Skip to main content
Elsevier - PMC COVID-19 Collection logoLink to Elsevier - PMC COVID-19 Collection
. 2021 Dec 5;57:103450. doi: 10.1016/j.msard.2021.103450

COVID-19 Vaccine intent in appalachian patients with multiple sclerosis

Hongyan Wu a,, Melanie Ward a, Ashlyn Brown b, Erica Blackwell a, Amna Umer c
PMCID: PMC8645289  PMID: 34911005

Abstract

Background: Rural people with Multiple Sclerosis (PwMS) face distinctive challenges in the COVID-19 pandemic. The purpose of this study was to determine the COVID-19 vaccine intent and factors associated with vaccine hesitancy among Appalachian adults with MS.

Method: We conducted a cross sectional phone and in-person survey of PwMS in a large academic center in West Virginia (WV) from February to May 2021. The study sample consists of 306 adult participants.

Results: Among the 306 participants, 104 (33.99%) indicated vaccine hesitancy. Statistically significant factors (p<0.05) associated with vaccine hesitancy compared to those who received or intend to get vaccinated included concerns about vaccine safety, vaccine causing MS relapse, vaccine making MS medication ineffective, vaccine causing other diseases, getting the COVID-19 infection, vaccine fast approval, vaccine ingredients, how well the vaccine works, and its side-effects. Additional factors included prior bad experiences with other vaccines, history of not getting the flu vaccine, and lack of consultation about COVID-19 vaccine with healthcare providers.

Conclusions: Vaccine hesitancy among Appalachian adult PwMS is higher compared to PwMS in the larger United States. Vaccine hesitancy is especially higher among those who are female, younger than 50 years old, and residing in rural areas. Concerns about vaccine safety, perception of infection risks, past vaccine behaviors and consultation with healthcare providers are important factors associated with vaccine intent. Factors influencing vaccine hesitancy in Appalachian PwMS are largely consistent with the general public, however, concerns for interaction between the vaccine and MS are specific to this population and thus could be the focus of further vaccine effort.

Keywords: Multiple sclerosis, COVID-19 vaccine, Vaccine intent, Appalachian, Vaccine hesitancy


Abbreviations

CI

Confidential Interval

COVID-19

Coronavirus disease 2019

DMT

Disease Modifying Therapy

MS

Multiple Sclerosis

OR

Odds Ratio

PwMS

People with multiple sclerosis

SD

Standard Deviation

WV

West Virginia

US

United States

1. Introduction

The unprecedented scale and severity of the current COVID-19 pandemic has catalyzed joint efforts globally to develop vaccines against the COVID-19 infection (Li et al., 2021). Despite the well-known fact that vaccinations have contributed to the significant reduction in mortality, morbidity and the eradication of several infectious diseases in the past, vaccine hesitancy, defined as “delay in acceptance or refusal of vaccination despite availability of vaccination services” (MacDonald and SWGoV, 2015) continues to post as a main hurdle to overcoming COVID-19. Rural PwMS face distinctive challenges in the pandemic (Murthy et al., 2021). Immunosuppressive mechanisms of action of some MS disease modifying therapies (DMTs) have raised concerns regarding increased risk of severe COVID-19 complications (Reyes et al., 2021; Simpson-Yap et al., 2021). Comorbidities and degree of MS-related disability may also influence risk of severe COVID-19 disease course in PwMS (Reyes et al., 2021; Chaudhry et al., 2020). PwMS living in rural areas may have more underlying chronic health conditions and less access to healthcare as well as lack of health insurances which puts them at additional disadvantage for COVID-19 complications (Murthy et al., 2021). Moreover, there are common misconceptions regarding the linkage between vaccination and MS/MS exacerbations (Marrie et al., 2021). Some newer DMTs (excluding interferons and glatiramer acetate) are also thought to be associated with safety concerns due to their long lasting immunosuppressive and immunomodulatory effects and require monitoring for infectious diseases (Jalkh et al., 2020). It is therefore important to know and understand the vaccine intent of this population. In this study, we conducted a cross-sectional survey aimed to determine COVID-19 vaccine intent in Appalachian PwMS and to examine factors associated with vaccine hesitancy.

