Cited by 34Data-Driven Disease SurveillanceDisaster Response and ManagementCOVID-19 epidemiological studies

Enhancing Situational Awareness to Prevent Infectious Disease Outbreaks from Becoming Catastrophic

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Lipsitch, Marc, Santillana, Mauricio·2019·Current Topics in Microbiology and Immunology

Abstract

Catastrophic epidemics, if they occur, will very likely start from localized and far smaller (non-catastrophic) outbreaks that grow into much greater threats. One key bulwark against this outcome is the ability of governments and the health sector more generally to make informed decisions about control measures based on accurate understanding of the current and future extent of the outbreak. Situation reporting is the activity of periodically summarizing the state of the outbreak in a (usually) public way. We delineate key classes of decisions whose quality depends on high-quality situation reporting, key quantities for which estimates are needed to inform these decisions, and the traditional and novel sources of data that can aid in estimating these quantities. We emphasize the important role of situation reports as providing public, shared planning assumptions that allow decision makers to harmonize the response while making explicit the uncertainties that underlie the scenarios outlined for planning. In this era of multiple data sources and complex factors informing the interpretation of these data sources, we describe four principles for situation reporting: (1) Situation reporting should be thematic, concentrating on essential areas of evidence needed for decisions. (2) Situation reports should adduce evidence from multiple sources to address each area of evidence, along with expert assessments of key parameters. (3) Situation reports should acknowledge uncertainty and attempt to estimate its magnitude for each assessment. (4) Situation reports should contain carefully curated visualizations along with text and tables.

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  • The patterns of mortality and testing observed across Greater Santiago are partially explained by an early failure of health care systems in informing the population with sufficient situational awareness about the real magnitude of the threat.

    “This early underreporting signal suggests that the patterns of mortality and testing observed across Greater Santiago are partially explained by an early failure of health care systems in informing the population with sufficient situational awareness about the real magnitude of the threat (15).”

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References 57 · Cited by 34

Research works printed but not linked: 1

  1. Bastos L, Economou T, Gomes M, Villela D, Bailey T, Codeço C. Modelling reporting delays for disease surveillance data [Internet]. arXiv [stat.AP]. 2017. Available from: http://arxiv.org/abs/1709.09150 · arXiv

Authors
Lipsitch, M., & Santillana, M.
Affiliations
  • Harvard University (US)
  • Boston Children's Hospital (US)
Corresponding author
Lipsitch, Marc
Venue
Current Topics in Microbiology and Immunology
Published
2019
Volume
424
Pages
59-74
ISSN
  • 0070-217X (ISSN-L)
  • 2196-9965
OpenAlex
W2958944865
Cited by
34
References
57
Citations by year
2026: 3 · 2025: 4 · 2024: 4 · 2023: 4 · 2022: 6 · 2021: 6 · 2020: 7
FWCI
17.76
Type
book chapter
Language
en
Open access
Locations
  • Current topics in microbiology and immunology (publishedVersion)
  • PubMed (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
Funders
  • National Institutes of Health
  • National Institute of General Medical Sciences (U54GM088558, R01GM130668)
Topics
  • Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
  • Health Sciences › Health Professions › Emergency Medical Services › Disaster Response and Management
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
Keywords
infectious disease outbreaks, uncertainty estimation, multi-source data, expert opinion, outbreak surveillance, public health planning, data visualization
MeSH terms
Awareness, Disaster Planning, Disasters, Disease Outbreaks, Humans, Epidemiological Monitoring

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