A Morrisville mother told WRAL News her 5-year-old received an accidental double-dose of Moderna's new COVID-19 vaccine.
This comes as the Food and Drug Administration alerted parents and health providers that children under the age of 11 may receive the incorrect dose of Moderna's updated COVID-19 vaccine -- but said the dosage is not believed to be dangerous.
The FDA said health providers may be confused over the dosage of the vaccine, which is available to children as young as 6 months of age.
According to the FDA, a single vial of Moderna's current vaccine for children 6 months to 11 years old contains "notably more" than the 0.25 mL dosage children should receive.
Pediatricians and health providers should withdraw 0.25 mL from the vial and discard the rest, the FDA said.
The FDA said it has has not identified any safety risks associated with administration of the higher dose in children. No adverse or serious reactions have been connected to dosing errors.
In a statement sent to WRAL News, the FDA said it "actively working with Moderna to communicate with healthcare providers to ensure the correct dosage of vaccine is administered in individuals 6 months through 11 years of age."
Roberts said her 5-year-old daughter received the vaccine on Oct. 18. Later, she got a call from her pediatrician's office.
"They called and said, we just want to let you know that we made a mistake while giving your daughter the vaccine. We gave her a double dose instead of a single dose," Roberts said.
Roberts said her daughter had a fever of 102.5 degrees for about 12 hours after she got her shot.
"She felt really bad and then her symptoms went away," Roberts said.
Roberts encourages other parents to ask their children's vaccine provider to double check their dosage.
"I understand human error, but this is not like you ordered too many tablecloths or something," she said. "You injected something into my child that you cant get out now.
Healthcare providers, parents and caregivers who have questions may contact FDAs Center for Biologics Evaluation and Research at ocod@fda.hhs.gov.
US workers ill with influenza or COVID-19 were less likely to work onsite than those with other acute respiratory infections (ARIs) after the pandemic than before, concludes a study led by Centers for Disease Control and Prevention (CDC) researchers.
For the study, published yesterday in Emerging Infectious Diseases, the researchers analyzed data from participants in the seven-state US Influenza Vaccine Effectiveness Network who had ARIs from 2018 to 2022.
Participants, who were aged 19 to 64 years, completed a follow-up survey 1 or 2 weeks after enrollment and were asked about their health and work. Network sites were located in Michigan, Pennsylvania, Texas, Washington, California, Wisconsin, and Tennessee.
During the pre-COVID flu seasons, 1,245 people had confirmed flu and 2,362 had other ARIs. During the pandemic, 114 people had flu, 1,888 had COVID-19, and 2,523 had other ARIs. Among those with any ARI, 82.6% with flu, 61.4% with COVID-19, and 49.6% with other ARIs reported having fever.
Of all participants, 14.0% had worked only remotely before illness, 18.5% had hybrid experience, and 67.5% had worked onsite only.
On the third day of illness, 18.5% of participants worked remotely during the pandemic, compared with 8.8% before. In prepandemic flu seasons, 64.4% of workers with flu and 40.3% of with other ARIs worked offsite. Amid the pandemic, 66.7% of employees with COVID-19 and 48.3% with other ARIs didn't go to work.
Hybrid and remote work policies might reduce workplace exposures and help control spread of respiratory viruses.
Relative to employees without hybrid work experience, those who worked remotely were significantly more likely to telework, an effect more pronounced amid COVID-19 than during prepandemic flu seasons. In contrast, workers who had worked only onsite were more likely to not work at all on their scheduled days.
Employees with COVID-19 or flu were less likely to go to work than people with other ARIs. Few people who tested positive for COVID-19 by the second or third day of symptoms worked onsite.
"Hybrid and remote work policies might reduce workplace exposures and help control spread of respiratory viruses," the authors wrote.
Study setting
The QENSIU is Scotlands sole centre for treating TSCI. Information about the Units creation and funding has been previously described [10]. In 2019, the last full calendar year prior to COVID-19 reaching the UK, 41% of patients were admitted to the QENSIU within 48h of injury, with 66% of all patients admitted within one week [11]. It is assumed all TSCIs that occur in Scotland will eventually be admitted to the QENSIU. Details of the aetiology, gender, age injury level and severity of all new admissions are entered into the QENSIU database. The database does not include information about people who die due to TSCI prior to admission.
