European Journal of Epidemiology (2021) 36:213–218 
https://doi.org/10.1007/s10654-021-00717-9
COVID-19
Gender specific excess mortality in Italy during the COVID‑19 
pandemic accounting for age
Emilio A. L. Gianicolo1,2  · Antonello Russo3 · Britta Büchler1 · Katherine Taylor1  · Andreas Stang4,5  · 
Maria Blettner1
Received: 13 October 2020 / Accepted: 4 January 2021 / Published online: 25 January 2021 
© The Author(s) 2021
Abstract
Since the beginning of the COVID-19 pandemic, data have been accumulated to examine excess mortality in the first half of 
2020. Mortality in the preceding year or years is used to calculate the expected number of deaths, which is then compared 
with the actual number of deaths in 2020. We calculated weekly age- and sex-specific mortality rates for 93.1% of the Ital-
ian municipalities for the years 2015–2019 and for the first 26 weeks in 2020. We assumed the mortality experience during 
2015–2019 as the reference period to calculate standardised mortality ratios. Furthermore, in order to compare the mortality 
experience of males and females, we calculated sex- and age- specific weekly direct standardised mortality rates and dif-
ferences between the observed and expected number of deaths. We observed considerable changes in the demographics in 
the Italian population between the years 2015 and 2020, particularly among people 60 years and older and among males. 
The population is aging and the proportion of elderly males has increased, which was not reflected adequately in previous 
estimates of excess mortality. Standardized excess mortality results show that in Italy between the 8th and 26th weeks in 
2020, there were 33,035 excess deaths, which is only 643 fewer deaths than the official COVID-19 death toll for this time 
period. A comparative increase in the mortality rates was observed in March among both sexes, but particularly for males. 
Comparisons with recently published data show considerably higher excess deaths, but these data were either not covering 
the complete country or did not account for age and sex. Neglecting the demographic changes in a region, even over a short 
time span, can result in biased estimates.
Keywords COVID-19 · Mortality · Italy, age standardisation · Sex differences
Introduction
Electronic supplementary material The online version of this 
article (https: //doi.org/10.1007/s1065 4-021-00717 -9) contains 
supplementary material, which is available to authorized users. COVID-19, the disease associated with Severe Acute Res-
piratory Coronavirus 2 (SARS-CoV-2), was first reported in 
*  Emilio A. L. Gianicolo Wuhan (Hubei Province, China), and as of 9 October 2020, 
 emilio.gianicolo@uni-mainz.de 36.4 million confirmed cases and over 1 million deaths 
1 Institute for Medical Biostatistics, Epidemiology have been reported worldwide [1]. Health care facilities, 
and Informatics (IMBEI), University Medical Center in particular intensive care units, in some countries have 
of the Johannes Gutenberg University of Mainz, Mainz, been overwhelmed with COVID-19 patients. Due to the lack 
Germany of effective treatment strategies or a vaccine, broad public 
2 Institute of Clinical Physiology of the Italian National health control measures have been recommended and imple-
Research Council (IFC-CNR), Lecce, Italy mented in most countries in order to reduce the transmission 
3 Institute of Atmospheric Sciences and Climate of the Italian of SARS-CoV-2.
National Research Council (CNR-ISAC), Lecce, Italy Countries have shown varying patterns in the spread of 
4 Institute of Medical Informatics, Biometry COVID-19, and Italy—in particular its northern region of 
and Epidemiology, University Hospital Essen, Essen, Lombardy—was among the most affected European coun-
Germany tries. However, comparing incidence and mortality between 
5 Department of Epidemiology, School of Public Health, countries is difficult due to high heterogeneity of testing 
Boston University, Boston, USA
Vol.:(012 3456789)
2 14 E. A. L. Gianicolo et al.
