writing case study and need the explanation and answer to help me learn.
Students may choose to either work independently or collaboratively with one classmate to complete this assignment. Student choice. The purpose of this assignment is to provide students practice in conducting a written review of one health policy primary research study. For some students, this may require a review of research terms and/or the structure of a published research study. A one page overview of the structure and content of research articles is listed here as as resource.
Select one study among four primary recently published studies posted here to review. Students may not select and review an alternate article. Only select one study based on your interest in health policy related to Ukrainian refugees, vaccine hesitency or assisted suicide.
Complete the attached research study review worksheet. Place your answers directly on the worksheet. Do not use a separate paper for this assignment.
Requirements: on the worksheet
Health Policy Research Review Worksheet
Answer directly onto this worksheet
Citation- list the selected health policy research publication citation formatted precisely, including spacing per your selected writing style.
Candio, P., Violato, M., Clarke, P. M., Duch, R., & Roope, L. S. (2023). Prevalence, predictors and reasons for covid-19 vaccine hesitancy: Results of a global online survey. Health Policy, 137, 104895. https://doi.org/10.1016/j.healthpol.2023.104895
Introduction/Background- what is the problem? the problem(s) which led to this study? This includes the scope of the problem described with evidence such as a statistical trend. This is not the research itself. Include at least one in-text reference in your answer and the full reference at the end of the worksheet.
The problem which led to this study is Vaccine hesitancy presenting challenge to Covid-19 control efforts. Ending the Covid-19 pandemic has been a challenge due to lack of trust, personnel beliefs, environmental and social factors. This study presents that” 80 percent of the population” have received the vaccination, the remaining 20 percent presents the problem of transmitting other variants of the disease.
Review of Literature (ROL) – What is known? Discuss the current studies and findings presented by the investigators specifically. Do not make broad statements. Summarize the ROL in one or two well developed paragraphs using a minimum of three in-text citations. Why is this study needed?
Research Question- what is the research question? Phrase as a question. The research purpose may be presented but write it as a question. Write in one sentence. Later you will discuss the answer or findings of the study to the question.
Study Variables- First define the research terms independent and dependent variables. These definitions are not in the article. Secondly, what are the independent and dependent variables in this study?
Study Design and Methods – be specific, precise, and complete in your answers.
Describe the study design (e.g., quantitative, qualitative, descriptive, exploratory, experimental, mixed-method, randomized control trial (RCT), survey, focus group, large existing data study). Define each study design term used (not in the article).
What is the study setting?
Describe the study sample. What were the inclusion and exclusion criteria for study participants?
Measurement – what instruments/tools/surveys were used in this study? Discuss each instrument and the associated reliability and validity of each (if reported)? Include instrument in-text citation. Lastly, define reliability and validity (not in the article). Discuss and define one type of reliability and one type of validity (not in the article).
Results- what were the main findings or results? List each research question and its answer/result if there are several. Clearly and specifically discuss the findings of this study.
What were at least two limitations of the study? Stated and unstated. Define what a limitation is (not in the article).
Discuss at least two health policy implications from this study. This discussion is based solely on this study.
References (formatted per writing style and using a citation manager software)
Prevalence, predictors and reasons for COVID-19 vaccine hesitancy: Results of a global online survey Paolo Candioa,b,c,*, Mara Violatob,c, Philip M Clarkeb,c,d, Raymond Duche, Laurence SJ Roopeb,c aDepartment of Economics and Management, University of Trento, Trento, Italy bHealth Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom cNational Institute for Health Research Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom dCentre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia eNuffield College, University of Oxford, Oxford, United Kingdom of Great Britain and Northern Ireland, UK ARTICLE INFO Keywords: Vaccine hesitancy COVID-19 Public health Predictors Global assessment ABSTRACT Vaccine hesitancy has the potential to cripple efforts to end the COVID-19 pandemic. Policy makers need to be informed about the scale, nature and drivers of this problem, both domestically and globally, so that effective interventions can be designed. To this end, we conducted a statistical analysis of data from the CANDOUR survey (n =15,536), which was carried out in 13 countries representing approximately half of the global population. Both pooled and country-level ordered regression models were estimated to identify predictors of vaccine hes-itancy and reasons for not getting vaccinated. We found high levels of hesitancy, particularly in high-income countries. Factors driving moderate hesitancy differed from those driving extreme hesitancy. A lack of trust in health care providers was consistently the underlying driver of more extreme hesitancy. Predictors of moderate hesitancy varied across countries, though being younger and female was typically associated with greater hes-itancy. While political ideology played a role in vaccine hesitancy in some countries, this effect was often moderated by income level, particularly in the US. Overall, the results suggest that different interventions such as mass-media campaigns and monetary incentives may be needed to target the moderately versus extremely hesitant. The lack of trust in health care professionals that drives extreme hesitancy may reflect deep societal mistrust in science and institutions and be challenging to overcome. 1.Introduction The COVID-19 pandemic continues to impose substantial costs worldwide to human life and to the economy . To tackle the virus, unprecedented efforts have been spent on developing and rolling out effective vaccines . In late 2020, following the first successful results from randomized controlled trials, it became clear that availability of a number of effective vaccines was soon to become a reality, giving hope for a return to normalcy . However, ending the COVID-19 pandemic remains an immense challenge, requiring not only global access to vaccines, but also very high levels of vaccine uptake. Whilst there had been hope that herd immunity would be obtained with COVID-19 vaccination rates of around 80 percent of populations [4,5], the emer-gence of more transmissible variants better equipped to evade existing vaccines means that almost 100% vaccination coverage is now desirable, likely including ongoing cycles of booster vaccinations [6–10]. As increasingly recognised by national and international authorities, a potentially serious barrier to overcoming this challenge is vaccine hesitancy . While vaccine hesitancy, which has been on the rise in recent decades , has been a public health concern for some time , its potential for crippling efforts to end the pandemic have placed it uniquely under the spotlight. A prerequisite for enabling policy makers to tackle COVID-19 vaccine hesitancy is understanding the scale of the problem. Clearly, this requires gauging the prevalence of vaccine hesitancy in populations. However, it is increasingly recognized that vaccine hesitancy is a spectrum, ranging from full acceptance (i.e., no hesitancy) to refusal . So, equally important is to estimate the de-gree to which hesitancy manifests itself. The factors driving moderate hesitancy may differ substantially from those driving strong hostility to *Corresponding author at: Via Vigilio Inama n. 5, 38122 Trento, Italy. E-mail address: email@example.com (P. Candio). Contents lists available at ScienceDirect Health policy journal homepage: www.elsevier.com/locate/healthpol https://doi.org/10.1016/j.healthpol.2023.104895 Received 24 March 2022; Received in revised form 10 July 2023; Accepted 17 August 2023