Approval for the collection and evaluation of data within the database was granted by the Data Custodian for the Queen Elizabeth University Hospital, Glasgow, Scotland.
All patients admitted to the QENSIU during the study period (1st January 2015 to 31st August 2022) were ascertained from the clinical database. The neurological level of injury and degree of impairment after TSCI was assessed by a Consultant in Spinal Injuries on admission and defined according to the International Neurological Classification of Spinal Injury using the American Spinal Injury Association Impairment Scale (AIS) [12]. Patients who were neurologically intact, and who were recorded as an AIS E on admission, were excluded along with those under 16 years of age. TSCI aetiology was classified in accordance with the International SCI core data set as assault, fall, transport, sports and leisure (including cycling for consistency with previous work [10] and falls that occurred during sporting activities, such as rock and mountain climbing) and other traumatic (deliberate self-harm (DSH), iatrogenic [13], and industrial) [14].
All data were analysed according to the level of restrictions placed on the public at that point in time. Scotland saw four different levels of lockdown applied during the COVID-19 pandemic, with Level 1 being the least severe and Level 4 being the most severe (equivalent to a full population-level lockdown) [15]. These levels are summarised in Fig.1. January 2015 to 31st March 2020 inclusive were denoted as the pre COVID-19 period, while September 2021 to August 2022 was classified as the post COVID-19 period. Incidence per million was calculated by comparing the incidence of TSCI in a calendar year with the corresponding years midyear population estimate [16]. As data was not yet available for 2022, the 2021 midyear population estimate was also used for 2022.
Periods of COVID-19 associated lockdowns are shown in grey dashed line. Level 0=no lockdown measures. Level 1=Restrictions on indoor meetings between households (maximum of 6 people from 2 households). Level 2=As level 1, plus no indoor meeting with other households with restrictions also placed on outdoor meetings (maximum of 6 people from 2 households). Level 3=As level 2, plus no alcohol sales indoors and outdoors with hospitality venues all to close by 6pm. Level 4=As level 3, plus closure of all non-essential shops, hospitality venues and gyms. The population is encouraged to only leave home for essential reasons (shopping, health care appointments etc). Equivalent to a full population-level lockdown.
Poisson regression models were used to examine the number of monthly TSCIs, adjusted for age, sex, year, season, tetraplegia, and injury completeness. The level of Covid-19 was the primary exposure variable. There is no evidence of over-dispersion. The model residual deviance/degrees of freedom was 1226.4/1462=0.84. This indicates mild under-inflation which could lead to slightly conservative standard error estimates. Year and month were initially modelled as penalised cubic splines in the generalised additive model framework as a preliminary analysis. The model revealed linear association for a year and non-linear association for a month (Supplementary Figure.1). The Month variable was categorised into seasons (December-February; March-May; June-August; September-November) based on the inflection points in the spline. The exposure variable was collapsed into a binary variable: No restriction to level 2; level 3 and 4 restrictions. Additive interactions between Covid-19 restrictions and: age (<45 vs. >=45), sex (female vs. male), tetraplegia, and complete injury were examined using relative excess risk due to interaction (RERI). Under this model, we estimated the counterfactual number of SCI cases as if level 3 and 4 restrictions did not occur. These, compared with the observed SCI cases, were used to estimate the number of reduced SCI cases due to COVID-19. Incidence was also analysed with a supplementary exposure variable of COVID-19 Stringency Index [17]. This score is a measure of lockdown level summated over 9 domains - school closures; workplace closures; cancellation of public events; restrictions on public gatherings; closures of public transport; stay-at-home requirements; public information campaigns; restrictions on internal movements; and international travel controls. The index is calculated as the mean score of the nine metrics, each taking a value of between 0 and 100. A higher score indicates a stricter response (i.e. 100=strictest response). If policies vary at the subnational level, the index is shown as the response level of the strictest sub-region. The incidence of deliberate self-harm was described in different periods since there was not sufficient power to conduct a formal analysis. R Statistical Software (version 4.2.2) was used with packages mgcv and interactionR. Descriptive data are presented as means plus standard deviations or 95% confidence intervals [14, 18]. Incidence rate ratio (IRR) and 95% CI were used to infer associations and their corresponding precision.
