Copyright
by
Dennis Ogeto Nyachoti, MPH, DrPH
2023
DEDICATION
To
My family
EXPLORING THE ASSOCIATION OF SOCIAL VULNERABILITIES WITH COVID-19
OUTCOMES AND REVIEWING STRATEGIES FOR PROMOTING
COVID-19 VACCINATION
by
DENNIS OGETO NYACHOTI
BSc. Public Health, Jomo Kenyatta University of Agriculture and Technology, 2016
Master of Public Health, The University of Texas at El Paso, 2020
Presented to the Faculty of The University of Texas
School of Public Health
in Partial Fulfillment
of the Requirements
for the Degree of
DOCTOR OF PUBLIC HEALTH
THE UNIVERSITY OF TEXAS
SCHOOL OF PUBLIC HEALTH
Houston, Texas
May 2023
ACKNOWLEDGEMENTS
I owe utmost gratitude to my dissertation supervisor, Dr. Andrew Springer, for his
continual encouragement and thoughtful feedback throughout this dissertation. I would also
like to thank my academic advisor, Dr. Leah Whigham, for her guidance, advice, and
mentorship. A special tribute to Dr. Ryan Ramphul and Dr. Nalini Ranjit for their valuable
input and review of this work. I also acknowledge Dr. Juan Aguilera for working with me as
an independent reviewer on the scoping review paper and for his motivation in the whole
process. Many thanks to Dania Mofleh for her input on the statistical analysis method. To my classmates and friends Crystal, Erica, Kempson, Priscila, Nivi, Abolore, and Pierre – you’re
fabulous. Dad, Mom, and the Nyachotis, you’ve been my pillar throughout my academic
journey - I can’t thank you enough. Above all, the Almighty!
EXPLORING THE ASSOCIATION OF SOCIAL VULNERABILITIES WITH COVID-19
OUTCOMES AND REVIEWING STRATEGIES FOR PROMOTING
COVID-19 VACCINATION
DENNIS OGETONYACHOTI, MPH, DrPH(c)
The University of Texas
School of Public Health, 2023
Dissertation Supervisor: Andrew Springer, DrPH
Academic Advisor: Leah Whigham, PhD
Coronavirus disease 2019 (COVID-19), caused by a Severe Acute Respiratory
Syndrome Coronavirus-2 (SARS-CoV-2), remains a public health threat across the globe.
Since its index case in December 2019, COVID-19 has spread worldwide, claiming over one
million lives in the United States (U.S.), of which more than 93,000 were from Texas. As
with other zoonotic coronaviruses, SARS-CoV-2 spreads through contact with infected
respiratory secretions or contaminated surfaces. Social Determinants of Health (SDoH) may be associated with COVID-19 outcomes, such as mortality and low vaccination uptake. This
dissertation sought to examine the association of the Minority Health Social Vulnerability
Index (MH SVI), a composite measure of 34 SDoH indicators, with COVID-19 mortality and vaccination coverage in Texas and explore strategies of interventions employed to promote
COVID-19 vaccination uptake in theU.S.
Paper 1 uses an ecological analysis of counties to examine the cross-sectional
association of MH SVI and COVID-19 mortality among all populations in Texas. Using
Geographic Information System (GIS), the paper displays a bivariate relationship between county-level MH SVI and COVID-19 deaths per 100,000 population. In addition, the paper
uses the negative binomial regression to assess the association between the MH SVI and
COVID-19 mortality rates in Texas. Similarly, paper 2 employs an ecological analysis
approach to determine the association between the MH SVI and COVID-19 vaccination
coverage among adolescents in Texas. The paper also demonstrates the distribution of
COVID-19 vaccination coverage and county-level MH SVI by counties in Texas using the GIS. In addition, paper 2 uses the negative binomial regression to determine the association
between MH SVI and COVID-19 vaccination coverage in Texas counties among
adolescents. Finally, paper 3 describes and explores the effectiveness of COVID-19
vaccination promotion strategies in the U.S. This paper utilizes the Preferred Reporting Items
for Systematic review and Meta-Analysis (PRISMA) and a scoping review method by
Arksey & O’Malley (2005) to present various theoretical underpinnings, change methods,
and effectiveness of strategies aimed at promoting COVID-19 vaccination uptake in the U.S.
