Evidence map›Paper›PMID 39914876›Full record

ArticleBMJ global health2025

Decision-making under epistemic, strategic and institutional uncertainty during COVID-19: findings from a six-country empirical study.

Sumegha Asthana, Sanjana Mukherjee, Alexandra L Phelan, Ibrahim B Gobir, J J Woo, Clare Wenham, Mohammad Mushtuq Husain, Tahmina Shirin, Nevashan Govender, Mohannad Al Nsour and 6 more

Abstract read
In one paragraph

Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Sumegha AsthanaCenter for Global Health Science and Security, Georgetown University, Washington, DC, USA sa1869@georgetown.edu.ORCID http://orcid.org/0000-0003-4186-2136
Sanjana MukherjeeO'Neill Institute for National and Global Health Law, Georgetown University, Washington, DC, USA.ORCID http://orcid.org/0000-0002-6039-9506
Alexandra L PhelanDepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Ibrahim B GobirGeorgetown Global Health LTD/GTE Nigeria, Abuja, Nigeria.
J J WooLee Kuan Yew School of Public Policy, National University of Singapore, Singapore.
Clare WenhamDepartment of Health Policy, The London School of Economics and Political Science, London, UK.ORCID http://orcid.org/0000-0001-5378-3203
Mohammad Mushtuq HusainIndependent consultant, Dhaka, Bangladesh.
Tahmina ShirinInstitute of Epidemiology Disease Control and Research, Dhaka, Bangladesh.
Nevashan GovenderDivision of Public Health Surveillance and Response, National Institute for Communicable Diseases, Johannesburg, South Africa.
Mohannad Al NsourEastern Mediterranean Public Health Network, Amman, Jordan.
Winifred UkponuGeorgetown Global Health LTD/GTE Nigeria, Abuja, Nigeria.
Adachioma Chinonso IhuezeIndependent consultant, Cambridge, Ontario, Canada.
Roujia LinCenter for Global Health Science and Security, Georgetown University, Washington, DC, USA.ORCID http://orcid.org/0009-0007-9728-9427
Sumit AsthanaIndependent consultant, Washington, DC, USA.
Renee Vongai MutareCenter for Global Health Science and Security, Georgetown University, Washington, DC, USA.
Claire J StandleyCenter for Global Health Science and Security, Georgetown University, Washington, DC, USA.ORCID http://orcid.org/0000-0002-4291-9723

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUncertainty is defined as limited knowledge or lack of predictability about past, present or future events. The COVID-19 pandemic management was significantly impacted by uncertainty, as the gaps between existing information and the necessary knowledge hindered decision-making. Current uncertainty literature primarily focuses on natural disasters, leaving a gap in understanding decision-making under uncertainty in times of public health emergencies. Analysing strategies for making decisions under uncertainty during the pandemic is crucial for future pandemic preparedness.

methodsUsing a comparative research design, we study the strategies governments used to make decisions under uncertainty during the COVID-19 pandemic. We collected data through desk reviews, stakeholder interviews and focus group discussions with stakeholders from government, academia and civil society from six purposefully selected countries: Nigeria, Singapore, South Africa, Bangladesh, Jordan and the UK.

resultsRegardless of political, geographic and economic context, all six countries adopted common strategies to make decisions under three types of uncertainties. Decision-making under epistemic uncertainty involved seeking expert advice and collecting evidence from other countries and international organisations. Decision-making under strategic uncertainty involved coordination, collaboration and communication. Decision-making under institutional uncertainty involved using or adapting pre-existing experiences, structures and relationships and establishing new institutions and processes.

conclusionsWe contribute to the theory and practice of public health crisis decision-making by presenting a unified national-level applied decision-making framework for events involving uncertainty. We provide practical guidance for approaches to enhance decision-making in future health crises that could also be used for other emergencies.

Indexed as

COVID-19Decision MakingBangladeshEmpirical ResearchFocus GroupsHumansJordanNigeriaPandemicsSARS-CoV-2South AfricaUncertaintyUnited KingdomCOVID-19decision makingglobal healthhealth policyqualitative study

Identifiers

PMID39914876
PMCPMC11800209

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.