Risk of SARS-CoV-2 Death is Low in Unvaccinated Individuals without Comorbidities

A person dying with an active diagnosis of SARS-CoV-2 is on average 78 years old and has four pre-existing conditions; adults less than 60 years old have on average three comorbidities when dying with SARS-CoV-2. This article estimates the risk of death posed by SARS-CoV-2 to individuals 16 to 59 years old without comorbidities and without vaccination against SARS-CoV-2.

Risk of SARS-CoV-2 in Adults

The analysis in this section is based on data by the Instituto Superiore di Sanità (ISS, [1]), a research institution supervised by the Italian Ministry of Health. The data was submitted autonomously by Italian hospitals before October 5, 2021, to the ISS. The data contains information about 7910 patients who died in hospitals. This article concerns itself with the calculation for risk of death given a diagnosed SARS-CoV-2 infection of an unvaccinated individual aged 16-59 years without comorbidities based on Table 2 in the Italian study. That is, the case fatality rate (CFR for short) is calculated. The CFR is not to be mistaken with the incidence fatality rate (IFR) which includes also non-diagnosed cases; the CFR is never larger than the IFR. For the purposes of this article, an adult is a person aged 16 to at most 59 years because this matches the age groups in the primary data source.

The data has a number of limitations:

  • Italian hospitals submitted data autonomously and their criteria for submission are not clear.
  • The data may not be representative of people infected with SARS-CoV-2 dying outside of hospitals.
  • The data does not distinguish between men and women; independent of age and comorbidities, men are at a noticeably higher risk to die from SARS-CoV-2.
  • The data in Table 2 does not contain information about the vaccination status.
  • The higher the age, the higher the SARS-CoV-2 risk of death. For example, in Figure 2 in [1] one can see that around two thirds of all deaths in the age group 10-59 are actually in the age group 50-59.

In an attempt to compensate for these shortcomings, this article aims to provide only an upper limit on the CFR.

The information that this article wants to uncover is the the probability of death given no comorbidities. According to Bayes' theorem, one must compute

p(D|C=0) = \frac{p(C=0|D) p(D)}{p(C=0)},

where p(X) is the probability of an event X, p(X | Y) is the conditional probability of X given Y, C denotes the number of comorbidities, and p(D) is the risk of death for an adult.

The data contains information about 54 dead persons without comorbidities. The data was gathered since the SARS-CoV-2 outbreak in Italy until October 2021. Hence, the data might include vaccinated and non-vaccinated persons. In the following we assume that all deaths occurred in non-vaccinated individuals because this article attempts to provide an upper limit on the CFR. Hence, the chance of a dead person having had no comorbidities is P(C=0|D) = \frac{54}{565} = 9.6\%.

For the probability of having no comorbidities, we take P(C=0) = 50\%; this is is the probability of having no comorbidities for a 60-year old person in Italy (the number is taken from Figure A.1, Panel 2 in [2]; the panel is missing in the final publication). The higher the age, the more likely it is to have comorbidities; using the estimate for elderly people will result in an overestimate of risk.

The probability of death P(D) can be directly computed from the number deaths and the number of diagnosed cases. The challenge with respect to this calculation is to find data that includes only unvaccinated adults. In general, the ISS is tracking this information (this data set is called COVID-19 ISS open data) but I did not find older versions of this data from before the Italian vaccination campaign started on December 27, 2020. For this reason, the data until March 20, 2021 from [3] will be used because by this date only 9% (5,241,725) of the population had received a first vaccine dose and 4% (2,434,964) the second dose, see the official government data; Alpha was still the dominant strain [4] meaning the vaccination was still effective at preventing symptomatic infection. Therefore, vaccinated individuals should have a smaller impact on the computed numbers. Delta causes more often symptomatic infections in non-vaccinated individuals but not necessarily more deaths [5]. Since it was not obvious how to acquire data for the age group 16-19, The data for the age group 20-59 is used instead of the age group 10-59 because risk of death is increasing with age leading to a risk overestimate. The table below shows the number of SARS-CoV-2 cases and deaths in Italian adults before March 21, 2021 and based on this data, p(D) = 0.24\%.

AgeCasesDeaths
20-29386,59890
30-39403,558188
40-49521,716849
50-59573,8003362
1,885,6724529
The number of diagnosed SARS-CoV-2 cases and deaths in Italy before March 21, 2021 [3].

Finally, one can calculate an estimate of the risk of death of a 16-59 year old person without comorbidities and without vaccination after being diagnosed with SARS-CoV-2. The risk estimate is

P(D|C=0) = \frac{9.6 \cdot 10^{-2} \cdot 2.4 \cdot 10^{-3}}{0.5} = 0.046%

or about 46 fatalities per 100,000 diagnosed cases.

