COVID-19 Vaccination Intention and Factors Associated with Hesitance and Resistance in the Deep South: Montgomery, Alabama
Abstract
:1. Introduction
2. Materials and Methods
2.1. Outcomes of Interest
2.2. Independent Variables
2.2.1. Demographics
2.2.2. COVID-19 Positivity and Mask Wearing
2.2.3. COVID-19 Information and Messaging
2.2.4. Level of Trust in the Accuracy of Information about the COVID-19 Vaccine from Sources
2.2.5. COVID-19 Vaccine Protection, Vaccine Development, and Vaccine Side-Effects
2.2.6. Racism in Healthcare
2.2.7. Food and Financial Impacts from the COVID-19 Pandemic
2.2.8. Mandatory COVID-19 Vaccinations
2.3. Statistical Analysis
3. Results
3.1. Demographics
3.2. COVID-19 Positivity and Mask Wearing
3.3. COVID-19 Information and Messaging
3.4. Level of Trust in the Accuracy of Information about the COVID-19 Vaccine from Sources
3.5. COVID-19 Vaccine Protection, Vaccine Development, and Vaccine Side-Effects
3.6. Racism in Healthcare
3.7. Food and Financial Impacts of the COVID-19 Pandemic and Mandatory Vaccinations
3.8. COVID-19 Vaccination Intention
3.9. Feature Importance Analysis
3.10. Multivariate Analysis: COVID-19 Vaccine Hesitancy
3.11. Multivariate Analysis: COVID-19 Vaccine Resistance
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Yuki, Y.; Fujiogi, M.; Koutsogiannaki, S. COVID-19 pathophysiology: A review. Clin. Immunol. 2020, 215, 108427. [Google Scholar] [CrossRef] [PubMed]
- Chan, J.F.-W.; Yuan, S.; Kok, K.-H.; To, K.K.-W.; Chu, H.; Yang, J.; Xing, F.; Liu, J.; Yip, C.C.-Y.; Poon, R.W.-S.; et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: A study of a family cluster. Lancet 2020, 395, 514–523. [Google Scholar] [CrossRef] [Green Version]
- Eguia, R.T.; Crawford, K.H.D.; Stevens-Ayers, T.; Kelnhofer-Millevolte, L.; Greninger, A.L.; Englund, J.A.; Boeckh, M.J.; Bloom, J.D. A human coronavirus evolves antigenically to escape antibody immunity. PLoS Pathog. 2021, 17, e1009453. [Google Scholar] [CrossRef] [PubMed]
- Berlin, D.A.; Gulick, R.M.; Martinez, F.J. Severe Covid-19. N. Engl. J. Med. 2020, 383, 2451–2460. [Google Scholar] [CrossRef] [PubMed]
- Guo, T.; Fan, Y.; Chen, M.; Wu, X.; Zhang, L.; He, T.; Wang, H.; Wan, J.; Wang, X.; Lu, Z. Cardiovascular Implications of Fatal Outcomes of Patients With Coronavirus Disease 2019 (COVID-19). JAMA Cardiol. 2020, 5, 811. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bilinski, A.; Emanuel, E.J. COVID-19 and Excess All-Cause Mortality in the US and 18 Comparison Countries. JAMA 2020, 324, 2100. [Google Scholar] [CrossRef]
- CDC. COVID Data Tracker. Available online: https://covid.cdc.gov/covid-data-tracker/#vaccination-demographics-trends (accessed on 9 August 2022).
- Mohammed, I.; Nauman, A.; Paul, P.; Ganesan, S.; Chen, K.-H.; Jalil, S.M.S.; Jaouni, S.H.; Kawas, H.; Khan, W.A.; Vattoth, A.L.; et al. The efficacy and effectiveness of the COVID-19 vaccines in reducing infection, severity, hospitalization, and mortality: A systematic review. Hum. Vaccines Immunother. 2022, 18, 1–20. [Google Scholar] [CrossRef]
- WHO. Ten Threats to Global Health in 2019. Available online: https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-2019 (accessed on 9 March 2022).
- JHU. COVID-19 Dashboard. Available online: https://coronavirus.jhu.edu/vaccines/international (accessed on 9 August 2022).
