Vaccinomics: a cross-sectional survey of public values

Figures & data

Figure 1. A. Vaccine hesitancy among parents of  young children 10 years old and younger, B. Vaccine hesitancy among parents of children  11 to 17 years old, and C. Vaccine hesitancy among parents without minor children

Table 1. Sociodemographic characteristics of the study population: weighted and unweighted

	Unweighted	Weighted^j		Unweighted	Weighted^j
Sociodemographic Factors	N = 1,925 (%)	%	Sociodemographic Factors	N = 1,925 (%)	%
Gender^a			Child <18 years old^g
Male	934 (48.5)	48.6	Yes	1,239 (64.4)	62.9
Female	976 (50.7)	50.6	No	686 (35.6)	37.1
Race/ethnicity^b			Youngest child’s age (years)^h
White, Non-Hispanic	1,136 (59.0)	61.8	≤5	323 (22.6)	22.2
Black, Non–Hispanic	230 (11.9)	11.4	6–10	401 (28.0)	27.7
Other	559 (29.0)	26.8	7–11	515 (36.0)	35.9
Respondent’s age (years)^c			≥18	181 (12.6)	13.3
18–34	691 (36.0)	36.0	Vaccine hesitancy: parents of young children^e
35–54	661 (34.4)	33.4	Low	396 (64.8)	64.4
≥55	569 (29.6)	30.6	High	328 (35.2)	35.6
Region^d			Vaccine hesitancy: parents of teenagers^f
Midwest	397 (20.6)	22.2	Low	376 (73.0)	72.4
Northeast	510 (26.5)	18.1	High	139 (27.0)	27.6
South	664 (34.5)	36.9	Vaccine hesitancy: adults without minor children ^i
West	351 (18.2)	22.6	Low	424 (61.8)	62.3
Household annual income^e			High	262 (38.2)	37.7
$0-$49,999	855 (44.4)	44.7	Science courses and training
$50,000-$99,999	508 (26.4)	26.7	High school	1,059 (55.0)	55.7
$100,000–$149,999	236 (12.3)	11.9	College	634 (32.9)	32.7
≥$150,000	290 (15.1)	14.8	Graduate/Continuing Education	315 (16.4)	15.8
Highest level of education^f			Work/Training	267 (13.9)	13.7
≤High school degree	893 (46.4)	47.1	None of the above	149 (7.7)	7.7
≤College/Associate/Bachelor’s degree	728 (37.8)	37.4	Beginning vs. end of survey vaccine safety^l
Masters/Profession/Doctorate degree	277 (14.4)	14.0	Mean difference	0.10	<0.01

^aGender: n = 15 “trans/prefer not to answer”.

^bRace/ethnicity: “other” includes n = 2 “don’t know” Hispanic ethnicity, n = 87 “prefer not to answer” race, n = 25 Hawaiian/Pacific Islander, n = 120 Asian, and n = 89 American Indian/Alaskan Native (multiple responses allowed).

^cRespondent’s age: n = 4 missing.

^dRegion: n = 3 missing, n = 3 “Puerto Rico/prefer not to answer”.

^eHOUSEHOLD annual income: n = 36 missing, n = 36 “prefer not to answer”.

^fEducation, n = 27 missing, n = 27 “prefer not to answer”.

^gParent status, baseline: n = 2 missing combined with n = 481 = no.

^hAge of youngest child: n = 12 “prefer not to answer”.

ⁱVaccine hesitancy among parents of children ≤10 years old estimated using a composite score from items adapted from Opel et al.,^1,2 unweighted n = 724; weighted n = 705.73.

^jVaccine hesitancy among parents of children 11–17 years old estimated using a composite score from items adapted from Gilkey et al.,³ unweighted n = 515; weighted n = 507.03.

^kVaccine hesitancy among adults without minor children measured based on Gilkey et al.,³.

^lEstimated mean difference using a t-test for paired, data (none missing). Taylor-linearized variance estimation for weighted survey data used. Unweighted N = 1,925; Weighted N = 1,927.87.

