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      Will they, or Won't they? Examining patients' vaccine intention for flu and COVID-19 using the Health Belief Model

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      Research in Social & Administrative Pharmacy
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          Abstract

          Background

          The twindemic of influenza and COVID-19 places pharmacists in a position of high-impact to inform and manage vaccination uptake. Given prior vaccine hesitancy in the US and the current high impact of COVID-19 on the population, it is imperative to understand and address factors that drive perceptions and intention to get vaccinated.

          Objectives

          The objectives of the study were to 1) determine impact of the COVID-19 pandemic on influenza vaccine uptake, on patient perceptions of vaccinations, vaccine intention, and health behaviors and 2) determine vaccine intention through the Health Belief Model.

          Methods

          An IRB-approved prospective Qualtrics-based survey was administered online to eligible respondents: non-pregnant panel respondents 18 years or older within the United States who could independently complete the entire questionnaire in English. Data analyses included descriptive statistics, psychometric analyses of the 5C and CoBQ tools, one-way ANOVA to compare demographic groups and vaccine intention items with survey scores, and mapping and path analysis of the HBM with one added domain (Decision Making Determinant, DMD).

          Results

          525 respondents completed the survey from October 23–29, 2020. Respondents aged 18–49, making less than $20,000 or an undisclosed income, and not having anyone close to them directly affected by COVID-19 showed a significant, negative impact of COVID-19 on health behavior and a significantly lower vaccine acceptance. The 5C and CoBQ showed moderately strong reliability. Mapping for the HBM revealed significant correlations between all modifying factors with Individual Perceptions except for Race/Ethnicity. Of the Individual Perceptions, Perceived Benefits (-.114) and Perceived Barriers (.307) significantly predicted DMD and directly impacted Vaccine Intention. DMD was not a significant mediator of Vaccination Intention.

          Conclusions

          Vaccination messaging should focus on a simple yet balanced view of benefits and risks, targeting those under age 50 and living in low-income households, to motivate uptake of influenza and COVID-19 vaccines.

          Highlights

          • Being within the age group 18–49, having a household income of $20,000 or less, and knowing someone affected by the COVID-19 pandemic significantly affected respondents' vaccine acceptance and negatively impacted health behavior.

          • Public health organizations have campaigned and marketed messages about COVID-19, our results indicate these cues to action do significantly impact vaccine intention.

          • People in the US may make decisions based on perceived individual benefits and risks rather than the population threat of infection and its dire consequences.

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          Most cited references37

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

          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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            Coronavirus Disease 2019 Case Surveillance — United States, January 22–May 30, 2020

