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. We were able to reconcile national prevalence estimates and case report data by allowing for changes over time in screening coverage and reporting completeness. In retrospective analysis, chlamydia prevalence was estimated to be almost twice the current levels in the absence of screening and partner notification. Although chlamydia screening and partner notification were both found to reduce chlamydia burden, the relative magnitude of their estimated impacts varied in our sensitivity analyses. The variation in the model predictions highlights the need for further data collection and research to improve our understanding of the natural history of chlamydia and the pathways through which prevention strategies affect transmission dynamics.

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. Under the base case, we estimate that by 2050, TB incidence will decline to 14 cases per million, a 52% (95% posterior interval (PI): 35, 67) reduction from 2016, and 82% (95% posterior interval: 78, 86) of incident TB will be among persons born outside of the United States. Intensified TB control could reduce incidence by 77% (95% posterior interval: 66, 85) by 2050. We predict TB may be eliminated in US-born but not non-US-born persons by 2100. Results were sensitive to numbers of people entering the United States with latent or active TB, and were robust to alternative interpretations of epidemiologic evidence. TB elimination in the United States remains a distant goal; however, strengthening TB prevention and treatment could produce important health benefits.

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

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. METHODS: We developed a national-level transmission model that divides the population by race/ethnicity, preferred gender of sex partners, age, gender, and sexual activity level. We compared our fitted model ("base case") to 4 alternative strategies: (i) no screening, (ii) full adherence to current screening guidelines, (iii) annual universal screening, or (iv) enhanced screening in groups with the highest infection burden. Main outcomes were incidence, infections averted, and incidence rate ratios by race/ethnicity. Mean values and 95% credible intervals were calculated from 1000 draws from parameter posterior distributions. RESULTS: The calibrated model reproduced observed trends in gonorrhea, including disparities in infection burden by race/ethnicity. We estimated that screening for gonorrhea from 2000 to 2015 averted 30% (95% credible intervals, 18-44%) of total infections that would otherwise have occurred. All alternative active screening strategies were estimated to further reduce, but not eliminate, gonorrhea infections relative to the base case, with differential impacts on the subpopulations of interest. CONCLUSIONS: Our model results suggest that screening has reduced gonorrhea incidence in the US population. Additional reductions in infection burden may have been possible over this period with increased screening, but elimination was unlikely.

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. We extracted information on modeling methodology, interventions, and key findings. RESULTS: We identified 47 publications (including two model comparison studies), which reported collectively on 29 distinct mathematical models. Nine models were individual-based, and 20 were deterministic compartmental models. The earliest studies evaluated the benefits of national-level screening programs and predicted potentially large benefits from increased screening. Subsequent trials and further modeling analyses suggested the impact might have been overestimated. Partner notification has been increasingly evaluated in mathematical modeling, whereas behavioral interventions have received relatively limited attention. CONCLUSIONS: Our review provides an overview of chlamydia transmission models and gives a perspective on how mathematical modeling has responded to increasing empirical evidence and addressed policy questions related to prevention of chlamydia infection and sequelae.

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 purpose of this study was to conduct a factor analysis and test the psychometric properties of a new measure, the NeoEAT - Mixed Breastfeeding and Bottle-Feeding (NeoEAT - Mixed Feeding), including internal consistency reliability, test-retest reliability, construct validity and known-groups validity. METHODS: Parents of infants younger than 7 months who had fed by both bottle and breast in the previous 7 days were invited to participate. Internal consistency reliability was tested using Cronbach's α. Test-retest reliability was tested between scores on the NeoEAT - Mixed Feeding completed 2 weeks apart. Construct validity was tested using correlations between the NeoEAT - Mixed-Feeding, the Infant Gastroesophageal Reflux Questionnaire - Revised (I-GERQ-R), and the Infant Gastrointestinal Symptoms Questionnaire (IGSQ). Known-groups validation was tested between healthy infants and infants with feeding problems. RESULTS: A total of 608 parents participated. Exploratory factor analysis revealed a 68-item scale with 5 sub-scales. Internal consistency reliability (Cronbach's α = .88) and test-retest reliability (r = 0.91; p < .001) were both acceptable. Construct validity was demonstrated through correlations with the I-GERQ-R (r = 0.57; p < .001) and IGSQ (r = 0.5; p < .001). Infants with feeding problems scored significantly higher on the NeoEAT - Mixed Feeding, indicating more problematic feeding symptoms, than infants without feeding problems (p < .001), supporting known-groups validity. CONCLUSIONS: The NeoEAT - Mixed Feeding is a 68-item parent-reported measure of breast- and bottle-feeding behavior for infants less than 7 months old that now has evidence of validity and reliability for use in clinical practice and research. The NeoEAT - Mixed Feeding can be used to identify infants with problematic feeding, guide referral decisions, and evaluate response to interventions.

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). We searched PubMed, Web of Science, Embase, Biosis, and Cochrane Library, and included studies from the earliest available date (Jan 1, 1962) to Aug 31, 2017. We identified 312 studies that met inclusion criteria. Predicted tuberculosis incidence varied widely across studies for each risk factor investigated. For population groups with no individual risk factors, annual incidence varied by several orders of magnitude, and 20-year cumulative incidence ranged from close to 0% to 100%. A substantial proportion of modelled results were inconsistent with empirical evidence: for 10-year cumulative incidence, 40% of modelled results were more than double or less than half the empirical estimates. These results demonstrate substantial disagreement between modelling studies on a central feature of tuberculosis natural history. Greater attention to reproducing known features of epidemiology would strengthen future tuberculosis modelling studies, and readers of modelling studies are recommended to assess how well those studies demonstrate their validity.