This falls flu shot will be designed to protect you from just three strains of the influenza virus, instead of the usual four, according to the U.S. Food and Drug Administration (FDA). Thats because an entire branch of the influenza family tree has died out, and experts say that's likely due, at least in part, to the COVID pandemic and the precautions many people were taking. Heres what to know about the now extinct Yamagata influenza B virus, what happened to it and how its disappearance will affect next years flu vaccines.
In the years leading up to the pandemic, Dr. Arnold Monto, a professor emeritus of epidemiology at the University of Michigan and member of the FDA's vaccine committee, tells Yahoo Life that scientists got a clue that Yamagata might be on the decline because it wasnt diversifying the way that B Victoria did," which is another lineage of influenza B. "Victoria was doing all the weird, wonderful things that flu viruses do," says Monto, "but that wasnt happening with B Yamagata."
Then the COVID pandemic hit, and scientists stopped seeing Yamagata in samples taken from patients with flu altogether. None at all extinction, says Monto.
Its impossible to say for sure what caused the death of the Yamagata strain, according to Monto and Dr. Pedro Piedra, a professor of molecular virology, microbiology and pediatrics at Baylor College of Medicine. But they and most virologists consider the various methods to slow the spread of COVID, like masking and social distancing, a major factor.
One reason that might have led to the extinction of Yamagata is that influenza B almost exclusively infects humans, Piedra tells Yahoo Life, while influenza infects animals. For viruses to stay alive, they need a host, he explains. So imagine for influenza B Yamagata, all of a sudden the ability to transmit is not possible, because the host is now protecting themselves through non-pharmacological interventions, such as avoiding close contact with other people to slow the spread of COVID.
The Victoria B strain was more prevalent than Yamagata before the pandemic and managed to hang on, but the year prior to the pandemic, there was less Yamagata circulating, so that when it took a hit, that hit was more dramatic, Piedra explains. Influenza A, meanwhile, had plenty of animal hosts to sustain it while humans hid out.
Each year, scientists have to guess which subtypes of influenza viruses they think will be most actively circulating in order to formulate the most protective vaccine possible. Thats a serious challenge because viruses are constantly recombining and mutating.
There are four broad types of influenza: A, B, C and D. But types C and D rarely appear and generally cause only mild illnesses. For this reason, the CDC and the World Health Organization dont consider them to be public health threats.
Strains of influenza A and B, on the other hand, circle the globe seasonally. More than 130 subtypes of influenza A have been discovered in nature, according to the CDC, while influenza B has been divided into just two groups, known as lineages: B Victoria and B Yamagata. But vaccine makers cant yet include more than four types of the flu virus in a given vaccine due to technological limitations. Since 2014, therefore, the vaccine has been made to protect against two strains of influenza A H1N1 and H3N2 and two strains of influenza B, Victoria and Yamagata.
But with the disappearance of Yamagata, the U.S. and much of the world will use a shot based on just three strains of flu or a trivalent vaccine instead of a quadrivalent vaccine, which is designed to protect against four strains.
Making a vaccine based on fewer flu strains could improve vaccine-making capacity globally, research suggests. It gives you a little more leeway, Piedra says.
It means that making the vaccine wont take quite as long, so scientists may have a little longer to pick the flu strains the vaccine is designed to block a decision that typically happens in May. Or, as Piedra explains: You will have the vaccine a little earlier, to be sure that everyone who wants to be is vaccinated. If the vaccine comes in late, its much harder to vaccinate everyone and have broad coverage.
Yes, say both Monto and Piedra. Theres no evidence that Yamagata B is still around, so the vaccine will be tailored to the strains that arecirculating. As a matter of principle, you dont want to vaccinate people with something that you dont need, says Monto.
Its also worth noting that it's not impossible for the B Yamagata strain to reemerge, says Piedra. But he adds that theres no reason to vaccinate against it now and no immediate cause for concern that it will come back. Also, according to Monto, there's a good reason to leave it out of the vaccine recipe. In the U.S., flu shots contain an inactivated virology-speak for dead bit of virus thats incapable of causing infection. But the nasal spray form uses whats called a live attenuated influenza vaccine, meaning it contains weakened, live viruses.
This version of the virus is generally too weak to cause illness, but "the concern there was about not wanting to bring back something that was gone by including B Yamagata in these vaccines, Monto says. So come the fall, the flu shot and nasal spray will protect against three subtypes instead.
A large European study published in Heart suggests that COVID-19 vaccines reduce the risk of heart failure and blood clots in veins or arteries for at least 6 months after SARS-CoV-2 infection.
University of Oxford investigators conducted a staggered cohort study using the electronic health records of 10.2million vaccinated and 10.4million unvaccinated COVID-nave people based on national COVID-19 vaccination campaigns in the United Kingdom, Spain, and Estonia from January to July 2021.
The study period was dominated by the Alpha and then Delta variants. Participants included adults of all ages and those at high risk for poor COVID-19 outcomes.
The study, which used vaccination as the time-varying exposure, included all COVID-19 vaccines available in Europe during the study period: AstraZeneca/Oxford, Pfizer/BioNTech, Johnson & Johnson (J&J), and Moderna.
Study outcomes of interest were ischemic stroke (IS), hemorrhagic stroke, transient ischemic attack (TIA), ventricular arrhythmia/cardiac arrest, myocarditis/pericarditis, myocardial infarction (MI, or heart attack), heart failure (HF), pulmonary embolism (PE), and deep vein thrombosis (DVT). Venous thromboembolism (VTE) was used as an aggregate of PE and DVT, and arterial thrombosis/thromboembolism (ATE) was a composite of IS, TIA, and MI.
While COVID-19 vaccines have proven effective against infection, hospitalization, and death, there have been reports of unusual blood clots after receipt of adenovirus-based COVID-19 vaccines (AstraZeneca and J&J), the authors noted, adding that a link was found between mRNA vaccines (Pfizer and Moderna) and a small risk of myocarditis.
"On the other hand, SARS-CoV-2 infection can trigger cardiac and thromboembolic complications," they wrote. "Previous studies showed that, while slowly decreasing over time, the risk for serious complications remain high for up to a year after infection."
Also, the risk of clots and myocarditis, which is inflammation of the heart muscle, is much higher after COVID-19 infection than after vaccination.
COVID vaccine effectiveness against HF, VTE, and ATE was 22%, 53%, and 45%, respectively, in the month after SARS-CoV-2 infection and 53%, 72%, and 61% at 3 to 6 months. A comparison of the Pfizerand AstraZeneca COVID-19 vaccines suggested a larger reduction in VTE from the former in the first month after vaccination, but no other differences were noted.
COVID-19 vaccination reduced the risk of post-COVID-19 cardiac and thromboembolic outcomes. These effects were more pronounced for acute COVID-19 outcomes, consistent with known reductions in disease severity following breakthrough versus unvaccinated SARS-CoV-2 infection.