strategies, testing potential of laboratories, and demographic Institute of Health, which recorded the first death on 21 
differences. This short article investigates the influence of February 2020 (8th calendar week). Due to this, our study 
the last point, period covers the time span: from the 8th to the 26th calen-
Official COVID-19 death registries only count deaths dar week of 2020 (February 21–June 30). COVID-19 deaths 
directly caused by COVID-19 (direct mortality). However, were confirmed by the Italian National Institute of Health, 
indirect mortality, referring to deaths not directly caused by which followed the criteria established by the WHO [9].
the COVID-19 disease but through circumstances caused Weekly population figures of the Italian population are 
by the COVID-19 pandemic (for example caused by over- not available. Therefore, we used population numbers pub-
burdened health care systems) should also be considered. lished by ISTAT as of 1 January of each year to calculate 
Thus, an excess of the overall mortality within a population sex- and age-specific weekly mortality rates. We did not con-
can be an indicator of the impact of COVID-19. In Italy, sider populations living in those municipalities (n = 537) for 
data on excess mortality have been reported but only on a which ISTAT did not provide mortality data.
restricted number of cities or regions [2, 3] or analyses have 
not accounted for age and sex standardisation [4]. The latter Standardised mortality ratios (SMR)
point is particularly important both from an epidemiological 
and a public health point of view. While comparing popula- Weekly average mortality ratios for the 8th to the 26th weeks 
tions over time, the evolving age structure must be consid- for the period 2015–2019 were calculated by dividing the 
ered. For example, as shown by Stang et al., in Germany weekly sex- and age-specific (0–29, 30–49, 50–59, 60–69, 
the proportion of the oldest people (e.g. in the age-group 70–79, 80+ years) number of deaths in each of the years 
80 years and older) has dramatically increased from 2016 2015–2019 by the sex and age-specific average populations 
to 2019 (+17.1%) [5]. In this age group COVID-19 was for the relevant year. Thereafter, we averaged the sex- and 
particularly lethal [6]. Therefore, ignoring changes of the age-specific rates for the overall period of 2015–2019 and 
age structure over time may result in a biased estimation of multiplied these rates by the age- and sex-specific popula-
excess mortality. Sex-specific data is also paramount when tion in Italy as of 1 January 2020, to calculate the expected 
dealing with COVID-19-related mortality, since different weekly number of deaths in 2020 for the calendar weeks 
patterns of COVID-19 mortality have been shown among 8–26. SMRs were calculated by dividing observed and 
males and females [7]. Daily sex- and age-specific all-cause expected number of deaths. We multiplied these values by 
mortality numbers in Italy from January to June 2020 are 100. 95% confidence intervals (95% CI) were calculated 
available from the Italian National Institute of Statistics [8]. based on the Byar’s approximation [10].
The aim of our study was to calculate sex- and age-specific 
weekly standardised mortality ratios and rates and estimate Differences between COVID‑19 deaths 
the excess of mortality during the pandemic using as refer- and the average number of deaths for the period 
ences the period of 2015–2019 in Italy and the European 2015–2019
standard population respectively. Furthermore, we compared 
the estimated excess of mortality with the officially regis- Weekly excess mortality for the weeks 8–26 in 2020 was cal-
tered COVID-19 mortality. culated as the difference between the observed and expected 
number of deaths.
For the same period, we calculated differences between 
Materials and methods the sex- and age-specific estimated number of excess deaths 
and the numbers of COVD-19 deaths as officially reported 
Mortality and population data by the Italian National Institute of Health. Finally, we cal-
culated the difference between the average number of deaths 
On August 10, 2020, the Italian National Institute of Statis- from 2015 to 2019 and the expected number of deaths.