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NORTH DAKOTA (KXNET) According to the CDC, COVID-19 vaccines help our bodies develop immunity to the virus that causes COVID-19 without us having to get the illness, and, in some areas COVID vaccines are required for employees, working for large businesses.
So, should the government be able to mandate said vaccines? This question for our major political parties, starts a fire.
Theres certainly people who disagree with me, and I respect that, thats fine. But its such a farce this whole thing that, and you know, what baffles me a little bit is, the Democrats used to be the party that complained about the big corporations. And I think weve been had by the big pharmaceutical companies, its a revolving door between the pharmaceuticals and the FDA and the CDC. I wish I had a product that I could get the government to force people or convince people to take thats invisible and create as much fear as they have, said Minot Senator, Jeff Hoverson.
Senator Hoverson says reports show that vaccines do more harm than good.
Just take the Veritas report, for example, which is underreported, by the way, 35,000 deaths, in one year from the COVID vaccine, said Sen. Hoverson.
As for our states Democratic party, they believe corporations should have the freedom to decide whether they require vaccines for their workers or if they dont.
We have found that many healthcare organizations like hospitals and long-term care organizations have found that its important to ensure that their employees are safe themselves and also not spreading the virus to the patients that they might be treating, said Fargo Senator, Karla Rose Hanson.
But, what about children, do they think the government should require that children be vaccinated against COVID-19?
Absolutely not, and, you know, I think people need to know as well that in 1986, our government cant remember what its called now. But theres an act of Congress that removes liability for pharmaceuticals, so vaccines are the only drug so to speak, that you cant sue the manufacturer for all the other drugs. And if they ever do get a court case, and a pharmaceutical does lose. Guess who pays for it? The taxpayer. So I dont know where anybody could find any ounce of freedom in that, said Sen. Hoverson.
Fargo Senator Josh Boschee responded by stating that, here in North Dakota, there is no mandate for COVID or any other vaccines.
We actually have the most, its been said by the medical profession, liberal policy, because families are able to opt out for a variety of reasons more than the reasons in many other states. So I think it should be a family decision, I think in consultation with their health care provider on whether children are vaccinated, said Sen. Boschee.
But you have to be able to make a decision on something thats not a fabrication. So thats why I dont think its fair to compare the COVID vaccine today to the polio vaccine back then, because I think when they actually did vaccines, they actually really did do what was in the best interest of the people. Thats not the case anymore, and we got to quit believing that it is. In my opinion, because theyre not, they dont have the person in mind informed consent is not there. And theres adverse incentive, said Sen. Hoverson.
Now lets shift a bit, we asked the panel, how they propose to address the rising healthcare costs, including the cost of prescription medications.
Well, we did have a bill that actually did control the price of insulin for state workers at least. And so these pharmaceutical companies are out of line, in my view, on many of their costs, because they, as was said earlier, they have no liability when someone gets sick from their product, but yet they are charging a huge amount of money for I mean, its crazy what theyre charging for some of these pills that people are taking or some of the shots, said Hazelton Senator Jeff Magrum.
State Senator Karla Rose Hanson says the cost of health care is a major issue for North Dakota families.
I think some of the solutions, its obviously a multi-pronged issue. Some of the issues that could help with that is at the federal level. President Biden has recently put forward the idea of negotiating on the highest-cost drugs that Medicare pays for. Our older Americans take a lot of drugs and being able to negotiate with the pharmaceutical companies on the cost of those drugs for these public health care plans will be a huge cost saver, said Karla Rose Hanson.
With more than 60 million people living in rural America, just today the Biden Administration announced its plan to take action to improve the health of rural communities and help rural healthcare providers stay open.
A piece of that puzzle includes Building on the Affordable Care Act and Inflation Reduction Act to increase access to affordable health coverage and care for those living in rural communities.
