Literature DB >> 36038407

Short-term mortality following COVID-19 vaccination in Bologna, Italy: a one-year study.

Elisa Stivanello1, Chiara Beghelli2, Francesco Cardoni3, Chiara Giansante4, Paolo Marzaroli5, Muriel Assunta Musti6, Vincenza Perlangeli7, Renato Todeschini8, Paolo Pandolfi9.   

Abstract

The main objective of the study is to assess whether there is an increased risk of mortality in the days following the administration of COVID-19 vaccines in Bologna Health Authority in the first year of COVID-19 vaccination campaign. A secondary objective was to describe causes of deaths occurred in the days after vaccination. We conducted a retrospective observational study on all residents of Bologna Health Authority who received at least one COVID-19 vaccination dose from December 27, 2020 to December 31, 2021 and compared mortality in the 3, 7, 14 30 days after vaccination (risk interval) with the mortality in the period of the same length (3, 7, 14 and 30 days) beyond the 30th day after the last dose of vaccination (control interval). The cohort included 717,538 people. The mortality rate was 2.24 per 100 person-years during the 30 days risk interval vs 2.72 in the control interval with an adjusted incidence rate ratio equal to 0.76 (95% CI: 0.70-0.83, p < 0.001). The risk of mortality is significantly lower (p < 0.001) also in the 3, 7, 14 days risk intervals than in the control intervals. This study shows that there is no increase in mortality in the short-term period after COVID-19 vaccines.
Copyright © 2022 Elsevier Ltd. All rights reserved.

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Keywords:  COVID-19; Mortality; Safety; Vaccination

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Year:  2022        PMID: 36038407      PMCID: PMC9393158          DOI: 10.1016/j.vaccine.2022.08.039

Source DB:  PubMed          Journal:  Vaccine        ISSN: 0264-410X            Impact factor:   4.169


Introduction

Since the emergence of COVID-19, the world has taken significant measures to cope with this disease. Global efforts have been made to develop different vaccines to curb the pandemic [1] and after less than a year from the start of the pandemic, multiple vaccines were developed. Between the end of 2020 and the beginning of 2021, several of them received emergency use approval by the Food and Drug Administration and conditional marketing authorization by the European Medicines Agency. Both mRNA (BNT162b2, Pfizer-BioNtech and mRNA-1273, Moderna) and AdenoVirus vaccines (ChAdOx1-S, Oxford/Astrazeneca and Ad26 CoV2-S, Johnson & Johnson) proved to be highly effective and safe in large randomized phase 3 clinical trials [2], [3], [4], [5]. However, rare outcomes associated with vaccines may not appear from the phase 3 trials because of the lack of sufficient power, because of the short follow up time of the studies and because the population included may differ from the population receiving the vaccine. For the same reasons, fatal events associated to vaccination may remain undisclosed in the premarket trial. At the same time, with the large vaccination campaign there are inevitably some cases whose death is close in time to their COVID-19 vaccine, raising questions on a possible relation between death and recent vaccination. These concurrent events receive great resonance in the media, generating suspicion and concerns in the population [6], [7] that likely attribute a causal link between the two events. Thus, monitoring vaccine safety is of utmost importance to protect the intended population and to reduce fears which might otherwise reduce vaccination adherence [8] and contribute to vaccine hesitancy [6], [7]. Various surveillance systems in different countries have been monitoring vaccination safety since the beginning of the vaccination campaign and by now have received numerous reports of fatal events occurring after vaccination although they mostly did not result to be correlated to vaccination [9], [10], [11], [12] in post-mortem investigation. Causal relationship was established only in very rare cases, such as for deaths linked to thrombotic events [13], [14]. However, besides surveillance systems and a few post-mortem investigation reports [13], evidence on the risk of mortality after vaccination is scanty. Until now, few studies have been conducted to assess whether mortality is increased following COVID-19 vaccination [15], [16], [17]. We conducted a study with the main objective of assessing whether there is an increased risk of mortality in the days following the administration of COVID-19 vaccines in the population of Bologna Health Authority from December 27, 2020 to December 31, 2021. A secondary objective was to describe the characteristics of deaths and causes of death occurred after vaccination.

