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

Abstract

Background: The 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.

Methods: We 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.

Findings: We 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.

Interpretation: About 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.

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

Figure 1

Global proportion of individuals with at least one underlying condition, by age and sex, and global prevalence of each underlying condition by age Grey lines represent individual countries and show variation around the global estimates (black lines). We excluded latent tuberculosis from our analysis but include it here to show the extent of overall tuberculosis that was excluded.

Figure 2

Number and percentage of population at increased risk and high risk of severe COVID-19 by age and region; and distribution of underlying conditions by age and region Each row of graphs presents data for a UN geographical region. The first and second columns show the number of individuals and percentage share of the population, respectively, in each risk group by age, with those at high risk divided into females and males. The third column shows the distribution of the 11 underlying conditions by age, including multimorbidity as a separate category. *Excludes latent infections.

Figure 3

Proportion of population at increased risk and high risk of severe COVID-19 by country and region The total length of each bar represents the share of the population at increased risk (ie, those with at least one condition listed as at increased risk in current guidelines); this excludes individuals considered to be at increased risk by virtue of their age alone. The darker bars represent the share of the population at high risk (ie, those that would require hospital admission if infected), with thin bars representing uncertainty intervals. Here, the population at risk is not age standardised. Thus, differences between countries are driven by differences in the population structure, as well as differences in risk at equivalent ages. This is appropriate when calculating the number and percentage of country populations that might need to be shielded or vaccinated. Another version of this figure shows the age-standardised population at risk (assuming the same population structure in each country), and thus allows more direct comparison of the risk at equivalent ages in different countries (appendix p 16).

Figure 3

Proportion of population at increased risk and high risk of severe COVID-19 by country and region The total length of each bar represents the share of the population at increased risk (ie, those with at least one condition listed as at increased risk in current guidelines); this excludes individuals considered to be at increased risk by virtue of their age alone. The darker bars represent the share of the population at high risk (ie, those that would require hospital admission if infected), with thin bars representing uncertainty intervals. Here, the population at risk is not age standardised. Thus, differences between countries are driven by differences in the population structure, as well as differences in risk at equivalent ages. This is appropriate when calculating the number and percentage of country populations that might need to be shielded or vaccinated. Another version of this figure shows the age-standardised population at risk (assuming the same population structure in each country), and thus allows more direct comparison of the risk at equivalent ages in different countries (appendix p 16).

Figure 4

Proportion of population at increased risk and high risk of severe COVID-19 by country For age-standardised estimates, see appendix (p 16).