ArticleInfluenza and other respiratory viruses2020
Implementing the World Health Organization Pandemic Influenza Severity Assessment framework-Singapore's experience.
Article in Influenza and other respiratory viruses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Assessment of Influenza Severity in Bhutan by Using WHO Framework Pandemic Influenza Severity Assessment (PISA): An Implementation Research Study.Influenza and other respiratory viruses · 2025Article
- De-escalation strategies for non-pharmaceutical interventions following infectious disease outbreaks: a rapid review and a proposed dynamic de-escalation framework.Globalization and health · 2021Review
- A novel data-driven methodology for influenza outbreak detection and prediction.Scientific reports · 2021Article
- Implementing the World Health Organization Pandemic Influenza Severity Assessment framework-Singapore's experience.Influenza and other respiratory viruses · 2020Article
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Abstract
backgroundWe report our experience in evaluating the severity of local influenza epidemics using the World Health Organization Pandemic Influenza Severity Assessment framework.
methodsWe assessed the severity of influenza by monitoring indicators of influenza transmissibility, seriousness of disease and impact on healthcare resource utilisation. Indicators were described by various parameters collected weekly from eight government hospitals, 20 government and 30 private primary care clinics, and the national public health laboratory. Transmissibility and seriousness of disease indicators were each represented by multiple parameters, and alert thresholds were set at the 70th and 90th percentile of a parameter's past 2-year surveillance data. We derived a collective measure for each indicator using the average percentile rank of the related parameters. Alert thresholds for the single impact parameter were set at predefined values and evaluated for its sensitivity, specificity and positive predictive value.
resultsFor the transmissibility and seriousness of disease parameters, calculation of the percentile rank was simple and independent of a parameter's underlying distribution. For the impact parameter, predefined alert thresholds had high sensitivity and specificity (>80%) but low positive predictive value (15%-30%). Assessment scales were used to qualitatively classify the activity of an indicator as low, moderate or high together with a confidence level.
conclusionWe applied different methods for threshold setting depending on the attributes of each parameter and indicator. For indicators represented by multiple parameters, an aggregated assessment of the indicator's level of activity and confidence level of the assessment was needed for effective reporting.
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