Methods

Study design setting and population

We conducted a retrospective cohort study in the vaccinated population of Bologna Health Authority (BHA). BHA is the local health care organization in charge of prevention and care of the population (about 890,000 inhabitants) living in a territory situated in Northern Italy which comprises Bologna Municipality, the main town, and other 44 municipalities. In BHA, as elsewhere in Italy, COVID-19 vaccination campaign started on December 27, 2020 and addressed first health care workers, the elderly and the frailest subjects and later was gradually extended in a schedule based primarily on age. Since December 2021 also 5–11 years old children were included as potential beneficiary of the vaccination. BNT162b2 was the first vaccine to be authorized, but shortly afterward also mRNA-1273 and ChAdOx1-S were available. Ad26 CoV2-S was authorized mid-March. Apart from some age criteria associated with the use of ChAdOx1-S, the choice of which vaccine to administer depended mainly on the product availability and for this reason BNT162b2 was the most frequently distributed. Nevertheless, due to lighter conservation requirements mRNA-1273 was preferred by general practitioners, for home administration and by nursing homes, whereas the Public Health Department that was in charge of the distribution of vaccines to the general population used mainly BNT162b2. We included all residents who received at least one dose of any COVID-19 vaccine authorized in Italy from December 27, 2020 to December 31, 2021. We excluded residents that moved to municipalities of other health authorities because of the uncertainty regarding their life status. The study population was identified by using the BHA COVID-19 Vaccination registry. This is a locally based register that contains information about type of vaccine, number of doses, dates and venue of administration for all subjects that received a dose of vaccine in the BHA area.

Exposure period

Participants were followed from the date of their last vaccination (day 1) for 60 days or to the date of death or to December 31, 2021 whichever occurred first. The follow-up period of each participant was divided in risk intervals and non-risk intervals (i.e. control intervals). We considered as risk interval the period within 3, 7, 14 and 30 days from day 1 and as control interval the period of the same length (3, 7, 14 and 30 days) of follow-up beyond the 30th day after the last dose of vaccination. We considered the last dose of the vaccine, assuming that the short-term mortality did not depend on the number of doses.

Outcomes and additional variables

The main outcome of the study was death from all causes. Deaths were identified by using Bologna’s Causes of Death Registry which covers all the deaths of the residents of the BHA catchment area and provides information about socio-demographic characteristics and on date, place, circumstances and initial cause of death. The cause of death derives from information recorded in the medical section of the death certificate and is classified according to the tenth revision of the ICD (International Classification of Diseases) and coded according to the WHO rules. All information is collected following national protocols. At the time of the study, the collection of all deaths that occurred during the study year, was considered complete. We also collected additional variables to characterise the study population and/or to consider as confounders. In particular, we retrieved comorbidities of the previous two years (cardiovascular, cerebrovascular, respiratory system diseases, tumors, diabetes, hypertension, Parkinson, dementia, mental health disorders, renal failure) of the population from the local frailty database which, in turn derives from hospital discharge records, exemption and pharmaceutical archives of 2019 and 2020. This database was also used to retrieve the frailty index. The index is obtained from a multiple predictive model and is attributed to each adult resident in BHA predicting the probability of urgent hospitalization or death in the following year [18]. It ranges from 0 to 100 and is categorized into 5 classes of frailty: very low (0–5.99), low (6–29.99), medium (30–49.99), high (50–79.99), and very high (80–100). The frailty index database is available only for 18+ residents. Information about SARS-CoV-2 infection was retrieved from a local surveillance database which contains demographic, clinical and epidemiological characteristics of all confirmed cases of SARS-CoV-2 infection in the BHA area. At the time of the study, confirmation of SARS-CoV-2 cases required a RT-PCR test using an oral and/or nasopharyngeal swab. All archives were linked with the BHA COVID-19 Vaccination registry by using the fiscal code, a unique identification code that is provided to all Italian citizens.

Ethics statement

This is a retrospective observational study where no new diagnostic tool or drug treatment was provided to any participant to conduct this study. Participant data were collected as part of standard public health surveillance activities. In accordance to Italian laws about personal data, informed consent was not required because unfeasible given the large sample size. Data were anonymized prior to the analyses after database linkage was done. Only one author conducting database linkage had access to patients identifying information.

