key: cord-0809192-cv5oc8ew
authors: Wang, Jing; Wagner, Abram L.; Chen, Ying; Jaime, Etienne; Hu, Xinwen; Wu, Shiqiang; Lu, Yihan; Ruan, Yuhua; Pan, Stephen W.
title: Would COVID-19 vaccination willingness increase if mobile technologies prohibit unvaccinated individuals from public spaces? A nationwide discrete choice experiment from China
date: 2021-10-22
journal: Vaccine
DOI: 10.1016/j.vaccine.2021.10.020
sha: 54e8d880ea6a68f7ee03e5e2305c5f1eddb295e7
doc_id: 809192
cord_uid: cv5oc8ew

BACKGROUND: Achieving COVID-19 community protection (aka, herd immunity) in China may be challenging because many individuals remain unsure or are unwilling to be vaccinated. One potential means to increase COVID-19 vaccine uptake is to essentially mandate vaccination by using existing mobile technologies that can prohibit unvaccinated individuals from certain public spaces. The “Health Code” is a ubiquitous mobile phone app in China that regulates freedom of travel based on individuals’ predicted risk of exposure to SARS-CoV-2. Green-colored codes indicate ability to travel unrestricted in low-risk regions; yellow-colored codes indicate prohibition from major public spaces and modes of public transportation. We examined the effects of a “Health Code”-based vaccine mandate on willingness to vaccinate for COVID-19 in China. METHODS: In August 2020, an online discrete choice experiment (DCE) was conducted among adults living in China. Participants completed up to six DCE choice sets, each containing two hypothetical COVID-19 vaccination scenario choices and a “do not vaccinate” choice. Half of the choice sets had a “Health Code” attribute that associated the “do not vaccinate” choice with a yellow Health Code implying restricted travel. Weighted, mixed effects multinomial logit regression was used to estimate preference utilities and predicted choice probabilities. RESULTS: Overall, 873 participants completed 4317 choice sets. Most participants attained at least college-level education (90.9%). 29.8% of participants were identified as vaccine hesitators (defined as being unsure or unwilling to receive a COVID-19 vaccination). With and without the “Health Code”-based vaccine mandate, there was an 8.6% (85% CI: 6.4% - 10.92%) and 17.3% (85% CI:13.1% - 21.6%) respective predicted probability that vaccine hesitators would choose “do not vaccinate” over a common vaccination scenario currently in China (i.e., free, domestic vaccine, 80% effectiveness, 10% probability of fever side-effects, administered in a large hospital, two doses). Corresponding predicted probabilities for people who did not express vaccine hesitancy was 0.3% (93% CI: 0.0% - 14.3%) and 3.5% (93% CI:2.3% - 4.8%). The “Health Code”-based mandate significantly increased willingness to vaccinate when vaccine efficacy was >60%. CONCLUSION: Among vaccine hesitators with higher educational attainment, willingness to vaccinate for COVID-19 appears to increase if mobile technology-based vaccine mandates prohibit unvaccinated individuals from public spaces and public transportation. However, such mandates may not increase willingness if perceived vaccine efficacy is low.

BACKGROUND As of 7 June 2021, there have been more than 3.7 million deaths from Coronavirus disease-2019 , causing unprecedented economic and social disruption (1) . Due in-part to limited healthcare resources and suboptimal recovery outcomes (2) (3) , COVID-19 vaccines are urgently needed to end the pandemic.

As of June 2021, there are 287 COVID-19 vaccine candidates under development, and five vaccines have been approved by the Chinese government (4) (5) . Three vaccines require two doses and are developed by Sinopharm Beijing (79.34% efficacy for symptomatic , Wuhan Co., Ltd. (72.51% efficacy), and Sinovac (50.65-91 .25% efficacy, depending on trial location) (6) (7) (8) . A fourth vaccine is a single-dose adenovirus vector vaccine developed by CanSinoBIO and which has shown 65.28% efficacy (9) . The fifth vaccine is a three-dose recombinant protein vaccine developed by the Institute of Microbiology of the Chinese Academy of Sciences and Anhui Zhifei Longcom Biopharmaceutical Co. Ltd., with 97% of vaccine recipients producing neutralizing antibodies (10) .