2. Material and methods

We conducted either a phone or in-person survey (at the end of their regular office visit) among PwMS in a single academic center in Appalachian WV from the beginning of February to the end of May 2021. We contacted 824 patients with a confirmed diagnosis of MS from the directory/ list of patient information listed in their medical record within three years preceding the study. The response rate was 37.13% and 306 participants completed the survey. Inclusion criteria included (1) Diagnosis of any subtype of MS (as confirmed by medical record review), (2) age 18 or older, and (3) seen in this academic center in the past 3 years.

The survey was adapted from a recent survey published on COVID-19 vaccine hesitancy (Puteikis and Mameniskiene, 2021), and divided into three parts: (1) vaccine intent (2) factors associated with vaccine hesitancy (3) demographic information. Questions related to “factors associated with vaccine hesitancy” were further categorized as “perceived vaccine safety,” “perceived disease susceptibility,” “past vaccine behaviors,” “influence from others,” and “concerns related to vaccine access.”

The study was approved by the West Virginia University IRB (protocol no. 2102228098). Surveys were collected anonymously. The participants consented to take part in the study and were informed that their participation in the survey was completely voluntary and they were free to stop at any time or refuse to answer any questions. They were also informed that all information they provided was confidential and could not be traced back to them. Additionally, they were made aware that there was no monetary compensation for their participation.

All statistical analysis was conducted in SAS version 9.4. Descriptive statistics included frequencies and percentage for categorical variables and means, standard deviation (SD) for continuous variables. The main outcome variable was a dichotomous variable that included a vaccine hesitancy group and those who had received or intended to get vaccinated. This variable was created using two questions. Participants were asked “Have you already received the COVID-19 vaccine?” (yes and no) and “If not, how likely are you going to get the vaccine?” that consisted of a 5-point Likert scale for how likely they were to get the vaccine (1- most unlikely, 2- unlikely, 3- neither likely nor unlikely (unsure), 4- likely, and 5- most likely), which was dichotomized as ‘not likely’ (1–3 points) and ‘likely’ (4–5 points). The participants who answered 1- 3 on this scale were defined as the participants who had vaccine hesitancy and did not intend to get the COVID-19 vaccine. Participants who answered ‘unsure’ were included in the hesitant group as they had not decided to get vaccinated at the time of their survey completion. This group was compared with participants who were either vaccinated or intended to get vaccinated. Age was analyzed as a continuous variable and was also categorized as ≤ 24, 25 – 34, 35 – 44, 45 – 54, 55 – 64, 65 – 74, and ≥ 75 years old. Education status included a binary variable of ≤ high-school and > high-school education. Rural status was defined as residing in an area not delineated as “urban area” using the U.S. Census Bureau urban definition (Bureau. USC. United States Census Bureau. 2010). Due to the common notion that older MS therapies such as interferons and glatiramer acetate are “safer” due to their well-established long-term safety profiles and monitoring strategies (Jalkh et al., 2020), we also grouped participants by their disease-modifying therapy (DMT) types. DMT was categorized as older, newer, and none. For this study, “older” DMTs include interferons and glatiramer acetates and the rest of the DMTs were categorized as “newer” DMTs. The survey question regarding “how well are you doing in terms of MS?” used the 5-point Likert scale and 1–3 points were categorized as ‘not doing well’ and 4–5 points were categorized as ‘doing well’. The questions that inquired about the participant's concern about different aspects of the vaccine included two types of responses. One was a 5-point Likert scale that included levels of concern (1- not at all concerned, 2- slightly concerned, 3- somewhat concerned, 4- moderately concerned, 5- strongly concerned), which was dichotomized as ‘not concerned’ by combining the 1–3 points and ‘concerned’ by combining the 4–5 points.

The second response included a binary response of ‘yes’ and ‘no’. Independent samples t-test was used to determines statistically significant difference between the means of the two groups (vaccine hesitancy group and the comparison group of those who had received or intend to get vaccinated) for the continuous variables. The Chi Square statistic and binary logistic regression was used to determine whether there is a statistically significant association between the two groups (vaccine hesitancy group and those who received or intend to get vaccinated) and categorical variables. The significance level of alpha = 0.05 was used to reject the null hypothesis of no difference between the two groups.

