Story-led Causal Inference
Epidemiology Journal
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5d ago
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Interpretations of Studies on SARS-CoV-2 Vaccination and Post-acute COVID-19 Sequelae
Epidemiology Journal
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5d ago
This article discusses causal interpretations of epidemiologic studies of the effects of vaccination on sequelae after acute severe acute respiratory syndrome coronavirus 2 infection. To date, researchers have tried to answer several different research questions on this topic. While some studies assessed the impact of postinfection vaccination on the presence of or recovery from post-acute coronavirus disease 2019 syndrome, others quantified the association between preinfection vaccination and postacute sequelae conditional on becoming infected. However, the latter analysis does not have a cau ..read more
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Erratum: “The Effect of Mobile Stroke Unit Care on Functional Outcomes: An Application of the Front-door Formula”
Epidemiology Journal
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5d ago
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Partial Identification of the Effects of Sustained Treatment Strategies
Epidemiology Journal
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5d ago
Although many epidemiologic studies focus on point identification, it is also possible to partially identify causal effects under consistency and the data alone. However, the literature on the so-called “assumption-free” bounds has focused on settings with time-fixed exposures. We describe assumption-free bounds for the effects of both static and dynamic sustained interventions. To provide intuition for the width of the bounds, we also discuss a mathematical connection between assumption-free bounds and clone-censor-weight approaches to causal effect estimation. The bounds, which are often wid ..read more
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Long-term Impact of Tropical Cyclones on Disease Exacerbation Among Children with Asthma in the Eastern United States, 2000–2018
Epidemiology Journal
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5d ago
Background: Tropical cyclones are associated with acute increases in mortality and morbidity, but few studies have examined their longer-term health consequences. We assessed whether tropical cyclones are associated with a higher frequency of symptom exacerbation among children with asthma in the following 12 months in eastern United States counties, 2000–2018. Methods: We defined exposure to tropical cyclones as a maximum sustained windspeed >21 meters/second at the county center and used coarsened exact matching to match each exposed county to one or more unexposed counties. We used longi ..read more
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Adaptive Time–Location Sampling for COMPASS: A SARS-CoV-2 Prevalence Study in Fifteen Diverse Communities in the United States
Epidemiology Journal
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5d ago
Background: COVID-19 has placed a disproportionate burden on underserved racial and ethnic groups, community members working in essential industries, those living in areas of high population density, and those reliant on in-person services such as transportation. The goal of this study was to estimate the cross-sectional prevalence of SARS-CoV-2 (active SARS-CoV-2 or prior SARS-CoV-2 infection) in children and adults attending public venues in 15 sociodemographically diverse communities in the United States and to develop a statistical design that could be rigorously implemented amidst unpredi ..read more
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Emulating a Target Trial of Interventions Initiated During Pregnancy With Healthcare Databases: The Example of COVID-19 Vaccination. The Authors Respond
Epidemiology Journal
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5d ago
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A Quantitative Bias Analysis Approach to Informative Presence Bias in Electronic Health Records
Epidemiology Journal
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5d ago
Accurate outcome and exposure ascertainment in electronic health record (EHR) data, referred to as EHR phenotyping, relies on the completeness and accuracy of EHR data for each individual. However, some individuals, such as those with a greater comorbidity burden, visit the health care system more frequently and thus have more complete data, compared with others. Ignoring such dependence of exposure and outcome misclassification on visit frequency can bias estimates of associations in EHR analysis. We developed a framework for describing the structure of outcome and exposure misclassification ..read more
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Prediction Under Interventions: Evaluation of Counterfactual Performance Using Longitudinal Observational Data
Epidemiology Journal
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5d ago
Predictions under interventions are estimates of what a person’s risk of an outcome would be if they were to follow a particular treatment strategy, given their individual characteristics. Such predictions can give important input to medical decision-making. However, evaluating the predictive performance of interventional predictions is challenging. Standard ways of evaluating predictive performance do not apply when using observational data, because prediction under interventions involves obtaining predictions of the outcome under conditions that are different from those that are observed for ..read more
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Thanks to Our Reviewers
Epidemiology Journal
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5d ago
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