Due to limited supply, COVID-19 vaccination campaigns in China initially targeted individuals engaged in medicine and healthcare, workers in public transportation, cold chain industry, and seafood markets, as well as priority groups traveling to high-risk countries or regions for work or study (11) . However, as COVID-19 vaccine stocks have increased in China, so too has access for the general population (12) . As of , virtually all adults residing in China are able to voluntarily receive free COVID-19 vaccination if they so wish (12) .

However, despite the relatively rapid roll-out of free and voluntary COVID-19 vaccines, the vast majority of residents in China have not yet been vaccinated. As of June 6, 2021, only 29.24% of Chinese residents have been vaccinated for , coverage far lower than other countries such as Israel (92.46%) or the United Arab Emirates (60%) (14) . Moreover, China's suboptimal vaccination rate is of increasing concern because new COVID-19 variants are more infectious, thus raising the minimum vaccination coverage threshold needed to reach community protection (aka, herd immunity) (15) . According to one recent estimate, 85% of the population will need to be vaccinated to achieve immunity (15) . Unfortunately, one national survey indicated that only 67.1% of people in China are willing to vaccinate for COVID-19 (16) . Approximately 1 of 3 individuals in China exhibit vaccine hesitancy, defined by the WHO

as "a delay in acceptance or refusal of acceptance of vaccines despite availability of vaccination services." (17) .

One potential means to augment COVID-19 vaccination rates is to implement vaccine mandates, defined as when "…vaccine refusal is legal, but when the state withholds from vaccine refusers social goods to which they would otherwise be entitled." (18) . Vaccine mandates vary in form and severity, ranging from symbolic civil codes without any actual enforcement (aka mirage mandates) to harsh sanctions in the form of fines or imprisonment imposed on transgressors (19) . Studies from Europe and the United States indicate that mandatory vaccinations with penalties are associated with higher vaccination coverage (20) .

In China, new mobile technologies developed in response to the COVID-19 pandemic have created new opportunities to rapidly implement broad vaccination mandates. The "Health Code" is a color-coded smartphone app used to classify individuals' risks of exposure to COVID-19 and serves as the basis for determining individuals' freedom of access to public spaces. A green color Health Code indicates a low risk of COVID-19 exposure, thus enabling the individual to move freely anywhere in low-risk geographic areas (21) . A yellow or red color code implies that the person has been to medium or high-risk areas or has close contacts with confirmed COVID-19 patients and thus needs to be quarantined. Individuals with yellow or red color Health Codes are effectively barred from major modes of public transportation (e.g., train, planes, subway), residential compounds, and some public venues. Individuals without smartphones (e.g., some children or elderly people) can apply for a temporary Health Code at their local government office valid for a limited time period. Security personnel and doormen at public transportation stations, residential compounds, and public spaces are charged with checking individuals' Health Codes and enforcing exclusion of entry with force if necessary. If individuals with yellow or red Health Codes try to enter prohibited public areas, they might be suspected of not cooperating with pandemic prevention measures and may need to bear criminal responsibility if their actions significantly undermine public health (22) . The Health Code color is determined by smartphone Global Positioning System travel history (GPS), relationships with high-risk individuals, and personal information and self-reported physical conditions reported in the Health Code app (21) . Individuals who refuse to use the Health Code essentially forego their rights to access the aforementioned public spaces. Given its ubiquity in Chinese society today, the Health Code could be an efficient and rapidly scalable means of implementing a COVID-19 vaccine mandate.

In the current study, we sought to examine the extent to which individuals who do and do not express vaccine hesitancy in China are more willing to be vaccinated for COVID-19 if the Health Code is hypothetically used to exclude unvaccinated individuals from public spaces.

