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. 2021 Jan 15;2:100077. doi: 10.1016/j.puhip.2021.100077

Population perspective comparing COVID-19 to all and common causes of death during the first wave of the pandemic in seven European countries

Bayanne Olabi a,∗, Jayshree Bagaria b, Sunil S Bhopal c, Gwenetta D Curry d, Nazmy Villarroel e, Raj Bhopal d
PMCID: PMC7836528  PMID: 33521739

Abstract

Objectives

Mortality statistics on the COVID-19 pandemic have led to widespread concern and fear. To contextualise these data, we compared mortality related to COVID-19 during the first wave of the pandemic across seven countries in Europe with all and common causes of death, stratifying by age and sex. We also calculated deaths as a proportion of the population by age and sex.

Study design

Analysis of population mortality data.

Methods

COVID-19 related mortality and population statistics from seven European countries were extracted: England and Wales, Italy, Germany, Spain, France, Portugal and Netherlands. Available data spanned 14–16 weeks since the first recorded deaths in each country, except Spain, where only comparable stratified data over an 8-week time period was available. The Global Burden of Disease database provided data on all deaths and those from pneumonia, cardiovascular disease combining ischaemic heart disease and stroke, chronic obstructive pulmonary disease, cancer, road traffic accidents and dementia in 2017.

Results

Deaths related to COVID-19, while modest overall, varied considerably by age. Deaths as a percentage of all cause deaths during the time period under study ranged from <0.01% in children in Germany, Portugal and Netherlands, to as high as 41.65% for men aged over 80 years in England and Wales. The percentage of the population who died from COVID-19 was less than 0.2% in every age group under the age of 80. In each country, over the age of 80, these proportions were: England and Wales 1.27% males, 0.87% females; Italy 0.6% males, 0.38% females; Germany 0.13% males, 0.09% females; France 0.39% males, 0.2% females; Portugal 0.2% males, 0.15% females; and Netherlands 0.6% males, 0.4% females.

Conclusions

Mortality rates from COVID-19 during the first wave of the pandemic were low including when compared to other common causes of death and are likely to decline further while control measures are maintained, treatments improve and vaccination is instituted. These data may help people to contextualise their risk and for decision-making by policymakers.

Keywords: COVID-19, Population, Mortality, Stratification, Age, Sex

1. Background

The COVID-19 pandemic, calamitous though it is, needs to be placed in perspective. It has been 12 months since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak was first identified [1], and deaths globally continue to rise. As of November 30, 2020, there have been an estimated 62, 195, 274 cases and 1,453,355 directly attributable deaths worldwide [2]. These are undoubtedly underestimates. These statistics have caused widespread concern and fear [3,4]. Some of this concern is clearly justified, but some – as we have demonstrated in children – is disproportionate, given that COVID-19 caused a small fraction of deaths in people under 18-years of age, even fewer than influenza [5].

Contextualising the impact of COVID-19 in relation to other causes of death, and to mortality rates in the population, helps to gain perspective. Total mortality related to COVID-19 is the most commonly reported statistic, which has been invaluable in galvanising public health interventions [6]; however, given important differentials by age and sex, stratifying the mortality data is essential [7].

We report age- and sex-stratified mortality data related to COVID-19 and compare these with all-cause and common causes of mortality using data from the Global Burden of Disease (GBD) study [8]. We examined two perspectives: firstly, mortality from COVID-19 and other common causes of death as a fraction of all deaths, and secondly, as a fraction of the population.

2. Methods

We extracted population size and COVID-19 mortality by age and sex from the National Institute for Demographic Studies website [9] for the following countries: England and Wales, Italy, Germany, Spain, France, Portugal and Netherlands. These countries were selected due to data availability, reporting comparable age groupings stratified by sex, and comparability of location in Western Europe, with reasonably similar health care systems, economy and capacity to collect data. Available data spanned 14–16 weeks since the first recorded deaths in each country, except Spain, where only comparable stratified data over an 8-week time period was available. Furthermore, these countries have had high death rates given their average age of the population is high compared with low- and middle-income countries. These countries, therefore, exemplify the impact of the pandemic at the higher end of the scale of mortality. Most other countries, especially with younger populations, can anticipate lower mortality.

We extracted annual age- and sex-specific death counts from the Global Burden of Disease 2017 study [8] for all causes and pneumonia, cardiovascular disease combining ischaemic heart disease and stroke (CVD), chronic obstructive pulmonary disease (COPD), cancer, road traffic accidents (RTA) and dementia; these six causes were selected as they represent common causes of death in adults [10]. As we have already reported similar analyses in children and young people [5], and the causes of death are very different from adults, we only compare COVID-19 and all-cause mortality.