vaccination  and such evidence is needed to inform the design of effective interventions, such as targeted communication strategies  or appropriate vaccine uptake incentives . Since the start of the pandemic, a rapidly growing literature has investigated hesitancy towards vaccination against COVID-19. From country-level analyses [18–21] to systematic reviews and meta-analyses [22–25], many important contributions have been made, particularly toward estimating levels and extent of hesitancy and identifying which groups within society hold unfavourable attitudes toward vaccination. Most studies have been within high income countries, where vaccination campaigns are well underway, while in low- and middle-income coun-tries, the evidence base on vaccine levels, extent and drivers remains limited . Vaccine hesitancy has always been a contextual, multi-faceted phe-nomenon, which is influenced by a wide array of individual as well as social and economic factors . However, in contrast to previous vaccinations, COVID-19 vaccination is central to public discourse and policy. The pandemic has dictated a sudden extraordinary mobilization of resources and measures limiting individual freedoms, hence un-doubtedly putting pressure on the role and mandate of public in-stitutions and agencies at all levels of society. Under such unprecedented circumstances, understanding what fundamentally drives hesitancy re-quires capturing and accounting for domains spanning across the social sciences. At the time of writing, several surveys are being conducted simultaneously to identify determinants and reasons for vaccine hesi-tancy and inform public policy design. From a conceptual standpoint, as with other vaccines, systematic differences in COVID-19 vaccine hesi-tancy can be reasonably expected to exist between different population subgroups, such as those based on age, gender, health and socio-economic status. However, additional information beyond socio-demographic characteristics such these can provide a more compre-hensive picture of the underlying reasons for vaccine hesitancy . Given the nature and scale of implications of the current pandemic it is therefore valuable to also consider factors such as political ideology and trust in health authorities, which are not typically included in health surveys , but could play a role in explaining vaccine hesitancy. While some individual country-level studies have addressed these concerns [30,31], inconsistency in survey and analysis methods used presents a substantial barrier to reliable comparative assessments of study findings. In turn, this is a barrier to informing national and in-ternational authorities and governments on future coordinated actions and communication strategies. To address these information needs, we present findings from a statistical analysis of an unusually rich 13-coun-try individual level dataset. This dataset, from the first wave of the CANDOUR study , represents approximately half the global population. 2.Methods 2.1.Data A detailed report of the CANDOUR survey is available elsewhere . In brief, 15,536 respondents (≥18 years old) from Australia, Brazil, Canada, Chile, China, Colombia, France, India, Italy, Spain, Uganda, UK and the USA were surveyed online between during the period November 24, 2020 to January 14, 2021. In all countries apart from Chile and Uganda, respondents were sampled by the sampling firm, Respondi. In Chile and Uganda, respondents were recruited using Facebook Ad Manager. All participants were aged 18 or older and signed a consent form before taking part in the survey. The median length of interview was 29.9 min. In the eleven Respondi-sampled countries, the modal incentive was £2.00. Respondents in Chile received payments of $3.00 and in Uganda $2.25. The final sample included an average of 1195 respondents per country (15,536 respondents overall). The average response rate across all countries (calculated as the fraction of complete responses over invited, eligible participants) was 21.3%. Duch et al. (2021)  compared the CANDOUR sample distributions with those obtained from the most recent available national census in each of the 13 countries. The CANDOUR sample and population age distributions were found to be similar in most countries, though with higher distributions of young respondents in Chile, China, Colombia and Uganda. The Chile sample over-represents women, while women are under-represented in India and Uganda. As is typical with online surveys, in virtually all countries (all except Italy and the UK), the highly educated are over-represented, and the lower-educated under-represented. Country-specific quota sampling based on age, gender, education and region was employed in order for the survey samples to roughly match the characteristics of the population of each country, except for India where target sample quotas were employed. To adjust for imbalances between the quotas and the final survey samples, post-stratification weights were constructed using a raking procedure and subsequently applied for statistical analysis. Demographic characteristics of the re-spondents are described in Table 1. 2.2.Measures The outcome measures were: 1 The extent of vaccine hesitancy. This was surveyed using the following question: “If a vaccine that protected you from COVID-19 was available, would you get it?” (“definitely get it”; “probably get it”; “probably not get it”; “definitely not get it”; “do not know”; “prefer not to say”) 2 Reasons for not getting vaccinated against COVID-19 [‘check all that apply’ question asked to respondents who either indicated that they would “definitely” or “probably” not get the vaccine or would only “probably” get the vaccine]: •Vaccine effectiveness – “I don’t believe the COVID-19 vaccine will be effective”; •Potential side effects – “I am concerned about dangerous side ef-fects from the COVID-19 vaccine”; •Herd immunity – ”Enough other people will accept vaccination so I will benefit from herd immunity”; •Infected – “I have already been infected with COVID-19 and believe I have developed natural immunity”; •No harm – “The COVID-19 virus will not be very harmful to my health”; •No trust – “I don’t trust the health care providers in this country”; •Other Socio-demographic characteristics of respondents selected for our analysis were: country of origin, age, gender, chronic health conditions, living with a partner, number of dependent children, education level, employment status, political ideology and quartile of the domestic in-come distribution. Political ideology was measured on a scale from 0 to 10 going from left to right, which we categorised into tertiles as left (0–3), centrist (4–7) and right (8–10). Income quartile was based on total household income, adjusted for household composition using the Modified OECD equivalence scale . 2.3.Statistical analysis Summary statistics were used to describe levels of vaccine hesitancy across the 13 countries. Both pooled and country-level regression ana-lyses were run to identify vaccine hesitancy determinants across and within the 13 countries under study, respectively. Ordered logistic regression models were estimated to identify individual-level predictors of vaccine hesitancy (five levels, in decreasing order: “definitely get it”; “probably get it”; “do not know”; “probably not get it”; “definitely not get it”). Three regression models built progressively including all the vari-ables identified above were estimated. Model 1 included variables P. Candio et al.
Table 1 Socio-demographic characteristics of respondents in the 13 countries. Australia (n =1360) Brazil (n =1426) Canada (n =1150) Chile (n =1122) China (n =1294) Colombia (n =1237) France (n =1146) India (n =1191) Italy (n =1081) Spain (n =1153) UK (n=,1165) US (n =1150) Uganda (n =1053) Age group (years) 18–29 324 (23.8%) 381 (26.7%) 240 (20.9%) 489 (43.6%) 303 (23.4%) 337 (27.2%) 193 (16.8%) 468 (39.3%) 176 (16.3%) 177 (15.4%) 148 (12.7%) 187 (16.3%) 648 (61.5%) 30–39 252 (18.5%) 307 (21.5%) 207 (18.0%) 185 (16.5%) 418 (32.3%) 336 (27.2%) 143 (12.5%) 468 (39.3%) 174 (16.1%) 199 (17.3%) 193 (16.6%) 229 (19.9%) 313 (29.7%) 40–49 239 (17.6%) 279 (19.6%) 192 (16.7%) 170 (15.2%) 221 (17.1%) 279 (22.6%) 178 (15.5%) 120 (10.1%) 236 (21.8%) 243 (21.1%) 208 (17.9%) 244 (21.2%) 75 (7.1%) 50–59 220 (16.2%) 233 (16.3%) 196 (17.0%) 185 (16.5%) 228 (17.6%) 194 (15.7%) 230 (20.1%) 84 (7.1%) 219 (20.3%) 211 (18.3%) 222 (19.1%) 176 (15.3%) 13 (1.2%) 60–69 197 (14.5%) 187 (13.1%) 189 (16.4%) 80 (7.10%) 94 (7.30%) 74 (6.0%) 298 (26.0%) 42 (3.5%) 228 (21.1%) 264 (22.9%) 246 (21.1%) 195 (17.0%) 4 (0.4%) 70+128 (9.40%) 39 (2.70%) 126 (11.0%) 13 (1.20%) 30 (2.30%) 17 (1.4%) 104 (9.1%) 9 (0.8%) 48 (4.4%) 59 (5.1%) 148 (12.7%) 119 (10.4%) 0% Gender Male 646 (47.4%) 706 (49.5%) 617 (53.6%) 436 (38.9%) 684 (52.7%) 520 (42.0%) 634 (55.3%) 720 (60.4%) 488 (45.1%) 560 (48.6%) 625 (53.6%) 580 (50.4%) 762 (72.4%) Female 715 (52.4%) 713 (50.0%) 528 (45.9%) 679 (60.5%) 610 (47.0%) 709 (57.3%) 507 (44.2%) 468 (39.3%) 590 (54.6%) 591 (51.3%) 536 (46.0%) 