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In August 2020, a discrete choice experiment (DCE) (23) was conducted to estimate effects of a "Health Code"-based vaccine mandate on willingness to vaccinate for COVID-19 in China.

Participants were asked to complete six choice sets containing two kinds of hypothetical COVID-19 vaccination scenarios and a "do not vaccinate" option. The development of the DCE included three stages: 1) Attribute and level selection, 2) DCE and questionnaire design, 3) DCE implementation.

The WHO defines vaccine hesitancy as "a delay in acceptance or refusal of acceptance of vaccines despite availability of vaccination services (24) ." All participants were asked to endorse their level of agreement or disagreement with the following statement: "If a COVID-19 vaccine were available, I would get vaccinated." Possible responses included "Strongly disagree", "Disagree", "Not Sure", "Agree", and "Strongly agree." Vaccine hesitators were identified as people that selected "Not Sure", "Disagree", or Strongly Disagree". More specifically, those who endorsed "Not sure" were regarded as expressing a delay in vaccination acceptance, while those who endorsed "Disagree" or "Strongly Disagree" were regarded as expressing refusal of vaccine acceptance.

First, attributes and levels were selected by conducting fourteen one-on-one qualitative interviews (three males and eleven females, aged 20 to 74 years) that focused on personal perspectives and preferences regarding COVID-19 vaccines and vaccination. Throughout attribute development, experts from relevant fields (e.g., infectious diseases, vaccines, community health, etc.) provided relevant feedback. Before finalizing attributes and levels, a pilot test of 20 participants recruited by convenience sampling was conducted. Finally, seven attributes with 20 associated levels were used to develop the DCE choice sets ( Table 1 ). The Health Code was an alternative-specific attribute, whereby the two vaccination scenarios were associated with a green color Health Code, but the "do not vaccinate" option was associated with a yellow-colored Health Code. Labels and pictures were developed for each attribute level to make them intuitive and easily understandable.

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A d-efficient design matrix with 36 different choice sets within 12 blocks was produced with NGENE (ChoiceMetrics, 2014) to efficiently increase the precision of parameter estimates (23). Each participant was randomly assigned to one of the twelve blocks. Every block consisted of six choice sets: three containing the Health Code attribute and three that did not. For each choice set, the participants were instructed to select one of two kinds of hypothetical COVID-19 vaccination scenarios or a "do not vaccinate" option. An example choice set is shown in Figure 1 . The design and number of blocks and choice sets were determined based on concerns of respondent cognitive burden, possible survey fatigue and requirements of statistical efficiency (25) .

The DCE was conducted through online surveys in August 2020 using convenience sampling of individuals who met the eligibility criteria: over 18 years old, living in China and provided informed consent. Participant recruitment was conducted on various social media and internet platforms within China (e.g., Wechat and Weibo), whereby interested individuals could anonymously complete the online survey. No material incentives were provided to study participants.

DCE data were analyzed using multinominal mixed effects logit regression models. Effect coding was used for all attribute levels. Additionally, weights were constructed based on the national sex and age distribution of China, so that the analysis would be more generalizable to the general population (26) . The combination of the age and sex resulted in 16 cells (2 levels of sex * 8 age groups = 16), is illustrated in Table 2 . To mitigate the influence of extremely large weights, weights among individuals over 50 years old were trimmed to be no greater than the median weight value + 6 times the inter-quartile range (27, 28) . The analyses were conducted among the whole sample and among those who did and did not express vaccine hesitancy. All analyses used the MLOGIT package in R with 1000 Halton draws (29) .