Statistical analysis

We computed frequencies of baseline characteristics of the study population and cases. For each risk interval we calculated the rate of mortality and compared with the corresponding control interval rate. We estimated raw and adjusted IRRs (incidence rate ratio) with 95% confidence interval (CI). Adjusted estimates were obtained by applying a multivariable Poisson regression model. The model included: age class (<18, 18–40, 41–64, 65–74, 75–80, 81–84, 85–90, >90 years), day of week and period of vaccination. The study period was divided in three periods (27 December 2020–30 April 2021; 1 May- 31 August 2021 and 1 September-31 December 2021) to take account of differences in mortality across the year; each subject was attributed a period according to the date of the last dose. In a secondary step we conducted a stratified analysis where a multivariable Poisson regression model was run also by gender, age class, type of vaccine, and excluding patients with a SARS-CoV-2 infection. The model included the same covariates as the main model, except for age which was continuous in the stratified analyses by age class. We replicated the analyses also after excluding all subjects that had a diagnosis of SARS-CoV-2 infection during the follow-up period because a protective effect of vaccination for COVID-19-related deaths was expected beyond the first week from the administration. In addition, the analyses were repeated in the adult (>18 years old) population using a model with frailty index, day of week and period of vaccination as covariates. All analyses were performed using STATA 16.1, Texas USA software.

Results

Between December 27, 2020 and December 31, 2021, 717,538 subjects resident in BHA received at least one dose of one of the authorized vaccines against COVID-19. Table 1 shows the main demographic characteristics of the study populations and the type of vaccine that was administered as last dose.
Table 1

Demographic and clinical characteristics of the study population.

Study population
No.%
Total717,538100
Sex
F370,81351.68
M346,72548.32
Age group (years)
0–1744,4556.20
18–40186,38625.98
41–64280,96539.16
65–7490,69012.64
75–8475,62310.54
>8439,4195.49
Citizenship
Italian645,60089.97
Non italian71,93810.03
Comorbidities (previous two years)*
Cardiovascular diseases50,1577.69
Tumours93,94214.41
Diabetes50,9667.82
Hypertension63,8729.79
Cerebrovascular diseases20,4173.13
Parkinson9,7291.49
Dementia6,6321.02
Mental health disorders17,4692.68
Diseases of the respiratory system22,5223.45
Renal failure9,5211.46
SARS-CoV-2 infection4,6190.64
Frailty class*
Very low472,81572.50
Low144,40122.14
Medium22,3203.42
High11,2441.72
Very high1,3650.21
Type of vaccine*
ChAdOx1-S23,5583.28
Ad26 CoV2-S5,5570.77
mRNA-1273260,40936.30
BNT162b2427,94359.65

Information not available for all.

Demographic and clinical characteristics of the study population. Information not available for all. During the follow-up period there have been 1152 deaths in the 30 days risk interval and 1015 in the 30 days control interval. Table 2 shows the main demographic and clinical characteristics and type of vaccine of the deaths. Deaths of risk and control intervals were mostly females and aged 85 or over. The most frequent comorbidities were tumours followed by cardiovascular diseases in deaths during the 31–60 days control period, whereas in deaths that occurred during risk intervals the ranking was reversed with 44% of people with cardiovascular diseases among the deaths in the 3 days risk interval. In regards to type of vaccine, we found that the most frequent vaccine was BNT162b2 in all risk and control intervals, mRNA-1273 was the second most frequent vaccine reaching 36.06 and 43.94% in the 7 and 3 days risk intervals.
Table 2

Demographic, clinical characteristics and vaccine administered of deaths occurred during risk and non-risk intervals.

