Key influencers of mass drug administration implementation and scale-up: a social network analysis of soil-transmitted helminth intervention platforms in Benin, India, and Malawi
Authors: Gwayi-Chore Marie-Claire , Aruldas Kumudha , Avokpaho Euripide , Chirambo Chawanangwa Mahebere , Saxena Malvika , Titus Angelin , Houngbégnon Parfait , Togbevi Comlanvi Innocent , Chabi Félicien , Nindi Providence , Simwanza James , Johnson Jabaselvi , Kalua Khumbo , Ibikounlé Moudachirou , Ajjampur Sitara Swarna Rao , Weiner Bryan J. , Walson Judd L. , Means Arianna Rubin 
Published: November 2024

Introduction

Large community-based public health programs, like mass drug administration (MDA), require coordination across many stakeholders. We used social network analysis (SNA) to systematically identify the network of stakeholders who influence delivery of school-based and community-wide MDA for soil-transmitted helminths (STH) in Benin, India, and Malawi and determine how network dynamics may impact implementation and scale-up across these delivery platforms.

Methods

This study was embedded within the implementation science research of the DeWorm3 Project, a hybrid clinical trial in Benin, India, &amp; Malawi testing the feasibility of STH transmission interruption via community-wide MDA. Sites developed lists of stakeholders engaged in both MDA programs and indicated stakeholders’ attitudes towards the intervention and influence over intervention delivery. We developed digital sociograms for both MDA networks by site, comparing baseline vs. endline. We descriptively compared changes over time in stakeholder attitudes and influence and key SNA measures, including centrality, centralization, and density.

Results

Across sites, we identified an expansive network of stakeholders involved in delivery of school-based (N= 139, 63, 58 vs. N=139, 162, 63) and community-wide MDA programs (N=52, 137, 54 vs. N=54, 136, 60) at baseline vs. endline in Benin, India, and Malawi, respectively. At both timepoints, a majority (&gt;70%) of stakeholders held positive attitudes towards both programs. For both programs, stakeholders with the highest degree centrality scores (i.e., the most connected individuals) were those responsible for implementation such as community drug distributors or school teachers, while those with the highest betweenness centrality scores (i.e. those who controlled resource or information flow across networks) were responsible for policy-making &amp; program leadership (e.g., NTD Program Managers). Low density scores indicated networks had poor overall connectedness due to minimal connectivity across administrative levels, while low centralization scores reflected stable networks where no single individual exhibited high control over resource flow.

Conclusion

During stages of innovation, redesign, or scale-up, analyzing the network of policymakers and implementers provides an opportunity to optimize effectiveness and efficiency of public health programs. Study findings provide useful insight for NTD policymakers and implementers in STH-endemic countries aiming to successfully interrupt STH transmission by transitioning from school-based to community-wide MDA.