Compliance with guidelines
We observed that, regardless of their profiles, contact tracers did not always rigorously follow contact tracing guidelines (positive agreement of 0.53 and negative agreement of 0.70). If the guidelines had been followed, we would have expected a PA and NA close to 1. There are several possible explanations for this lack of agreement:
Tracers may have deliberately not followed the guidelines after making their own assessment of the risk of infection. Indeed, it was observed during the pandemic that doctors might have been reluctant to apply externally imposed requirements concerning the provision and prioritization of patient care [9].
They may not have known the guideline criteria.
Participants may have erroneously reported the decision of the contact tracer and/or the guideline-based risk classification. We cannot verify this as self-reporting was the only data source used for this study.
Interviewed contacts may have deliberately offered selective information to the contact tracer as a result of mistrust or to obtain benefits associated with a particular contact classification. Mistrust is one of the obstacles to contact tracing described by Megnin-Viggars et al. [10] In their study, several obstacles to efficient contact tracing are identified at the level of the person being traced, not at the level of the contact tracer making their assessment, which is where the current study provides novel insights.
Respondents may have erroneously filled out the questionnaire, e.g. due to lack of attention or recollection bias.
Addressing these obstacles may improve the effectiveness and efficiency of contact tracing by making it more comprehensive and better targeted at individuals at highest risk of infection. Our study was observational, we did not find much literature on the actual implementation of contact tracing strategies. We therefore believe that our results can help to address the gap in knowledge on this topic.
Comparing the PA and NA results of the different contact tracers profiles reveals that they do not vary significantly from one profile to another. Our study does not, therefore, suggest that any of the profiles included applied the guideline criteria differently to the other profiles.
The secondary attack rate among contacts classified as HRCs by the contact tracers was 29%, which is higher than what we found in the literature [11,12,13] but comparable to the results of 27% found by Proesmans et al. who studied the performance of contact tracing in Belgium [14]. Our methodology made it possible to verify whether contact classification as high risk and low risk was useful, by comparing the infection risk in both groups. A Poisson regression found that the infection risk for HRCs was significantly higher than for LRCs. The RR between both groups was, at 3.1 for classifications by the contact tracer, which was significantly greater than for guideline-based classifications, for which the RR was 2.2. Contact tracers may thus have applied criteria that are not included in the definition of a HRC to assess the contacts risk of infection. They also may have had access to additional information for processing their case (existence of a cluster in the company, access to the quantitative results of the index cases PCR test, which may have suggested high viral shedding [15], etc.). We did not come across any research that used the same methodology as ours to calculate the RR of infection between HRCs and LRCs. Several studies, however, have applied a similar methodology to compare positivity rates among HRCs and LRCs. Sahoo et al. [16], Velhal D et al. [17] and Sharma et al. [18] collected information about 3411, 1486 and 1430 health care workers respectively. They were classified as HRCs and LRCs. Sahoo et al. obtained positivity rates of 3.8% for HRCs and 1.9% for LRCs. Velhal D et al. obtained positivity rates of 9.01% for HRCs and 2.72% for LRCs. Sharma et al. obtained positivity rates of 19.5% for HRCs and 0.6% for LRCs. We observe that their contact classification was similar and based on the CDC criteria. Risk stratification in contact tracing was found to be effective, however as it was in our study, even though the risk ratio was not calculated in these studies. Their positivity rates are lower than ours which could be attributed to the timing of the data collection (less contagious variants) and the limitations of our study. While they focused on populations of healthcare workers, we opted to include other professional fields.
The third variable, potential immunization, was included because we suspected that it would reduce transmission risk, as has been described [19, 20], which could have biased our results. Surprisingly, the Poisson regression showed the opposite, with an RR of 2.0 for potentially immune participants compared to non-immune participants. Numerous factors could explain this inconsistency. Our criteria for potential immunization were broad and probably resulted in the inclusion of non-immune participants. Furthermore, we cannot be certain that participants considered to be non-immune were indeed not immune, as case under-ascertainment was common during the first waves of COVID-19 infections [21]. Potentially immune healthcare workers may have been assigned to COVID-19 units, thus being at higher risk of infection but also were more often vaccinated and more intensely screened than other respondents were. Potentially immunized workers may have taken more risk in relation to exposure to others as a consequence of feeling protected from infection and severe disease [22]. The emergence of the Delta variant may have partially neutralized the protection offered by the vaccine against infection [23].