Table 2. The overall frequency and proportion of the study sample experienced with serious reactions to vaccines, genetic testing experience, and support for biobanks

Survey items		Weighted %
Have you or anyone you know ever had a serious reaction to a vaccine? Serious reactions include permanent disability, hospitalization, life-threatening illness, or death?^a
	No	76.5
	Yes	19.7
	Don’t know	3.8
Did you or your provider report the reaction to the Vaccine Adverse Events Reporting System (VAERS) or the Vaccines Injury Compensation Program (VICP)?
	No	28.5
	Yes	57.1
	Don’t know	14.4
Among those who had or knew someone who had a serious reaction to a vaccine: If you had a rare, serious reaction to a vaccine, how likely would you be to let your doctor submit a sample from you (for example: a vial of blood or swab from your mouth) to a biobank?^b
	Extremely unlikely	6.0
	Unlikely	8.3
	Likely	36.0
	Extremely likely	49.7
Independent groups of scientists who are experts in research ethics and local community members oversee how biobanks manage people’s information. Does having this kind of independent, research ethics oversight make you more likely to submit a sample to a vaccine biobank?^b
	No	10.6
	Yes	81.9
	Don’t know	7.5
If Likely or extremely likely to give a sample: What is the primary reason you would participate in a vaccine biobank?^b
	To help others	50.4
	Interest in science and/or medicine	21.6
	It’s the right thing to do	18.9
	To help myself	8.5
	Other	0.6
Have you ever had your genes or DNA tested? For example, in your doctor’s office or through an in-home test like 23andme, ancestry.com, or one purchased in a pharmacy?^c
	No	71.8
	Yes	27.3
If had DNA tested: Where were your genes or DNA tested? Select all that apply.^d
	I was tested in a doctor’s office or other medical setting	62.4
	I used an in-home test (for example:through 23andme, ancestry.com, or one purchased in a pharmacy)	49.4
	Other	2.8
If had DNA tested: Did you share the gene or DNA test result with any of the following people? Select all that apply.^d
	Family	85.5
	Friends	34.1
	Co-worker	10.5
	My doctor, nurse, physician’s assistant, a nurse practitioner, or a pharmacist	30.7
	My alternative medicine provider(s) (for example: chiropractor, naturopath, massage therapist, or acupuncturist)	9.0
Would you support a $0.25 fee on all vaccines to fund vaccinomics research? The $0.25fee would mostly be paid by the government and health insurance companies, who pay formost people’s vaccines now. It is unlikely you would have to pay morefor vaccines because of this fee.
	No	16.4
	Yes	70.8
	Don’t know	12.8

^aSerious reaction: Unweighted n = 71 “don’t know” included with n = 1,465 “no”.

^bunweighted n = 389 had a serious vaccine reaction and were asked these items.

^cunweighted n = 17 (weighted proportion: 0.9%) “prefer not to answer.

^dunweighted n = 535 had a DNA test and were asked these items; multiple responses allowed; results may not sum to 100%; Taylor-linearized variance estimation for weighted survey data used. Unweighted N = 1,925; Weighted N = 1,927.87.

Table 3. The overall frequency and proportion of participants’ responses to questions about the ethical and policy implications of vaccinomics

	Weighted %
	Strongly Disagree	Disagree	Agree	Strongly Agree	Strongly Agree or Agree
Vaccinomics (based on genes/DNA) would help me make informed decisions about vaccines FOR MYSELF.	2.5	6.1	51.5	39.9	91.4
Asked of parents only: Vaccinomics (based on genes/DNA) would help me make informed decisions about vaccines FOR MY CHILD.^a	2.7	4.6	51.1	41.6	92.7
I am afraid that my gene or DNA test result could prevent me from getting a vaccine.^b	27.4	50.6	15.6	6.4	22.0
I am afraid that using genes or DNA in vaccine decisions could increase race/ethnic discrimination.^b	26.6	44.4	20.3	8.7	29.0
I would have my genes or DNA tested if it would help my doctor or another healthcare provider know which vaccines are best for ME.^b	6.7	16.5	42.5	34.3	76.8
I am concerned my HEALTH INSURANCE COMPANY would learn my gene or DNA test result.^b	15.6	38.8	30.1	15.5	45.5
I am concerned the U.S. GOVERNMENT would learn my gene or DNA test result.^b	15.0	38.0	32.6	14.5	47.0
I would be concerned about the security of my gene or DNA test result^b	13.0	30.7	37.4	18.9	56.3
I would support vaccinomics even if it made vaccine schedules more complex.^b	6.2	22.5	52.4	18.8	71.2
Vaccinomics would make me have more confidence in vaccines than I do now.^b	7.6	21.7	50.4	20.3	70.7
Vaccinomics is likely to help other people.^b	5.1	12.2	52.1	30.5	82.6
Vaccinomics is likely to help me.^b	6.2	18.0	50.4	25.4	75.8