To compare mortality estimates from the GBD with those from COVID-19, mortality rates for non-COVID-19 causes for each country were adjusted based on the number of weeks that COVID-19 data were available for (Supplementary Table 1).

Data were analysed by country, age and sex with deaths related to COVID-19 and to other specific causes as a fraction of both all causes of death and population size. Data extraction and analysis was carried out by BO and checked independently by JB. Butterfly charts with stacked bars display these data graphically.

3. Results

Table 1 shows mortality by cause, age and sex in the seven countries from March 09, 2020 until July 09, 2020 (for specific dates see Supplementary Table 1) and the percentage of COVID-19 deaths and other causes of death with respect to all-cause mortality. Fig. 1 summarises these data.

Table 1.

Mortality data by country, cause, age and sex: specific causes of death, including COVID-19, are shown as raw data, percentage of all-cause deaths and percentage of population for each country’s demographic group.

Country Demographic group Population (n) All cause deaths (n) COVID-19 deaths
 Pneumonia deaths
 CVD deaths
 COPD deaths
 Cancer deaths
 RTA deaths
 Dementia deaths
n % of all cause deaths % died in this group n % of all cause deaths % died in this group n % of all cause deaths % died in this group n % of all cause deaths % died in this group n % of all cause deaths % died in this group n % of all cause deaths % died in this group n % of all cause deaths % died in this group
England and Wales
 0–9 M 3701011 555 2 0.36 0
F 3522739 429 1 0.23 0
10–19 M 3448335 189 7 3.7 0
F 3273242 111 5 4.5 0
20–29 M 3954548 633 46 7.27 0 9 1.42 0 17 2.69 0 1 0.16 0 66 10.43 0 104 16.43 0 0 0 0
F 3785684 277 27 9.75 0 7 2.53 0 9 3.25 0 1 0.36 0 63 22.74 0 22 7.94 0 0 0 0
30–30 M 3920605 1085 121 11.15 0 23 2.12 0 91 8.39 0 4 0.37 0 163 15.02 0 69 6.36 0 0 0 0
F 3956326 627 85 13.56 0 15 2.39 0 40 6.38 0 3 0.48 0 228 36.36 0.01 15 2.39 0 0 0 0
40–49 M 3749942 2349 427 18.18 0.01 59 2.51 0 422 17.97 0.01 29 1.23 0 574 24.44 0.02 63 2.68 0 4 0.17 0
F 3815410 1519 263 17.31 0.01 37 2.44 0 141 9.28 0 21 1.38 0 720 47.4 0.02 16 1.05 0 5 0.33 0
50–59 M 3906270 5142 1491 29 0.04 130 2.53 0 1167 22.7 0.03 149 2.9 0 1963 38.18 0.05 56 1.09 0 27 0.53 0
F 4016425 3667 777 21.19 0.02 90 2.45 0 395 10.77 0.01 134 3.65 0 2006 54.7 0.05 18 0.49 0 32 0.87 0
60–69 M 3041563 10620 3149 29.65 0.1 287 2.7 0.01 2372 22.34 0.08 644 6.06 0.02 4794 45.14 0.16 45 0.42 0 153 1.44 0.01
F 3199239 7442 1647 22.13 0.05 200 2.69 0.01 954 12.82 0.03 559 7.51 0.02 3921 52.69 0.12 20 0.27 0 175 2.35 0.01
70–79 M 2308296 18924 7027 37.13 0.3 719 3.8 0.03 4380 23.15 0.19 1514 8 0.07 7474 39.49 0.32 45 0.24 0 839 4.43 0.04
F 2576981 14771 4137 28.01 0.16 600 4.06 0.02 2594 17.56 0.1 1296 8.77 0.05 5840 39.54 0.23 31 0.21 0 1054 7.14 0.04
80+
 M 1184681 36116 15044 41.65 1.27 2959 8.19 0.25 9066 25.1 0.77 2697 7.47 0.23 8939 24.75 0.75 55 0.15 0 4461 12.35 0.38
F
 1754512
 49714
 15351
 30.88
 0.87
 4376
 8.8
 0.25
 11892
 23.92
 0.68
 2962
 5.96
 0.17
 8753
 17.61
 0.5
