CLAIM
New paper suggests Covid mRNA vaccination rates are linked to increases in overall deaths
DETAILS
Misrepresents source: The preprint used to support the claim investigated the correlation between the distribution of mortality across Dutch cities and COVID-19 vaccination coverage. However, Berenson presented some numerical results as if it were an increase in overall mortality. Furthermore, this numerical result wasnt adjusted for possible bias. Inadequate support: The preprint used to support the claim used city-level data and not individual-level data which precludes drawing conclusions on the impact of vaccination on the risk of dying. Furthermore, all possible confounding factors arent accounted for, which may bias the final results.
KEY TAKE AWAY
COVID-19 vaccines have been tested in several large clinical trials. Their effectiveness largely outweigh the risk of rare side effects. A study comparing vaccination coverage and all-cause mortality in Dutch cities doesnt show that COVID-19 vaccines increase the risk of dying. The studys design is not appropriate to draw such a conclusion.
REVIEW More than 80% of the Dutch population over 12 has been vaccinated against COVID-19, as of August 2022. Large clinical trials and ongoing monitoring of the millions vaccinated worldwide show that COVID-19 vaccines effectiveness largely outweigh the risks of rare side effects and effectively protect against severe forms of the disease.
However, inaccurate claims that these vaccines are dangerous, increase the risk of death, or weaken the immune system frequently circulated on social media, and Health Feedback already debunked several of them.
Journalist Alex Berenson made such a claim in July 2022 when he stated on Substack that new results suggested Covid mRNA vaccination rates are linked to increases in overall deaths. Berenson had made multiple inaccurate and misleading claims about COVID-19 and vaccines that Health Feedback previously debunked.
In his article from 28 July 2022, Berenson reported on a preprint (a study not yet peer-reviewed or accepted by a journal) published by Andr Redert, who previously worked as a researcher in computing sciences but is not trained in virology, immunology, or epidemiology. In that preprint, Redert compared the all-cause mortality and vaccination coverage in Dutch cities.
Although Berenson acknowledged that the preprint doesnt demonstrate that vaccination caused an increase in all-cause mortality, this is implied by the Substack articles headline. Berenson also combined his take on Rederts preprint with observations of increased all-cause mortality in highly vaccinated countries. Regardless of whether this last statement is accurate, it is clear that Berensons subtext is that mRNA vaccination causes an increase in mortality. The readers comments section at the bottom of the article clearly shows that this is how his article is interpreted.
As we explain below, however, Berensons interpretation is incorrect and based on a flawed interpretation of the preprints results. Rederts preprint itself suffers from limitations that weaken the conclusions that can be made about vaccine safety.
In his paper, Redert looked at the distribution of mortality and vaccination coverage between Dutch cities. Some cities presented an all-cause mortality above average, and others, below. Similarly, some cities had vaccination coverage above the national average and other cities below. Redert then tried to determine if there was a correlation between the two and, if so, what proportion of the mortality was distributed across cities in the same way as vaccination coverage. In other words, Redert asked to what extent a city with an above average vaccination coverage would see its all-cause mortality also rise above average or, conversely, drop below average.
Redert observed that the weekly mortality partially correlated with vaccine coverage. In other words, cities with an all-cause mortality above average tended to also exhibit vaccination coverage above average.
However, it is important to stress that Rederts preprint only established correlations between vaccination coverage and mortality, and didnt demonstrate any causal association. Correlation by itself doesnt prove that one event is the cause of another. Rederts preprint also doesnt provide any biological explanation or medical evidence showing that vaccination increases the likelihood of dying.
Furthermore, Redert used city-level data: all-cause mortality and vaccination coverage in that same city. Drawing conclusions on the risk of individuals dying from average data obtained at the city level is known as an ecological fallacy. In our case, city-level data tell us nothing as to whether vaccinated people were overrepresented among those who died, for instance.
Therefore, data from Rederts preprint arent suitable to support Berensons suggestion that vaccination is linked to an increase in all-cause mortality.
In his account of Rederts preprint, Berenson misinterpreted some of the results and used them to draw ill-founded conclusions.
Redert provided the example of a given week where 5% of the total 4,000 deaths from all causes of that weekthat is, 200 deathswere distributed between cities in the same way the vaccination coverage was. The remaining 3,800 deaths were distributed across cities in a manner uncorrelated with vaccination coverage.
Berenson apparently interpreted this 5% of vaccination-correlated mortality as an increase in the total number of deaths, because he also claimed that his 5% figure was consistent with other data reporting a 5% excess mortality in several countries. He then went on to comment that a 5% increase would actually represent many more dead people in the long run.
However, Berensons interpretation of this piece of data is erroneous. This 5% figure from Rederts preprint is not related to the number of all-cause deaths that Berenson cited. Rederts analysis focused on the distribution of deaths across all cities, not on the total number of deaths. In fact, Redert warned: These [5% deaths] are not 200 additional deaths related to vaccination, it means that 200 out of 4k deaths were distributed over municipalities in the same pattern as vaccination coverage.