^aAsked of unweighted n = 1,239 parents of children<18 only.

^bThese items had a positively and negatively worded version. The scale of the negatively worded items was reversed and combined with its positively phrased counterpart for analysis. Taylor-linearized variance estimation for survey data used for all data. Unweighted N = 1,925; Weighted N = 1,927.87.

Table 4. Among people who agree/strongly agree with hypothetical scenarios, the frequency and proportion of participants’ concerns about the ethical and policy implications of vaccinomics: stratified by sociodemographic characteristics

	Weighted %
	Parent Status^b			Highest level of Education^c				Household Annual Income^d					Respondent’s Age (years)^e
	Child ≤18 years old	No/prefer not to ans. Answer	P-value	≤High school deg.	≤College degree	Graduate degree	P-value	≤$49,999	$50,000-$99,999	$100,000-$149,999	≥$150,000	P-value	18-34	35-54	≥55	P-value
Vaccinomics (based on genes/DNA) would help me make informed decisions about vaccines FOR MYSELF.^a	92.5	90.4	0.14	89.3	93.4	95.4	<.01	89.6	93.1	92.7	96.8	<0.01	88.7	93.3	93.5	<.01
Asked of parents only: Vaccinomics (based on genes/DNA) would help me make informed decisions about vaccines FOR MY CHILD.^a	92.7	n/a	n/a	89.9	93.9	96.7	<.01	90.0	94.4	94.3	97.6	<0.01	91.0	93.4	96.2	.05
I am afraid that I might not be able to get a vaccine because of my genes or DNA.^a	22.4	21.3	0.60	22.4	18.7	28.1	<.01	20.5	20.1	23.4	26.0	0.15	27.2	21.9	15.5	<.01
I am afraid that using genes or DNA in vaccine decisions could increase race/ethnic discrimination.^a	29.6	28.1	0.51	28.7	27.2	33.4	.12	28.6	28.9	29.6	28.1	0.97	32.0	30.2	23.7	.01
I would have my genes or DNA tested if it would help my doctor or another healthcare provider know which vaccines are best for ME.^a	76.5	77.3	0.67	73.7	79.6	82.7	<.01	75.5	79.4	76.9	78.3	0.35	71.8	74.8	86.2	<.01
I would support vaccinomics even if it made vaccine schedules more complex.^a	71.2	71.2	0.98	70.5	72.1	72.8	.83	70.5	72.9	69.0	75.2	0.28	69.5	70.6	74.7	.13
Vaccinomics would make me have more confidence in vaccines than I do now.^a	71.2	69.9	0.56	65.7	74.7	78.7	<.01	68.2	71.0	70.8	80.7	<0.01	67.3	72.3	73.8	.02
Vaccinomics is likely to help other people.^a	82.1	83.6	0.42	81.1	84.2	84.4	.27	81.3	85.2	81.1	84.7	0.43	75.8	83.0	90.6	<.01
Vaccinomics is likely to help me.^a	78.0	72.1	<0.01	71.5	79.7	80.7	<.01	76.3	71.5	82.8	78.1	0.01	70.4	77.5	80.9	<.01
I am concerned my HEALTH INSURANCE COMPANY would learn my gene or DNA test re	47.2	43.0	0.08	44.3	45.0	50.9	.12	43.6	43.8	52.6	49.8	0.01	47.4	48.4	40.2	.01
I am concerned the U.S. GOVERNMENT would learn my gene or DNA test result	46.5	48.0	0.53	48.2	44.5	48.7	.17	48.1	44.6	44.8	48.9	0.49	51.5	45.8	42.7	<.01
I am concerned about the security of my gene or DNA test result	55.6	57.6	0.41	55.2	55.9	60.5	.15	57.0	55.4	53.1	57.9	0.91	54.7	57.7	56.6	.48