Control interval
Risk interval
Follow up period31–60 days
1–30 days
1–14 days
1–7 days
1–3 days
No.%No.%No.%No.%No.%
Total1,0151001,15210048710020810066100
Sex
Female53352.5161553.3926955.2412158.173553.03
Male48247.4953746.6121844.768741.833146.97
Age group (years)
0–17010.0910.2110.480
18–4080.7980.6961.2331.4411.52
41–64605.91716.16224.5294.3323.03
65–7410310.151079.29469.45209.6257.58
75–8428227.7832328.0413427.526028.852030.30
>8456255.3764255.7327857.0811555.293857.58
Citizenship
Italian1,00398.821,14299.1348298.9720498.086598.48
Non italian121.18100.8751.0341.9211.52
Civic status
Single989.7012811.185210.742813.5957.69
Married40940.5041936.5916534.097938.352741.54
Widowed47146.6355348.3024550.629546.123147.69
Divorced323.17453.93224.5541.9423.08
Education
University525.58595.53235.07594.6611.56
High school12513.4113012.186013.223015.541117.19
Secondary school28530.5835533.2714732.386131.611625.00
Primary school47050.4352349.0222449.349348.193656.25
Comorbidities (previous two years)*
Cardiovascular diseases35635.2842937.5718137.637335.612843.75
Tumours37236.8737432.7515933.066732.682437.50
Diabetes22422.2028124.6112024.955828.291726.56
Hypertension34033.7035531.0915231.606531.712132.81
Cerebrovascular diseases23222.9924621.5410020.794722.931421.88
Parkinson10510.41978.49387.90199.2723.13
Dementia16516.3520417.868317.264120.001015.63
Mental health disorders393.87363.15102.0841.950
Diseases of the respiratory system15915.7619517.088016.634120.001523.44
Renal failure12812.6916614.547214.973617.561015.63
SARS-CoV-2 infection636.241099.46346.9862.8811.52
Frailty class*
Very low545.35514.47204.1694.3934.69
Low37236.8740235.2017837.017335.612234.38
Medium28628.3433429.2513227.445627.321320.31
High25224.9828625.0412325.575225.372132.81
Very high454.46696.04285.82157.3257.81
Type of vaccine
ChAdOx1-S363.57211.8261.2310.4811.52
Ad26 CoV2-S20.2020.1710.2110.480
mRNA-127326726.4633629.1715832.447536.062943.94
BNT162b271070.3779368.8432266.1213162.983654.55

Information not available for all.

Demographic, clinical characteristics and vaccine administered of deaths occurred during risk and non-risk intervals. Information not available for all. There were some differences in the distribution of frail subjects, with more subjects with very high or high frailty in deaths occurred in the 1–3 days risk interval in comparison with deaths occurred during other intervals. The mortality rate was 2.24 per 100 person-years during the 1–30 days risk interval and was 2.72 per 100 in the 31–60 days control interval (Table 3 ) with an unadjusted incidence rate ratio (IRR) equal to 0.83 (95% CI: 0.76–0.90, p < 0.0001) (Table 4 ). Similar IRR (0.75, 95% CI: 0.69–0.82, p < 0.0001) was observed in the sample where all SARS-CoV-2 infections that occurred after vaccination were excluded with rates of 2.04 and 2.56 per 100 person-years in the 1–30 days risk and the 31–60 days control period respectively. As Table 3 shows, for any length of follow-up period the risk interval had lower mortality rate than the 31–60 days control interval.
Table 3

Deaths, person-years and mortality rate × 100 during the risk and control intervals, with 95% confidence interval (CI) by follow-up period in all study population and after excluding subjects who had a confirmed SARS-CoV-2 infection after vaccination.

n. deathsPerson-yearsRate × 100 person-years95 %CI
All study population
Control interval 31–60 days1,01537,3582.722.552.89
Risk interval 1–30 days1,15251,3382.242.122.38
1–14 days48727,3291.781.631.95
1–7 days20815,1301.371.191.57
1–3 days665,8361.130.871.44



After excluding people with a SARS-CoV-2 infection after vaccination
Control interval 31–60 days95237,1572.562.402.73
Risk interval 1–30 days1,04351,0082.041.922.17
1–14 days45327,1491.671.521.83
1–7 days20215,0291.341.171.54
1–3 days655,7981.120.871.43
Table 4

Incident rate ratio (IRR) and relative 95% confidence interval (CI) by follow-up period and sex, age class and vaccine type and after excluding subjects that had a confirmed SARS-CoV-2 infection after vaccination.

