Next Article in Journal
Multivariate Analysis of Adverse Reactions and Recipient Profiles in COVID-19 Booster Vaccinations: A Prospective Cohort Study
Next Article in Special Issue
Attitudes toward COVID-19 and Other Vaccines: Comparing Parents to Other Adults, September 2022
Previous Article in Journal
Exploring Community Perceptions of COVID-19 and Vaccine Hesitancy in Selected Cities of Ethiopia: A Qualitative Study
Previous Article in Special Issue
The Social Ecological Model: A Framework for Understanding COVID-19 Vaccine Uptake among Healthcare Workers—A Scoping Review
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Association between Vaccination Status for COVID-19 and the Risk of Severe Symptoms during the Endemic Phase of the Disease

Oliver Mendoza-Cano
Xóchitl Trujillo
Mónica Ríos-Silva
Agustin Lugo-Radillo
Verónica Benites-Godínez
Jaime Alberto Bricio-Barrios
Herguin Benjamin Cuevas-Arellano
Eder Fernando Ríos-Bracamontes
Walter Serrano-Moreno
Yolitzy Cárdenas
3 and
Efrén Murillo-Zamora
Facultad de Ingeniería Civil, Universidad de Colima, km. 9 Carretera Colima-Coquimatlán, Coquimatlán 28400, Mexico
Centro de Estudios e Investigación en Biocultura, Agroecología, Ambiente y Salud Colima, Ex-Hacienda Nogueras S/N, Nogueras 28450, Mexico
Centro Universitario de Investigaciones Biomédicas, Universidad de Colima, Av. 25 de Julio 965, Colima 28045, Mexico
CONAHCyT—Centro Universitario de Investigaciones Biomédicas, Universidad de Colima, Av. 25 de Julio 965, Colima 28045, Mexico
CONAHCyT—Faculty of Medicine and Surgery, Universidad Autónoma Benito Juárez de Oaxaca, Ex Hacienda Aguilera S/N, Carr. a San Felipe del Agua, Oaxaca 68020, Mexico
Coordinación de Educación en Salud, Instituto Mexicano del Seguro Social, Calzada del Ejercito Nacional 14, Tepic 63169, Mexico
Unidad Académica de Medicina, Universidad Autónoma de Nayarit, Ciudad de la Cultura Amado Nervo, Tepic 63155, Mexico
Facultad de Medicina, Universidad de Colima, Av. Universidad 333, Colima 28040, Mexico
Facultad de Ciencias, Universidad de Colima, Bernal Díaz del Castillo 340, Colima 28045, Mexico
Departamento de Medicina Interna, Hospital General de Zona No. 1, Instituto Mexicano del Seguro Social, Av. Lapislázuli 250, Villa de Álvarez 28984, Mexico
Unidad de Investigación en Epidemiología Clínica, Instituto Mexicano del Seguro Social, Av. Lapislázuli 250, Villa de Álvarez 28984, Mexico
Author to whom correspondence should be addressed.
Vaccines 2023, 11(10), 1512;
Submission received: 29 August 2023 / Revised: 15 September 2023 / Accepted: 19 September 2023 / Published: 22 September 2023


The global health emergency caused by COVID-19 concluded in May 2023, marking the beginning of an endemic phase. This study aimed to evaluate the association between vaccination status and other patient characteristics and the risk of severe disease during this new endemic period. A nationwide cohort study was conducted in Mexico, where we analyzed data from 646 adults who had received positive confirmation of COVID-19 through PCR testing from May to August 2023. The overall risk of severe symptoms in the study sample was 5.3%. The average time elapsed from the last vaccine shot to symptom onset was over six months in all the immunized groups (1, 2 or 3 vaccine doses). Compared to unvaccinated patients, those with three vaccine doses showed an elevated risk of severe symptoms. Advancing age and various chronic comorbidities (specifically cardiovascular, kidney, and obstructive pulmonary conditions) were associated with a heightened risk of severe COVID-19 manifestations. These findings underscore the ongoing seriousness of COVID-19, even in an endemic phase, underscoring the urgent need for tailored interventions aimed at high-risk patients.

