Journal of Population Sciences
Table 2 Details of the presented approaches for excess mortality estimation during the COVID-19 pandemic
Study | Geography | Demographics | Data | Method | Main Results | Consideration of Long-term Trends in Mortality | Quantification of Stochasticity | Dealing with Correlations among time series |
|---|---|---|---|---|---|---|---|---|
Magnani et al. | 4,433 Italian municipalities | No sex distinction Two age groups | Daily death numbers from January 1st to April 15th, 2015-2020 Yearly population estimates for January 1st, 2015–2019 Daily Death numbers attributed to COVID-19 by lab testing in 2020 | Mean mortality rates by calendar days for 2015–2020 are computed Daily mortality rate estimates in 2020 are computed and assumed to follow a Poisson distribution Relative risk estimates with 95% CIs are computed relative to the baseline mean rates for 2015–2019 | Statistically significant increase in mortality rates between early-March and mid-April, 2020 in Italy Only significant for North and parts of Central Italy Only significant for persons above age 59, except for Lombardia (both age groups significant) | None | Poisson assumption for observed deaths in 2020 | None |
Michelozzi et al. | 19 Italian cities | Two sexes Four age groups | Daily death numbers from January 1st, 2015 to April 18th, 2020 | Mean death numbers by calendar days for 2015–2020 are computed Daily death numbers implicitly assumed to be Gaussian, 95% PIs of baseline data are computed Comparison of observed death numbers with PIs | Statistically significant excess mortality in Italy between mid-March and mid-April, 2020 In the North, statistically significant excess mortality for males for all investigated age groups (age 15 and older), for females for age groups 65 and older In the Center and South only statistically significant excess mortality for very old females (above age 84) and males (above age 74) | None | Prediction assumed Gaussian with a standard deviation of past five years | None |
NYC DOHMH | New York City | None | Daily death numbers with a lab-confirmed COVID-19 infection in 2020 | Daily death numbers are predicted by OLS fit of the Serfling model to daily death numbers of baseline period Comparison of observed with expected daily death numbers Comparison of COVID-19 associated deaths with overall excess mortality estimate | Excess mortality after March 10th, with a large share of confirmed or suspected COVID-19 cases | Serfling model | None | None |
EUROMOMO | 22 EU-28 countries 2 German federal states | No sex distinction Seven age groups | Weekly all-cause death numbers since week 1, 2016 | Poisson model fit to baseline data 95% PIs derived from the GLM model Comparison of observed weekly death numbers to 95% PIs | Statistically significant excess mortality in all countries for age groups 45+ between circa calendar weeks 11 and 19, 2020; death numbers above threshold in calendar weeks 13–15 for persons aged 15–44 years; no significant excess mortality among children Significant excess mortality observed in Belgium, France, Ireland, Italy, Netherlands, Portugal, Spain, Sweden, Switzerland, and the UK No significant excess mortality in Austria, Denmark, Estonia, Finland, Greece, Hungary, Luxembourg, Malta, Norway, and the two German federal states | Poisson model | PIs from the GLM model | None |
Ours | 19 countries in Europe and the Middle East | Two sexes Four age groups | Weekly all-cause mortality rate estimates since week 2, 2000 by HMD Daily official COVID-19 associated deaths in 2020 by ECDC | Principal component analysis on all 152 time series of logit mortality rates simultaneously OLS fit of logistic SARIMA model to past course of first PC Monte Carlo simulation of weekly forecasts of all PCs Retransformation of simulations to simulations of age-sex- and country-specific mortality rates Multiplication of simulations with population estimates for 2020 Derivation of nonparametric PIs for forecasts of death numbers Comparison of observed all-cause and COVID-19 associated weekly death numbers with PIs of forecasts | No significant excess mortality for persons below age 65, slightly significant excess mortality among females aged 65-74 years, statistically significant excess mortality among males above age 64 and females above age 74 years in calendar weeks 13–16, 2020 Statistically significant overall excess mortality only observable for Belgium, France, Netherlands, Scotland, Sweden, Poland, and Spain; results for Switzerland inconclusive; no significant excess mortality in Austria, Estonia, Finland, Hungary, Israel, Latvia, Lithuania, Norway, Portugal, Slovakia, and Slovenia | Logistic trend fitted to first principal component time series | SARIMA models and Monte Carlo simulation of principal component time series with nuisance derived from 20 years of past data, leading to stochastic estimates of all mortality rate series | Correlations among age groups and countries completely covered by principal component analysis |