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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
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Remote Laboratory Management: Respiratory Virus Diagnostics
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A Multi-Criteria Framework for Pandemic Response Measures.

Love Ekenberg1,2,3, Adriana Mihai3,4, Tobias Fasth2,5

  • 1International Institute for Applied Systems Analysis, IIASA, Laxenburg, Austria.

Frontiers in Public Health
|May 10, 2021
PubMed
Summary

This study proposes an integrated framework to improve decision-making for pandemic risk mitigation. It addresses uncoordinated responses and uncertainty by incorporating epidemiological and socioeconomic factors for better disaster risk reduction strategies.

Keywords:
SEIR modelsmanaging and mitigating the risk of COVID 19 pandemicmulti-criteria decision analysisparticipation and inclusionrisk governance

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Area of Science:

  • Public Health Policy
  • Disaster Risk Management
  • Epidemiology

Background:

  • COVID-19 pandemic highlighted unpreparedness and uncoordinated national responses in disaster risk reduction.
  • Limited evidence and high uncertainty allowed strategic narratives to influence public perception and policy decisions.
  • Rhapsodic decision-making processes complicated effective pandemic management.

Purpose of the Study:

  • To propose an integrated framework for decision analysis in pandemic situations.
  • To provide a policy-oriented approach for containing virus spread considering epidemiologic and socioeconomic factors.
  • To evaluate mitigation measures for catastrophic events and inform future pandemic response strategies.

Main Methods:

  • Developed an integrated framework for decision analysis under ambiguity.
  • Applied a multi-stakeholder, multi-criteria context incorporating epidemiologic estimations and socioeconomic factors.
  • Utilized a co-creative process to elicit stakeholder attitudes, perceptions, and preferences.

Main Results:

  • The framework was demonstrated using Romania as a case study for evaluating COVID-19 mitigation measures.
  • The approach facilitates structured analysis of pandemic effects and narrative production.
  • It aims to enhance response strategies for future pandemics and hazardous events.

Conclusions:

  • The proposed framework offers a more elaborated decision analysis for managing pandemics and similar crises.
  • It supports better policy development by integrating diverse factors and stakeholder input.
  • This approach improves preparedness and response strategies for future public health emergencies.