1. Introduction

The emergence of the COVID-19 pandemic, resulting from the infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), had high social and economic implications [1]. Concurrently with vaccine development, significant progress was achieved in reducing virus transmission and mitigating its virulence [2]. Consequently, the global health emergency classification associated with COVID-19 was lifted, signifying the shift of the disease into an endemic stage [3].
Mexico’s COVID-19 vaccination plan was characterized by a tiered approach prioritising high-risk populations and essential workers [4]. The initial phases, which started on 24 December 2020 [5], focused on healthcare personnel, the elderly population, and individuals with underlying health conditions, acknowledging their increased vulnerability to severe COVID-19 outcomes [6]. As vaccine availability allowed, the strategy expanded to encompass broader demographic groups, ultimately targeting a substantial proportion of the population. By the end of the first quarter of 2023, nearly 78% of the country’s total population had received at least one dose of a COVID-19 vaccine [7].
In Mexico, a total of eight COVID-19 vaccines were authorized and administered. These vaccines include BNT162b2 (Pfizer-BioNTech; New York, NY, USA–Mainz, Germany), AZD1222 (AstraZeneca; Cambridge, UK), Ad26.COV2-S (Janssen-CILAG; Beerse, Belgium–Schaffhausen, Switzerland), CX-024414 (Moderna; Cambridge, MA, USA), BBIBP-CorV (Sinopharm; Shanghai, China), CoronaVac (Sinovac Biotech; Beijing, China), BBV152 (Bharat Biotech; Hyderabad, India), and Ad5-nCoV (CanSino Biologics, Tianjin, China) [8].
The post-global emergency phase resulting from COVID-19 is marked by the prevailing presence of the XBB.1.5 subvariant of Omicron SARS-CoV-2, recognized for its heightened transmissibility [9]. Evaluating predictors of severe COVID-19 during the endemic phase of the disease, including the effect of vaccination status, holds critical importance for effective public health planning and resource allocation [10].
In addition, the identification of predictors can aid in refining risk stratification models, enabling healthcare systems to allocate medical interventions better and prioritize vulnerable individuals [11]. Finally, insights into predictors of severe outcomes can guide the development of targeted preventive strategies and therapeutic interventions, potentially reducing the burden on healthcare infrastructure and minimizing the impact of the disease on individuals and communities [12]. However, and to the best of our knowledge, no published studies have comprehensively evaluated predictors of severe symptoms after the conclusion of the COVID-19 emergence.
Hence, this study aimed to assess the effect of COVID-19 vaccination status on the risk of severe laboratory-confirmed illness in adults during the endemic phase of the disease. Furthermore, the study evaluated the association between different patient characteristics and the risk of severe manifestations. Our hypothesis posited that vaccinated adults, compared to their unvaccinated counterparts, might experience a decreased risk of severe symptoms during the endemic phase of COVID-19.

2. Materials and Methods

We conducted a nationwide and retrospective cohort study in Mexico during August 2023. Potentially eligible subjects (comprising laboratory-confirmed COVID-19 cases using reverse-transcription polymerase chain reaction, RT-PCR) were sourced from nominal records within an epidemiological surveillance system for viral respiratory diseases, targeting SARS-CoV-2, influenza virus, and other pathogens of public health concern. This system, known as SINOLAVE, primarily sourced data from patients’ medical records and, when applicable, death certificates. SINOLAVE is managed by the Mexican Institute of Social Security (IMSS), which provides healthcare services to approximately 60% (72 million people) of Mexico’s total population [13].
Adult patients aged 18 years and above, who exhibited respiratory symptoms suggestive of COVID-19 between 5 May and 10 August 2023, were eligible. Patients with a negative RT-PCR test result and those lacking complete clinical and epidemiological data of interest were excluded. A total of 172 patients under 18 years of age and 21 patients with insufficient data of interest were excluded.
In accordance with normative guidelines [14], clinical specimens obtained as nasopharyngeal or deep nasal swabs were employed for RT-PCR testing. Nucleic acids were extracted from a 200 μL sample using the MagNa Pure LC Total Nucleic Acid Isolation Kit automated system (catalog: 03038505001; Roche Diagnostics, Mannheim, Germany), following the protocols detailed in the study by Fernandes-Matano et al. [15]. Detection of SARS-CoV-2 was performed using the primers and probes proposed by Corman et al. [16], utilizing the SuperScript III Platinum One-step qRT-PCR System (catalog: 12574035; Invitrogen Carlsbad, CA, USA) in conjunction with the 7500 Fast Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). The analytical procedure was carried out within the network of laboratories dedicated to epidemiological surveillance under the jurisdiction of the IMSS.
Demographic and clinical variables were extracted from the audited surveillance system. Vaccination status was assessed based on the number of COVID-19 vaccine doses received (none, 1, 2, or 3). When applicable, the dates of vaccine shots were utilized to calculate the number of days elapsed between the last shot and the onset of symptoms. The analyzed comorbidities were determined by physician-diagnosed history (no/yes). The following conditions were assessed: current tobacco use, obesity (defined by a body mass index [BMI] of 30 or above), asthma, chronic obstructive pulmonary disease (COPD), type 2 diabetes mellitus, cardiovascular disease, chronic kidney disease (CKD), and immunosuppression (due to any cause).
Severe COVID-19, our primary binary outcome (no/yes), was defined by the occurrence of pneumonia. The latter was characterized by the presence of respiratory clinical symptoms (including cough, fever, dyspnea, and chest pain), coupled with radiographic evidence of pneumonia (evidenced by bilateral ground glass opacities or consolidations visible on computed tomography [CT] or X-ray) necessitating hospitalization [14].
Summary statistics were calculated. We utilized risk ratios (RR) and 95% confidence intervals to evaluate the association between vaccination status and other exposures of interest with the risk of severe COVID-19 manifestations. These estimations were derived using generalized linear regression models. We constructed 11 models, one for each independent variable and a final multiple model that incorporated all explanatory variables. In the construction of the multiple regression model, we adhered to the Hosmer and Lemeshow approach. Thus, variables that exhibited a p -value of <0.2 in bivariate analysis, or those identified as potential confounders based on scientific rationale, were included, irrespective of their p -value [17].
In the generalized linear regression analysis context, the unvaccinated group was designated as the reference category for calculating the relevant estimates. This choice of reference category was made to establish a baseline for comparing vaccination effects [18], as previously employed during the COVID-19 emergency [19,20,21]. Such an approach aligns with the fundamental principles of causality in epidemiology [22] and ultimately facilitates a more robust assessment of the vaccine’s efficacy in reducing the risk of severe outcomes [23].
This study obtained approval from the Local Committee of Ethics in Health Research (601) of the IMSS (approval R-2023-601-015). None of the participants were physically present or interviewed during any phase of this study, and all researchers adhered to stringent ethical guidelines.

