Abstract
The COVID-19 pandemic has prompted researchers to find treatments and vaccines to control SARS-CoV-2. There are some hypotheses about the benefit of respiratory virus vaccines, like MMR, for COVID-19 pneumonia severity, morbidity, and mortality. The influenza vaccine is one of the most frequently used respiratory virus vaccines covered by one of the Iranian insurance institutes. We have a symmetrical group of participants that have received this vaccine that could be compared with each other. We compared 3,379 persons aged 20 - 75 years for the effect of the influenza vaccine on COVID-19 mortality. We ultimately found that it does not affect mortality caused by COVID-19 pneumonia, but it can decrease the hospitalization cost in people over 65 years with a history of chronic disease.
Keywords: COVID-19, Influenza, Vaccine, Pneumonia, Mortality
1. Background
A novel coronavirus named Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), first reported in December 2019, has spread worldwide (1). Almost five million deaths have been reported from over 250 million positive cases by November 6, 2021. Coronaviruses (CoVs) mainly spread through respiratory droplets released from the saliva and mucus secretions from the mouth and nose during coughing, laughing, talking, breathing, sneezing, and singing (2). These virus droplets may have access to the body mainly via the nose, mouth, and eyes but not via the intact skin (3). Although SARS-CoV-2 is less lethal than the two earlier coronaviruses, SARS and MERS, it is more contagious (4).
The COVID-19 deaths are primarily attributed to respiratory failure caused by the cytokine storm, possibly due to the over-stimulation of the immune system (5). Many patients who die from SARS-CoV-2 respiratory infection have had concomitant infections or comorbidities (6). There is no effective and approved treatment for this respiratory infection. Prevention of other respiratory pathogen infections would help decrease COVID-19 infection mortality (7, 8).
Various COVID-19 resistance rates have been reported among different age groups. Infection rates were lower among children than among adults and elders. Though the mechanism for different severities and infection susceptibilities is unknown, this could be due to different quantities and qualities of the immune efficiency due to recent or previous vaccinations and infections.
2. Objectives
It appears that people in geographical locations with a high MMR vaccination rate have a lower COVID-19 death rate (9). There is also evidence that 955 sailors from the USS Roosevelt tested positive for the Coronavirus. The sailors exhibited milder symptoms, which may have been because all US Navy recruits must receive the MMR vaccine (10). Similarly, influenza vaccination may play a role in decreasing SARS-CoV-2 infection mortality. Our study tests this hypothesis.
3. Methods
The study population consisted of all insured individuals by one of the basic national health insurance organizations of the Islamic Republic of Iran, which covers flu vaccine administration for the insured according to eligibility criteria. This prospective study was conducted between August 2020 and February 2020. First, information about the people covered by this organization was extracted from relevant and reputable databases. In total, 21,071 persons aged 20 - 75 years were randomly selected from the list of insured persons covered by the mentioned insurance organization. Among them, 19,293 persons formed the study sample. Via three phases of short message service (SMS) notification, all of the individuals were asked to answer the questions by referring to the electronic portal of the insurance organization. During 30 days of the data collection phase, 3,435 persons referred to the announced electronic portal and completed the questionnaire. The accuracy of the answers was checked by calling the respondents. Therefore, individuals were divided into two general groups in this study: Vaccinated and non-vaccinated. This research utilized a researcher-made questionnaire of multiple-choice questions.
The questionnaires were reviewed and refined. Extra information on demographic data and costs of 3,379 people were also extracted from the organization’s databases, including gender, age, geographical area of residence, the total number of visits to medical centers, the total cost of treatment, frequency of inpatient services use, and the total cost of inpatient services during the study period.
4. Results
In this study, 1,172 people who had been vaccinated against the flu were compared with 2,207 people who had not been vaccinated. The two groups were matched for age and gender. However, the vaccinated people were older on average and had more frequent comorbidities (Table 1).
