Neonatal Eating Assessment Tool - Mixed Breastfeeding and Bottle-Feeding (NeoEAT - Mixed Feeding): factor analysis and psychometric properties.

Background: Early identification of feeding difficulty in infancy is critical to supporting breastfeeding and ensuring optimal nutrition for brain development. The Neonatal Eating Assessment Tool (NeoEAT) is a parent-report assessment that currently has two versions: NeoEAT - Breastfeeding and NeoEAT - Bottle-feeding for use in breast and bottle-fed infants, respectively. There are currently no valid and reliable parent-report measures to assess feeding through a combination of both breast and bottle delivery.

The Impact of Screening and Partner Notification on Chlamydia Prevalence and Numbers of Infections Averted in the United States, 2000-2015: Evaluation of Epidemiologic Trends Using a Pair-Formation Transmission Model.

Population-level effects of control strategies on the dynamics of Chlamydia trachomatis transmission are difficult to quantify. In this study, we calibrated a novel sex- and age-stratified pair-formation transmission model of chlamydial infection to epidemiologic data in the United States for 2000-2015. We used sex- and age-specific prevalence estimates from the National Health and Nutrition Examination Surveys, case report data from national chlamydia surveillance, and survey data from the Youth Risk Behavior Survey on the proportion of the sexually active population aged 15-18 years.

Estimated Impact of Screening on Gonorrhea Epidemiology in the United States: Insights From a Mathematical Model.

Unlabelled: The burden of gonorrhea infections in the United States is high. There are marked disparities by race/ethnicity and sexual orientation. We quantified the impact of screening and treatment on gonorrhea rates in the US population aged 15 to 39 years for the period 2000 to 2015 and estimated the impact that alternative screening strategies might have had over the same period.

Prospects for Tuberculosis Elimination in the United States: Results of a Transmission Dynamic Model.

We estimated long-term tuberculosis (TB) trends in the US population and assessed prospects for TB elimination. We used a detailed simulation model allowing for changes in TB transmission, immigration, and other TB risk determinants. Five hypothetical scenarios were evaluated from 2017 to 2100: 1) maintain current TB prevention and treatment activities (base case); 2) provision of latent TB infection testing and treatment for new legal immigrants; 3) increased uptake of latent TB infection screening and treatment among high-risk populations, including a 3-month isoniazid-rifapentine regimen; 4) improved TB case detection; and 5) improved TB treatment quality.

Progression from latent infection to active disease in dynamic tuberculosis transmission models: a systematic review of the validity of modelling assumptions.

Mathematical modelling is commonly used to evaluate infectious disease control policy and is influential in shaping policy and budgets. Mathematical models necessarily make assumptions about disease natural history and, if these assumptions are not valid, the results of these studies can be biased. We did a systematic review of published tuberculosis transmission models to assess the validity of assumptions about progression to active disease after initial infection (PROSPERO ID CRD42016030009).

The Use of Mathematical Models of Chlamydia Transmission to Address Public Health Policy Questions: A Systematic Review.

Background: Mathematical models of chlamydia transmission can help inform disease control policy decisions when direct empirical evaluation of alternatives is impractical. We reviewed published chlamydia models to understand the range of approaches used for policy analyses and how the studies have responded to developments in the field.

Methods: We performed a literature review by searching Medline and Google Scholar (up to October 2015) to identify publications describing dynamic chlamydia transmission models used to address public health policy questions.