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.

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.

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.

This paper describes the study protocol, which aims to evaluate the effectiveness of a multifaceted intervention package called ‘Enhanced Primary Healthcare’ (EnPHC) on the process of care and intermediate clinical outcomes among patients with Type 2 diabetes mellitus (T2DM) and hypertension. Other outcome measures include patients’ experience and healthcare providers’ job satisfaction.

Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care.

Cervical cancer is the fourth most common cancer among women worldwide, causing more than 300 000 deaths globally each year. In addition to screening and prevention, effective cancer treatment is needed to reduce cervical cancer mortality. We discuss the role of imaging in cervical cancer management and estimate the potential survival effect of scaling up imaging in several different contexts.