Table 1. Specifications of Vaccinated and Non-vaccinated Groups a.
| Variables | Vaccinated (N = 1172) | Non-vaccinated (N = 2207) | P-Value |
|---|---|---|---|
| Age (mean ± SD) | 58.2 ± 9.8 | 57.1 ± 10.7 | 0.004 |
| Male gender | 1082 (92.3) | 1910 (86.5) | 0.0001 |
| Diabetes | 385 (32.8) | 578 (26.2) | 0.0001 |
| CV events history | 374 (31.9) | 461 (20.9) | 0.0001 |
| Hypertension | 434 (37.0) | 608 (27.5) | 0.0001 |
| Malignancies | 53 (4.5) | 48 (2.2) | 0.0001 |
| Organ transplantation | 30 (2.6) | 18 (0.8) | 0.0001 |
| Immunosuppressive therapy | 127 (10.8) | 113 (5.1) | 0.0001 |
| Current chemotherapy | 48 (4.1) | 41 (1.9) | 0.0001 |
| Asthma | 67 (5.7) | 55 (2.5) | 0.0001 |
| COPD | 53 (4.5) | 25 (1.1) | 0.0001 |
| Chemical gas exposure | 439 (37.5) | 493 (22.3) | 0.0001 |
| Morbid obesity | 42 (3.6) | 63 (2.9) | 0.24 |
a Values are expressed as No. (%) unless otherwise indicated.
Comparing the two groups in terms of COVID-19 diagnosis and mortality rates did not show any statistically significant difference (Table 2).
Table 2. Comparison of Outcomes in Vaccinated and Non-vaccinated Groups a.
| Variables | Vaccinated (N = 1172) | Non-vaccinated (N = 2207) | P-Value |
|---|---|---|---|
| Mortality | 7 (0.6) | 17 (0.8) | 0.67 |
| COVID-19 diagnosis | 51 (4.5) | 82 (3.8) | 0.35 |
a Values are expressed as No. (%).
A comparison of the dead and living groups showed that studied population were older and, unexpectedly, the percentage of females was higher in the dead group. People with malignancy treated with immunosuppressants and chemotherapy, asthma, and chronic respiratory disease were more likely to die. There were fewer cases in the group of dead people with a history of exposure to chemical gases (Table 3).
Table 3. Analysis of Variables in Dead and Living Groups a.
| Variables | Dead (N = 24) | Living (N = 3354) | P-Value |
|---|---|---|---|
| Age (mean ± SD) | 62.9 ± 15.8 | 57.4 ± 10.4 | 0.01 |
| Male gender | 17 (70.8) | 2974 (88.7) | 0.01 |
| Diabetes | 8 (33.3) | 955 (23.5) | 0.65 |
| CV events history | 7 (29.2) | 827 (24.7) | 0.61 |
| Hypertension | 7 (29.2) | 1034 (30.8) | 0.86 |
| Malignancies | 2 (8.3) | 99 (3.0) | 0.12 |
| Organ transplantation | 0 | 48 (1.4) | - |
| Immunosuppressive therapy | 4 (16.7) | 236 (7.0) | 0.07 |
| Current chemotherapy | 2 (8.3) | 87 (2.6) | 0.08 |
| Asthma | 3 (12.5) | 119 (3.5) | 0.05 |
| COPD | 2 (8.3) | 76 (2.3) | 0.05 |
| Chemical gas exposure | 2 (8.3) | 930 (27.7) | 0.03 |
| Morbid obesity | 1 (4.2) | 104 (3.1) | 0.76 |
| Recent influenza vaccination | 7 (29.2) | 1164 (34.7) | 0.67 |
| COVID-19 diagnosis | 2 (8.3) | 131 (3.9) | 0.43 |
a Values are expressed as No. (%) unless otherwise indicated.
In terms of COVID-19 infection, the history of chronic respiratory diseases, in particular asthma, history of exposure to chemical gases, and history of cardiovascular diseases were significantly correlated to the greater risk of COVID-19 infection, as noted in Table 4. Diabetes was marginally higher in the infected group.