 50
 0.1
 0
 9657
 19.43
 0.55
Italy
 0–9 M 2617094 297 1 0.34 0
F 2473388 230 3 1.3 0
10–19 M 2980600 177 0 0 0
F 2788274 82 0 0 0
20–29 M 3212204 413 12 2.91 0 4 0.97 0 15 3.63 0 1 0.24 0 59 14.29 0 131 31.72 0 0 0 0
F 2989066 170 4 2.35 0 2 1.18 0 7 4.12 0 1 0.59 0 51 30 0 33 19.41 0 0 0 0
30–30 M 3559151 692 43 6.21 0 8 1.16 0 71 10.26 0 3 0.43 0 152 21.97 0 110 15.9 0 0 0 0
F 3515067 372 23 6.18 0 5 1.34 0 25 6.72 0 2 0.54 0 188 50.54 0.01 22 5.91 0 0 0 0
40–49 M 4593789 2062 213 10.33 0 24 1.16 0 335 16.25 0.01 15 0.73 0 709 34.38 0.02 135 6.55 0 3 0.15 0
F 4648865 1308 83 6.35 0 11 0.84 0 110 8.41 0 9 0.69 0 818 62.54 0.02 28 2.14 0 4 0.31 0
50–59 M 4578610 5339 893 16.73 0.02 62 1.16 0 974 18.24 0.02 63 1.18 0 2555 47.86 0.06 132 2.47 0 26 0.49 0
F 4773621 3242 281 8.67 0.01 35 1.08 0 307 9.47 0.01 38 1.17 0 2119 65.36 0.04 37 1.14 0 30 0.93 0
60–69 M 3511037 11244 2600 23.12 0.07 150 1.33 0 2052 18.25 0.06 262 2.33 0.01 5898 52.45 0.17 113 1 0 166 1.48 0
F 3826173 6537 811 12.41 0.02 84 1.28 0 797 12.19 0.02 132 2.02 0 3804 58.19 0.1 47 0.72 0 196 3 0.01
70–79 M 2727000 22667 6201 27.36 0.23 406 1.79 0.01 4701 20.74 0.17 940 4.15 0.03 9940 43.85 0.36 171 0.75 0.01 1124 4.96 0.04
F 3235533 15600 2708 17.36 0.08 249 1.6 0.01 2908 18.64 0.09 457 2.93 0.01 6217 39.85 0.19 86 0.55 0 1488 9.54 0.05
80+
 M 1605281 48987 9581 19.56 0.6 1358 2.77 0.08 14039 28.66 0.87 3230 6.59 0.2 11900 24.29 0.74 313 0.64 0.02 5409 11.04 0.34
F
 2724793
 72006
 10279
 14.28
 0.38
 1637
 2.27
 0.06
 21594
 29.99
 0.79
 2737
 3.8
 0.1
 11038
 15.33
 0.41
 313
 0.43
 0.01
 14119
 19.61
 0.52
Germany
 0–9 M 3896272 469 0 0 0
F 3692363 377 1 0.27 0
10–19 M 3987129 245 2 0.82 0
F 3718528 135 0 0 0
20–29 M 5110948 763 6 0.79 0 8 1.05 0 22 2.88 0 2 0.26 0 85 11.14 0 163 21.36 0 0 0 0
F 4689659 288 3 1.04 0 5 1.74 0 13 4.51 0 2 0.69 0 63 21.88 0 38 13.19 0 0 0 0
30–30 M 5437398 1258 17 1.35 0 16 1.27 0 99 7.87 0 5 0.4 0 207 16.45 0 103 8.19 0 0 0 0
F 5209047 617 6 0.97 0 9 1.46 0 41 6.65 0 3 0.49 0 244 39.55 0 23 3.73 0 0 0 0
40–49 M 5251175 3406 53 1.56 0 49 1.44 0 532 15.62 0.01 36 1.06 0 937 27.51 0.02 108 3.17 0 5 0.15 0
F 5175082 1892 22 1.16 0 22 1.16 0 166 8.77 0 25 1.32 0 967 51.11 0.02 29 1.53 0 5 0.26 0
50–59 M 6767896 11228 236 2.1 0 185 1.65 0 2162 19.26 0.03 274 2.44 0 4420 39.37 0.07 146 1.3 0 41 0.37 0
F 6706270 5985 85 1.42 0 88 1.47 0 622 10.39 0.01 182 3.04 0 3361 56.16 0.05 42 0.7 0 43 0.72 0
60–69 M 4987359 19577 641 3.27 0.01 400 2.04 0.01 4256 21.74 0.09 881 4.5 0.02 8473 43.28 0.17 105 0.54 0 228 1.16 0
F 5315052 10993 229 2.08 0 197 1.79 0 1568 14.26 0.03 561 5.1 0.01 5686 51.72 0.11 41 0.37 0 248 2.26 0
70–79 M 3503497 35800 1372 3.83 0.04 1011 2.82 0.03 9333 26.07 0.27 1883 5.26 0.05 12722 35.54 0.36 123 0.34 0 1463 4.09 0.04
F 4182432 25405 667 2.63 0.02 591 2.33 0.01 5609 22.08 0.13 1177 4.63 0.03 8915 35.09 0.21 74 0.29 0 2014 7.93 0.05
80+
 M 2025017 56548 2673 4.73 0.13 2077 3.67 0.1 18661 33 0.92 2855 5.05 0.14 11747 20.77 0.58 109 0.19 0.01 5192 9.18 0.26
F
 3364089
 89167
 3030
 3.4
 0.09
 2357
 2.64
 0.07
 28968
 32.49
 0.86
 3579
 4.01
 0.11
 12535
 14.06
 0.37