565 (49.1%) 265 (25.2%) Chronic health conditions None 601 (45.4%) 610 (44.9%) 535 (48.4%) 504 (45.8%) 897 (70.6%) 762 (63.0%) 583 (53.0%) 505 (44.0%) 570 (54.7%) 560 (49.6%) 590 (51.9%) 397 (35.7%) 631 (62.7%) 1 397 (30.0%) 749 (55.1%) 328 (29.7%) 406 (36.9%) 286 (22.5%) 334 (27.6%) 518 (47.1%) 374 (32.6%) 333 (32%) 401 (35.5%) 325 (28.6%) 376 (33.8%) 324 (32.2%) 2+325 (24.6%) NA 242 (21.9%) 191 (17.4%) 87 (6.9%) 113 (9.4%) NA 268 (23.4%) 139 (13.3%) 169 (15.0%) 221 (19.5%) 340 (30.6%) 51 (5.1%) Education level Primary 244 (17.9%) 251 (17.6%) 58 (5.0%) 12 (1.1%) 290 (22.3%) 185 (15%) 131 (11.4%) 329 (27.6%) 27 (2.5%) 110 (9.5%) 143 (12.3%) 44 (3.8%) 41 (3.9%) Secondary 525 (38.5%) 424 (29.7%) 549 (47.7%) 384 (34.2%) 206 (15.9%) 520 (42.0%) 538 (47.0%) 269 (22.6%) 741 (68.6%) 460 (39.9%) 606 (52.0%) 523 (45.5%) 337 (32.0%) University 575 (42.2% 638 (44.7%) 531 (46.2%) 690 (61.5%) 780 (60.1%) 516 (41.7%) 456 (39.8%) 593 (49.8%) 290 (26.8%) 570 (49.4%) 397 (34.1%) 571 (49.7%) 661 (62.8%) Other 20 (1.5%) 113 (7.9%) 12 (1.0%) 36 (3.2%) 22 (1.7%) 16 (1.3%) 21 (1.8%) 0% 23 (2.1%) 13 (1.1%) 19 (1.6%) 12 (1.0%) 14 (1.3%) Living with a partner No 516 (37.8%) 583 (40.9%) 503 (43.7%) 643 (57.3%) 266 (20.5%) 527 (42.6%) 368 (32.1%) 451 (37.9%) 377 (34.9%) 374 (32.4%) 441 (37.9%) 442 (38.4%) 444 (54.2%) Yes 822 (60.3%) 786 (55.1%) 639 (55.6%) 461 (41.1%) 1025 (79.0%) 679 (54.9%) 760 (66.3%) 733 (61.5%) 675 (62.4%) 761 (66.0%) 713 (61.2%) 702 (61.0%) 344 (42.0%) Australia (n =1360) Brazil (n =1426) Canada (n =1150) Chile (n =1122) China (n =1294) Colombia (n =1237) France (n =1146) India (n =1191) Italy (n =1081) Spain (n =1153) UK (n=,1165) US (n =1150) Uganda (n =1053) Dependent children no 903 (67.2%) 769 (55.2%) 833 (72.9%) 632 (57.0%) 488 (38.0%) 536 (44.2%) 783 (69.2%) 400 (34.7%) 634 (59.8%) 733 (64.4%) 849 (73.3%) 683 (59.9%) 231 (28.8%) Yes 441 (32.8%) 624 (44.8%) 309 (27.1%) 309 (43.0%) 798 (62.1%) 678 (55.9%) 348 (30.8%) 752 (65.3%) 427 (40.3%) 405 (35.6%) 310 (26.8%) 458 (40.1%) 571 (71.2%) Employment status Employed 685 (52.7%) 783 (57.7%) 611 (54.0%) 316 (29.2%) 870 (67.0%) 727 (61.0%) 651 (56.8%) 866 (73.6%) 639 (62.7%) 692 (60.9%) 639 (55.5%) 692 (61.2%) 456 (57.1%) Unemployed 103 (7.9%) 204 (15.0%) 81 (7.2%) 111 (10.3%) 22 (1.7%) 159 (13.4%) NA 64 (5.4%) 125 (12.3%) 157 (13.8%) 78 (6.8%) 66 (5.8%) 283 (35.5%) Pension / Capital Income NA 163 (12.0%) 252 (22.3%) 40 (3.7%) 218 (16.8%) 28 (2.4%) NA 24 (2.0%) 81 (8.0%) 195 (17.2%) 284 (24.7%) 189 (16.7%) 2 (0.3%) Other 513 (39.4%) 207 (15.3%) 188 (16.6%) 616 (56.9%) 188 (14.5%) 277 (23.3%) 495 (43.2%) 222 (18.9%) 174 (17.1%) 93 (8.2%) 150 (13.0%) 183 (16.2%) 57 (7.1%) Political ideology Left 199 (17.5%) 277 (23.7%) 243 (24.3%) 324 (33.6%) NA 224 (21.7%) 206 (24.0%) 62 (5.7%) 233 (26.6%) 419 (40.2%) 210 (21.4%) 202 (20.2%) 171 (18.1%) Centrist 670 (58.9%) 540 (46.2%) 636 (63.5%) 552 (57.3%) NA 607 (58.9%) 488 (56.9%) 520 (48.1%) 452 (51.5%) 497 (47.7%) 629 (64.0%) 462 (46.1%) 564 (59.7%) Right 269 (23.6%) 351 (30.1%) 122 (12.2%) 87 (9.0%) NA 200 (19.4%) 164 (19.1%) 499 (46.2%) 192 (21.9%) 127 (12.2%) 144 (14.7%) 338 (33.7%) 210 (22.2%) Domestic income Bottom 25% 10,573 (7651) 5044 (2366) 14,259 (6526) 78,980 (44,549) 21,232 (8335) 188,354 (95,879) 7771 (2941) NA 4448 (1925) 6024 (2302) 7723 (3345) 10,409 (5222) 638,035 (187,495) 26% 50% 31,400 (4987) 13,949 (2997) 31,535 (4502) 210,507 (43,886) 80,139 (29,255) 510,109 (109,541) 14,695 (1023) NA 10,285 (1347) 12,002 (1676) 16,082 (1820) 27,902 (5421) 1750,493 (424,781) 51% 75% 53,641 (7973) 27,827 (5335) 48,754 (5226) 429,514 (96,377) 151,233 (18,917) 1068,411 (230,295) 22,156 (2050) NA 16,370 (2295) 18,977 (2152) 24,462 (2952) 49,535 (8614) 3886,272 (869,514) Top 25% 142,235 (226,678) 111,844 (110,470) 87,487 (33,548) 1275,219 (1159,727) 318,736 (159,292) 6834,591 (3972,647) 36,264 (10,888) NA 35,357 (20,641) 32,594 (10,273) 45,694 (17,660) 141,790 (41,429) 1.88e+07 (3.81e+07) Note: age expressed in years; domestic income: mean (SD) of quartile in local currency; residual%: other or not specified categories; NA=not available. P. Candio et al.
reflecting the context in which individuals lived (country of origin) and characteristics intrinsic to the person (age, gender and chronic health conditions). Model 2 included model 1 variables as well as education level, whether they lived with a partner and whether they had depen-dent children. Finally, model 3 included model 2 variables and re-spondent’s employment status, political ideology and income level. The proportional odds assumption required by ordered logistic regression was tested using a likelihood ratio test. If this assumption was rejected by the test, partial proportional odds models  were estimated using an autofit procedure. Model selection was based on the AIC / BIC criteria . Using the same approach, logistic regression models were esti-mated to identify predictors of each of the reasons for not getting vaccinated mentioned above. Statistical significance was set at p <0.05. All analyses were performed using STATA 16 software . Our quota sampling approach greatly limited the extent of missing information, hence we applied a complete case analysis approach. 3.Results 3.1.Prevalence Marked disparities in COVID-19 vaccine hesitancy were found across the 13 countries under study. In Brazil, Uganda and India, around two thirds of the population stated that they would “definitely” get a vac-cine, whereas only 15% (95% CI: 12.9 to 17.3) in France, 22% (95% CI: 17.7 to 27.0) in China and 29% (95% CI: 26.5 to 32.2) in Italy would do so. By contrast, France led in the proportion of individuals who said they would “definitely not” get a COVID-19 vaccine at 24% (95% CI: 21.0 to 26.4), followed by the US at 12% (95% CI: 10.0 to 14.4) and Italy at 10% (95% CI: 8.5 to 12.6). The proportion of those who would “probably” get a vaccine ranged between 22% (95% CI: 19.3 to 24.8) in Brazil and 55% (95% CI: 49.5 to 60.5) in China, bringing the combined proportion of individuals with favourable attitudes towards vaccination (i.e., defini-tively or probably accepting) to 85% (95% CI: 82.1 to 86.9) and 77% (95% CI: 71.6 to 81.8) in those two countries, respectively. On the other hand, in France this total only reached 44% (95% CI: 40.8 to 47.0), followed by Italy (62%, 95% CI: 59.2 to 65.3), and the US (64%, 95% CI: 60.6 to 67.1). 3.2.Predictors of vaccine hesitancy 3.2.1.Pooled analysis The between-country disparities described in Fig. 1 are also evident in Table 2 where, compared to the UK, Brazil, Chile, Colombia, India and Uganda showed lower average levels of hesitancy, whereas France, Italy, the US, Spain and Canada showed significantly higher average levels of hesitancy. An older age starting from 50 years old, being diagnosed with a chronic condition and having children were all independently asso-ciated with lower hesitancy levels, relative to the respective reference categories. Women consistently reported greater hesitancy relative to men. While there was some evidence to suggest that those with a primary education were less willing to get a vaccine than those with a university- level education, employment status did not predict attitudes toward vaccination in our survey. We found that belonging to the centre and right sides of the political spectrum was negatively associated with a willingness to get vaccinated compared to the left. However, we also found a non-linear association between income level and vaccine hesi-tancy, whereby the bottom quartile (poorest) in each country were more likely to be hesitant compared to the top 25%, but less or similarly hesitant to the two intermediate categories. Model 3 was selected as providing the best fit based on the AIC / BIC criteria. Except for living with a partner, the likelihood ratio test (i.e., to check for which model variables the proportional odds assumption was not be justified) , failed for all the covariates included in the selected model, meaning that the average coefficients shown in Table 2 were not uniform across hesitancy levels. Results from a partial proportional odds model (Supplementary material, Table A) revealed that the difference observed between the UK and the other four countries where hesitancy levels were lower (Brazil, Chile, Colombia and Uganda) was primarily driven by a positive dif-ference in the proportion of respondents who would probably get vaccinated. In contrast, the higher levels of hesitancy observed for Canada, Italy and Spain were driven by a relatively smaller proportion of that group. In the US, the average higher level of hesitancy shown in Table 2 was primarily driven by a higher proportion of respondents who would “definitely not” get vaccinated. For age, the oldest cohorts ( >70 years old) were consistently less Fig. 1.COVID-19 vaccine hesitancy levels in the 13 countries. P. Candio et al.