"COVID-19 vaccination reduced the risk of post-COVID-19 cardiac and thromboembolic outcomes," the study authors wrote. "These effects were more pronounced for acute COVID-19 outcomes, consistent with known reductions in disease severity following breakthrough versus unvaccinated SARS-CoV-2 infection."
They called for future research on the additive effect of COVID-19 vaccination on the risk of post-vaccine and/or post-COVID cardiac events and blood clots as well as possible waning of protection over time and with emerging variants and the effect of booster doses.
CLAIM
U.S. doctors found that long Covid developed in 70 percent of cases after vax injection, not after infection
DETAILS
Inadequate support: The claim that most cases of long COVID occur after vaccination, not infection, is based on poorly described anecdotes that dont provide sufficient evidence to support the claim. The preprint cited also didnt show how common these symptoms are or whether COVID-19 vaccination caused them.
KEY TAKE AWAY
Some people have reported symptoms resembling long COVID after COVID-19 vaccination. Research on these symptoms is still limited, and their potential link with COVID-19 vaccines remains undetermined. However, these cases are rare, and the risk associated with SARS-CoV-2 infection far outweighs the risk of developing long-term complications after COVID-19 vaccination. Studies are ongoing to better understand the cause of post-vaccination symptoms and their possible relationship with COVID-19 vaccines.
The original post, published on the Telegram channel Disclose.tv, had received over 200,000 views at the time of writing. The post linked to a website with the same name that reproduced an op-ed by physicians Pierre Kory and Paul Marik published in The Hill on 6 March 2024.
Disclose.tv is a Germany-based outlet that operates as a news aggregator. According to an investigation by Logically, the site originated from a forum focused on conspiracy theories.
The website itself no longer seems to publish overt conspiracies. However, Logically and Deutsche Welle (DW) News found that Disclose.tv continues to share conspiracy theories, pseudoscience, and hate content through its social media accounts, which have around five million followers. In 2017, PolitiFact included Disclose.tv in its list of websites containing deliberately false or fake stories.
Kory and Marik are the president and chief scientific officer, respectively, of the fringe medical group Front Line COVID-19 Critical Care (FLCCC) Alliance. This group extensively promoted the use of ivermectin off-label to prevent and treat COVID-19 despite a lack of evidence supporting this use.
FLCCC Alliance has also promoted other unproven therapies, like nattokinase, for treating long COVID and post-vaccination symptoms.
As we will demonstrate below, Kory and Mariks op-ed is yet another example of such unsupported claims. The op-ed doesnt provide credible evidence indicating that COVID-19 vaccination is behind most cases of long COVID. Instead, the authors relied on unverifiable anecdotes that cant support their claim, as we will show below.
Cases of post-vaccination symptoms resembling long COVID have been reported to the U.S. Vaccine Adverse Event Reporting System (VAERS). However, studies suggest they are rare and far less common than cases of long COVID after infection, as this review will explain.
The op-ed claimed that, after evaluating over 1,000 individuals with long COVID, [a]pproximately 70 percent of these patients said their reported symptoms occurred in the minutes, hours, days and weeks after COVID vaccination, as opposed to after COVID infection.
The authors based the 70% figure on data from a private practitioner who is also a member of the fringe medical group FLCCC Alliance. The op-ed didnt include any explanation about the methodology used to calculate the 70% figure. This is important, as it provides the necessary information to assess the validity of the results. In addition, other issues make the 70% figure unreliable.
First, the fact that these symptoms began after vaccination alone isnt enough to demonstrate that the vaccine caused them, despite what the op-ed seemed to imply. A temporal association, while a necessary component for determining if there is a causal effect, is only the first step and requires further investigations.
Second, the figure is based exclusively on the patients perceptions of symptoms developed after they received a COVID-19 vaccine. There is no indication that the evaluation included analyses or tests that objectively assessed the presence and severity of these symptoms.
Finally, the op-ed didnt indicate whether the evaluation considered factors other than vaccination as a cause or contributing factor to the observed symptoms. These include, for example, a previous SARS-CoV-2 infection or the existence of underlying medical conditions.
In other words, the claim is entirely based on anecdotal descriptions of symptoms that patients self-reported from a single private practice. The problem with such data is that it is highly prone to biases, as neurologist Steven Novella explained in Science-Based Medicine.
For instance, the patients who go to that specific private practice might not be representative of the general population (selection bias), meaning the observations may not be generalizable to everyone. The fact that the observations relied on self-reporting also introduces a risk of recall bias due to the patients inaccurate or partial recollection of events. Data collected in this way is also subject to distortions (reporting bias) and biased interpretations that support either the patients or the doctors preexisting beliefs (confirmation bias).
Theres no evidence that the physician or Kory and Marik attempted to account for these potential biases in their interpretation of the data.
The high risk of bias, the lack of information about the data and methodology, and the FLCCC Alliances record of spreading misinformation cast serious doubts over the figures credibility.
To further support the claim that adverse events from COVID-19 vaccination, including persistent symptoms, are common, Kory and Marik cited a preprint by Krumholz et al. uploaded to the preprint server medRxiv on 10 November 2023[1]. A preprint is a preliminary version of a manuscript that has yet to be evaluated by other experts.
As the title of the preprint clearly states, the authors conducted A Descriptive Analysis of Reported Symptoms and Patient Experiences After Covid-19 Immunization.
The analysis involved 241 individuals aged 18 and older who participated in the Yale Listen to Immune, Symptom and Treatment Experiences Now (LISTEN) study from May 2022 to July 2023. This study, administered online, collects information about symptoms and medical history with the purpose of better understanding long COVID and post-vaccine adverse events.
The researchers objective was to characterize chronic post-vaccination syndrome, defined by self-report in response to whether the individual thought the vaccine had injured them.
To do that, the authors used surveys to evaluate the type of symptoms, their severity and duration, the treatments participants had tried, and new medical conditions diagnosed since vaccination. The authors excluded people reporting long COVID.
Unlike The Hill op-ed, the preprint fully described the methodology used. The authors also considered variables that could influence the observations, such as demographics (age, gender, race, country of residence, marital status, household income, employment status, and insurance status), preexisting medical conditions, prior SARS-CoV-2 infection, and vaccination status, and the type of COVID-19 vaccine participants received.
The results showed a diverse range of reported symptoms beginning soon after COVID-19 vaccination. In many cases, these symptoms were severe, debilitating, and persisted for a year or more. The authors concluded that people reporting post-vaccination syndrome in the evaluated group were generally highly symptomatic, had poorer health, and had tried many treatment strategies without success.
In contrast to the op-ed, the preprint clearly stated the limitations of the analysis in its Discussion section, including the lack of a control group and the reliance on self-reporting. It also explained that the method of selecting the participants led to discrepancies compared to the overall population. Therefore, the authors concluded that it is not possible to estimate the incidence or who might be most susceptible to this condition.
The authors further highlighted that the cause of the reported symptoms remained undetermined. The net benefit of the covid-19 vaccination program is clear, the authors stated. However, the temporal relationship between vaccination and the onset of symptoms suggests a potential relationship that requires further investigation.