 102
 0.11
 0
 14124
 15.84
 0.42
Spain
 0–9 M 2251517 137 1 0.73 0
F 2119341 107 1 0.93 0
10–19 M 2520800 60 3 5 0
F 2362647 35 2 5.71 0
20–29 M 2464472 148 15 10.14 0 2 1.35 0 7 4.73 0 1 0.68 0 21 14.19 0 37 25 0 0 0 0
F 2383466 63 9 14.29 0 1 1.59 0 3 4.76 0 0 0 0 16 25.4 0 9 14.29 0 0 0 0
30–30 M 3076176 333 42 12.61 0 5 1.5 0 37 11.11 0 3 0.9 0 69 20.72 0 40 12.01 0 0 0 0
F 3091412 173 21 12.14 0 3 1.73 0 12 6.94 0 1 0.58 0 79 45.66 0 8 4.62 0 0 0 0
40–49 M 3943490 1028 140 13.62 0 17 1.65 0 167 16.25 0 11 1.07 0 341 33.17 0.01 48 4.67 0 2 0.19 0
F 3869686 550 77 14 0 7 1.27 0 46 8.36 0 5 0.91 0 322 58.55 0.01 10 1.82 0 2 0.36 0
50–59 M 3457353 2685 465 17.32 0.01 42 1.56 0 463 17.24 0.01 55 2.05 0 1310 48.79 0.04 42 1.56 0 11 0.41 0
F 3516656 1295 191 14.75 0.01 18 1.39 0 125 9.65 0 22 1.7 0 817 63.09 0.02 13 1 0 13 1 0
60–69 M 2543236 4709 1282 27.22 0.05 78 1.66 0 798 16.95 0.03 206 4.37 0.01 2448 51.99 0.1 34 0.72 0 69 1.47 0
F 2738641 2102 540 25.69 0.02 34 1.62 0 263 12.51 0.01 58 2.76 0 1152 54.8 0.04 14 0.67 0 80 3.81 0
70–79 M 1771960 7506 3321 44.24 0.19 179 2.38 0.01 1386 18.47 0.08 576 7.67 0.03 3133 41.74 0.18 34 0.45 0 359 4.78 0.02
F 2128590 4388 1565 35.67 0.07 93 2.12 0 757 17.25 0.04 163 3.71 0.01 1547 35.26 0.07 17 0.39 0 527 12.01 0.02
80+
 M 1060385 17826 6339 35.56 0.6 751 4.21 0.07 4075 22.86 0.38 1983 11.12 0.19 4200 23.56 0.4 40 0.22 0 2046 11.48 0.19
F
 1800567
 24941
 6522
 26.15
 0.36
 878
 3.52
 0.05
 6178
 24.77
 0.34
 1620
 6.5
 0.09
 3407
 13.66
 0.19
 29
 0.12
 0
 5352
 21.46
 0.3
France
 0–9 M 3957228 516 2 0.39 0
F 3798527 401 1 0.25 0
10–19 M 4266196 222 2 0.9 0
F 4062792 114 2 1.75 0
20–29 M 3737191 662 14 2.11 0 4 0.6 0 15 2.27 0 1 0.15 0 69 10.42 0 191 28.85 0.01 0 0 0
F 3733717 251 7 2.79 0 3 1.2 0 8 3.19 0 1 0.4 0 57 22.71 0 41 16.33 0 0 0 0
30–30 M 4025803 1081 55 5.09 0 11 1.02 0 68 6.29 0 2 0.19 0 186 17.21 0 125 11.56 0 0 0 0
F 4262454 504 35 6.94 0 5 0.99 0 28 5.56 0 1 0.2 0 210 41.67 0 25 4.96 0 0 0 0
40–49 M 4233782 2698 158 5.86 0 31 1.15 0 291 10.79 0.01 13 0.48 0 858 31.8 0.02 108 4 0 4 0.15 0
F 4350667 1445 82 5.67 0 14 0.97 0 102 7.06 0 7 0.48 0 786 54.39 0.02 26 1.8 0 4 0.28 0
50–59 M 4294564 6914 617 8.92 0.01 100 1.45 0 835 12.08 0.02 73 1.06 0 3439 49.74 0.08 90 1.3 0 25 0.36 0
F 4490542 3563 291 8.17 0.01 44 1.23 0 257 7.21 0.01 36 1.01 0 2184 61.3 0.05 30 0.84 0 29 0.81 0
60–69 M 3792182 13799 1630 11.81 0.04 245 1.78 0.01 1896 13.74 0.05 295 2.14 0.01 7487 54.26 0.2 77 0.56 0 182 1.32 0
F 4207424 6925 677 9.78 0.02 107 1.55 0 640 9.24 0.02 122 1.76 0 4067 58.73 0.1 39 0.56 0 206 2.97 0
70–79 M 2598072 16729 2989 17.87 0.12 430 2.57 0.02 2782 16.63 0.11 506 3.02 0.02 7641 45.68 0.29 64 0.38 0 835 4.99 0.03
F 3095588 10423 1354 12.99 0.04 228 2.19 0.01 1437 13.79 0.05 246 2.36 0.01 4499 43.16 0.15 39 0.37 0 1109 10.64 0.04
80+
 M 1492161 40808 5864 14.37 0.39 2049 5.02 0.14 9166 22.46 0.61 1630 3.99 0.11 10548 25.85 0.71 96 0.24 0.01 5037 12.34 0.34
F
 2664813
 60011
 5456
 9.09
 0.2
 2691
 4.48
 0.1
 13366
 22.27
 0.5
 1900
 3.17
 0.07
 10404
 17.34
 0.39
 99
 0.16
 0
 12925
 21.54
 0.49
Portugal
 0–9 M 458227 56 0 0 0