likely to be vaccine hesitant, while for the 50–59- and 60–69 years old groups, the overall lower hesitancy was predominantly driven by greater numbers at the lowest levels of hesitancy. We also found that the posi-tive effect of belonging to the political centre (higher hesitancy level) was mainly driven by a lower proportion of respondents who would “definitely” get vaccinated. However, this effect was driven by a higher proportion of those who would “definitely not” be vaccinated amongst those with a right-wing ideology. 3.2.2.Country-level analysis The effects estimated across the 13 countries discussed above were confirmed only in part when we focused on the individual countries (Supplementary material, Table B). While in Australia, France, the UK and Uganda, the negative and broadly linear association previously found between an age above 50 years old and vaccine hesitancy was again observed, and at an even larger magnitude than across the panel, in the remaining countries this was no longer the case. In Brazil and Colombia, being only between 30 and 49 years old was negatively associated with hesitancy, while in the other countries either there was no evidence of age being a predictor or results indicated that an older age was in fact associated with higher levels of vaccine hesitancy, particularly so in the US. Table 2 Predictors of COVID-19 vaccine hesitancy. Vaccine hesitancya Variables Model 1 Model 2 Model 3 Ref: UK В SE β SE β SE Australia 0.238*** 0.086 0.235*** 0.087 0.153 0.102 Brazil 0.594*** 0.101 0.651*** 0.104 0.766*** 0.123 Canada 0.163* 0.085 0.212** 0.086 0.168* 0.097 Chile 0.402*** 0.133 0.393*** 0.126 0.408** 0.173 China 0.821*** 0.1 0.880*** 0.102 – – Colombia 0.411*** 0.105 0.405*** 0.106 0.483*** 0.147 France 1.814*** 0.089 1.932*** 0.089 1.784*** 0.107 India 0.607*** 0.09 0.494*** 0.094 – – Italy 0.961*** 0.088 0.938*** 0.09 0.762*** 0.104 Spain 0.326*** 0.082 0.393*** 0.083 0.379*** 0.096 US 0.827*** 0.097 0.838*** 0.097 0.862*** 0.106 Uganda 0.678*** 0.093 0.708*** 0.105 0.774*** 0.139 Ref: 18–29 years 30–39 0.154*** 0.058 0.044 0.062 0.043 0.079 40–49 0.014 0.063 0.103 0.069 0.024 0.081 50–59 0.194*** 0.063 0.141** 0.068 0.138* 0.081 60–69 0.334*** 0.07 0.316*** 0.075 0.322*** 0.091 70+ 0.743*** 0.104 0.742*** 0.107 0.699*** 0.124 Ref: Male Female 0.398*** 0.04 0.400*** 0.041 0.458*** 0.049 Other 0.38 0.257 0.236 0.271 0.232 0.333 Ref: Healthy N. of health conditions =1 0.181*** 0.046 0.182*** 0.046 0.240*** 0.054 N. of health conditions =2+ 0.345*** 0.063 0.341*** 0.063 0.419*** 0.076 Ref: Primary education Secondary 0.065 0.068 0.086 0.101 University 0.285*** 0.068 0.181* 0.104 Other 0.09 0.154 0.219 0.272 Ref: Living alone Living with a partner (adult) 0.146*** 0.046 0.053 0.055 Don’t know/Prefer not to say 0.432** 0.177 0.455 0.298 ref: no dependent children dependent children 0.144*** 0.048 0.181*** 0.059 Ref: Employed Unemployed 0.07 0.09 Pension/Capital Income 0.044 0.104 Ref: Employed Other 0.012 0.068 Ref: Left political ideology Centre 0.286*** 0.057 Right 0.300*** 0.075 Ref: 0–25% domestic income 26% 50% 0.198** 0.099 51% 75% 0.09 0.111 75% 100% 0.281** 0.114 /cut1 0.078 0.078 0.198* 0.104 0.086 0.164 /cut2 1.516*** 0.081 1.410*** 0.104 1.603*** 0.165 /cut3 2.034*** 0.081 1.931*** 0.104 2.047*** 0.165 /cut4 3.057*** 0.086 2.960*** 0.106 3.014*** 0.168 Observations 14,921 14,543 9235 Note: afive levels, in decreasing order: “definitely get it”; “probably get it”; “do not know”; “probably not get it”; “definitely not get it”). Ordered logistic models. Robust standard errors in parentheses. ***p <0.01,. **p <0.05,. *p <0.1. P. Candio et al. In line with the pooled analysis, being diagnosed with a chronic condition was fairly consistently associated with higher willingness to get a vaccine (except in Brazil and Uganda). Women reported higher levels of hesitancy relative to men, except in China where they were more likely to get a vaccine. Level of education (Australia, Brazil and Chile), living with a partner (Australia and Chile) and having children (Canada, France and Spain) were found to play a role in attitudes toward vaccination only in a minority of countries. Unlike in the pooled model, employment status had a significant effect in five countries. In Chile, China and India being unemployed or receiving some form of income alternative to a salary, including from capital gains or pensions, was positively associated with vaccine hesitancy, while in Canada and the UK the latter category of respondents was more favourable toward getting vaccinated. Political ideology was found to be a predictor of vaccine hesitancy in six countries, with evidence of a positive political gradient (higher hesitancy as we move further to the right) only in Brazil, Canada, Italy and Spain. Finally, in five countries (Australia, France, Spain, the UK and the US) a negative socio-economic gradient in hesitancy was observed. In Canada, only respondents from the top quartile of the in-come distribution were significantly less likely to be hesitant, whereas in Brazil and Uganda the third and top quartiles respectively were signif-icantly more hesitant than those in the lowest quartile. 3.2.3.Reasons for not getting vaccinated Reasons for not getting a vaccine were fairly uniformly distributed across the 13 countries (Supplementary material, Table C), with con-cerns regarding the potential side effects of vaccination against COVID- 19 being consistently the most frequent, from 37.8% (95 CI 33.2–42.6) in India to 67.7% (95 CI 63.4–71.5) in Spain (Supplementary material, Table D). The probability of reporting reasons for not getting vaccinated increased with hesitancy levels, especially those regarding vaccine effectiveness and trust in health care providers. Overall, patterns of heterogeneity differed markedly across countries both in terms of individual beliefs and attitudes toward vaccination against COVID-19 (Supplementary material, Tables E to Q). Worthy of note however, gender seemed to play a consistent role across most countries in terms of its association with specific types of reason for not getting a vaccine. Men were more likely than women to indicate lack of effectiveness (Australia and United Kingdom), no trust in the health care providers (Australia and US), a belief that enough people will be vaccinated to reach herd immunity (Australia, Brazil Canada and US) and that the virus will not be harmful to their health (Australia, Colombia, France and US) as reasons for not getting a vaccine. In Chile only, men were more likely to offer a belief of having been already infected as a reason for not getting vaccinated, whereas in India and Uganda this seemed to be the case for women. By contrast, women were consistently more likely than men to report concerns over the potential side effects in France, Spain, US and Uganda. Evidence for age-dependent patterns for the reasons for not getting a vaccine was found, although less uniformly across countries than for gender. Except for India and Uganda, where age groups were similarly likely to give any of the six specified reasons, in all the remaining 11 countries age was significantly associated with specific reasons. In particular, concerns regarding vaccine effectiveness appeared to be more of an issue for the younger cohorts, compared to respondents aged at least 60 years old, in Australia, Canada, China, France and Italy. Conversely, these concerns were associated with being older in Colombia and Brazil. In all countries except France, age was associated with offering lack of trust in health care providers as a reason for not getting vaccinated, but there was no consistent direction of this associ-ation. In the US, concerns regarding the potential side effects of a vac-cine were particularly prevalent across respondents aged 40 years old or above, whereas a belief of having been already infected was particularly associated with the youngest cohort of 18–29 years old as a reason for not vaccinating. 4.Discussion 4.1.Main findings This study provided a global assessment and multi-country com-parison of the prevalence, predictors and reasons for hesitancy toward vaccination against COVID-19 in the general adult population. We analysed data from the CANDOUR project, which surveyed 13 countries around the world, from high and low and middle-income settings, rep-resenting about half the global population and very diverse social and economic contexts. Overall, like many other studies [23,24,39,40], we found high levels of vaccine hesitancy, particularly amongst high in-come countries, with France leading with almost a quarter of re-spondents saying they would definitely not get vaccinated and less than half who would definitely or probably get vaccinated. Compared to the UK, which appeared to hold a median position in terms of average hesitancy levels, between-country differences were found, in most cases, to be primarily driven by differences in the proportion of those with degrees of indecision about whether or not to get vaccinated. An exception was the US, where respondents who would definitely not get vaccinated were disproportionally represented. We found that the drivers of more extreme hesitancy differed from drivers of more moderate hesitancy. Lack of trust in health care pro-viders was found to play a central role in extreme hesitancy, consistently across the large majority of countries. This may relate to, and be deeply rooted in, a wider lack of trust in public institutions as previously found in comparable research studies [30,31,41]. Although there may not be a quick and simple solution to this broader challenge, we believe that this should be recognized as a major reason for strong hesitancy against COVID-19 vaccination by policymakers and stakeholders trying to develop effective strategies, particularly multi-country interventions and campaigns. To support such endeavours future research should consider how to improve trust in public institutions and in science. Even with Delta and possibly more so with Omicron , it is unfortunately not the case that, as originally hoped, 70–80% of coverage would generate herd immunity and eliminate the threat from COVID . This means that very high levels of coverage will need to be achieved and maintained over time, so the hardest to convince people will remain an issue for the foreseeable future. More moderate hesitancy was also associated with a lack of trust in health care professionals in many countries, but to a lesser degree than in extreme hesitancy, and other factors such as gender and age played a more important role in many countries. Political ideology also played a role, but less consistently across countries and with this effect often being modified by income level, such as in the US where those on the political right at top income levels were similarly hesitant as those on the left side of the political ideology spectrum. Moreover, concerns regarding potential side effects were the most frequent reason for vac-cine hesitancy in all the countries studied. Reasons for not getting vaccinated differed between genders across countries. Hesitant females were generally more motivated by safety concerns, while men were motivated by a belief that herd immunity would be reached, irre-spectively of their behaviour, or that the virus would not be harmful to their personal health. 