Article Text
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.
- health policy
- respiratory infections
- control strategies
- SARS
This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
Statistics from Altmetric.com
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Handling editor Seye Abimbola
Twitter @rimashretta, @_francocarol
Collaborators CoMo Consortium: Proochista Ariana; Penny Hancock; Roberto A Kraenkel; Sompob Saralamba; Nantasit Luangasanatip; Sheetal Prakash Silal; Jared Norman; Rachel Hounsell; Sai Thein Than Tun; Yu Nandar Aung; Bakare Emmanuel A; Biniam Getachew; Sandra Adele; Semeeh A Omoleke; Rashid U Zaman; Nicholas Letchford; Daniel M Parker; Sunil Pokharel; Dipti Lata; Siyu Chen; 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; Sudhir Venkatesan; Sarin K C; 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.
Contributors RA, LW and WP-N developed the CoMo model. OC developed the online model application. CF and RC consulted on the model structure. NH, RS, AMo, FA, AMi, HS, KA and MNS are early model users that helped revise the model structure and the online application. RA and LW wrote the initial manuscript draft. All authors revised the draft manuscript.
Funding RA is funded by the Bill and Melinda Gates Foundation (OPP1193472). LW is funded by the Li Ka Shing Foundation. CF is funded by grant #2017/26770-8, São Paulo Research Foundation (FAPESP). The CoMo Consortium has support from the Oxford University COVID-19 Research Response Fund (ref: 0009280). Scientific writing assistance and editorial support was provided by Adam Bodley, according to Good Publication Practice guidelines.
Map disclaimer The depiction of boundaries on this map does not imply the expression of any opinion whatsoever on the part of BMJ (or any member of its group) concerning the legal status of any country, territory, jurisdiction or area or of its authorities. This map is provided without any warranty of any kind, either express or implied.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement There are no data in this work.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.