F 438988 40 0 0 0
10–19 M 543042 34 0 0 0
F 520053 19 0 0 0
20–29 M 545347 93 1 1.08 0 2 2.15 0 2 2.15 0 0 0 0 12 12.9 0 27 29.03 0 0 0 0
F 540688 28 1 3.57 0 1 3.57 0 1 3.57 0 0 0 0 7 25 0 4 14.29 0 0 0 0
30–30 M 610964 160 1 0.63 0 4 2.5 0 10 6.25 0 1 0.63 0 29 18.13 0 19 11.88 0 0 0 0
F 650915 94 1 1.06 0 2 2.13 0 5 5.32 0 1 1.06 0 40 42.55 0.01 4 4.26 0 0 0 0
40–49 M 750095 578 10 1.73 0 16 2.77 0 71 12.28 0.01 5 0.87 0 190 32.87 0.03 28 4.84 0 1 0.17 0
F 826398 291 10 3.44 0 6 2.06 0 26 8.93 0 3 1.03 0 155 53.26 0.02 7 2.41 0 1 0.34 0
50–59 M 696521 1417 38 2.68 0.01 39 2.75 0.01 233 16.44 0.03 23 1.62 0 655 46.22 0.09 34 2.4 0 5 0.35 0
F 782400 617 17 2.76 0 15 2.43 0 70 11.35 0.01 8 1.3 0 351 56.89 0.04 9 1.46 0 5 0.81 0
60–69 M 595393 2456 102 4.15 0.02 81 3.3 0.01 476 19.38 0.08 76 3.09 0.01 1147 46.7 0.19 31 1.26 0.01 30 1.22 0.01
F 691534 1203 46 3.82 0.01 36 2.99 0.01 194 16.13 0.03 26 2.16 0 597 49.63 0.09 11 0.91 0 35 2.91 0.01
70–79 M 415892 4032 190 4.71 0.05 218 5.41 0.05 950 23.56 0.23 210 5.21 0.05 1459 36.19 0.35 30 0.74 0.01 165 4.09 0.04
F 548704 2900 125 4.31 0.02 131 4.52 0.02 712 24.55 0.13 108 3.72 0.02 887 30.59 0.16 15 0.52 0 245 8.45 0.04
80+
 M 236885 8133 478 5.88 0.2 735 9.04 0.31 2329 28.64 0.98 603 7.41 0.25 1715 21.09 0.72 28 0.34 0.01 788 9.69 0.33
F
 424571
 11756
 626
 5.32
 0.15
 843
 7.17
 0.2
 3740
 31.81
 0.88
 669
 5.69
 0.16
 1558
 13.25
 0.37
 24
 0.2
 0.01
 1942
 16.52
 0.46
Netherlands 0–9 M 913891 117 0 0 0
F 869613 93 0 0 0
10–19 M 1027835 47 1 2.13 0
F 980499 30 0 0 0
20–29 M 1117353 126 3 2.38 0 1 0.79 0 3 2.38 0 0 0 0 18 14.29 0 24 19.05 0 0 0 0
F 1084435 68 0 0 0 1 1.47 0 2 2.94 0 0 0 0 17 25 0 6 8.82 0 0 0 0
30–30 M 1060110 184 8 4.35 0 2 1.09 0 14 7.61 0 1 0.54 0 42 22.83 0 14 7.61 0 0 0 0
F 1048089 132 3 2.27 0 2 1.52 0 8 6.06 0 1 0.76 0 61 46.21 0.01 4 3.03 0 0 0 0
40–49 M 1127000 501 16 3.19 0 6 1.2 0 70 13.97 0.01 6 1.2 0 186 37.13 0.02 15 2.99 0 1 0.2 0
F 1134107 387 15 3.88 0 4 1.03 0 33 8.53 0 7 1.81 0 228 58.91 0.02 5 1.29 0 1 0.26 0
50–59 M 1258588 1466 102 6.96 0.01 24 1.64 0 228 15.55 0.02 34 2.32 0 726 49.52 0.06 18 1.23 0 7 0.48 0
F 1249800 1208 44 3.64 0 17 1.41 0 95 7.86 0.01 50 4.14 0 783 64.82 0.06 8 0.66 0 8 0.66 0
60–69 M 1038005 3418 334 9.77 0.03 70 2.05 0.01 563 16.47 0.05 149 4.36 0.01 1845 53.98 0.18 19 0.56 0 49 1.43 0
F 1051908 2419 167 6.9 0.02 45 1.86 0 244 10.09 0.02 156 6.45 0.01 1469 60.73 0.14 10 0.41 0 46 1.9 0
70–79 M 730336 5852 1047 17.89 0.14 177 3.02 0.02 1099 18.78 0.15 391 6.68 0.05 2637 45.06 0.36 27 0.46 0 268 4.58 0.04
F 791774 4254 588 13.82 0.07 120 2.82 0.02 690 16.22 0.09 321 7.55 0.04 1851 43.51 0.23 16 0.38 0 290 6.82 0.04
80+ M 307968 9555 1861 19.48 0.6 566 5.92 0.18 2131 22.3 0.69 754 7.89 0.24 2548 26.67 0.83 36 0.38 0.01 1074 11.24 0.35
F 490852 14006 1943 13.87 0.4 743 5.3 0.15 3242 23.15 0.66 819 5.85 0.17 2518 17.98 0.51 26 0.19 0.01 2535 18.1 0.52
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Abbreviations: COVID-19, coronavirus disease 2019; COPD, chronic obstructive pulmonary disease; CVD, cardiovascular disease; RTA, road traffic accident.