We specifically evaluated the risk classification of contacts and found it to be useful for identifying individuals at high risk of infection. We also demonstrated that targeting of testing is improved when a knowledgeable tracer performs the risk assessment.
Our study has several limitations. It was retrospective and based on an anonymous online survey, both factors which may have reduced the accuracy of the data. Participants could stop filling out the questionnaire at any time, which may also have reduced accuracy and completeness. Although participants received information describing the subject of the study in their email, this information may have led to a selection bias.
Healthcare workers were overrepresented in the study population. This is unsurprising because the organization through which participants were recruited (CESI) is particularly active in this sector, and healthcare workers were probably more exposed to COVID-19, leading to more COVID-19 contacts at work [24]. Stratification by job category would have been useful as risk differs significantly from one field to another. It was unfortunately not feasible due to the sample size.
The questionnaire was created during the first half of 2021, shortly after the start of vaccination and before the administration of booster doses. For this reason, we defined vaccination status rather broadly.
Furthermore, in the section concerning compliance, results for individuals traced by someone else or no one should be interpreted with caution, as many individuals in this category answered I dont know to the question about their contact classification. This latter answer was an exclusion criterion. There was therefore a selection bias that may have influenced the PA and NA.
Finally, the respondents knew the results of their test following contact, which may have had an impact on their questionnaire answers. For example, participants who tested positive may have seen the risk as greater when they replied to the questionnaire than when they responded to the contact tracer. This may have had an impact on both the calculation of the PA/NA and the comparison of the infection risk of HRC and LRC, as per contact tracer and guideline-based classification.
November 03, 2023
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Patients with asthma who were hospitalized for COVID-19 had less severe disease and lower mortality rates than patients with no airway disease, according to a study published in The Journal of Allergy or Clinical Immunology: In Practice.
However, patients with COPD who were hospitalized for COVID-19 had more severe disease and higher mortality rates than those with no airway disease, Yunqing Liu, MS, PhD, department of biostatistics, Yale School of Public Health, and colleagues wrote.
The study examined data from 8,395 patients admitted to Yale New Haven Health System between March 1, 2020, and April 1, 2021, for COVID-19. These patients included 969 with asthma, 1,132 with COPD, 768 with both asthma and COPD and 5,526 with no airway disease.
The 11.5% prevalence of asthma in this population was comparable with the 10.5% prevalence of asthma throughout Connecticut, the researchers said. COPD prevalence included 13.5% in the study cohort and 6.1% in the state, indicating increased risk for hospitalization for COVID-19 for patients with COPD, the researchers continued.
Patients with no airway disease had a median sequential organ failure assessment (SOFA) score of 0.32. Comparatively, patients with asthma had a significantly lower median SOFA score, at 0.15 (P < .01), and the patients with COPD had a significantly higher median score, at 0.86 (P < .01).
Compared with the absolute mortality rate of 11% among those with no airway disease, patients with asthma showed a significantly lower rate at 5%, whereas those with COPD showed a significantly higher rate at 21% (P < .01 for both). However, at 14%, the absolute mortality rate among those with asthma and COPD did not significantly differ from the no airway disease group, suggesting that asthma and COPD may have offsetting effects on the severity of COVID-19, the researchers wrote.
Specifically, compared with the no airway disease group, a multivariate logistic regression analysis showed patients with asthma had 35% lower adjusted odds for mortality of COVID-19 (OR = 0.65; 95% CI, 0.48-0.89) whereas patients with COPD had 40% higher odds for mortality (OR = 1.4; 95% CI, 1.16-1.67).
Patients with no airway disease and those with both asthma and COPD had comparable odds for mortality (OR = 0.99; 95% CI, 0.77-1.26), further suggesting that asthma may offset the risk for severe COVID-19 among patients with COPD, the researchers wrote.
Further, the researchers found significant associations between mortality and higher total white blood cell counts, immature granulocyte counts and neutrophil counts in all four disease groups.