Table 4. Analysis of Univariate Factors Associated With COVID-19 a.
| Variables | COVID-19 Diagnosis (N = 133) | No COVID-19 Diagnosis (N = 3180) | P-Value |
|---|---|---|---|
| Age (mean ± SD) | 57.5 ± 10.4 | 57.5 ± 10.8 | 0.95 |
| Male gender | 115 (86.5) | 2820 (88.7) | 0.43 |
| Diabetes | 47 (35.3) | 902 (28.4) | 0.08 |
| CV events history | 43 (32.3) | 775 (24.4) | 0.04 |
| Hypertension | 44 (33.1) | 987 (31.0) | 0.62 |
| Malignancies | 2 (1.5) | 98 (3.1) | 0.30 |
| Organ transplantation | 2 (1.5) | 44 (1.4) | 0.91 |
| Immunosuppressive therapy | 13 (9.8) | 221 (6.9) | 0.21 |
| Current chemotherapy | 5 (3.8) | 84 (2.6) | 0.43 |
| Asthma | 10 (7.5) | 108 (3.4) | 0.01 |
| COPD | 6 (4.5) | 70 (2.2) | 0.08 |
| Chemical gas exposure | 62 (46.6) | 846 (26.6) | 0.0001 |
| Morbid obesity | 4 (3.0) | 100 (3.1) | 0.93 |
| Recent influenza vaccination | 51 (38.3) | 1094 (34.4) | 0.35 |
a Values are expressed as No. (%) unless otherwise indicated.
More extensive analyses demonstrated that a history of cardiovascular disease increased the risk of COVID-19 infection by about 1.5 times [OR = 1.48 (1.02 - 2.15), P = 0.04]. A history of diabetes also increased the COVID-19 infection by 40% [OR = 1.38 (0.96 - 1.99), P = 0.08]. Also, a history of bronchiectasis and COPD increased the risk of COVID-19 by 2.9 and 2.1 times, respectively. A separate analysis of vaccinated and non-vaccinated groups did not yield new results.
An analysis was done separately in groups with and without underlying chronic disease. Out of 1,476 people who did not have a chronic disease, 47 (3.2%) had COVID-19, while it was 86 out of 1787 (4.5%) in people who had at least one chronic disease (P = 0.02). Multivariate analysis showed that only gender and age had independent effects on mortality, and interestingly, women were more likely to die. A history of influenza vaccine showed no impact on mortality (Table 5).
Table 5. Multivariate Analysis.
| Variables | B | S.E. | Wald | df | Sig. | Exp(B) |
|---|---|---|---|---|---|---|
| Gender Code | 0.962 | 0.481 | 4.001 | 1 | 0.045 | 2.618 |
| Age | -0.045 | 0.020 | 5.092 | 1 | 0.024 | 0.956 |
| COVID-19 | 0.030 | 0.614 | 0.002 | 1 | 0.961 | 1.030 |
| Diabetes | -0.151 | 0.477 | 0.100 | 1 | 0.752 | 0.860 |
| CV events history | 0.015 | 0.253 | 0.003 | 1 | 0.953 | 1.015 |
| Hypertension | 0.139 | 0.170 | 0.672 | 1 | 0.412 | 1.149 |
| Malignancies | -0.104 | 0.226 | 0.212 | 1 | 0.645 | 0.901 |
| Immunosuppressive therapy | -0.174 | 0.122 | 2.031 | 1 | 0.154 | 0.840 |
| Morbid obesity | -0.025 | 0.158 | 0.026 | 1 | 0.872 | 0.975 |
| Current chemotherapy | -0.093 | 0.114 | 0.660 | 1 | 0.416 | 0.911 |
| Asthma | -10.130 | 0.697 | 2.629 | 1 | 0.105 | 0.323 |
| COPD | -0.441 | 0.457 | 0.932 | 1 | 0.334 | 0.643 |
| Bronchiectasis | -0.066 | 0.238 | 0.076 | 1 | 0.782 | 0.936 |
| Recent influenza vaccination | 0.472 | 0.481 | 0.9 65 | 1 | 0.326 | 1.604 |
| Constant | 5.422 | 1.884 | 8.280 | 1 | 0.004 | 226.222 |
Multivariate analysis of factors affecting COVID-19 showed that these factors did not significantly impact the disease, except for chronic respiratory diseases, which showed a partially independent effect (Table 6).
