Optimizing peer-led health interventions: A social network analysis approach for identifying influential fishermen in Malawi
13 affiliations
- 1Helse Nord Tuberculosis Initiative, Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi
- 2Department of Infectious Disease Epidemiology and International Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
- 3Malawi-Liverpool-Welcome Clinical Research Programme, Blantyre, Malawi
- 4Malawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi
- 5Department of Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
- 6School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
- 7Institute of Resilient Health Systems, Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- 8Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom
- 9School of Health and Wellbeing, University of Glasgow, Scotland, United Kingdom
- 10Department of Global Health, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- 11Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- 12Institute for Global Health, University College London, London, United Kingdom
- 13Africa Health Research Institute, KwaZulu-Natal, South Africa
Abstract
Social network interventions (SNIs) can leverage influential individuals within personal networks to amplify health behavior adoption and intervention diffusion. While SNIs are potentially effective in enhancing uptake of HIV prevention and other interventions, identifying optimal peer leaders remains challenging. This study assessed how social network-based approaches can improve peer leader identification compared to non-structural approaches (i.e., those that do not use network data for promoter selection). Between 8th October 2024 and 31st March 2025, we mapped the social connections among fishermen in two communities in Mangochi, Malawi. The communities had previously participated in a cluster-randomized trial (FISH), which aimed to create demand among fishermen for HIV and schistosomiasis services via peer-nominated leaders. Using Network Canvas and a photographic census, we conducted a network survey, capturing ties, support roles and interaction frequency. Whole-network maps were constructed, centrality measures and the key player problem positive (KPP-POS) algorithm were applied to identify the highest-ranking individuals as potential promoters. We compared the reach (i.e., proportion of nodes within two steps of a promoter) of peer-nominated leaders selected by FISH to these sociometric methods. We recruited 370 of 397 eligible fishermen (mean age 34.8years [SD 13.11]). Both communities exhibited sparse, low-reciprocity networks with long path lengths. One network had two dense cores, while the other featured a single core. There was no evidence of assortative mixing by education, age or village of residence. FISH trial peer leaders were not consistently central in the constructed maps. The KPP-POS algorithm identified alternative, more dispersed nodes, achieving the highest reach (66% in F001; 75% in F024) versus in-degree (58%, 67%), closeness (58%, 68%), betweenness (58%, 69%) and eigenvector (60%, 68%) promoter sets. Our findings highlight that strategically identified promoters can achieve good reach within social networks, crucial for effective public health programming in complex settings like fishing communities.
Related
- Optimizing broiler transport under hot-climate conditions: interventions across pre-transport, in-transit, and post-transport stages.
- Computational Framework for Identifying Ion Channel Mutation-Compensating Interventions
- Identifying Network Factors Driving Changes in Brain Connectivity During Aging via Stochastic Actor-Oriented Models
- Multi-scale local network structure critically impacts epidemic spread and interventions
- Optimizing an Automated Processing Pipeline for Regional Macromolecular Proton Fraction and Volume Measurements in the Brain
BibTeX
@article{mukoka2026optimizing,
title = {{Optimizing peer-led health interventions: A social network analysis approach for identifying influential fishermen in Malawi}},
author = {Madalo Mukoka and Alison Price and Marriott Nliwasa and Owen Mhango and Mphatso Mwapasa and Moses K. Kumwenda and Hussein H. Twabi and Robina Semphere and Takondwa C. Msosa and Chisomo Msefula and Augustine T. Choko and Guy Harling and Katherine Fielding},
journal = {PLOS Global Public Health},
year = {2026},
month = sep,
doi = {10.1371/journal.pgph.0007185},
url = {https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0007185},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Optimizing peer-led health interventions: A social network analysis approach for identifying influential fishermen in Malawi
AU - Madalo Mukoka
AU - Alison Price
AU - Marriott Nliwasa
AU - Owen Mhango
AU - Mphatso Mwapasa
AU - Moses K. Kumwenda
AU - Hussein H. Twabi
AU - Robina Semphere
AU - Takondwa C. Msosa
AU - Chisomo Msefula
AU - Augustine T. Choko
AU - Guy Harling
AU - Katherine Fielding
PY - 2026
DA - 2026/09/09
JO - PLOS Global Public Health
DO - 10.1371/journal.pgph.0007185
UR - https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0007185
AB - Social network interventions (SNIs) can leverage influential individuals within personal networks to amplify health behavior adoption and intervention diffusion. While SNIs are potentially effective in enhancing uptake of HIV prevention and other interventions, identifying optimal peer leaders remains challenging. This study assessed how social network-based approaches can improve peer leader identification compared to non-structural approaches (i.e., those that do not use network data for promoter selection). Between 8th October 2024 and 31st March 2025, we mapped the social connections among fishermen in two communities in Mangochi, Malawi. The communities had previously participated in a cluster-randomized trial (FISH), which aimed to create demand among fishermen for HIV and schistosomiasis services via peer-nominated leaders. Using Network Canvas and a photographic census, we conducted a network survey, capturing ties, support roles and interaction frequency. Whole-network maps were constructed, centrality measures and the key player problem positive (KPP-POS) algorithm were applied to identify the highest-ranking individuals as potential promoters. We compared the reach (i.e., proportion of nodes within two steps of a promoter) of peer-nominated leaders selected by FISH to these sociometric methods. We recruited 370 of 397 eligible fishermen (mean age 34.8years [SD 13.11]). Both communities exhibited sparse, low-reciprocity networks with long path lengths. One network had two dense cores, while the other featured a single core. There was no evidence of assortative mixing by education, age or village of residence. FISH trial peer leaders were not consistently central in the constructed maps. The KPP-POS algorithm identified alternative, more dispersed nodes, achieving the highest reach (66% in F001; 75% in F024) versus in-degree (58%, 67%), closeness (58%, 68%), betweenness (58%, 69%) and eigenvector (60%, 68%) promoter sets. Our findings highlight that strategically identified promoters can achieve good reach within social networks, crucial for effective public health programming in complex settings like fishing communities.
SN - 2767-3375
ER -