3. Results

Data from 646 patients with laboratory-confirmed COVID-19 were analyzed. As presented in Figure 1, approximately half (47.2%, n = 305/646) of the included adults experienced symptom onset in May 2023. Nearly two-thirds (62.5%, n = 404/646) of the participants were female, and the overall median age was 44 years and ranged (interquartile range) from 29 to 60 years old. The overall risk of severe symptoms in the study sample was 5.3% ( n = 34/646).
The average time interval between the date of the final vaccine administration and the onset of symptoms was 304.3 ± 111.4 days for individuals who had received one dose, 218.7 ± 63.3 days for those who had received two doses, and 202.1 ± 49.7 days for individuals who had received a vaccine booster (third dose). Participants who experienced severe COVID-19, when compared to those with non-severe disease, were found to have a higher likelihood of being vaccinated (at least one dose: 38.2% vs. 17.2%, p = 0.002). This difference was particularly more pronounced among those who had received three vaccine doses (23.5% vs. 3.9%, p < 0.001).
As presented in Table 1, patients with severe symptoms had a higher likelihood of being male and were older than those with non-severe COVID-19. They also had a higher prevalence of a personal history of the assessed chronic comorbidities, specifically COPD (17.7% vs. 1.8%, p < 0.001), type 2 diabetes mellitus (38.2% vs. 13.2%, p < 0.001), cardiovascular disease (14.7% vs. 1.5%, p < 0.001), CKD (14.7% vs. 2.8%, p < 0.001), and immunosuppression (8.8% vs. 1.5%, p = 0.002).
In the multiple generalized linear regression model presented in Table 2, compared to unvaccinated participants, those who had received three vaccine doses revealed a 19% increased risk of severe disease (RR = 1.19, 95% CI 1.11–1.28, p < 0.001). The estimates for the remaining categories, involving one or two vaccine shots, did not demonstrate statistical significance.
Patients with COPD exhibited the highest risk of severe COVID-19 (RR = 1.23, 95% CI 1.11–1.37, p = 0.004), followed by the risk associated with a personal history of cardiovascular disease (RR = 1.19, 95% CI 1.06–1.33, p = 0.004), and CKD (RR = 1.12, 95% CI 1.02–1.23, p = 0.020). The study sample did not yield any other significant associations.

