefit against severe disease. In persons 75+ years, the model estimated that annual boosters would reduce absolute annual risk of severe COVID-19 by 199 (uncertainty interval: 183-232) cases per 100,000 persons, compared to a one-time booster vaccination.

Selection Bias Requires Selection: The Case of Collider Stratification Bias.

In epidemiology, collider stratification bias, the bias resulting from conditioning on a common effect of two causes, is oftentimes considered a type of selection bias, regardless of the conditioning methods employed. In this commentary, we distinguish between two types of collider stratification bias: collider restriction bias due to restricting to one level of a collider (or a descendant of a collider) and collider adjustment bias through inclusion of a collider (or a descendant of a collider) in a regression model. We argue that categorizing collider adjustment bias as a form of selection bias may lead to semantic confusion, as adjustment for a collider in a regression model does not involve selecting a sample for analysis.

COVID-19 annual update: a narrative review.

Three and a half years after the pandemic outbreak, now that WHO has formally declared that the emergency is over, COVID-19 is still a significant global issue. Here, we focus on recent developments in genetic and genomic research on COVID-19, and we give an outlook on state-of-the-art therapeutical approaches, as the pandemic is gradually transitioning to an endemic situation. The sequencing and characterization of rare alleles in different populations has made it possible to identify numerous genes that affect either susceptibility to COVID-19 or the severity of the disease.

Early OxyContin Marketing Linked To Long-Term Spread Of Infectious Diseases Associated With Injection Drug Use.

The initial marketing of the opioid analgesic OxyContin in 1996 increased fatal drug overdoses over the course of the opioid epidemic in the US. However, the long-term impacts of this marketing on complications of injection drug use, a key feature of the ongoing crisis, are undetermined. This study evaluated the effects of exposure to initial OxyContin marketing on the long-term trajectories of injection drug use-related outcomes in the US.

Increased HIV Transmissions With Reduced Insurance Coverage for HIV Preexposure Prophylaxis: Potential Consequences of .

A US federal court recently ruled against requiring health insurers to cover human immunodeficiency virus (HIV) preexposure prophylaxis (PrEP) under the Affordable Care Act. For every 10% decrease in PrEP coverage resulting from this ruling among US men who have sex with men, we estimate an additional 1140 HIV infections in the following year in that population.

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

Background: Since 2014, multiple outbreaks of human immunodeficiency virus (HIV) among people who inject drugs have occurred across the United States along with hepatitis C virus (HCV), skin and soft tissue infections (SSTIs), and infective endocarditis (IE), creating a converging public health crisis.

Methods: We analyzed the temporal patterns of infectious disease and overdose using a hierarchical Bayesian distributed lag logistic regression model examining the probability that a given geographic area experienced at least 1 HIV case in a given month as a function of the counts/rates of overdose, HCV, SSTI, and IE and associated medical procedures at different lagged time periods.

Results: Current-month HIV is associated with increasing HCV cases, abscess incision and drainage, and SSTI cases, in distinct temporal patterns.

Geographic and temporal trends in fentanyl-detected deaths in Connecticut, 2009-2019.

Purpose: Since 2012 fentanyl-detected fatal overdoses have risen from 4% of all fatal overdoses in Connecticut to 82% in 2019. We aimed to investigate the geographic and temporal trends in fentanyl-detected deaths in Connecticut during 2009-2019.

Methods: Data on the dates and locations of accidental/undetermined opioid-detected fatalities were obtained from Connecticut Office of the Chief Medical Examiner.

Opioid use disorder Cascade of care framework design: A roadmap.

Unintentional overdose deaths, most involving opioids, have eclipsed all other causes of US deaths for individuals less than 50 years of age. An estimated 2.4 to 5 million individuals have opioid use disorder (OUD) yet a minority receive treatment in a given year.

Surveillance for endemic infectious disease outbreaks: Adaptive sampling using profile likelihood estimation.

Outbreaks of an endemic infectious disease can occur when the disease is introduced into a highly susceptible subpopulation or when the disease enters a network of connected individuals. For example, significant HIV outbreaks among people who inject drugs have occurred in at least half a dozen US states in recent years. This motivates the current study: how can limited testing resources be allocated across geographic regions to rapidly detect outbreaks of an endemic infectious disease? We develop an adaptive sampling algorithm that uses profile likelihood to estimate the distribution of the number of positive tests that would occur for each location in a future time period if that location were sampled.

Adventures in COVID-19 Policy Modeling: Education Edition.

Purpose Of Review: To introduce readers to policy modeling, a multidisciplinary field of quantitative analysis, primarily used to help guide decision-making. This review focuses on the choices facing educational administrators, from K-12 to universities in the USA, as they confronted the COVID-19 pandemic. We survey three key model-based approaches to mitigation of SARS-CoV-2 spread in schools and on university campuses.

The Dynamics of Infectious Diseases Associated With Injection Drug Use in Lawrence and Lowell, Massachusetts.

Background: There are a wide variety of infectious complications of injection drug use. Understanding the trajectory of these complications might inform the development of an early warning system for human immunodeficiency virus (HIV) outbreaks that occur regularly among people who inject drugs (PWID).

Methods: A distributed lag Poisson regression model in the Bayesian setting was used to examine temporal patterns in the incidence of injection-associated infectious diseases and their association with HIV cases in Lawrence and Lowell, Massachusetts between 2005 and 2018.

Maximizing the Efficiency of Active Case Finding for SARS-CoV-2 Using Bandit Algorithms.

Even as vaccination for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) expands in the United States, cases will linger among unvaccinated individuals for at least the next year, allowing the spread of the coronavirus to continue in communities across the country. Detecting these infections, particularly asymptomatic ones, is critical to stemming further transmission of the virus in the months ahead. This will require active surveillance efforts in which these undetected cases are proactively sought out rather than waiting for individuals to present to testing sites for diagnosis.

Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis.

Background: Opioid misuse and deaths are increasing in the United States. In 2017, Ohio had the second highest overdose rates in the US, with the city of Cincinnati experiencing a 50% rise in opioid overdoses since 2015. Understanding the temporal and geographic variation in overdose emergencies may help guide public policy responses to the opioid epidemic.

Dynamics of the HIV outbreak and response in Scott County, IN, USA, 2011-15: a modelling study.

Background: In November, 2014, a cluster of HIV infections was detected among people who inject drugs in Scott County, IN, USA, with 215 HIV infections eventually attributed to the outbreak. This study examines whether earlier implementation of a public health response could have reduced the scale of the outbreak.

Methods: In this modelling study, we derived weekly case data from the HIV outbreak in Scott County, IN, and on the uptake of HIV testing, treatment, and prevention services from publicly available reports from the US Centers for Disease Control and Prevention (CDC) and researchers from Indiana.

Bayesian adaptive algorithms for locating HIV mobile testing services.

Background: We have previously conducted computer-based tournaments to compare the yield of alternative approaches to deploying mobile HIV testing services in settings where the prevalence of undetected infection may be characterized by 'hotspots'. We report here on three refinements to our prior assessments and their implications for decision-making. Specifically, (1) enlarging the number of geographic zones; (2) including spatial correlation in the prevalence of undetected infection; and (3) evaluating a prospective search algorithm that accounts for such correlation.

Comparison of treatment effect sizes from pivotal and postapproval trials of novel therapeutics approved by the FDA based on surrogate markers of disease: a meta-epidemiological study.

Background: The U.S. Food and Drug Administration (FDA) often approves new drugs based on trials that use surrogate markers for endpoints, which involve certain trade-offs and may risk making erroneous inferences about the medical product's actual clinical effect.