Overall, this dissertation contributes to the literature on COVID-19 pandemic
disparities. It also identifies specific vulnerabilities and SDoH indicators that health planners
need to focus on while implementing COVID-19 control programs in Texas and the U.S.
Finally, these findings offer opportunities for planners and researchers to expand
implementation science research and practice on vaccination interventions in the U.S.
TABLE OF CONTENTS
List of Tables ................................................................................................................. i
List of Figures .............................................................................................................. ii
Background................................................................................................................... 1
Literature Review..................................................................................................... 1
Conceptual Framework........................................................................................... 5
Public Health Significance ..................................................................................... 7
Specific Aim .............................................................................................................. 10
Specific Aims ....................................................................................................... 10
References ............................................................................................................ 13
Journal Article 1 ...................................................................................................... 18
Association of Social Vulnerability And COVID-19 Mortality Rates in Texas Between
March 15, 2020, and July 21, 2022: An EcologicalAnalysis................................ 18
Introduction .......................................................................................................... 19
Specific Aims ....................................................................................................... 21
Methods.................................................................................................................. 22
Results .................................................................................................................... 25
Discussion ............................................................................................................. 33
Conclusion............................................................................................................... 36
References .............................................................................................................. 38
Journal Article 2 .......................................................................................................... 42
The Association Between Social Vulnerability and COVID-19 Vaccination Coverage
Among Adolescents in Texas................................................................................... 42
Introduction ........................................................................................................... 43
Specific Aims ......................................................................................................... 45
Methods................................................................................................................... 46
Results .................................................................................................................... 48
Choropleth Map of the County-Level MH SVI and COVID-19 Vaccination Coverage in
Texas.................................................................................................................... 51
Discussion ............................................................................................................. 55
Conclusion............................................................................................................... 58
References .............................................................................................................. 59
Journal Article 3 .......................................................................................................... 63
Exploring COVID-19 Vaccination Intervention Strategies: A Scoping Review of Literature
................................................................................................................................. 63
Introduction ............................................................................................................ 64
Specific Aims ......................................................................................................... 66
Methods................................................................................................................... 66
Results .................................................................................................................... 69
Discussion .............................................................................................................. 81
Conclusion............................................................................................................... 85
References .............................................................................................................. 86
LIST OF TABLES
Background Table 1. Comparison between the "traditional" SVI and MH SVI ....... 8
Paper 1 Table 1. List of Study Variables and Data Sources ................................ 24
Paper 1 Table 2. County-level characteristics in Texas between March 15, 2020 – July 21,
