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Acta Bio Medica : Atenei Parmensis logoLink to Acta Bio Medica : Atenei Parmensis
. 2021 Oct 1;92(Suppl 6):e2021420. doi: 10.23750/abm.v92iS6.12241

An assessment of case-fatality and infection-fatality rates of first and second COVID-19 waves in Italy

Tommaso Filippini 1, Federico Zagnoli 1, Matteo Bosi 1, Maria Edvige Giannone 1, Cristina Marchesi 2, Marco Vinceti 1,3,✉
PMCID: PMC8851028  PMID: 34739462

Abstract

Background and aim:

The exact COVID-19 severity is still not well defined and it is hotly debated due to a few methodological issues such as the uncertainties about the spread of the SARS-CoV-2 infection.

Methods:

We investigated COVID-19 case-fatality rate and infection-fatality rate in 2020 in Italy, a country severely affected by the pandemic, basing our assessment on publicly available data, and calculating such measures during the first and second waves.

Results:

We found that province-specific crude case-fatality rate in the first wave (February-July 2020) had a median value of 12.0%. Data about infection-fatality rate was more difficult to compute, due to large underestimation of SARS-CoV-2 infection during the first wave when asymptomatic individuals were very rarely tested. However, when using reference population-based seroprevalence data for anti-SARS-CoV-2 antibodies collected in May-July 2020, we computed an infection-fatality rate of 2.2%. During the second wave (Sep-Dec 2020), when SARS-CoV-2 testing was greatly increased and extended to many asymptomatic individuals, we could only compute a ‘hybrid’ case/infection-fatality rate with a value of 2.2%, similar to the infection-fatality rate of the first wave.

Conclusions:

Overall, this study allowed to assess the COVID-19 case- and infection-fatality rates in Italy before of variant spread and vaccine availability, confirming their high values compared with other airborne infections like influenza. Our findings for Italy were similar to those characterizing other Western European countries.

Keywords: COVID-19, case-fatality rate, epidemiology, infection-fatality rate, outbreak, public health, SARS-CoV-2, seroprevalence, wave

Introduction

The COVID-19 pandemic is one of the greatest medical challenges of the last century (1), especially for the possible clinical presentation as a severe and life-threatening disease (2), with limited therapeutic options, and long-term sequelae (3-5). Since the beginning, attempts to control the pandemic spread relied on public health measures such as social distancing, contact tracing, use of face masks and other protective gears (like googles or face shields in health care settings), and lockdowns with limitations of population mobility (6-10). Still in recent months that vaccines are available, the presence of virus variants and the possibility of reinfection are of great concern (11-13).

Italy was the first Western country severely hit by the pandemic, with a widespread population involvement, especially in the North of the country during the first wave (14). Factors associated with increased susceptibility to COVID-19 onset and severity, following the infection with SARS-CoV-2, have been shown to be male sex, and presence of a comorbidity such as hypertension, diabetes, cardiovascular disease, or chronic lung disease (15,16). Also, environmental factors may play a role increasing COVID-19 susceptibility and severity (17-21) as also reported in previous studies carried out in Northern Italy suggesting a positive association between air pollutant levels with both SARS-CoV-2 incidence and COVID-19 mortality (22-24).

During the 2020, Italy experienced two pandemic waves. The first wave started with the first diagnosed case on February 20, 2020 and lasted till end of June 2020, leading to the implementation of a tight lockdown from March 8 to May 4, 2020 (6). After a brief summer period characterized by light restrictions due to the very low number of newly diagnosed cases, from September 2020 cases rapidly increased again, leading to a second, lighter lockdown from November 6, 2020 (25). Since begin of the vaccination campaign in a few subjects in December 27, 2020 and during the 2021, Italy has experienced a subsequent third wave in February-May 2021 and a fourth one in the most recent period, although the last ones have been largely mitigated by the growing number of vaccinated people (26).

Due to lack of a large availability of SARS-CoV-2 swab tests during the first wave, SARS-CoV-2 infection testing was limited to subjects with symptoms potentially related to COVID-19 as well to health professionals (27-29). From the end of the first lockdown, availability of SARS-CoV-2 swab tests greatly increased and, therefore, testing has been extended to asymptomatic and pauci-symptomatic subjects (30). In particular, drive-through facilities have been implemented in several Italian cities with up to 1000 daily tests (31). For this reason, number of SARS-CoV-2 infections was certainly underestimated during the first wave (14), as also confirmed by the nationwide seroprevalence data made available by the National Institute of Statistics based on a population-based survey conducted in May-July 2020 (32). As consequence, there are uncertainties and controversies about the severity of COVID-19 and namely its case-fatality rate (number of COVID-19 deaths divided by COVID-19 cases, i.e. the symptomatic subjects diagnosed with the disease) and infection-fatality rate (number of deaths divided by overall number of cases of SARS-CoV-2 infection, i.e. including both symptomatic and asymptomatic subjects), due to methodological issues (33). Such issues include the censoring when the outcome is still unknown at the time of the investigation, the occurrence of ascertainment biases (34-36), especially the underestimation SARS-CoV-2 infection and COVID-19 incidence during an emergency situation as during the pandemic spread, and heterogeneity in classifying the outcome, i.e. COVID-19 related deaths (37-41).