4.2.Comparison with previous studies Together with a few other studies of this kind, our study has collected data from multiple countries and analysed them using a single meth-odological approach. Our consistent comparative approach facilitates ascertaining whether the heterogeneity in vaccine hesitancy between countries observed across individual country-level assessments stems from actual heterogeneity across countries or simply from different methodological approaches. Our findings align partly with those re-ported in another global survey conducted in 19 countries (n =13,426) in June 2020 which found that, overall, 71.5% of respondents would P. Candio et al. accept a vaccine against COVID-19 and that vaccine acceptance was generally higher in low and middle-income countries . In line with our findings in terms of levels of vaccine acceptance, another survey  conducted in eight Western countries (n =18,231) found France being the most hesitant, with only 45% of respondents being willing to accept a vaccine at the end of 2020, while the UK was amongst the top countries with around three quarters. Both those multi-country studies found an overall negative associa-tion between age and vaccine hesitancy in their pooled analyses. Our results on greater hesitancy amongst females are consistent with Lind-holt et al. (2021)  and a recent meta-analysis . In contrast, Lazarus et al. (2021)  found that men were less likely than women to accept a vaccine. such divergence could be explained by the different groups of countries considered and the way the vaccine hesitancy questions were asked. In fact, in our study we found that women were more hesitant than men primarily in Western countries, while in China – which was included in the study by Lazarus et al. (2021)  - the opposite was the case and in India, Uganda and Brazil no difference was found. However, as mentioned above, differences in data collection and analysis methods make it difficult to identify the real reasons for the observed differences. Interestingly, Lazarus et al. (2021)  included political ideology in their regression models and found it to be significantly associated with vaccine hesitancy, although only in a bivariate analysis. These authors however used a different set of covariates in their fully adjusted model, including conspiracy beliefs and trust in the government, which are likely to moderate the effect of political ideology on hesitancy. We instead found political ideology to interact with income level, which was not included in the analysis by Lindholt et al. (2021) . Nonetheless, the effect of political ideology has been found inconsistent across countries as it is likely to be moderated by what governing party is responsible for tackling the pandemic in each country . 4.3.Strengths and limitations A strength of the CANDOUR survey is that it provides insights into the attitudes and concerns that people held right at a time when the prospect of imminent COVID-19 vaccination was becoming a reality, that is between November and December 2020, but before later public concerns emerged over the safety of specific vaccines. For this reason, the findings from this study provide a valuable baseline of stated pref-erences (i.e., what if a vaccine would be available), which can be compared with actual vaccine uptake levels in the population, particu-larly in countries with advanced vaccine programmes. At the time of writing, in the UK rates of doses administered have been relatively stable since they became available to the public, with double-vaccinated reaching over 90% in the elderly and 75% of the total adult popula-tion . In the US instead, while a steep increase in the number of doses administered has been observed until April 2021, a likewise decrease has also been observed since then , with faltering rates amongst certain subgroups (e.g., over 75 years old) and double-vaccinated reaching 68% of the adult population . In many LMICs, however, distribution of vaccines doses is still only in the early stages  and calls for donation of vaccine doses from high income countries have been made . The present study was limited to a cross-sectional design, and in-dividuals’ attitudes toward vaccination might have changed over time due to a dynamic and changing scenario, especially considering the relatively high levels of vaccine coverage in many countries. Never-theless, longitudinal analyses have shown that attitudes toward vacci-nation remain relatively stable over time especially amongst individuals holding the most extreme views . This makes the heterogeneity analysis presented here a potentially valuable source of information about subgroups to target and communication strategies for health au-thorities around the world. However, the urgency of providing timely and accurate information to public authorities imposed a constraint on the extent and depth of our investigation and analyses, hence limiting the number of dimensions and vaccine hesitancy drivers considered. The CANDOUR survey was designed to investigate attitudes towards a hypothetical vaccine, whereas several vaccines have been developed over the last 12 months. Some of these vaccines have been met with scepticism. For example, evidence of an extremely low possibility of blot clots led to the Oxford AstraZeneca vaccine being temporarily banned from distribution in some countries and restricted for use only by certain age groups in others. Unfortunately, these very low risks have been blown out of proportion in much popular discourse via fearmongering and the spread of conspiracy theories . Plans are currently in place to carry out a series of future CANDOUR survey waves, which will enable future research to better track the dynamics of vaccine hesitancy over time. The CANDOUR study shares the same limitations as other online surveys. Selection bias could have arisen as only individuals who had access to the web and were internet-literate could provide a response. This limits the generalisability of our findings accordingly, especially in countries where that is not the norm for large sections of the population. In addition, data were incomplete for part of the samples and variables (e.g., no income data for India), hence increasing the probability of se-lection bias being induced in our analyses. However, quota sampling strategies were implemented, generating samples that roughly matched the populations on key characteristics (i.e., age, gender, education and region). Furthermore, post-stratification weights were calculated and applied to all the regression models to account for remaining imbal-ances. Nonetheless, unobserved heterogeneity may be present and could not be accounted, especially in LMICs where representativeness was likely more limited . 5.Conclusions COVID-19 vaccine hesitancy is a major challenge for many countries around the world. With the emergence of the more transmissible vari-ants, herd immunity is now unlikely, meaning that there is no threshold beyond which increasing vaccination rates would cease to be valuable. The evidence on vaccine hesitancy provided in this study can help inform the targeting and nature of interventions, such as communication strategies and vaccination incentives, that will be required for life in many countries to safely return to some form of normalcy. Future efforts should focus on monitoring attitudes towards vaccination and identi-fying the degree to which these stated preferences can predict actual behaviour in the population and be modified by interventions such as informational campaigns or incentives. The ongoing pandemic provides public authorities with an opportunity to build trust in institutions upon which public policy crucially hinges, and vaccine literacy which is important for managing the current pandemic, as well as preparing for the next health emergency. Declaration of Competing Interest None. As corresponding author, I confirm that the manuscript has been read and approved for submission by all the named authors. All the authors contributed to the writing of the final manuscript. The research was supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) and the COVID-19 Oxford Vaccine Trial. Mara Violato receives funding from the NIHR Applied Research Collaboration Oxford and Thames Valley at Oxford Health NHS Foundation Trust. Mara Violato and Paolo Candio were partly supported by the NIHR Applied Research Collaboration (ARC) Oxford and Thames Valley. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The funding bodies had no involvement in the study design, in the collection, analysis, and interpretation of the data and the writing of the manuscript. P. Candio et al. Supplementary materials Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.healthpol.2023.104895. References Cutler DM, Summers LH. 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Use APA Standard for CUSON and APA Concise Guide for Undergraduates (2020). Polack, F.P., Thomas, S.J., Kitchin, N., Absalon, J., Gurtman, A., Lockhart, S., Perez, J.L., Marc, G.P., Moreira, E.D., Zerbini, C., Bailey, R., Swanson, K.A., Roychoudoudhury, S., Koury, K., Li, P., Kalina, W.V., Cooper, D., Frenck, R.W., Hammitt, L. L., … Türeci, Ö. (2020). Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine. The New England Journal of Medicine, 383(27), 2603-2615. What is the first author’s background (e.g. nurse or pharmacist, credentials- PhD, DNSc, and current job and organization) that demonstrates their credibility to conduct the study? Are they cited in the references for previously published research? Describe the team involved in this research. Dr. Fernando P. Polack is a reputable Specialist in Pedriatric Infectious Diseases. He is the Casar Milstein Professor of Pediatrics in the Vanderbilt University School of Medicine, a faculty member at the Vanderbilt Vaccine Center, and the Scientific Director of Fundacion INFANT in Buenos Aires, Argentina. Dr. Polack has authored numerous scientific manuscripts in journals, including North England Journal of Medicine, Nature Medicine, Journal of Experimental Medicine, PNAS, and many others. His prestigious research is funded by the Bill & Melinda Gates Foundation and other international organizations. What is/are the research question(s)? State very clearly and precisely. What is the efficacy of the 2 dose regimen of BNT162b2 mRNA Pfizer vaccine against Covid-19 in the 16 years of age and older population? What is the reactogenic profile (local and systemic responses) of the 2 dose regimen of BNT162b2 mRNA Pfizer vaccine in the 16 years of age and older population? Is the 2 dose regimen of BNT162b2 mRNA Covid-19 Pfizer vaccine safe for administration for the 16 years of age and older population? Why is the study important/significant? The study significance is typically discussed in the introduction and first few paragraphs of a research article. Such as, how prevalent the problem is or how it affects patients negatively (e.g. pain). In response to the global crisis of a pandemic that has been caused by Covid-19, safe and effective prophylactic vaccines are desperately needed. The pandemic of Covid-19 has led to world-wide devastating effects such as medical, economic, and social consequences. Older adults, persons with certain coexisting conditions, and front-line workers are at the highest risk of being affected by Covid-19 and its long-term complications. Globally, 110,941,712 individuals have been infected by Covid-19 and there have been 2,456,923 deaths as a result of Covid-19 (“COVID-19 Map,” 2020). The most common immediate symptoms of Covid-19 include fever, new or increased cough, new or increased muscle pain, new loss of taste or smell, sore throat, diarrhea, or vomiting (“COVID-19 (coronavirus): Long-term effects,” 2020). Although Covid-19 is characterized by a presentation of certain symptoms, other individuals infected by Covid-19 are presented asymptomatic. The virus also presents long-term effects on the body. Covid-19 is possible of triggering a long-term inflammatory response within the body that can affect the lungs, heart, and brain, which increases the risk of long-term health issues (“COVID-19 (coronavirus: Long-term effects,” 2020). The public health crisis of Covid-19 has overwhelmed the healthcare system globally. As of February 19th, 2021, 1,730,332 hospitalizations due to Covid-19 have been reported (COVID Data Tracker Weekly Review,” 2021). Not only has the pandemic of Covid-19 caused a dramatic impact in the healthcare system, the pandemic has also impacted the economy and has led to an economic crisis as a result. The pandemic resulted in a spike of 2.5 million Americans seeking employment and these numbers have remained elevated since April of 2020 (Bauer et al., 2020). According to Brookings, “The economic crisis is unprecedented in its scale: the pandemic has created a demand shock, a supply shock, and a financial shock all at once (Bauer, et al., 2020).” The pandemic of Covid-19 has led to a dramatic disruption in the personal lives of many, the healthcare system to become drastically overwhelmed, and created a global economic crisis. Because of the dramatic impact that Covid-19 has had, this research study was necessary in order to discover a safe and effical vaccine that could prevent the further repercussions that individuals have experienced globally due to Covid-19. Review of the literature (ROL) Describe and briefly summarize the research literature and current events that supports conducting this study? Be specific here and cite studies. You are trying to understand and convey why this study was needed and conducted. The review of literature for this article introduced important information regarding the populations most at risk for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), Covid-19, and its complications. Older adults, people with comorbidities, front-line workers, and younger adults have an increased risk of contracting the virus. Due to the rapidly evolving Covid-19 pandemic and its resulting complications within medical, economic, and social domains, there is urgent need for an effective vaccine to be safely administered to the population. Previous clinical trials administering the vaccine candidate BNT162b2 progressed through phase 1 to phase 3 showing promising results. During phase 1 in a clinical trial the initial goal is to test the safety and reactogenicity of the vaccine candidate (Singh & Mehta, 2016). The secondary goal is to collect the immune response data (Singh & Mehta, 2016). BNT162b2 contained the SARS-CoV-2 full-length spike, including a modification by a proline mutation in order to secure it in the prefusion conformation. Studies conducted in the United States and Germany found that two doses of BNT162b2 elicited lofty antibody titers and robust antigen CD8+ and CD4+ T-cell responses. In addition, the local and systemic effects of BNT162b2 represented by the reactogenicity profile were short-term. During phase 2 in a clinical trial the initial goal is to determine the preparation and optimal dose of the vaccine (Singh & Mehta, 2016). The secondary goal is to further test safety, immunogenicity, and efficacy end-points (Singh & Mehta, 2016). Vaccine immunogenicity refers to the ability of a vaccine to elicit an immune response (Banaszkiewicz & Radzikowski, 2013). Due to phase 2 not being directly mentioned in this research article it is presumed that the BNT162b2 vaccine candidate progressed into phase 3 with ease. During phase 3 in a clinical trial the vaccine safety and efficacy are evaluated (Singh and Mehta, 2016). There is an assessment of the effects of the final formulation of the vaccine (Singh & Mehta, 2016). What gap in knowledge is there in the research literature that supports the need for this study? The gap in knowledge in the research literature is the discussion of the safety, efficacy, and immunogenicity of the two doses of BNT162b2 vaccine candidate in preventing Covid-19 in the population of 16 years of age and older. Due to the rapidly evolving pandemic the need for this study is meant to provide research-based evidence for emergency authorization of the use of the vaccine candidate. This research article is meant to review the findings from phase 2/3 of the clinical trials. Collection of data during these phases are ongoing concerning the vaccine’s immunogenicity and immune response durability. Methods– this is the plan for the study/ how it was conducted. The methods are described after the introduction. Describe the study design that aims to answer the research question(s). These are the broad research design terms and there may be several different descriptors for one study. For example, a qualitative study may use focus groups or a quantitative study may use a survey and clinical data (e.g. blood pressure) to answer the research question(s). The authors typically state the study design, such as a “randomized controlled trial” was used for this study to answer the research questions. Define each study design term. The study design is a multinational, placebo-controlled, observer-blinded, efficacy clinical trial. It can be considered a randomized controlled trial (RCT) in which the trial assesses reactogenicity and immunogenicity of the vaccine candidate BNT162b2. The trial was also assessing the safety and efficacy of BNT162b2. A placebo-controlled study design is when there are two groups where one receives the vaccine and the other receives the placebo. In this study everything else is the same between the groups in order to reduce influence from confounding variables (“Placebo-Controlled Trials,” 2021). An observer-blinded study design is when the site staff administering the vaccine does not know if the participant is receiving the vaccine or the placebo (Schmidt, 2019). A RCT is an experimental study that normally involves large samples and is conducted at multiple sites (Schmidt, 2019). The three criteria the study met to be considered a RCT was randomization, control, and manipulation (Schmidt, 2019). The RCT included a total of 43,548 participants that were 16 years and older across 152 sites worldwide. At these individual sites, the participants were randomized for the study. Randomization into the treatment and control groups was done with an interactive Web-based system. The participants were randomly assigned in a 1:1 ratio to receive the vaccine or the placebo. The participants were administered either the two doses of BNT162b2 or the placebo, intramuscularly in the deltoid, 21 days apart. An independent variable is the variable that influences the dependent variable (Schmidt, 2019). The independent variable of this study was the BNT162b2 vaccine. A dependent variable is the outcome that is influenced by the independent variable (Schmidt, 2019). Dependent variables of this study included the safety and efficacy of the vaccine. Vaccine safety is when the disease is significantly greater a threat than the means of protecting against the said disease (Offit, 2020). Vaccine efficacy is the percent reduction of disease among the vaccinated population (Singh & Mehta, 2016). The safety of the BNT162b2 vaccine was determined by utilizing multiple data collection analyses. One way safety was determined was through the assessment of any reaction from the participants by the site staff at the time of vaccine administration. Another way was through the reporting of any reaction and/or adverse event by the participants in the provided electronic diary. The efficacy of the BNT162b2 vaccine was determined by the end-points of the clinical trial. This included that there was no evidence of infection within 7 days after receiving the second dose of the vaccine or the placebo. It also included that there were no participants that had no protocol deviations resulting in leaving the clinical trial. The vaccine efficacy was calculated by 100✕(1-IRR). IRR represents the calculated ratio of the confirmed Covid-19 cases per 1000 persons. A confounding variable is any extraneous variable that interferes with the relationship of the independent and dependent variables (Schmidt, 2019). The confounding variables of this study included age, ethnicity, missing data, comorbidities, and reasons why participants had to leave the clinical trial. Describe the setting or place in which the study was conducted. This may include a state, or part of the country, a hospital, a department or clinic. Be as descriptive as possible, describing where the study participants engaged in the study. An example may be a “large