2022............................................................................................................................. 26
Paper 1 Table 3. Association between Covariates and COVID-19 Mortality Rates, Texas,
March 15, 2020 – July 21, 2022 ............................................................................... 29
Paper 1 Table 4. Association between the composite county-level MH SVI, its components,
and COVID-19 Mortality Rates, Texas, March 15, 2020 – July 21, 2022 ............... 30
Paper 1 Table 5. Association between the county-level MH SVI subcomponents and
COVID-19 Mortality Rates, Texas, March 15, 2020 – July 21, 2022........................ 32
Paper 1 Table 6. Association between the county-level MH SVI subcomponents and
COVID-19 Mortality Rates, Texas, as of July 21, 2022............................................. 33
Paper 2 Table 1. Characteristics of counties by urbanicity in Texas ......................... 49
Paper 2 Table 2. Association between the composite county-level MH SVI, its components,
and COVID-19 Vaccination Coverage, Texas, May 10, 2021, to July 15, 2022 ... 53
Paper 2 Table 3. Association betweenthe MH SVI subcomponents, and COVID-19
Vaccination Coverage, Texas, May 10, 2021, to July 15, 2022 ............................. 54
Paper 3 Table 1. Characteristics of the studies included (n=8) as of December 31, 2022, in
the U.S......................................................................................................................... 71
Paper 3 Table 2. Intervention Strategies aimed at Promoting COVID-19 Vaccination
Coverage in the U.S ................................................................................................ 76
Paper 3 Table 3. Evidence of the Effectiveness of COVID-19 Interventions in Increasing
COVID-19 Vaccination Coverage ............................................................................. 80
LIST OF FIGURES
Background Figure 1. Conceptual framework of the influence of social vulnerability factors
on COVID-19 mortality and vaccination coverage .................................................... 6
Paper 1 Figure 1. Bivariate map showing the composite County-level MH SVI overlaid on
Mortality rate per 100 000 population for each county in Texas, March 2020 – July 2022... 28
Paper 2 Figure 1. Choropleth (side by side) maps showing the composite MH SVI and
COVID-19 vaccination coverage for each county in Texas ...................................... 51
Paper 3 Figure 1. PRISMA Flowchart for Study Selection
Process......................................................................................................................... 69
BACKGROUND
Coronavirus disease 2019 (COVID-19) is a highly contagious disease caused by
Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) [1-3]. COVID-19 is
suspected to be a zoonotic disease originating from bats, and spreadsmainly through directcontact with infected droplets, respiratory secretions, or contaminated objects [3,4]. Since December 2019, SARS-CoV-2 has infected over 676 million people and claimed close to 7
million lives as of March 10, 2023, globally [5]. The virus has also mutated to multiple
subvariants with higher transmissibility and the ability to neutralize antibodies [6,7].
Although studies indicate SARS-CoV-2 subvariants are less severe [8], evidence shows that
these mutations are likely to continue emerging, resulting in COVID-19 endemicity [9].
Continued spread of SARS-CoV-2 with low COVID-19 vaccination uptake is a key driving factor for COVID-19-related deaths and severe disease [10]. Understanding the role
of social factors contributing to COVID-19 adverse outcomes is necessary to protect lives
and control the pandemic [11]. Thus, this dissertation aims to examine the social factors
associated with increased COVID-19 mortality and low vaccinations in Texas and assess the evidence of the effectiveness of COVID-19 vaccination intervention strategies in the United
States (U.S.).
Literature Review
Since the first case of SARS-CoV-2 on January 20, 2020, the U.S. has recorded over
one million deaths as of March 10, 2023 [5]. During the same period, Texas, the second
largest state in the U.S. in size and population, reported 93,390 COVID-19-related deaths
[12]. In addition, Texas isamong the leading states with the highest cases (400+) of
Multisystem Inflammatory Syndrome (MIS-C), a rare but severe post-COVID-19 condition
affecting children and adolescents [13].
Although COVID-19 severity may vary from person to person, the most common
symptoms include fever, cough, headache, malaise, difficulty breathing, diarrhea, and
vomiting [1-4]. Infected individuals may also develop long COVID [2], septic shock,
coagulation dysfunction, and multiple organ failure [1,2]. Typically, these complications and
death occur among theelderly and people with underlying comorbidities such as diabetes,
heart disease, cancer, and asthma [1-3]. In addition, children and adolescents can develop
MIS-C [14] and post-COVID-19 syndrome [15].
Since its inception, COVID-19 vaccination has remained the most effective strategy
to control the pandemic, especially after relaxing mask and social distancing mandates
[16,17]. However, many U.S. residents are yet to receive the vaccine or do not plan to get
their children vaccinated[18]. For instance, as of March 1, 2023, over eight million
adolescents aged 12-17 were yet to receive their first dose of the COVID-19 vaccine [19].
Promoting healthy behaviors among adolescents, such as vaccination, is particularly
important given some evidence that positive behaviors learned during adolescence are likely
to persist to adulthood [20-22].