In this study, we aimed at assessing COVID-19 fatality rates in Italy, focusing on case-fatality and infection-fatality rates during the first and second waves on a provincial level during the first year of the COVID-19 pandemic, when neither virus variants were present in the country nor the vaccination campaign had started yet (42,43).

Methods

We downloaded publicly available COVID-19 data from the website of the Civil Protection Agency (44) and National Institute of Statistics (45), collecting daily data flow that Italian regions had to mandatorily provide with a provincial level of detail. In detail, we used the number of newly diagnosed infections with SARS-CoV-2 (corresponding to the new positive tests of infection based on quantitative reverse transcription polymerase chain reaction) and number of COVID-19 deaths in two time frames: from February 24-June 30, 2020 (first wave), and from September 1-December 31, 2020 (second wave). We also used data about anti-SARS-CoV-2 antibody seroprevalence recently made available at a provincial level by a survey carried out by the National Institute of Statistics in May-July 2020 (32). In order to take into account possible differences in time-frame between the first wave period and the seroprevalence survey, we also considered as alternative first wave period February 24-July 31, 2020.

We calculated the province-specific case-fatality rate, also called ratio (34,46), for the first and second waves by dividing the number of deaths by the number of diagnosed positive cases in the two periods February 24-June 30 and February 24-July 31, 2020. We then calculated the province-specific infection-fatality rate (34) by dividing the number of deaths occurred during the first wave (February 24-June 30, 2020) by the estimated number of seroprevalent subjects using data of the National Institute of Statistics carried out in the period May-July 2020 (32). We eventually computed the rate between deaths and positive molecular tests during the September 1-December 31 period, that we called ‘case/infection-fatality rate’ due to the hybrid nature of such indicator, whose denominator included asymptomatic and symptomatic SARS-CoV-2 infected cases due to nationwide marked changes in testing availability and policy (14). All these estimates were crude, i.e. unadjusted for age and sex.

Using data made publicly available by the European Center for Disease Control (ECDC), we also retrieved COVID-19 cases and deaths occurred in all European countries during the 2020, available on a weekly basis (47). As we did with Italian provinces, we calculated the case-fatality rate and the case/infection- fatality rate for the first and second waves, respectively. For this purpose, we considered as first wave the time from the beginning of the virus spread up to summer period (June 30, 2020) when cases waned in almost all countries (some countries experienced a unique wave in the 2020). The beginning of second wave was considered variable according to the raising of the curve up to the end of the year, generally January 1, 2021 based on the weekly availability of data (47).

We also compared data of fatality rate of COVID-19 with seasonal flu. We retrieved data of flu cases through reports released by the National Institute of Health (48), while we used annual flu deaths available from the National Institute of Statistics (49). We excluded the most recent years, taking into account the influence of the COVID-19 pandemic in the circulation of other airborne infections (50).

To investigate the relation between province-specific estimates, we used linear regression to fit a restricted cubic spline model with three knots at fixed percentiles (10th, 50th and 90th) of first wave distribution and weighted by the provincial population in 2020 (51). We used a multivariable model adjusted for aging index, percentage commuting outside the municipality of residence on a daily basis, and percentage of dwellings occupied by only one resident, available using 2011 census data of the National Institute of Statistics (51). We used the Stata statistical software (Version-17.0 Stata Corp., College Station-TX, 2021) for all analyses.

Results

Table 1 presents detailed information about number of cases and deaths divided by first and second waves along with seroprevalence data in the Italian provinces. In Italy, diagnosed cases and deaths during the first wave were 235,839 and 35,048, respectively. Corresponding values for the second wave were 1,808,260 cases and 40,392 deaths.

Table 1.

Number of SARS-CoV-2 cases, COVID-19 deaths, COVID-19 case-fatality rate (deaths/cases*100) in the first (1st) wave (February 24-June 30), and case/infection-fatality rate (deaths/cases*100) in the second (2nd) waves (September 30-December 31) in 2020 divided by province and region. SARS-CoV-2 seroprevalence (%) after the 1st wave (period May-July 2020) and infection-fatality rate (deaths/seroprevalents*100).