academic emergency room in the northeast US”. The study was conducted at 152 sites worldwide. The United States included 130 sites. Argentina included 1 site. Brazil included 2 sites. South Africa included 4 sites. Germany included 6 sites. Turkey included 9 sites. Describe the study sample (study participants) and how the researcher recruited or obtained the study sample. What were the inclusion criteria for the study participants? What were the exclusion criteria for the study participants? The study sample occurred between July 27, 2020 and November 14, 2020. In total, 44,820 participants were screened at the 152 sites. After the completion of screening, 43,548 of these participants were randomly assigned to the treatment or control group. Among these participants, 43,448 received injections. These participants were divided to receive BNT162b2 (21,720 persons) or receive a placebo (21,728 persons). By October 9, 2020, the data cut-off date, there were a total of 37,706 participants who provided safety data after the second dose. This data contributed to the safety data set the research team formulated. The researchers obtained the study sample through volunteerism. At the 152 sites, the individual site staff would educate regularly-attending clients, who met the inclusion and exclusion criteria, about the clinical trial. Through the education about the clinical trial, the clients could then volunteer to be a part of the clinical trial. Inclusion criteria provides the key features of the participants that the researchers want to ensure are included in their study sample (Patino, 2018). Exclusion criteria provides the features of the participants that could interfere with the desired outcome of the research (Patino, 2018). The research study team recruited the study sample with inclusion and exclusion criteria. The inclusion criteria for the study: Adults 16 years of age and older. Persons were healthy or had stable chronic medical conditions including (not limited to): Human immunodeficiency virus (HIV). Hepatitis B virus. Hepatitis C virus. The exclusion criteria for the study: Previous Covid-19 infection. Immunosuppressive therapy treatment. Diagnosis of an immunocompromising condition. Describe the steps to how data was collected – include all the specific steps in collecting the data for the study such that you could use these steps to replicate the study as best possible from what is published. Pfizer was responsible for the data collection and BioNTech contributed to the data interpretation. The research article states that data was collected in a quantitative manner. The data that was collected included local and systemic reactions (reactogenicity), and any adverse events the participants had following the two doses of the vaccine. Safety data was collected as counts, percentages, and Clopper-Pearson 95% confidence intervals. The steps of the study included: IRB approval for this research study was obtained. Consent forms for the study participants were given and collected. Participants are tested for serum antibodies indicating past Covid-19 infection before their first administration of the vaccine. Previous Covid-19 infection is an exclusion criteria. Randomization of participants into the active vaccine and placebo groups was utilized. The first assessment of reaction was performed by site staff within 30 minutes after administration of the first dose. The site staff was blinded to whether the participant was receiving the vaccine or the placebo. The site staff performed the administration of the vaccine intramuscularly (deltoid). The site staff explained to the participants how to record their experiences in an electronic diary provided for them throughout the clinical trial. The participants recorded any reactogenic and/or adverse events they experienced. Participants were tested for Covid-19 during this first visit. Researchers required follow-up visits one day and one week after the first vaccination in order to collect data on how the participants were doing. The second assessment of reaction was performed by site staff within 30 minutes after administration of the second dose. The site staff performed the administration of the vaccine intramuscularly (deltoid). Researchers required follow-up appointments one and two weeks after the second vaccination in order to collect data on how the participants were doing. The data was collected from the follow-up appointments and the participants' recordings in their individual electronic diary. After the second dose administration, the researcher contacted the participants who were in the placebo group. They notified the participants to inform them of which group they were in so they could receive the active vaccine when it was available for administration. This interferes with data collection pertaining to the placebo group because ethically these participants must be provided the active vaccine. Researchers will require the participants to have follow-up appointments for up to 24 months after the administration of the second vaccination. The data will be collected from the follow-up appointments and the participants' recordings in their electronic diary. What instruments or tools were used to collect data? Name and describe every instrument, survey tool, clinical data or other that was used in this research project. Describe what each measures and include reliability and validity data reported. The study design included an electronic diary in which participants recorded their experiences during the clinical trial. The participants were either prompted to record (solicited), or recorded without a prompt (unsolicited). Standard thermometers were provided to the participants. When and how reactions were assessed/reported: Within 30 minutes after administration of each dose by site staff. Within 7 days after receiving each dose (solicited). Any reactogenic and/or adverse events. Any use of pain and/or antipyretic medication. 14 weeks after receiving the second dose. For this article adverse events were recorded up to this date. Will be recorded through 1 month after receiving the second dose (unsolicited). Will be recorded through 6 months after receiving the second dose (unsolicited). There were multiple statistical instruments utilized to collect data. Such as: Clopper-Pearson 95% confidence intervals were used to collect local and systemic reactions, and adverse events the participants had following the vaccination. This was based upon the terms presented in version 23.1 of the Medical Dictionary for Regulatory Activities (MedDRA). Vaccine efficacy was calculated by 100✕(1-IRR). IRR represents the calculated ratio of the confirmed Covid-19 cases per 1000 persons. This was compared between the active vaccine group and placebo group. Bayesian beta-binomial model was used to calculate the 95.0% credible interval for vaccine efficacy. When performing the final analysis, a success boundary of 98.6% was used. The success boundary of 98.6% was utilized to analyze the probability of vaccine efficacy to control the overall type 1 error rate and to compensate for the noted interim analysis. Results – after the study was conducted, who participated and what were the results or findings Describe the characteristics of the sample – who participated? How many? Description of the participants such as gender, age, diagnosis, and other relevant characteristics that allowed them to be in the study Between July 27th, 2020, and November 14th, 2020, a total of 43,548 persons, 16 years of age or older, worldwide underwent screening and randomization at 152 sites. On October 9th, a total of 37,706 participants provided an average of at least two months of safety data available after receiving the second dose of the vaccine. The safety data collected by the 37,706 participants contributed to the main safety data set for this research study. Among these 37,706 participants, 49% were female, 83% were White Causasian, 9% were Black or African American, 28% were Hispanic or Latinx, 35% were obese, and 21% had at least one coexisting medical condition. The average age of the participants was 52 years, and 42% of participants were older than 55 years of age. Describe the main findings – what were the answers to the research question(s). What did the researchers find? Best to list the research questions and its answer together to completely answer the question(s). What is the efficacy of the 2 dose regimen of BNT162b2 mRNA Pfizer vaccine against Covid-19 in the 16 years of age and older population? The 2 dose regimen of BNT162b2 vaccine was found to be 95% effective against Covid-19. The results met the research study’s prespecified success criteria, which were to establish a probability above 98.6% of true vaccine efficacy being greater than 30% and exceeding the minimum FDA criteria for authorization. During the analysis of the subgroups in which more than 10 cases of Covid-19 Discussion occurred, the lower limit of the 95% confidence interval for efficacy was more than 30%. What is the reactogenic profile (local and systemic responses) of the 2 dose regimen of BNT162b2 mRNA Covid-19 Pfizer vaccine in the 16 years of age and older population? The favorable safety profile of BNT162b2 was observed in phase 1 testing and was confirmed in the phase ⅔ portion of the trial. As in phase 1, the reactogenicity was generally mild or moderate, and reactions were less common and milder in older adults than in younger adults. During the study, systemic reactogenicity was found more common and severe after the second dose than after the first dose of the vaccine. The local reactogenicity was found to be similar after the two doses of the vaccine. Severe fatigue was observed in approximately 4% of the vaccine recipients, which demonstrates a higher prevalence than that observed in recipients of some vaccines recommended for older adults.Overall, from the analysis of the results, the reactogenicity events were transient and resolved within a few days of onset. Is the 2 dose regimen of BNT162b2 mRNA Covid-19 Pfizer vaccine safe for administration for the 16 years of age and older population? The results of this study demonstrate that the BNT162b2 vaccine is effective in creating immunity against Covid-19, while also exceeding the minimum FDA criteria for authorization for administration to the 16 years of age and older population. The adverse events presented during the study did not present a concern for withholding vaccine administration to the public and demonstrated substantial and proportionate data to support the safety of the BNT162b2 vaccine. What were the study