To assess the quality of childbirth care and its determinants along the continuum of care in Gondar town public health facility in Ethiopia.

An institution-based, cross-sectional study was employed. Completed data were imported to Stata V.16 for cleaning and analysis. A generalised structural equation model was employed to examine the relationships along the continuum of childbirth care and to determine the factors affecting the quality of childbirth care.

This study was conducted among a total of 865 women who delivered in the public health facility of Gondar, Ethiopia, from 19 May to 30 June 2022.

The study revealed the proportion of good-quality childbirth care during admission, intrapartum and immediate postpartum period was 59% (95% CI 55.7, 62.4), 76.8% (95% CI 73.8, 79.5) and 45% (95% CI 41.7, 48.5), respectively. Postsecondary educational status of mothers (β=0.60, 95% CI 0.16, 1.04) and maternal age of 25–35 (β=0.68, 95% CI 0.33, 1.02) were predictors of quality of care at admission. Referral hospital (β=0.43, 95% CI 0.10, 0.76), presence of guidelines (β=1.36, 95% CI 0.72, 1.99) and provider age of 25–35 (β=0.61, 95% CI 0.12, 1.10) affected the quality of care during the intrapartum period. Urban residence (β=0.52, 95% CI 0.12, 0.93), skilled birth attendant experience (β=0.19, 95% CI 0.11, 0.28) and number of delivery couches (β=–0.29, 95% CI –0.44, –0.13) had significant associations with the quality of childbirth care during the immediate postpartum period.

Although our study found improvements in the quality of childbirth care along the continuum compared with previous studies, more workers are needed to alleviate the problem of poor-quality service. Different maternal, provider and facility factors were found to be predictors of the quality of childbirth care.

This systematic review aimed to summarise existing literature on the impacts of armed conflicts on tuberculosis burden and treatment outcomes.

A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

PubMed, Web of Science, Cumulative Index to Nursing and Allied Health Literature Plus, Scopus, ScienceDirect, Embase and medRxiv.

Three reviewers independently screened, selected eligible studies and extracted data. A narrative review was undertaken to summarise the findings qualitatively.

Eleven studies were included in this review, reporting on tuberculosis incidence rates, prevalence and treatment outcomes, including mortality. Overall, the impact of armed conflicts on case notifications was variable. Six studies reported overall increases in tuberculosis case notifications following the onset of conflicts, while three studies reported overall decreases in tuberculosis case notifications. Factors, including limited access to healthcare services, challenges in surveillance and laboratory confirmation, the destruction of health systems and incapacitating the healthcare workforce, contributed to a decrease in the number of notified cases. The higher tuberculosis notification in some of the studies could be attributed to the disruption of tuberculosis prevention and control programmes as well as increased socioeconomic deprivation, including malnutrition, mass migration, poor living conditions and overcrowding that are worsened during conflicts. Armed conflicts without effective interventions were associated with worse tuberculosis treatment outcomes, including lower proportions of people with treatment success and higher proportions of people with loss to follow-up, mortality and treatment failure. However, implementing various interventions in conflict settings (such as establishing a National Tuberculosis Control Programme) led to higher tuberculosis notification rates and treatment success.

The impact of armed conflicts on tuberculosis notification is complex and is influenced by multiple factors. The findings of this review underscore the importance of concerted efforts to control tuberculosis in conflict settings using available resources.

People having close contact with drug-resistant tuberculosis (DR-TB) patients are at increased risk of contracting and developing the disease. However, no comprehensive review has been undertaken to estimate the burden of DR-TB among contacts of DR-TB patients. Therefore, the current systematic review will quantify the prevalence and incidence of DR-TB among contacts of DR-TB patients.

Systematic searches will be conducted in Medline, Embase, Web of Science, Scopus, Cochrane Central Register of Controlled trials (CENTRAL) and Cumulative Index to Nursing and Allied Health Literature (CINHAL) databases. The search will be conducted without restrictions on time, language and geography. A random-effects meta-analysis will be conducted for effect estimates. The pooled prevalence and incidence of DR-TB will be compared between people with and without contact with DR-TB patients. The presence of heterogeneity between studies will be assessed by Higgins I² statistics. Subgroup analysis will be conducted to determine the source of heterogeneity. The risk of bias will be assessed using a visual inspection of the funnel plot and Egger’s regression test statistics. Trim and fill analysis will be done in the presence of publication bias. A sensitivity analysis will be conducted by trimming low-quality studies. The systematic review will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines.

Ethical approval will not be required for this study as it will be a systematic review and meta-analysis based on previously published evidence. The findings of the systematic review will be presented at scientific conferences and published in scientific journals.

The protocol is published in PROSPERO with registration number CRD42023390339.

Early diagnosis and treatment of tuberculosis (TB) is one of the key strategies to achieve the WHO End TB targets. This study aimed to develop and validate a simple, convenient risk score to diagnose pulmonary TB among presumptive TB cases.

This prediction model used Ethiopian national TB prevalence survey data and included 5459 presumptive TB cases from all regions of Ethiopia. Logistic regression was used to determine which variables are predictive of pulmonary TB. A risk prediction model was developed, incorporating significant variables (p

Of total participants, 94 (1.7%) were confirmed to have TB. The final prediction model included three factors with different scores: (1) TB contact history, (2) chest X-ray (CXR) abnormality and (3) two or more symptoms of TB. The optimal cut-off point for the risk score was 6 and was found to have a good discrimination accuracy (c-statistic=0.70, 95% CI: 0.65 to 0.75). The risk score has sensitivity of 51.1%, specificity of 79.9%, positive predictive value of 4.3% and negative predictive value of 98.9%. After internal validation, the optimism coefficient was 0.003, which indicates the model is internally valid.

We developed a risk score that combines TB contact, number of TB symptoms and CXR abnormality to estimate individual risk of pulmonary TB among presumptive TB cases. Though the score is easy to calculate and internally validated, it needs external validation before widespread implementation in a new setting.