Also, this 5% figure is the result of Rederts analysis for one weekweek 50 of 2021used as an example and isnt necessarily representative of the entire pandemic, contrary to what Berenson suggested.
Third, many confounding factors bias the direct comparison of all-cause mortality and vaccination coverage. Confounding factors are variables that affect the outcome of an experiment, but arent the variables being studied. If scientists dont factor in the influence of confounding factors in their study, they may draw erroneous conclusions about causality. For example, older people are more likely to get vaccinated against COVID-19 and to die from any cause. Therefore, one would expect that cities with an older population will exhibit a higher than average vaccination coverage and a higher all-cause mortality without any causal association between the two.
Redert was well aware of these confounding factors and proposed a way to take them into account by normalizing his results to pre-pandemic mortality data. However, this 5% figure Berenson extracted from the preprint comes from the raw data and not from the normalized data adjusted for confounding factors. Considering all the above, it is clear that Berensons take on Rederts paper is thus flawed and his conclusions are inaccurate.
Even when considering the adjustments for confounding factors proposed by Redert, the studys design limits what can be concluded from it.
First, Redert used weekly mortality data, but these data were compared with the final vaccination coverage of November 2021. In order to really compare if the mortality correlated with the vaccination coverage, at least partially, it would be better to use mortality and vaccination coverage data from the same week. Given that the study aimed to investigate whether vaccination impacted all-cause mortality, one could even imagine comparing the mortality of a given week with the vaccination coverage of an earlier time period, but not with the final vaccine coverage.
Second, Redert took into account some important confounding factors by normalizing his results by the mortality in 2019, before the COVID-19 pandemic. While this can correct confounding factors due to demographic, such as age or wealth, it would not correct for any other possible confounding factors that would affect both all-cause mortality and vaccine coverage during the pandemic. For instance, we can hypothesize that cities heavily impacted by COVID-19 will tend to vaccinate more, resulting in higher vaccination coverage, but at the same time would suffer from greater disruption to vital elements such as transport and healthcare that could worsen all-cause mortality.
Berenson incorrectly suggests that COVID-19 vaccination can increase all-cause mortality based on the results from a non-peer-reviewed publication. However, Berensons interpretation of the publication is flawed. Furthermore, several limitations in the design of the study itself make it impossible to draw conclusions from the results. By contrast, large clinical trials, as well as the millions vaccinated against COVID-19 in real-world conditions show that COVID-19 vaccines benefits largely outweigh their risks.
See original here:
Effectiveness of BNT162b2 Vaccine against Omicron in Children 5 to 11 Years of Age | NEJM nejm.org
Link:
Effectiveness of BNT162b2 Vaccine against Omicron in Children 5 to 11 Years of Age | NEJM - nejm.org
A recent article published inCell Reports Medicine demonstrated that Bacillus Calmette-Guerin (BCG) vaccinations might offer a platform for protection against emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and other pathogenic infections in type 1 diabetics.
During the past 17 years, randomized clinical studies and epidemiological investigations showed that the BCG vaccine against tuberculosis protected people from numerous infections, such as upper respiratory tract infections, malaria, leprosy, bacterial, and viral infections. Additionally, the BCG vaccine might safeguard humans from immunological disorders like multiple sclerosis and type 1 diabetes.
There is a demand for effective and safe platform vaccines to immunize against SARS-CoV-2 infection and other contagious pathogens. As the SARS-CoV-2 pandemic got underway, epidemiological studies started to find a link between neonatal BCG vaccination and lower coronavirus disease 2019 (COVID-19) mortality and morbidity, even in elderly adults decades following the standard newborn vaccinations on a nation-by-nation basis. On the contrary, several global groups with various neonatal exposures, BCG strains, and other communities did not exhibit these benefits.
Since adults or newborns have never received the BCG vaccine in the United States (US), a randomized study of BCG for potential COVID-19 protection provides a clear comparison in a vaccine-naive US adult population.
In the current placebo-controlled, double-blinded, randomized phase II/III research, the scientists assessed the efficacy and safety of the multi-dose BCG vaccinations for preventing COVID-19 and other infectious illnesses in a SARS-CoV-2-unvaccinated, high-risk-community-based group, over 15 months, from 1 January 2020 to April 2021.
The authors aimed to discover whether the BCG vaccine would provide a platform vaccine approach to safeguard against a wide range of infectious diseases, such as SARS-CoV-2 infection in the at-risk population.
Type 1 diabetic adults were considered the high-risk group in the study. The team recruited 144 participants and randomly assigned 48 to placebo and 96 to BCG arms. Further, no volunteers dropped out during the 15-month research.