- CDC. COVID-19 Vaccination Trends in the United States, National and Jurisdictional, 2 August 2022 ed; Centers for Disease Control and Prevention: Atlanta, GA, USA, 2022. [Google Scholar]
- Vasan, R.S.; Zuo, Y.; Kalesan, B. Divergent Temporal Trends in Morbidity and Mortality Related to Heart Failure and Atrial Fibrillation: Age, Sex, Race, and Geographic Differences in the United States, 1991–2015. J. Am. Heart Assoc. 2019, 8, e010756. [Google Scholar] [CrossRef] [Green Version]
- Loop, M.S.; Howard, G.; De Los Campos, G.; Al-Hamdan, M.Z.; Safford, M.M.; Levitan, E.B.; McClure, L.A. Heat Maps of Hypertension, Diabetes Mellitus, and Smoking in the Continental United States. Circ. Cardiovasc. Qual. Outcomes 2017, 10, e003350. [Google Scholar] [CrossRef] [Green Version]
- U.S. Census Bureau, U.S.C. 2010 Census Shows Black Population has Highest Concentration in the South. 2010. Available online: https://www.census.gov/newsroom/releases/archives/2010_census/cb11-cn185.html (accessed on 9 March 2022).
- ADPH. Alabama’s COVID-19 Vaccine Distribution Dashboard. Available online: https://alpublichealth.maps.arcgis.com/apps/dashboards/e4a232feb1344ce0afd9ac162f3ac4ba (accessed on 9 August 2022).
- Bureau, U.S.C. Quick Facts: Montgomery City Alabama. Available online: https://www.census.gov/quickfacts/fact/table/montgomerycityalabama/PST040221 (accessed on 9 August 2022).
- Romer, D.; Jamieson, K.H. Conspiracy theories as barriers to controlling the spread of COVID-19 in the U.S. Soc. Sci. Med. 2020, 263, 113356. [Google Scholar] [CrossRef]
- Khubchandani, J.; Macias, Y. COVID-19 vaccination hesitancy in Hispanics and African-Americans: A review and recommendations for practice. Brain Behav. Immun. Health 2021, 15, 100277. [Google Scholar] [CrossRef] [PubMed]
- Chevallier, C.; Hacquin, A.-S.; Mercier, H. COVID-19 Vaccine Hesitancy: Shortening the Last Mile. Trends Cogn. Sci. 2021, 25, 331–333. [Google Scholar] [CrossRef] [PubMed]
- Soares, P.; Rocha, J.V.; Moniz, M.; Gama, A.; Laires, P.A.; Pedro, A.R.; Dias, S.; Leite, A.; Nunes, C. Factors Associated with COVID-19 Vaccine Hesitancy. Vaccines 2021, 9, 300. [Google Scholar] [CrossRef] [PubMed]
- Sallam, M. COVID-19 Vaccine Hesitancy Worldwide: A Concise Systematic Review of Vaccine Acceptance Rates. Vaccines 2021, 9, 160. [Google Scholar] [CrossRef]
- Pomara, C.; Sessa, F.; Ciaccio, M.; Dieli, F.; Esposito, M.; Giammanco, G.M.; Garozzo, S.F.; Giarratano, A.; Prati, D.; Rappa, F.; et al. COVID-19 Vaccine and Death: Causality Algorithm According to the WHO Eligibility Diagnosis. Diagnostics 2021, 11, 955. [Google Scholar] [CrossRef]
- Dror, A.A.; Eisenbach, N.; Taiber, S.; Morozov, N.G.; Mizrachi, M.; Zigron, A.; Srouji, S.; Sela, E. Vaccine hesitancy: The next challenge in the fight against COVID-19. Eur. J. Epidemiol. 2020, 35, 775–779. [Google Scholar] [CrossRef]
- Troiano, G.; Nardi, A. Vaccine hesitancy in the era of COVID-19. Public Health 2021, 194, 245–251. [Google Scholar] [CrossRef]
- Oquendo, M.A.; Baca-Garcia, E.; Artés-Rodríguez, A.; Perez-Cruz, F.; Galfalvy, H.C.; Blasco-Fontecilla, H.; Madigan, D.; Duan, N. Machine learning and data mining: Strategies for hypothesis generation. Mol. Psychiatry 2012, 17, 956–959. [Google Scholar] [CrossRef] [Green Version]
- Peng, L.-N.; Hsiao, F.-Y.; Lee, W.-J.; Huang, S.-T.; Chen, L.-K. Comparisons Between Hypothesis- and Data-Driven Approaches for Multimorbidity Frailty Index: A Machine Learning Approach. J. Med. Internet Res. 2020, 22, e16213. [Google Scholar] [CrossRef]
