Meru Sheel1, Julie Collins1, Mike Kama2, Devina Nand3, Daniel Faktaufon2, Josaia Samuela3, Viema Biaukula4, Christopher Haskew5, James Flint6, Katrina Roper1, Angela Merianos4, Martyn D Kirk1, Eric Nilles4. 1. National Centre for Epidemiology and Population Health, Australian National University, Building 62, Mills Road, Canberra, ACT 2610, Australia. 2. Fiji Centre for Communicable Disease Control, Ministry of Health and Medical Services, Suva, Fiji. 3. Ministry of Health and Medical Services, Suva, Fiji. 4. Division of Pacific Technical Support, World Health Organization, Suva, Fiji. 5. Health Emergencies Programme, World Health Organization, Geneva, Switzerland. 6. Hunter New England Population Health, Wallsend, Australia.
Abstract
OBJECTIVE: To assess the performance of an early warning, alert and response system (EWARS) developed by the World Health Organization (WHO) - EWARS in a Box - that was used to detect and control disease outbreaks after Cyclone Winston caused destruction in Fiji on 20 February 2016. METHODS: Immediately after the cyclone, Fiji's Ministry of Health and Medical Services, supported by WHO, started to implement EWARS in a Box, which is a smartphone-based, automated, early warning surveillance system for rapid deployment during health emergencies. Both indicator-based and event-based surveillance were employed. The performance of the system between 7 March and 29 May 2016 was evaluated. Users' experience with the system was assessed in interviews using a semi-structured questionnaire and by a cross-sectional survey. The system's performance was assessed using data from the EWARS database. FINDINGS: Indicator-based surveillance recorded 34 113 cases of the nine syndromes under surveillance among 326 861 consultations. Three confirmed outbreaks were detected, and no large outbreak was missed. Users were satisfied with the performance of EWARS and judged it useful for timely monitoring of disease trends and outbreak detection. The system was simple, stable and flexible and could be rapidly deployed during a health emergency. The automated collation, analysis and dissemination of data reduced the burden on surveillance teams, saved human resources, minimized human error and ensured teams could focus on public health responses. CONCLUSION: In Fiji, EWARS in a Box was effective in strengthening disease surveillance during a national emergency and was well regarded by users.
OBJECTIVE: To assess the performance of an early warning, alert and response system (EWARS) developed by the World Health Organization (WHO) - EWARS in a Box - that was used to detect and control disease outbreaks after Cyclone Winston caused destruction in Fiji on 20 February 2016. METHODS: Immediately after the cyclone, Fiji's Ministry of Health and Medical Services, supported by WHO, started to implement EWARS in a Box, which is a smartphone-based, automated, early warning surveillance system for rapid deployment during health emergencies. Both indicator-based and event-based surveillance were employed. The performance of the system between 7 March and 29 May 2016 was evaluated. Users' experience with the system was assessed in interviews using a semi-structured questionnaire and by a cross-sectional survey. The system's performance was assessed using data from the EWARS database. FINDINGS: Indicator-based surveillance recorded 34 113 cases of the nine syndromes under surveillance among 326 861 consultations. Three confirmed outbreaks were detected, and no large outbreak was missed. Users were satisfied with the performance of EWARS and judged it useful for timely monitoring of disease trends and outbreak detection. The system was simple, stable and flexible and could be rapidly deployed during a health emergency. The automated collation, analysis and dissemination of data reduced the burden on surveillance teams, saved human resources, minimized human error and ensured teams could focus on public health responses. CONCLUSION: In Fiji, EWARS in a Box was effective in strengthening disease surveillance during a national emergency and was well regarded by users.
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