Understanding the role of social factors in COVID-19 adverse outcomes including
death and low vaccinations, is an important step toward mitigating the pandemic [11]. Social
Determinants of Health (SDoH) represent the distal factorsof influence that may shape
health outcomes, including COVID-19 vaccinations [23-25]. According to the World Health Organization (WHO), SDoH are “the forces and systems shaping the collective conditions in
which people are born, grow, work, live, and age, as well as the conditions of their daily
lives” [26]. Related to SDoH are social vulnerabilities, defined as the ability of groups or individuals to anticipate, cope, resist, and recover from the effects of a disaster or disease
outbreak [27], which may also contribute to increased COVID-19 mortality or low
vaccination uptake.
For example, most people with low socioeconomic status work in essential sectors
such as healthcare or transport industry [23], which puts them at risk of COVID-19 exposure. In addition, a study showed that individuals in the U.S. without high school diploma are less
likely to receive the COVID-19 vaccine [28]. Another study indicated that low-income
families were less likely to practice physical distancing or isolation, especially if they lived in
small housing settings with no extra rooms [24]. Furthermore, a recent ecological study
found that economic inequalities were positively correlated with COVID-19-related deaths
across all 3220 counties in the U.S. and its territories [29].
Health literacy and healthcare access defined as “the degree to which individuals
have the capacity to obtain, process, and understand basic health information needed tomake appropriate health decisions” and the “timely use of personal health services to achieve the best possible health outcomes,” respectively [30], can also influence COVID-19 outcomes. For example, health-literate people are likely to understand and follow prevention measures
such as vaccination andsocial distancing without presenting with skepticism [24]. Black,
Indigenous and People of Color (BIPOC) and the Hispanic population may lack health insurance, have low education and poor transportation, which are key factors for the low
utilization of healthcare services including vaccinations [25,28,31].
Social and community contexts from which people operate, live, work, learn, or grow
may also contribute to health outcomes. For instance, communities with good cohesion and
support tend tohave lower mortality rates and greater longevity [24]. On the contrary, racial discriminative and unsupportive environments contribute to adverse social outcomes such as high school dropouts, increased crime, and poverty, all associated with poor health outcomes
[24]. For example, there have been reports of stigmatization toward Black Americans for
using masks, bandanas, and other pieces of cloth in criminal activities [32]. Such
discriminatory perceptions and racial stereotypes jeopardize efforts to mitigate the COVID-
19 pandemic.
Poor housing, akey factor in social vulnerability, especially during natural
calamities, may also influence COVID-19 outcomes. For instance, people living in poor
housing structures may lack indoor plumbing and thus have limited access to potable water,
essential for personal hygiene [23]. Moreover, literature has also shown that crowded
housing units are responsible for the secondary transmission of COVID-19 [33]. In addition,
poor housing structures may have limited ventilation (an essential factor for indoor
transmission), molds, and tobacco smoke, which are precursors for asthma [24]. Nguyen et al. [34] also posit that individuals living in “other types” of housing, such as mobile homes, boats, vans, or recreational vehicles, were less likely to receive the COVID-19 vaccine than
those living inmulti-unit housing. Ahmad et al. [35] add that poor housing increased the
relative risk of COVID-19 incidence and mortality by 59% and 63%, respectively.
Neighborhoods and built environments can also be vital in understanding social
vulnerabilities associated with COVID-19 outcomes [23]. For instance, people living in areas with poor air quality are likely to develop asthma, a risk factor for COVID-19 mortality rates
[24]. Air pollutants such as atmospheric Particulate Matter (PM) can also function as
“vehicles” to drive the transmission of SARS-CoV-2 from one person to another [36]. In
addition, neighborhoods with lower income and education levels, lack of health insurance, and a higher percentage older than 65 years can be precursors for COVID-19 mortality and
low vaccine uptake [37]. Furthermore, neighborhoods with ahigher percentage of
households without internet may have limited access to health information and be less likely
to work from home, thus causing higher susceptibility to SARS-CoV-2 exposure [24].