Discussion

The authors of [6] compute the incidence fatality rate (the ratio of the number of deaths and the number of cases, diagnosed or not) and estimate it to be around 19 per 100,000 population for men 50-59 years old in high-income countries; men of all age groups have a higher SARS-CoV-2 risk than women and risk increases with age. The IFR should be lower than the CFR so this data point does not contradict the result above.

The table below attempts to provide an idea how severe the computed CFR is. This is difficult because of possible shortcomings of the data like non-representative samples, missing data (e.g., gender), under-counting, over-counting, confounding factors, or altogether different statistics (e.g., IFR instead of CFR). For example, in the case of influenza, a comparison is difficult because these virii are endemic and vaccines have existed for many years [7]. Nevertheless, SARS-CoV-2 does not seem to pose a major risk for young adults without comorbidities.

Cause/comorbidityDescriptionStatisticDeath rate per 100,000Source
VaricellaAdultsCFR21[8]
SARS-CoV-2Age group 16-59, no comorbiditiesCFR43(see above)
Influenza--CFR<100[9]
SARS-CoV-2Age group 20-29, men, no comorbiditiesIFR1.4Table 1 in [6]
SARS-CoV-2 vaccinationNot a risk signal2[10]
Road accident2019, Germany4[11]
Suicide2019, Germany11[12]
SARS-CoV-2Age group 50-59, men, no comorbiditiesIFR19Table 1 in [6]
SARS-CoV-2Age group 50-59, men, at least one comorbidityIFR787Table 1 in [6]
(All causes)2019, Germany1130[13]
CFR and IFR of various ailments without vaccination where applicable. The German population in 2019 was 83.09 millions [14] and the data from [6] refers to high-income countries (HICs).

Appendix

The first chapter of the Pink Book [15] contains an explanation of the terms immunity and vaccination (emphasis mine):

Immunity is the ability of the human body to tolerate the
presence of material indigenous to the body and to eliminate
foreign substances.

[...]

Active immunity is protection produced by a person’s own immune system. The immune system is stimulated by an antigen to produce antibody-mediated and cell-mediated immunity. Unlike passive immunity, which is temporary, active immunity usually lasts for many years, often for a lifetime.

[...]

Another way to produce active immunity is by vaccination. Vaccines contain antigens that stimulate the immune system to produce an immune response that is often similar to that produced by the natural infection. With vaccination, however, the recipient is not subjected to the disease and its potential complications.

