dc.contributor.author |
Jayasekara, R |
|
dc.contributor.author |
Siriwardana, C |
|
dc.contributor.author |
Amaratunga, D |
|
dc.contributor.author |
Haigh, R |
|
dc.date.accessioned |
2023-06-23T07:16:18Z |
|
dc.date.available |
2023-06-23T07:16:18Z |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Jayasekara, R., Siriwardana, C., Amaratunga, D., & Haigh, R. (2022). Evaluating the network of stakeholders in Multi-Hazard Early Warning Systems for multiple hazards amidst biological outbreaks: Sri Lanka as a case in point. Progress in Disaster Science, 14, 100228. https://doi.org/10.1016/j.pdisas.2022.100228 |
en_US |
dc.identifier.issn |
2590-0617 |
en_US |
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/21150 |
|
dc.description.abstract |
Synergized impacts of simultaneous hazards amidst COVID-19 have called for the need for highly collaborative multi-sectoral approaches for disaster preparedness planning. In such a context, this study aims at evaluating the network of stakeholders in the National Early Warning System of Sri Lanka during preparedness planning. Social Network Analysis was used to visualise the network of stakeholders for selected hazard scenarios. Furthermore, a series of key informant interviews were conducted focusing on disaster preparedness planning during the recent multiple hazard scenarios. The findings highlight the need for a framework to guide the stakeholder coordination in preparedness planning for multiple hazards. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
Elsevier |
en_US |
dc.subject |
Multi-Hazard |
en_US |
dc.subject |
Multi-Hazard Early Warning |
en_US |
dc.subject |
Simultaneous hazards |
en_US |
dc.subject |
COVID-19 |
en_US |
dc.subject |
Multi-sectoral approach |
en_US |
dc.subject |
Systemic risk |
en_US |
dc.title |
Evaluating the network of stakeholders in Multi-Hazard Early Warning Systems for multiple hazards amidst biological outbreaks: Sri Lanka as a case in point |
en_US |
dc.type |
Article-Full-text |
en_US |
dc.identifier.year |
2022 |
en_US |
dc.identifier.journal |
Progress in Disaster Science |
en_US |
dc.identifier.volume |
14 |
en_US |
dc.identifier.database |
ScienceDirect |
en_US |
dc.identifier.pgnos |
100228[9p.] |
en_US |
dc.identifier.doi |
https://doi.org/10.1016/j.pdisas.2022.100228 |
en_US |