Region/Province Population Jan 1, 2020 Cases 1st wave Cases 2nd wave Seroprev. (%) Deaths 1st wave Deaths 2nd wave Case-fatality rate 1st wave Infection-fatality rate 1st wave Case/infection fatality rate 2nd wave
Aosta Valley 125501 1195 5771 3.72 145 239 12.1 3.1 4.1
Aosta 125501 1195 5771 3.72 145 239 12.1 3.1 4.1
Lombardy 10103969 91813 368273 7.35 16633 8321 18.1 2.2 2.3
Bergamo 1116384 14375 12873 24.3 3137 193 21.8 1.2 1.5
Brescia 1268455 15626 25468 7.63 2686 422 17.2 2.8 1.7
Como 603828 4093 29531 2.00 587 794 14.3 4.8 2.7
Cremona 358347 6612 7664 19.7 1130 123 17.1 1.6 1.6
Lecco 337087 2831 10303 6.66 481 236 17.0 2.1 2.3
Lodi 230607 3570 6936 7.10 679 140 19.0 4.1 2.0
Mantua 411062 3496 12260 6.57 684 288 19.6 2.5 2.3
Milan 3279944 24379 147720 3.95 4252 3197 17.4 3.3 2.2
Monza/Brianza 878267 5772 42090 4.52 979 895 17.0 2.5 2.1
Pavia 546515 5568 18869 5.95 1241 543 22.3 3.7 2.9
Sondrio 180941 1584 6954 5.30 212 201 13.4 2.2 2.9
Varese 892532 3907 47605 1.71 565 1289 14.5 3.7 2.7
Veneto 4907704 18937 227276 1.92 2028 4960 10.7 2.1 2.2
Belluno 201972 1191 13369 1.88 114 330 9.6 3.0 2.5
Padua 939672 3954 41651 2.32 318 608 8.0 1.5 1.5
Rovigo 233386 444 6932 2.39 36 204 8.1 0.6 2.9
Treviso 888309 2673 45715 1.89 322 783 12.0 1.9 1.7
Venice 851663 2682 35612 1.68 299 863 11.1 2.1 2.4
Verona 930339 5127 44073 2.23 586 1195 11.4 2.8 2.7
Vicenza 862363 2866 39924 1.33 353 977 12.3 3.1 2.4
Emilia-Romagna 4467118 28061 137052 2.90 4353 3431 15.5 3.4 2.5
Bologna 1017806 5229 32314 2.33 732 936 14.0 3.0 2.9
Ferrara 344840 1044 7886 0.72 173 222 16.6 7.0 2.8
Forlì-Cesena 394833 1740 10213 1.04 196 164 11.3 4.8 1.6
Modena 707292 3873 25945 1.10 480 601 12.4 6.2 2.3
Parma 453930 3657 8701 5.84 901 215 24.6 3.4 2.5
Piacenza 287236 4428 10187 9.54 956 252 21.6 3.5 2.5
Ravenna 389634 1030 11337 1.18 81 430 7.9 1.8 3.8
Reggio nell’Emilia 531751 4913 18248 4.45 581 306 11.8 2.5 1.7
Rimini 339796 2147 12221 2.79 253 305 11.8 2.9 2.5
Piedmont 4341375 30989 162730 3.45 4029 3537 13.0 2.7 2.2
Alessandria 419037 4063 13240 2.08 659 470 16.2 7.7 3.5
Asti 213216 1874 7960 2.13 249 217 13.3 5.5 2.7
Biella 174384 1046 5748 6.59 194 112 18.5 1.7 1.9
Cuneo 586568 2862 24081 0.87 373 494 13.0 7.3 2.1
Novara 368040 2792 12443 5.21 367 272 13.1 1.9 2.2
Turin 2252379 15889 87788 3.58 1844 1712 11.6 2.3 2.0
Verbano-Cusio-Ossola 157455 1140 5515 9.05 132 122 11.6 0.9 2.2
Vercelli 170296 1323 5955 3.52 211 138 15.9 3.5 2.3
Trentino-South Tyrol 1074819 7502 43303 3.19 693 1041 9.2 2.0 2.4
Bolzano 532080 2639 26559 2.95 288 504 10.9 1.8 1.9
Trento 542739 4863 16744 3.42 405 537 8.3 2.2 3.2
Friuli-Venezia Giulia 1211357 3308 45651 1.02 362 1426 10.9 2.9 3.1
Gorizia 139206 216 5904 0.12 5 104 2.3 -† 1.8
Pordenone 312619 702 9792 1.88 68 291 9.7 1.2 3.0
Trieste 233276 1393 9107 0.59 209 270 15.0 -† 3.0
Udine 526256 997 20848 0.93 80 761 8.0 1.6 3.7
Liguria 1543127 9473 46958 3.24 1563 1276 16.5 3.1 2.7
Genoa 835829 5573 29304 3.61 943 853 16.9 3.1 2.9
Imperia 213919 1494 4806 2.39 231 79 15.5 4.5 1.6
La Spezia 219196 860 7142 1.89 159 189 18.5 3.8 2.6
Savona 274183 1546 5706 3.83 230 155 14.9 2.2 2.7
Tuscany 3722729 9779 108429 0.90 1088 2491 11.1 3.3 2.3
Arezzo 341766 676 9779 1.23 47 168 7.0 1.1 1.7
Florence 1004298 3192 29864 0.53 401 839 12.6 7.5 2.8
Grosseto 220785 396 3708 1.18 28 73 7.1 1.1 2.0
Livorno 333509 477 8079 0.56 62 195 13.0 3.3 2.4
Lucca 388678 1351 11010 0.42 151 192 11.2 9.3 1.7
Massa and Carrara 193934 1051 6442 0.00 153 179 14.6 -‡ 2.8
Pisa 422310 930 15667 1.55 91 341 9.8 1.4 2.2