Elevated blood eosinophil counts, which the researchers noted are biomarkers of T2 inflammation, were associated with lower risks for mortality in all four disease groups, especially for patients with asthma. Also, patients with asthma, including those with both asthma and COPD, had higher levels of eosinophils on admission.
Specifically, after adjusting for cofounders, patients with absolute eosinophil counts of 200 cells/L or higher had lower odds for mortality compared with patients with lower eosinophil counts (OR = 0.52; 95% CI, 0.33-0.8).
But after adjusting for eosinophil levels, these differences in mortality between the groups persisted, including an odds ratio of 0.67 (95% CI, 0.49-0.92) for the asthma group and 1.38 (95% CI, 1.15-1.66) for COPD, indicating that peripheral eosinophilia does not fully explain the protection associated with asthma, according to the researchers.
Noting significant differences in exposure to systemic corticosteroids between the groups, the researchers also found an overall increase in mortality associated with IV methylprednisolone therapy (OR = 4.77; 95% CI, 3.69-6.17), which they called expected due to its selective use in patients with severe COVID-19.
Yet multiple regression analysis adjusted for exposure to systemic corticosteroids still showed a significant increase in mortality among patients with COPD and a significant decrease in patients with asthma and eosinophilia.
Patients at risk for severe COVID-19 require more intensive mitigation strategies such as social distancing, vaccine boosters and early outpatient pharmacotherapy, the researchers wrote, making their identification critical.
Based on these results, patients with COPD are at higher risk for severe COVID-19 and patients with asthma are at lower risk, the researchers continued. These differences may be due to protection conferred by T2 inflammation, the researchers added, but further clinical and mechanistic studies would be needed to confirm this association.
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Liu Y, et al. J Allergy Clin Immunol Pract. 2023;doi:10.1016/j.jaip.2023.07.006.
Disclosures: Liu reports no relevant financial disclosures. Please see the study for all other authors relevant financial disclosures.
Denisa E. Ferastraoaru, MD
One of the most interesting findings is that differences in mortality between patients with asthma and COPD persisted even after adjustment for serum eosinophil counts. This suggests that peripheral eosinophilia might not be the main nor the only factor associated with lower mortality of COVID-19 in patients with asthma.
This might explain why patients with asthma on biologics working on the T2 pathway do not have worse COVID-19 outcomes than those not on monoclonal biologics. Likewise, COPD worsened outcomes even among those with high eosinophil counts. This demonstrates fundamental differences between asthma and COPD.
The results that COVID-19 patients with higher absolute eosinophil counts (greater than 200 cells/L) had lower odds of mortality compared with those with lower serum eosinophil levels are similar with our prior published data in our Bronx asthmatic population.
Since the beginning of the pandemic, we noticed that our patients with asthma do better in terms of COVID-19 outcomes compared with those who do not have asthma. Even now, 3 years after the COVID-19 pandemic started, we cannot fully explain these observations. However, clinical and mechanistic research studies have emerged since that hopefully will shed more light in this field.
It is possible that the differences in lung inflammation in those with pre-existing asthma and pre-existing COPD are important in COVID-19 outcomes, as well as the age and associated comorbidities. It is known that COPD patients are older, a factor that is associated by itself with worse COVID-19 outcomes.
Although at this time there are no differences in the way we treat COVID-19 patients with asthma and COPD, current findings suggest that COVID-19 prevention strategies and early outpatient treatment for SARS-CoV-2 infection should be implemented with priority for patients with COPD.
Although there is overlap in the medications used to treat these chronic respiratory conditions, this is a clear demonstration of how these two differ. Characterizing respiratory disease accurately as asthma or COPD is important to risk assess patients and to provide them anticipatory guidance.
The exact mechanism through which patients with asthma have lower odds for dying of COVID-19 is not clear. More data are also needed to identify if the odds for mortality of COVID-19 vary based on other allergic disorders, such as allergic rhinitis, rhinosinusitis and atopic dermatitis. Identifying these mechanisms might develop into new treatment and preventative modalities.
