Chlamydia screening in high schools offers a way to reach adolescents outside of a traditional clinic setting. Using transmission dynamic modeling, we examined the potential impact of high-school-based chlamydia screening programs on the burden of infection within intervention schools and surrounding communities, under varying epidemiological and programmatic conditions.

The burden of non-communicable diseases (NCDs) is rapidly increasing in low- and middle-income countries, but remains largely unknown among people living with HIV (PLWH) in most sub-Saharan African countries.

There is increasing evidence regarding the importance of allergic sensitization through the skin. In this review, we provide an overview of the atopic march and immune mechanism underlying the sensitization and effector phase of food allergy. We present experimental models and human data that support the concept of epicutaneous sensitization and how this forms one half of the dual-allergen exposure hypothesis. We discuss specific important elements in the skin (FLG and other skin barrier gene mutations, Langerhans cells, type 2 innate lymphoid cells, IL-33, TSLP) that have important roles in the development of allergic responses as well as the body of evidence on environmental allergen exposure and how this can sensitize an individual. Given the link between skin barrier impairment, atopic dermatitis, food allergy, allergic asthma, and allergic rhinitis, it is logical that restoring the skin barrier and prevention or treating atopic dermatitis would have beneficial effects on prevention of related allergic diseases, particularly food allergy. We present the experimental and human studies that have evaluated this approach and discuss various factors which may influence the success of these approaches, such as the type of emollient chosen for the intervention, the role of managing skin inflammation, and differences between primary and secondary prevention of atopic dermatitis to achieve the desired outcome.

Personal and indoor air pollution monitors represent two ways to assess acute air pollution exposures; however, few reproductive epidemiology studies have incorporated these tools.

Epidemiologic studies of the short-term effects of ambient particulate matter (PM) on the risk of acute cardiovascular or cerebrovascular events often use data from administrative databases in which only the date of hospitalization is known. A common study design for analyzing such data is the case-crossover design, in which exposure at a time when a patient experiences an event is compared to exposure at times when the patient did not experience an event within a case-control paradigm. However, the time of true event onset may precede hospitalization by hours or days, which can yield attenuated effect estimates. In this article, we consider a marginal likelihood estimator, a regression calibration estimator, and a conditional score estimator, as well as parametric bootstrap versions of each, to correct for this bias. All considered approaches require validation data on the distribution of the delay times. We compare the performance of the approaches in realistic scenarios via simulation, and apply the methods to analyze data from a Boston-area study of the association between ambient air pollution and acute stroke onset. Based on both simulation and the case study, we conclude that a two-stage regression calibration estimator with a parametric bootstrap bias correction is an effective method for correcting bias in health effect estimates arising from delayed onset in a case-crossover study.

In settings of high tuberculosis incidence, previously treated individuals remain at high risk of recurrent tuberculosis and contribute substantially to overall disease burden. Whether tuberculosis case finding and preventive interventions among previously treated people are cost-effective has not been established. We aimed to estimate costs and health benefits of annual post-treatment follow-up examinations and secondary preventive therapy for tuberculosis in a tuberculosis-endemic setting.

To plan for the financial sustainability of immunization programs and make informed decisions to improve immunization coverage and equity, decision-makers need to know how much these programs cost beyond the cost of the vaccine. Non-vaccine delivery cost estimates can significantly influence the cost-effectiveness estimates used to allocate resources at the country level. However, many low- and middle-income countries (LMICs) do not have immunization delivery unit cost estimates available, or have estimates that are uncertain, unreliable, or old. We undertook a Bayesian evidence synthesis to generate country-level estimates of immunization delivery unit costs for LMICs.