Why COVID-19 vaccination cannot be ruled out as an explanation for all-cause excess mortality in the pandemic’s aftermath: A population-level study of over 3,000 US counties with over 320 million people

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In parallel, research has shown side effects from COVID-19 vaccination and increased deaths. Therefore, one cannot rule out COVID-19 vaccination as an explanation for the excess mortality. Methods US county-level data were used to model 2022 and 2023 all-cause excess mortality as dependent variables and per capita COVID-19 vaccine uptake at the end of 2021 and 2022 as independent variables. I included lagged dependent variables as controls. The data include over 3,000 US counties. Results A one-unit increase in per-capita vaccination uptake was significantly associated with a .042 (95% CI: .030–.055) increase in 2022 all-cause excess mortality, and significantly associated with a.030 (95% CI: .024–.036) increase in 2023. Conclusions COVID-19 vaccine uptake was significantly positively associated with all-cause excess mortality. Given the time asymmetry between vaccine uptake and all-cause excess mortality, the inclusion of lagged dependent variables as controls, and the large number of observations, the study has strong internal validity. " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/15-244", "name": "Why COVID-19 vaccination cannot be ruled out as an explanation for..." } } ] } Home Browse Why COVID-19 vaccination cannot be ruled out as an explanation for... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Aarstad J. Why COVID-19 vaccination cannot be ruled out as an explanation for all-cause excess mortality in the pandemic’s aftermath: A population-level study of over 3,000 US counties with over 320 million people [version 1; peer review: awaiting peer review] . F1000Research 2026, 15 :244 ( https://doi.org/10.12688/f1000research.177279.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Brief Report Why COVID-19 vaccination cannot be ruled out as an explanation for all-cause excess mortality in the pandemic’s aftermath: A population-level study of over 3,000 US counties with over 320 million people [version 1; peer review: awaiting peer review] Jarle Aarstad https://orcid.org/0000-0002-6650-6667 Jarle Aarstad https://orcid.org/0000-0002-6650-6667 PUBLISHED 12 Feb 2026 Author details Author details Western Norway University of Applied Sciences, Bergen, Norway Jarle Aarstad Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing OPEN PEER REVIEW REVIEWER STATUS AWAITING PEER REVIEW Abstract Background Research has shown consistent excess all-cause mortality since the COVID-19 pandemic, but without a clear explanation. In parallel, research has shown side effects from COVID-19 vaccination and increased deaths. Therefore, one cannot rule out COVID-19 vaccination as an explanation for the excess mortality. Methods US county-level data were used to model 2022 and 2023 all-cause excess mortality as dependent variables and per capita COVID-19 vaccine uptake at the end of 2021 and 2022 as independent variables. I included lagged dependent variables as controls. The data include over 3,000 US counties. Results A one-unit increase in per-capita vaccination uptake was significantly associated with a .042 (95% CI: .030–.055) increase in 2022 all-cause excess mortality, and significantly associated with a.030 (95% CI: .024–.036) increase in 2023. Conclusions COVID-19 vaccine uptake was significantly positively associated with all-cause excess mortality. Given the time asymmetry between vaccine uptake and all-cause excess mortality, the inclusion of lagged dependent variables as controls, and the large number of observations, the study has strong internal validity. READ ALL READ LESS Keywords COVID-19 vaccination; all-cause excess mortality; population level; county, US; SARS‑CoV‑2. Corresponding Author(s) Jarle Aarstad ( [email protected] ) Close Corresponding author: Jarle Aarstad Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2026 Aarstad J. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Aarstad J. Why COVID-19 vaccination cannot be ruled out as an explanation for all-cause excess mortality in the pandemic’s aftermath: A population-level study of over 3,000 US counties with over 320 million people [version 1; peer review: awaiting peer review] . F1000Research 2026, 15 :244 ( https://doi.org/10.12688/f1000research.177279.1 ) First published: 12 Feb 2026, 15 :244 ( https://doi.org/10.12688/f1000research.177279.1 ) Latest published: 12 Feb 2026, 15 :244 ( https://doi.org/10.12688/f1000research.177279.1 ) Introduction Although COVID-19-related deaths have decreased since the beginning of 2022 ( Our World in Data, 2024 ), the all-cause excess mortality has been consistent ( Kasper et al., 2025 ; Mostert et al., 2024 ; White et al., 2025 ). Why? One potential