Population/SubgroupIRR95 %CIp-value
1–30 days vs 31–60 days
Unadjusted estimateOverall0.830.760.90<0.0001
Adjusted estimates*Overall0.760.700.830.0001
Sex
Female0.790.700.890.0001
Male0.730.640.82<0.0001
Age group (years)
<65$0.810.581.120.1926
65–740.530.400.71<0.0001
75–840.640.540.76<0.0001
>840.830.740.940.0024
Vaccine type
ChAdOx1-S0.300.160.540.0001
Ad26 CoV2-S0.580.074.590.6055
mRNA-12730.770.650.910.0018
BNT162b20.760.680.84<0.0001
Excluding SARS-CoV-2 infection0.750.690.82<0.0001



1–14 days vs 31–44 days
Unadjusted estimateOverall0.630.560.71<0.0001
Adjusted estimates*Overall0.620.550.70<0.0001
Sex
Female0.670.560.790.0001
Male0.570.470.68<0.0001
Age group (years)
<65$0.580.350.960.0357
65–740.440.290.660.0001
75–840.500.390.64<0.0001
>840.700.600.83<0.0001
Vaccine type
ChAdOx1-S0.170.060.450.0004
Ad26 CoV2-S0.250.016.840.3755
mRNA-12730.670.530.850.0014
BNT162b20.600.510.70<0.0001
Excluding SARS-CoV-2 infection0.630.550.72<0.0001



1–7 days vs 31–37 days
Unadjusted estimateOverall0.500.420.60<0.0001
Adjusted estimates*Overall0.500.420.60<0.0001
Sex
Female0.600.470.760.0001
Male0.410.320.54<0.0001
Age group (years)
<65$0.440.220.880.0204
65–740.410.220.740.0031
75–840.380.270.53<0.0001
>840.590.460.76<0.0001
Vaccine type
ChAdOx1-S0.100.010.810.0347
Ad26 CoV2-S0.100.010.810.0347
mRNA-12730.600.430.830.0033
BNT162b20.460.370.58<0.0001
Excluding SARS-CoV-2 infection0.540.450.65<0.0001



1–3 days vs 31–33 days
Unadjusted estimateOverall0.410.290.56<0.0001
Adjusted estimates*Overall0.380.280.52<0.0001
Sex
Female0.440.290.680.0002
Male0.340.220.52<0.0001
Age group (years)
<65$0.340.091.380.1310
65–740.240.080.710.0094
75–840.230.130.40<0.0001
>840.530.350.810.0036
Vaccine type
ChAdOx1-S0.130.021.100.0676
Ad26 CoV2-S0.130.021.100.0676
mRNA-12730.760.431.330.3562
BNT162b20.290.190.43<0.0001
Excluding SARS-CoV-2 infection0.430.310.59<0.0001

Adjusted for age, day of week and period of vaccination.

Age class 18–40 and 41–64 are grouped to increase the number of events.

Deaths, person-years and mortality rate × 100 during the risk and control intervals, with 95% confidence interval (CI) by follow-up period in all study population and after excluding subjects who had a confirmed SARS-CoV-2 infection after vaccination. Incident rate ratio (IRR) and relative 95% confidence interval (CI) by follow-up period and sex, age class and vaccine type and after excluding subjects that had a confirmed SARS-CoV-2 infection after vaccination. Adjusted for age, day of week and period of vaccination. Age class 18–40 and 41–64 are grouped to increase the number of events. The adjusted risk of mortality is significantly lower in all risk intervals than in the control intervals (p < 0.001) (Table 4). When replicating the analyses by different strata, the IRR is significantly below 1 in both sexes, in all age groups except for the <65 years old group (30 and 3 days risk interval) and in receivers of Ad26 CoV2-S (calculated only for the 30 and 14 days risk interval) or ChAdOx1-S and mRNA-1273 (3 days risk interval). Similar results were obtained when the analyses were replicated in the +18 population adjusting for the frailty index (Table 1 Supplementary material). Table 5 shows place and causes of death during the study intervals. During the 31–60 days control interval there was a significantly (p < 0.001) higher proportion of hospital deaths than in the risk intervals and this difference was greater (58.37% vs 30.30%) when comparing the 3 days following vaccination, while the proportion of home deaths was greater in the 3 days risk interval (45.45% vs 22.79%).
Table 5

Place and causes of deaths by control and risk intervals.