3. Results

3.1. Survey participants

Among the 306 participants, 237 (77.45%) were female with a mean age 49.39 (SD=13.5) and 69 (22.54%) were male with a mean age 53.59 (SD=13.31). Majority of the survey participants (52.61%) were older than 50 years old. The median age of all the survey participants was 50 years and the most prevalent age group was 45–54 years (26.14%). More than one third of the participants (n = 105, 35.12%) had less or equal to high school education and 151 (50.5%) survey participants lived in a rural area. Nearly one fifth of the participants (21%) were not on any DMTs, 33 (11%) were on older therapies and 204 (68%) were on newer DMTs. In terms of disease susceptibility, a majority of the survey participants considered themselves to be at low risk for COVID-19 infection (73.6%). Nearly half of the participants (51.97%) considered themselves as “not doing well” in terms of MS and 146 (48.03%) considered themselves as “doing well” (Table 1 ).

Table 1.

Population characteristics of the study among patients with Multiple Sclerosis (MS) in a single academic center in Appalachian WV (February to May 2021, N= 306).

Variables Categories N %
Age 24 7 2.29
25 – 34 34 11.11
35 – 44 65 21.24
45 – 54 80 26.14
55 – 64 65 21.24
65 −74 47 15.36
75 8 2.61
Mean (SD) 50.34 13.55
Education High School 105 35.12
> High School 194 64.88
Gender Female 237 77.45
Male 69 22.55
Geographic location1 Rural 151 50.5
Urban 148 49.5
Perception of current MS condition2 Not good 158 51.97
Good 146 48.03
Use of Disease Modifying Therapy (DMT)3 No 63 21
New 204 68
Old 33 11
Vaccine intent4 Do not intent 104 33.99
Received/scheduled/intend 202 66.01
Perceived risk of getting the COVID-19 infection High 80 26.4
Low 223 73.6
Concerned about vaccine causing MS relapse Yes 122 40.13
No 182 59.87
Concerned about vaccine making MS medication ineffective Yes 97 32.77
No 199 67.23
Concerned about MS medicine making the vaccine ineffective Yes 93 31.53
No 202 68.47
COVID-19 vaccine information source Doctor(s) 57 18.94
Friends 4 1.33
Internet 95 31.56
TV 47 15.61
Others 98 32.56
Concerned about where to get the vaccine Yes 24 7.89
No 280 92.11
Concerned about vaccine cost Yes 12 3.99
No 289 96.01
Have a ride to get the vaccine Yes 288 96
No 12 4
Received the flu vaccine in the past year Yes 169 55.59
No 135 44.41

1Geographic location was categorized as Rural and Urban using zip code level data using the U.S. Census Bureau rural definition (United States Census Bureau, 2010).

2Participants were asked “How well you are doing in terms of MS?” and the response was collected using a 5-point Likert scale and 1–3 points were categorized as ‘not doing well’ and 4–5 points were categorized as ‘doing well’.

3DMT New drugs included: Aubagio (teriflunomide), Cellcept (mofetil), Gilenya (fingolimod), Kesimpta (ofatumumab), Lemtrada (alemtuzumab), Mavenclad (cladribine), Mayzent (siponimod), Ocrevus (ocrelizumab), Rituxan (rituximab), Tecfidera (dimethyl fumarate), Tysabri (natalizumab),Vumerity (diroximel fumarate) Old drugs included: Avonex (interferon beta-1a), Copaxone (glatiramer acetate), Plegridy (peginterferon beta-1a).

4This variable was created using two questions. Participants were asked “Have you already received the COVID-19 vaccine?” (yes and no) and “If not, how likely are you going to get the vaccine?” that consisted of a 5-point Likert scale which was dichotomized as ‘unlikely’ (1–3 points) and ‘likely’ (4–5 points).

3.2. Outlook on vaccines

At the conclusion of the survey collection out of 306 participants, 148 participants (48.37%) had already received a COVID-19 vaccine and two additional participants were scheduled to receive the vaccine. 156 participants (50.98%) had not received the vaccine. Among those who had not been vaccinated, 66.24% did not intend to get vaccinated. Overall, 104 participants (33.99%) indicated that they were unlikely to be vaccinated and 202 (66.01%) had either received the vaccine or intended to get vaccinated.