            The coronavirus disease 2019 (COVID-19) pandemic resulted in 5,817,385 reported cases and 362,705 deaths worldwide through May, 30, 2020, † including 1,761,503 aggregated reported cases and 103,700 deaths in the United States. § Previous analyses during February–early April 2020 indicated that age ≥65 years and underlying health conditions were associated with a higher risk for severe outcomes, which were less common among children aged 10% of persons in this age group. TABLE 2 Reported underlying health conditions* and symptoms † among persons with laboratory-confirmed COVID-19, by sex and age group — United States, January 22–May 30, 2020 Characteristic No. (%) Total Sex Age group (yrs) Male Female ≤9 10–19 20–29 30–39 40–49 50–59 60–69 70–79 ≥80 Total population 1,320,488 646,358 674,130 20,458 49,245 182,469 214,849 219,139 235,774 179,007 105,252 114,295 Underlying health condition§ Known underlying medical condition status* 287,320 (21.8) 138,887 (21.5) 148,433 (22.0) 2,896 (14.2) 7,123 (14.5) 27,436 (15.0) 33,483 (15.6) 40,572 (18.5) 54,717 (23.2) 50,125 (28.0) 34,400 (32.7) 36,568 (32.0) Any cardiovascular disease¶ 92,546 (32.2) 47,567 (34.2) 44,979 (30.3) 78 (2.7) 164 (2.3) 1,177 (4.3) 3,588 (10.7) 8,198 (20.2) 16,954 (31.0) 21,466 (42.8) 18,763 (54.5) 22,158 (60.6) Any chronic lung disease 50,148 (17.5) 20,930 (15.1) 29,218 (19.7) 363 (12.5) 1,285 (18) 4,537 (16.5) 5,110 (15.3) 6,127 (15.1) 8,722 (15.9) 9,200 (18.4) 7,436 (21.6) 7,368 (20.1) Renal disease 21,908 (7.6) 12,144 (8.7) 9,764 (6.6) 21 (0.7) 34 (0.5) 204 (0.7) 587 (1.8) 1,273 (3.1) 2,789 (5.1) 4,764 (9.5) 5,401 (15.7) 6,835 (18.7) Diabetes 86,737 (30.2) 45,089 (32.5) 41,648 (28.1) 12 (0.4) 225 (3.2) 1,409 (5.1) 4,106 (12.3) 9,636 (23.8) 19,589 (35.8) 22,314 (44.5) 16,594 (48.2) 12,852 (35.1) Liver disease 3,953 (1.4) 2,439 (1.8) 1,514 (1.0) 5 (0.2) 19 (0.3) 132 (0.5) 390 (1.2) 573 (1.4) 878 (1.6) 1,074 (2.1) 583 (1.7) 299 (0.8) Immunocompromised 15,265 (5.3) 7,345 (5.3) 7,920 (5.3) 61 (2.1) 146 (2.0) 646 (2.4) 1,253 (3.7) 2,005 (4.9) 3,190 (5.8) 3,421 (6.8) 2,486 (7.2) 2,057 (5.6) Neurologic/Neurodevelopmental disability 13,665 (4.8) 6,193 (4.5) 7,472 (5.0) 41 (1.4) 113 (1.6) 395 (1.4) 533 (1.6) 734 (1.8) 1,338 (2.4) 2,006 (4.0) 2,759 (8.0) 5,746 (15.7) Symptom§ Known symptom status† 373,883 (28.3) 178,223 (27.6) 195,660 (29.0) 5,188 (25.4) 12,689 (25.8) 51,464 (28.2) 59,951 (27.9) 62,643 (28.6) 70,040 (29.7) 52,178 (29.1) 28,583 (27.2) 31,147 (27.3) Fever, cough, or shortness of breath 260,706 (69.7) 125,768 (70.6) 134,938 (69.0) 3,278 (63.2) 7,584 (59.8) 35,072 (68.1) 42,016 (70.1) 45,361 (72.4) 51,283 (73.2) 37,701 (72.3) 19,583 (68.5) 18,828 (60.4) Fever †† 161,071 (43.1) 80,578 (45.2) 80,493 (41.1) 2,404 (46.3) 4,443 (35.0) 20,381 (39.6) 25,887 (43.2) 28,407 (45.3) 32,375 (46.2) 23,591 (45.2) 12,190 (42.6) 11,393 (36.6) Cough 187,953 (50.3) 89,178 (50.0) 98,775 (50.5) 1,912 (36.9) 5,257 (41.4) 26,284 (51.1) 31,313 (52.2) 34,031 (54.3) 38,305 (54.7) 27,150 (52.0) 12,837 (44.9) 10,864 (34.9) Shortness of breath 106,387 (28.5) 49,834 (28.0) 56,553 (28.9) 339 (6.5) 2,070 (16.3) 13,649 (26.5) 16,851 (28.1) 18,978 (30.3) 21,327 (30.4) 16,018 (30.7) 8,971 (31.4) 8,184 (26.3) Myalgia 135,026 (36.1) 61,922 (34.7) 73,104 (37.4) 537 (10.4) 3,737 (29.5) 21,153 (41.1) 26,464 (44.1) 28,064 (44.8) 28,594 (40.8) 17,360 (33.3) 6,015 (21.0) 3,102 (10.0) Runny nose 22,710 (6.1) 9,900 (5.6) 12,810 (6.5) 354 (6.8) 1,025 (8.1) 4,591 (8.9) 4,406 (7.3) 4,141 (6.6) 4,100 (5.9) 2,671 (5.1) 923 (3.2) 499 (1.6) Sore throat 74,840 (20.0) 31,244 (17.5) 43,596 (22.3) 664 (12.8) 3,628 (28.6) 14,493 (28.2) 14,855 (24.8) 14,490 (23.1) 13,930 (19.9) 8,192 (15.7) 2,867 (10.0) 1,721 (5.5) Headache 128,560 (34.4) 54,721 (30.7) 73,839 (37.7) 785 (15.1) 5,315 (41.9) 23,723 (46.1) 26,142 (43.6) 26,245 (41.9) 26,057 (37.2) 14,735 (28.2) 4,163 (14.6) 1,395 (4.5) Nausea/Vomiting 42,813 (11.5) 16,549 (9.3) 26,264 (13.4) 506 (9.8) 1,314 (10.4) 6,648 (12.9) 7,661 (12.8) 8,091 (12.9) 8,737 (12.5) 5,953 (11.4) 2,380 (8.3) 1,523 (4.9) Abdominal pain 28,443 (7.6) 11,553 (6.5) 16,890 (8.6) 349 (6.7) 978 (7.7) 4,211 (8.2) 5,150 (8.6) 5,531 (8.8) 6,134 (8.8) 3,809 (7.3) 1,449 (5.1) 832 (2.7) Diarrhea 72,039 (19.3) 32,093 (18.0) 39,946 (20.4) 704 (13.6) 1,712 (13.5) 