4. Discussion

Our findings suggest that SARS-CoV-2 vaccination may not provide enduring protection against severe disease, preventing us from confirming our initial hypothesis. Furthermore, we observed that patients who received three vaccine doses were more likely to develop severe symptoms. However, as the remaining vaccinated groups (1 or 2 vaccine shots) did not show an elevated risk for severe disease compared to unvaccinated adults, this finding should be interpreted cautiously. To gain a more comprehensive understanding of the vaccine’s effects in the endemic phase of COVID-19, further research with a larger sample size is imperative.
The presented results underscore that specific patient-related factors, especially age and the presence of pre-existing chronic conditions, significantly contribute to an elevated risk of encountering severe cases of COVID-19 during the endemic phase of the illness. The association between advancing age and the presence of chronic diseases with an escalated risk of severe disease has been widely documented throughout the entire course of the pandemic’s progression [24,25].
These insights highlight the need for tailored and focused public health strategies that prioritize managing and caring for individuals burdened with chronic health conditions [26]. Such an approach is pivotal for alleviating the impact of severe cases and optimizing patient outcomes within the evolving framework of the endemic phase.
Within our study sample, individuals who had received a vaccine booster were at increased risk for severe disease compared to those who remained unvaccinated. It is worth noting, however, that the mean interval between the vaccination date and the onset of symptoms extended beyond six months for participants who had received a booster shot and those who had been administered one or two vaccine doses. Consequently, it was anticipated that the antibody titers would fall below protective levels [27].
Additionally, it is important to highlight that the median age of patients who had received three vaccine doses (48, interquartile range [IQR] 37–66 years old) was higher (p = 0.047) than that of unvaccinated individuals (44, IQR 29–60 years old) (data not presented). These factors may collectively contribute to the observed scenario, and the documented association must be interpreted cautiously.
As of March 2023, about three-quarters (77.5%) of the Mexican population had received at least one dose of the COVID-19 vaccine [7]. However, in our study sample, the vaccine coverage (at least one dose) was 18.2%. Taking into account Mexico’s high disease burden during the critical phases of the pandemic emergency [28], the fact that our study exclusively focused on enrolling symptomatic cases, and considering the prolonged effectiveness of active immunization in comparison to passive immunization [29,30,31], we hypothesize that previous SARS-CoV-2 infections might exert an undisclosed influence on the observed vaccination rates within our study.
This latter hypothesis is based on the concept that individuals who have recuperated from previous infections might perceive a unique risk-benefit equilibrium in relation to vaccination [32,33]. Such a perception could potentially underlie the observed fluctuations in uptake rates, as outlined in our analysis. These factors underscore the complex interplay among natural immunity, vaccination approaches, and public attitudes. Consequently, further investigation is warranted to elucidate its potential influence on vaccination campaigns and the broader population’s immunity landscape.
Our study did not observe a significant association between obesity, defined by a BMI of 30 or higher, and the risk of severe symptoms [34]. We hypothesize that this lack of association may be attributed to an unexpectedly low prevalence of obesity among individuals with mild symptoms (11.3%) and severe disease (20.6%). According to the latest (2022) National Health and Nutrition Survey, the overall prevalence of obesity among Mexican adults stands at 36.9% [35]. Further research is needed to understand the relationship between obesity and severe COVID-19 during this endemic phase.
A personal history of asthma was associated with the risk of severe symptoms in the bivariate analysis but did not maintain significance in the multiple models. This observation aligns with findings reported in prior published studies [36,37,38].
The incorporation of cases verified through RT-PCR testing is a major strength of this study. Nevertheless, it is essential to acknowledge and address potential limitations inherent in our research methodology. First, our research did not encompass an evaluation of the antibody titers within vaccinated adults. Consequently, we could not evaluate a correlation between these antibody levels and the risk of experiencing severe manifestations of COVID-19. This aspect represents a gap in our study that warrants consideration in future research endeavors.
Second, the personal history of COPD was associated with a 23% escalation in the risk of severe COVID-19 symptoms (RR = 1.23, 95% CI 1.11–1.37; p < 0.001). This observed increase in risk constitutes the highest effect within our study cohort. However, the exposure assessment was conducted as a dichotomous variable, thereby excluding the inclusion of other pertinent clinical data, such as disease staging. The absence of these comprehensive factors may limit the depth of our conclusions and warrant further exploration.
Third, it is pertinent to recognize the contextual influence of the pandemic’s evolution. The elevated likelihood of previous SARS-CoV-2 infections due to the pandemic’s progression potentially introduces a confounding factor that might have impacted our obtained results. Pre-existing anti-SARS-CoV-2 nucleocapsid antibodies could have been detected through a straightforward serological test, indicating a previous SARS-CoV-2 infection. The interplay between prior infections and vaccination status might be complex and could contribute to variations in the severity of outcomes.
Fourth, we lacked genomic data pertaining to the specific SARS-CoV-2 variant and subvariant implicated in each analyzed individual. Nevertheless, relying on authoritative information sourced from the genomic surveillance of COVID-19 in Mexico, it is apparent that the XBB.1.5 (‘Kraken’) subvariant of the Omicron lineage was notably prevalent throughout the study period [39].
Fifth, information regarding concurrent infections (i.e., bacterial or viral) is not systematically collected by the analyzed system, so we cannot assess its impact on the risk of severe manifestations in the analyzed cohort.

5. Conclusions

As the world transitions into an era wherein COVID-19 evolves into a persistent public health challenge, prioritizing tailored approaches aimed at safeguarding and aiding these susceptible populations should continue to stand as a paramount objective for healthcare systems and policymakers. Our study may enrich our comprehension of the evolving dynamics characterizing COVID-19 within an endemic phase. The heightened susceptibility to severe manifestations among specific groups accentuates the significance of upholding vigilant surveillance protocols, bolstering vaccination initiatives, and devising healthcare strategies that effectively attend to the distinct requirements of individuals at an elevated risk.