Pistoia 293059 747 9640 0.96 76 199 10.2 2.7 2.1
Prato 258152 532 9790 1.02 47 203 8.8 1.8 2.1
Siena 266238 427 4450 2.17 32 102 7.5 0.6 2.3
Umbria 880285 1385 26064 0.67 80 530 5.8 1.4 2.0
Perugia 655403 1008 19843 0.71 51 369 5.1 1.1 1.9
Terni 224882 377 6221 0.55 29 161 7.7 2.4 2.6
Marches 1518400 6549 33194 2.59 987 720 15.1 2.5 2.2
Ancona 469750 1875 9711 2.16 218 185 11.6 2.1 1.9
Ascoli Piceno 206363 290 4790 4.95 12 125 4.1 0.1 2.6
Fermo 173004 473 4337 2.16 67 69 14.2 1.0 1.6
Macerata 312146 1154 7851 2.16 145 159 12.6 2.2 2.0
Pesaro and Urbino 357137 2757 6505 4.95 545 182 19.8 3.1 2.8
Lazio 5865544 8010 148533 1.00 863 2815 10.8 1.4 1.9
Frosinone 485241 663 12990 0.19 79 162 11.9 8.6 1.2
Latina 576655 607 13625 0.50 44 294 7.2 1.5 2.2
Rieti 154232 411 4565 3.00 41 149 10.0 0.9 3.3
Rome 4333274 5872 108988 1.05 672 2016 11.4 1.4 1.8
Viterbo 316142 457 8365 1.52 27 194 5.9 0.6 2.3
Abruzzo 1305770 3261 31124 1.29 461 794 14.1 2.7 2.6
Chieti 383189 818 6284 1.40 131 136 16.0 2.4 2.2
L’Aquila 296491 225 10604 0.54 11 350 4.9 0.7 3.3
Pescara 318678 1586 5447 1.69 239 116 15.1 4.4 2.1
Teramo 307412 632 8789 1.48 80 192 12.7 1.8 2.2
Molise 302265 426 5971 0.81 28 175 6.6 1.1 2.9
Campobasso 218679 364 3829 0.66 22 110 6.0 1.4 2.9
Isernia 83586 62 2142 1.19 6 65 9.7 0.6 3.0
Campania 5785861 4648 182462 0.89 517 2915 11.1 1.0 1.6
Avellino 413926 552 8289 0.00 62 143 11.2 -‡ 1.7
Benevento 274080 209 4423 0.00 19 137 9.1 -‡ 3.1
Caserta 922171 543 33741 1.48 53 540 9.8 0.4 1.6
Naples 3082905 2652 111294 1.04 314 1811 11.8 1.0 1.6
Salerno 1092779 692 24715 0.31 69 284 10.0 2.1 1.1
Apulia 4008296 4502 84951 0.88 566 2037 12.6 1.6 2.4
Bari 1249246 1491 33237 1.50 153 636 10.3 0.8 1.9
Barletta-Andria-Trani 388390 380 10058 0.77 66 295 17.4 2.2 2.9
Brindisi 390456 659 5795 0.85 67 100 10.2 2.0 1.7
Foggia 616310 1170 18639 1.02 161 655 13.8 2.6 3.5
Lecce 791122 521 6420 0.01 85 114 16.3 -† 1.8
Taranto 572772 281 10802 0.67 34 237 12.1 0.9 2.2
Basilicata 556934 400 10055 0.72 36 214 9.0 0.9 2.1
Potenza 360936 189 6739 0.83 27 156 14.3 0.9 2.3
Matera 195998 211 3316 0.50 9 58 4.3 0.9 1.7
Calabria 1924701 1179 22191 0.51 129 368 10.9 1.3 1.7
Catanzaro 354851 214 3134 0.40 31 49 14.5 2.2 1.6
Cosenza 700385 468 6676 0.78 48 176 10.3 0.9 2.6
Crotone 170718 119 2065 0.11 10 35 8.4 5.2 1.7
Reggio di Calabria 541278 294 8586 0.18 29 81 9.9 3.1 0.9
Vibo Valentia 157469 84 1730 1.12 11 27 13.1 0.6 1.6
Sicily 4968410 3056 89352 0.37 342 2390 11.2 1.9 2.7
Agrigento 429611 135 3651 0.19 24 107 17.8 3.0 2.9
Caltanissetta 260779 186 3733 0.00 18 81 9.7 -‡ 2.2
Catania 1104974 779 26464 0.26 103 849 13.2 3.6 3.2
Enna 162368 438 2866 0.00 34 76 7.8 -‡ 2.7
Messina 620721 474 10246 0.32 59 136 12.4 2.9 1.3
Palermo 1243328 500 24929 0.89 43 665 8.6 0.4 2.7
Ragusa 321215 87 6490 0.30 6 161 6.9 0.6 2.5
Siracusa 397037 321 5112 0.14 47 162 14.6 8.8 3.2
Trapani 428377 136 5861 0.00 8 153 5.9 -‡ 2.6
Sardinia 1630474 1366 28920 0.50 145 712 10.6 1.8 2.5
Cagliari 430914 253 6573 0.38 19 161 7.5 1.2 2.4
Nuoro 206843 78 6055 0.24 12 123 15.4 2.4 2.0
Oristano 156078 61 2416 0.43 8 51 13.1 1.2 2.1
Sassari 489634 875 8997 0.78 90 247 10.3 2.4 2.7
South Sardinia 347005 99 4879 0.42 16 130 16.2 1.1 2.7
Italy 60244639 235839 1808260 2.49 35048 40392 14.9 2.2 2.2
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†Provinces excluded due to implausible data of seroprevalences since the estimated number of seroprevalent subjects are less than the number of positive cases at the end of the first wave. ‡Provinces excluded due to missing/null data about seroprevalence.

