| Summary: | Background: Community Health Global Network (CHGN) is a collaborative network, founded to strengthen collaboration between community-based health programs - many of which are faith based initiatives. It seeks to address this in two ways: through its global network of players in community health and in the formation of “Clusters.” CHGN Clusters are networks of community health programmes and individuals in specific geographical locations. This case report outlines the formation of the Kenya Cluster. Aims: To describe the steps in the formation of the Kenya Cluster and to outline the primary outcomes and potential impact of the network. To discuss how learning from the Kenya Cluster may assist other established Clusters and the initiation of new Clusters. Method: Information for this case report was gained from meetings and consultations with various individuals including leaders and members of the Kenya Cluster, other national community health experts, CHGN International staff and advisors to CHGN Uttarakhand Cluster in India. In addition, information was gained from personal observation during in-country field work. Results: The Kenya Cluster is emerging as a platform for community health programs to connect and network. These connections have led to transfer of information through stories, best practice, training, contacts and opportunities amongst Cluster members. The Cluster has also established links with government and multilaterals enabling greater access to support at the community level. Conclusions: There is early indication that the formation of the Kenya Cluster is supportive of the Cluster model as a unique way of strengthening collaboration between community health programs. Clusters have the potential to improve the link between faith-inspired initiatives and secular and multilateral development organisations. Lessons from the Kenya Cluster can progress the development of other Clusters. Further evaluation will be conducted to assess the impact of the Kenya Cluster and the overall impact of the Cluster approach.
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