^aThese items had a positively and negatively worded version. The scale of the negatively worded items was reversed and combined with its positively phrased counterpart for analysis.

^bparent status: no/prefer not to answer includes n = 2 “prefer not to answer.

^ceducation: n = 3 “prefer not to answer,” ≤college includes some college, Associate’s or Bachelor’s Degree.

^cincome: n = 4 “prefer not to answer”.

^dage: n = 4 “prefer not to answer.” Taylor-linearized variance estimation for survey data used for all data; p-values estimated using two-sided general tests of association. Unweighted N = 1,925; Weighted N = 1,927.87.

Table 5. Among people who agree/strongly agree with hypothetical scenarios, the frequency and proportion of participants’ concerns about the ethical and policy implications of vaccinomics: stratified by experience with a serious vaccine reaction, vaccine hesitancy, and trust in public health authorities

	Weighted %
				Vaccine Hesitancy
	Serious Vaccine Reaction^b			Parents of Young Children			Parents of Teenagers			Adults without Minor Children			Trust in PHA
	No	Yes	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value
Vaccinomics (based on genes/DNA) would help me make informed decisions about vaccines FOR MYSELF.	92.1	92.8	<.01	94.3	86.7	<.01	97.7	82.8	<.01	96.1	81.0	<0.01	86.0	97.4	<.01
Asked of parents only: Vaccinomics (based on genes/DNA) would help me make informed decisions about vaccines FOR MY CHILD.	92.5	95.7	.01	95.9	85.9	<.01	97.7	83.9	<.01	N/A	N/A	N/A	89.6	96.7	<.01
I am afraid that I might not be able to get a vaccine because of my genes or DNA.^a	18.3	33.7	<.01	21.4	24.8	.31	18.9	28.8	.02	18.4	25.7	0.03	30.5	13.8	<.01
I am afraid that using genes or DNA in vaccine decisions could increase race/ethnic discrimination.^a	24.9	42.8	<.01	30.9	33.1	.54	24.2	33.6	.04	26.2	29.5	0.37	38.9	19.9	<.01
Vaccinomics is likely to help me.^a	79.7	64.7	<.01	79.1	71.2	.02	83.8	70.8	<.01	79.8	60.6	<0.01	61.6	88.6	<.01
Vaccinomics would make me have more confidence in vaccines than I do now.^a	74.2	62.3	<.01	71.5	65.5	.11	78.8	62.5	<.01	79.8	60.6	<0.01	57.4	83.3	<.01
Vaccinomics is likely to help other people.^a	86.0	72.6	<.01	81.7	76.2	.09	91.7	68.8	<.01	87.5	77.8	<0.01	70.3	93.8	<.01
My confidence in vaccines would increase if the U.S. government spent more money studying how safe vaccines are now and telling the public the results.^a	70.0	57.6	<.01	66.7	60.1	.09	69.9	57.0	.01	75.3	60.6	<.01	57.4	75.3	<.01
I would have my genes or DNA tested if it would help my doctor or another healthcare provider know which vaccines are best for ME.^a	80.9	64.8	<.01	79.1	70.5	.01	83.5	62.2	<.01	84.4	67.4	<.01	63.5	89.1	<.01
I would support vaccinomics even if it made vaccine schedules more complex.^a	75.4	59.9	<.01	72.2	66.4	.12	77.2	63.1	<.01	77.5	61.3	<.01	63.5	89.1	<.01
	Serious Vaccine Reaction^b,f			Parents of Young Children^c			Parents of Teenagers^d			Adults without Minor Children^e			Trust in PHA^f
	No	Yes	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value
I am concerned my HEALTH INSURANCE COMPANY would learn my gene or DNA test re	44.6	47.7	.30	45.3	48.6	.41	46.7	51.5	.35	40.3	46.7	.11	51.5	40.7	<.01
I am concerned the U.S. GOVERNMENT would learn my gene or DNA test result	44.9	51.3	<.01	44.8	46.8	.62	43.4	56.6	.01	45.2	53.0	.05	53.3	41.2	<.01
I am concerned about the security of my gene or DNA test result	55.6	56.0	.04	51.5	56.3	.24	54.7	68.1	<.01	57.3	58.5	.77	60.3	52.7	<.01

