Publications by authors named "Jason R Gantenberg"
Epidemiologic research questions often focus on evaluating binary outcomes, yet curricula and scientific literature do not always provide clear guidance or examples on selecting and calculating an appropriate measure of association in these scenarios. Reporting inappropriate measures may lead to misleading statistical conclusions. We present a hands-on tutorial that includes annotated code written in an open-source statistical programming language (R) showing readers how to apply, compare, and understand four methods used to estimate a risk or prevalence ratio (or difference), rather than presenting an odds ratio.
View Article and Find Full Text PDFArticle Synopsis
- Respiratory syncytial virus (RSV) poses significant health risks to infants in the US, with exposure timing linked to their birth month; some months lead to higher risks of serious lower respiratory tract infections (LRTI).
- A study analyzed insurance claims from infants born between July 2016 and February 2020, focusing on their first RSV season and the medical attention required for RSV LRTI, revealing varying risks based on birth month.
- Infants born from May to September faced the highest risks of medically attended RSV LRTI during their first season, while those born from October to December had higher hospitalization rates; findings support the use of nirsevimab to mitigate these risks.
Epidemiologic research questions often focus on evaluating binary outcomes, yet curricula and scientific literature do not always provide clear guidance or examples on selecting and calculating an appropriate measure of association in these scenarios. Reporting inappropriate measures may lead to misleading statistical conclusions. We present a hands-on tutorial that includes annotated code written in an open-source statistical programming language (R) showing readers how to apply, compare, and understand four methods used to estimate a risk or prevalence ratio (or difference), rather than presenting an odds ratio.
View Article and Find Full Text PDFAccurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. We conducted a simulation study to evaluate a super learner's predictions of 3 seasonal measures of influenza hospitalizations in the United States: peak hospitalization rate, peak hospitalization week, and cumulative hospitalization rate.
View Article and Find Full Text PDFBackground: Respiratory syncytial virus (RSV) is a leading cause of infant hospitalization in the United States. Preterm infants and those with select comorbidities are at highest risk of RSV-related complications. However, morbidity due to RSV infection is not confined to high-risk infants.
View Article and Find Full Text PDFPurpose: The purpose of the study was to estimate the effect of exposure to neighborhood poverty in adolescence on HIV/STI prevalence in early adulthood.
Methods: Longitudinal data from three waves of the National Longitudinal Study of Adolescent to Adult Health were analyzed. The primary exposure was living in a high- versus medium/low-poverty neighborhood during wave I.
Objectives: Identifying prescribing strategies that improve the efficiency of PrEP should increase its impact at the population level. This study identifies PrEP allocation criteria that most effectively reduce 10-year HIV incidence by 25%, in accordance with the US National HIV/AIDS Strategy's goal for the proportionate reduction in new diagnoses.
Methods: We used a discrete-time stochastic agent-based model to simulate several PrEP engagement strategies.