A Qualitative Exploratory Study of the Political Commitment for Nutrition Programming: A Case Study of Anambra and Kebbi States of Nigeria

In Nigeria, varying levels of malnutrition across states present a critical challenge to public health, demanding tailored policy responses. This paper delves into the specific issues and dynamics influencing nutrition programs in the country. Advocating for nutrition-sensitive actions requires analyzing context-specific political commitment. This article presents a case study on two Nigerian states with varying malnutrition profiles to explore the political economy of nutrition. The study used stakeholder analysis, in-depth interviews, and semi-structured interviews through workshops, incorporating the Political Commitment Rapid Assessment Tool. The objective was to measure political commitment, the window of opportunity for action, and stakeholder analysis. The results showed that despite having a significant child malnutrition problem, Kebbi State received a high political commitment to nutrition, with proportions ranging from 0.67 to 1 in each of the six domains measured. On the other hand, Anambra State, where malnutrition was less severe, had varying commitment levels. Institutional commitment was marginally high (0.67), expressed commitment was high (0.71), and budgetary commitment was lower at 0.33. Kebbi had better support for programs dependent on foreign donors than Anambra. Both states need to use media to increase awareness about nutrition issues. When the nutrition situation is severe, foreign donors' influence grows. In conclusion, there are opportunities for strategic framing and advocacy of the nutrition profile of the states. Local state media can be effective, and institutional coordination committees that include various sectors already facilitate commitment to nutrition actions. However, individual, uncoordinated sectoral action can counterbalance the benefits of these committees. Further possibilities to generate political commitment for nutrition in the states are available. This study not only offers insights into the effectiveness of political strategies in addressing malnutrition but also lays the groundwork for future research and provides actionable recommendations for government policymaking.

Assessing the uncertainty around age-mixing patterns in HIV transmission inferred from phylogenetic trees

Understanding age-mixing patterns in Human Immunodeficiency Virus (HIV) transmission networks can enhance the design and implementation of HIV prevention strategies in sub-Saharan Africa. Due to ethical consideration, it is less likely possible to conduct a benchmark study to assess which sampling strategy, and sub-optimal sampling coverage which can yield best estimates for these patterns. We conducted a simulation study, using phylogenetic trees to infer estimates of age-mixing patterns in HIV transmission, through the computation of proportions of pairings between men and women, who were phylogenetically linked across different age groups (15-24 years, 25-39 years, and 40-49 years); and the means, and standard deviations of their age difference. We investigated also the uncertainty around these estimates as a function of the sampling coverage in four sampling strategies: when missing sequence data were missing completely at random (MCAR), and missing at random (MAR) with at most 30%-50%-70% of women in different age groups being in the sample. The results suggested that age-mixing patterns in HIV transmission can be unveiled from proportions of phylogenetic pairings between men and women across age groups; and the mean, and standard deviation of their age difference. A 55% sampling coverage was sufficient to provide the best values of estimates of age-mixing patterns in HIV transmission with MCAR scenario. But we should be cautious in interpreting proportions of men phylogenetically linked to women because they may be overestimated or underestimated, even at higher sampling coverage. The findings showed that, MCAR was the best sampling strategy. This means, it is advisable not to use sequence data collected in settings where we can find a systematic imbalance of age and gender to investigate age-mixing in HIV transmission. If not possible, ensure to take into consideration the imbalance in interpreting the results.