^aThese items had a positively and negatively worded version. The scale of the negatively worded items was reversed and combined with its positively phrased counterpart for analysis.

^bSerious Reactions: unweighted n = 71 “don’t know” responses combined with n = 1,465 “no” for analysis.

^cParents of Young Children: unweighted n = 724; weighted n = 706.

^dParents of Teenagers: unweighted n = 515, weighted n = 507.

^eAdults without minor children: weighted n = 686, unweighted n = 706, includes unweighted n = 2 “prefer not to answer” parent status” and unweighted n = 12 “prefer not answer” child’s age; Taylor-linearized variance estimation for weighted survey data used; p-values estimated using two-sided general tests of association.

^fUnweighted N = 1,925; Weighted N = 1,927.87.

Table 6. The overall frequency and proportion of participants’ responses to questions about vaccine prioritization, screening tests, and government spending to improve vaccine safety

	Weighted %
	Strongly Disagree	Disagree	Agree	Strongly Agree	Strongly Agree or Agree
If there was a short supply of vaccine, it would make sense for the people “more susceptible” to infection to get it first.^a	8.5	17.0	44.7	29.8	74.5
If there was a short supply of vaccine, it would make sense for the “more contagious” people to get it first.^a	7.1	17.2	44.2	31.4	75.7
It would bother me if my doctor identified me as “more contagious” or “more susceptible.”^a	17.4	41.3	29.5	11.9	41.3
Getting vaccinated should be an individual’s choice, even if they are “more contagious” or “more susceptible.”^a	11.4	25.6	41.1	21.9	63.0
Identifying people as “more contagious” or “more susceptible will hurt people.^a	18.0	43.1	27.8	11.1	38.9
	Extremely Unlikely	Unlikely	Likely	Extremely Likely	Extremely Likely or likely
If your genes or DNA showed you to be “more contagious” or likely to get other people sick, how likely would you be to get vaccinated to PROTECT OTHER PEOPLE?^a	13.3	30.5	30.3	25.8	56.2
	I would be angry because I would want the vaccine	I would be okay with this decision	I would not care because I would not want the vaccine anyway	Other	Okay/Not care/Other
If you were told you were NOT going to be among the first groups vaccinated during an infectious disease outbreak because your genetics showed you were not “more contagious” or “more susceptible” to infection, how might you react?^a
I would be angry	23.2	65.9	8.6	2.3	76.8
	Strongly Disagree	Disagree	Agree	Strongly Agree	Strongly Agree or Agree
Screening tests that warn who is at increased risk of paralysis and death from vaccines will be worthwhile if they help predict who will have an adverse reaction.^a	7.6	21.7	50.4	20.3	64.7
The U.S. government should invest in making vaccines more effective instead of trying to reduce the risk of very serious and rare events, like paralysis and death after getting a vaccine.^a	5.4	23.7	47.8	23.2	71.0
My confidence in vaccines would increase if the U.S. government spent more money studying how safe vaccines are now and telling the public the results.^a	7.6	21.7	50.4	20.3	66.9

^aThese items had a positively and negatively worded version. The scale of the negatively worded items was reversed and combined with its positively phrased counterpart for analysis. Taylor-linearized variance estimation for survey data used for all data. Unweighted N = 1,925; Weighted N = 1,927.87.