Fig. 1.

Fig. 1

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Stacked bar charts showing mortality from seven causes of death as a percentage of all-cause deaths by age and sex in six European countries.

Across all countries the number of deaths related to COVID-19 demonstrated a sharp increase with age, and there were greater numbers of deaths in males than females. Deaths related to COVID-19 represented a small proportion of all deaths overall, though this varied considerably by age being less than 0.01% in children in Germany, Portugal and Netherlands, and as high as 41.65% for men aged over 80 years in England and Wales. In groups under the age of 70, COVID-19 was never the commonest cause of death although it was an important contributor.

Fig. 2 shows the percentage of the population who died from COVID-19 and the six other causes (Supplementary Figure 1 provides continuous x-axes to 100%). These figures show that, cumulatively, mortality from the six common causes of death was less than 1% in every age group, except in those aged over 80 years, where this percentage ranged from 1 to 4%. The percentage of the population dying from COVID-19 was less than 0.2% in every age group under the age of 80 across all countries, less than or equal to 0.1% under the age of 70 and less than 0.04% under the age of 60. In each country, over the age of 80, these proportions were: England and Wales 1.27% males, 0.87% females; Italy 0.6% males, 0.38% females; Germany 0.13% males, 0.09% females; France 0.39% males, 0.2% females; Portugal 0.2% males, 0.15% females; and Netherlands 0.6% males, 0.4% females.

Fig. 2.

Fig. 2

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Stacked bar charts showing mortality data from seven causes of death in six countries as a percentage of the population in each demographic group. Discontinuous x-axes are used.

Graphical representation of the data from Spain are shown in Supplementary Figure 2, as these represent on an 8-week time period, compared to other countries, which represent data over 14–16 weeks.

