Evidence map›Paper›PMID 32553130›Full record

ArticleThe Lancet. Global health2020

Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study.

Andrew Clark, Mark Jit, Charlotte Warren-Gash, Bruce Guthrie, Harry H X Wang, Stewart W Mercer, Colin Sanderson, Martin McKee, Christopher Troeger, Kanyin L Ong and 7 more

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 575 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
575citing papers in PubMed, 7 pooled it
155.5field-weighted citation impact, top 1% of its field
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

575 citing papers in PubMed, 7 syntheses or guidelines pooled it, 1,222 citations in OpenAlex.

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  10. Improving Hand Hygiene Behavior Using a Novel Theory-Based Intervention During the COVID-19 Pandemic.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2022
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515 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 6 institutions in 3 countries.

Andrew ClarkDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: andrew.clark@lshtm.ac.uk.
Mark JitDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Charlotte Warren-GashDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Bruce GuthrieCentre for Population Health Sciences, Usher Institute, University of Edinburgh, Edinburgh, UK.
Harry H X WangSchool of Public Health, Sun Yat-Sen University, Guangzhou, China.
Stewart W MercerCentre for Population Health Sciences, Usher Institute, University of Edinburgh, Edinburgh, UK.
Colin SandersonDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
Martin McKeeDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
Christopher TroegerDepartment for Health Metrics, University of Washington, Seattle, WA, USA.
Kanyin L OngInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Francesco ChecchiDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Pablo PerelDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Sarah JosephIAVI Human Immunology Laboratory, Imperial College London, London, UK.
Hamish P GibbsDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Amitava BanerjeeInstitute of Health Informatics, University College London, London, UK.
Rosalind M EggoDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group
London School of Hygiene & Tropical Medicine · GBUniversity of Edinburgh · GBUniversity of Washington · USImperial College London · GBSun Yat-sen University · CNUniversity College London · GB

Funding

Medical Research Council MC_PC_19065Medical Research Council MR/S003975/1Wellcome Trust 201440/Z/16/Z
6 · The paper itself

Abstract

backgroundThe risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk.

methodsWe estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as "at increased risk of severe COVID-19" in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection-hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection-hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies.

findingsWe estimated that 1·7 billion (UI 1·0-2·4) people, comprising 22% (UI 15-28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from <5% of those younger than 20 years to >66% of those aged 70 years or older). We estimated that 349 million (186-787) people (4% [3-9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from <1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3-12) of males to be at high risk compared with 3% (2-7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease.

interpretationAbout one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds.

fundingUK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research.

Indexed as

Severity of Illness IndexAdolescentAdultAgedAged, 80 and overChildChild, PreschoolChronic DiseaseCoronavirus InfectionsCOVID-19FemaleGlobal HealthHumansMaleMiddle AgedModels, Statistical

Identifiers

PMID32553130
PMCPMC7295519
OpenAlexW3034823740

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.