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From the 100 Day Mission to 100 lines of software development: how to improve early outbreak analytics

  • Carmen Tamayo Cuartero
  • , Anna C. Carnegie
  • , Zulma M. Cucunuba
  • , Anne Cori
  • , Sara M. Hollis
  • , Rolina D. Van Gaalen
  • , Amrish Y. Baidjoe
  • , Alexander F. Spina
  • , John A. Lees
  • , Simon Cauchemez
  • , Mauricio Santos
  • , Juan D. Umaña
  • , Chaoran Chen
  • , Hugo Gruson
  • , Pratik Gupte
  • , Joseph Tsui
  • , Anita A. Shah
  • , Geraldine Gomez Millan
  • , David Santiago Quevedo
  • , Neale Batra
  • Andrea Torneri, Adam J. Kucharski
  • London School of Hygiene and Tropical Medicine
  • Imperial College London
  • World Health Organization
  • National Institute of Public Health and the Environment
  • Medecins Sans Frontieres
  • Applied Epi
  • European Molecular Biology Laboratory
  • Institut Pasteur Paris
  • Universidad de los Andes Colombia
  • Swiss Federal Institute of Technology Zurich
  • Data.org
  • University of Oxford
  • UK Public Health Rapid Support Team
  • Universidad Javeriana
  • Hasselt University

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

Since the COVID-19 pandemic, considerable advances have been made to improve epidemic preparedness by accelerating diagnostics, therapeutics, and vaccine development. However, we argue that it is crucial to make equivalent efforts in the field of outbreak analytics to help ensure reliable, evidence-based decision making. To explore the challenges and key priorities in the field of outbreak analytics, the Epiverse-TRACE initiative brought together a multidisciplinary group of experts, including field epidemiologists, data scientists, academics, and software engineers from public health institutions across multiple countries. During a 3-day workshop, 40 participants discussed what the first 100 lines of code written during an outbreak should look like. The main findings from this workshop are summarised in this Viewpoint. We provide an overview of the current outbreak analytic landscape by highlighting current key challenges that should be addressed to improve the response to future public health crises. Furthermore, we propose actionable solutions to these challenges that are achievable in the short term, and longer-term strategic recommendations. This Viewpoint constitutes a call to action for experts involved in epidemic response to develop modern and robust data analytic approaches at the heart of epidemic preparedness and response.

Original languageEnglish
Pages (from-to)e161-e166
JournalThe Lancet Digital Health
Volume7
Issue number2
DOIs
StatePublished - Feb 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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