Vaccine safety concerns were associated with vaccine hesitancy (OR=7.14, 95% CI: 4.18–12.17). The safety concerns included concerns about vaccine side effects (OR=10.45, 95% CI: 6.02–18.15), fast vaccine approval process (OR=8.91, 95% CI: 4.81–16.51), vaccine ingredients (OR=6.33, 95% CI: 3.74–10.7), and vaccine efficacy (OR=4, 95% CI: 2.41–6.62). Concerns about the vaccine causing other diseases also contributed to vaccine hesitancy (OR=7.12, 95% CI: 4.14–12.24). Additional factors specific to PwMS include concerns about the vaccine causing MS relapse and making DMTs ineffective (OR=4.94, 95% CI: 2.97–8.23 and OR=4.06, 95% CI: 2.42–6.81 respectively). The perceptions of how well survey participants were doing in terms of MS was not associated with vaccine intent (p 0.6194, OR=0.89, 95% CI: 0.55–1.42) but the perception of infection risks was statistically significantly associated with vaccine hesitancy (OR=1.77, 95% CI: 1.05–3). Having not received the flu vaccine in the past year and having had bad experiences with vaccines in the past were also shown to influence vaccine intent (OR=4, 95% CI: 2.42–6.61 and OR=2.33, 95% CI: 1.23–4.42 respectively). Lack of consultation with healthcare providers was associated with vaccine hesitancy (OR=3.53, 95% CI: 2.13–5.84) (Table 2 ).

Table 2.

Factors associated with vaccine intent among patients with Multiple Sclerosis (MS) in a single academic center in Appalachian WV (February to May 2021, N= 306).

Factors Variables Categories Do Not Intend Received/Intend OR (95% CI) p-value
N 306 104 (33.99) 202 (66.01)
Socio-demographic Age < 50 65 (62.5) 80 (39.6) 2.54 (1.56, 4.14) <0.0001
50 39 (37.5) 122 (60.4) -
Mean (SD) 45.90 (13.58) 52.62 (12.99) <0.0001
Education High School 43 (42.57) 62 (31.31) 1.63 (0.99, 2.67) 0.0537
> High School 58 (57.43) 136 (68.69) -
Sex Female 88 (84.62) 149 (73.76) 1.96 (1.05, 3.63) 0.0314
Male 16 (15.38) 53 (26.24) -
Geographic location1 Rural 61 (60.4) 90 (45.45) 1.83 (1.12, 2.98) 0.0145
Urban 40 (39.6) 108 (54.55) -
MS related Use of DMT2 No 24 (23.3) 39 (19.8) 0.95 (0.4, 2.25) 0.9012
New 66 (64.08) 138 (70.05) 0.74 (0.35, 1.57) 0.4272
Old 13 (12.62) 20 (10.15) -
Perception of current MS condition3 Not good 52 (50) 106 (53) 0.89 (0.55, 1.42) 0.6194
Good 52 (50) 94 (47) -
Concerned about vaccine causing MS relapse Yes 67 (65.05) 55 (27.36) 4.94 (2.97, 8.23) <0.0001
No 36 (34.95) 146 (72.46) -
Concerned about vaccine making MS medication ineffective Yes 54 (53.47) 43 (22.05) 4.06 (2.42, 6.81) <0.0001
No 47 (46.53) 152 (77.95) -
Concerned about MS medicine
making the vaccine ineffective
Yes 38 (38.38) 55 (28.06) 1.6 (0.96, 2.66) 0.0716
No 61 (61.62) 141 (71.94) -
Perceived risk of getting COVID-19 infection High 35 (33.98) 45 (22.5) 1.77 (1.05, 3) 0.0318
Low 68 (66.02) 155 (77.5) -
Anticipated reasons/concerns Concerned about how well COVID-19 vaccine works Yes 63 (52.5) 39 (21.67) 4 (2.41, 6.62) <0.0001
No 57 (47.5) 141 (78.33) -
Concerned about vaccine causing other diseases Yes 77 (75.49) 61 (30.2) 7.12 (4.14, 12.24) <0.0001
No 25 (24.51) 141 (69.8) -
Concerned about vaccine approved fast Yes 88 (85.44) 79 (39.7) 8.91 (4.81, 16.51) <0.0001
No 15 (14.56) 120 (60.3) -
Concerned about vaccine ingredients Yes 67 (65.69) 46 (23.23) 6.33 (3.74, 10.7) <0.0001
No 35 (34.31) 152 (76.77) -
Concerned about vaccine safety Yes 66 (64.08) 39 (20) 7.14 (4.18, 12.17) <0.0001
No 37 (35.92) 156 (80) -
Concerned about side-effects of the vaccine Yes 74 (71.15) 38 (19.1) 10.45 (6.02, 18.15) <0.0001
No 30 (28.85) 161 (80.9) -
Others Received the flu vaccine in the past year No 69 (66.35) 66 (33) 4 (2.42, 6.61) <0.0001
Yes 35 (33.65) 134 (67) -
Had adverse experience with vaccine in the past Yes 23 (22.33) 22 (11) 2.33 (1.23, 4.42) 0.0086
No 80 (77.67) 178 (89) -
Talked to doctor about COVID 19 vaccine No 55 (53.4) 49 (24.5) 3.53 (2.13, 5.84) <0.0001
Yes 48 (46.6) 151 (75.5) -