Table 7. Among people who agree/strongly agree with hypothetical scenarios, the frequency and proportion of participants’ concerns related to vaccine prioritization and screening: stratified by experience with a serious vaccine reaction, vaccine hesitancy, and trust in public health authorities

	Weighted %
				Vaccine Hesitancy
	Serious Vaccine Reaction^b			Parents of Young Children			Parents of Teenagers			Adults without Minor Children			Trust in PHA
	No	Yes	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value
If there was a short supply of vaccine, it would make sense for the people “more susceptible” to infection to get it first.^a	78.8	59.4	<.01	71.9	65.2	.07	77.5	65.5	.01	82.4	75.3	.03	63.3	84.4	<.01
If there was a short supply of vaccine, it would make sense for the “more contagious” people to get it first.^a	80.7	60.6	<.01	71.1	74.5	.34	80.9	69.0	<.01	78.8	76.3	.46	64.5	85.4	<.01
It would bother me if my doctor identified me as “more contagious” or “more susceptible.”^a	38.1	50.7	<.01	45.1	44.7	.93	39.8	50.3	.04	34.4	39.6	.18	47.3	35.9	<.01
Getting vaccinated should be an individual’s choice, even if they are “more contagious” or “more susceptible.”^a	60.4	73.9	<.01	69.5	61.7	.04	63.2	64.1	.84	60.8	56.7	.30	67.2	59.7	<.01
	Serious Vaccine Reaction^b,f			Parents of Young Children^c			Parents of Teenagers^d			Adults without Minor Children^e			Trust in PHA^f
	No	Yes	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value
Identifying people as “more contagious” or “more susceptible will hurt people.^a	36.2	45.1	<.01	41.8	42.3	.91	35.7	46.8	.03	31.2	44.4	<.01	49.1	30.1	<.01
If your genes or DNA showed you to be “more contagious” or likely to get other people sick, how likely would you be to get vaccinated to PROTECT OTHER PEOPLE?^a	57.4	50.2	.05	53.4	55.9	.54	58.8	52.5	.22	62.5	46.9	<.01	51.6	59.5	<.01
Screening tests that warn who is at increased risk of paralysis and death from vaccines will be worthwhile if they help predict who will have an adverse reaction.^a	67.8	57.0	<.01	64.8	62.1	.50	67.4	58.7	.07	67.8	62.7	.19	58.2	70.8	<.01
The U.S. government should invest in making vaccines more effective instead of trying to reduce the risk of very serious and rare events, like paralysis and death after getting a vaccine.^a	68.9	80.7	<.01	80.3	69.9	.01	72.5	69.1	.53	67.2	65.5	.69	74.4	68.7	.02
	Serious Vaccine Reaction^b,f			Parents of Young Children^c			Parents of Teenagers^d			Adults without Minor Children^e			Trust in PHA^f
	No	Yes	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value	Low	High	P-value
My confidence in vaccines would increase if the U.S. government spent more money studying how safe vaccines are now and telling the public the results.^a	70.0	57.6	<.01	66.7	60.1	.09	69.9	57.0	<.01	75.3	60.6	<.01	57.4	75.3	<.01
If you were told you were NOT going to be among the first groups vaccinated during an infectious disease outbreak because your genetics showed you were not “more contagious” or “more susceptible” to infection, how might you react? Please check all that apply.^a
I would be angry because I would want the vaccine.	20.7	34.4	<.01	26.6	31.0	.23	26.5	21.4	.25	19.7	11.9	.01	27.9	18.9	<.01

^aThese items had a positively and negatively worded version. The scale of the negatively worded items was reversed and combined with its positively phrased counterpart for analysis.

^bSerious Reactions: unweighted n = 71 “don’t know” responses combined with n = 1,465 “no” for analysis

^cParents of Young Children: unweighted n = 724; weighted n = 706

^dParents of Teenagers: unweighted n = 515, weighted n = 507.