The present parallel trial was derived from an ongoing randomized, double-blinded study of BCG for treating long-established adult type 1 diabetes. Therefore, all participants were fully immunized with three BCG or placebo vaccinations at the SARS-CoV-2 pandemic onset in the US on 1 January 2020.
The study results indicated that, contrary toantigen-specific COVID-19 vaccinations, no participants experienced any systemic side effects from BCG during the vaccination period. Localized skin reactions are a known side effect of the BCG vaccine and typically start between two and four weeks after vaccination. No excessive local responses were documented as adverse reactions. Notably, other SARS-CoV-2 vaccinations were not yet available during the timespan of the trial and had no impact on the research.
The BCG vaccine was 92% effective against SARS-CoV-2 infection, with a cumulative incidence of 1% of BCG-treated subjects and 12.5% of placebo-treated volunteers meeting the criteria for confirmed COVID-19 diagnosis based on symptoms and positive serologies. Besides, the team discovered no polymerase chain reaction (PCR)-positive symptomatic subjects in the BCG arm, i.e., 0%, compared to five symptomatic, PCR-positive participants in the placebo cohort, i.e., 10.4%.
If only the PCR data were regarded, these results demonstrated 100% efficacy for the BCG vaccine against SARS-CoV-2 infection at 0.99 posterior probability. In addition, there were no SARS-CoV-2-related deaths in either the placebo group or the BCG group.
The researchers noted that excluding the COVID-19 viral epitope II, practically all SARS-CoV-2 domains included in the heatmap comparisons exhibited anoticeably greater cumulation of antibody reactivity in the placebo cohort relative to the BCG arm. Besides, BCG vaccination decreased the duration and severity of all infectious illness symptoms versus the placebo group.
Moreover, the study data showed that all infectious illness symptoms of BCG recipients were similar to or less severe than those of their household members. On the other hand, relative to their household members, most placebo participants experienced a more severe illness. BCG recipients typically felt mildersymptoms than placebo recipients or non-diabetic householdcontrols.
In conclusion, the study illustrated that the BCG vaccine offers efficient protection against COVID-19 and comprehensive protection against other infectious diseases in type 1 diabetic adults in the US.
The study findings also depicted that the BCG vaccination was efficient, safe, cost-effective, and perhaps protective against the constantly evolving SARS-CoV-2 strain of the COVID-19 pandemic, given its extensive protection against other infections. The authors mentioned that although the efficacy of the BCG vaccine requires one to two years to manifest, the immunity might last decades.
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Shares of COVID-19 vaccine maker Novavax cratered Tuesday as the U.S. biotech company slashed its sales forecast due to a slump in demand for its shots. The company's stock dived 31% after it cut its 2022 sales outlook in half.
Novavax's protein-based vaccine was a latecomer to the market. It was authorized by the Food and Drug Administration for use by adults in the U.S. onlylast month, long after a majority of adults had already been vaccinated with Pfizer, Moderna or Johnson & Johnson shots. Only 7,381 Novavax vaccine doses have been administered in the U.S., government data shows.
The company alluded to softening demand for the COVID-19 vaccine in its earnings call Monday. Novavax CEO Stanley Erck said that hurdles in getting approval to administer booster shots and first doses to younger Americans have also hurt sales, as these applications are the company's best bet for finding a market.
The Novavax COVID-19 vaccine has not been authorized by the FDA for use as a booster vaccination.
"Receiving booster and adolescent label expansions globally has taken longer than expected, and expanding our label is our core commercial priority. When coupled with global oversupply, this drove a shift in demand for our vaccine from the second quarter into the second half of the year and into 2023," Erck said in the call.
Novavax does not expect any additional revenue through Covax, an international alliance aimed at ensuring vaccine equity by delivering doses to low- and middle-income countries. The company had expected to sell 350 millions shots through the partnership.
Wall Street analyst Adam Crisafulli of Vital Knowledge highlighted Novavax's earnings miss. Revenue for the second quarter came in at $186 million, versus Wall Street forecasts of $975 million.
Novavax slashed its full-year earnings guidance to $2 billion to $2.3 billion, from a previous estimate of $4 billion to $5 billion.
"It's just an issue of earnings and guidance. The report last night was pretty disappointing and the guidance was slashed significantly. From a bigger-picture perspective, there's a sense that the COVID opportunity is diminishing overall while Novavax just came out of the gate too far behind the mRNA products," Crisafulli told CBS MoneyWatch.
View post:
Novavax shares plunge on weak demand for its COVID-19 vaccine - CBS News
The new poll shows that only 19% of people age 50-64, and 44% of people over 65, have gotten two booster doses.
With officially reported cases surging in recent weeks, and many more cases going unreported because results of at-home tests arent tracked, the poll has some surprising findings about older adults experiences with the disease and testing.
In all, 50% of those aged 50 to 64, and 69% of those over age 65, said they had never had COVID-19 by late July 2022.