1Geographic location was categorized as Rural and Urban using zip code level data using the U.S. Census Bureau rural definition (United States Census Bureau, 2010).

2 Disease Modifying Therapy (DMT)New drugs included: Aubagio (teriflunomide), Cellcept (mofetil), Gilenya (fingolimod), Kesimpta (ofatumumab), Lemtrada (alemtuzumab), Mavenclad (cladribine), Mayzent (siponimod), Ocrevus (ocrelizumab), Rituxan (rituximab), Tecfidera (dimethyl fumarate), Tysabri (natalizumab),Vumerity (diroximel fumarate) Old drugs included: Avonex (interferon beta-1a), Copaxone (glatiramer acetate), Plegridy (peginterferon beta-1a).

3Participants were asked “How well you are doing in terms of MS?” and the response was collected using a 5-point Likert scale and 1–3 points were categorized as ‘not doing well’ and 4–5 points were categorized as ‘doing well’.

Female gender (OR=1.96, 95% CI: 1.05–3.63), age younger than 50 years old (OR=2.54, 95% CI: 1.56–4.14) and residing in a rural area (OR=1.83, 95% CI: 1.12–2.98) were significantly associated with vaccine hesitancy. Educational status (p 0.0537, OR=1.63, 95% CI: 0.99–2.67) and DMTs (new vs old) (OR=0.74, 95% CI: 0.35–1.57) were not significantly associated with vaccine intent (Table 2). Most survey participants did not have concerns about vaccine cost (289, 96.01%), transportation (288, 96%), or where to get the vaccine (280, 92.11%). 95 (31.56%) participants listed the internet as their primary source of information about the vaccine, followed by doctors (57, 18.94%), and television (47, 15.61%). About one third of patients chose “other” as their source of information about the vaccine.

4. Discussion

4.1. Appalachian PWMS

Age distribution of participants in this study were consistent with the general MS population (Marrie et al., 2021; Wallin et al., 2019; Dilokthornsakul et al., 2016). Female to male ratio was 3.43, which is also consistent with typical MS demographics (Marrie et al., 2021; Wallin et al., 2019). Several demographic findings in this study are distinctive. The percentage of our survey participants who had less than or equal to high school level of education (35.12%) is higher than the national average (28.1%) (Bureau. USC. U.S 2021) but lower than the average of the Appalachian regions (63.8%) (Pollard and Jacobsen 2021). A high percentage of our study participants (50.5%) lived in rural areas; in the general Appalachian population only 10% of residents live in rural counties (Appalachian Regional Commission 2020) Thus, our study may have important implications specifically regarding vaccine concerns in more rural patients.

4.2. Vaccine hesitancy among appalachian pwms

According to a survey of 7420 participants in the US by Appalachian Regional Commission (2020), estimates of COVID-19 vaccine hesitancy declined from 46% in October 2020 to 35.2% in March 2021. A nationally representative household panel survey during March-May 2021 showed that 23.2% of young adults aged 18–39 years were probably or definitely not going to get vaccinated (Daly et al., 2021). Another national online survey of PwMS (N = 359) in early January 2021, showed that 20.3% were vaccine hesitant (Baack et al., 2021). In comparison, the vaccine hesitancy rate in the survey population in this study was higher (33.76%).

