Population vulnerability to COVID-19 in Europe: a burden of disease analysis

Abstract

Background: Evidence has emerged showing that elderly people and those with pre-existing chronic health conditions may be at higher risk of developing severe health consequences from COVID-19. In Europe, this is of particular relevance with ageing populations living with non-communicable diseases, multi-morbidity and frailty. Published estimates of Years Lived with Disability (YLD) from the Global Burden of Disease (GBD) study help to characterise the extent of these effects. Our aim was to identify the countries across Europe that have populations at highest risk from COVID-19 by using estimates of population age structure and YLD for health conditions linked to severe illness from COVID-19.Methods: Population and YLD estimates from GBD 2017 were extracted for 45 countries in Europe. YLD was restricted to a list of specific health conditions associated with being at risk of developing severe consequences from COVID-19 based on guidance from the United Kingdom Government. This guidance also identified individuals aged 70 years and above as being at higher risk of developing severe health consequences. Study outcomes were defined as: (i) proportion of population aged 70 years and above; and (ii) rate of YLD for COVID-19 for vulnerable health conditions across all ages. Bivariate groupings were established for each outcome and combined to establish overall population-level vulnerability. Results:Countries with the highest proportions of elderly residents were Italy, Greece, Germany, Portugal and Finland. When assessments of population-level YLD rates for COVID-19 vulnerable health conditions were made the highest rates were observed for Bulgaria, Czech Republic, Croatia, Hungary and Bosnia and Herzegovina. A bivariate analysis indicated that the countries at high-risk across both measures of vulnerability were: Bulgaria; Portugal; Latvia; Lithuania; Greece; Germany; Estonia; and Sweden.Conclusion: Routine estimates of population structures and non-fatal burden of disease measures can be usefully combined to create composite indicators of vulnerability for rapid assessments, in this case to severe health consequences from COVID-19. Countries with available results for sub-national regions within their country, or national burden of disease studies that also use sub-national levels for burden quantifications, should consider using non-fatal burden of disease estimates to estimate geographical vulnerability to COVID-19.

Belgian COVID-19 Mortality, Excess Deaths, Number of Deaths per Million, and Infection Fatality Rates (8 March - 9 May 2020)

“…A relatively older population will lead to considerably more deaths, for constant IFR structure. As reported by Wyper et al[1], in Belgium 13.1% of the population is 70+ (the European continent extremes being Israel for 7.7% and Italy for 16.4%), among whom further 42.2% are 80+ (with extremes 31.5% in Czechia and 44.5% in France). Larger elderly fractions may have various demographic reasons.…”

“…Although DPM and IFR clearly increase with age, adjusting for age distribution of a country is of less importance when comparing European and Western countries. Despite differences in the age distribution between European countries, Canada and the US [28], most fluctuate around a proportion of 20% of the population above 65 years. The age distribution would be more important when comparing Western versus African or Asian countries.…”

“…The copyright holder for this this version posted June 20, 2020. ; https://doi.org/10.1101/2020.06.20.20136234 doi: medRxiv preprint [1], which might contribute.…”

Monitoring the psychological, social, and economic impact of the COVID‐19 pandemic in the population: Context, design and conduct of the longitudinal COVID‐19 psychological research consortium (C19PRC) study

“…(4) the ability of a country's health service to conduct widespread testing for COVID-19, to initiate and maintain a robust contacttracing system for confirmed COVID-19 cases, and to provide optimal care for individuals diagnosed with COVID-19; (5) the timing, nature and severity of "lockdown" restrictions (and the subsequent implementation of policies and procedures to "unwind" such restrictions); and (6) the public's motivation and ability to comply with the lockdown restrictions, as well as their attendance to, and engagement with, national public health initiatives enacted to prevent the spread of the virus (Hale et al, 2020, p. 31;V. J. Lee, Chiew, & Khong, 2020;Olagnier & Mogensen, 2020;Wyper et al, 2020).…”

“…Between‐country differences in COVID‐19 related outcomes, although clearly evident in the earliest surveillance studies (World Health Organisation, 2020a, 2020b), are not easily explained, and may be related to a host of macro and micro‐level factors including: (1) the size and geographical location of a country; (2) the characteristics of a country's population (e.g. age/sex/health conditions distribution); (3) the level of population density within a country; (4) the ability of a country's health service to conduct widespread testing for COVID‐19, to initiate and maintain a robust contact‐tracing system for confirmed COVID‐19 cases, and to provide optimal care for individuals diagnosed with COVID‐19; (5) the timing, nature and severity of “lockdown” restrictions (and the subsequent implementation of policies and procedures to “unwind” such restrictions); and (6) the public's motivation and ability to comply with the lockdown restrictions, as well as their attendance to, and engagement with, national public health initiatives enacted to prevent the spread of the virus (Hale et al, 2020, p. 31; V. J. Lee, Chiew, & Khong, 2020; Olagnier & Mogensen, 2020; Wyper et al, 2020).…”