National average seroprevalence was 2.49%, with the highest values in Bergamo (24.3%), Cremona (19.7%), and Piacenza (9.5%). Six provinces (Avellino, Benevento, Caltanissetta, Enna, Massa-Carrara and Trapani) reported null seroprevalence, while three provinces, Lecce, Gorizia and Trieste, showed extremely low and implausible seroprevalence rates. We considered these latter provinces as unwarranted outliers arising from a low and potentially highly biased participation in the survey since the estimated number of seroprevalent subjects is lower than the ascertained cases during the first wave. For this reason, we removed these provinces from the analyses concerning the infection-fatality rate.

Figure 1 shows the case-fatality rate (from swab testing) and the infection-fatality rate (from seroprevalence data) in the first wave, and the case/infection-fatality rate (from swab testing) in the second wave across the Italian provinces. Overall in Italy, crude case-fatality rate was 14.9% for the first wave and 2.2% for the second wave, while the crude infection-fatality rate based on seroprevalence after the first wave was 2.2%. Province-specific values of case-fatality rate showed a median value of 12% (ranging from 2.3% in Gorizia to 24.6% in Parma), while the infection-fatality rate using seroprevalence data was much lower with a median value of 2.2%. During the second wave, SARS-CoV-2 testing greatly increased and was extended also to asymptomatic subjects, leading to a ‘mixed’ case/infection-fatality rate with median value of 2.2%, comparable to the infection fatality rate of 2.2% (Table 1).

Figure 1.

Figure 1.

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Crude case-fatality rate (deaths per 100 cases) for first wave (February 24-June 30, 2020), infection-fatality rate (deaths per 100 cases) after the first wave, and case/infection-fatality rate for the second (September 1-December 31, 2020) wave.

