Immunisation is one of the most valuable, impactful and cost-effective public health interventions which delivers positive health, social and economic benefits. Globally, 4 million deaths worldwide are prevented by childhood vaccination every year. In Ethiopia, despite huge progress being made, the routine immunisation coverage has never reached the targeted figures and planned goals. Pastoralist communities are often disproportionately under-vaccinated, and there is often a confluence of interrelated factors that drive this outcome. This study enables us to identify factors affecting immunisation service utilisation in the pastoralist communities of Ethiopia, which helps to design effective and context-specific interventions.

This study aims to explore the behavioural and social drivers (BeSDs) of routine immunisation among the communities with high numbers of zero-dose and under-immunised children in Afar, Somali and Gambella regions of Ethiopia.

A qualitative exploratory study was conducted in three selected regions of Ethiopia (Gambella, Somali and Afar) from 9 November 2023 to 30 December 2023. Purposive sampling was used. A total of 33 interviews were conducted in the three regions. Sample size was determined based on idea saturation. Data was collected using interview guides. The interview guide was developed after reviewing relevant literature, desk review and using the journey to health and immunisation framework. A separate interview guide was developed for the journey mapping exercise, in-depth interview, healthcare workers discussion guide, focus group discussion and observation. Data was analysed thematically.

Behavioural (lack of awareness, lack of reminder/forgetting, misperception about vaccines, negative previous experience, lost card and fear of post-vaccination adverse events).

Structural (language barrier, long distance from home to facility, high cost of transportation, long waiting time, limited training of healthcare professionals and incentives, inconvenient service hours, shortage of health professionals, disrespect by the healthcare provider), Socio-cultural (competing priorities, low community engagement, lack of decision-making autonomy, limited husband involvement, workload, rural residence and larger family size were the commonly mentioned barriers to routine immunisation uptake. On the other hand, structural (house to house visit by health extension workers, counselling about adverse events, presence of outreach service, affordability (free of charge)), behavioural and socio-cultural (knowledge of adverse event management, and respect from community) were enablers to routine immunisation service uptake in pastoralist communities.

The study found several individual and contextual factors affecting routine immunisation uptake in pastoralist communities. Context-specific and tailored interventions which address zero dose drivers should be designed so as to enhance vaccine uptake. The findings suggested the need to design context-specific interventions to address the aforementioned barriers to immunisation.

This study aimed to compare the nutritional status and dietary intake between khat chewer and non-chewer women of reproductive age in Halaba Zone, South Ethiopia.

A comparative cross-sectional study was conducted.

The study was conducted in Halaba Zone, South Ethiopia.

A total of 792 (396 khat chewers and 396 non-chewers) women of reproductive age were selected by a simple random sampling technique from 20 June 2023 to 26 August 2023.

Dietary intake was assessed by a single 24-hour recall method. The nutrient adequacy ratio and mean adequacy ratio were applied to estimate the adequacy of micronutrients. Standing height was measured using a wall-mounted stadiometer to the nearest 0.1 cm, and weight of the women was measured to the nearest 0.1 kg on a battery-powered digital scale (Seca Gmbh & Co. KG, Germany). A linear regression model was fitted to determine the relationship between nutritional status and khat chewing. Binary logistic regression analyses were used to estimate the odds of nutrient intake inadequacy among the two study groups. A p value of

Women who chewed khat had a higher prevalence of underweight (36.6%) than those who did not (9.4%). The mean (SD) body mass index for khat chewer women was 48.66±5.39 kg, while that of non-chewer women was 55.29±6.75 kg. Women who chewed khat were significantly more likely to be underweight than those who had never chewed khat (β = –1.91, 95% CI –2.30 to –1.53; p12 (AOR=2.79 (95% CI 1.79 to 4.36), p

Women who chewed khat were significantly more likely to be underweight compared with those who had never chewed khat. Khat chewers were more likely than non-chewers to have inadequate carbohydrate, protein, thiamine, riboflavin, niacin, vitamin B₁₂, zinc and calcium intake. Public health interventions aimed at improving the nutritional status of women of reproductive age should develop strategies to address the spread of khat-chewing habits.

Ethiopia, the second most populous country in Africa, faces significant demographic transitions, with fertility rates playing a central role in shaping economic and healthcare policies. Family planning programmes face challenges due to funding limitations. The recent suspension of the US Agency for International Development funding exacerbates these issues, highlighting the need for accurate birth forecasting to guide policy and resource allocation. This study applied time-series and advanced machine-learning models to forecast future birth trends in Ethiopia.

Secondary data from the Ethiopian Demographic and Health Survey from 2000 to 2019 were used. After data preprocessing steps, including data conversion, filtering, aggregation and transformation, stationarity was checked using the Augmented Dickey-Fuller (ADF) test. Time-series decomposition was then performed, followed by time-series splitting. Seven forecasting models, including Autoregressive Integrated Moving Average, Prophet, Generalised Linear Models with Elastic Net Regularisation (GLMNET), Random Forest and Prophet-XGBoost, were built and compared. The models’ performance was evaluated using key metrics such as root mean square error (RMSE), mean absolute error (MAE) and R-squared value.

GLMNET emerged as the best model, explaining 77% of the variance with an RMSE of 119.01. Prophet-XGBoost performed reasonably well but struggled to capture the full complexity of the data, with a lower R-squared value of 0.32 and an RMSE of 146.87. Forecasts were made for both average monthly births and average births per woman over a 10-year horizon (2025–2034). The forecast for average monthly births indicated a gradual decline over the projection period. Meanwhile, the average births per woman showed an increasing trend but fluctuated over time, influenced by demographic shifts such as changes in fertility preferences, age structure and migration patterns.

This study demonstrates the effectiveness of combining time-series models and machine learning, with GLMNET and Prophet XGBoost emerging as the most effective. While average monthly births are expected to decline due to demographic transitions and migration, the average births per woman will remain high, reflecting persistent fertility preferences within certain subpopulations. These findings underscore the need for policies addressing both population trends and sociocultural factors.