Modelling the pandemic: attuning models to their contexts

The evidence produced in mathematical models plays a key role in shaping policy decisions in pandemics. A key question is therefore how well pandemic models relate to their implementation contexts. Drawing on the cases of Ebola and influenza, we map how sociological and anthropological research cont...

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Bibliographic Details
Published in:BMJ global health Vol. 5; no. 6; p. e002914
Main Authors: Rhodes, Tim, Lancaster, Kari, Lees, Shelley, Parker, Melissa
Format: Journal Article
Language:English
Published: England BMJ Publishing Group Ltd 01.06.2020
BMJ Publishing Group LTD
BMJ Publishing Group
Subjects:
Analysis
Communicable Disease Control
Coronavirus Infections - epidemiology
Coronavirus Infections - immunology
Coronaviruses
Correspondence
COVID-19
Decision making
Disease transmission
Ebola virus
Epidemics
Global health
Health Policy
Hemorrhagic Fever, Ebola - epidemiology
Hemorrhagic Fever, Ebola - immunology
Hospitals
Humans
Immunity, Herd
Influenza
Influenza A Virus, H1N1 Subtype - physiology
Influenza A Virus, H5N1 Subtype - physiology
Influenza, Human - epidemiology
Influenza, Human - immunology
Intervention
Mathematical models
Models, Biological
Pandemics
Pneumonia, Viral - epidemiology
Pneumonia, Viral - immunology
Public health
Quarantine
Science
Sociology
Uncertainty
Virus Diseases - epidemiology
public health
ISSN:2059-7908, 2059-7908
Online Access:Get full text
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Summary:The evidence produced in mathematical models plays a key role in shaping policy decisions in pandemics. A key question is therefore how well pandemic models relate to their implementation contexts. Drawing on the cases of Ebola and influenza, we map how sociological and anthropological research contributes in the modelling of pandemics to consider lessons for COVID-19. We show how models detach from their implementation contexts through their connections with global narratives of pandemic response, and how sociological and anthropological research can help to locate models differently. This potentiates multiple models of pandemic response attuned to their emerging situations in an iterative and adaptive science. We propose a more open approach to the modelling of pandemics which envisages the model as an intervention of deliberation in situations of evolving uncertainty. This challenges the ‘business-as-usual’ of evidence-based approaches in global health by accentuating all science, within and beyond pandemics, as ‘emergent’ and ‘adaptive’.
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ISSN:2059-7908
2059-7908
DOI:10.1136/bmjgh-2020-002914