Control interval
Risk interval
31–60 days
1–30 days
1–14 days
1–7 days
1–3 days
No.%No.%No.%No.%No.%
Total1,0151001,15210048710020810066100
Place of death
Home23022.7933228.8217936.768440.383045.45
Hospital58958.3759051.2219740.457335.102030.30
Nursing home15415.2615913.808016.433818.271218.18
Other424.16716.16316.37136.2546.06
Causes of deaths
Natural causes95694.751,09494.9746094.4619995.676395.45
Certain infectious and parasitic diseases373.67292.52132.6773.3711.52
COVID-19424.16978.42275.5452.400
Neoplasms24524.2819917.277515.402913.94913.64
Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism80.7960.5220.4110.4811.52
Endocrine, nutritional, and metabolic diseases363.57534.60214.31136.2546.06
Mental and behavioural disorders464.56544.69224.5294.3346.06
Diseases of the nervous system424.16282.43132.6773.3711.52
Diseases of the circulatory system31230.9240234.918738.47937.982436.36
Diseases of the respiratory system838.231059.11408.21209.621319.70
Diseases of the digestive system353.47453.91214.3194.3311.52
Diseases of the skin and subcutaneous tissue40.4060.5220.4100
Diseases of the musculoskeletal system and connective tissue30.3060.5220.4120.960
Diseases of the genitourinary system454.46393.39214.3173.3723.03
Congenital malformations, deformations and chromosomal abnormalities10.100000
Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified171.68252.17142.87115.2934.55
External causes of morbidity and mortality595.85585.03275.5494.3334.55
Place and causes of deaths by control and risk intervals. As far as causes of death are concerned, there were more deaths for neoplasms and nervous system diseases and fewer for circulatory and respiratory diseases in the control intervals than in the risk intervals. COVID-19-related deaths were higher among events occurred 30 days following vaccination than in the 31–60 days control interval.

Discussion

This study assesses whether the days following vaccination for the prevention of COVID-19 are associated with an increase in mortality. We conducted a retrospective evaluation among all vaccinated subjects and found that the days following vaccination were not characterized by an increase in mortality. On the contrary, they were associated with a reduction in mortality in all risk periods. Whether we considered a short-time frame after administration (3, 7 days) or a longer time frame (14, 30 days) the mortality rate was lower than the rate observed one month since vaccination. This finding was replicated for recipients of any approved vaccine, BNT162b2, mRNA-1273, ChAdOx1-S and Ad26 CoV2-S, although with varying degrees of strength and significance. This finding is in line with previous epidemiological studies [15], [16], [17] on mortality associated with vaccines used to prevent COVID-19 in spite of the differences in objectives, study population, follow-up period and other differences in study design. Bardenheier et al. [17] compared vaccinated and unvaccinated residents of nursing homes and monitored deaths and other adverse events for 7 days and found lower mortality rates in vaccinated. Xu et al. [16] conducted a cohort study and analysed non-COVID related deaths during a 7 months follow up period and also reported lower rates of mortality between vaccinated and did not find major safety problems following the first or second dose of the vaccines. Lv et al. [15] reported on 55 deaths following vaccination noting that the majority of the reported deaths were in people aged 85 and older with serious underlying health conditions. As already remarked by other authors [16] it is unlikely that the vaccine has a protective effect, especially when we excluded COVID-19 related events. Rather, the lower mortality observed by other authors [16] was ascribed by a healthy vaccine effect or, as an alternative hypothesis, by healthier risk behaviours adopted by vaccinated than non-vaccinated in studies with both vaccinated and unvaccinated groups. Although we included only vaccinated subjects, our finding can also be ascribed by the healthy vaccine effect based on selective prescription [19]. It is unlikely that people who were in very unstable conditions and that were prone to death received a dose of vaccination. Nevertheless, the vaccine was administered also to very old and frail people that were sufficiently well at the moment of the administration but that might have had a rapid decline in health in the time frame of a month. An important secondary finding of our study is that deaths occurred in the days immediately following vaccination occurred more often at home and for circulatory diseases than in hospital or for neoplasms and neurological diseases. This finding corroborates the healthy vaccine effect suggesting that hospitalized patients in terminal phase were excluded from the vaccination. The same did not happen for patients with circulatory disease whose outcome is by the very nature of this disease, more sudden and less predictable. We observe also that the lower mortality risk is present in all strata, but it does not achieve significance in younger groups or with Ad26 CoV2-S or ChAdOx1-S where the number of events is very small nor in the 3 days following mRNA-1273 which was mainly administered at home and in nursing home residents where more subjects in unstable conditions might have received the vaccine. During the post-market surveillance a link was highlighted between COVID-19 vaccines and some severe, adverse events, in particular: thrombosis, thrombocytopenia and transverse myelitis following ChAdOx1-S [20], [21] anaphylaxis following mRna vaccines, myocarditis and pericarditis in younger [10], [22] also following mRNA vaccines. In addition, in some post-mortem investigation a causative relationship between vaccines and deaths in the 72 h after receiving the vaccine has been observed [8], [13]. These events are nevertheless very rare and so far there is a general consensus that the benefits of vaccination far outweigh the potential risks [10], [11]. Fatal events occur at any time and do occur also in temporal association with preventive measures. In this sense by studying all deaths after vaccination we did not observe any negative impact on mortality in the short-term.