In summary, while the preprint documented and characterized self-reported symptoms following COVID-19 vaccination, it didnt attribute them to any specific cause. It also didnt show how common these cases are in the general population, as FactCheck.org explained. Therefore, these results dont provide sufficient evidence to support Kory and Mariks claim.
COVID-19 vaccines are safe and highly effective at reducing the risk of severe COVID-19. But as with other medical interventions, they carry a small risk of rare complications. Certain COVID-19 vaccines are associated with rare cases of severe allergic reactions (anaphylaxis) and a slightly increased risk of blood clotting, Guillain-Barr syndrome, and heart inflammation.
But these severe reactions to vaccination are infrequent. Most people only experience mild side effects that go away in a few days.
A spokesperson from the U.S. Centers for Disease Control and Prevention (CDC) told FactCheck.org that the agency is aware of reports in the Vaccine Adverse Event Reporting System (VAERS) and in the media of a wide range of long-lasting symptoms following COVID-19 vaccination (such as fatigue, headache, and difficulty concentrating).
These symptoms, which usually appear within the first weeks after vaccination, have been popularly called Long Vax due to their resemblance with long COVID symptoms. However, the clinical characteristics of these symptoms and their potential link to vaccination are currently unclear.
In July 2023, an article in Science discussed how scientists had begun acknowledging post-vaccination symptoms as a real phenomenon that warrants further research.
Some researchers suggest that post-vaccination symptoms share some similarities with two known medical conditions. The first one is small fiber neuropathy, an uncommon chronic condition that affects a persons ability to sense pain. This results in numbness, painful tingling, or burning sensations in the feet and hands[2].
The second one is a condition called postural orthostatic tachycardia syndrome (POTS)[3,4]. This condition specifically affects people when they transition from lying down to standing up, causing muscle weakness, fast heart rate, fatigue, and brain fog.
About half of the cases of small fiber neuropathy are caused by underlying medical conditions, with diabetes being the most common cause. The other half of the cases happen for no known reason. It is also unknown what causes POTS, and no diagnostic tests are available. These limitations make it difficult to study the potential connection between these conditions and COVID-19 vaccination.
To date, only a few studies have addressed long-term symptoms after COVID-19 vaccination.
One preprint uploaded to medRxiv on 17 May 2022 evaluated symptoms of neuropathy after COVID-19 vaccination in 23 participants[5]. The authors found a variety of neuropathic symptoms following COVID-19 vaccination that improved when treated with corticosteroids in some patients. Corticosteroids are a type of anti-inflammatory drug that also reduces the activity of the immune system. This led the authors to hypothesize that the symptoms observed might be the result of immune reactions, similar to what happens in COVID-19 patients. But these results havent been published in a scientific journal yet.
In December 2022, a team at Cedars-Sinai Medical Center published a study analyzing the occurrence of POTS in almost 285,000 people who had received a COVID-19 vaccine[6]. The study found that the rate of POTS symptoms was 33% higher within the 90 days following vaccination than in the three months before. However, it also found that the rate of POTS symptoms was much higher (52%) after SARS-CoV-2 infection.
Diagnosing post-vaccination symptoms is challenging due to the overlap in the reported symptoms with other conditions, including long COVID, neuropathy, PTOS, and chronic fatigue syndrome. For example, distinguishing between post-vaccine symptoms and long COVID with a high degree of certainty would require demonstrating that the person had no previous SARS-CoV-2 infection. This is difficult, given the large number of infections and the fact that many of them went unnoticed.
Because of the difficulties in making an accurate diagnosis, estimating the rate at which these symptoms occur is also complicated. However , researchers suggest that the number of cases potentially attributable to COVID-19 vaccination is likely very low, as many suspected post-vaccine symptoms are due to causes other than vaccination.
In May 2023, the Paul-Ehrlich-Institut (Germany) issued a statement saying it had found no safety signal for the occurrence of these symptoms after [COVID-19] vaccination. The agency found that the reporting rate of chronic fatigue syndrome, post-vaccination syndrome, POTS, and post-acute COVID-19 syndrome in the adverse reaction database of the European Medicines Agency was less than one suspected case per 100,000 vaccinations. The agency concluded that persistent symptoms following COVID-19 vaccination are therefore extremely rarely reported.
Likewise, the CDC spokesperson explained to FactCheck.org that to date, no unusual or unexpected patterns of long-lasting symptoms or health problems following vaccination have been linked to vaccination by COVID-19 vaccine safety monitoring systems.
Mounting evidence suggests that long-term symptoms following COVID-19 vaccination are a genuine phenomenon. However, Kory and Mariks op-ed doesnt provide evidence that these post-vaccination symptoms occur frequently in the general population or that COVID-19 vaccines are the cause.
Current evidence instead suggests that long-term post-vaccination symptoms are rare. While the temporal association suggests a potential link between these symptoms and COVID-19 vaccines, a connection between both remains unconfirmed. Further studies are warranted to better understand why these symptoms occur and how to treat them.
Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis. 2020;20(5):5334. https://doi.org/10.1016/S1473-3099(20)30120-1.
Article CAS PubMed PubMed Central Google Scholar
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from patients with pneumonia in China, 2019. NEJM. 2020;382(8):72733. https://doi.org/10.1056/NEJMoa2001017.
Article CAS PubMed Google Scholar
World Health Organization. Coronavirus disease (COVID-19): Vaccine research and development 2021. https://www.who.int/news-room/questions-and-answers/item/coronavirus-disease-(covid-19)-vaccine-research-and-development. Accessed 15 February 2024.
Viveiros-Rosa SG, Mendes CD, Farfn-Cano GG, El-Shazly M. The race for clinical trials on Omicron-based COVID-19 vaccine candidates: updates from global databases. Narra J. 2022;2(3):e88e. https://doi.org/10.52225/narra.v2i3.88.
Article CAS PubMed PubMed Central Google Scholar
Polack FP, Thomas SJ, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al. Safety and efficacy of the BNT162b2 mRNA COVID-19 vaccine. NEJM. 2020;383(27):260315. https://doi.org/10.1056/NEJMoa2034577.
Article CAS PubMed Google Scholar
Baden LR, El Sahly HM, Essink B, Kotloff K, Frey S, Novak R, et al. Efficacy and safety of the mRNA-1273 SARS-CoV-2 vaccine. NEJM. 2021;384(5):40316. https://doi.org/10.1056/NEJMoa2035389.
Article CAS PubMed Google Scholar
Hassan W, Kazmi SK, Tahir MJ, Ullah I, Royan HA, Fahriani M, et al. Global acceptance and hesitancy of COVID-19 vaccination: a narrative review. Narra J. 2021;1(3). https://doi.org/10.52225/narra.v1i3.57.
Dror AA, Eisenbach N, Taiber S, Morozov NG, Mizrachi M, Zigron A, et al. Vaccine hesitancy: the next challenge in the fight against COVID-19. Eur J Epidemiol. 2020;35:7759. https://doi.org/10.1007/s10654-020-00671-y.
Article CAS PubMed PubMed Central Google Scholar
Dub E, Laberge C, Guay M, Bramadat P, Roy R, Bettinger JA. Vaccine hesitancy: an overview. Hum Vaccin Immunother. 2013;9(8):176373. https://doi.org/10.4161/hv.24657.
Article PubMed PubMed Central Google Scholar
Khubchandani J, Sharma S, Price JH, Wiblishauser MJ, Sharma M, Webb FJ. COVID-19 vaccination hesitancy in the United States: a rapid national assessment. J Community Health. 2021;46:2707. https://doi.org/10.1007/s10900-020-00958-x.
Article PubMed PubMed Central Google Scholar
Dub E, Vivion M, MacDonald NE. Vaccine hesitancy, vaccine refusal and the anti-vaccine movement: influence, impact and implications. Expert Rev Vaccines. 2015;14(1):99117. https://doi.org/10.1586/14760584.2015.964212.
Article CAS PubMed Google Scholar
Larson HJ, Jarrett C, Eckersberger E, Smith DM, Paterson P. Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: a systematic review of published literature, 20072012. Vaccine. 2014;32(19):21509. https://doi.org/10.1016/j.vaccine.2014.01.081.
Article PubMed Google Scholar
Machingaidze S, Wiysonge CS. Understanding COVID-19 vaccine hesitancy. Nat Med. 2021;27(8):13389. https://doi.org/10.1038/s41591-021-01459-7.
Article CAS PubMed Google Scholar
Centers for Disease Control and Prevention. COVID-19 vaccination coverage and vaccine confidence among children 2023. https://www.cdc.gov/vaccines/imz-managers/coverage/covidvaxview/interactive/children.html. Accessed 11 September 2023.
Smith LE, Amlt R, Weinman J, Yiend J, Rubin GJ. A systematic review of factors affecting vaccine uptake in young children. Vaccine. 2017;35(45):605969. https://doi.org/10.1016/j.vaccine.2017.09.046.
Article PubMed Google Scholar
Liu PL, Zhao X, Wan B. COVID-19 information exposure and vaccine hesitancy: the influence of trust in government and vaccine confidence. Psychol Health Med. 2023;28(1):2736. https://doi.org/10.1080/13548506.2021.2014910.
Article PubMed Google Scholar
Sapienza A, Falcone R. The role of trust in COVID-19 vaccine acceptance: considerations from a systematic review. Int J Environ Res Public Health. 2022;20(1):665. https://doi.org/10.3390/ijerph20010665.
Article PubMed PubMed Central Google Scholar
Washington HA. Medical apartheid: the dark history of medical experimentation on Black americans from colonial times to the present. Doubleday Books; 2006.
Freimuth VS, Quinn SC, Thomas SB, Cole G, Zook E, Duncan T. African americans views on research and the Tuskegee Syphilis Study. Soc Sci Med. 2001;52(5):797808. https://doi.org/10.1016/S0277-9536(00)00178-7.
Article CAS PubMed Google Scholar
Dovidio JF, Penner LA, Albrecht TL, Norton WE, Gaertner SL, Shelton JN. Disparities and distrust: the implications of psychological processes for understanding racial disparities in health and health care. Soc Sci Med. 2008;67(3):47886. https://doi.org/10.1016/j.socscimed.2008.03.019.
Article PubMed Google Scholar
Feagin J, Bennefield Z. Systemic racism and US health care. Soc Sci Med. 2014;103:714. https://doi.org/10.1016/j.socscimed.2013.09.006.
Article PubMed Google Scholar
Wang Q, Yang L, Jin H, Lin L. Vaccination against COVID-19: a systematic review and meta-analysis of acceptability and its predictors. Prev Med. 2021;150:106694. https://doi.org/10.1016/j.ypmed.2021.106694.
Article PubMed PubMed Central Google Scholar
Lazarus JV, Ratzan SC, Palayew A, Gostin LO, Larson HJ, Rabin K, et al. A global survey of potential acceptance of a COVID-19 vaccine. Nat Med. 2021;27(2):2258. https://doi.org/10.1038/s41591-020-1124-9.
Article CAS PubMed Google Scholar
Faasse K, Newby J. Public perceptions of COVID-19 in Australia: perceived risk, knowledge, health-protective behaviors, and vaccine intentions. Front Psychol. 2020;11:551004. https://doi.org/10.3389/fpsyg.2020.551004.
Article PubMed PubMed Central Google Scholar
Trent M, Seale H, Chughtai AA, Salmon D, MacIntyre CR. Trust in government, intention to vaccinate and COVID-19 vaccine hesitancy: a comparative survey of five large cities in the United States, United Kingdom, and Australia. Vaccine. 2022;40(17):2498505. https://doi.org/10.1016/j.vaccine.2021.06.048.
Article CAS PubMed Google Scholar
Szilagyi PG, Shah MD, Delgado JR, Thomas K, Vizueta N, Cui Y, et al. Parents intentions and perceptions about COVID-19 vaccination for their children: results from a national survey. Pediatrics. 2021;148(4). https://doi.org/10.1542/peds.2021-052335.
Fisher CB, Gray A, Sheck I. COVID-19 pediatric vaccine hesitancy among racially diverse parents in the United States. Vaccines. 2021;10(1):31. https://doi.org/10.3390/vaccines10010031.
Article CAS PubMed PubMed Central Google Scholar
Ruiz JB, Bell RA. Parental COVID-19 vaccine hesitancy in the United States. Public Health Rep. 2022;137(6):11629. https://doi.org/10.1177/00333549221114346.
Article PubMed PubMed Central Google Scholar
Joshi A, Kaur M, Kaur R, Grover A, Nash D, El-Mohandes A. Predictors of COVID-19 vaccine acceptance, intention, and hesitancy: a scoping review. Front Public Health. 2021;9:698111. https://doi.org/10.3389/fpubh.2021.698111.
Article PubMed PubMed Central Google Scholar
Fisher CB, Bragard E, Jaber R, Gray A. COVID-19 vaccine hesitancy among parents of children under five years in the United States. Vaccines. 2022;10(8):1313. https://doi.org/10.3390/vaccines10081313.
Article PubMed PubMed Central Google Scholar
Ku L. The association of social factors and health insurance coverage with COVID-19 vaccinations and hesitancy, July 2021. J Gen Intern Med. 2022;37(2):40914. https://doi.org/10.1007/s11606-021-07213-6.
Article PubMed Google Scholar
McElfish PA, Selig JP, Scott AJ, Rowland B, Willis DE, Reece S, et al. Associations between general vaccine hesitancy and healthcare access among arkansans. J Gen Intern Med. 2023;38(4):8417. https://doi.org/10.1007/s11606-022-07859-w.
Article PubMed Google Scholar
McNaghten A, Brewer NT, Hung M-C, Lu P-J, Daskalakis D, Abad N, et al. COVID-19 vaccination coverage and vaccine confidence by sexual orientation and gender identityUnited States, August 29October 30, 2021. Morb Mortal Wkly Rep. 2022;71(5):171. https://doi.org/10.15585/mmwr.mm7105a3.
Article CAS Google Scholar
Mensah GA, Johnson LE, Zhang X, Stinson N, Carrington K, Malla G, et al. Community Engagement Alliance (CEAL): a National Institutes of Health program to advance health equity. Am J Public Health. 2023;0(0):e16. https://doi.org/10.2105/AJPH.2023.307476.
Article Google Scholar
Bonett S, Lin W, Sexton-Topper P, Wolfe J, Golinkoff J, Deshpande A et al. Assessing and improving data integrity in web-based surveys: a comparison of fraud detection systems in a COVID-19 study. JMIR Form Res Forthcom https://doi.org/10.2196/47091.
Walker RJ, Eisenhauer E, Thompson EL, Butler R, Metheny N, Barroso CS, et al. COVID-19 information, trust, and risk perception across diverse communities in the United States: initial findings from a multistate community engagement alliance (CEAL). Am J Public Health. 2024;114(S1):S11223. https://doi.org/10.2105/AJPH.2023.307504.
Article PubMed PubMed Central Google Scholar
Aron A, Aron EN. Statistics for the behavioral and social sciences. Prentice Hall; 2002.
Jose S, Cyriac MC, Dhandapani M, Joseph J. COVID-19 vaccination intention and hesitancy: mistrust on COVID-19 vaccine benefit a major driver for vaccine hesitancy among healthcare workers; a cross-sectional study in North India. J Prev Med Hyg. 2022;63(2):E219. https://doi.org/10.15167/2421-4248/jpmh2022.63.2.1952.
Article PubMed PubMed Central Google Scholar
Raslan MA, Raslan SA, Shehata EM, Mahmoud AS, Sabri NA, Alzahrani KJ, et al. COVID-19 vaccination in pediatrics: was it valuable and successful? Vaccines. 2023;11(2):214. https://doi.org/10.3390/vaccines11020214.
Article CAS PubMed PubMed Central Google Scholar
Quinn S, Jamison A, Musa D, Hilyard K, Freimuth V. Exploring the continuum of vaccine hesitancy between African American and white adults: results of a qualitative study. PLoS Curr. 2016. https://doi.org/10.1371/currents.outbreaks.3e4a5ea39d8620494e2a2c874a3c4201. 8.
Article PubMed PubMed Central Google Scholar
Dub E, Gagnon D, MacDonald NE. Strategies intended to address vaccine hesitancy: review of published reviews. Vaccine. 2015;33(34):4191203. https://doi.org/10.1016/j.vaccine.2015.04.041.
Article PubMed Google Scholar
Shim E, Chapman GB, Townsend JP, Galvani AP. The influence of altruism on influenza vaccination decisions. J R Soc Interface. 2012;9(74):223443. https://doi.org/10.1098/rsif.2012.0115.
Article PubMed PubMed Central Google Scholar
Smith PJ, Humiston SG, Marcuse EK, Zhao Z, Dorell CG, Howes C, et al. Parental delay or refusal of vaccine doses, childhood vaccination coverage at 24 months of age, and the Health Belief Model. Public Health Rep. 2011;126(2suppl):13546. https://doi.org/10.1177/00333549111260S215.
Article PubMed PubMed Central Google Scholar
Balaji JN, Prakash S, Joshi A, Surapaneni KM, editors. A scoping review on COVID-19 vaccine hesitancy among the lesbian, gay, bisexual, transgender, queer, intersex and asexual (LGBTQIA+) community and factors fostering its refusal. Healthcare; 2023. https://doi.org/10.3390/healthcare11020245.
Garg I, Hanif H, Javed N, Abbas R, Mirza S, Javaid MA, et al. COVID-19 vaccine hesitancy in the LGBTQ+population: a systematic review. Infect Dis Rep. 2021;13(4):87287. https://doi.org/10.3390/idr13040079.
Article PubMed PubMed Central Google Scholar
Shen AK, Browne S, Srivastava T, Michel JJ, Tan AS, Kornides ML. Factors influencing parental and individual COVID-19 vaccine decision making in a pediatric network. Vaccines. 2022;10(8):1277. https://doi.org/10.3390/vaccines10081277.
Article PubMed PubMed Central Google Scholar
The following first appeared in the Substack of Eric Topol, MD, called Ground Truths.
As we recently hit March 11, 2020 the 4-year anniversary of when WHO finally declared COVID a global pandemic, and today, March 13th, when the US declared it a national emergency, we're still learning every day about SARS-CoV-2's impact, its evolution, protection from vaccination, and more. Here's a quick summary of what I think is worth reviewing:
The global excess mortality hasreached about 30 million lost livesattributable to COVID, and theGlobal Burden of Disease published a major paperthis week in The Lanceton the toll it has taken for reducing life expectancy in 204 countries summarized as "The COVID-19 pandemic caused the most severe drops in life expectancy seen in 50+ years."The study did not address disability among survivors, with multiple concurrent studies reinforcing the prevalence of long COVID in tens of millions of people.
Here in the United States, it is striking to review the updated data on partisan gap death rates, as reflected by counties who voted Republican in the 2020 election. According to Ashley Wu, graphics editor at the New York Times, the curves are continuing to diverge, both weekly and cumulatively. There was no divergence when vaccines were first administered but since that time the death rates continue to worsen in counties with 70%+ Republican voters compared with <30%.
Multiple state level data, such as Washington's, indicate the protection from death with a booster, almost halving the rate in people age 65 and older.
The JN.1 variant took over globally and a number of subvariants (JN.1.11.1, JN.1.18,JN.1.13, JN.1.18) are showing up with added spike mutations such as R346T and F456L, but without signs of wastewater levels on the rise or other concerning metrics.
But BA.2.87.1, is the major "Omicron-like" event out there that has been the subject of five recent papers/preprints (here,here,here,hereandhere). That, in itself, should tell you it's a variant of interest. It's chock full of new mutations compared with the variants that came long previously, and many of these are deletions.
In itself, it is not a threat as there's no sign it is more immunoevasive or transmissible. In fact, the consensus is that it's less evasive of our immune response, the current booster works to achieve good levels of neutralizing antibodies, and some of the monoclonal antibodies that were previously found to be resistant to earlier variants may be effective again.That's great news. But as Yunlong Cao and his team appropriately warned us,"BA.2.87.1 may not become widespread until it acquires multiple [receptor binding domain] RBD mutations to achieve sufficient immune evasion comparable to that of JN.1."
It's much too early to know whether (and when) this will take place, but after 4 years if there's anything to predict, it is that the virus will find its way (through selection) to infect more hosts and repeat human hosts.
A big study was reportedyesterday that addressed the question of protection from COVID shots against blood clotsdeep vein thrombosis and pulmonary embolism, heart attacks, strokes, and heart failure. The data are from three countriesUK, Spain and Estonia, from electronic health records of over 20 million people. All these outcomes were reduced by prior COVID vaccination compared with no vaccination, especially in the first 30 days after an infection, but many showed durable protection out to 1 year follow-up (stroke, TIA, heart failure, DVT, PE).
This is different from the 40-50% protection of vaccinations vs long COVID symptoms. It's specifically addressing major cardiovascular outcome protection from being vaccinated. Major welcome news!
I remain very disappointed and surprised by the recent change (1 March) of CDC policy towards isolation, without regard to using rapid antigen tests.Their own data shows that at least 1 in 3 people will still be infectious at 5 days after symptom onset!That's by culturable virus, the gold standard, which tracks very closely with the rapid tests. To reduce infecting others, especially high risk vulnerable individuals, no less adding to the toll of long COVID, rapid tests should be used before people circulate.
Thanks for reading Ground Truths and please share the post to your network of friends and colleagues if you found it useful.
Study design and participants
We studied a cohort of 2111 participants (>18 years of age) who were recruited between 14 December 2021 and 29 September 2022 to the PerMed prospective observational study from all across Israel27,36. Of the 2,111 participants, 1932 participants reported receipt of>1 doses of the BNT162b2 mRNA COVID-19 vaccine, and 856 participants reported receipt of>1 doses of the influenza vaccine. Specifically, of the 1932 participants receiving COVID-19 vaccination, during the study, 146 received their first dose, 209 their second dose, 1545 their third dose, and 685 their fourth dose. Of the 856 participants who received influenza vaccination, 791 received the seasonal dose for 20212022, 188 received the seasonal dose for 20222023, and 125 received both seasonal doses. Participant recruitment was conducted via advertisements on social media and word-of-mouth. Each participant signed an informed consent form after receiving a comprehensive explanation of the study from a professional survey company. The participants were equipped with a Garmin Vivosmart 4 smartwatch and installed two apps on their smartphones: a dedicated mobile application (PerMed App), that collected daily self-reported questionnaires37, and an application that passively recorded the smartwatch data. Further information regarding data collection architecture and the PerMed dashboard is provided in our previous works13,25,27 and the Supplementary Material (Appendix B).
We hired a professional survey company to recruit participants as well as to keep them engaged throughout the PerMed study. The survey company was responsible for guaranteeing that the participants met the studys requirements, in particular, that they agreed to wear the smartwatch and fill in the daily questionnaires at least three times a week. We implemented several measures to minimize attrition and churn of participants and consequently improve the quality, continuity, and reliability of the collected data. First, participants who did not fill out the daily questionnaire by 7 p.m. received a notification in their mobile app to fill out the questionnaire. Second, a dedicated dashboard that allowed the survey company to identify participants who continually neglected to complete the daily questionnaires at least three times a week or did not wear their smartwatch for a long duration of time was developed. These participants were contacted by the survey company (either by text messages or phone calls) and were encouraged to better adhere to the study protocol. Third, to strengthen participants engagement, a weekly personalized summary report was generated for each participant and was available inside the PerMed application. Similarly, a monthly newsletter with recent findings from the study and useful tips regarding the smartwatchs capabilities was sent to the participants. At the end of the study, participants will receive all personal insights that were obtained and can keep the smartwatch as a gift.
After joining the PerMed study, participants filled out the enrollment questionnaire, and information on participants sex, age, and underlying medical conditions, was collected. The list of underlying medical conditions consisted of hypertension, diabetes, heart disease, chronic lung disease, immune suppression, cancer, renal failure, and body mass index (BMI)>30 (BMI is defined as weight in kilograms divided by the square of height in meters). Participants filled out a daily questionnaire through the PerMed mobile application27,36. The questionnaire allowed participants to report their signs and symptoms from a closed list of local and systemic reactionspreviously observed in BNT162b2 mRNA COVID-19 or influenza vaccines31,38, with an option to add other symptoms as free text. A detailed description of the questionnaire is provided in the Supplementary Material (Appendix A pp 68).
Participants were equipped with Garmin Vivosmart 4 smart fitness trackers. Among many physiological measurements, the smartwatch provides continuous measures of heart rate, stress, and daily resting heart rate capabilities39. Since the HRV measure is not accessible through Garmins application programming interface, we used Garmins stress level measure instead, which is computed based on the HRV measure40. HRV-based stress is a measure between 1 to 100 computed by Garmin and is categorized into four tiers: rest (125), low (2650), medium (5175), and high (76100)41. Specifically, the Garmin device uses heart rate data to determine the interval between each heartbeat. The variable length of time between each heartbeat is regulated by the bodys autonomic nervous system. Less variability between beats correlates with higher stress levels, whereas an increase in variability indicates less stress41,42,43. When we examined data collected in our study, we identified a heart rate sample approximately every 15s, a stress sample every 180s, and a daily sampling of resting heart rate.
We performed several preprocessing steps on the daily questionnaire data and smartwatch physiological measures before analyzing the data. For the daily questionnaires, if participants filled in the daily questionnaire more than once on a given day we considered only the last entry reported. For the HRV-based stress and heart rate measures collected by the smartwatches, we computed the mean value for each hour of data. Then, to impute missing values, we performed a linear interpolation. Finally, data was smoothed by calculating the moving average value using a 5-h sliding window.
For each participant, we defined the 7days before vaccination as a baseline period. For the analysis which involves self-reported questionnaires and for the machine learning model, we included only participants who filled out at least one questionnaire during the baseline period and at least one questionnaire during the 7days following vaccination. Those questionnaires are required to determine whether symptoms reported by the participants should be considered side effects. We defined a reaction as a post-vaccination side effect if it had not been reported during the baseline period. For the questionnaire data, we calculated the percentage and corresponding 95% CI of participants who reported new systemic reactions in the 7days following vaccination. We used a Beta distribution to calculate the 95% CI.
For the analysis involving smartwatch measurements, we included participants who had at least one overlapping period of data (i.e., the same day of the week and same hour during the day for the heart rate and HRV-based stress measures, and the same day of the week for the daily resting heart rate) during their baseline and post-vaccination periods. The overlapping periods are required for computing the change in measurement values between the baseline and post-vaccination periods. To calculate the changes in continuous Garmin smartwatch measurements (heart rate and HRV-based stress measures) over the 07days post-vaccination, with those of the baseline period, we calculated for each participant the difference between the measurement of each hour during the seven days post-vaccination and that of the corresponding hours in the baseline period (keeping the same day of the week and the same hour during the day). For the daily resting heart rate, we calculated the differences in the same manner (keeping the same day of the week). A Randomized control trial31, and prior studies analyzing physiological measures via smartwatches and self-reported questionnaires13, demonstrate a significant decrease in local and systemic reactions within 72h post-vaccination. Consequently, our classification problem focused on determining whether a moderate to severe reaction occurred within this 72h post-inoculation period.
Based on data from the Centers for Disease Control and Prevention, we stratified the participant-reported post-vaccination side effects by the severity of the reactions they reported in the questionnaire in the post-vaccination period by the appearance of symptoms, as follows:
No reaction
Mild reaction: abdominal pain, back or neck pain, feeling cold, muscle pain, weakness, headache, dizziness, vomiting, sore throat, diarrhea, cough, leg pain, ear pain, loss of taste and smell, swelling of the lymph nodes.
Moderate to severe reaction: fast heartbeat, hypertension, chest pain, dyspnea (shortness of breath), fever, confusion, and chills.
Participants were classified into one of the three categories, based on the most severe symptom that was reported in their post-vaccination period.
We stratified participants by the severity of their reactions. Participants who did not report a reaction, or had a Mild reaction following vaccination were classified in the No- or Mild-reaction group, and the remaining participants were classified in the Moderate to severe reaction group. We developed ML models to predict and detect the participant-reported side effect severity following COVID-19 or influenza vaccinations. The prediction model utilized sociodemographics, side effects from previous doses collected from questionnaires, and smartwatch information, but only before the vaccine, while the detection model also utilized the smartwatch measures 72h post-vaccination information.
The entire data set has been randomly divided into 5 separate non-overlapping test sets. For each test set, a model is trained using all the remaining data, ensuring an equal percentage of positive cases between train and test sets to take into account imbalanced positive and negative classes.
Several machine learning techniques were evaluated for both models: Gradient Boosted Decision Trees (XGBoost), Random Forest (RF), Multi-Layer Perceptron (MLP), and K-Nearest Neighbors (KNN).
The XGBoost package was used for training Gradient Boosted Decision Trees44, while the Scikit-learn machine learning library was used to implement the other models45.
Performances of the testing samples from each model are reported by mean AUROC, sensitivity (SE), and specificity (SP). SE and SP are defined as the fraction of positive and negative individuals correctly classified, respectively. These values are based on the point in the ROC that optimized the Youden index46,47. For each classifier, we applied a grid search within our stratified cross-validation framework and optimized our model selection using the mean AUROC.
The interpretable nature of the decision tree model allows for the evaluation of feature importance estimates48. The XGBoost in-model feature importance was used to demonstrate each predictor variables effect on the detection of the participant-reported side effect severity.
For evaluation of the differences in terms of AUROC, a bootstrap test (n=1000) for the difference was used. We repeatedly sampled the dataset with replacement in a stratified manner. We trained the prediction and detection models for each bootstrap sample and computed AUROC on the unique data points that were not selected in the current bootstrap sample. Each model is trained and tested with its subset features and the best hyperparameters. For each bootstrap sample, we computed the AUROC difference between the prediction and detection models and generated a distribution of bootstrapped differences. Finally, we calculated the p-value which is the proportion ofbootstrapped differences that is less than or equal to 0.
Before participating in the study, all subjects were advised, both orally and in writing, as to the nature of the study and gave written informed consent to the study protocol, which was approved by the Tel Aviv University Institutional Review Board (0002522-1). All methods were performed in accordance with the relevant guidelines and regulations.
A Pentagon watchdog review of the military's COVID-19 vaccine exemption process found that each of the branches largely complied with policies and, in some cases, even went beyond what was required to consider service members' requests for religious accommodation.
While rejecting a number of accusations that the services hadn't properly reviewed waiver requests, the Pentagon's inspector general did fault the Army and Air Force for taking too long to process the requests and wrote in a report released Thursday that discharges were inconsistent, leaving some service members with full benefits while others were left with partial benefits.
The exemption process became the subject of political and legal scrutiny amid the height of the pandemic after some service members filed legal challenges that ultimately made their way to the U.S. Supreme Court.
READ NEXT: Navy Fires Commander of USS Ohio -- 3rd Submarine Skipper Relieved in 7 Months
The investigation was kicked off in February 2022 after the inspector general "received complaints through the DoD Hotline between August 2021 and June 2022 alleging that the Military Services were improperly processing COVID-19 vaccination exemption requests," the report said. "We continued to receive complaints and, on June 2, 2022, the Acting DoD Inspector General issued a memorandum ... to the Secretary of Defense."
That memo told Defense Secretary Lloyd Austin that the watchdog "found a trend of generalized assessments" and "denial memorandums we reviewed generally did not reflect an individualized analysis."
It was an allegation that was key to the arguments of several court cases filed by service members that were largely successful in halting discharges over a refusal to comply with the policy.
However, the inspector general ultimately found no evidence that the services were "rubber stamping" denials, declaring that investigators "found no evidence of a lack of individual review by the decision authorities."
Investigators said that the officials that they interviewed discussed the cases "in detail," but they created approval and denial letter templates to both streamline the process and make sure all the required information was being conveyed to service members.
The allegations of "rubber stamping" even made it to at least one of the offices and prompted discussions among staffers about whether the wording should be altered. Ultimately, the unnamed office kept the templates out of a desire to provide consistency for the denials and out of a fear that more customized letters would suggest service members weren't all being reviewed under the same standard.
The report also noted at one point that some requests were considered by the services, even though they didn't need to be. The report cited four requests by Army soldiers whose chaplains "determined that four Service members did not have sincerely held religious beliefs to support a religious accommodation, as required by DoD policy."
"In each case, the Army decision authority stated that they considered the Service member's request regardless of the chaplain's assessment," the report said.
The Army and Air Force's delays in meeting their 90- and 30-day processing deadlines, respectively, were chalked up to the large volume of requests -- more than 16,000, as of January 2023.
Out of the requests reviewed by the inspector general, the Army's cases averaged 192 days to receive a decision while the Air Force's requests averaged 168 days.
Staffers in the offices that typically handle exemption requests told investigators that they normally handled just a few requests per year and on simpler topics such as grooming or clothing -- not something as complex as vaccinations.
Investigators also faulted the services for discharging service members under varying discharge types or reentry codes. While the report explained that "this occurred because the DoD did not have department-level guidance requiring uniformity," they nevertheless pointed out that "service members experienced different impacts to their educational benefits and eligibility to reenlist in military service after discharge."
The report recommended that the Pentagon review its exemption process to try to increase its efficiency "during periods of high-volume requests" and create a better policy to standardize reentry codes. It also noted that both recommendations were accepted by the Defense Department, which has already begun making changes.
Related: Military Services Will Amend COVID Vaccine Refuser Records So They Aren't Passed Over for Promotions
Canadas National Advisory Committee on Immunization has published guidance on the use of Nuvaxovid XBB.1.5, a recombinant protein subunit COVID-19 vaccine, in Canada. The recommendations state that Nuvaxovid XBB.1.5 can be used in unvaccinated or previously vaccinated individuals aged 12 years and older.
This recommendation supports efforts to provide greater access to a non-mRNA protein-based COVID-19 vaccine option and could help achieve improved immunization rates. The vaccine has been distributed by the Public Health Agency of Canada across the regions, and provincial public health programs can advise on specific availabilities.