Author Contributions

O.M.-C. and E.M.-Z. contributed to the development of the research concept. E.M.-Z., X.T. and M.R.-S. were involved in designing and implementing the research methodology. O.M.-C., A.L.-R., V.B.-G., H.B.C.-A., W.S.-M. and Y.C. conducted the formal analysis of the data. X.T., M.R.-S., V.B.-G., J.A.B.-B., H.B.C.-A., E.F.R.-B. and W.S.-M. participated in the interpretation of the research findings. O.M.-C. and E.M.-Z. drafted the initial manuscript. A.L.-R., J.A.B.-B., E.F.R.-B. and Y.C. provided critical feedback and revised the manuscript. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

This study was reviewed and approved by the Local Committee of Ethics in Health Research (601) of the IMSS (approval R-2020-601-015).

Informed Consent Statement

Since the data set analyzed was derived from the normative surveillance of COVID-19 and was fully deidentified before delivery to the research group, the requirement for consent to participate was waived.

Data Availability Statement

The data and materials analyzed in this study are available from the corresponding author upon request.


The group of researchers expresses gratitude to the Health Research Coordination of the Mexican Social Security Institute for their invaluable support in conducting the research and disseminating the findings.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Balqis-Ali, N.Z.; Fun, W.H.; Ismail, M.; Ng, R.J.; Jaaffar, F.S.A.; Low, L.L. Addressing Gaps for Health Systems Strengthening: A Public Perspective on Health Systems’ Response towards COVID-19. Int. J. Environ. Res. Public. Health 2021, 18, 9047. [Google Scholar] [CrossRef]
  2. Haque, A.; Pant, A.B. Mitigating COVID-19 in the face of emerging virus variants, breakthrough infections and vaccine hesitancy. J. Autoimmun. 2022, 127, 102792. [Google Scholar] [CrossRef] [PubMed]
  3. United Nations. UN News: WHO Chief Declares End to COVID-19 as a Global Health Emergency. 2023. Available online:,-5%20May%202023&text=The%20head%20of%20the%20UN,no%20longer%20a%20global%20threat (accessed on 12 August 2023).
  4. Ramos-Dávila, E.M.; González-Treviño, M.; Garza-Garza, L.A.; Ruiz-Lozano, R.E.; Ibarra-Salazar, N.; Martinez-Resendez, M.F. Challenges in the COVID-19 vaccination era: Prioritization of vaccines among essential workers in Mexico. J. Glob. Health Econ. Policy 2021, 1. [Google Scholar] [CrossRef]
  5. Mexican Ministry of Health. Press Release 266: COVID-19 Vaccination Campaign Begins in Mexico. Available online: (accessed on 5 September 2023). (In Spanish).
  6. Group, C.-V.T.A. Sequential prioritization for vaccination against SARS-CoV-2 in the Mexican population. Preliminary recommendations. Salud Pública México 2021, 63, 286–307. [Google Scholar]
  7. Johns Hopkins Univesity. Coronavirus Resource Center: Mexico’s Overview. Updates on 10 March 2023. Available online: (accessed on 5 September 2023).
  8. Federal Commission for the Protection against Sanitary Risks of the Government of Mexico. Authorized COVID-19 Vaccines. Available online: (accessed on 9 September 2023). (In Spanish).
  9. Parums, D.V. Editorial: The XBB.1.5 (‘Kraken’) Subvariant of Omicron SARS-CoV-2 and its Rapid Global Spread. Med. Sci. Monit. 2023, 29, e939580. [Google Scholar] [CrossRef]
  10. Fu, Y.; Zeng, L.; Huang, P.; Liao, M.; Li, J.; Zhang, M.; Shi, Q.; Xia, Z.; Ning, X.; Mo, J.; et al. Severity-onset prediction of COVID-19 via artificial-intelligence analysis of multivariate factors. Heliyon 2023, 9, e18764. [Google Scholar] [CrossRef]
  11. Bhargava, A.; Fukushima, E.A.; Levine, M.; Zhao, W.; Tanveer, F.; Szpunar, S.M.; Saravolatz, L. Predictors for Severe COVID-19 Infection. Clin. Infect. Dis. 2020, 71, 1962–1968. [Google Scholar] [CrossRef]