Strengths and limitations

This was a large population-based study encompassing a period of one year where we looked at multiple timeframe after vaccination and thus including potential deaths for anaphylactic reactions that may occur within a short delay, but also for myocarditis, pericarditis and thrombotic complications that can occur two weeks later [8], [13]. In addition, as we adopted a risk interval approach we did not have to compare vaccinated with unvaccinated that are expected to be very different and as such introduce bias in the results. Another strength of the study was the availability of the causes of deaths which gave us the opportunity to provide a deep insight into the main findings of the study. This study has several limitations that should be taken into account when interpreting the results. One of the main limits of the study is that possible longer-term death associated with vaccination were not detected. In addition, as our goal was to study short-term mortality associated with vaccination, some events that occurred 30 days after vaccination (the control interval) might have a relationship with the vaccine. Other study design with longer follow-up should be conducted to explore long-term adverse events and long-term mortality of COVID-19 vaccines. Another limit of the study is the small size of some subgroups which is not sufficient to detect significant differences. By observing the main clinical characteristics of the participants, we did not find important differences when comparing deaths during the risk vs the control interval. By comprising >700,000 vaccinated subjects of all ages and analysing all fatal events occurred after the administration of COVID-19 vaccines, we did not find any negative impact in the short-term mortality during the first year of the campaign, a finding that may contribute to reducing hesitancy towards these vaccines. All authors attest they meet the ICMJE criteria for authorship.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
  18 in total

1.  Covid-19: Norway investigates 23 deaths in frail elderly patients after vaccination.

Authors:  Ingrid Torjesen
Journal:  BMJ       Date:  2021-01-15

2.  [Development of a predictive model of death or urgent hospitalization to identify frail elderly].

Authors:  Paolo Pandolfi; Natalina Collina; Paolo Marzaroli; Elisa Stivanello; Muriel Assunta Musti; Chiara Giansante; Vincenza Perlangeli; Lorenzo Pizzi; Sara De Lisio; Fausto Francia
Journal:  Epidemiol Prev       Date:  2016 Nov-Dec       Impact factor: 1.901

3.  Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine.

Authors:  Lindsey R Baden; Hana M El Sahly; Brandon Essink; Karen Kotloff; Sharon Frey; Rick Novak; David Diemert; Stephen A Spector; Nadine Rouphael; C Buddy Creech; John McGettigan; Shishir Khetan; Nathan Segall; Joel Solis; Adam Brosz; Carlos Fierro; Howard Schwartz; Kathleen Neuzil; Larry Corey; Peter Gilbert; Holly Janes; Dean Follmann; Mary Marovich; John Mascola; Laura Polakowski; Julie Ledgerwood; Barney S Graham; Hamilton Bennett; Rolando Pajon; Conor Knightly; Brett Leav; Weiping Deng; Honghong Zhou; Shu Han; Melanie Ivarsson; Jacqueline Miller; Tal Zaks
Journal:  N Engl J Med       Date:  2020-12-30       Impact factor: 91.245

4.  Mortality Rate and Characteristics of Deaths Following COVID-19 Vaccination.

Authors:  Gang Lv; Jing Yuan; Xiaomo Xiong; Minghui Li
Journal:  Front Med (Lausanne)       Date:  2021-05-14

5.  Post COVID-19 vaccine deaths - Singapore's early experience.

Authors:  Audrey Yeo; Benjamin Kuek; Mandy Lau; Shi Rui Tan; Shijia Chan
Journal:  Forensic Sci Int       Date:  2022-01-19       Impact factor: 2.676

6.  Risks of myocarditis, pericarditis, and cardiac arrhythmias associated with COVID-19 vaccination or SARS-CoV-2 infection.

