DECENTRALIZED IMMUNIZATION MONITORING: LESSONS LEARNED FROM FOUR STATES - NIGERIA.

Background: Low immunization coverage in Nigeria accounts for 2.3 million children with zero doses, increasing morbidity and mortality. The government prioritizes 100 local government areas for strategic interventions aiming for a 15% reduction in zero-dose (ZD) children by 2024.

Assessing attitudes towards violence against women and girls, their determinants and health-seeking behaviour among women and men in South Sudan: a cross-sectional national survey.

Objective: Investigating attitudes accepting two categories of violence against women and girls (VAWG) (intimate partner violence-IPV-and other expressions of VAWG) and their association with seven demographic/social determinants and health-seeking behaviours in South Sudan.

Design: Cross-sectional study using data from the South Sudan National Household Survey 2020.

Setting: South Sudan.

Evolution of two distinct variable lymphocyte receptors in lampreys: VLRD and VLRE.

Jawless vertebrates possess an alternative adaptive immune system in which antigens are recognized by variable lymphocyte receptors (VLRs) generated by combinatorial assembly of leucine-rich repeat (LRR) cassettes. Three types of receptors, VLRA, VLRB, and VLRC, have been previously identified. VLRA- and VLRC-expressing cells are T cell-like, whereas VLRB-expressing cells are B cell-like.

How to estimate health service coverage in 58 districts of Benin with no survey data: Using hybrid estimation to fill the gaps.

The global movement to use routine information for managing health systems to achieve the Sustainable Development Goals, relies on administrative data which have inherent biases when used to estimate coverage with health services. Health policies and interventions planned with incorrect information can have detrimental impacts on communities. Statistical inferences using administrative data can be improved when they are combined with random probability survey data.

Innovative approach to improve information accuracy in a two-district cross-sectional study in Bihar, India.

Objective: Combine Health Management Information Systems (HMIS) and probability survey data using the statistical annealing technique (AT) to produce more accurate health coverage estimates than either source of data and a measure of HMIS data error.

Setting: This study is set in Bihar, the fifth poorest state in India, where half the population lives below the poverty line. An important source of data, used by health professionals for programme decision making, is routine health facility or HMIS data.