Examining power dynamics in global health governance using topic modeling and network analysis of Twitter data.

OBJECTIVES: Despite increases in global health actors and funding levels, health inequities persist. We empirically tested whether global health governance (GHG) operates under the rational actor model (RAM) and characterised GHG power dynamics. DESIGN: We collected approximately 75 000 tweets of 20 key global health actors, between 2016 and 2020, using Twitter API. We generated priorities from tweets collected using topic modelling. Priorities from tweets were compared with stated priorities from content analyses of policy documents and with revealed priorities from network analyses of development assistance for health funding data. Comparing priorities derived from Twitter, policy documents and funding data, we can test whether GHG operates under RAM and characterise power dynamics in GHG. PARTICIPANTS: 20 global health actors were identified based on a consensus of three peer-reviewed articles mapping global health networks. All tweets of each actor were collected in 3-month intervals from November 2016 to May 2020. Policy documents and developmental assistance for health (DAH) financial data for each actor were collected for the same period. RESULTS: We find all 20 actors and the global health system collectively fulfil the three conditions of RAM based on stated and revealed priorities. We also find compulsory and institutional power asymmetries in GHG. Funding organisations have compulsory power over channels of DAH and implementing institutions they directly fund. Funding organisations also have transitive influence over implementing institutions receiving DAH funding. CONCLUSIONS: We find that there is a correlation between the priorities of large funders and the priorities of health actors. This correlation in conjunction with GHG operating under the RAM and the asymmetric power held by funders raises issues. GHG under the RAM grants large funders majority of the power to determine global health priorities and ultimately influencing outcomes while implementing organisations, especially those that work closest with populations, have little to limited influence in priority-setting.

Applying the health capability profile to empirically study chronic hepatitis B in rural Senegal: a social justice mixed-methods study protocol.

INTRODUCTION: Despite the early implementation of hepatitis B vaccination and the ongoing decentralisation of chronic hepatitis B (CHB) care, over 10% of the Senegalese adult population lives with CHB and liver cancer remains a main cause of death. Investigating factors associated with CHB infection, prevention of CHB-related morbidity, and prevention and treatment of mortality secondary to CHB calls for a holistic and multidimensional approach. This paper presents the adaptation of the health capability profile (HCP) to a specific epidemiological issue and empirical setting: it seeks to identify and analyse inter-related abilities and conditions (health capabilities) in relation to the CHB epidemic in the rural area of Niakhar, Senegal. METHODS AND ANALYSIS: This ongoing study relies on a sequential social justice mixed-methods design. The HCP is comprehensively adapted to CHB in rural Senegal and guides the design and conduct of the study. Objective and subjective data are collected at the individual level following a mixed-methods explanatory core design. The quantitative module, embedded in the ANRS12356 AmBASS cross-sectional survey (exhaustive sampling), is used to select a purposeful sampling of participants invited for one-on-one qualitative interviews. Additional data are collected at the institutional and community level through health facility surveys and an ethnography (in-depth interviews) of local and national CHB stakeholders. Data analysis adopts a synergistic approach to produce a multilayered analysis of individual HCPs and crosscutting analysis of the 15 health capabilities. The data integration strategy relies on a mixed-methods convergent core design, and will use 0-100 health capability scores as well as flow diagrams to measure and characterise levels of development and interactions among health capabilities, respectively. ETHICS AND DISSEMINATION: This study was approved by Senegalese and French authorities. Results dissemination through local workshops and scientific publications aim at fuelling effective policy change towards CHB-related health capability.