COVID-19 vaccine acceptability, determinants of potential vaccination, and hesitancy in public: A call for effective health communication

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Abstract

BACKGROUND:

Coronavirus disease rapidly spreads across the entire world in < 2 months and gravely jeopardizes the regular human routine. The medical fraternity recommends a vaccine as one of the best solutions to save the universe. However, to be effective, the population should reflect an encouraging attitude to accept it. The study aimed to measure vaccine acceptability and reason for hesitancy among the public.

MATERIALS AND METHODS:

Eight hundred and forty one adults visiting a tertiary care hospital responded to a pretested validated questionnaire on vaccine acceptability and hesitancy. The Chi-square test and independent t-test, followed by multinomial logistic regression, were used to analyze the findings.

RESULTS:

Overall, 53.4% ( n = 445) of participants interested to take vaccine, 27.2% ( n = 229) were not sure, and the remaining 19.4% ( n = 163) did not intent to vaccinate. Gender ( P = 0.013), information on the vaccine ( P = 0.022), chances to get coronavirus disease in the next 6 months ( P < 0.001), awareness on India COVID-19 vaccine ( P < 0.001), Indian manufacturing company of vaccine ( P < 0.001), family history of the laboratory-confirmed case ( P < 0.001), and health status ( P = 0.011) found a significant association with intention to vaccination (a response “yes” vs. “no” and “not sure”). Reasons for vaccine hesitancy included specific antivaccine attitudes and beliefs, a concern of fear and phobia, lack of information, and safety issues on the vaccine.

CONCLUSIONS:

This institute-specific survey revealed that approximately every 4 in 8 people were not sure to take the vaccine, and one in five people refused to be vaccinated. The study recommends using target-based health education to understand and address vaccine-specific concerns to enhance vaccine coverage, and boost confidence among the population.

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Most cited references 24

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An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.

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A global survey of potential acceptance of a COVID-19 vaccine

Jeffrey V Lazarus, Scott C Ratzan, Adam Palayew … (2020)

Several coronavirus disease 2019 (COVID-19) vaccines are currently in human trials. In June 2020, we surveyed 13,426 people in 19 countries to determine potential acceptance rates and factors influencing acceptance of a COVID-19 vaccine. Of these, 71.5% of participants reported that they would be very or somewhat likely to take a COVID-19 vaccine, and 61.4% reported that they would accept their employer’s recommendation to do so. Differences in acceptance rates ranged from almost 90% (in China) to less than 55% (in Russia). Respondents reporting higher levels of trust in information from government sources were more likely to accept a vaccine and take their employer’s advice to do so.

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Determinants of COVID-19 vaccine acceptance in the US

Amyn A. Malik, SarahAnn McFadden, Jad Elharake … (2020)

Background The COVID-19 pandemic continues to adversely affect the U.S., which leads globally in total cases and deaths. As COVID-19 vaccines are under development, public health officials and policymakers need to create strategic vaccine-acceptance messaging to effectively control the pandemic and prevent thousands of additional deaths. Methods Using an online platform, we surveyed the U.S. adult population in May 2020 to understand risk perceptions about the COVID-19 pandemic, acceptance of a COVID-19 vaccine, and trust in sources of information. These factors were compared across basic demographics. Findings Of the 672 participants surveyed, 450 (67%) said they would accept a COVID-19 vaccine if it is recommended for them. Males (72%) compared to females, older adults (≥55 years; 78%) compared to younger adults, Asians (81%) compared to other racial and ethnic groups, and college and/or graduate degree holders (75%) compared to people with less than a college degree were more likely to accept the vaccine. When comparing reported influenza vaccine uptake to reported acceptance of the COVID-19 vaccine: 1) participants who did not complete high school had a very low influenza vaccine uptake (10%), while 60% of the same group said they would accept the COVID-19 vaccine; 2) unemployed participants reported lower influenza uptake and lower COVID-19 vaccine acceptance when compared to those employed or retired; and, 3) Black Americans reported lower influenza vaccine uptake and lower COVID-19 vaccine acceptance than all other racial groups reported in our study. Lastly, we identified geographic differences with Department of Health and Human Services (DHHS) regions 2 (New York) and 5 (Chicago) reporting less than 50 percent COVID-19 vaccine acceptance. Interpretation Although our study found a 67% acceptance of a COVID-19 vaccine, there were noticeable demographic and geographical disparities in vaccine acceptance. Before a COVID-19 vaccine is introduced to the U.S., public health officials and policymakers must prioritize effective COVID-19 vaccine-acceptance messaging for all Americans, especially those who are most vulnerable.

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Author and article information

Journal

Journal ID (nlm-ta): J Educ Health Promot

Journal ID (iso-abbrev): J Educ Health Promot

Journal ID (publisher-id): JEHP

Title: Journal of Education and Health Promotion

Publisher: Wolters Kluwer - Medknow (India )

ISSN (Print): 2277-9531

ISSN (Electronic): 2319-6440

Publication date Collection: 2021

Publication date (Electronic): 29 October 2021

Volume: 10

Electronic Location Identifier: 392

Affiliations

[1] Department of Nursing, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India

[1 ] Department of Internal Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India

[2 ] Department of Nursing, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India

[3 ] Department of Internal Medicine, Division of Diabetic and Metabolism, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India

Author notes

Address for correspondence: Dr. Mukesh Bairwa, Department of Internal Medicine, All India Institute of Medical Sciences, Rishikesh - 249203, Uttarakhand, India. E-mail: drmukeshbairwa1982@ 123456gmail.com

Article

Publisher ID: JEHP-10-392

DOI: 10.4103/jehp.jehp_327_21

PMC ID: 8641716

PubMed ID: 34912928

SO-VID: 8734bd2d-aa42-40f4-afc7-21a25f3a2a52

License:

This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

COVID-19 vaccine acceptability, determinants of potential vaccination, and hesitancy in public: A call for effective health communication

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Abstract

BACKGROUND:

MATERIALS AND METHODS:

RESULTS:

CONCLUSIONS:

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Novel Coronavirus Disease COVID-19

Most cited references 24

An interactive web-based dashboard to track COVID-19 in real time

A global survey of potential acceptance of a COVID-19 vaccine

Determinants of COVID-19 vaccine acceptance in the US

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