Despite growing evidence on the factorscontributing to COVID-19 outcomes [38- 40], impact of social vulnerabilities on COVID-19 mortality and vaccination, has not been well established. Furthermore, research lacks a comprehensive assessment of the SDoH to understand better which indicators influence COVID-19 mortality and vaccination status in Texas. Additionally, no review studies to date have explored strategies that hold promise to
promote COVID-19 vaccination uptake among all populations in the U.S.
Conceptual Framework
Several frameworks have been utilized to understand the comprehensive assessment
of SDoH on health outcomes and inequities, including the Socio-ecological Model (SEM),
which demonstrates the complex interplay of individual, interpersonal, community, and
societal factors onhealth [41]. The socialvulnerability conceptual framework builds on SEM and incorporates SDoH to exhibit a risk model that could contribute to COVID-19 mortality and low vaccinations. Notably, social vulnerability has been posited to influence COVID-19 mortality and vaccinations in multiple interrelated ways (Figure 1). For instance, education
levels determine the employment status ofindividuals, which inturn impacts their income
levels and the health insurance status they hold, which determines the utilization of
healthcare services [24].
• Inaccessibility to Healthcare
• Medical Vulnerabilities (co-mobidities)
• Lack of Health Insurance
• Low health Literacy
Acknowledging the complexity of social vulnerability and health outcomes, the Centers for
Disease Control and Prevention (CDC) and Geospatial Research, Analysis & Services
Program (GRASP) created a measure to assist public health responders in identifying regions
and communities needing support before, during, or after adisaster or disease outbreak
High COVID-19
Infections
Background Figure 1.Conceptual framework of the influence of social vulnerability factors on COVID-19 mortality and vaccination coverage
Public Health Significance
COVID-19 remains a significant burden globally, including in the U.S. [1-3]. Recent reports indicate the emergence of new and troubling subvariants of SARS-CoV-2 [6,7] and likelihood of COVID-19 persisting to endemicity [9]. In addition, ethnic and racial minority groups and those with low social and economic status continue to experience worse health
outcomes due to COVID-19 [23,45].
Since the beginning of the pandemic, several population-based (ecological) studies
have used the SVI to predict COVID-19 outcomes, including mortality rates [43,46,47] and vaccination coverage [48-50]. However, this literature has utilizedonly four SVI components without exploring additional and potential social risk factors such as healthcare utilization,
medical vulnerabilities, and specific race categories and languages. Moreover, a recent
systematic review indicated SVI's inadequacy to incorporate indicators responsible for
vulnerabilities in pandemics [51].
In response to these SVI limitations, the Office of Minority Health at the U.S.
Department of Health and Human Services partnered with the CDC in2021 to develop the Minority Health Social Vulnerability Index (MHSVI) [52]. The new MH SVI incorporates the additional components and indicators: “medical vulnerability, health care infrastructure
and access, and specific race categories and languages" to make a total of 34 SDoH
indicators (Table 1).
Background Table 1.Comparison between the "traditional" SVI and MH SVI
Source: Minorityhealth.hhs.gov
Despite the existence of the modified SVI measure, to the best of my knowledge, no studies have examined the association between MH SVI and COVID-19 outcomes in Texas. In addition, past studies examining the association between SVI and COVID-19 outcomes
have focused on adult populations [46-49], even with the most recent study using the MH
SVI, assessed vaccination coverage among adults in the U.S [53], thus warranting extension
to younger populations such as the adolescents (12 -15-year-old, a recently approved
subgroup for COVID-19 vaccination by the FDA). Also, there are no scoping reviews
exploring COVID-19 vaccination promotion strategies among all populations in the U.S.