  12. Wynants, L.; Van Calster, B.; Collins, G.S.; Riley, R.D.; Heinze, G.; Schuit, E.; Bonten, M.M.J.; Dahly, D.L.; Damen, J.A.A.; Debray, T.P.A.; et al. Prediction models for diagnosis and prognosis of covid-19: Systematic review and critical appraisal. BMJ 2020, 369, m1328. [Google Scholar] [CrossRef]
  13. Government of Mexico. Press Release 030/2022: With 79 Years of Existence, IMSS Has Demonstrated Its Capacity to Respond to Natural Disasters and Health Crises. Available online: (accessed on 6 September 2023). (In Spanish).
  14. General Directorate of Epidemiology in Mexico. Standardized Guideline for Epidemiological and Laboratory Surveillance of Viral Respiratory Disease. Updated on 7 April 2022. Available online: (accessed on 5 September 2023). (In Spanish).
  15. Fernandes-Matano, L.; Monroy-Munoz, I.E.; Bermudez de Leon, M.; Leal-Herrera, Y.A.; Palomec-Nava, I.D.; Ruiz-Pacheco, J.A.; Escobedo-Guajardo, B.L.; Marin-Budip, C.; Santacruz-Tinoco, C.E.; Gonzalez-Ibarra, J.; et al. Analysis of influenza data generated by four epidemiological surveillance laboratories in Mexico, 2010–2016. Epidemiol. Infect. 2019, 147, e183. [Google Scholar] [CrossRef]
  16. Corman, V.M.; Landt, O.; Kaiser, M.; Molenkamp, R.; Meijer, A.; Chu, D.K.; Bleicker, T.; Brunink, S.; Schneider, J.; Schmidt, M.L.; et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance 2020, 25, 2000045. [Google Scholar] [CrossRef]
  17. Hosmer, D.W., Jr.; Lemeshow, S.; Sturdivant, R.X. Applied Logistic Regression; John Wiley & Sons: Hoboken, NJ, USA, 2013; Volume 398. [Google Scholar]
  18. Hinkle, D.E.; Oliver, J.D. Regression Analysis with Dummy Variables: Use and Interpretation. J. Vocat. Educ. Res. 1986, 11, 17–32. [Google Scholar]
  19. Liu, Q.; Qin, C.; Liu, M.; Liu, J. Effectiveness and safety of SARS-CoV-2 vaccine in real-world studies: A systematic review and meta-analysis. Infect. Dis. Poverty 2021, 10, 132. [Google Scholar] [CrossRef]
  20. Zheng, C.; Shao, W.; Chen, X.; Zhang, B.; Wang, G.; Zhang, W. Real-world effectiveness of COVID-19 vaccines: A literature review and meta-analysis. Int. J. Infect. Dis. 2022, 114, 252–260. [Google Scholar] [CrossRef] [PubMed]
  21. Anderegg, N.; Althaus, C.L.; Colin, S.; Hauser, A.; Laube, A.; Mausezahl, M.; Wagner, M.; Zaffora, B.; Riou, J. Assessing real-world vaccine effectiveness against severe forms of SARS-CoV-2 infection: An observational study from routine surveillance data in Switzerland. Swiss Med. Wkly. 2022, 152, w30163. [Google Scholar] [CrossRef]
  22. Shimonovich, M.; Pearce, A.; Thomson, H.; Keyes, K.; Katikireddi, S.V. Assessing causality in epidemiology: Revisiting Bradford Hill to incorporate developments in causal thinking. Eur. J. Epidemiol. 2021, 36, 873–887. [Google Scholar] [CrossRef] [PubMed]
  23. World Health Organization. Evaluation of COVID-19 Vaccine Effectiveness: Interim Guidance, 17 March 2021; World Health Organization: Geneva, Switzerland, 2021. [Google Scholar]
  24. Murillo-Zamora, E.; Sanchez-Pina, R.A.; Trujillo, X.; Huerta, M.; Rios-Silva, M.; Mendoza-Cano, O. Independent risk factors of COVID-19 pneumonia in vaccinated Mexican adults. Int. J. Infect. Dis. 2022, 118, 244–246. [Google Scholar] [CrossRef] [PubMed]
  25. Gallo Marin, B.; Aghagoli, G.; Lavine, K.; Yang, L.; Siff, E.J.; Chiang, S.S.; Salazar-Mather, T.P.; Dumenco, L.; Savaria, M.C.; Aung, S.N.; et al. Predictors of COVID-19 severity: A literature review. Rev. Med. Virol. 2021, 31, 1–10. [Google Scholar] [CrossRef]
  26. Muller-Wieland, D.; Marx, N.; Dreher, M.; Fritzen, K.; Schnell, O. COVID-19 and Cardiovascular Comorbidities. Exp. Clin. Endocrinol. Diabetes 2022, 130, 178–189. [Google Scholar] [CrossRef]
  27. Hernandez-Suarez, C.; Murillo-Zamora, E. Waning immunity to SARS-CoV-2 following vaccination or infection. Front. Med. 2022, 9, 972083. [Google Scholar] [CrossRef]
