Government institutional emergent issues and gaps in disaster management mechanisms for WASH: a case study of Zambia's Kanyama peri-urban area

This paper endeavours to characterise emergent issues and gaps in government institutional disaster management mechanisms for water, sanitation, and hygiene (WASH) in peri-urban areas. It is a case of Zambia's Kanyama peri-urban area and focuses on disaster management issues related to prevention, preparedness, and response. To gain an in-depth inductive perspective of emerging issues and inferred gaps, the study used a Straussian Grounded Theory approach by conducting semi-structured interviews with government institutions. Following that, the qualitative data were analysed using open and axial coding. Emergent issues and gaps with regard to mechanisms for emergency sanitation in peri-urban areas have been characterised. The characterised emergent issues and associated gaps include the following: (a) mandate and institutional policy; (b) responsiveness of authorities; (c) community engagement; and (d) stakeholder engagement. Of these emergent issues, mandate and institutional policy is the most outstanding and the critical institutions in the disaster management mechanisms generally are the disaster management and local government authorities. Inadequacies and inefficiencies in the preparedness and response by institutions is highly influenced by the centralisation of preparedness for response. Furthermore, community engagement is cardinal in the effective implementation of preparedness, prevention, and response to disaster management mechanisms in peri-urban WASH by planning authorities. HIGHLIGHTS Characterisation of emergent issues and gaps in government institutional management mechanisms. Inadequacies and inefficiencies in preparedness and response by institutions as being influenced by centralisation. The importance of community engagement in disaster management mechanisms. Interdependencies of institutions when handling disasters. The usage of the Grounded Theory when dealing with qualitative data.