Heterogeneity in subnational mortality in the context of the COVID-19 pandemic: the case of Belgian districts in 2020.
Bayesian models
Belgium
Covid19
Mortality
Small-area
Subnational
Journal
Archives of public health = Archives belges de sante publique
ISSN: 0778-7367
Titre abrégé: Arch Public Health
Pays: England
ID NLM: 9208826
Informations de publication
Date de publication:
06 May 2022
06 May 2022
Historique:
received:
13
12
2021
accepted:
26
03
2022
entrez:
7
5
2022
pubmed:
8
5
2022
medline:
8
5
2022
Statut:
epublish
Résumé
The COVID-19 pandemic has led to major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shocks at the sub-national level, rigorously accounting for the different sources of uncertainty. Using death registration data from Belgium, we first assess change in the heterogeneity of districts' standardized mortality ratios in 2020, when compared to previous years. We then measure the shock effect of the pandemic using district-level values of life expectancy, comparing districts' observed and projected life expectancy, accounting for all sources of uncertainty (stemming from life-table construction at district level and from projection methods at country and district levels). Bayesian modelling makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts. The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial: while some districts barely show any impact, the Bruxelles-Capitale and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33-3.05) and 2.10 (95% CI:0.86-3.30) years, respectively. The year 2020 was associated with an increase in the heterogeneity of mortality levels at a subnational scale in comparison to past years, measured in terms of both standardized mortality ratios and life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results. Developing sub-national mortality estimates taking careful account of uncertainty is key to identifying which areas have been disproportionately affected.
Sections du résumé
BACKGROUND
BACKGROUND
The COVID-19 pandemic has led to major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shocks at the sub-national level, rigorously accounting for the different sources of uncertainty.
METHODS
METHODS
Using death registration data from Belgium, we first assess change in the heterogeneity of districts' standardized mortality ratios in 2020, when compared to previous years. We then measure the shock effect of the pandemic using district-level values of life expectancy, comparing districts' observed and projected life expectancy, accounting for all sources of uncertainty (stemming from life-table construction at district level and from projection methods at country and district levels). Bayesian modelling makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts.
RESULTS
RESULTS
The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial: while some districts barely show any impact, the Bruxelles-Capitale and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33-3.05) and 2.10 (95% CI:0.86-3.30) years, respectively. The year 2020 was associated with an increase in the heterogeneity of mortality levels at a subnational scale in comparison to past years, measured in terms of both standardized mortality ratios and life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results.
CONCLUSION
CONCLUSIONS
Developing sub-national mortality estimates taking careful account of uncertainty is key to identifying which areas have been disproportionately affected.
Identifiants
pubmed: 35524287
doi: 10.1186/s13690-022-00874-7
pii: 10.1186/s13690-022-00874-7
pmc: PMC9073828
doi:
Types de publication
Journal Article
Langues
eng
Pagination
130Subventions
Organisme : Fonds Sp?cial de recherche (FSR)
ID : IACS FSR19 MASQUE
Informations de copyright
© 2022. The Author(s).
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