In Table 2 we report SARS-CoV-2 cases and COVID-19 deaths occurred in European countries in 2020 divided in the two pandemic waves, and the case-fatality and case/infection-fatality rates in European countries for the first and second waves, respectively. Overall, Italy showed one of the highest first-wave case-fatality rate (14.43%) along with other severely hit countries such as France (18.22%), Belgium (15.48), and UK (14.15%) compared to the value of EE/EEA area (10.59%) (Table 2 and Figure 2). In the majority of European countries, the second wave began from August to mid-September 2020, with some exceptions reporting an earlier onset in July, namely France, Spain, Malta, and Ukraine, with consequent difficulties in the comparison. Overall in 2020, the EE/EEA area showed a fatality rate of 2.38%, with the highest values reported by Bulgaria (3.78%), Greece (3.54%), and Italy (3.49%).

Table 2.

Crude case-fatality (deaths per 100 cases) for the first (1st) wave for all EU/EEA countries (+ Switzerland and United Kingdom) from the beginning of the pandemic to June 30 if not differently specified, and case/infection-fatality rate (deaths per 100 cases) for the second (2nd) wave. Time-frame is different with the begin of the second wave indicated for each country, while the end was January 3, 2021 for all countries.

Country Total population 2020† Cases 1st wave Deaths 1st wave Case-fatality 1st wave 2nd wave time-frame Cases 2nd wave Deaths 2nd wave Case/infection fatality 2nd wave Total 2020 cases Total 2020 deaths 2020 fatality
Andorra 76177 855 52 6.08 14 Sep 6848 31 0.45 8192 84 1.03
Austria 8901064 18269 706 3.86 14 Sep 331239 5497 1.66 364574 6253 1.72
Belgium 11522440 62394 9660 15.48 14 Sep 556759 9927 1.78 651968 19876 3.05
Bulgaria 6951482 5740 246 4.29 5 Oct 181464 6834 3.77 203051 7678 3.78
Croatia 4058165 3151 113 3.59 5 Oct 195299 3774 1.93 212958 4072 1.91
Cyprus 888005 1003 19 1.89 12 Oct 21988 106 0.48 23974 131 0.55
Czech Republic 10693939 12556 352 2.80 31 Aug 722615 12005 1.66 747003 12431 1.66
Denmark 5822763 12832 606 4.72 7 Sep 151164 747 0.49 168711 1374 0.81
Estonia 1328976 1993 63 3.16 23 Oct 25110 178 0.71 29521 251 0.85
Finland 5525292 7272 309 4.25 7 Sep 28628 289 1.01 36919 607 1.64
France 67320216 164068 29893 18.22 27 Jul 2457579 34845 1.42 2636772 65037 2.47
Germany 83166711 196554 9016 4.59 7 Sep 1524714 25249 1.66 1775513 34574 1.95
Greece 10718565 3519 192 5.46 10 Aug 134476 4745 3.53 140099 4957 3.54
Hungary 9769526 4183 589 14.08 31 Aug 322890 9363 2.90 328851 9977 3.03
Iceland 364134 1830 10 0.55 14 Sep 3589 19 0.53 5754 29 0.50
Ireland 4964440 25527 1741 6.82 7 Sep 72215 482 0.67 101887 2259 2.22
Italy 59641488 241611 34861 14.43 31 Aug 1887228 39855 2.11 2155446 75332 3.49
Latvia 1907675 1124 30 2.67 21 Sep 40972 644 1.57 42497 680 1.60
Liechtenstein 38747 84 1 1.19 5 Oct 2096 34 1.62 2222 35 1.58
Lithuania 2794090 1836 79 4.30 5 Oct 142802 1856 1.30 147987 1950 1.32
Luxembourg 626108 4522 110 2.43 14 Sep 39725 382 0.96 46919 506 1.08
Malta 514564 671 9 1.34 27 Jul 12520 208 1.66 13219 217 1.64
Monaco 39244 75 1 1.33 5 Oct 685 2 0.29 907 3 0.33
The Netherlands 17407585 50621 6127 12.10 31 Aug 750122 5383 0.72 820193 11598 1.41
Norway 5367580 8895 251 2.82 19 Oct 34579 171 0.49 50715 449 0.89
Poland 37958138 35950 1517 4.22 28 Sep 1235617 26729 2.16 1322947 29161 2.20
Portugal 10295909 43897 1614 3.68 7 Sep 371365 5356 1.44 431623 7196 1.67
Romania 19328838 28973 1750 6.04 21 Sep 527648 11544 2.19 640429 15979 2.50
San Marino 34453 698 42 6.02 12 Oct 1741 20 1.15 2493 62 2.49
Slovakia 5457873 1798 28 1.56 21 Sep 306848 2616 0.85 314117 2657 0.85
Slovenia 2095861 1700 111 6.53 7 Sep 122684 2761 2.25 125858 2891 2.30
Spain 47332614 251789 28388 11.27 6 Jul 1702891 22672 1.33 1958844 51078 2.61
Sweden 10327589 70612 5576 7.90 5 Oct 366858 4232 1.15 462661 10125 2.19
Switzerland 8606033 32184 1685 5.24 5 Oct 405397 5455 1.35 459660 7238 1.57
Ukraine 43733759 48500 1249 2.58 20 Jul 1015251 17369 1.71 1074093 18854 1.76
United Kingdom 68059863 287121 40632 14.15 7 Sep 2307627 33473 1.45 2654779 75024 2.83
EU/EEA countries 45309377 1264974 133967 10.59 - - - - 15963232 379360 2.38
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† Population data from Eurostat (47).

Figure 2.

Figure 2.

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Map and histograms of case-fatality and case/infection-fatality during the first and second waves in EU/EEA countries (+ Switzerland and United Kingdom).

In Table 3, we report data about cases of seasonal flu epidemics, and we computed an average case-fatality rate from past seasons of 0.01%, which is orders of magnitude lower of COVID-19 disease.

Table 3.

Number of influenza cases and deaths in Italy during the most recent seasonal flu epidemics.

Season Flu cases ISTAT report Flu deaths
2012/2013 5995000 2013 417
2013/2014 4542000 2014 272
2014/2015 6299000 2015 675
2015/2016 4876900 2016 316
2016/2017 5440900 2017 663
2017/2018 8677300 2018 745
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When we compared the case-fatality rate of the first wave with the infection-fatality rate after the first wave using seroprevalence data in the Italian provinces using the spline analysis (Figure 3), we found a substantially linear positive association up to approximately 12% of case-fatality rate in the first wave corresponding to 3.6 infection-fatality rate, while the curve flattened at higher values.

Figure 3.

Figure 3.

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Comparison of first wave case-fatality rate (using positive swab data to estimate COVID-19 cases) and infection-fatality rate (using May-June seroprevalence data to estimate infected cases) considering the time frames February 24-June 30, 2020 (A) and February 24-July 31, 2020 (B). Spline regression model adjusted for aging index, percentage commuting outside the municipality of residence on a daily basis, and percentage of dwellings occupied by only one resident.

In the spline regression model comparing case-fatality rate in the first wave with the case/infection-fatality rate in the second wave, we did not find any relation between the two variables. On average, the case-fatality rate was 5.6 times 95% CIs (95% CI 5.2-6.1) higher in the first compared to the second wave (Figure 4).

Figure 4.

Figure 4.

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Comparison of first and second wave case-fatality rate in a spline regression model adjusted for aging index, percentage commuting outside the municipality of residence on a daily basis, and percentage of dwellings occupied by only one resident.

Discussion

At the end 2020, Italy was one of the countries reporting the highest number of confirmed positive cases as well as COVID-19 deaths (52). Since many uncertainties still exist about the real impact and severity of COVID-19 pandemic (33,37,53,54), in the present investigation we provided an assessment of the COVID-19 case-fatality and infection-fatality rates during the 2020 in Italian provinces.

Overall, our data confirmed that during the first wave, when almost all subjects underwent SARS-CoV-2 testing due to presence of symptoms related to COVID-19, the Italian case-fatality rate was as high as around 15%, being much higher than the infection-fatality rate. Conversely, during the second wave, the case/infection fatality rate we could compute waned to a much lower value of 2.2%. The most plausible explanation for this discrepancy is the hybrid nature of the latter estimate, due to the different policy for SARS-CoV-2 infection assessment. In fact, during the first wave only suspected cases due to travelling from high risk countries or with symptoms suggesting of COVID-19 were tested (55), while during the second waves also asymptomatic cases underwent swab testing. These findings appear to be confirmed by the assessment of the infection-fatality rate estimated through seroprevalence data, almost identical to COVID-19 fatality during the second wave, with the same overall national value of 2.2%. In addition, the comparison of the COVID-19 fatality rates in other European countries demonstrated generally a higher case-fatality rate for Italy during the first wave, and a marked decrease during the second wave that could have been at least partially due to the increase of population screening with SARS-CoV-2 swab testing of a large proportion of asymptomatic individuals (55). However, since the availability of SARS-CoV-2 molecular testing increased all over Europe during the second wave, our results may also indicate that the severity of the disease and the spread of the infection decreased in Italy with time during 2020, as compared with the other European countries, for reasons possibly related to the higher severity of the first wave, such as a larger prevalence of immunity in the population, or the increased depletion of highly susceptible individuals due to the high first wave COVID-19 mortality (56-59).