It is important to extend this observation to other respiratory viral infections. Does eosinophilia help prevent other viral asthma or COPD exacerbations? We need to understand if eosinophils are the cells that help fight or prevent serious COVID-19 infections. Alternatively, they could be markers of a milieu that is unfavorable to COVID-19. Understanding how the eosinophilic state reduces COVID-19 morbidity and mortality is an important next step.
Manish Ramesh, MD, PhD, associate professor and chief of the division of allergy-immunology, Albert Einstein College of Medicine/Montefiore Medical Center, also contributed to this Perspective.
Reference:
Ferastraoaru DE, et al. J Allergy Clin Immunol Pract. 2021;doi:10.1016/j.jaip/2020.12.045.
Denisa E. Ferastraoaru, MD
Associate Professor, Allergy-Immunology, Albert Einstein College of Medicine/Montefiore Medical Center
Disclosures: Ferastraoaru reports no relevant financial disclosures.
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A new investigation led by researchers from the University College London and Dartmouth College suggests 14% of Americans had long COVID by the end of 2022. The details of the investigation are published in PLOS One.
Moreover, Americans who report having experienced long COVID said they also experienced more anxiety, low mood, and difficulty with memory.
All data was based on 461,550 respondents to the US Census Bureaus Household Pulse Survey, conducted from June 2022 to December 2022. Researchers compared survey answers among those who said they have had long COVID, those who said they have had COVID-19 but no lingering symptoms, and those who had never had COVID-19.
Forty-seven percent of survey respondents said they had been previously infected with COVID-19. Of those,13.3% said they had suffered "severe symptoms" during their illness. For people who had COVID that resolved within 3 months, only 7% said they had severe symptoms, compared with 24% for those who had had long COVID in the past and 31% who currently had long COVID.
Little is known about long Covid and its impact on health and wellbeing.
Among the 14% who said they had experienced long COVID, 7% said they were currently experiencing ongoing symptoms.
"Little is known about long Covid and its impact on health and wellbeing, but there is a growing body of evidence that many people experience persistent and concerning symptoms," study co-author Alex Bryson, PhD, MSc, of the University College London Social Research Institute, said in a press release.
In general women were more likely than men to report long COVID, as were people with lower education levels. The highest rate of long COVID was in West Virginia (18% of the population) and the lowest in Hawaii (11%).
Long COVID was independently associated with low mood, especially anxiety.
"Those who have ever had long Covid remain more likely to report low mood, challenges in carrying out daily tasks, and challenges with memory, concentration and understanding, compared to people who have never had long Covid," said Bryson.
In related news, researchers have reached an agreement on how best to measure the severity and impact of long COVID by identifying a "Core Outcome Measure Set" (COMS), according to a new report published in the Lancet Respiratory Medicine.
Different countries, public health agencies, and clinics have shifting guidelines for how to identify and classify long COVID, with most relying on the World Health Organizations assessment that a long COVID patient must suffer new or ongoing symptoms at least 12 weeks after initial infection.
In the present report, 594 individuals from 58 countries participated in an online consensus meeting to develop the COMS. Twelve core outcomes for long COVID patients were identified, including fatigue or exhaustion, pain, post-exertion symptoms, work or occupational and study changes, and cardiovascular, nervous system, cognitive, mental health, and physical outcomes.
"This research has significantly narrowed down the range of preferred outcome measurement instrument options for researchers and clinicians to consider, said Paula Williamson, PhD, of the University of Liverpool in a press release.
COMS is the first step to developing long COVID treatments, the authors said, because it allows for clinicians to develop measurement tools to codify symptoms.