Table 6. Multivariate Analysis of Factors Affecting COVID 19.
| Variables | B | S.E. | Wald | df | Sig. | Exp(B) |
|---|---|---|---|---|---|---|
| Gender Code | -0.236 | 0.264 | 0.800 | 1 | 0.371 | 0.790 |
| Age | -0.003 | 0.009 | 0.093 | 1 | 0.761 | 0.997 |
| Diabetes | 0.274 | 0.199 | 1.895 | 1 | 0.169 | 1.315 |
| CV events history | 0.157 | 0.103 | 2.303 | 1 | 0.129 | 1.170 |
| Hypertension | -0.032 | 0.069 | 0.210 | 1 | 0.647 | 0.969 |
| Malignancies | -0.272 | 0.190 | 2.039 | 1 | 0.153 | 0.762 |
| Immunosuppressive therapy | 0.048 | 0.063 | 0.585 | 1 | 0.444 | 1.049 |
| Morbid obesity | -0.040 | 0.076 | 0.279 | 1 | 0.598 | 0.961 |
| Current chemotherapy | 0.065 | 0.064 | 1.054 | 1 | 0.305 | 1.067 |
| Asthma | 0.651 | 0.372 | 3.068 | 1 | 0.080 | 1.918 |
| COPD | 0.109 | 0.247 | 0.194 | 1 | 0.659 | 1.115 |
| Bronchiectasis | 0.139 | 0.105 | 1.743 | 1 | 0.187 | 1.149 |
| Recent influenza vaccination | 0.076 | 0.189 | 0.160 | 1 | 0.689 | 1.079 |
| Constant | -2.889 | 0.744 | 15.094 | 1 | 0.000 | 0.056 |
Analysis of factors affecting health costs showed that total costs were higher in the vaccinated group because these people were at high risk, were older, and needed greater demands. However, hospitalization and imaging costs were non-significantly lower in the vaccinated group (Table 7).
Table 7. Analysis of Factors Affecting Health Costs.
| Variables and History of Influenza Vaccination | N | Mean | Std. Deviation | Std. Error Mean | P-Value |
|---|---|---|---|---|---|
| Hospitalization cost (2018) (IRR) | 0.65 | ||||
| No | 399 | 63018760.95 | 86640905.370 | 4337470.499 | |
| Yes | 266 | 59963221.65 | 85304220.930 | 5230337.368 | |
| Radiography cost (2018) (IRR) | 0.59 | ||||
| No | 1376 | 3382072.71 | 18886186.190 | 509137.458 | |
| Yes | 833 | 2977903.70 | 13162817.280 | 456064.588 | |
| Visit cost (2018) (IRR) | 0.000 | ||||
| No | 2107 | 2795952.34 | 2587397.137 | 56367.766 | |
| Yes | 1146 | 3920477.52 | 3094557.972 | 91412.653 | |
| Drug cost (2018) (IRR) | 0.000 | ||||
| No | 2109 | 12990007.85 | 39511805.730 | 860376.596 | |
| Yes | 1160 | 18511311.80 | 30730340.820 | 902273.874 | |
| Test cost (2018) (IRR) | 0.000 | ||||
| No | 1674 | 2688451.36 | 3433791.621 | 83925.939 | |
| Yes | 1006 | 3323310.68 | 3814911.935 | 120277.814 | |
| Total cost (2018) (IRR) | 0.000 | ||||
| No | 2152 | 37354303.48 | 76796865.440 | 1655473.986 | |
| Yes | 1160 | 47597349.75 | 68692286.050 | 2016874.965 | |
| Hospitalization cost (2019) (IRR) | 0.57 | ||||
| No | 409 | 73205548.95 | 103935971.800 | 5139303.045 | |
| Yes | 259 | 68820241.44 | 85692080.710 | 5324646.814 | |
| Radiography cost (2019) (IRR) | 0.92 | ||||
| No | 1376 | 3653143.92 | 17321328.270 | 466951.716 | |
| Yes | 822 | 3579883.44 | 13020608.450 | 454145.871 | |
| Visit cost (2019) (IRR) | 0.000 | ||||
| No | 1621 | 3053668.89 | 3601901.951 | 89462.366 | |
| Yes | 974 | 3600435.67 | 3492060.379 | 111892.832 | |
| Drug cost (2019) (IRR) | 0.000 | ||||
| No | 2109 | 3105911.54 | 3014019.966 | 65630.821 | |
| Yes | 1151 | 4392823.41 | 3735317.527 | 110100.645 | |
| Test cost (2019) (IRR) | 0.000 | ||||
| No | 2131 | 17022517.77 | 45322908.140 | 981806.818 | |
| Yes | 1165 | 23054263.10 | 43907170.020 | 1286389.491 | |
| Total cost (2019) (IRR) | 0.001 | ||||
| No | 2167 | 44843601.72 | 92737312.830 | 1992163.835 | |
| Yes | 1166 | 56165027.27 | 83170966.850 | 2435692.590 |
A separate analysis of hospitalization and imaging costs (type 1 cost) and the costs of visits, tests, and drugs (type 2 cost) in the group with a history of special disease showed the following results in Table 8.
Table 8. Comparison of Cost of Vaccinated and Non-vaccinated Groups.
| Variables | Vaccinated | Non-vaccinated | P-Value |
|---|---|---|---|
| Type 1 cost for disease group (IRR) | 78,953,947 | 99,928,242 | 0.08 |
| Type 2 cost in disease group (IRR) | 36,972,762 | 31,558,206 | 0.01 |
| Type 1 cost in disease-free group (IRR) | 70,946,484 | 65,529,560 | 0.69 |
| Type 2 cost in disease-free group (IRR) | 25,822,055 | 21,886,501 | 0.40 |
In other words, influenza vaccination in people with a history of at least one chronic disease significantly reduced the costs of hospitalization and radiology by 110 million Rials per patient per year. However, it increased the outpatient costs by an average of five million Tomans per patient per year. Altogether, vaccination would save 60 million Rials per patient per year.
5. Discussion
Contrary to current information on sex differences in COVID-19 hospitalization and mortality, the percentage of female mortality was higher in our study, possibly because of men's health status (11). Mortality and morbidity from COVID-19 are higher among cancer patients because of the clinical challenges of cancer management, including immunosuppression, aging, and comorbidities (12). This agrees with our report and national studies in the UK (13) and Sweden (14). Asthma and chronic respiratory disease are associated with a risk of severe disease and mortality in COVID-19 infection.
Contrary to expectations, a history of exposure to chemical gases had the opposite effect on mortality. Several reasons can explain this. First, these people in the country are under the constant support of treatment and examination throughout their lives and are treated with the slightest change in their condition. Second, these fragile individuals may have been more careful and taken more stringent preventive measures, as previously reported (15). Third, general quarantine applied for most of the study period resulted in a significant reduction in air pollution (16), which is known to promote the exacerbation of lung disease (17), including COVID-19 exacerbation (18).
A further examination showed that a history of cardiovascular disease increased the risk of COVID-19 infection by 1.5 times because of the COVID-19 effect on the cardiovascular system, which increased the risk of cardiovascular events (19).
5.1. Conclusion
A history of influenza vaccine showed no effect on mortality caused by COVID-19 pneumonia. However, it decreased hospitalization costs in people over 65 years with a history of at least one chronic disease.
Footnotes
Authors' Contribution: Study concept and design, R. M., and A. K.; Analysis and interpretation of data, A. K., and H. F.; Drafting of the manuscript, H. F.; Critical revision of the manuscript for important intellectual content, R. M., F. A., and M. A.; Statistical analysis, A. N. and V.A.
Conflict of Interests: The authors have no conflicts of interest to declare. All co-authors have seen and agree with the contents of the manuscript and there is no financial interest to report.
Data Reproducibility: The data presented in this study are uploaded during submission as a supplementary file and are openly available for readers upon request [Dataset name: supporting information, File type: docx.].
Funding/Support: It was not declared by the authors.