9,867 (19.2) 12,769 (21.3) 13,958 (22.3) 15,536 (22.2) 10,349 (19.8) 4,402 (15.4) 2,742 (8.8) Loss of smell or taste 31,191 (8.3) 12,717 (7.1) 18,474 (9.4) 67 (1.3) 1,257 (9.9) 6,828 (13.3) 6,907 (11.5) 6,361 (10.2) 5,828 (8.3) 2,930 (5.6) 775 (2.7) 238 (0.8) Abbreviation: COVID-19 = coronavirus disease 2019. * Status of underlying health conditions known for 287,320 persons. Status was classified as “known” if any of the following conditions were reported as present or absent: diabetes mellitus, cardiovascular disease (including hypertension), severe obesity (body mass index ≥40 kg/m2), chronic renal disease, chronic liver disease, chronic lung disease, immunocompromising condition, autoimmune condition, neurologic condition (including neurodevelopmental, intellectual, physical, visual, or hearing impairment), psychologic/psychiatric condition, and other underlying medical condition not otherwise specified. † Symptom status was known for 373,883 persons. Status was classified as “known” if any of the following symptoms were reported as present or absent: fever (measured >100.4°F [38°C] or subjective), cough, shortness of breath, wheezing, difficulty breathing, chills, rigors, myalgia, rhinorrhea, sore throat, chest pain, nausea or vomiting, abdominal pain, headache, fatigue, diarrhea (≥3 loose stools in a 24-hour period), or other symptom not otherwise specified on the form. § Responses include data from standardized fields supplemented with data from free-text fields. Information for persons with loss of smell or taste was exclusively extracted from a free-text field; therefore, persons exhibiting this symptom were likely underreported. ¶ Includes persons with reported hypertension. ** Includes all persons with at least one of these symptoms reported. †† Persons were considered to have a fever if information on either measured or subjective fever variables if “yes” was reported for either variable. Among 287,320 (22%) cases with data on individual underlying health conditions, those most frequently reported were cardiovascular disease (32%), diabetes (30%), and chronic lung disease (18%) (Table 2); the reported proportions were similar among males and females. The frequency of conditions reported varied by age group: cardiovascular disease was uncommon among those aged ≤39 years but was reported in approximately half of the cases among persons aged ≥70 years. Among 63,896 females aged 15–44 years with known pregnancy status, 6,708 (11%) were reported to be pregnant. Among the 1,320,488 cases, outcomes for hospitalization, ICU admission, and death were available for 46%, 14%, and 36%, respectively. Overall, 184,673 (14%) patients were hospitalized, including 29,837 (2%) admitted to the ICU; 71,116 (5%) patients died (Table 3). Severe outcomes were more commonly reported for patients with reported underlying conditions. Hospitalizations were six times higher among patients with a reported underlying condition than those without reported underlying conditions (45.4% versus 7.6%). Deaths were 12 times higher among patients with reported underlying conditions compared with those without reported underlying conditions (19.5% versus 1.6%). The percentages of males who were hospitalized (16%), admitted to the ICU (3%), and who died (6%) were higher than were those for females (12%, 2%, and 5%, respectively). The percentage of ICU admissions was highest among persons with reported underlying conditions aged 60–69 years (11%) and 70–79 years (12%). Death was most commonly reported among persons aged ≥80 years regardless of the presence of underlying conditions (with underlying conditions 50%; without 30%). TABLE 3 Reported hospitalizations,* , † intensive care unit (ICU) admissions, § and deaths ¶ among laboratory-confirmed COVID-19 patients with and without reported underlying health conditions, ** by sex and age — United States, January 22–May 30, 2020 Characteristic (no.) Outcome, no./total no. (%)†† Reported hospitalizations*,† (including ICU) Reported ICU admission§ Reported deaths¶ Among all patients Among patients with reported underlying health conditions Among patients with no reported underlying health conditions Among all patients Among patients with reported underlying health conditions Among