Explaining covid-19 performance: what factors might predict national responses?

Fran Baum; Toby Freeman; Connie Musolino; Mimi Abramovitz; Wim De Ceukelaire; Joanne Flavel; Sharon Friel; Camila Giugliani; Philippa Howden-Chapman; Nguyen Thanh Huong; Leslie London; Martin McKee; Jennie Popay; Hani Serag; Eugenio Villar

doi:10.1136/bmj.n91

Explaining covid-19 performance: what factors might predict national responses?

BMJ. 2021 Jan 28:372:n91. doi: 10.1136/bmj.n91.

Authors

Affiliations

¹ Flinders University College of Medicine and Public Health, Southgate Institute for Health, Society and Equity, Australia.
² City University of New York, Silberman School of Social Work, USA.
³ Third World Health Aid, Belgium.
⁴ Australian National University, Menzies Centre for Health Governance, School of Regulation and Global Governance (RegNet), Australia.
⁵ Universidade Federal do Rio Grande do Sul, Faculdade de Medicina, Brazil.
⁶ University of Otago Wellington, Department of Public Health, New Zealand.
⁷ Hanoi University of Public Health, Vietnam.
⁸ University of Cape Town, School of Public Health and Family, South Africa.
⁹ London School of Hygiene and Tropical Medicine, ECOHOST, UK.
¹⁰ Lancaster University Division of Health Research, Institute for Health Research, UK.
¹¹ Universidad Peruana Cayetano Heredio, Peru.

PMID: 33509924
PMCID: PMC7842256
DOI: 10.1136/bmj.n91

Abstract

Correspondence to: F Baum fran.baum@flinders.edu.au

Fran Baum and colleagues discuss the factors that affected prediction of the success of national responses to covid-19 and will influence future pandemic preparedness

MeSH terms

COVID-19 / diagnosis*
COVID-19 / epidemiology
COVID-19 / prevention & control
COVID-19 / virology
Civil Defense / statistics & numerical data
Civil Defense / trends
Cost of Illness
Disease Outbreaks / prevention & control
Disease Outbreaks / statistics & numerical data
Forecasting / methods
Global Health / economics
Global Health / standards*
Global Health / statistics & numerical data
Humans
Politics
Public Health / standards*
Public Health / statistics & numerical data
Risk Factors
SARS-CoV-2 / genetics*