Assessing the geographic and socioeconomic determinants of vaccine coverage in Ethiopia: A spatial and multistage analysis at the district level.

Background: Despite substantial progress over the past decades, many Ethiopian children still lack the full WHO-recommended immunization schedule. Notably, diphtheria-pertussis-tetanus-Hib-HepB and measles vaccines present large coverage disparities in Ethiopia. This study integrated routine, survey and census data from health, geographic and socioeconomic sources at the district level.

Inequalities in tuberculosis control in Ethiopia: A district-level distributional modelling analysis.

Background: Implementation studies indicate that the addition of tuberculosis diagnosis and treatment services into the community health extension workers' tasks-that is 'task-shifting'-improved case detection and treatment outcomes in Ethiopia. Given resource and operational constraints, only a limited number of areas can be targeted by an expanded task-shifting program. Therefore, we mapped the distributional disparities in tuberculosis services across regions and districts and modelled the equity pathways towards optimising national scale-up of this task-shifting intervention in Ethiopia.

Estimating immunization coverage at the district level: A case study of measles and diphtheria-pertussis-tetanus-Hib-HepB vaccines in Ethiopia.

Ethiopia has made significant progress in the last two decades in improving the availability and coverage of essential maternal and child health services including childhood immunizations. As Ethiopia keeps momentum towards achieving national immunization goals, methods must be developed to analyze routinely collected health facility data and generate localized coverage estimates. This study leverages the District Health Information Software (DHIS2) platform to estimate immunization coverage for the first dose of measles vaccine (MCV1) and the third dose of diphtheria-pertussis-tetanus-Hib-HepB vaccine (Penta3) across Ethiopian districts ("woredas").

Development and internal validation of a prediction model for long-term opioid use-an analysis of insurance claims data.

In the United States, a public-health crisis of opioid overuse has been observed, and in Europe, prescriptions of opioids are strongly increasing over time. The objective was to develop and validate a multivariable prognostic model to be used at the beginning of an opioid prescription episode, aiming to identify individual patients at high risk for long-term opioid use based on routinely collected data. Predictors including demographics, comorbid diseases, comedication, morphine dose at episode initiation, and prescription practice were collected.