4. Discussion

The COVID-19 pandemic is an international emergency warranting a comprehensive, medical, public health and economic response [11]. Our methods and analyses provide a population perspective on the pandemic during the first wave in, some of the worst affected countries in the world. It is unlikely that the patterns will change in the second wave but they may in subsequent waves given successful vaccination programmes, which are likely to reduce mortality substantially in older age groups. These data show that the high level of mortality is primarily seen in older adults, particularly men. However, even in the most affected groups, other causes of death were more common than COVID-19, and in all groups under the age of 70, COVID-19 did not represent the most common cause of death. Our non-COVID-19 mortality data from the Global Burden of Disease 2017 study allowed us to estimate deaths for different age groups. Given the potential impact of lockdowns on access to healthcare, particularly for those with chronic conditions, it is likely that mortality patterns from these other causes will change in this pandemic year, most likely with increases in cardiovascular diseases and cancer but possibly reductions in infectious diseases including influenza.

These data also highlight the very small percentages of deaths related to COVID-19 relative to population size, representing less than 0.2% in all groups under the age of 80. Mortality related to the first wave of the COVID-19 pandemic in Europe mainly occurred during the months of March, April and May and was subsequently brought under greater control during the summer months. We cannot forecast population impact on mortality patterns of future and waves of the pandemic. We can see, however, the population impact on mortality during the first wave has been modest except in those over 80 years of age. In the immediate future, the relative proportions of deaths from COVID-19 compared to other causes in these European countries are likely to decline as control measures, while being relaxed, are likely to be applied partially and intermittently for some years. Better treatments and widespread vaccination are also likely to reduce COVID-19 mortality.

Mortality related to COVID-19 is known to be higher in males than in females and higher in older age groups and the mechanisms for these differential effects have been postulated [12,13]. Other important factors have also been recognised to lead to poorer outcomes following COVID-19 infection, including co-morbidity [14] and ethnicity, with data suggesting that ethnic minority groups are at increased risk of death from COVID-19[15]. Though these have not been analysed in this study, ensuring a holistic approach when determining and addressing risk is important.

We acknowledge limitations of this study. We found variations between countries in proportions of deaths but have not emphasised them as data collection factors may contribute to this. For example, the COVID-19 mortality data from France represented only in-hospital deaths, whereas England and Wales also counted community deaths, including hospices, care homes and patients’ homes [9]. A further limitation is that data from Spain only represented an 8-week time span during the initial outbreak, as their data reporting methods changed beyond May [9], hindering access to comparable data since then. Defining COVID-19 mortality rates is also contentious, as data pertains to clinically apparent PCR-positive infections, underestimating true mortality [16]. Furthermore, there may be several reasons why the mortality totals exceed 100 in England and Wales, Italy and Spain. The GBD data may reflect death certificates that record more than one of the listed causes of death under study here, therefore leading to an overestimation of the cumulative totals. Without access to real-time mortality data on all causes, we are also unable to assess the ongoing effect of the pandemic on mortality related to other causes, such as cancer and cardiovascular disease, which may rise as healthcare resources have been both curtailed and diverted [17]. This analysis does not examine underlying comorbidities in people who died, which would provide further important perspectives for responding to the pandemic. Finally, morbidity from COVID-19 is clearly substantial but quantitative data in populations are not available and we were unable to replicate our work using morbidity data. Morbidity, both as a risk factor for mortality, and as a consequence of the infection is an important area for future research.

Our data from seven European countries provides an important public message for policymakers, healthcare workers and the public, who are trying to understand the impact of COVID-19 and the risk of dying. Other population-level studies have been conducted using UK data to contextualise these risks [18,19]. Misinformation has been a problem, perpetuating public fear and anxiety, impacting on the increasing burden of adverse mental health during the pandemic and even contributing to suicide risk [20,21].

By presenting and interpreting population perspectives on mortality related to COVID-19 compared with other common causes of death, stratified by age and sex, we have provided perspectives to allow policymakers, professionals and the media to tailor both communications and interventions to manage the pandemic, including the level of anxiety and fear provoked by previously published mortality statistics, primarily daily and cumulative totals. Similar analyses are required globally and for the duration of the pandemic. More research is required to incorporate morbidity to produce a broader perspective on the true health impact of COVID-19[15].

Funding

None.

Contributions

RB conceived the study. SB and JB developed the methodology, which was expanded by BO. BO carried out data extraction, which was checked independently by JB. BO carried out the data analysis. All authors contributed to the interpretation of the data. BO wrote the first draft of the manuscript, which was substantially edited by all authors. All authors approved the final version. All authors had access to the data and are responsible for data integrity and completeness.

Declaration of competing interest

None reported.