reason is delayed diagnosis and treatment during the pandemic, and another is the effects of COVID-19 infection not captured by COVID-19-related deaths ( White et al., 2025 ). Not ruling out those, in this study, I address whether COVID-19 vaccination has affected all-cause excess mortality as another potential explanation. My motive is grounded in research showing that COVID-19 vaccination increased the risk of myocarditis ( Karlstad et al., 2022 ), which can be deadly ( Kim et al., 2023 ), and other serious side effects have also been reported ( Faksova et al., 2024 ), including in randomized trials ( Fraiman et al., 2022 ). In line with those studies, “deaths increased significantly (95% CIs) in 10 of 11 weeks after COVID-19 vaccination compared to the first week”, among young people in England, and doubled in three ( Aarstad, 2024 , p. 908). Similarly, other data from England showed that COVID-19 “vaccination, despite a potential temporary protection, … increased mortality” ( Aarstad, 2025 , p. 2). Finally, a recent South Korean study showed increased cancer rates among COVID-19 vaccinated compared to unvaccinated ( Kim et al., 2025 ). Taken together, the studies indicate that COVID-19 vaccination may have had detrimental health effects, and accordingly, cannot be ruled out as a potential explanation for the consistent all-cause excess mortality. To assess whether COVID-19 vaccination can explain all-cause excess mortality, a population-level unit of analysis is required. Accordingly, in this study, I analyzed US counties. Materials and methods The data were taken from the US Centers for Disease Control and Prevention (CDC) databases concerning county-level population, deaths ( US Centers for Disease Control, 2025a ), and vaccination uptake ( US Centers for Disease Control, 2025b ). They are publicly available, thereby increasing the study’s transparency. All-cause excess mortality as the dependent variable To estimate all-cause excess mortality as the dependent variable, e.g., for 2022, I first carried out the following calculations: (total deaths in 2022/population in 2022)/((total deaths in 2018+2019)/(total population in 2018+2019)). Next, I multiplied the expression by 100. If a county reported 1-9 deaths, the CDC database coded them as missing. For consistency, I also coded 0 reported deaths as missing for a very small number of counties. For missing data in either 2018 or 2019, I coded them as missing for both years. Vaccine uptake as the independent variable The independent variable – counties’ COVID-19 vaccination doses per capita – was modeled in the lagged year. I.e., for the 2022 analysis, I included vaccine data at the end of 2021, and for the 2023 analysis, at the end of 2022. Vaccine data were included from counties reporting positive values for Completeness_pct ( US Centers for Disease Control, 2025b ) (see below for the inclusion of this concept as a control). To model a proxy for doses per capita, I first summarized the number of doses administered in each county for Administered_Dose1_Recip, Series_Complete_Yes, Booster_Doses, Second_Booster_50Plus, and Bivalent_Booster_5Plus. Next, I divided the number by the population sizes in 2021 and 2022, respectively, and multiplied the result by 100. One county reporting more than 500 doses administered per 100 at the end of 2022 was omitted from the 2023 analysis. Lagged dependent variables as controls For the 2022 analyses, I included lagged dependent variables for 2021 and 2020 as controls, and for the 2023 analyses, I included lagged dependent variables for 2020, 2021, and 2022 as controls. The approach accounts “for historical factors that cause current differences in the dependent variable that are difficult to account for in other ways” ( Wooldridge, 2006 , p. 315). Moreover, including “additional lags yields more accurate parameter estimates” ( Wilkins, 2018 , p. 393). Completement_pct as a control The Completement_pct concept “[r]epresents the proportion of people with a completed primary series whose Federal Information Processing Standards (FIPS) code is reported and matches a valid county FIPS code in the jurisdiction” ( US Centers for Disease Control, 2025b ). I include it as a control, since a relatively low value may be a proxy for underreporting of vaccine uptake. In the following regression analyses, the Completement_pct at the end of 2021 ranges from 59.8 to 99.1, with a mean of 95.0 and a median of 97.5. At the end of 2022, the Completement_pct ranges from 73.4 to 98.9, with a mean of 95.8 and a median of 97.5. Results Table 1 reports regressions with robust standard errors, weighted by counties’ population sizes. In Model 1, 2022 all-cause excess mortality is the dependent variable, and 2023 all-cause excess mortality in Model 2. All analyses are done in Stata ( StataCorp., 2023 ). Table 1. Regressions with robust standard errors, weighted by counties’ population sizes. The dependent variables are all-cause excess mortality in 2022 (Model 1) and 2023 (Model 2). Model 1 Model 2 Observation year 2022 2023 Per-capita vaccine uptake at the end of 2021 .042 * [1.43] (.030; .055) Per-capita vaccine uptake at the end of 2022 .030 * [1.35] (.024; .036) Dependent variable in 2022 .577 * (.536; .618) Dependent variable in 2021 .500 * .169 * (.459; .541) (.137; .202) Dependent variable in 2020 .007 -.085 * (-.027; .041) (-.114; -.057) Completement_pct at the end of 2021 -.088 * (-.125; -.051) Completement_pct at the end of 2022 -.126 * (-.183; -.069) F-value 194.6 * 423.8 * R-sq. .454 .580 Number of counties 3,060 3,067 Population 327,898,854 329,420,891 Population-weighted average per-capita vacc. uptake 144.3 194.3 All-cause excess mort. if vacc. uptake is weighted av. 113.8 106.9 (113.4; 114.1) (106.6; 107.1) All-cause excess mortality if vaccine uptake is zero 107.7 101.1 (106.0; 109.4) (100.0; 102.2) Pct. change in mort. due to the vaccine 5.67 5.73 (3.89; 7.46) (4.53; 6.93) Total US deaths 3,279,857 3,090,964 Change in deaths due to the vaccine 176,031 167,566 (123,590; 228,473) (134,417; 200,715) * p< .001. 95% CIs in parentheses. Numbers in bold are of particular interest. Variance inflation factors (VIFs) in brackets concerning per-capita vaccine uptake at the end of 2021 (Model 1) and 2022 (Model 2), respectively. Intercepts are omitted. 2022 all-cause excess mortality (Model 1) Model 1 shows that a one-unit increase in per-capita vaccination uptake at the end of 2021 was significantly associated with a.042 (95% CI: .030–.055) increase in 2022 all-cause excess mortality. The variance inflation factor (VIF) of 1.43 indicates no multicollinearity concerning vaccine uptake. Below the bold line, Model 1 reports that the weighted average – i.e., the “overall” – per-capita vaccine uptake at the end of 2021 was 144.3 doses per 100. Using Stata’s margins post-estimation command ( Williams, 2012 ) with that number, on the Model 1 vaccine estimate, returned a value of 113.8 (95% CI: 113.4–114.1). I.e., when including control variables, the 2022 all-cause excess mortality was 13.8%, based on the county-population-weighted average of vaccine uptake at the end of 2021. Assuming zero vaccine uptake using the margins post-estimation command with that number, on Model 1 estimates, returned a value of 107.7 (95% CI: 106.0–109.4). I.e., the all-cause excess mortality was 7.7% when assuming zero vaccine uptake at the end of 2021. The findings imply that the weighted average of vaccine uptake was associated with 5.67% (95% CI: 3.89–7.46) higher mortality than assuming zero vaccine uptake. As the US in 2022 had 3,279,857 deaths ( US Centers for Disease Control, 2024a ), this implies that the weighted average vaccine uptake was associated with 176,031 (95% CI: 123,590–228,473) additional deaths compared to zero vaccine uptake. (The CIs in this paragraph were achieved by using Stata’s nlcom algebra function on the margins post-estimations.) 2023 all-cause excess mortality (Model 2) Model 2 shows that a one-unit increase in per-capita vaccination uptake at the end of 2022 was significantly associated with a.030 (95% CI: .024–.036) increase in 2023 all-cause excess mortality. The VIF of 1.35 indicates no multicollinearity concerning vaccine uptake. Below the bold line, Model 2 reports that the weighted average – i.e., the “overall” – per-capita vaccine uptake at the end of 2022 was 194.3 doses per 100. Using Stata’s margins post-estimation command ( Williams, 2012 ) with that number, on the Model 2 vaccine estimate, returned a value of 106.9 (95% CI: 106.6–107.1). I.e., when including control variables, the 2023 all-cause excess mortality was 6.9%, based on the weighted average vaccine uptake at the end of 2022. Assuming zero vaccine uptake using the margins post-estimation command with that number, on Model 2 estimates, returned a value of 101.1 (95% CI: 100.0–102.2). I.e., the all-cause excess mortality was 1.1% when assuming zero vaccine uptake at the end of 2022. The findings imply that the weighted average vaccine uptake was associated with 5.73% (95% CI: 4.53–6.93) higher mortality than assuming zero vaccine uptake. As the US in 2023 had 3,090,964 deaths ( US Centers for Disease Control, 2024b ), this implies that the weighted average vaccine uptake was associated with 167,566 (95% CI: 134,417–200,715) additional deaths compared to zero vaccine uptake. Conclusion US county-level data showed that COVID-19 vaccine uptake was significantly positively associated with all-cause excess mortality in both 2022 and 2023. Given the time asymmetry between vaccine uptake and all-cause excess mortality, the inclusion of lagged dependent variables as controls, the large number of observations, and the strongly significant effects, I argue that the study has strong internal validity. As other