The probability of choosing the "do not vaccinate" alternative (choice "i") rather than another hypothetical COVID-19 vaccination scenario (choice "j") was estimated using Equation 1. Statistically significant effects of the Health Code on COVID-19 vaccination willingness were assessed by non-overlap of confidence intervals. To maintain a Type I error probability of 0.05 (i.e., alpha=0.05), confidence intervals were set between 84% and 95%, depending on the ratio of standard deviations of the two groups being compared, as recommended by Knol et al (30) . 95% confidence intervals were not constructed by default because doing so would have led to an overly conversative alpha level of 0.0056 (30) . Confidence intervals for predicted choice

probabilities were calculated using the Delta method (31) . In total, the "do not vaccinate" choice probabilities were calculated for sixteen plausible vaccination scenarios within China, based on the most recent vaccination information (6) (7) (8) (9) (10) (32) (33) (34) .

Study protocols were approved by the Ethics Review Board of Xi'an Jiaotong-Liverpool University (protocol number: 19-03-85). Each participant provided informed consent prior to enrollment, and participation was anonymous.

In 15 days, 970 individuals agreed to participate in the survey, 43 of whom did not meet the study eligibility criteria, and 54 of whom did not complete at least one choice set. Hence, 873 (90% of eligible respondents) completed 4317 choice sets. 29.78% of participants were identified as vaccine hesitators (defined as being unsure or unwilling to receive a COVID-19 vaccination).

Participant characteristics are presented in Table 2 . Most participants were female (62.54%), between 18 and 24 years old (71.36%), and most attained at least college-level education (90.88%). Among participants, 38.83% felt they were at risk of becoming infected with COVID-19 and 46.62% were unsure about the safety of COVID-19 vaccines. . Scenarios 1 to 12 most closely reflect the current vaccination situation in China. Generally, the probability of choosing "Do not vaccinate" was higher among those who showed COVID-19 vaccine hesitancy than those who did not express vaccine hesitancy. In addition, the Health Code attribute generally reduced the probability of selecting "Do not vaccinate".

Among those hesitant to receive a COVID-19 vaccine, the Health Code appeared to significantly increase participants' willingness to vaccinate in some but not all vaccination scenarios. For example, the Health Code appears to have reduced the probability of choosing "Do not vaccinate" from 17.34% (85% CI: 13.13% -21.55%) to 8.61% (85%CI: 6.37% -10.85%) when the vaccination scenario is a free, domestic vaccine with 80% effectiveness, 10% probability of fever side-effect, two doses, and administered in a big hospital (Figure 2 ; Scenario 1). However, the Health Code does not appear to have had a significant effect on choosing "Do not vaccinate" when the hypothetical vaccine effectiveness is 60% or below and is administered in a community health clinic (Figure 2 ; Scenario 5). The Health Code appeared to significantly increase COVID-19 vaccination willingness in scenarios 1, 2, 4, 7, and 10 ( Figure 2 ).

Among those not hesitant to receive a COVID-19 vaccine, the Health Code also appeared to significantly increase participants' willingness to vaccinate in some but not all vaccination scenarios. For example, the Health Code appears to have reduced the probability of choosing "Do not vaccinate" from 13.77% (86% CI: 10.80% -16.75%) to 0.82% (87% CI: 0.00% -2.03%) when the vaccination scenario is a free, domestic vaccine with 60% effectiveness, 10% probability of fever side-effect, one or two doses, and administered in a private clinic ( Figure  3 ; Scenario 6). The Health Code appeared to significantly increase COVID-19 vaccination willingness in scenarios 6, 9, 11, 14, 15 , and 16 ( Figure 3 ).

Increasing COVID-19 vaccination coverage is a major goal of countries throughout the world to combat the spread of SARS-CoV-2. However, refusing or delaying COVID-19 vaccination is common worldwide and in China. To the best of our knowledge, this study is the first to quantitatively demonstrate that those hesitant to receive a COVID-19 vaccine in China are Page 9 of 27 V15 06SSEP2021 more willing to be vaccinated for COVID-19 if mobile technologies are used to exclude unvaccinated individuals from public spaces. These findings are instructive for policy makers seeking to augment COVID-19 vaccination rates in China, especially given low rates of influenza vaccination among adults during the H1N1 pandemic in 2009 (35) .