The study findings of higher vaccine hesitancy in younger, female and rural residents are consistent with past literature findings (Ehde et al., 2021; Fisher et al., 2020; Ruiz and Bell, 2021; Kreps et al., 2020). Prior studies of the general public indicated that individuals with lower education were less likely to pursue vaccination (Ehde et al., 2021; Fisher et al., 2020; Kreps et al., 2020), However, educational status was not associated with vaccine hesitancy in our study population. This discrepancy can be potentially explained by lower vaccine hesitancy in people with pre-existing conditions (Pollard and Jacobsen 2021), and factors indicated by Kreps et al. (2020) that included higher awareness and health literacy, higher trust and interaction with healthcare professionals, and lower pre-existing vaccine hesitancy. Factors found in this study to be significantly associated with vaccine hesitancy in Appalachian PwMS are mostly consistent with those found in past studies in the general population: vaccine safety concerns (Ehde et al., 2021; Ruiz and Bell, 2021; Khubchandani et al., 2021), perception of infection risks (Ehde et al., 2021; Fisher et al., 2020; Ruiz and Bell, 2021; Kreps et al., 2020; Khubchandani et al., 2021; Reiter et al., 2020), flu vaccine status (Ehde et al., 2021; Fisher et al., 2020; Ruiz and Bell, 2021), past experience with other vaccines (Reiter et al., 2020), and consultations with healthcare providers (Ehde et al., 2021; Khubchandani et al., 2021; Reiter et al., 2020). Among the safety concerns, participants indicated that they were concerned about vaccine side effects, fast vaccine approval, vaccine ingredients, and vaccine efficacy. PwMS were specifically concerned about the vaccine causing MS relapses and reducing the efficacy of the DMTs. This is consistent with past findings in MS patients (Marrie et al., 2021).

Common barriers affecting health disparities in the Appalachian region such as access, transportation, cost and health insurance issues were not concerns in our survey population. Partnering with local independent pharmacies and distribution by the national guards aided initial success of the vaccine rollout in West Virginia (Dube et al., 2013). Other health indicators influencing Appalachian health disparities (How West Virginia became a U.S 2021), such as lack of access to healthcare providers, chronic health conditions, health behaviors, mental health conditions, and health cultures were not measured in this study.

4.3. Study limitations

The study was a cross-sectional study based on phone and in-person surveys, therefore, limited due to respondent bias, especially when participants were interviewed directly by their healthcare providers. Moreover, since the study sample was not random, the results may not be generalizable due to the nature of its sample selection. The study needs to be replicated in multiple academic centers in different geographic areas to ensure generalizability of this study. Last, the survey process spanned over several months, during which vaccine availability steadily increased and specific vaccine recommendations for MS became more widely available and thus those who indicated vaccine hesitancy in the beginning of the survey may have changed their mind later on (Appalachian Regional Commission 2017).

5. Conclusions

Vaccine hesitancy is a complex issue which is largely influenced by cultural, economic, political, and demographic context (Puteikis and Mameniskiene, 2021). The results from our study showed that compared to the national survey result of PwMS (Baack et al., 2021), Appalachian adult PwMS in a large academic center in WV demonstrated higher vaccine hesitancy, especially among those who are female, younger than 50 years old, and residing in rural areas. Concerns about vaccine safety, perception of infection risks, past vaccine behaviors and consultation with healthcare providers are important factors associated with vaccine intent. Factors influencing vaccine hesitancy in PwMS are largely consistent with the general public, however, concerns for interaction between the vaccine and MS are specific to this population thus could be the focus of further vaccine effort. Vaccine cost and transportation to vaccine sites were not barriers to vaccination in this Appalachian population. Health disparity concerns in general Appalachian population such as lack of health insurance/cost or access to a vaccination site were not barriers to vaccination in our survey population.

Thus far, there have been no significant concerns about either increased risk of MS relapses or lowered MS DMT efficacy from the COVID-19 vaccines that were available to patients in this study (KFF 2021). In contrast, some data does suggest worse outcomes in some MS patients who contracted COVID-19, depending on specific DMT, degree of disability and other comorbid conditions (Reyes et al., 2021). In our study, the majority of patients felt their risk of COVID-19 infection was low, and concerns about vaccine-related MS risks were associated with vaccine hesitancy. A recently published survey of the MS population by Marrie et al. (2021) found that 43% of participants reported that their neurologist had ever asked about their immunization history (Marrie et al., 2021). In our study a lower percentage of patients received most of their information about vaccines from their healthcare providers, instead receiving information from the internet, television, or other combined sources. This has particular implications regarding potential opportunities for interventions to improve vaccine uptake in Appalachian PwMS, especially rural patients. On a public health level, information distributed through media channels (internet, television, etc.) may be more likely to effectively reach patients. On an individual level, referring patients to reliable internet resources for vaccine information (such as those available from the National Multiple Sclerosis Society) (Kelly et al., 2021) as well as direct discussion between providers and patients regarding vaccine safety and MS-specific risks of COVID-19 infection may also be opportunities for improvement in vaccine acceptance in this population.