In the 50-to-64 age group, 29% said they had had COVID-19 once, 9% said they had had it more than once, and 12% said they may have had it but werent sure.
In the over-65 group, 24% said they had had it once, 2% had had it more than once and 5% said they may have had it.
At-home tests, which were scarce until early 2022 and have been made available for free through the federal government, health insurance companies and community locations, have been used by 44% of older adults. The percentage who had ever used an at-home test was highest among those aged 50 to 64, those with higher incomes and education levels, and those who are working.
Meanwhile, 57% of older adults had had PCR testing, which is what feeds the official reporting of COVID-19 rates, but has become less widely used in recent months given the ease and availability of at-home tests. The same groups that were more likely to have used at-home tests were also more likely to have had a PCR test.
SEE ALSO: Which older adults are getting their flu shots and COVID boosters?
But 28% of those over age 65, and 22% of those age 50 to 64, said they had never been tested for COVID-19. Those with high school educations or less, and those with incomes under $30,000, were most likely to say this.
Of those who said they had had COVID-19 at least once, 21% said they had never gotten a test but had had symptoms. Meanwhile, 53% of this group said they had tested positive on a home test and 43% said they had a positive PCR test; respondents could indicate that they had tested positive on both kinds of tests.
Fall booster attitudes varied based on COVID-19 history. Two thirds (66%) of those who had not had COVID-19 by the time they took the survey, and had received a COVID-19 vaccine in the past, said they were very likely to get a fall booster, as did 56% of vaccinated people who had had COVID-19 once.
Meanwhile, 39% of those who had had COVID-19 more than once, and had received at least one dose of COVID-19 vaccine, said they were not likely to get a booster this fall.
The poll also asked older adults if they plan to get vaccinated against influenza this fall; the optimal time for this years flu shots is likely to coincide with the availability of new COVID-19 boosters. Vaccine experts have advised in the past that the two vaccines can be given at the same time.
The difference between the two age groups was striking:
74% of people over 65 said they were very likely to get a flu shot, compared with 46% of people age 50 to 64.
Another 13% of the younger group, and 6% of the older group, said they were somewhat likely to get a flu shot.
Education level made a big difference in flu shot likelihood, with 70% of those who have college degrees or higher saying they are very likely to get a flu shot, compared with 53% of those whose formal educations ended earlier.
Three quarters (75%) of those who said they were very likely to get a flu shot were also people who had gotten at least one dose of COVID-19 vaccine and said they were very likely to get a fall COVID-19 booster.
In contrast, 20% of those who have never gotten a dose of COVID vaccine said they were likely to get a flu shot.
We cant forget that flu can pose a threat to older and more medically vulnerable adults, and the same precautions that work against COVID-19 vaccination, masks, good ventilation and keeping sick people away from others until their symptoms are over work against flu, says Malani. Although we avoided a twindemic of both viruses at once last winter, its not clear well be so lucky again this winter. I encourage everyone to follow the CDC recommendations for their age and health status regarding vaccination and prevention.
The National Poll on Healthy Aging results are based on responses from a nationally representative sample of 1,024 adults aged over 50 from the Foresight 50+ Omnibus panel, which draws from the Foresight 50+ Panel by AARP and NORC at the University of Chicago who answered a wide range of questions online and by phone in late July, 2022. Questions were written, and data interpreted and compiled, by the IHPI team.Read past National Poll on Healthy Aging reports.
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Introduction
The coronavirus disease 2019 (COVID-19) pandemic is a global pandemic. As of December 23, 2021, the World Health Organization (WHO) data platform showed a total of 275,233,892 confirmed cases of COVID-19 and 5,364,996 deaths worldwide.1 The Delta variant and highly mutated Omicron variant have made the COVID-19 pandemic even worse.2,3 Because the population at large is generally susceptible to COVID-19, vaccination against COVID-19 is an effective means of preventing transmission.4 Patients with rheumatic disease are more likely to be infected with COVID-19 than the general population.5 Another study by Ungaro et al suggested that the systemic use of corticosteroids may add to the risk of severe COVID-19 for patients with autoimmune and chronic inflammatory diseases.6 A number of guidelines at home and abroad recommend that eligible patients with rheumatic disease receive the COVID-19 vaccine when their condition is stable.7,8 At present, however, the general population generally does not have strong vaccination intentions and hesitates to get vaccinated, which leads to delays in vaccination and prevention.911 In this study, we investigated the perceptions of COVID-19 infection in patients with rheumatic disease in our hospital through an online questionnaire on the Wenjuanxing platform (web link: http://www.wjx.cn), analyzed the factors influencing their willingness to receive a COVID-19 vaccine, and analyzed the characteristics of patients who had been vaccinated in an attempt to better counsel patients with rheumatic disease regarding vaccination.