Access, affordability, awareness, and acceptance have been identified as the key drivers of suboptimal vaccination rates (35) . Given the wide publicity and increasing availability of free COVID-19 vaccines in China as of June 2021, public acceptance likely poses the most formidable challenge to achieving optimal vaccination rates in China. Similar to previous surveys (16), we found that approximately only 67% of participants explicitly expressed willingness to be vaccinated for COVID-19. Hence, it appears unlikely that community protection against COVID-19 can be achieved by exclusively relying on those who have already agreed to vaccinate. Mandates and activation "nudges" (36) are likely needed to encourage vaccine uptake among those ambivalent or disinclined to vaccinate.

Gradually escalating vaccination incentives and sanctions over time may be a promising strategy to increase vaccination rates while minimizing potential risk to public trust. For example, numerous provinces in China have already begun to incentivize vaccination by issuing special gold-colored Health Codes and digital badges for individuals who voluntarily completed their COVID-19 vaccination regimens (37) . Establishing such pro-vaccination social norms and status symbols may help persuade some vaccine hesitant individuals to vaccinate, but realistically may not be sufficiently salient to motivate vaccine hesitant individuals who hold serious concerns about COVID-19 vaccine efficacy and side-effects (38) .

If necessary, using the Health Code to exclude unvaccinated individuals from public spaces may be a rapidly scalable and salient means of increasing COVID-19 vaccine willingness in China. First, the Health Code app is already firmly embedded within the daily lives of most residents of China (38) . Not only is the Health Code app infrastructure already well established, but its regulation of access to public space has already been normalized throughout society (39) . In fact, as the COVID-19 vaccination campaigns accelerate nationwide, the "Health Code" is already being linked to individuals' vaccination records. As of June 19, 2021, unvaccinated individuals were still able to obtain a Green "Health Code" (40) . Second, results from the current study strongly suggest that both those who did and did not express vaccine hesitancy were more willing to vaccinate for COVID-19 if their Health Code color is tied to their vaccination status. It is worth noting that, the salience of the Health Code appeared to be greater for vaccinations occurring in big hospitals compared to private clinics and community health centers. In addition, even when a yellow color Health Code was associated with refusal to vaccinate, probabilities of vaccine refusal remained relatively high when vaccine efficacy was

<60% or lower (additional results available upon request), and when the vaccine was a feebased foreign brand. Further studies are needed to elucidate the mechanisms of these findings.

As a last resort, criminalization and coercion are theoretically possible if all other strategies have failed to adequately raise COVID-19 vaccination rates. According to the 2019 Vaccination Law of China, Chinese citizens residing in China are obliged to be vaccinated with vaccines listed in the national program schedule (41). Hence, citizens could theoretically be legally obliged to vaccinate for COVID-19 if it were added to the vaccination schedule. However, despite having legal means to pressure COVID-19 vaccination, the government appears reluctant to adopt such severe sanctions at this time (42). Broad coercive vaccine mandates have high potential to profoundly undermine public trust and should only be considered in the direst public health emergencies. Due partly to the relatively low number of COVID-19 cases in China after the initial outbreak in early 2020 (43), the general public may feel that such coercive measures at this time are unnecessary. Moreover, public confidence in vaccines has already been shaken by several high-profile cases of substandard vaccine production practices in recent years (44) (45) , and cannot be taken for granted.

It is also important to remember that a minority of the population will refuse to vaccinate for COVID-19 no matter what incentives or sanctions are imposed. Some adamant vaccine refusals will be based on medical conditions such as allergies or immunocompromised states, and must be granted medical exemptions (46). In order to discourage prevarication about one's true medical condition, vaccine medical exemptions should be conditioned on the judgement of professional health care providers, rather than solely self-report. Qualitative research on Health Code usage in China suggests that some individuals will deliberately misreport essential data in order to avoid travel restrictions (39) .