Contributor's statement page

Ms. Hongyan Wu conceptualized and designed the study, conducted phone and in office surveys, drafted the initial manuscript, and reviewed and revised the manuscript.

Dr. Melanie Ward conceptualized and designed the study, conducted phone and in office surveys, and critically reviewed the manuscript for important intellectual content.

Ms. Ashlyn Brown and Ms. Erica Blackwell conducted phone and in office surveys and critically reviewed the manuscript for important intellectual content.

Dr. Amna Umer conceptualized and designed the study, carried out the statistical analyses, interpreted the data findings, and critically reviewed the manuscript for important intellectual content.

All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Acknowledgements

Sincere appreciation to Dr. Aman Dabir, Dr. Zubeda Sheikh, Dr. Shitiz Sriwastava for their useful suggestions and general support throughout the process.

References

  1. Appalachian Regional Commission . 2017. Health Disparities in Appalachia Executive Summary.https://www.arc.gov/wp-content/uploads/2017/08/Health_Disparities_in_Appalachia_Executive_Summary.pdf [Google Scholar]
  2. Appalachian Regional Commission . 2020. Rural Appalachia Compared to the Rest of Rural America.https://www.arc.gov/rural-appalachia/ Accessed Oct 28, 2021. [Google Scholar]
  3. Baack B.N., Abad N., Yankey D., et al. COVID-19 vaccination coverage and intent among adults aged 18-39 Years - United States, March-May 2021. MMWR Morb. Mortal Wkly. Rep. 2021;70(25):928–933. doi: 10.15585/mmwr.mm7025e2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bureau. USC. U.S . 2021. Census Bureau Releases New Educational Attainment Data.https://www.census.gov/newsroom/press-releases/2020/educational-attainment.html Published 2020. Updated March 30, 2020. August 1. [Google Scholar]
  5. Bureau. USC. United States Census Bureau. 2010. Rural America. https://mtgis-portal.geo.census.gov/arcgis/apps/MapSeries/index.html?appid=49cd4bc9c8eb444ab51218c1d5001ef6. Published 2010. Updated MArch 30, 2020. Accessed August 1, 2021. [Google Scholar]
  6. Chaudhry F., Bulka H., Rathnam A.S., et al. COVID-19 in multiple sclerosis patients and risk factors for severe infection. J. Neurol. Sci. 2020;418 doi: 10.1016/j.jns.2020.117147. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Daly M., Jones A., Robinson E. Public trust and willingness to vaccinate against COVID-19 in the US From October 14, 2020, to March 29, 2021. JAMA. 2021;325(23):2397–2399. doi: 10.1001/jama.2021.8246. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Dilokthornsakul P., Valuck R.J., Nair K.V., Corboy J.R., Allen R.R., Campbell J.D. Multiple sclerosis prevalence in the United States commercially insured population. Neurology. 2016;86(11):1014–1021. doi: 10.1212/WNL.0000000000002469. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Dube E., Laberge C., Guay M., Bramadat P., Roy R., Bettinger J. Vaccine hesitancy: an overview. Hum. Vacc. Immunother. 2013;9(8):1763–1773. doi: 10.4161/hv.24657. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Ehde D.M., Roberts M.K., Humbert A.T., Herring T.E., Alschuler K.N. COVID-19 vaccine hesitancy in adults with multiple sclerosis in the United States: a follow up survey during the initial vaccine rollout in 2021. Mult. Scler. Relat. Disord. 2021;54 doi: 10.1016/j.msard.2021.103163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Fisher K.A., Bloomstone S.J., Walder J., Crawford S., Fouayzi H., Mazor K.M. Attitudes toward a potential SARS-CoV-2 vaccine: a survey of U.S. Adults. Ann. Intern. Med. 2020;173(12):964–973. doi: 10.7326/M20-3569. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. 2021. How West Virginia became a U.S. Leader in Vaccine Rollout. The New York Times.https://www.nytimes.com/2021/01/24/us/west-virginia-vaccine.html Accessed Oct.20,2021. [press release] [Google Scholar]