tics (ISTAT) published daily sex- and age-specific mortality 
data up to 30 June (26th calendar week). ISTAT obtained Direct standardised mortality rates and sex ratios 
these figures by integrating population (Anagrafe Nazion- of age‑standardised mortality rates
ale della Popolazione Residente) and national tax registries 
(Anagrafe tributaria) [9]. For 537 municipalities this integra- In order to compare the mortality experience of males and 
tion was evaluated by ISTAT as unreliable. However, figures females, for 2020 and for the period 2015–2019 we calcu-
were available for 7357 of 7904 municipalities (93.1%). lated sex- and age-specific weekly direct standardised mor-
To determine the number of officially recorded COVID- tality rates and related 95% confidence intervals assuming 
19 deaths in Italy, we used data from the Italian National 
1 3
Gender specific excess mortality in Italy during the COVID-19 pandemic accounting for age 215
the standard European population as the Ref. [11]. Fur- 17.5% from 2015 to 2020 compared to 8.4% for females over 
thermore, to quantify sex differences in age-standardised 80 years old (Table 1).
mortality rates, we calculated sex ratios of age-standardised 
mortality rates with women in the denominator. Standardised mortality ratios (SMR)
In the reference period 2015–2019, the average number of 
Results deaths in the time span from the 8th to the 26th calendar 
week was 219,064 (Table 2). The expected number of deaths 
Demographic changes in Italy over the years 2015– was 229,864, which amounts to an overall SMR of 114.4 
2020 (95%IC 113.9–114.8) (Fig. 1). SMRs lower than 100 were 
observed in the youngest age groups for both males and 
Using demographic data as of 1 January of each year, in females (Fig. 1). We found a difference of 33,035 between 
Italy the group aged 80+ years increased from 3,977,449 observed (262,899) and expected number (229,864) of 
in 2015 to 4,442,048 in 2020 (+11.7%), and the population deaths between the 8th and the 26th calendar week. The 
over 60 years old increased from 16,849,329 to 17,874,053 oldest age groups (60+ years) drove this excess mortality 
in the same time period (6.1%) (Table 1). Sex-specific fig- (Table 2 and Fig. 1). In the same period, the Italian National 
ures also show a considerable change, in particular with the Institute of Health registered 33,678 COVID-19 deaths 
proportion of males over 80 years old, which increased by (Table 2).
Table 1  Population of Italy by Age 2015 2016 2017 2018 2019 2020 Percentage 
age and sex from 2015 to 2020 groups c hangea
as of 1 January of each year (years)
Males
0–29 9,033,691 8,968,422 8,917,180 8,881,148 8,809,898 8,716,257 − 3.5
30–49 8,812,266 8,641,810 8,472,187 8,306,681 8,152,940 7,996,011 − 9.3
50–59 4,229,923 4,327,588 4,424,956 4,506,789 4,578,610 4,656,253 10.1
60–69 3,447,664 3,512,422 3,507,570 3,511,156 3,511,037 3,554,434 3.1
70–79 2,562,600 2,550,154 2,624,947 2,680,724 2,727,000 2,753,864 7.5
80+ 1,415,446 1,455,925 1,498,901 1,541,109 1,605,281 1,663,746 17.5
Total 29,501,590 29,456,321 29,445,741 29,427,607 29,384,766 29,340,565 − 0.5
Females
0–29 8,578,416 8,491,875 8,410,523 8,332,551 8,250,728 8,160,630 − 4.9
30–49 8,857,074 8,688,700 8,507,209 8,328,661 8,163,932 7,996,508 − 9.7
50–59 4,434,913 4,531,162 4,624,040 4,705,957 4,773,621 4,844,927 9.2
60–69 3,743,962 3,818,736 3,816,067 3,823,808 3,826,173 3,870,741 3.4
70–79 3,117,654 3,085,625 3,152,112 3,199,498 3,235,533 3,252,966 4.3
80+ 2,562,003 2,593,132 2,633,753 2,665,891 2,724,793 2,778,302 8.4
Total 31,294,022 31,209,230 31,143,704 31,056,366 30,974,780 30,904,074 − 1.2
Males and females
0–29 17,612,107 17,460,297 17,327,703 17,213,699 17,060,626 16,876,887 − 4.2
30–49 17,669,340 17,330,510 16,979,396 16,635,342 16,316,872 15,992,519 − 9.5
50–59 8,664,836 8,858,750 9,048,996 9,212,746 9,352,231 9,501,180 9.7
60–69 7,191,626 7,331,158 7,323,637 7,334,964 7,337,210 7,425,175 3.2
70–79 5,680,254 5,635,779 5,777,059 5,880,222 5,962,533 6,006,830 5.7
80+ 3,977,449 4,049,057 4,132,654 4,207,000 4,330,074 4,442,048 11.7
Total 60,795,612 60,665,551 60,589,445 60,483,973 60,359,546 60,244,639 − 0.9
a Percentage change from 2015 to 2020
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 216 E. A. L. Gianicolo et al.