- Sheetal, A.; Feng, Z.; Savani, K. Using Machine Learning to Generate Novel Hypotheses: Increasing Optimism About COVID-19 Makes People Less Willing to Justify Unethical Behaviors. Psychol Sci 2020, 31, 1222–1235. [Google Scholar] [CrossRef]
- Friederich, P.; Krenn, M.; Tamblyn, I.; Aspuru-Guzik, A. Scientific intuition inspired by machine learning-generated hypotheses. Mach. Learn. Sci. Technol. 2021, 2, 025027. [Google Scholar] [CrossRef]
- Guo, Y.; Yin, S.; Chen, S.; Ge, Y. Predictors of underutilization of lung cancer screening: A machine learning approach. Eur. J. Cancer Prev. 2022, 31, 523–529. [Google Scholar] [CrossRef] [PubMed]
- Ruan, J.; Xu, Y.M.; Zhong, B.L. Depressive disorders in older Chinese adults with essential hypertension: A classification tree analysis. Front. Cardiovasc. Med. 2022, 9, 1035203. [Google Scholar] [CrossRef]
- Kelly, B.J.; Southwell, B.G.; McCormack, L.A.; Bann, C.M.; Macdonald, P.D.M.; Frasier, A.M.; Bevc, C.A.; Brewer, N.T.; Squiers, L.B. Predictors of willingness to get a COVID-19 vaccine in the U.S. BMC Infect. Dis. 2021, 21, 338. [Google Scholar] [CrossRef] [PubMed]
- McElfish, P.A.; Willis, D.E.; Shah, S.K.; Bryant-Moore, K.; Rojo, M.O.; Selig, J.P. Sociodemographic Determinants of COVID-19 Vaccine Hesitancy, Fear of Infection, and Protection Self-Efficacy. J. Prim. Care Community Health 2021, 12, 215013272110407. [Google Scholar] [CrossRef]
- United States Census Bureau. Who Are the Adults Not Vaccinated against COVID? Available online: https://www.census.gov/library/stories/2021/12/who-are-the-adults-not-vaccinated-against-covid.html (accessed on 9 March 2022).
- Cavanaugh, A.M.; Spicer, K.B.; Thoroughman, D.; Glick, C.; Winter, K. Reduced Risk of Reinfection with SARS-CoV-2 After COVID-19 Vaccination—Kentucky, May–June 2021. MMWR Morb. Mortal. Wkly. Rep. 2021, 70, 1081–1083. [Google Scholar] [CrossRef]
- Kreps, S.; Prasad, S.; Brownstein, J.S.; Hswen, Y.; Garibaldi, B.T.; Zhang, B.; Kriner, D.L. Factors Associated with US Adults’ Likelihood of Accepting COVID-19 Vaccination. JAMA Netw. Open 2020, 3, e2025594. [Google Scholar] [CrossRef]
- Ward, J.K.; Alleaume, C.; Peretti-Watel, P. The French public’s attitudes to a future COVID-19 vaccine: The politicization of a public health issue. Soc. Sci. Med. 2020, 265, 113414. [Google Scholar] [CrossRef]
- Detoc, M.; Bruel, S.; Frappe, P.; Tardy, B.; Botelho-Nevers, E.; Gagneux-Brunon, A. Intention to participate in a COVID-19 vaccine clinical trial and to get vaccinated against COVID-19 in France during the pandemic. Vaccine 2020, 38, 7002–7006. [Google Scholar] [CrossRef]
- Puri, N.; Coomes, E.A.; Haghbayan, H.; Gunaratne, K. Social media and vaccine hesitancy: New updates for the era of COVID-19 and globalized infectious diseases. Hum. Vaccines Immunother. 2020, 16, 2586–2593. [Google Scholar] [CrossRef]
- Baines, A.; Ittefaq, M.; Abwao, M. #Scamdemic, #Plandemic, or #Scaredemic: What Parler Social Media Platform Tells Us about COVID-19 Vaccine. Vaccines 2021, 9, 421. [Google Scholar] [CrossRef] [PubMed]
- Schaffer Deroo, S.; Pudalov, N.J.; Fu, L.Y. Planning for a COVID-19 Vaccination Program. JAMA 2020, 323, 2458. [Google Scholar] [CrossRef] [PubMed]
- Chen, H.; Li, X.; Gao, J.; Liu, X.; Mao, Y.; Wang, R.; Zheng, P.; Xiao, Q.; Jia, Y.; Fu, H.; et al. Health Belief Model Perspective on the Control of COVID-19 Vaccine Hesitancy and the Promotion of Vaccination in China: Web-Based Cross-sectional Study. J. Med. Internet Res. 2021, 23, e29329. [Google Scholar] [CrossRef] [PubMed]
- Wong, L.P.; Alias, H.; Wong, P.-F.; Lee, H.Y.; Abubakar, S. The use of the health belief model to assess predictors of intent to receive the COVID-19 vaccine and willingness to pay. Hum. Vaccines Immunother. 2020, 16, 2204–2214. [Google Scholar] [CrossRef]
Variables | n (%)/Mean (sd) |
---|---|
N = 1000 | |
Demographics | |
Age | |
18–29 | 216 (21.6%) |
30–44 | 270 (27.0%) |
45–64 | 311 (31.1%) |
≥65 | 203 (20.3%) |
Race | |
Black/African American | 607 (60.7%) |
White/Caucasian | 304 (30.4%) |
Other | 89 (8.9%) |
Gender | |
Male | 463 (46.3%) |
Female | 523 (52.3%) |
Prefer to self-describe | 14 (1.4%) |
Highest Level of Education Completed | |
High school graduate or less | 350 (35.0%) |
Some college/technical school | 300 (30.0%) |
University undergraduate degree | 200 (20.0%) |
Post-graduate degree | 150 (15.0%) |
Have children <18 years old living in your house | 296 (29.6%) |
COVID-19 Positivity and Mask Wearing | |
Have you or anyone you know tested positive for COVID-19? | |
Yes, I have | 54 (5.4%) |
Yes, someone I know | 683 (68.3%) |
Yes, I have and someone I know | 37 (3.7%) |
No, neither | 225 (22.5%) |
Do you know anyone who has received a COVID-19 vaccine shot? | |
No | 386 (38.6%) |
Yes | 614 (61.4%) |
Since the start of the new year, how often have you worn a mask while in public places? | |
Never | 20 (2.0%) |
Rarely | 25 (2.5%) |
Sometimes | 56 (5.6%) |
Most of the time | 134 (13.4%) |
All of the time | 766 (76.6%) |
COVID-19 Information and Messaging | |
From the list below, what information about COVID-19 has been the | |
most difficult for you to understand or find? | |
How to keep yourself safe from COVID-19 | 152 (10.56%) |
When and where to get tested for COVID-19 | 242 (24.90%) |
What to do when you feel sick | 75 (8.33%) |
Information about COVID-19 vaccine safety | 220 (16.18%) |
Information about COVID-19 vaccine availability | 312 (40.01%) |
The public health messages I have heard about COVID-19 have been clear and easy to understand | 3.1 (0.9) |
Trust | |
To what extent do you trust each of the following sources to provide you with accurate information about the COVID-19 vaccine: | |
Employer | 3.4 (1.3) |
Healthcare providers | 4.1 (1.1) |
Locally elected government officials | 3.2 (1.3) |
Elected officials in the federal government | 3.2 (1.4) |
Officials in the state’s department of public health | 3.7 (1.2) |
Friends and Family | 3.7 (1.1) |
Local television news | 3.5 (1.2) |
National television news | 3.2 (1.3) |
Social media, such as Facebook, Twitter and Instagram | 2.3 (1.2) |
Religious organizations | 3.2 (1.3) |
COVID-19 Vaccine Protection, Vaccine Development, and Vaccine Side-Effects | |
Based on what you know about the COVID-19 vaccine, how confident would you be that it would protect you and your family from getting sick with COVID-19? | 3.7 (1.2) |
How confident are you that the development of the COVID-19 vaccine is taking the needs of Black people into account? | 3.4 (1.3) |
How concerned are you that there would be side-effects from the new COVID-19 vaccines? | 3.9 (1.2) |
Racism in Healthcare | |
Generally speaking, how often do you think our healthcare systemtreats people unfairly based on their race or ethnic background? | 3.3 (1.2) |
Food and Financial Impacts of the COVID-19 Pandemic and Mandatory Vaccinations | |
Has the COVID-19 pandemic caused you to have a lack of food at any time? | |
No | 714 (71.4%) |
Yes | 286 (28.6%) |
Since the start of the COVID-19 pandemic, would you say you and your household are better off or worse off financially than you were before the pandemic? | |