Therefore, the overarching aim of this dissertation is to examine associations of county-level
MH SVI and COVID-19 mortality rates and COVID-19 vaccination coverage among all
populations and adolescents in Texas, respectively, and assess the evidence of the
effectiveness of COVID-19 vaccination promotion interventions in the U.S.
Understanding how social vulnerabilities within MHSVI are associatedwith
COVID-19 outcomes will guide the design of public health interventions and policies and
direct future research related to COVID-19 and similar pandemics. In particular, the novel
MH SVI study contributes to the limited literature on medical vulnerabilities and healthcare
infrastructure and access with COVID-19 outcomes. Also, findings from this dissertation
align with the Healthy People 2030 affirmative call to agencies, professionals, and academics
to improve social environments where people are born, grow, live, and work and address
health inequities [44]. Finally, by exploring the association of individual SDoH factors (MH SVI subcomponents) with COVID-19, this dissertation identifies specific areas of focus in controlling COVID-19 pandemic and helps public health agencies to be better prepared for
future outbreaks.
SPECIFIC AIM
The overarching aim of this dissertation is to1) examine the association between county-level MH SVI and COVID-19 outcomes (mortality and vaccination coverage) in Texas; and 2) describe and assess evidence of strategies in literature aiming to promote
COVID-19 vaccinations among all populations in the U.S. The specific aims of the
dissertation research are as follow:
Specific Aims
Paper 1
Aim 1. To assess the association between the county-level composite MH SVI and COVID-
19 mortality rates in Texas from March 15, 2020,to July 21, 2022.
. Hypothesis: County-level composite MH SVI will be significantly and positively
associated with COVID-19 mortality rates in Texas counties.
Aim 2. To examine the independent association between county-level MH SVI components (socioeconomic status, household composition and disability, minority status and language,
housing type and transportation, health care infrastructure and access, and medical
vulnerability) and their subcomponents (i.e., individual SDoH indicators for each
component) and COVID-19 mortality rates in Texas from March 15, 2020, to July 21, 2022.
. Hypothesis: County-level MH SVI individual components (and their
subcomponents) will be positively and significantly associated with COVID-19
mortality rates in Texas counties.
Aim 3. To evaluate the association between minority status (racial/ethnic and language) and
COVID-19 mortality rates.
. Hypothesis: Minority status (racial/ethnic and language) will be positively and
significantly associated with COVID-19 mortality rates in Texas counties.
Paper 2
Aim 1. To assess the association between county-level composite MH SVI and COVID-19 vaccination coverage among Texas adolescents (12–15-year-olds) from May 10, 2021 to July
15, 2022.
. Hypothesis: County-level composite MH SVI will be significantly and inversely associated with COVID-19 vaccination coverage among adolescents (12–15-year-
olds) in Texas counties.
Aim 2. To assess the independent association between county-level MH SVI components (socioeconomic status, household composition and disability, minority status and language,
housing type and transportation, health care infrastructure and access, and medical
vulnerability) and COVID-19 vaccination coverage among adolescents (12–15-year-olds) in
Texas from May 10, 2021 to July 15, 2022.
. Hypothesis: Each county-level MH SVI component score will be inversely
associated with COVID-19 vaccination coverage among adolescents (12–15-year-
olds) in Texas counties.
Aim 3. To examine the independent association between county-level MH SVI
subcomponents and COVID-19 vaccination coverage among adolescents (12–15-year-olds)
in Texas from May 10, 2021 to July 15, 2022.
. Hypothesis: County-level MH SVI subcomponents will be significantly and
inversely associated with COVID-19 vaccination coverage among adolescents (12–
15-year-olds) in Texas counties.
Paper 3
Aim 1. To describe the characteristics of intervention studies conducted to date (December
31, 2022) on COVID-19 vaccination promotion strategies among all populations in the U.S.,
including study designs, length of evaluation, study measures, and study sample
characteristics.
Aim 2. To describe the interventions that have been conducted in the U.S. to promote
COVID-19 vaccination coverage among all populations, including their theoretical basis, type of change methods used, settings of interventions, length of interventions, and other
delivery-related characteristics that include mode of delivery of interventions.