Authors:  Martina Patone; Xue W Mei; Lahiru Handunnetthi; Sharon Dixon; Francesco Zaccardi; Manu Shankar-Hari; Peter Watkinson; Kamlesh Khunti; Anthony Harnden; Carol A C Coupland; Keith M Channon; Nicholas L Mills; Aziz Sheikh; Julia Hippisley-Cox
Journal:  Nat Med       Date:  2021-12-14       Impact factor: 53.440

Review 7.  Autopsy Findings and Causality Relationship between Death and COVID-19 Vaccination: A Systematic Review.

Authors:  Francesco Sessa; Monica Salerno; Massimiliano Esposito; Nunzio Di Nunno; Paolo Zamboni; Cristoforo Pomara
Journal:  J Clin Med       Date:  2021-12-15       Impact factor: 4.241

8.  Safety of mRNA vaccines administered during the initial 6 months of the US COVID-19 vaccination programme: an observational study of reports to the Vaccine Adverse Event Reporting System and v-safe.

Authors:  Hannah G Rosenblum; Julianne Gee; Ruiling Liu; Paige L Marquez; Bicheng Zhang; Penelope Strid; Winston E Abara; Michael M McNeil; Tanya R Myers; Anne M Hause; John R Su; Lauri E Markowitz; Tom T Shimabukuro; David K Shay
Journal:  Lancet Infect Dis       Date:  2022-03-07       Impact factor: 25.071

9.  COVID-19 vaccine acceptance and hesitancy in low- and middle-income countries.

Authors:  Julio S Solís Arce; Shana S Warren; Niccolò F Meriggi; Alexandra Scacco; Nina McMurry; Maarten Voors; Georgiy Syunyaev; Amyn Abdul Malik; Samya Aboutajdine; Opeyemi Adeojo; Deborah Anigo; Alex Armand; Saher Asad; Martin Atyera; Britta Augsburg; Manisha Awasthi; Gloria Eden Ayesiga; Antonella Bancalari; Martina Björkman Nyqvist; Ekaterina Borisova; Constantin Manuel Bosancianu; Magarita Rosa Cabra García; Ali Cheema; Elliott Collins; Filippo Cuccaro; Ahsan Zia Farooqi; Tatheer Fatima; Mattia Fracchia; Mery Len Galindo Soria; Andrea Guariso; Ali Hasanain; Sofía Jaramillo; Sellu Kallon; Anthony Kamwesigye; Arjun Kharel; Sarah Kreps; Madison Levine; Rebecca Littman; Mohammad Malik; Gisele Manirabaruta; Jean Léodomir Habarimana Mfura; Fatoma Momoh; Alberto Mucauque; Imamo Mussa; Jean Aime Nsabimana; Isaac Obara; María Juliana Otálora; Béchir Wendemi Ouédraogo; Touba Bakary Pare; Melina R Platas; Laura Polanco; Javaeria Ashraf Qureshi; Mariam Raheem; Vasudha Ramakrishna; Ismail Rendrá; Taimur Shah; Sarene Eyla Shaked; Jacob N Shapiro; Jakob Svensson; Ahsan Tariq; Achille Mignondo Tchibozo; Hamid Ali Tiwana; Bhartendu Trivedi; Corey Vernot; Pedro C Vicente; Laurin B Weissinger; Basit Zafar; Baobao Zhang; Dean Karlan; Michael Callen; Matthieu Teachout; Macartan Humphreys; Ahmed Mushfiq Mobarak; Saad B Omer
Journal:  Nat Med       Date:  2021-07-16       Impact factor: 87.241

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