Data from patients with rheumatic disease who presented to the Rheumatology and Immunology Department Outpatient Clinic at our hospital from July 320, 2021, were collected in the database. After cluster sampling by disease, these patients data were randomly sequenced using a random number table, and then patients were randomly selected. They completed the questionnaire under the instruction of a blinded medical worker. Four hundred sixty-three questionnaires were distributed, and 463 were effectively returned (recovery rate = 100%).
The inclusion criteria for patients with rheumatic immune disease were as follows: 1. Patients with rheumatoid arthritis who met the classification criteria for rheumatoid arthritis formulated by the American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) in 2010; 2. Patients with systemic lupus erythematosus (SLE) who met the SLE classification criteria established by the EULAR/ACR in 2019; 3. Patients with Sjgrens syndrome who met the 2016 ACR/EULAR classification criteria for Sjgrens syndrome; 4. Patients with polymyositis/dermatomyositis who met the dermatomyositis diagnostic criteria developed by Bohan and Pete in 1975; 5. Patients with gout conforming to the gout classification criteria formulated by the ACR/EULAR in 2015; 6. Patients with osteoarthritis who met the diagnostic criteria for osteoarthritis revised by the ACR in 1995;
7. Patients with ankylosing spondylitis who met the classification criteria for axial spondylarthritis (SpA) recommended by the ASAS (International Spondylarthritis Expert Collaboration Group) in 2009; 8. Patients with psoriatic arthritis who met the 2006 CASPAR classification diagnostic criteria; 9. Patients who underwent enteroscopy and were diagnosed with inflammatory bowel disease-associated arthritis that is consistent with the diagnosis of ulcerative colitis and Crohns disease with peripheral arthritis and axial joint disease, in which the diagnosis could be made by excluding other joint diseases; 10. Patients with systemic sclerosis who met the 2013 ACR/EULAR classification criteria for systemic sclerosis;
11. Patients with Takayasu arteritis who met the 1990 ACR diagnostic criteria for Takayasu arteritis; 12. Patients with Antineutrophil cytoplasmic antibody-associated vasculitis who met the provisional classification criteria of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis included in the 2017 EULAR-ACR criteria; 13. Adult patients with Stills disease who met the 1992 Japanese Yamaguch criteria; 14. Patients with polymyalgia rheumatica who met the 2005 ACR/EULAR PMR classification criteria for polymyalgia rheumatica; 15. Patients with IgG4-related diseases who met the 2019 ACR/EULAR IgG4-related disease classification criteria; 16. Patients with mixed connective tissue disease who met the 1983 Kahn diagnostic criteria; 17. Patients with undifferentiated connective tissue disease with one or more typical symptoms or signs of rheumatism, one or more high-titer autoantibodies, and for whom the course of disease was > 2 years, excluding patients with any other connective tissue disease; and 18. Patients with antiphospholipid antibody syndrome who met the 2006 revised classification criteria for Sapporo antiphospholipid syndrome. Patients were evaluated for disease remission or acute exacerbation according to their symptoms, signs and auxiliary examinations according to the diseases evaluation criteria; for example, patients received a DAS28 score for rheumatoid arthritis (a DAS score <2.6 indicates remission), an SLE-DAI score for SLE (an SLEDAI score 4 indicates inactivity), and an ASDAS score for ankylosing spondylitis (an ASDAS score < 1.3 indicates inactivity). The exclusion criteria included patients aged <18 years old, patients who were illiterate, patients with a loss of comprehension and expression ability, and critically ill patients.
Each patient could only complete the questionnaire once. Verification of validity was established through a questionnaire setting the quality control conditions as follows: 1) Only when the response to Question 8 of the Questionnaire (Are you a patient with rheumatic immune disease? [single-choice question, if you choose yes, please continue to answer; if you choose no, the questionnaire is invalid]) was affirmative was the questionnaire considered valid; 2) A total answering time <10 s or > 2 min invalidated the questionnaire; and 3) Each question must be completed before the next question was presented. Incomplete answer sheets were not collected. The information of all questionnaires was checked by the Wenjuanxing online system and double-checked by the investigator. Forty-six (9.9%) invalid questionnaires were excluded; thus, 417 were valid.
The participants scanned the QR code of Wenjuanxing on WeChat and completed the self-designed online questionnaire titled A Survey on the Willingness of Patients with Rheumatic Disease to Receive a COVID-19 Vaccine. There were 25 questions in the questionnaire, covering the basic information of the respondents and assessing their rheumatic disease status, their perceptions of COVID-19 infection risk and its impact on rheumatic disease, their perception levels and willingness to receive a COVID-19 vaccine, and their COVID-19 vaccination status. The Cronbachs alpha coefficient of the questionnaire reliability test was 0.715, which was acceptable The KaiserMeyerOlkin (KMO) test of validity was 0.5, and the cumulative variance interpretation rate was 62.41%.