Table 2  Average number of deaths from 2015 to 2019, number of deaths in 2020, and expected number of deaths in 2020 by age and sex in Italy 
for calendar weeks 8–26
Age Average number Number of Number of Number of Number of Difference Number of 
groups of deaths deaths observed deaths expected officially regis- observed deaths between number observed deaths in 
(years) 2015–2019 (A) in 2020 (B) in 2020 (C) tered as death in 2020— of observed 2020—expected—
COVID-19 (D) expected (B − C) deaths and aver- officially death 
age number of COVID-19 
deaths (B − A) (B − C − D)
Male
0–29 1015 752 995 13 − 243 − 263 − 256
30–49 3201 2935 3047 255 − 112 − 266 − 367
50–59 6022 6542 6298 892 244 520 − 648
60–69 12,839 14,489 13,003 2597 1486 1650 − 1111
70–79 25,944 31,989 26,983 6194 5006 6045 − 1188
80+ 55,825 70,930 60,888 9572 10,042 15,105 470
Total 104,845 127,637 111,215 19,523 16,422 22,792 − 3101
Female
0–29 555 416 541 7 − 125 − 139 − 132
30–49 1872 1700 1777 105 − 77 − 172 − 182
50–59 3660 3758 3811 281 − 53 98 − 334
60–69 7455 7793 7555 810 238 338 − 572
70–79 17,943 20,344 18,405 2706 1939 2401 − 767
80+ 82,734 101,251 86,561 10,246 14,690 18,517 4444
Total 114,219 135,262 118,650 14,155 16,612 21,043 2457
Total
0–29 1570 1168 1537 20 − 369 − 402 − 389
30–49 5073 4635 4824 360 − 189 − 438 − 549
50–59 9681 10,300 10,109 1173 191 619 − 982
60–69 20,294 22,282 20,558 3407 1724 1988 − 1683
70–79 43,887 52,333 45,388 8900 6945 8446 − 1955
80+ 138,559 172,181 147,449 19,818 24,732 33,622 4914
Total 219,064 262,899 229,864 33,678 33,035 43,835 − 643
Direct standardised mortality rates and sex ratios During the reference period 2015–2019, standardised 
of age‑standardised mortality rates mortality rates were higher among males than among 
females (average sex ratio of age-standardised mortality 
During the 9th–17th calendar weeks, both males and females rates in the weeks 1-26–1.39, range 1.34–1.44). However, 
showed increased direct standardised rates (Fig. 2). On aver- the sex ratio increased markedly between the 10th and the 
age the standardised rate in the first 8 calendar weeks in the 14th week, reaching its maximum in the 12th week (1.69).
period 2015–2019 was equal to 16.9 and to 23.1 per 100,000 
among females and males respectively (data not shown). In 
the same calendar week in 2020, the mortality rates were Discussion
lower among males and females (females 14.8; males 20.3). 