  13. Jalkh G., Abi Nahed R., Macaron G., Rensel M. Safety of newer disease modifying therapies in multiple sclerosis. Vaccines. 2020;9(1) doi: 10.3390/vaccines9010012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Kelly H., Sokola B., Abboud H. Safety and efficacy of COVID-19 vaccines in multiple sclerosis patients. J. Neuroimmunol. 2021;356 doi: 10.1016/j.jneuroim.2021.577599. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. KFF. Vaccine Monitor: some Who Were Hesitant to Get a Vaccine in January Say They Changed Their Mind Because of Family, Friends and Their Personal Doctors. https://www.kff.org/coronavirus-covid-19/press-release/vaccine-monitor-some-who-were-hesitant-to-get-a-vaccine-in-january-say-they-changed-their-mind-because-of-family-friends-and-their-personal-doctors/. Published 2021. Updated July 13, 2021. Accessed August 1, 2021.
  16. Khubchandani J., Sharma S., Price J.H., Wiblishauser M.J., Sharma M., Webb F.J. COVID-19 vaccination hesitancy in the United States: a rapid national assessment. J. Commun. Health. 2021;46(2):270–277. doi: 10.1007/s10900-020-00958-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Kreps S., Prasad S., Brownstein J.S., et al. Factors associated with US adults’ likelihood of accepting COVID-19 vaccination. JAMA Netw. Open. 2020;3(10) doi: 10.1001/jamanetworkopen.2020.25594. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Li Y., Tenchov R., Smoot J., Liu C., Watkins S., Zhou Q. A comprehensive review of the global efforts on COVID-19 vaccine development. ACS Cent. Sci. 2021;7(4):512–533. doi: 10.1021/acscentsci.1c00120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. MacDonald N.E., SWGoV Hesitancy. Vaccine hesitancy: definition, scope and determinants. Vaccine. 2015;33(34):4161–4164. doi: 10.1016/j.vaccine.2015.04.036. [DOI] [PubMed] [Google Scholar]
  20. Marrie R.A., Kosowan L., Cutter G.R., Fox R., Salter A. Uptake and attitudes about immunizations in people with multiple sclerosis. Neurology. 2021;11(4):327–334. doi: 10.1212/CPJ.0000000000001099. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Murthy B.P., Sterrett N., Weller D., et al. Disparities in COVID-19 vaccination coverage between urban and rural counties - United States, December 14, 2020-April 10, 2021. MMWR Morb. Mortal Wkly. Rep. 2021;70(20):759–764. doi: 10.15585/mmwr.mm7020e3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Pollard K., Jacobsen L. Appalachian Regional Commision; 2021. The Appalachian region: a data overview from the 2015-2019 American Community Survey Chartbook.https://www.arc.gov/wp-content/uploads/2021/06/PRB_ARC_Chartbook_ACS_2015-2019_FINAL_2021-06_R1.pdf [Google Scholar]
  23. Puteikis K., Mameniskiene R. Factors associated with COVID-19 vaccine hesitancy among people with epilepsy in Lithuania. Int. J. Environ. Res. Public Health. 2021;18(8) doi: 10.3390/ijerph18084374. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Reiter P.L., Pennell M.L., Katz M.L. Acceptability of a COVID-19 vaccine among adults in the United States: how many people would get vaccinated? Vaccine. 2020;38(42):6500–6507. doi: 10.1016/j.vaccine.2020.08.043. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Reyes S., Cunningham A.L., Kalincik T., et al. Update on the management of multiple sclerosis during the COVID-19 pandemic and post pandemic: an international consensus statement. J. Neuroimmunol. 2021;357 doi: 10.1016/j.jneuroim.2021.577627. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Ruiz J.B., Bell R.A. Predictors of intention to vaccinate against COVID-19: results of a nationwide survey. Vaccine. 2021;39(7):1080–1086. doi: 10.1016/j.vaccine.2021.01.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Simpson-Yap S., De Brouwer E., Kalincik T., et al. Associations of disease-modifying therapies with COVID-19 severity in multiple sclerosis. Neurology. 2021 doi: 10.1212/WNL.0000000000012753. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Wallin M.T., Culpepper W.J., Campbell J.D., et al. The prevalence of MS in the United States: a population-based estimate using health claims data. Neurology. 2019;92(10):e1029–e1040. doi: 10.1212/WNL.0000000000007035. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Multiple Sclerosis and Related Disorders are provided here courtesy of Elsevier

RESOURCES