  28. Palacio-Mejia, L.S.; Hernandez-Avila, J.E.; Hernandez-Avila, M.; Dyer-Leal, D.; Barranco, A.; Quezada-Sanchez, A.D.; Alvarez-Aceves, M.; Cortes-Alcala, R.; Fernandez-Wheatley, J.L.; Ordonez-Hernandez, I.; et al. Leading causes of excess mortality in Mexico during the COVID-19 pandemic 2020–2021: A death certificates study in a middle-income country. Lancet Reg. Health Am. 2022, 13, 100303. [Google Scholar] [CrossRef]
  29. Frutos, A.M.; Kuan, G.; Lopez, R.; Ojeda, S.; Shotwell, A.; Sanchez, N.; Saborio, S.; Plazaola, M.; Barilla, C.; Kenah, E.; et al. Infection-Induced Immunity Is Associated with Protection Against Severe Acute Respiratory Syndrome Coronavirus 2 Infection and Decreased Infectivity. Clin. Infect. Dis. 2023, 76, 2126–2133. [Google Scholar] [CrossRef]
  30. De Gier, B.; Huiberts, A.J.; Hoeve, C.E.; den Hartog, G.; van Werkhoven, H.; van Binnendijk, R.; Hahne, S.J.M.; de Melker, H.E.; van den Hof, S.; Knol, M.J. Effects of COVID-19 vaccination and previous infection on Omicron SARS-CoV-2 infection and relation with serology. Nat. Commun. 2023, 14, 4793. [Google Scholar] [CrossRef] [PubMed]
  31. Bobrovitz, N.; Ware, H.; Ma, X.; Li, Z.; Hosseini, R.; Cao, C.; Selemon, A.; Whelan, M.; Premji, Z.; Issa, H.; et al. Protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against the omicron variant and severe disease: A systematic review and meta-regression. Lancet Infect. Dis. 2023, 23, 556–567. [Google Scholar] [CrossRef]
  32. Karlsson, L.C.; Soveri, A.; Lewandowsky, S.; Karlsson, L.; Karlsson, H.; Nolvi, S.; Karukivi, M.; Lindfelt, M.; Antfolk, J. Fearing the disease or the vaccine: The case of COVID-19. Pers. Individ. Dif. 2021, 172, 110590. [Google Scholar] [CrossRef]
  33. Caserotti, M.; Girardi, P.; Rubaltelli, E.; Tasso, A.; Lotto, L.; Gavaruzzi, T. Associations of COVID-19 risk perception with vaccine hesitancy over time for Italian residents. Soc. Sci. Med. 2021, 272, 113688. [Google Scholar] [CrossRef] [PubMed]
  34. Yang, J.; Hu, J.; Zhu, C. Obesity aggravates COVID-19: A systematic review and meta-analysis. J. Med. Virol. 2021, 93, 257–261. [Google Scholar] [CrossRef] [PubMed]
  35. Campos-Nonato, I.; Galván-Valencia, Ó.; Hernández-Barrera, L.; Oviedo-Solís, C.; Barquera, S. Prevalencia de obesidad y factores de riesgo asociados en adultos mexicanos: Resultados de la Ensanut 2022. Salud Pública México 2023, 65, s238–s247. [Google Scholar] [CrossRef] [PubMed]
  36. Wu, T.; Yu, P.; Li, Y.; Wang, J.; Li, Z.; Qiu, J.; Cui, L.; Mou, Y.; Sun, Y. Asthma does not influence the severity of COVID-19: A meta-analysis. J. Asthma 2022, 59, 1188–1194. [Google Scholar] [CrossRef]
  37. Liu, S.; Cao, Y.; Du, T.; Zhi, Y. Prevalence of Comorbid Asthma and Related Outcomes in COVID-19: A Systematic Review and Meta-Analysis. J. Allergy Clin. Immunol. Pract. 2021, 9, 693–701. [Google Scholar] [CrossRef]
  38. Eger, K.; Bel, E.H. Asthma and COVID-19: Do we finally have answers? Eur. Respir. J. 2021, 57, 2004451. [Google Scholar] [CrossRef]
  39. General Directorate of Epidemiology of the Government of Mexico. Genomic Surveillance Report of SARS-CoV-2 in Mexico as of 14 August 2023. Available online: (accessed on 28 August 2023). (In Spanish).
Figure 1. Date of symptoms onset of enrolled subjects, Mexico 2023.
Figure 1. Date of symptoms onset of enrolled subjects, Mexico 2023.
Vaccines 11 01512 g001
Table 1. Characteristics of the study sample for selected variables, Mexico 2023.
Table 1. Characteristics of the study sample for selected variables, Mexico 2023.
CharacteristicSevere COVID-19 p
      Female390 (63.7)14 (41.2)0.008
      Male222 (36.3)20 (58.8)
Age (years, median and IQR)43 (28–58)68 (59–76)<0.001
COVID-19 vaccination status
      Not vaccinated507 (82.8)21 (61.8)<0.001
      One dose19 (3.1)0 (0)