Invariably, some individuals will refuse vaccination, even without medical contraindications. For example, religious beliefs and conscientious objection are common non-medical reasons for vaccine refusals in the North America (47), despite evidence that non-medical exemption (NME) policies appear significantly associated with higher disease incidence (48) . Historically, NMEs have not been institutionalized in China, and policy makers must carefully consider if NMEs should be issued for COVID-19 vaccines. Formalizing NMEs for COVID-19 vaccination could lead to calls for NMEs to be issued for additional vaccines. If COVID-19 vaccination NMEs are indeed issued, then it will be critical that those seeking NMEs comply with educational and administrative requirements. For example, NMEs in Germany are only issued to parents after they have completed an educational workshop so that they fully understand the medical implications of refusing vaccination (47) . Imposing such requirements will also help encourage vaccination uptake among those able to vaccinate but are simply

unwilling to complete the administrative procedures (47) . In any case, in the longer term, future research and policies should focus on addressing the structural drivers of vaccine hesitancy in China. Widely publicized cases of substandard vaccine production and administration in recent years have undermined public trust in vaccines, and must be restored through greater regulatory measures, transparency, and public engagement (44) .

Our study has several limitations. First, compared to China's general population, our study sample was relatively young and had high levels of educational attainment. We weighted the sample by age and sex to make the sample more reflective of China's general population, but results may have limited generalizability to individuals with lower educational attainment. Second, the study did not exclude people who were already vaccinated for COVID-19, had recovered from COVID, or had medical issues precluding vaccination. Nevertheless, at the time of the survey, the vast majority of the population did not belong to any of the aforementioned groups (49). Third, the study only elucidated participants' stated choices, which is distinct from actual behavior. However, evidence suggests that real-world human behavior is closely associated with DCE results (50) . Fourth, our DCE study was conducted in August 2020, when the COVID-19 vaccine was not available in China. As COVID-19 vaccination campaigns have expanded and more individuals become vaccinated, COVID-19 vaccination preferences may have changed since the study data were collected. Lastly, we did not assess how trust and attitudes towards the government may be impacted if the Health Code is used to restrict unvaccinated individuals from public spaces, even if vaccination willingness is increased.

Findings from this nationwide DCE study indicate that among individuals with higher educational attainment, willingness to vaccinate for COVID-19 in China will increase if the Health Code is used to restrict unvaccinated individuals from public spaces, assuming that vaccine efficacy is greater than 60%. If necessary, policy makers in China can consider using the Health Code to mandate COVID-19 vaccination uptake, but exemption procedures and impacts on public trust must be carefully deliberated and balanced. The bold data indicate the standard deviation estimates of coefficients are statistically significant.

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S13:100¥/Imp/10%SE/90%

S14:500¥/Imp/10%SE/90%

S15:100¥/Imp/10%SE/60%

S16:500¥/Imp/10%SE/60%

HCC: Health Code Color; 100¥=100CNY; 500¥=500CNY; Dom=Domestic

10%SE = 10% Probably of fever side-effects

= 90% Effectiveness; BH= Big Hospital; CHC= Community Health Center

1D= One Dose; 2D= Two Doses

3D = Three Doses

S13:100¥/Imp/10%SE/90%

S14:500¥/Imp/10%SE/90%

S15:100¥/Imp/10%SE/60%

S16:500¥/Imp/10%SE/60%

HCC: Health Code Color; 100¥=100CNY; 500¥=500CNY; Dom=Domestic

10%SE = 10% Probably of fever side-effects

= 90% Effectiveness; BH= Big Hospital; CHC= Community Health Center

1D= One Dose; 2D= Two Doses

3D = Three Doses

We are grateful to the study participants who made this research possible. Many thanks also to Benjamin Craig for providing early guidance on the selection of DCE attributes.

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: