BMJ Global Health (Dec 2020)

Modelling the COVID-19 pandemic in context: an international participatory approach

  • Ali Mirzazadeh,
  • Hamid Sharifi,
  • Proochista Ariana,
  • Sunil Pokharel,
  • Siyu Chen,
  • Ricardo Aguas,
  • Sudhir Venkatesan,
  • Lisa White,
  • Nathaniel Hupert,
  • Rima Shretta,
  • Wirichada Pan-Ngum,
  • Olivier Celhay,
  • Ainura Moldokmatova,
  • Fatima Arifi,
  • Keyrellous Adib,
  • Mohammad Nadir Sahak,
  • Caroline Franco,
  • Renato Coutinho,
  • Penny Hancock,
  • Roberto A. Kraenkel,
  • Sompob Saralamba,
  • Nantasit Luangasanatip,
  • Sheetal Prakash Silal,
  • Jared Norman,
  • Rachel Hounsell,
  • Sai Tun,
  • Yu Nandar Aung,
  • A Bakare Emmanuel,
  • Biniam Getachew,
  • Sandra Adele,
  • Semeeh A. Omoleke,
  • Rashid U Zaman,
  • Nicholas Letchford,
  • Daniel M. Parker,
  • Dipti Lata,
  • Shwe Sin Kyaw,
  • Inke N D Lubis,
  • Ivana Alona,
  • John Robert C. Medina,
  • Chris Erwin G. Mercado,
  • Sana Eybpoosh,
  • Ibrahim Mamadu,
  • Manar Marzouk,
  • Nicole Feune de Colombi,
  • Lorena Suárez-Idueta,
  • Francisco Obando,
  • Luzia Freitas,
  • Michael G. Klein,
  • David Scales,
  • Dooronbekova Aizhan,
  • Chynar Zhumalieva,
  • Aida Estebesova,
  • Aibek Mukambetov,
  • Shamil Ibragimov,
  • Aisuluu Kubatova,
  • Phetsavanh Chanthavialy,
  • Amel H. Salim,
  • KC Sarin,
  • Priyanka Shrestha,
  • Sayed Ataullah Saeedzai,
  • Jenny Hsieh,
  • Mick Soukavong,
  • Yuki Yunanda,
  • Handoyo Harsono,
  • Mahnaz Hossain Fariba,
  • Viviana Mabombo,
  • Nicole Advani,
  • Nusrat Jabin,
  • Reshania Naidoo,
  • Parinda Wattanasri,
  • Amen-Patrick Nwosu,
  • Sopuruchukwu Obiesie

DOI
https://doi.org/10.1136/bmjgh-2020-003126
Journal volume & issue
Vol. 5, no. 12

Abstract

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The SARS-CoV-2 pandemic has had an unprecedented impact on multiple levels of society. Not only has the pandemic completely overwhelmed some health systems but it has also changed how scientific evidence is shared and increased the pace at which such evidence is published and consumed, by scientists, policymakers and the wider public. More significantly, the pandemic has created tremendous challenges for decision-makers, who have had to implement highly disruptive containment measures with very little empirical scientific evidence to support their decision-making process. Given this lack of data, predictive mathematical models have played an increasingly prominent role. In high-income countries, there is a long-standing history of established research groups advising policymakers, whereas a general lack of translational capacity has meant that mathematical models frequently remain inaccessible to policymakers in low-income and middle-income countries. Here, we describe a participatory approach to modelling that aims to circumvent this gap. Our approach involved the creation of an international group of infectious disease modellers and other public health experts, which culminated in the establishment of the COVID-19 Modelling (CoMo) Consortium. Here, we describe how the consortium was formed, the way it functions, the mathematical model used and, crucially, the high degree of engagement fostered between CoMo Consortium members and their respective local policymakers and ministries of health.