Better off | 380 (38.0%) |
Worse off | 620 (62.0%) |
Now looking ahead, do you think during the next 12 months you and your household will be better off financially or worse off, or just about the same as now? | |
Better off | 181 (18.1%) |
Worse off | 250 (25.0%) |
About the same | 569 (56.9%) |
Though there are no plans for it, do you feel making the COVID-19 vaccine mandatory statewide is a beneficial or harmful idea? | |
Don’t know | 159 (15.9%) |
Neither | 93 (9.3%) |
Harmful | 247 (24.7%) |
Beneficial | 500 (50.0%) |
Vaccination Intention | |
Vaccine Intention when the Vaccine Becomes Available to You | |
Yes/Acceptance (as soon as it’s available) | 623 (62.3%) |
Wait/Hesitancy (combine a few weeks/months/a year after it’s available) | 226 (22.6%) |
Resistance/No (I won’t get the vaccine ever) | 151 (15.1%) |
Of those with vaccine acceptance, the main motivation to get the vaccine right away | |
To protect myself from COVID-19 | 318 (51.0%) |
I want to protect my community | 55 (8.9%) |
To protect those around me from COVID-19 | 104 (16.8%) |
To help end the pandemic more quickly | 126 (20.3%) |
Other | 19 (3.0%) |
Of those with vaccine acceptance, where would you prefer to get vaccinated | |
Local Pharmacy like CVS or Walgreens | 254 (28.9%) |
Hospital | 169 (19.2%) |
Sports Stadium | 18 (2.0%) |
Your Doctor’s Office | 289 (32.9%) |
Mobile unit deployed by the department of health in your neighborhood | 87 (9.9%) |
Local schools | 17 (1.9%) |
At a mall | 16 (1.8%) |
Somewhere else | 29 (3.3%) |
Of those with vaccine hesitancy, the top reason for the wait | |
See how it works in other people | 26 (15.1%) |
Let high-risk people go first | 81 (47.2%) |
Wait until it is easier to get one | 43 (24.9%) |
Other | 22 (12.8%) |
Importance Ranking | Feature Importance Scores | Variables |
---|---|---|
1 | 0.13 | Level of confidence in the COVID-19 vaccine providing protection from COVID-19 |
2 | 0.09 | Level of trust in accuracy of COVID-19 vaccine information: Healthcare providers |
3 | 0.06 | Frequency of mask wearing while in public places |
4 | 0.06 | Level of COVID-19 vaccine side-effects concerns |
5 | 0.06 | Level of trust in accuracy of COVID-19 vaccine information: Locally elected government officials |
6 | 0.05 | Age |
7 | 0.04 | Level of trust in accuracy of COVID-19 vaccine information: Officials in the state’s department of public health |
8 | 0.04 | Level of trust in accuracy of COVID-19 vaccine information: Local television news |
9 | 0.04 | Level of trust in accuracy of COVID-19 vaccine information: Elected officials in the federal government |
10 | 0.03 | Frequency of racism in healthcare system |
11 | 0.03 | Level of trust in accuracy of COVID-19 vaccine information: Employer |
12 | 0.03 | Public health messages: Clear and easy to understand |
13 | 0.03 | Level of trust in accuracy of COVID-19 vaccine information: Social media |
14 | 0.03 | Education level |
15 | 0.03 | Level of trust in accuracy of COVID-19 vaccine information: Family and friends |
16 | 0.03 | Level of trust in accuracy of COVID-19 vaccine information: Religious organizations |
17 | 0.02 | Level of trust in accuracy of COVID-19 vaccine information: National television news |
18 | 0.02 | Race |
19 | 0.02 | COVID-19 vaccine development is taking the needs of Black people into account |
20 | 0.02 | COVID-19 pandemic caused a lack of food at any time |
21 | 0.02 | COVID-19 positivity: You or anyone you know |
22 | 0.02 | Children <18 years old living at home |
23 | 0.02 | Future financial impact of the COVID-19 pandemic |
24 | 0.02 | Know anyone who has received the COVID-19 vaccine |
25 | 0.01 | Current financial impact of the COVID-19 pandemic |
26 | 0.01 | Gender |
COVID-19 Vaccination Intention | ||||||||
---|---|---|---|---|---|---|---|---|
Hesitancy (Reference: Acceptance) | Resistance (Reference: Acceptance) | |||||||
aOR | 95%, CI | p-Value | aOR | 95%, CI | p-Value | |||
Age | 0.42 | 0.29 | 0.61 | 0.00 | 0.15 | 0.07 | 0.32 | 0.00 |
Race (reference: White/Caucasian) | ||||||||
Black/African American | 1.14 | 0.58 | 2.24 | 0.71 | 1.09 | 0.35 | 3.42 | 0.88 |
Other | 1.96 | 0.60 | 6.43 | 0.27 | 2.25 | 0.99 | 2.11 | 0.05 |
Female (reference: male) | 1.95 | 1.02 | 3.73 | 0.04 | 4.45 | 1.15 | 1.73 | 0.03 |
Education level | 1.21 | 0.88 | 1.65 | 0.25 | 0.82 | 0.45 | 1.48 | 0.51 |
Frequency of wearing a mask while in public places | 0.40 | 0.29 | 0.56 | 0.00 | 0.26 | 0.14 | 0.47 | 0.00 |
Based on what you know about the COVID-19 vaccine, how confident would you be that it would protect you and your family from getting sick with COVID-19? | 0.68 | 0.47 | 0.98 | 0.04 | 0.25 | 0.16 | 0.41 | 0.00 |
How concerned are you that there would be side-effects from the COVID-19 vaccine. | 0.57 | 0.32 | 1.04 | 0.07 | 0.78 | 0.48 | 1.27 | 0.31 |
Generally speaking, how often do you think our healthcare system treats people unfairly based on their race or ethnic background (i.e., racism in healthcare) | 1.06 | 0.84 | 1.34 | 0.61 | 0.81 | 0.57 | 1.14 | 0.23 |
Public health messages I have heard about COVID-19 have been clear and easy to understand | 0.57 | 0.42 | 0.78 | 0.00 | 1.24 | 0.67 | 2.30 | 0.49 |
To what extent do you trust that the following sources to provide you with accurate information about the COVID-19 vaccine: | ||||||||
Healthcare providers | 0.92 | 0.66 | 1.27 | 0.60 | 0.32 | 0.18 | 0.58 | 0.00 |
Locally elected government officials | 0.84 | 0.57 | 1.24 | 0.37 | 0.55 | 0.32 | 0.94 | 0.03 |
Officials in the state’s department of public health | 0.92 | 0.68 | 1.24 | 0.58 | 0.53 | 0.30 | 0.93 | 0.03 |
Local television news | 0.93 | 0.65 | 1.34 | 0.70 | 0.78 | 0.50 | 1.21 | 0.27 |
Elected officials in the federal government | 0.93 | 0.63 | 1.36 | 0.70 | 0.95 | 0.57 | 1.56 | 0.83 |
Employer | 0.87 | 0.66 | 1.15 | 0.33 | 1.00 | 0.67 | 1.49 | 0.99 |
Social media, such as Facebook, Twitter, and Instagram | 1.21 | 0.87 | 1.68 | 0.26 | 1.62 | 1.03 | 2.54 | 0.04 |
Friends and family | 1.51 | 1.03 | 2.20 | 0.03 | 1.18 | 0.66 | 2.13 | 0.58 |
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Gray, C.A.; Lesser, G.; Guo, Y.; Shah, S.; Allen, S.; Wilkinson, L.L.; Sims, O.T. COVID-19 Vaccination Intention and Factors Associated with Hesitance and Resistance in the Deep South: Montgomery, Alabama. Trop. Med. Infect. Dis. 2022, 7, 331. https://doi.org/10.3390/tropicalmed7110331
Gray CA, Lesser G, Guo Y, Shah S, Allen S, Wilkinson LL, Sims OT. COVID-19 Vaccination Intention and Factors Associated with Hesitance and Resistance in the Deep South: Montgomery, Alabama. Tropical Medicine and Infectious Disease. 2022; 7(11):331. https://doi.org/10.3390/tropicalmed7110331
Chicago/Turabian StyleGray, Cicily A., Grace Lesser, Yuqi Guo, Swapn Shah, Shauntice Allen, Larrell L. Wilkinson, and Omar T. Sims. 2022. "COVID-19 Vaccination Intention and Factors Associated with Hesitance and Resistance in the Deep South: Montgomery, Alabama" Tropical Medicine and Infectious Disease 7, no. 11: 331. https://doi.org/10.3390/tropicalmed7110331