^eAdults without minor children: weighted n = 686, unweighted n = 706, includes unweighted n = 2 “prefer not to answer” parent status” and unweighted n = 12 “prefer not answer” child’s age; Taylor-linearized variance estimation for weighted survey data used; p-values estimated using two-sided general tests of association.

^fUnweighted N = 1,925; Weighted N = 1,927.87.

Table 8. The overall frequency and proportion of how respondents prefer the U.S. government prioritize funding and implement vaccinomics

	Weighted %
	More	Equal	Less
If you were making decisions about how the U.S. government spends money, would vaccinomics get more, an equal amount or less money than:
Breast and prostate cancer research and development	37.3	49.1	13.6
Diabetes research and development	34.2	53.4	12.4
Heart disease research and development	38.2	47.9	13.9
If you were making decisions about how the U.S. government spends money, would vaccinomics get more, an equal amount or less money than:
Studies about safety and effectiveness of current vaccines	39.0	55.4	5.5
Buying vaccines for U.S. children whose families cannot afford them	42.5	48.4	9.1
Supporting the use of vaccines for children in poor countries	39.8	48.6	11.7
If vaccinomics could make personalized vaccine recommendations available in the next 15 years, how should this information be used for CHILDREN? ^a		Yes
To make vaccines safer and more effective for all children		78.6
To identify children most likely to have serious and dangerous reactions to vaccines		61.0
To identify children most likely to be more contagious		54.0
To identify children most likely to be more susceptible		50.6
Genes or DNA should NOT be used to make decisions about vaccines for children		14.3
None of the above		4.4
If vaccinomics could make personalized vaccine recommendations available in the next 15 years, how should it be used for ADULTS? ^a		Yes
To make vaccines safer and more effective for all adults		72.1
To identify adults most likely to have serious and dangerous reactions to vaccines		61.7
To identify adults most likely to be more contagious		54.3
To identify adults most likely to be more susceptible		50.2
Genes should NOT be used to make decisions about vaccines for adults		13.7
None of the above		4.5

^aMultiple responses allowed; percentages may not sum to 100%; Taylor-linearized variance estimation for weighted survey data used. Unweighted N = 1,925; Weighted N = 1,927.87.

Table 9. Potential associations between opposition to vaccinomics and prioritization: expecting to feel angry if not prioritized for vaccination and strongly agreeing/agreeing that vaccination is an individual’s choice

	Unadjusted Analyses
	Expecting to Feel Angry		Individual’s Choice
	PR (95% CI)^i	P-value	PR (95% CI)^i	P–value
Experience with a serious vaccine reaction^a
No/Don’t know	Ref		Ref
Yes	1.68 (1.41, 2.00)	<.01	1.23 (1.14, 1.32)	<.01
Education^b
≤High school degree	Ref		Ref
≤College degree	0.94 (0.78, 1.14)	0.51	0.95 (0.88, 1.03)	0.23
Graduate degree	1.41 (1.14, 1.78)	<.01	1.15 (1.05, 1.26)	<.01
Parents of children <18 years old
No/Prefer not to answer	Ref		Ref
Yes	1.59 (1.31, 1.93)	<.01	1.10 (1.02, 1.18)	0.02
Age (years)^c
18–34	Ref		Ref
35-54	2.46 (1.91, 3.17)	<.01	1.09 (0.99, 1.19)	0.07
≥55	2.14 (1.65, 2.78)	<.01	1.13 (1.03, 1.23)	<.01
Vaccine hesitancy among parents of young children^d
Low	Ref		Ref
High	1.08 (0.85, 1.37)	.53	0.86 (0.77, 0.97)	.01
Vaccine hesitancy: parents of teenagers^e
Low	Ref		Ref
High	0.81 (0.56, 1.17)	.25	1.01 (0.87, 1.17)	.92
Vaccine hesitancy: adults without minor children^f
Low	Ref		Ref
High	0.58 (0.39, 0.86)	<.01	0.94 (0.82, 1.07)	.33
Household annual income^g
≤$49.999	Ref		Ref
$50,000-$99,999	1.18 (0.96, 1.46)	.12	1.06 (0.97, 1.16)	.19
$100,000-$149,999	1.22 (0.94, 1.60)	.14	1.10 (0.98, 1.23)	.09
≥$150,000	1.58 (1.27, 1.97)	<.01	1.15 (1.05, 1.27)	<.01
Trust in public health authorities
Low	Ref		Ref
High	0.68 (0.57, 0.80)	<.01	0.89 (0.83, 0.96)	<.01
Region^h
Midwest	Ref		Ref
Northeast	1.38 (1.07, 1.78)	.01	1.09 (0.98, 1.21)	.10
South	1.25 (0.98, 1.60)	.08	1.10 (0.99, 1.21)	.08
West	1.32 (1.00, 1.73)	.05	1.12 (1.00, 1.25)	.05
Race/ethnicity
White, non-Hispanic	Ref		Ref
Black, non-Hispanic	1.48 (1.18, 1.87)	<.01	0.98 (0.88, 1.10)	.79
Other	1.24 (1.03, 1.49)	.02	1.00 (0.92, 1.08)	.99
Gender^i
Male	Ref		Ref
Female	1.08 (0.98, 1.18)	.11	0.96 (0.89, 1.03)	.25