[15], Chapter 1

References

    [1] SARS-CoV-2 positive deaths surveillance Group, "Characteristics of SARS-CoV-2 patients dying in Italy. Report based on available data on October 5th, 2021," Instituto Superiore Di Santina 2021.
    [BibTeX] [Download]
    @techreport{ISS-2021-10-20,
    author = {{SARS-CoV-2 positive deaths surveillance Group}},
    title = {Characteristics of SARS-CoV-2 patients dying in Italy. Report based on available data on October 5th, 2021},
    year = {2021},
    institution = {Instituto Superiore Di Santina},
    url = {https://www.epicentro.iss.it/en/coronavirus/bollettino/Report-COVID-2019_5_october_2021.pdf},
    urldate = {2021-12-04},
    }
    [2] S. Ghisolfi, I. Almås, J. C. Sandefur, T. von Carnap, J. Heitner, and T. Bold, Predicted COVID-19 fatality rates based on age, sex, comorbidities and health system capacity, 2020.
    [BibTeX] [Download]
    @misc{GhisolfiAS2020_preprint,
    author = {Ghisolfi, Selene and Alm{\aa}s, Ingvild and Sandefur, Justin C. and von Carnap, Tillman and Heitner, Jesse and Bold, Tessa},
    title = {Predicted {COVID-19} fatality rates based on age, sex, comorbidities and health system capacity},
    year = {2020},
    url = {https://www.medrxiv.org/content/10.1101/2020.06.05.20123489v1},
    urldate = {2021-12-11},
    note = {Preprint},
    }
    [3] G. Calafiore and G. Fracastoro, COVID-19 case data for Italy stratified by age class, 2021.
    [BibTeX] [Download]
    @misc{CalafioreF2021,
    author = {Giuseppe Calafiore and Giulia Fracastoro},
    title = {{COVID-19} case data for Italy stratified by age class},
    year = {2021},
    url = {https://arxiv.org/abs/2104.06199},
    urldate = {2021-12-28},
    }
    [4] P. Stefanelli, A. L. Presti, L. Ambrosio, A. D. Martino, S. Morabito, G. Vaccari, I. Di Bartolo, A. Knijn, F. Riccardo, D. Petrone, M. Spuri, A. Bella, and P. Pezzotti, "Prevalenza e distribuzione delle varianti del virus SARS-CoV-2 di interesse per la sanitá pubblica in Italia," Instituto Superiore Di Santina 2021.
    [BibTeX] [Download]
    @techreport{ISS-2021-06-11,
    author = {Paola Stefanelli and Alessandra Lo Presti and Luigina Ambrosio and Angela Di Martino and Stefano Morabito and Gabriele Vaccari and Di Bartolo, Ilaria and Arnold Knijn and Flavia Riccardo and Daniele Petrone and Matteo Spuri and Antonino Bella and Patrizio Pezzotti},
    title = {Prevalenza e distribuzione delle varianti del virus SARS-CoV-2 di interesse per la sanit\'{a} pubblica in Italia},
    note = {Rapporto n. 2 dell'11 guigno 2021},
    year = {2021},
    institution = {Instituto Superiore Di Santina},
    url = {https://www.epicentro.iss.it/coronavirus/pdf/sars-cov-2-monitoraggio-varianti-rapporti-periodici-11-giugno-2021.pdf},
    urldate = {2021-12-28},
    }
    [5] D. Loconsole, F. Centrone, C. Morcavallo, S. Campanella, M. Accogli, A. Sallustio, D. Peccarisi, A. Stufano, P. Lovreglio, and M. Chironna, "Changing Features of COVID-19: Characteristics of Infections with the SARS-CoV-2 Delta (B.1.617.2) and Alpha (B.1.1.7) Variants in Southern Italy," Vaccines, vol. 9, iss. 11, 2021. doi:10.3390/vaccines9111354
    [BibTeX]
    @article{LoconsoleCM2021,
    author = {Daniela Loconsole and Francesca Centrone and Caterina Morcavallo and Silvia Campanella and Marisa Accogli and Anna Sallustio and Davide Peccarisi and Angela Stufano and Piero Lovreglio and Maria Chironna},
    title = {Changing Features of {COVID-19}: Characteristics of Infections with the {SARS-CoV-2} {D}elta ({B.1.617.2}) and {A}lpha ({B.1.1.7}) Variants in Southern Italy},
    year = {2021},
    journal = {Vaccines},
    volume = {9},
    number = {11},
    doi = {10.3390/vaccines9111354},
    }
    [6] S. Ghisolfi, I. Almås, J. C. Sandefur, T. von Carnap, J. Heitner, and T. Bold, "Predicted COVID-19 fatality rates based on age, sex, comorbidities and health system capacity," BMJ Global Health, vol. 5, iss. 9, 2020. doi:10.1136/bmjgh-2020-003094
    [BibTeX] [Download]
    @article{GhisolfiAS2020,
    author = {Ghisolfi, Selene and Alm{\aa}s, Ingvild and Sandefur, Justin C. and von Carnap, Tillman and Heitner, Jesse and Bold, Tessa},
    title = {Predicted {COVID-19} fatality rates based on age, sex, comorbidities and health system capacity},
    year = {2020},
    journal = {BMJ Global Health},
    volume = {5},
    number = {9},
    doi = {10.1136/bmjgh-2020-003094},
    url = {https://gh.bmj.com/content/5/9/e003094},
    urldate = {2021-12-26},
    }
    [7] M. Papadakis, "Why comparing coronavirus disease 2019 (COVID-19) and seasonal influenza fatality rates is like comparing apples to pears," Infection Control & Hospital Epidemiology, 2021. doi:10.1017/ice.2021.140
    [BibTeX]
    @article{Papadakis2021,
    author = {Papadakis, Marios},