The survey data from the questionnaires were exported and analyzed using SPSS (version 22.0) statistical software. Univariate analysis was performed by a 2 test, and multivariate analysis was performed by logistic regression (=0.05, two-sided test). Analysis of variance (ANOVA) was used to analyze the impact of six variables, including the sex, age, marital status, educational level, place of residence, and occupation (medical or nonmedical) of the respondent, the respondents family members, relatives, and friends perceptions of COVID-19 infection risk, as well as the impact of the patients perception of COVID-19 infection on rheumatic disease. Twelve factors, including the sex, age, marital status, educational level, place of residence, and occupation (medical or nonmedical) of the respondent, the respondents family members, relatives and friends perceptions of COVID-19 infection risk, disease assessment, risk perception of COVID-19 infection, perception of the impact of COVID-19 infection on rheumatic disease, perception of the impact of COVID-19 vaccination on rheumatic disease, and vaccination with other vaccines in the last 5 years (other than the COVID-19 vaccine), were analyzed as independent variables and the willingness to receive COVID-19 vaccination was analyzed as a dependent variable in logistic linear regression analysis.
Since this was a survey study, the study was granted an exemption from the requirement of written informed consent by the institutional ethics committee of Heping Hospital Affiliated to Changzhi Medical College. Oral consent was obtained from the participants (or their parent/legal guardian/next of kin) for participation in the study. This study was conducted ethically in accordance with the World Medical Association Declaration of Helsinki and complied with the guidelines for human studies.
The demographic characteristics of the respondents are presented in Table 1. Among the participants, the majority were female (292 [70.02%]). The age distribution was as follows: 39 respondents were aged 1829 years (9.35%); 77 were aged 3039 years (18.47%); 123 were aged 4049 years (29.50%); 122 were aged 5059 years (29.26%); 39 were aged 6065 years (9.35%); and 17 were aged > 65 years (4.08%). Most of the respondents were married (376 [90.17%]). The respondents places of residence were as follows: 184 lived in cities (44.12%); 96 lived in counties (23.02%); 32 lived in towns (7.67%); 104 lived in villages (24.94%); and 1 had no permanent residence (0.24%). The occupations of the participants were as follows: 19 were medical workers (4.56%); and 398 were nonmedical workers (95.44%). The occupations of the respondents family members, relatives, and friends were as follows: 124 were medical workers (29.74%); and 293 were nonmedical workers (70.26%).
Table 1 Demographic Details of the Study Participants
Among the participants, 350 (83.93%) were in the remission stage of rheumatic disease, while 67 (16.07%) were in the active stage. Four hundred seventeen participants had 448 episodes of rheumatic disease. The composition of rheumatic disease among the participants was as follows (the respondents were permitted to choose more than one option): 171 had rheumatoid arthritis (38.17%); 74 had SLE (16.52%); 65 had ankylosing spondylitis (14.51%); 31 had gout (6.92%); 26 had Sjogrens syndrome (5.8%); 18 had osteoarthritis (4.02%); 14 had connective tissue disease (3. 13%); 7 had systemic sclerosis (1.56%); 5 had Takayasu arthritis (1.12%); 4 had polymyalgia rheumatica (0.90%); 3 had psoriatic arthritis (0.67%); 3 had ANCA-related vasculitis (0.67%); 3 had antiphospholipid antibody syndrome (0.67%); 2 had polymyositis (0.45%); 2 had dermatomyositis (0.45%); 2 had undifferentiated spondyloarthropathy, 2 (0.45%); 2 had adult-onset Stills disease (0.45%); and 16 had other rheumatic diseases (3.57%).
Among the participants, 127 (30.46%) believed they had no risk of COVID-19 infection, while 199 (47.72%) were uncertain about their risk. The results of ANOVA showed that the sexes had different risk perceptions of COVID-19 infection (p<0.05), while age, marital status, place of residence, respondent occupation (medical or nonmedical), and the occupations of the respondents family members, relatives, and friends had no statistical significance on the risk perception of COVID-19 infection (P > 0.05, Table 2). A chi-square test was performed regarding the risk perception of COVID-19 infection among the sexes: specifically, 36.80% of the men chose no risk at all compared to 27.74% of the women; 17.60% of the men chose basically no risk compared to 10.62% of the women; and 53.08% of the women chose unclear compared to 35.20% of the men (p<0.05; Table 3).