Data from clinical trials continue to show broad neutralization responses to currently circulating forward-drift variants including JN.1 and JN.4 for our protein-based non-mRNA COVID-19 vaccine, while maintaining a favorable side effect profile. Peer-reviewed real-world effectiveness data is being published that shows the immune responses seen in our trials translates into COVID-19 prevention in the real world.1
References:
1. Link-Gelles R, et al. Early Estimates of Updated 20232024 (Monovalent XBB.1.5) COVID-19 Vaccine Effectiveness Against Symptomatic SARS-CoV-2 Infection Attributable to Co-Circulating Omicron Variants Among Immunocompetent Adults Increasing Community Access to Testing Program, United States, September 2023January 2024. MMWR. 2024; accessed online February 28, 2024, at https://www.cdc.gov/mmwr/volumes/73/wr/mm7304a2.htm?s_cid=mm7304a2_w
Image Credits: Brian Lawless / PA Images / Getty Images
Two years ago, the Irish government fixed a vulnerability in its national COVID-19 vaccination portal that exposed the vaccination records of around a million residents. But details of the vulnerability werent revealed until this week after attempts to coordinate public disclosure with the government agency stalled and ended.
Security researcher Aaron Costello said he discovered the vulnerability in the COVID-19 vaccination portal run by the Irish Health Service Executive (HSE) in December 2021, a year after mass vaccinations against COVID-19 began in Ireland.
Costello, who has deep expertise in securing Salesforce systems, now works as a principal security engineer at AppOmni, a security startup with a commercial interest in securing cloud systems.
In a blog post shared with TechCrunch ahead of its publication, Costello said the vulnerability in the vaccination portal built on Salesforces health cloud meant that any member of the public registering with the HSE vaccination portal could have accessed the health information of another registered user.
Costello said the vaccine administration records of over a million Irish residents were accessible to anyone else, including full names, vaccination details (including reasons for administering or refusals to take vaccines), and the type of vaccination, among other types of data. He also found internal HSE documents were accessible to any user through the portal.
Thankfully, the ability to see everyones vaccination administration details was not immediately obvious to regular users who were using the portal as intended, Costello wrote.
The good news is that nobody other than Costello discovered the bug, and the HSE kept detailed access logs that show there was no unauthorised accessing or viewing of this data, per a statement given to TechCrunch.
We remediated the misconfiguration on the day we were alerted to it, said HSE spokesperson Elizabeth Fraser in a statement to TechCrunch when asked about the vulnerability.
The data accessed by this individual was insufficient to identify any person without additional data fields being exposed and, in these circumstances, it was determined that a Personal Data Breach report to the Data Protection Commission was not required, said the HSE spokesperson.
Ireland is subject to strict data protection laws under the European Unions GDPR regulation, which governs data protection and privacy rights across the EU.
Costellos public disclosure marks more than two years since first reporting the vulnerability. His blog post included a multi-year timeline revealing a back-and-forth between various government departments that were unwilling to take claim to public disclosure. He was ultimately told that the government would not publicly disclose the bug as though it never existed.
Organizations are not obligated, even under GDPR, to disclose vulnerabilities that have not resulted in a mass theft or access of sensitive data and that fall outside of the legal requirements of an actual data breach. That said, security is often built off the knowledge of others, especially those who have experienced security incidents themselves. Sharing that knowledge could help prevent similar exposures at other organizations that might otherwise go unaware. This is why security researchers tend to lean toward public disclosure to prevent a repeat of mistakes from yesteryear.
Epilepsy was linked to a significantly increased the risk for hospitalization and death from COVID-19 early in the pandemic, while healthcare utilization rates in this patient population declined, data from two linked studies showed.
Results showed that individuals with epilepsy had a 60% higher risk for hospitalization and a 33% higher risk of dying from COVID-19 than those without the disorder. However, during the pandemic, the number of hospitalizations and ER visits by people with epilepsy dropped by as much as 30%.
"The neurotropic effects of Sars-CoV-2 might explain some of this increased risk for people with epilepsy, or epilepsy might be associated with alterations in the immune system, predisposing to more severe COVID-19," the investigators, led by Owen Pickrell, MBBChirm, PhD, Swansea University, United Kingdom, wrote.
The findings were published online on March 5, 2024, in Epilepsia.
Epilepsy is one of the most common neurological conditions and affects approximately 50 million people worldwide, with significant comorbidity and an increased risk for early death.
During the pandemic, clinicians treating people with epilepsy and other conditions shifted their skills to treat an ever-increasing number of patients with COVID-19, which may have hindered epilepsy-specific services for a time.
To further explore how the COVID-19 pandemic may have affected the health of this patient population, researchers analyzed health records from a large database with information about hospital admissions, primary care visits, COVID-19 vaccination status, and demographics of 90% of Welsh residents.
Those living with epilepsy before or during the study period (March 1, 2020, to June 31, 2021) were identified and compared with controls without epilepsy.
The analysis included approximately 27,280 people with epilepsy and 136,400 matched controls. Among those with epilepsy, there were 158 deaths (0.58%) and 933 hospitalizations (3.4%). In comparison, there were 370 deaths (0.27%) and 1871 hospitalizations (1.4%) in the control group.
Unadjusted analyses showed the risk of dying from COVID-19 for those with epilepsy vs controls was more than twofold higher (hazard ratio [HR], 2.15; 95% CI; 1.78-2.59) and the increase in the risk for hospitalization was similar (HR, 2.15; 95% CI; 1.94-2.37).
After adjusting for 40 comorbidities, including serious mental illness, asthma, and diabetes, those with epilepsy had a 60% increased risk for hospitalization (adjusted HR [aHR], 1.60) and a 33% increased risk for death (aHR, 1.33) than those without epilepsy (all P < .0001).
The findings "may have implications for prioritizing future COVID-19 treatments and vaccinations for people with epilepsy," the investigators wrote.
Study limitations included the inability to account for the effect of vaccinations or prior infections with SARS-CoV-2. Moreover, the study did not account for geographical or temporal variations in prevalence and COVID-19 variants.
In the related study, researchers analyzed healthcare utilization by people with epilepsy before and after the pandemic using the same database. Results showed hospital admissions, ER visits, and outpatient visits significantly decreased during the pandemic.
In the year before the pandemic, people with epilepsy had double the rate of ER visits (rate ratio [RR], 2.36), hospital admissions (RR, 2.08), and outpatient appointments (RR, 1.92) compared with matched controls.
However, during the pandemic there was a greater reduction in hospital admissions (RR, 0.70; 95% CI, 0.69-0.72) and ER visits (RR, 0.78; 95% CI, 0.77-0.70) in those with epilepsy vs matched controls (RR, 0.82; 95% CI, 0.81-0.83) as well as hospital visits and ER visits (RR, 0.87; 95% CI, 0.86-0.88; all P < .0001). New epilepsy diagnoses also decreased during the pandemic (RR, 0.73; P < .0001)
The redeployment of epileptologists during the pandemic also meant that epilepsy
consultations and investigations were canceled, making it harder for people with epilepsy to access specialty care, the researchers noted.
"Our research also showed that there were fewer new diagnoses of epilepsy and fewer contacts with health services by people with epilepsy, during the period we examined," Huw Strafford, lead data analyst for the studies, said in a release.
Both studies were funded by Health and Care Research Wales. Pickrell reported receiving speaker fees from UCB Pharma and Angelini Pharma, travel grants from Angelini Pharma, and an unrestricted grant from UCB Pharma.