    title = {Why comparing coronavirus disease 2019 (COVID-19) and seasonal influenza fatality rates is like comparing apples to pears},
    year = {2021},
    journal={Infection Control \& Hospital Epidemiology},
    doi = {10.1017/ice.2021.140},
    publisher={Cambridge University Press},
    note = {Letter to the Editor},
    }
    [8] A. Lopez, T. Harrington, and M. Marin, "Varicella," in Epidemology and Prevention of Vaccine-Preventable Diseases, 14 ed., E. Hall, P. A. Wodi, J. Hamborsky, V. Morelli, and S. Schillie, Eds., Public Health Foundation, 2021.
    [BibTeX] [Download]
    @inbook{LopezHM2021,
    author = {Adriana Lopez and Theresa Harrington and Mona Marin},
    title = {Varicella},
    editor = {Elisha Hall and Wodi, A. Patricia and Jennifer Hamborsky and Valerie Morelli and Sarah Schillie},
    booktitle = {Epidemology and Prevention of Vaccine-Preventable Diseases},
    edition = {14},
    year = {2021},
    institution = {Centers for Disease Control and Prevention},
    publisher = {Public Health Foundation},
    location = {Washington, D.C., USA},
    note = {The Pink Book},
    url = {https://www.cdc.gov/vaccines/pubs/pinkbook/downloads/varicella.pdf},
    }
    [9] J. K. Taubenberger and D. M. Morens, "1918 Influenza: the Mother of All Pandemics," Emerging Infectious Diseases, vol. 12, iss. 1, 2006. doi:10.3201/eid1201.050979
    [BibTeX]
    @article{TaubenbergerM2006,
    author = {Jeffery K. Taubenberger and David M. Morens},
    title = {1918 Influenza: the Mother of All Pandemics},
    year = {2006},
    journal = {Emerging Infectious Diseases},
    volume = {12},
    number = {1},
    doi = {10.3201/eid1201.050979},
    }
    [10] Paul-Ehrlich-Institut, "Sicherheitsbericht. Verdachtsfälle von Nebenwirkungen und Impfkomplikationen nach Impfung zum Schutz vor COVID-19 seit Beginn der Impfkampagne am 27.12.2020 bis zum 30.11.2021," 2021.
    [BibTeX] [Download]
    @techreport{PEI20211223,
    author = {{Paul-Ehrlich-Institut}},
    title = {Sicherheitsbericht. Verdachtsf\"{a}lle von Nebenwirkungen und Impfkomplikationen nach Impfung zum Schutz vor {COVID-19} seit Beginn der Impfkampagne am 27.12.2020 bis zum 30.11.2021},
    year = {2021},
    url = {https://www.pei.de/SharedDocs/Downloads/DE/newsroom/dossiers/sicherheitsberichte/sicherheitsbericht-27-12-20-bis-30-11-21.pdf?__blob=publicationFile&v=7},
    urldate = {2021-12-27},
    note = {In German},
    }
    [11] Statistisches Bundesamt, 6,6% weniger Verkehrstote im Jahr 2019. Pressemitteilung Nr. 061 vom 27. Februar 2020, 2020.
    [BibTeX] [Download]
    @misc{DestatisPR061,
    author = {{Statistisches Bundesamt}},
    title = {{6,6}% weniger Verkehrstote im Jahr 2019. Pressemitteilung Nr. 061 vom 27. Februar 2020},
    year = {2020},
    url = {https://www.destatis.de/DE/Presse/Pressemitteilungen/2020/02/PD20_061_46241.html},
    urldate = {2021-12-25},
    }
    [12] H. Müller-Pein, "Suizide in Deutschland 2020," Deutsche Gesellschaft für Suizidprävention 2021.
    [BibTeX] [Download]
    @techreport{Naspro2020,
    author = {M\"{u}ller-Pein, Hannah},
    title = {Suizide in Deutschland 2020},
    titleaddon = {Nationales Suizidpr\"{a}ventionsprogramm f\"{u}r Deutschland},
    year = {2021},
    institution = {Deutsche Gesellschaft f\"{u}r Suizidpr\"{a}vention},
    url = {www.naspro.de/dl/Suizidzahlen2020.pdf},
    urldate = {2021-10-26},
    note = {Last updated November 2021; in German},
    }
    [13] Statista, Sterberate in Deutschland in den Jahren von 1950 bis 2020, 2021.
    [BibTeX] [Download]
    @misc{Statista1013303,
    author = {Statista},
    title = {Sterberate in Deutschland in den Jahren von 1950 bis 2020},
    year = {2021},
    url = {https://de.statista.com/statistik/daten/studie/1013303/umfrage/sterberate-in-deutschland/},
    urldate = {2021-12-25},
    note = {In German},
    }
    [14] Statista, Germany: Total population from 2016 to 2026, 2021.
    [BibTeX] [Download]
    @misc{Statista624170,
    author = {Statista},
    title = {Germany: Total population from 2016 to 2026},
    year = {2021},
    url = {https://www.statista.com/statistics/624170/total-population-of-germany/},
    urldate = {2021-12-27},
    }
    [15] Epidemology and Prevention of Vaccine-Preventable Diseases, 14 ed., E. Hall, P. A. Wodi, J. Hamborsky, V. Morelli, and S. Schillie, Eds., Public Health Foundation, 2021.
    [BibTeX] [Download]
    @book{PinkBook2021,
    editor = {Elisha Hall and Wodi, A. Patricia and Jennifer Hamborsky and Valerie Morelli and Sarah Schillie},
    title = {Epidemology and Prevention of Vaccine-Preventable Diseases},
    edition = {14},
    year = {2021},
    institution = {Centers for Disease Control and Prevention},
    publisher = {Public Health Foundation},
    location = {Washington, D.C., USA},
    note = {The Pink Book},
    url = {https://www.cdc.gov/vaccines/pubs/pinkbook/},
    }