Footnotes

Appendix A
Supplementary data to this article can be found online at https://doi.org/10.1016/j.puhip.2021.100077.
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Appendix A. Supplementary data

The following are the Supplementary data to this article:

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References

  • 1.Yang X., Yu Y., Xu J., et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir. Med. 2020;8(5):475–481. doi: 10.1016/S2213-2600(20)30079-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.John Hopkins University Coronavirus resource center https://coronavirus.jhu.edu/map.html
  • 3.Jungmann S.M., Witthöft M. Health anxiety, cyberchondria, and coping in the current COVID-19 pandemic: which factors are related to coronavirus anxiety? J. Anxiety Disord. 2020:102239. doi: 10.1016/j.janxdis.2020.102239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.The Guardian. Anxiety on rise due to coronavirus, say mental health charities. https://www.theguardian.com/world/2020/mar/13/anxiety-on-rise-due-to-coronavirus-say-mental-health-charities
  • 5.Bhopal S., Bagaria J., Bhopal R. Children’s mortality from COVID-19 compared with all-deaths and other relevant causes of death: epidemiological information for decision-making by parents, teachers, clinicians and policymakers. Publ. Health. 2020;185:19–20. doi: 10.1016/j.puhe.2020.05.047. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Yuan J., Li M., Lv G., Lu Z.K. Monitoring transmissibility and mortality of COVID-19 in Europe. Int. J. Infect. Dis. 2020;95:311–315. doi: 10.1016/j.ijid.2020.03.050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Bhopal R. Covid-19 worldwide: we need precise data by age group and sex urgently. BMJ. 2020:369. doi: 10.1136/bmj.m1366. [DOI] [PubMed] [Google Scholar]
  • 8.GHDx. Global burden of disease study 2017 (GBD 2017) data resources. 2020. http://ghdx.healthdata.org/gbd-2017 accessed.
  • 9.Ined. Demographics of COVID-19 deaths. 2020. https://dc-covid.site.ined.fr/en/ accessed.
  • 10.Moraga P., Collaborators G. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390(10100):1151–1210. doi: 10.1016/S0140-6736(17)32152-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Bhopal R.S. COVID-19 zugzwang: potential public health moves towards population (herd) immunity. Public Health in Practice. 2020:100031. doi: 10.1016/j.puhip.2020.100031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Gebhard C., Regitz-Zagrosek V., Neuhauser H.K., Morgan R., Klein S.L. Impact of sex and gender on COVID-19 outcomes in Europe. Biol. Sex Differ. 2020;11(1):1–13. doi: 10.1186/s13293-020-00304-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Nikolich-Zugich J., Knox K.S., Rios C.T., Natt B., Bhattacharya D., Fain M.J. SARS-CoV-2 and COVID-19 in older adults: what we may expect regarding pathogenesis, immune responses, and outcomes. Geroscience. 2020:1–10. doi: 10.1007/s11357-020-00186-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Yang J., Zheng Y., Gou X., et al. Prevalence of comorbidities in the novel Wuhan coronavirus (COVID-19) infection: a systematic review and meta-analysis. Int. J. Infect. Dis. 2020;94:91–95. doi: 10.1016/j.ijid.2020.03.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Aldridge R.W., Lewer D., Katikireddi S.V., et al. Black, Asian and Minority Ethnic groups in England are at increased risk of death from COVID-19: indirect standardisation of NHS mortality data. Wellcome Open Research. 2020;5(88):88. doi: 10.12688/wellcomeopenres.15922.1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Baud D., Qi X., Nielsen-Saines K., Musso D., Pomar L., Favre G. Real estimates of mortality following COVID-19 infection. Lancet Infect. Dis. 2020;20(7):773. doi: 10.1016/S1473-3099(20)30195-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Watkins J., Wulaningsih W. Three further ways that the COVID-19 pandemic will affect health outcomes. Int. J. Publ. Health. 2020:1. doi: 10.1007/s00038-020-01383-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.McCartney G., Leyland A., Walsh S., Ruth D. Scaling COVID-19 against inequalities: should the policy response consistently match the mortality challenge? J. Epidemiol. Community Health. 2020 doi: 10.1136/jech-2020-214373. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Spiegelhalter D. Use of “normal” risk to improve understanding of dangers of covid-19. Br. Med. J. 2020;370:m3259. doi: 10.1136/bmj.m3259. [DOI] [PubMed] [Google Scholar]
  • 20.Mamun M.A., Griffiths M.D. First COVID-19 suicide case in Bangladesh due to fear of COVID-19 and xenophobia: possible suicide prevention strategies. Asian journal of psychiatry. 2020;51:102073. doi: 10.1016/j.ajp.2020.102073. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Gunnell D., Appleby L., Arensman E., et al. Suicide risk and prevention during the COVID-19 pandemic. The Lancet Psychiatry. 2020;7(6):468–471. doi: 10.1016/S2215-0366(20)30171-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

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