Aim 3. To describe the evidence of the effectiveness of COVID-19 interventions in
increasing COVID-19 vaccination coverage among all populations in the U.S.
REFERENCES
1. Ahn, D.-G., Shin, H.-J., Kim, M.-H., Lee, S., Kim, H.-S., Myoung, J., Kim, B.-T., & Kim, S.-J. Current Status of Epidemiology, Diagnosis, Therapeutics, and Vaccines forNovel Coronavirus Disease 2019 (COVID-19). Journal of Microbiology and
Biotechnology. 2020, 30(3), 313–324. https://doi.org/10.4014/jmb.2003.03011
2. Cabrera Martimbianco, A. L., Pacheco, R. L., Bagattini, Â. M., & Riera, R. Frequency,
signs and symptoms, and criteria adopted for long COVID-19: A systematic review.
International Journal of Clinical Practice. 2021, 75(10), e14357.
https://doi.org/10.1111/ijcp.14357
3. Rahman, S., Montero, M. T. V., Rowe, K., Kirton, R., & Kunik, F. Epidemiology,
pathogenesis, clinical presentations, diagnosis and treatment of COVID-19: A review of current evidence. Expert Review of Clinical Pharmacology. 2021, 14(5), 601–621.
https://doi.org/10.1080/17512433.2021.1902303
4. Jin, Y., Yang, H., Ji, W., Wu, W., Chen, S., Zhang, W., & Duan, G. Virology,
Epidemiology, Pathogenesis, and Control of COVID-19. Viruses. 2020, 12(4), E372. https://doi.org/10.3390/v12040372
5. John Hopkins Coronavirus Resource Center. Coronavirus COVID-19 Global Cases by
the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University
(JHU). Available online: https://coronavirus.jhu.edu/map.html [accessed March 10 2023].
6. Gobeil, S. M.-C., Henderson, R., Stalls, V., Janowska, K., Huang, X., May, A.,
Speakman, M., Beaudoin, E., Manne, K., Li, D., Parks, R., Barr, M., Deyton, M., Martin, M., Mansouri, K., Edwards, R. J., Eaton, A., Montefiori, D. C., Sempowski, G. D., …
Acharya, P. Structural diversity of the SARS-CoV-2 Omicron spike. Molecular Cell. 2022, 82, 2050 – 2068. https://doi.org/10.1016/j.molcel.2022.03.028
7. Gowrisankar, A., Priyanka, T. M. C., & Banerjee, S. Omicron: A mysterious variant of
concern. The European Physical Journal Plus. 2022, 137(1), 100.
https://doi.org/10.1140/epjp/s13360-021-02321-y
8. Rahimi, F., & Abadi, A. T. B. The Omicron subvariant BA. 2: Birth of a new challenge during the COVID-19 pandemic. International Journal of Surgery (London, England). 2022, 99, 106261.
9. Lavine, J. S., Bjornstad, O. N., & Antia, R. Immunological characteristics govern the transition of COVID-19 to endemicity. Science. 2021, 371(6530), 741–745.
https://doi.org/10.1126/science.abe6522
10. Cuadros DF, Moreno CM, Musuka G, Miller FD, Coule P and MacKinnon NJ.
Association Between Vaccination Coverage Disparity and the Dynamics of the COVID- 19 Delta and Omicron Waves in the US. Front. Med. 2022, 9:898101. doi:
10.3389/fmed.2022.898101.
11. Sah, P., Moghadas, S. M., Vilches, T. N., Shoukat, A., Singer, B. H., Hotez, P. J.,
Schneider, E. C., & Galvani, A. P. Implications of suboptimal COVID-19 vaccination
coverage in Florida and Texas. The Lancet Infectious Diseases. 2021, 21(11), 1493–1494. https://doi.org/10.1016/S1473-3099(21)00620-4
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