patients with no reported underlying health conditions Among all patients Among patients with reported underlying health conditions Among patients with no reported underlying health conditions Sex Male (646,358) 101,133/646,358 (15.6) 49,503/96,839 (51.1) 3,596/42,048 (8.6) 18,394/646,358 (2.8) 10,302/96,839 (10.6) 864/42,048 (2.1) 38,773/646,358 (6.0) 21,667/96,839 (22.4) 724/42,048 (1.7) Female (674,130) 83,540/674,130 (12.4) 40,698/102,040 (39.9) 3,087/46,393 (6.7) 11,443/674,130 (1.7) 6,672/102,040 (6.5) 479/46,393 (1.0) 32,343/674,130 (4.8) 17,145/102,040 (16.8) 707/46,393 (1.5) Age group (yrs) ≤9 (20,458) 848/20,458 (4.1) 138/619 (22.3) 84/2,277 (3.7) 141/20,458 (0.7) 31/619 (5.0) 16/2,277 (0.7) 13/20,458 (0.1) 4/619 (0.6) 2/2,277 (0.1) 10–19 (49,245) 1,234/49,245 (2.5) 309/2,076 (14.9) 115/5,047 (2.3) 216/49,245 (0.4) 72/2,076 (3.5) 17/5,047 (0.3) 33/49,245 (0.1) 16/2,076 (0.8) 4/5,047 (0.1) 20–29 (182,469) 6,704/182,469 (3.7) 1,559/8,906 (17.5) 498/18,530 (2.7) 864/182,469 (0.5) 300/8,906 (3.4) 56/18,530 (0.3) 273/182,469 (0.1) 122/8,906 (1.4) 24/18,530 (0.1) 30–39 (214,849) 12,570/214,849 (5.9) 3,596/14,854 (24.2) 828/18,629 (4.4) 1,879/214,849 (0.9) 787/14,854 (5.3) 135/18,629 (0.7) 852/214,849 (0.4) 411/14,854 (2.8) 21/18,629 (0.1) 40–49 (219,139) 19,318/219,139 (8.8) 7,151/24,161 (29.6) 1,057/16,411 (6.4) 3,316/219,139 (1.5) 1,540/24,161 (6.4) 208/16,411 (1.3) 2,083/219,139 (1.0) 1,077/24,161 (4.5) 58/16,411 (0.4) 50–59 (235,774) 31,588/235,774 (13.4) 14,639/40,297 (36.3) 1,380/14,420 (9.6) 5,986/235,774 (2.5) 3,335/40,297 (8.3) 296/14,420 (2.1) 5,639/235,774 (2.4) 3,158/40,297 (7.8) 131/14,420 (0.9) 60–69 (179,007) 39,422/179,007 (22.0) 21,064/42,206 (49.9) 1,216/7,919 (15.4) 7,403/179,007 (4.1) 4,588/42,206 (10.9) 291/7,919 (3.7) 11,947/179,007 (6.7) 7,050/42,206 (16.7) 187/7,919 (2.4) 70–79 (105,252) 35,844/105,252 (34.1) 20,451/31,601 (64.7) 780/2,799 (27.9) 5,939/105,252 (5.6) 3,771/31,601 (11.9) 199/2,799 (7.1) 17,510/105,252 (16.6) 10,008/31,601 (31.7) 286/2,799 (10.2) ≥80 (114,295) 37,145/114,295 (32.5) 21,294/34,159 (62.3) 725/2,409 (30.1) 4,093/114,295 (3.6) 2,550/34,159 (7.5) 125/2,409 (5.2) 32,766/114,295 (28.7) 16,966/34,159 (49.7) 718/2,409 (29.8) Total (1,320,488) 184,673/1,320,488 (14.0) 90,201/198,879 (45.4) 6,683/88,441 (7.6) 29,837/1,320,488 (2.3) 16,974/198,879 (8.5) 1,343/88,441 (1.5) 71,116/1,320,488 (5.4) 38,812/198,879 (19.5) 1,431/88,441 (1.6) Abbreviation: COVID-19 = coronavirus disease 2019. * Hospitalization status was known for 600,860 (46%). Among 184,673 hospitalized patients, the presence of underlying health conditions was known for 96,884 (53%). † Includes reported ICU admissions. § ICU admission status was known for 186,563 (14%) patients among the total case population, representing 34% of hospitalized patients. Among 29,837 patients admitted to the ICU, the status of underlying health conditions was known for 18,317 (61%). ¶ Death outcomes were known for 480,565 (36%) patients. Among 71,116 reported deaths through case surveillance, the status of underlying health conditions was known for 40,243 (57%) patients. ** Status of underlying health conditions was known for 287,320 (22%) patients. Status was classified as “known” if any of the following conditions were noted as present or absent: diabetes mellitus, cardiovascular disease including hypertension, severe obesity body mass index ≥40 kg/m2, chronic renal disease, chronic liver disease, chronic lung disease, any immunocompromising condition, any autoimmune condition, any neurologic condition including neurodevelopmental, intellectual, physical, visual, or hearing impairment, any psychologic/psychiatric condition, and any other underlying medical condition not otherwise specified. †† Outcomes were calculated as the proportion of persons reported to be hospitalized, admitted to an ICU, or who died among total in the demographic group. Outcome underreporting could result from outcomes that occurred but were not reported through national case surveillance or through clinical progression to severe outcomes that occurred after time of report. Discussion As of May 30, a total of 1,761,503 aggregate U.S. cases of COVID-19 and 103,700 associated deaths were reported to CDC. Although average daily reported