ArticleBulletin of the World Health Organization2019
Evaluation of the early warning, alert and response system after Cyclone Winston, Fiji, 2016.
Article in Bulletin of the World Health Organization, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Web-Based Apps for Responding to Acute Infectious Disease Outbreaks in the Community: Systematic Review.JMIR public health and surveillance · 2021Pooled it
- Seasonal and meteorological determinants of district level acute watery diarrhea incidence in Fiji, 2016-2023: a time-series analysis.BMC public health · 2026Article
- Evaluation of the implementation of the EWARS Mobile epidemiological surveillance tool in Sudanese refugee camps in Eastern Chad: a retrospective and population-based surveillance study.Frontiers in epidemiology · 2025Article
- Software Tools to Facilitate Community-Based Surveillance: A Scoping Review.Global health, science and practice · 2023Article
- Arboviral Disease Outbreaks in the Pacific Islands Countries and Areas, 2014 to 2020: A Systematic Literature and Document Review.Pathogens (Basel, Switzerland) · 2022Review
- Could Emergency Diseases Surveillance Systems Be Transitioned to Routine Surveillance Systems? A Proposed Transition Strategy for Early Warning, Alert, and Response Network.Frontiers in medicine · 2022Review
- Expert perspectives on priorities for supporting health security in the Pacific region through health systems strengthening.PLOS global public health · 2022Article
- Novel Approach to Support Rapid Data Collection, Management, and Visualization During the COVID-19 Outbreak Response in the World Health Organization African Region: Development of a Data Summarization and Visualization Tool.JMIR public health and surveillance · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
objectiveTo 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.
methodsImmediately 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.
findingsIndicator-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.
conclusionIn Fiji, EWARS in a Box was effective in strengthening disease surveillance during a national emergency and was well regarded by users.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.