EpiNurse, Health Monitoring by Local Nurses on Nepal Earth Quake 2015

• Main Authors: Kanbara, Sakiko, Pandey, Apsara, Estuar, Ma. Regina Justina E, Lee, Hyeon Ju, Miyazaki, Hiroyuki
• Format: text
• Published: Archīum Ateneo 2020
• Subjects: Participatory monitoring; Information and communications technology; Nursing; Health security; Disaster risk reduction; Computer Sciences; Databases and Information Systems; Medicine and Health Sciences
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/332; https://link.springer.com/chapter/10.1007/978-981-15-0924-7_15#auth-Sakiko-Kanbara
• Institution: Ateneo De Manila University

The name, EpiNurse, refers to local nurses who perform epidemiological surveillance and care to ensure human security in and communicate with health authorities on the health status of communities. They collect and report epidemiological information by using easy-to-use technology in communities in which access to health information of the populace is hindered by catastrophic accidents or other geo-/socio-political reasons. EpiNurse Nepal Project (August 2015–April 2016) carried out epidemiological surveillances at 24 camps in 9 districts after the 2015 Nepal earthquake. By applying ICT and questionnaire, EpiNurse member nurses collected shelter-related data and information, such as location and timestamps, and geo-tagged photos. Identification of typical health behavior patterns and comparative information about differences between community and temporary shelters provided insights into the health security assessment. This initiative experiments how nurse should collect and deliver the health emergency information on their own local culture, lifestyle, and perceptions. The potential of EpiNurse concept lies not only in producing innovative research outcomes by improving or optimizing existing ICT application in health sector, but also in promoting research knowledge and exchange of ideas regarding social issues and challenges in the field of health emergency and community resilience. The most critical challenge in practice relates to collecting and storing data, which later would have been generated into reasonable health security index information to be used for predicting the likelihood of occurrence of health emergency events. It is necessary to apply human behavior modeling using geospatial technology in order to create data transferring modules for first responders and civilian populations regarding DRR and behaviors.