Interestingly, our results are partially conflicting with data from a recent meta-analysis suggesting much lower value (2.7%) during the first wave in European region (33) but higher estimates for Italy with a mean value of 7.8% (median=8.58%) and range from 1.7% up to 14.5%. This high heterogeneity could be explained by the modality of case-fatality assessment among different studies. In particular, the lower value was reported from a study implementing modelling techniques, e.g. SEIR (Susceptible-Exposed-Infective-Recovered) model (60), as well as when based on incomplete data when the first wave was still ongoing (61). Conversely, studies using real and comprehensive data demonstrated similar or even higher estimates compared with the present study (62-64). Interestingly, a comparable pattern of discrepancies in the estimation of case-fatality rate can be noted also for other countries severely hit by the pandemic such as United Kingdom and France (33). For these reasons, despite such modelling demonstrated a high reliability in the prediction of pandemic tend/curves (65,66), the estimation of disease case-fatality was not so effective and reliable, also since that the number of infections and deaths may be affected by other determinants, in particular the advances in SARS-CoV-2 infection as well as COVID-19 diagnosis (67), and especially treatment (68-70).

The occurrence of a high case-fatality rate in Italy was not entirely unexpected, being explained by the demographic and health characteristics of the Italian population. Also, at the very beginning of the pandemic in Italy, a case-fatality rate of 7.2% was estimated by the National Institute of Health (71), much higher compared with the one reported in China (72). Indeed, COVID-19 demonstrated to be more severe and deadly in vulnerable individuals due to older age and/or comorbidities (73,74), leading to a higher mortality in older subjects (75). Similarly, our findings are consistent with the recent report of the National Institute of Statistics, as they found a slightly higher (sex and age-adjusted) case-fatality rate of 4.3% in the entire 2020 (52). Consistently with our findings, such analysis yielded a higher value in the first pandemic period (although based on a slightly different timeframe, February-May 2020), i.e. 6.6%, a lower value in June-September (1.5%), and again a slightly higher value in October (2.4%).

Results of the seroprevalence nationwide survey confirmed that some Northern Italy areas were heavily affected during the first wave (76), especially the provinces of Bergamo, Brescia, Lodi, Cremona in Lombardy region, and Piacenza and Parma in Emilia-Romagna region (14). Such provinces were those that experienced the highest decrease in the hybrid case/infection fatality rate we could compute for the second wave, consistently with a pattern we have documented for COVID-19 incidence (14).

Our results indicated that the case-fatality rate of COVID-19 was much higher as compared with influenza through 2020 and independently from the time period, indicating that COVID-19 should not be considered a simply flu-like syndrome (77,78), with much larger implications in terms of population and public health burden. This further confirms how relevant is the implementation of effective preventive medicine measures against SARS-CoV-2 infection and COVID-19 including but not limited to vaccination, also in the absence of most effective therapy for this disease (79). Finally, our findings are particularly relevant from a public health perspective since they highlight how different was the impact of the COVID-19 pandemic compared to the seasonal flu and other outbreaks, taking into account the number of affected people and deaths, the health care systems overload, and the psychological and economic burden (80-82).

Our study has some limitations. First, we used aggregated data at a provincial level, showing much higher level of geographical detail than the previous ‘regional’ analyses but still not entirely homogeneous in terms of population size characteristics, despite we tried to control for some potential confounders. In addition, we could not calculate sex- and age-standardized estimates, and therefore the comparison across different geographical areas must be made with caution (83).

Strengths of our analysis include the assessment of the COVID-19 severity during the first two pandemic waves when there was no circulation of virus variants (43), making unlikely this possible confounding related to differences in virus transmission and severity (84,85). Similarly, the vaccination campaign effectively began in January 2021 (86), thus not affecting the susceptibility of subjects and the reliability of our analysis.

Conclusions

Our findings demonstrate that COVID-19 severity in Italy, as assessed through either case-fatality or infection-fatality rates, has been much higher compared with other airborne infections like influenza, while being substantially similar to a few other Western European countries. They also indicate that COVID-19 case-fatality rate and infection fatality rate substantially differ, though such measures are difficult to assess, due to methodological issues and potential biases that can affect these estimates. An adequate assessment of COVID-19 severity may also be of major relevance to plan and test public health interventions aimed at curbing the spread of SARS-CoV-2 infection.

Conflict of interest:

Each author declares that he/she has no commercial associations (e.g. consultancies, stock ownership, equity interest, patent/licensing arrangement etc.) that might pose a conflict of interest in connection with the submitted article.

Funding:

This study was supported by grants UNIMORE FAR 2020 Interdisciplinare Linea FCRMO - Fondazione Cassa di Risparmio di Modena to Dr. Filippini, and FISR 2020-COVID19 by the Italian Ministry of the University and the Research to Dr. Vinceti.

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