strengths? limitations? Identified by the authors and perhaps others that you identify. Study strengths: This research study provided a large sample for research due to the urgency and impact of the necessity for immunization against Covid-19. Supplement analyses were provided in this research study among diverse subgroups defined by age, sex, race, ethnicity, obesity, and presence of a coexisting condition in determining the overall safety and efficacy of the BNT162b2 vaccine. This inclusion of a diverse sample found in this study was provided by the quantity and diversity of available testing sites globally utilized for the research study. The research plan involves a continual plan of safety monitoring for two years after the administration of the second dose of the BNT162b2 vaccine. The study’s sample provided a substantial equivalence of both male and female participants to be followed in the study. This research provided effective randomization of the study’s sample designated at the 152 testing sites located globally. Standardization of key elements between the vaccine trials was utilized for this research study’s analyses to provide comprehensive and effective data. This research study provided inclusion for all participants in the safety assessment. The results of this study provided evidence that Covid-19 can be prevented by immunization. Data collected from this study provided proof of the concept that RNA-based vaccines are a promising alternative for protecting individuals against infection. This research study demonstrated the speed with which an RNA-based vaccine can be developed with a sufficient investment of resources available. The development of the BNT162b2 vaccine was initiated on January 10th, 2020, and in less than 11 months later, demonstrations of safety and efficacy were provided for this vaccine. This study provides evidence that RNA-based vaccines can be utilized as a major new tool to combat pandemics and other infectious disease outbreaks. The continuous phase 1/2/3 trial design of this research study can provide a model to reduce the protracted development timelines that have delayed the availability of vaccines against other infection of medical significance. This research data contributes to the evidence needed to approve the BNT162b2 vaccine for public administration. Study limitations: This research study did not include younger adolescents (12 to 15 years old), children, and pregnant women in their sample. Special risk groups were not included in this study’s sample. Participants that had been infected with Covid-19 prior to this study were excluded. Although the study provided data to support the BNT162b2 vaccine high efficacy and had a low number of vaccine breakthrough cases, a correlate of protection was not established during this study. A correlate of protection determines the extent of vaccine-induced immunity provided against the specific infection that the vaccine is given to prevent (Plotkin, 2010). The research data did not address whether the BNT162b2 vaccine prevents asymptomatic infection. The research data did not address the BNT162b2 vaccine’s developed immune response after just one dose of the vaccine. The testing in this study did not determine whether the current cold storage requirements for the BNT162b2 vaccine may be alleviated or altered without interfering with the safety and or efficacy of the vaccine. The study’s sample did not provide a large diverse population of represented minorities in comparison with the white caucasian population represented in the study. The research data did not address potential drug interactions with the BNT162b2 vaccine that could affect the efficacy and or safety of the vaccine. Although this particular study was designed to follow participants for safety and efficacy for two years after the second dose of the vaccine, researchers are ethically unable to collect data of the placebo participants for two years without offering active immunization provided by the vaccine. This limitation is due to the ethical and practical barriers that are present given high BNT162b2 vaccine efficacy supported by this study’s data. With this limitation, the assessment of long-term safety and efficacy for this vaccine will not be provided in the context of maintaining a placebo group for the planned follow-up period of two years after the second dose of the vaccine. The occurrence of adverse events more than two to three and half months following the administration of the second dose of the BNT162b2 vaccine remained to be determined in the continual two year period of this research study plan. Although this study provided a high vaccine efficacy, comprehensive information on the duration of the BNT162b2 vaccine’s protection remains to be determined. What are the implications of the study evidence for nursing practice? Describe how we might use the findings in clinical care and teaching? What resources would you suggest for your patients and families? The implications of the study evidence for nursing practice provide research data to support the advocacy of administering the BNT162b2 vaccine in order to develop immunity against Covid-19, an infectious disease that has devastated millions globally. Nurses will play an important role in the administration of the Covid-19 vaccine. A responsibility of a nurse is to provide safe and effective care to their patients. This research study provides substantial evidence to support the safety and efficacy of the BNT162b2 vaccine in individuals that are 16 years of age or older. Vaccine apprehension has increased dramatically among individuals during the Covid-19 pandemic. Nurses will need to acknowledge vaccine apprehension and provide education for these patients to help alleviate their concerns and provide them sufficient information that patients may make educated decisions that will benefit their overall health and well-being. Safety and efficacy of the BNT162b2 is a concern to the general public population and the research data collected in this study can be used in clinical care and teaching can be used to educate patients on the common known side effects of the vaccine and immunization that the vaccine has against Covid-19. In addition to the research data provided in this study, the Centers for Disease Control and Prevent, the World Health Organization, the U.S. National Library of Medicine, and the U.S. National Institutes of Health are all reliable resources that should be suggested to patients for additional education about Covid-19 and the Covid-19 vaccine options. What are the implications for future medical or nursing research? Would you replicate the study? How so? Perhaps with a different population? What would you do to improve the study next time? This particular research study provided evidence to support the concept that RNA-based vaccines are a promising new approach for protecting individuals against infectious diseases. This study also demonstrated the speed with which an RNA-based vaccine can be developed with a sufficient investment of resources. With this substantial evidence provided in this study, future medical or nursing research can be implicated in enhancing the development of RNA-based vaccines to be used as a major tool to combat pandemics, other infectious disease outbreaks, and prominent infectious diseases of general health concern. This study provided comprehensive data to support the public usage of the BNT162b2 vaccine to develop immunity against Covid-19 in individuals of 16 years of age and older. In the future potential replication of this study, it would be necessary for the study to have an inclusion of children, younger adolescents (12-15 years of age), and pregnant and breastfeeding women in the study’s sample. Due to evidence from this study that supports the safety and high efficacy of the BNT162b2 vaccine, future research studies should be conducted to collect additional data and determine the BNT162b2 vaccine’s efficacy and safety in these certain populations that were either excluded from this study. Minority groups were not provided with a proportional representation in this study. In future research, it would be beneficial to include a more proportionate representation of minority groups due the increased prominence of vaccine apprehension present in minority groups (Doubek & Greene, 2020). Another improvement for future research would be to include participants that have been infected with Covid-19 prior to the administration of the BNT162b2 vaccine. By involving inclusion of these particular populations in a future research study, vaccine apprehension can be potentially reduced, more of the global population can be provided with protection against Covid-19, and there can be a continual effort towards achieving world-wide herd immunity against the infectious disease of Covid-19. References Banaszkiewicz, A., & Radzikowski, A. (2013, November 7). Efficacy, effectiveness, immunogenicity - are not the same in vaccinology. NCBI. . Bauer, L., Broady, K. E., Edelberg, W., & O'Donnell, J. (2021, February 2). Ten facts about COVID-19 and the U.S. economy. Brookings. COVID-19 (coronavirus): Long-term effects. (2020, November 17). COVID-19 (coronavirus): Long-term effects. Mayo Clinic. . COVID-19 Map. (2020). Johns Hopkins Coronavirus Resource Center. https://coronavirus.jhu.edu/map.html. COVID Data Tracker Weekly Review. (2021). Centers for Disease Control and Prevention. Doubek, J., & Greene, D. (2020, November 24). Black People Are More Hesitant About A Vaccine. A Leading Nurse Wants To Change That. NPR. .npr.or le-are-more-hesitant-about-a-vaccine-a-leading-nurse-wants-to-change-t. Fernando P. Polack. CIPP XVI 16th International Congress of Pediatric Pulmonary. . Offit, P. (2020, May 19). Vaccine Safety: Are Vaccines Safe? Children’s Hospital of Philadelphia. cines-safe#:%7E:text=Vaccine%20Education%20Center&text=The%20first%20definitio n%20of%20the,at%20the%20site%20of%20injection. Patino, C., & Ferreira, J. (2018). Inclusion and exclusion criteria in research studies: definitions and why they matter. PubMed Central (PMC). ia%20are%20defined%20as,%2C%20clinical%2C%20and%20geographic%20characteri stics. Placebo-Controlled Trials. Massachusetts General Hospital. (2021). Plotkin, S. A. (2010, July). Correlates of protection induced by vaccination. Clinical and vaccine Schmidt, N. A., & Brown, J. M. (2019). Evidence-Based Practice for Nurses: Appraisal and Application of Research (4th ed.). Jones & Bartlett Learning. Singh, K., & Mehta, S. (2016). The clinical development process for a novel preventive vaccine: An overview. PubMed Central (PMC).