cases and deaths are declining, 7-day moving averages of daily incidence of COVID-19 cases indicate ongoing community transmission. ¶¶¶¶ The COVID-19 case data summarized here are essential statistics for the pandemic response and rely on information systems developed at the local, state, and federal level over decades for communicable disease surveillance that were rapidly adapted to meet an enormous, new public health threat. CDC aggregate counts are consistent with those presented through the Johns Hopkins University (JHU) Coronavirus Resource Center, which reported a cumulative total of 1,770,165 U.S. cases and 103,776 U.S. deaths on May 30, 2020.***** Differences in aggregate counts between CDC and JHU might be attributable to differences in reporting practices to CDC and jurisdictional websites accessed by JHU. Reported cumulative incidence in the case surveillance population among persons aged ≥20 years is notably higher than that among younger persons. The lower incidence in persons aged ≤19 years could be attributable to undiagnosed milder or asymptomatic illnesses among this age group that were not reported. Incidence in persons aged ≥80 years was nearly double that in persons aged 70–79 years. Among cases with known race and ethnicity, 33% of persons were Hispanic, 22% were black, and 1.3% were AI/AN. These findings suggest that persons in these groups, who account for 18%, 13%, and 0.7% of the U.S. population, respectively, are disproportionately affected by the COVID-19 pandemic. The proportion of missing race and ethnicity data limits the conclusions that can be drawn from descriptive analyses; however, these findings are consistent with an analysis of COVID-19–Associated Hospitalization Surveillance Network (COVID-NET) ††††† data that found higher proportions of black and Hispanic persons among hospitalized COVID-19 patients than were in the overall population ( 4 ). The completeness of race and ethnicity variables in case surveillance has increased from 20% to >40% from April 2 to June 2. Although reporting of race and ethnicity continues to improve, more complete data might be available in aggregate on jurisdictional websites or through sources like the COVID Tracking Project’s COVID Racial Data Tracker. §§§§§ The data in this report show that the prevalence of reported symptoms varied by age group but was similar among males and females. Fewer than 5% of persons were reported to be asymptomatic when symptom data were submitted. Persons without symptoms might be less likely to be tested for COVID-19 because initial guidance recommended testing of only symptomatic persons and was hospital-based. Guidance on testing has evolved throughout the response. ¶¶¶¶¶ Whereas incidence among males and females was similar overall, severe outcomes were more commonly reported among males. Prevalence of reported severe outcomes increased with age; the percentages of hospitalizations, ICU admissions, and deaths were highest among persons aged ≥70 years, regardless of underlying conditions, and lowest among those aged ≤19 years. Hospitalizations were six times higher and deaths 12 times higher among those with reported underlying conditions compared with those with none reported. These findings are consistent with previous reports that found that severe outcomes increased with age and underlying condition, and males were hospitalized at a higher rate than were females ( 2 , 4 , 5 ). The findings in this report are subject to at least three limitations. First, case surveillance data represent a subset of the total cases of COVID-19 in the United States; not every case in the community is captured through testing and information collected might be limited if persons are unavailable or unwilling to participate in case investigations or if medical records are unavailable for data extraction. Reported cumulative incidence, although comparable across age and sex groups within the case surveillance population, are underestimates of the U.S. cumulative incidence of COVID-19. Second, reported frequencies of individual symptoms and underlying health conditions presented from case surveillance likely underestimate the true prevalence because of missing data. Finally, asymptomatic cases are not captured well in case surveillance. Asymptomatic persons are unlikely to seek testing unless they are identified through active screening (e.g., contact tracing), and, because of limitations in testing capacity and in accordance with guidance, investigation of symptomatic persons is prioritized. Increased identification and reporting of asymptomatic cases could affect patterns described in this report. Similar to earlier reports on COVID-19 case surveillance, severe outcomes were more commonly reported among persons who were older and those with underlying health conditions ( 1 ). Findings in this report align with demographic and severe outcome trends identified through COVID-NET ( 4 ). Findings from case surveillance are evaluated along with enhanced surveillance data and serologic survey results to provide a comprehensive picture of COVID-19 trends, and differences in proportion of cases by racial and ethnic groups should continue to be examined in enhanced surveillance to better understand populations at highest risk. Since the U.S. COVID-19 response began in January, CDC has built on existing surveillance capacity to monitor the impact of illness nationally. Collection of detailed case data is a resource-intensive public health activity, regardless of disease incidence. The high incidence of COVID-19 has highlighted limitations of traditional public health case surveillance approaches to provide real-time intelligence and supports the need for continued innovation and modernization. Despite limitations, national case surveillance of COVID-19 serves a critical role in the U.S. COVID-19 response: these data demonstrate that the COVID-19 pandemic is an ongoing public health crisis in the United States that continues to affect all populations and result in severe outcomes including death. National case surveillance findings provide important information for targeted enhanced surveillance efforts and development of interventions critical to the U.S. COVID-19 response. Summary What is already known about this topic? Surveillance data reported to CDC through April 2020 indicated that COVID-19 leads to severe outcomes in older adults and those with underlying health conditions. What is added by this report? As of May 30, 2020, among COVID-19 cases, the most common underlying health conditions were cardiovascular disease (32%), diabetes (30%), and chronic lung disease (18%). Hospitalizations were six times higher and deaths 12 times higher among those with reported underlying conditions compared with those with none reported. What are the implications for public health practice? Surveillance at all levels of government, and its continued modernization, is critical for monitoring COVID-19 trends and identifying groups at risk for infection and severe outcomes. These findings highlight the continued need for community mitigation strategies, especially for vulnerable populations, to slow COVID-19 transmission.
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              Determinants of COVID-19 vaccine acceptance in the US

              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
                Res Social Adm Pharm
                Res Social Adm Pharm
                Research in Social & Administrative Pharmacy
                Elsevier Inc.
                1551-7411
                1934-8150
                30 December 2020
                30 December 2020
                Affiliations
                [1]Western University of Health Sciences College of Pharmacy, United States
                Author notes
                []Corresponding author. Associate Dean for Assessment and Professor, College of Pharmacy Western University of Health Sciences, 309 E. Second Street, Pomona, CA, 91766, United States.
                Article
                S1551-7411(20)31240-7
                10.1016/j.sapharm.2020.12.012
                7833824
                33431259
                6cc5f926-a382-4798-9068-8bbf85dd1bcb
                © 2020 Elsevier Inc. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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                : 10 December 2020
                : 22 December 2020
                : 23 December 2020
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