research has shown consistent all-cause excess mortality in the aftermath of the COVID-19 pandemic, this study partly explains the observed trend. Also, it shows that COVID-19 vaccination side effects are reflected in increased US county-level mortality. A limitation is that the study does not distinguish between different types of COVID-19 vaccines administered, which I encourage future research to investigate. Declarations This paper is based on a preprint posted on https://www.preprints.org/manuscript/202512.2548 Ethics approval and consent to participate: Not applicable, as I used only publicly available data. Consent for publication Not applicable. Authors’ contributions Single-authored paper. Availability of data and material All data used in this study are publicly available from the following sources: US Centers for Disease Control. CDC Wonder 2025. Available from: https://wonder.cdc.gov/controller/datarequest/D157;jsessionid=28045589A4024FF98CAAE2667979 and US Centers for Disease Control. COVID-19 Vaccinations in the United States, County 2025. Available from: https://data.cdc.gov/Vaccinations/COVID-19-Vaccinations-in-the-United-States-County/8xkx-amqh/about_data . Acknowledgements Not applicable. References Aarstad J: Deaths among young people in England increased significantly in 10 of 11 weeks after COVID-19 vaccination and doubled in three. EXCLI J. 2024; 23 : 908–911. PubMed Abstract | Publisher Full Text | Free Full Text Aarstad J: Mortality involving and not involving COVID-19 among vaccinated vs. unvaccinated in England between Apr 21 and May 23. F1000Res. 2025; 14 : 133. Faksova K, Walsh D, Jiang Y, et al. : COVID-19 vaccines and adverse events of special interest: A multinational Global Vaccine Data Network (GVDN) cohort study of 99 million vaccinated individuals. Vaccine. 2024; 42 (9): 2200–2211. PubMed Abstract | Publisher Full Text Fraiman J, Erviti J, Jones M, et al. : Serious adverse events of special interest following mRNA COVID-19 vaccination in randomized trials in adults. Vaccine. 2022; 40 (40): 5798–5805. PubMed Abstract | Publisher Full Text | Free Full Text Karlstad Ø, Hovi P, Husby A, et al. : SARS-CoV-2 Vaccination and Myocarditis in a Nordic Cohort Study of 23 Million Residents. JAMA Cardiol. 2022; 7 (6): 600–612. PubMed Abstract | Publisher Full Text | Free Full Text Kasper PK, Ioana C, Taulant M, et al. : COVID-19 advocacy bias in the BMJ: meta-research evaluation. BMJ Open Quality. 2025; 14 (1): e003131. PubMed Abstract | Publisher Full Text | Free Full Text Kim HJ, Kim M-H, Choi MG, et al. : 1-year risks of cancers associated with COVID-19 vaccination: a large population-based cohort study in South Korea. Biomark. Res. 2025; 13 (1): 114. PubMed Abstract | Publisher Full Text | Free Full Text Kim M-J, Jung HO, Kim H, et al. : 10-year survival outcome after clinically suspected acute myocarditis in adults: A nationwide study in the pre-COVID-19 era. Plos One. 2023; 18 (1): e0281296. PubMed Abstract | Publisher Full Text | Free Full Text Mostert S, Hoogland M, Huibers M, et al. : Excess mortality across countries in the Western World since the COVID-19 pandemic: 'Our World in Data' estimates of January 2020 to December 2022. BMJ Public Health. 2024; 2 (1): e000282. Publisher Full Text Our World in Data: Coronavirus (COVID-19) Vaccinations.2024. Retrieved March 29, 2025. Reference Source StataCorp: Version 18. StataCorp LP; 2023. US Centers for Disease Control: Mortality in the United States, 2022.2024a. Retrieved August 4. Reference Source US Centers for Disease Control: Mortality in the United States, 2023.2024b. Retrieved August 4. Reference Source US Centers for Disease Control: CDC Wonder.2025a. Retrieved July 21. Reference Source US Centers for Disease Control: COVID-19 Vaccinations in the United States, County.2025b. Retrieved July 22. Reference Source White RA, Nygaard AB, Søraas A, et al. : Excess all-cause mortality in Norway in 2024. Scand. J. Public Health. 2025; 14034948251371830. PubMed Abstract | Publisher Full Text Wilkins AS: To lag or not to lag?: Re-evaluating the use of lagged dependent variables in regression analysis. Polit. Sci. Res. Methods. 2018; 6 (2): 393–411. Williams R: Using the margins command to estimate and interpret adjusted predictions and marginal effects. Stata J. 2012; 12 (2): 308–331. Reference Source Wooldridge JM: Introductory econometics: A modern approach. Cenage; 3rd ed.2006. Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 12 Feb 2026 ADD YOUR COMMENT Comment Author details Author details Western Norway University of Applied Sciences, Bergen, Norway Jarle Aarstad Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (1) version 1 Published: 12 Feb 2026, 15:244 https://doi.org/10.12688/f1000research.177279.1 Copyright © 2026 Aarstad J. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. 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