      Two doses62 (10.1)5 (14.7)
      Three doses24 (3.9)8 (23.5)
Personal history of:
      Smoking (current), yes21 (3.4)4 (11.8)0.014
      Obesity (BMI ≥ 30), yes69 (11.3)7 (20.6)0.101
      Asthma, yes10 (1.6)1 (2.9)0.566
      COPD, yes11 (1.8)6 (17.7)<0.001
Type 2 diabetes mellitus, yes81 (13.2)13 (38.2)<0.001
Cardiovascular disease, yes9 (1.5)5 (14.7)<0.001
CKD, yes17 (2.8)5 (14.7)<0.001
Immunosuppression (any cause), yes9 (1.5)3 (8.8)0.002
Abbreviations: COVID-19, coronavirus disease 2019; IQR, interquartilic range; BMI, body mass index; COPD, chronic pulmonary obstructive disease; CKD, chronic kidney disease. Notes: (1) The absolute frequencies ( n ) and relative frequencies (%) are presented unless specified as the median; (2) The p-values from chi-squared or U-test are reported accordingly.
Table 2. Factors associated with the risk of severe COVID-19, Mexico 2023.
Table 2. Factors associated with the risk of severe COVID-19, Mexico 2023.
Characteristic RR   ( 95 %   CI ) ,   p
Bivariate AnalysisMultivariate Analysis
      Male1.05 (1.01–1.09), 0.0081.03 (0.99–1.07), 0.082
Age (per each additional year)1.003 (1.001–1.004), <0.0011.002 (1.001–1.003), <0.001
COVID-19 vaccination status
      Not vaccinated1.001.00
      One dose0.96 (0.87–1.06), 0.4370.95 (0.87–1.05), 0.342
      Two doses1.04 (0.98–1.09), 0.2201.02 (0.97–1.08), 0.345
      Three doses1.23 (1.14–1.33), <0.0011.19 (1.11–1.28), <0.001
Personal history of:
Obesity (BMI ≥ 30)
      Yes1.05 (0.99–1.10), 0.1011.04 (0.99–1.09), 0.135
Smoking (current)
      Yes1.12 (1.02–1.22), 0.0141.08 (0.99–1.17), 0.076
Type 2 diabetes mellitus
      Yes1.11 (1.05–1.16), <0.0011.02 (0.97–1.07), 0.404
Cardiovascular disease
      Yes1.37 (1.22–1.53), <0.0011.19 (1.06–1.33), 0.004
      Yes1.36 (1.23–1.51), <0.0011.23 (1.11–1.37), <0.001
      Yes1.02 (1.01–1.03), <0.0011.04 (0.92–1.18), 0.556
      Yes1.20 (1.09–1.32), <0.0011.12 (1.02–1.23), 0.020
Immunosuppression (any cause)
      Yes1.22 (1.08–1.39), 0.0021.09 (0.96–1.23), 0.185
Abbreviations: COVID-19, coronavirus disease 2019; RR, risk ratio; CI, confidence interval; BMI, body mass index; COPD, chronic pulmonary obstructive disease; chronic kidney disease. Notes: (1) Generalized linear regression models were used to obtain the reported estimates; (2) The estimates from the multiple regression model were adjusted for all the variables presented in the table; (3) In the context of COVID-19 vaccination status, the unvaccinated group was selected as the reference to quantify the change in risk associated with receiving the vaccine.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Mendoza-Cano, O.; Trujillo, X.; Ríos-Silva, M.; Lugo-Radillo, A.; Benites-Godínez, V.; Bricio-Barrios, J.A.; Cuevas-Arellano, H.B.; Ríos-Bracamontes, E.F.; Serrano-Moreno, W.; Cárdenas, Y.; et al. Association between Vaccination Status for COVID-19 and the Risk of Severe Symptoms during the Endemic Phase of the Disease. Vaccines 2023, 11, 1512.

AMA Style

Mendoza-Cano O, Trujillo X, Ríos-Silva M, Lugo-Radillo A, Benites-Godínez V, Bricio-Barrios JA, Cuevas-Arellano HB, Ríos-Bracamontes EF, Serrano-Moreno W, Cárdenas Y, et al. Association between Vaccination Status for COVID-19 and the Risk of Severe Symptoms during the Endemic Phase of the Disease. Vaccines. 2023; 11(10):1512.

Chicago/Turabian Style

Mendoza-Cano, Oliver, Xóchitl Trujillo, Mónica Ríos-Silva, Agustin Lugo-Radillo, Verónica Benites-Godínez, Jaime Alberto Bricio-Barrios, Herguin Benjamin Cuevas-Arellano, Eder Fernando Ríos-Bracamontes, Walter Serrano-Moreno, Yolitzy Cárdenas, and et al. 2023. "Association between Vaccination Status for COVID-19 and the Risk of Severe Symptoms during the Endemic Phase of the Disease" Vaccines 11, no. 10: 1512.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop