Key data for outbreak evaluation: building on the Ebola experience

Anne Cori, Christl A Donnelly, Ilaria Dorigatti, Neil M Ferguson, Christophe Fraser, Tini Garske, Thibaut Jombart, Gemma Nedjati-Gilani, Pierre Nouvellet, Steven Riley, Maria D Van Kerkhove, Harriet Mills, Isobel M Blake

Research output: Contribution to journalArticle (Academic Journal)peer-review

26 Citations (Scopus)
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Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical to guide an effective public health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained in the West African Ebola epidemic and prior emerging infectious disease outbreaks to set out a checklist of data needed to: 1) quantify severity and transmissibility; 2) characterise heterogeneities in transmission and their determinants; and 3) assess the effectiveness of different interventions. We differentiate data needs into individual-level data (e.g. a detailed list of reported cases), exposure data (e.g. identifying where / how cases may have been infected) and population level data (e.g. size/demographics of the population(s) affected and when/where interventions were implemented). A remarkable amount of individual-level and exposure data was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However, gaps in population-level data (particularly around which interventions were applied when and where) posed challenges to the assessment of (3). Here we highlight recurrent data issues, give practical suggestions for addressing these issues and discuss priorities for improvements in data collection in future outbreaks.
Original languageEnglish
Article number20160371
Number of pages14
JournalPhilosophical Transactions B: Biological Sciences
Issue number1721
Early online date10 Apr 2017
Publication statusPublished - 26 May 2017


  • West African Ebola epidemic
  • epidemic
  • mathematical modelling
  • outbreak response
  • data
  • public health

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