Table 2 Analysis of the Impact of Demographic Details on the Perception of COVID-19 Infection Risk
Table 3 Analysis of the Impact of Sex on the Perception of COVID-19 Infection Risk
Among the participants, 64 (15.35%) thought that even if they were infected with COVID-19, it would have no impact on their rheumatic disease, 30 (7.19%) thought it would have a negligible impact, 20 (4.8%) thought it would have a moderate impact, 29 (6.95%) thought it would have a considerable impact, 27 (6.47%) thought it would have an enormous impact, and 247 (59.23%) were not certain about the impact (Table 4). The results of ANOVA showed that the occupation (medical or nonmedical) of the respondents was significantly associated with the impact of COVID-19 infection on rheumatic disease (P <0.05); however, sex, age, marital status, place of residence, occupations of the respondents family members, relatives, and friends (medical or nonmedical), and the perception of the impact of COVID-19 infection on rheumatic disease were not statistically significant (P > 0.05). Chi-square test analysis showed that 31.58% and 26.32% of the participants who were medical workers chose no impact at all and unclear, respectively, compared to 14.57% and 60.89% of nonmedical workers, respectively (P <0.05; Table 5).
Table 4 ANOVA Between Demographic Details and the Perception of the Impact of COVID-19 Infection on Rheumatic Disease
Table 5 Chi-Square Analysis Between the Occupations (Medical versus Nonmedical) of the Participants and Their Perceptions of the Impact of COVID-19 Infection on Rheumatic Disease
Among the 417 collected questionnaires regarding COVID-19 vaccination willingness, 38 (9.11%) of the participants completely rejected vaccination, 5 (1.20%) were uncertain but inclined to reject vaccination, 7 (1.68%) were partially inclined to reject vaccination, and 52 (12.47%) wanted to postpone vaccination. In contrast, 21 (5.04%) of the participants partially intended to accept vaccination, 26 (6.24%) intended to accept vaccination but were also unsure, and 268 (64.27%) were willing to accept vaccination.
Logistic linear regression analysis showed that sex, the occupations of the respondents, their family members, relatives, and friends (medical or nonmedical), and the perception of the impact of COVID-19 infection on rheumatic disease had a statistically significant effect on the willingness to receive the COVID-19 vaccine (P <0.05; Table 6). ANOVA was performed regarding the degree of vaccination willingness and the four factors influencing vaccination willingness. Sex, occupation, the perception of the impact of COVID-19 infection on rheumatic disease, and vaccination willingness were analyzed by ANOVA (P <0.05) as follows: males (6.351.30) were more willing than females (5.552.12) to receive vaccination, nonmedical workers (5.841.89) were more willing than medical workers (4.632.65) to receive vaccination, and patients who thought COVID-19 infection had no impact on rheumatic disease (6.581.48) were more willing than those who were uncertain about vaccination (5.722.04) to receive vaccination; the OR values were negatively correlated (Table 7).
Table 6 Logistic Regression Analysis of Factors Influencing COVID-19 Vaccine Willingness
Table 7 ANOVA of the Degree of Willingness and Factors Influencing the Degree of Willingness to Be Vaccinated Against COVID-19
Among the 417 participants, 167 (44.60%) received the COVID-19 vaccine, and 231 (55.40%) did not. Of the 167 patients in the vaccinated group, 152 (91.02%) had no adverse reactions, while 15 (8.98%) had adverse reactions, including 3 with mild pain at the injection site, 3 with aggravated joint pain, 2 with mild dizziness, 2 with mild nausea, 2 with mild abdominal pain, 2 with mild rash, and 1 with a runny nose. Of the patients in the unvaccinated group, 245 options chose not to be vaccinated. The respondents were permitted to choose more than one option. Fourteen responses (5.71%) did not understand the vaccination process or found it to be too troublesome, 13 (5.31%) found it difficult to make an appointment due to the shortage of vaccines, 2 (0.82%) were not satisfied with the preventive effect of the vaccine, 44 (17.96%) were worried about the quality or side effects of the vaccine, 12 (4.90%) claimed their vaccinations had been scheduled but it was not time for the appointment, 117 (47.76%) thought they did not belong to the population that needed to be vaccinated, and 43 (17.55%) chose other reasons.