Reduced rates were also observed during the fall and winter In the time periods under study, we found a crude excess 
months in 2019 (Fig. 2). However, during the 9th–17th cal- mortality of 43,835 when comparing the average number of 
endar weeks, mortality increased dramatically, peaking in deaths in the reference period 2015–2019 with the number 
the 13th week when mortality rates were equal to 23.7 and observed in 2020. However, if the evolving demographic 
37.5 among females and males respectively (Fig. 2). structure is taken into consideration, this difference becomes 
1 3
Gender specific excess mortality in Italy during the COVID-19 pandemic accounting for age 217
officially recognized COVID-19 deaths in this time period. 
The authors partially attributed this difference to under-iden-
tification of COVID-19 deaths. However, Alicandro et al. 
used the average deaths in 2015-2019 without considering 
changes of the age- and sex-distribution over time. Using age 
standardisation, we estimated 7414 fewer deaths than Ali-
candro et al. in the same period (data not reported in tables).
Limitations and strengths of the study
While interpreting the difference between the estimated 
excess mortality and the officially registered COVID-19 
deaths, the lack of 100% mortality reporting should be con-
sidered. Since municipalities for which the Italian National 
Institute of Statistics did not provide daily all-cause mortal-
ity data account for 5.2% of the total mortality in the years 
2015–2019, the difference between the excess of mortality 
and the number of deaths officially registered as COVID-19 
might be underestimated.
Furthermore, the choice of a reference period is some-
what arbitrary in nature; a different reference may have 
produced different results. For instance, removing from the 
reference period a year which presented high mortality rates 
because of seasonal influenza would reduce the estimated 
expected number of deaths.
While a considerable portion of the excess mortality is 
likely a direct effect of the COVID-19, indirect effects are 
also important. During the country-wide lock-down in Italy, 
access to healthcare was limited, and residents had medical 
procedures cancelled or delayed. The psychological effects 
of lock-down and coping mechanisms such as increased drug 
and alcohol abuse may also have a role in the excess mortal-
ity [12]. On the other hand, with the lock-down, fewer deaths 
may have occurred for other reasons, for example due to 
fewer car accidents and work-related accidents. This is a pos-
sible explanation for the reduction in deaths in 2020 among 
the younger age groups in Italy, particular among men but 
also for women. One should also consider changes in mor-
tality patterns before the onset of COVID-19 in the Italian 
population. For example, a warmer 2019 winter and a mild 
influenza season preceding January 2020 means the number 
of people particularly vulnerable to COVID-19 was higher 
Fig. 1  Standardised mortality ratios (SMR) on a logaritmic scale and 
95% CI by age and sex in Italy for calendar weeks 8–26. Expected than it might have been had these aspects been different.
numbers are calculated with 2015–2019 as the reference period ISTAT could not provide general mortality data for 537 
municipalities; however, there is no evidence that these 
municipalities are clustered in specific regions. Thus, we 
much smaller (33,035) with only 643 fewer deaths than the can assume that data available is representative of the 
official number of COVID-19 deaths. whole country. Furthermore, only yearly population data 
Alicandro et  al. found 44,107 more deaths occurred was considered for the analysis. We could not use weekly 
between March and May 2020 (from week 10 to week 22) population figures to estimates the weekly mortality rates 
compared to the average number of deaths in these months in 2020 because these figures are not available in a timely 
between 2015 and 2019. This is 10,721 more deaths than manner.
1 3
 218 E. A. L. Gianicolo et al.
Fig. 2  Direct standardised mor-
tality rates (DSR) per 100,000 
at the baseline (2015–2019 
dotted line) and in 2020 (solid 
line) for males (blue lines) 
and females (red lines) Italy, 
calendar weeks from the 8th to 
the 26th
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bution 4.0 International License, which permits use, sharing, adapta- bl.2020.0336.
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as you give appropriate credit to the original author(s) and the source, ies markedly by age. The Lancet. 2020;396(10250):532–3. https 
provide a link to the Creative Commons licence, and indicate if changes ://doi.org/10.1016/S0140 -6736(20)31748 -7.
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