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

Authors :
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
Source :
BMJ Global Health, Vol 5, Iss 12 (2020)
Publication Year :
2020
Publisher :
BMJ Publishing Group, 2020.

Abstract

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.

Details

Language :
English
ISSN :
20597908
Volume :
5
Issue :
12
Database :
Directory of Open Access Journals
Journal :
BMJ Global Health
Publication Type :
Academic Journal
Accession number :
edsdoj.2eff4a88992d40f3a47ac8ba5b120e29
Document Type :
article
Full Text :
https://doi.org/10.1136/bmjgh-2020-003126