Contributor Information
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References
- 1.Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med. 2020;382(8):727–33. doi: 10.1056/NEJMoa2001017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.El-Baz LM, Elwakeel KZ, Elgarahy AM. COVID-19 from mysterious enemy to an environmental detection process: a critical review. Innov Infrastruct Solut. 2020;5(3):1–13. doi: 10.1007/s41062-020-00334-7. [DOI] [Google Scholar]
- 3.Cirrincione L, Plescia F, Ledda C, Rapisarda V, Martorana D, Moldovan RE, et al. COVID-19 Pandemic: Prevention and Protection Measures to Be Adopted at the Workplace. Sustainability. 2020;12(9):3603. doi: 10.3390/su12093603. [DOI] [Google Scholar]
- 4.Ashour HM, Elkhatib WF, Rahman MM, Elshabrawy HA. Insights into the Recent 2019 Novel Coronavirus (SARS-CoV-2) in Light of Past Human Coronavirus Outbreaks. Pathogens. 2020;9(3) doi: 10.3390/pathogens9030186. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Blagosklonny MV. From causes of aging to death from COVID-19. Aging (Albany NY). 2020;12(11):10004–21. doi: 10.18632/aging.103493. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Yancy CW. COVID-19 and African Americans. JAMA. 2020;323(19):1891–2. doi: 10.1001/jama.2020.6548. [DOI] [PubMed] [Google Scholar]
- 7.Jamaati H, Dastan F, Esmaeili Dolabi S, Varahram M, Hashemian SM, Nasiri Rayeini S, et al. COVID-19 in Iran: A model for Crisis Management and Current Experience. Iran J Pharm Res. 2020;19(2):1–8. doi: 10.22037/ijpr.2020.113365.14255. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Mendelson M. Could enhanced influenza and pneumococcal vaccination programs help limit the potential damage from SARS-CoV-2 to fragile health systems of southern hemisphere countries this winter? Int J Infect Dis. 2020;94:32–3. doi: 10.1016/j.ijid.2020.03.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Gold JE, Tilley LP, Baumgartl W. MMR vaccine appears to confer strong protection from COVID-19: few deaths from SARS-CoV-2 in highly vaccinated populations. ResearchGate. 2020;Preprint doi: 10.13140/RG.2.2.32128.25607. [DOI] [Google Scholar]
- 10.Fidel PJ, Noverr MC. Could an Unrelated Live Attenuated Vaccine Serve as a Preventive Measure To Dampen Septic Inflammation Associated with COVID-19 Infection? mBio. 2020;11(3) doi: 10.1128/mBio.00907-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Gomez JMD, Du-Fay-de-Lavallaz JM, Fugar S, Sarau A, Simmons JA, Clark B, et al. Sex Differences in COVID-19 Hospitalization and Mortality. J Womens Health (Larchmt). 2021;30(5):646–53. doi: 10.1089/jwh.2020.8948. [DOI] [PubMed] [Google Scholar]
- 12.Wang L, Sun Y, Yuan Y, Mei Q, Yuan X. Clinical challenges in cancer patients with COVID-19: Aging, immunosuppression, and comorbidities. Aging (Albany NY). 2020;12(23):24462–74. doi: 10.18632/aging.104205. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Bloom CI, Drake TM, Docherty AB, Lipworth BJ, Johnston SL, Nguyen-Van-Tam JS, et al. Risk of adverse outcomes in patients with underlying respiratory conditions admitted to hospital with COVID-19: a national, multicentre prospective cohort study using the ISARIC WHO Clinical Characterisation Protocol UK. Lancet Respir Med. 2021;9(7):699–711. doi: 10.1016/S2213-2600(21)00013-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Bergman J, Ballin M, Nordstrom A, Nordstrom P. Risk factors for COVID-19 diagnosis, hospitalization, and subsequent all-cause mortality in Sweden: a nationwide study. Eur J Epidemiol. 2021;36(3):287–98. doi: 10.1007/s10654-021-00732-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020;323(20):2052–9. doi: 10.1001/jama.2020.6775. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Le Quéré C, Jackson RB, Jones MW, Smith AJ, Abernethy S, Andrew RM, et al. Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement. Nat Clim Change. 2020;10(7):647–53. doi: 10.1038/s41558-020-0797-x. [DOI] [Google Scholar]
- 17.Guan WJ, Zheng XY, Chung KF, Zhong NS. Impact of air pollution on the burden of chronic respiratory diseases in China: time for urgent action. Lancet. 2016;388(10054):1939–51. doi: 10.1016/S0140-6736(16)31597-5. [DOI] [PubMed] [Google Scholar]
- 18.Pozzer A, Dominici F, Haines A, Witt C, Munzel T, Lelieveld J. Regional and global contributions of air pollution to risk of death from COVID-19. Cardiovasc Res. 2020;116(14):2247–53. doi: 10.1093/cvr/cvaa288. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Harrison SL, Buckley BJR, Rivera-Caravaca JM, Zhang J, Lip GYH. Cardiovascular risk factors, cardiovascular disease, and COVID-19: an umbrella review of systematic reviews. Eur Heart J Qual Care Clin Outcomes. 2021;7(4):330–9. doi: 10.1093/ehjqcco/qcab029. [DOI] [PMC free article] [PubMed] [Google Scholar]