The results of this questionnaire survey showed that different sexes had different risk perceptions regarding COVID-19 infection. The proportion of men who thought there was no risk at all and that the risk was negligible was greater than that of women, while the proportion of women who chose unclear was greater than that of men, which indicated that men tend to underestimate the risk perception of COVID-19 infection, while women lack awareness of the risk of COVID-19 infection. There was a difference between medical workers and nonmedical workers in the perception of the impact of COVID-19 infection on rheumatic disease. The proportion of medical workers who thought there was no impact was 31.58%, which was greater than that of nonmedical workers (14.57%). The proportion of nonmedical workers who were unclear about the level of impact was 60.80%, which was greater than that of medical workers (26.32%). These results suggested that a large number of people are still unaware of or lack knowledge about the impact of COVID-19 infection on rheumatic disease, while a very high proportion of medical workers believe that there is no impact at all. A multicenter study showed that female sex, a fear of being infected, and the nursing profession are the main factors affecting vaccination for the population with mental health disturbances.12 Another study among adult participants found that males have a poor perception of the risk of COVID-19 and do not practice self-quarantining.13 Our results showed that sex and the medical profession have a significant impact on the perception of COVID-19 infection risk, which is consistent with published reports.1215
Among unvaccinated patients with rheumatic disease, 64.27% were completely willing to be vaccinated against COVID-19, while 26.62% were hesitant. The factors that influenced willingness to vaccinate included sex, occupation, and the perception of the impact of COVID-19 infection on rheumatic disease. The vaccination willingness of male patients was higher than that of female patients, and the vaccination willingness of nonmedical workers was higher than that of medical workers. The survey results by Yurttas et al compared the willingness to be vaccinated among the healthy population, patients with rheumatic diseases and medical workers and found that males and medical workers were more willing to be vaccinated.16 Therefore, clinically, male patients with rheumatic diseases are more likely to be persuaded to be vaccinated. The perception of the impact of COVID-19 infection on rheumatic disease was negatively correlated with vaccination willingness. The greater a patient thought of the impact of COVID-19 vaccines, the lower their vaccination willingness, which was consistent with the results of previous research.1720 High perceived susceptibility to COVID-19 also makes people more inclined to receive a COVID-19 vaccine.10 A survey in 2021 shows that only 54.9% of patients with rheumatic and musculoskeletal diseases were willing to receive the COVID-19 vaccine, although they perceived themselves to be at risk of being infected.21 Similar to the survey,21 64.27% of the patients with rheumatic disease in our study were willing to receive the vaccine, which indicates that their concept of vaccination should be improved.
In this survey, 167 patients (44.60%) with rheumatic disease received the COVID-19 vaccine. Looking at the management experience of other infectious diseases, herd immunity can help vaccination programs and protect unvaccinated, immunocompromised populations.22 A vaccination rate of 70%-80%, or more, will be effective in achieving herd immunity.22 A vaccination rate of 6072% is recommended for herd immunity, although a rate of 8490% is much better.23 The adverse reactions in the unvaccinated patients were mild pain at the injection site, dizziness, nausea, rash, a runny nose, and aggravated joint pain, which were general adverse reactions. As reported, pain, headache, and fatigue were the most frequent adverse reactions to COVID-19.24 Our results did not differ from the existing reports. The incidence of adverse reactions was 8.98%, which was higher than that in the COVID-19 vaccine surveillance report (11.86/100,000 doses) released by the China CDC on May 28, 2021.25 The relatively high rate of adverse reactions may be due to the relatively low immunity of patients with rheumatic disease. The reaction to the vaccine would be intensified, but because there were no serious adverse reactions, it can be concluded that the safety of the vaccine is relatively high. Among the unvaccinated participants, as many as 47.76% said that they did not receive the vaccine because they did not think they were among the population that needed to be vaccinated. This finding is closely related to a persons perception of COVID-19, as previously reported.1820
The global COVID-19 pandemic has not been controlled, and there have been many local outbreaks in China. Only when the vaccination rate reaches the level of herd immunity can the disease be controlled.23 Due to the characteristics of rheumatic disease, such as multisystem damage, repeated recurrence, long-term survival of patients with the disease, and massive application of immunosuppressive drugs, a number of vaccination guidelines and expert opinions have been published for this special population with rheumatic immune diseases at home and abroad.8,26 Patients with rheumatic disease are more susceptible to COVID-19 infection than the general population, have a high mortality rate and are very likely to have adverse reactions.8,26 The experts suggest that these patients should receive vaccines as early as possible, while adjusting their therapies against rheumatic disease;8,26 however, a patients low awareness of the risk of COVID-19 infection and vaccination and excessive anxiety about the disease have led to low vaccination willingness and a low vaccination rate.1720 Indeed, the publicity of professional medical knowledge should be enhanced. With the help of health care experts and social media, health communication campaigns should be improved and populations at risk should be targeted.27 We should provide verified communication from physicians offices to the public via multiple channels, such as the internet, newspapers, radio, television, popular medical science platforms, and health education programs, to eliminate hesitation for vaccination and comprehensively enhance confidence in vaccination.28 Under the requirement of herd immunity against COVID-19 infection, it is even more important to strengthen international cooperation, play a leading role in the government, and strengthen the quality control of COVID-19.29 According to our results and previous reports,1720,2329 we should improve the perception and education of patients with low immune capacity, thereby improving their vaccination willingness, achieving safe vaccination, accomplishing herd immunity as soon as possible, and avoiding the health hazards aggravated by COVID-19.
A limitation of this study was that this was a single-center small sample survey, so it is still necessary to expand the sample size to verify the results.
The sex of patients with rheumatoid diseases, whether they were medical workers or not, the level of knowledge about the risk of COVID-19 infection and the impact of vaccination on the disease were shown to be key factors influencing patients willingness to receive a COVID-19 vaccine. The vaccination rate of patients with rheumatic disease was correspondingly low, and the rate of adverse reactions was slightly higher than that in the general population.
The authors report no conflicts of interest in this work.
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