^a n = 71 “don’t know” responses combined with 1,465 “no” for analysis.

^bEducation: unweighted n = 27 missing; ≤college includes some college, Associate’s or Bachelor’s Degree.

^cAge: unweighted n = 27 4 missing.

^dParents of young children: unweighted n = 724, Weighted N = 705.73.

^eParents of teenagers: unweighted n = 515, weighted n = 507.03.

^fAdults without minor children: unweighted n = 686, weighted n = 715.12.

^gHousehold annual income: unweighted n = 36 missing.

^hRegion: unweighted n = 3 missing.

ⁱGender: n = 15 transgender excluded

^jPrevalence Ratios (PR) and 95% Confidence Interval (95% CI) estimated using log binomial regression for survey data. Taylor-linearized variance estimation used. Taylor-linearized variance estimation used; p-values estimated using general tests of association. Unweighted N = 1,925; Weighted N = 1,927.87.

Table 10. Potential associations between expected opposition to vaccinomics and prioritization: expecting to feel angry if not prioritized for vaccination and strongly agreeing/agreeing that vaccination is an individual’s choice

	Adjusted Analyses: Parsimonious Models
	Expecting to Feel Angry^c		Individual’s Choice
	aPR (95% CI)	P-value	aPR (95% CI)	P-value
Experience with a serious vaccine reaction^a
No/Don’t know	Ref		Ref
Yes	1.84 (1.25, 2.70)	<.01	1.16 (1.07, 1.25)	<.01
Trust in public health authorities
Low	Ref		Ref
High	0.67 (0.47, 0.96)	.03	0.91 (0.84, 0.98)	.01
Vaccine hesitancy among adults without minor children
Low	Ref
High	0.49 (0.32, 0.73)	<.01	N/A
Education^b
≤High school			Ref
≤College	N/A		0.93 (0.86, 1.01)	0.09
Graduate degree	N/A		1.11 (1.00, 1.21)	0.04
Parents of children <18 years old
No/Prefer not to answer			Ref
Yes	N/A		1.09 (1.00, 1.17)	.04

^a n = 71 “don’t know” responses combined with 1,465 “no” for analysis.

^bEducation: unweighted n = 27 missing; ≤college includes some college, Associate’s or Bachelor’s Degree.

^cExpecting to feel angry: education and parent status excluded due to p < 0.05 in a saturated adjusted model (data not shown). Unweighted N = 686 adults without minor children included; Weighted N = 715.12.

^dIndividual’s choice: Vaccine hesitancy among adults without minor children excluded due to p > 0.05 in univariate analysis (Table 9). Adjusted Prevalence Ratios (aPR) and 95% Confidence Interval (95% CI) estimated using log binomial regression for survey data and the difficult option to facilitate model convergence. Taylor-linearized variance estimation used; p-values estimated using general tests of association. Unweighted N = 1,925; Weighted N = 1,927.87.

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