Breaking ground on the Meadowbrook Park COVID-19 Memorial and planting the first of forty-two native Dura-Heat River Birch Multi-stem trees, November 3, 2023 at Meadowbrook Park in Ellicott City. (Left to right) Johns Hopkins Howard County medical Center Vice President of Medical Affairs / Chief Medical Officer Jeanette Nazarian, Recreation and Parks Director Nick Mooneyhan, Council Member District 4 Deb Jung, Recreation & Parks Advisory Board David Grabowski (Chair), County Council Chair Christiana Rigby, County Executive Dr. Calvin Ball, Sheriff Marcus Harris, Shahan Rizvi, Health Department Deputy Health Officer Antigone Vickery, Fire and Rescue Deputy Chief Robert Smeltzer, and Howard County Board of Education member Linfeng Chen, Ph.D. (Jeffrey F. Bill/Baltimore Sun Media)
General clinical features
Among the cohort of 9782 children diagnosed with ARIs, 5021 cases (51.3%) were identified prior to the onset of the COVID-19 pandemic (20182019), while 4761 cases (48.7%) were diagnosed during the pandemic period (20202022). Compared with the pre-COVID, the proportion of children aged 0~<1 years on ARIs was lower during the COVID-19 pandemic (p<0.05). Gender distribution exhibited no significant variation between the two periods (p>0.05), as indicated in Table1.
Between 2018 and 2022, the yearly counts of ARIs cases were 2356, 2665, 1092, 1681, and 1988, with the lowest number of inpatient ARIs cases in 2020. The annual percentage of positive cases was 12.99%, 19.32%, 20.32%, 19.45%, and 12.68%, as presented in Table S1. Indeed, the Chinese government implemented prompt and stringent epidemic prevention measures starting in January 2020, including home isolation and mask mandates. From December 2021, children above the age of 3 (except those with specific contraindications) received SARS-CoV-2 vaccinations in Shaoxing. The positive rate of respiratory viruses among children over 3 years old was 8.31% (52/626) in 2022 and 7.61% (29/381) in 2021. Importantly, the detection rate of common respiratory viruses did not exhibit a significant decrease after the introduction of the new coronavirus vaccination (P=0.69).
The identification of one or more viruses was observed in 16.35% (n=821/5021) of samples prior to COVID-19 and 17.06% (n=812/4761) during the pandemic, as detailed in Table1. The cumulative detection rate of respiratory viruses experienced a decline from January to April and increased from October to December during both study periods (Fig.1A).
Positive cases and infection rates of respiratory viruses among hospitalized children with ARIs from 2018 to 2022. A: Total positive cases and infection rates for all respiratory viruses. B: Positive cases and infection rates of RSV. C: Positive cases and infection rates of ADV. D: Positive cases and infection rates of Flu (A) E: Positive cases and infection rates of Flu (B) F: Positive cases and infection rates of PIV-1. G: Positive cases and infection rates of PIV-2. H: Positive cases and infection rates of PIV-3.
RSV emerged as the predominant virus prior to and during COVID-19, accounting for 50.79% of positive samples in 20182019 and 76.48% in 20202022. Notably, the RSV positive rate during 20202022 exhibited a more significant increase than in 20182019 (13.04% vs. 9.38%, p<0.05). Conversely, the positive rates of ADV, PIV2 and 3, and Flu B experienced more significant reductions during 20202022 compared to 20182019 (p<0.05), while the positive rates for Flu A and PIV1 exhibited no significant differences between the two periods (p>0.05) (Table1).
The temporal distribution of infections and positive rates is depicted in Fig.1B, wherein RSV infections and positive rates displayed seasonal fluctuations annually between September and May from 2018 to 2019, 2020 to 2021, and 2021 to 2022. A notable surge occurred from December 2019 to January 2020. ADV infections and positive rates exhibited seasonal fluctuations between January 2019 and January 2020, with a sharp decline between April 2020 and January 2022. Flu A infections and positive rates remained low between April 2020 and April 2022, with a modest increase observed in children during the COVID-19 recovery phase from May 2022 to September 2022. Flu B infections and positive rates were low between April 2020 and April 2021, with a subsequent modest increase after July 2021, although remaining lower compared to the same period prior to the COVID-19 outbreak. Notably, PIV1, PIV2, and PIV3 infections declined after January 2020 (Fig.1C H).
A total of 11 samples yielded positive results for two viruses, with 6 instances prior to COVID-19 and 5 during the pandemic (0.12% vs. 0.10%, p>0.05). Throughout COVID-19, the most prevalent mixed infection was ADV in conjunction with PIV3, accounting for 25.71% of mixed infection cases. Nevertheless, cases of more than two concurrent virus detections were not observed during the two study periods.
Patients were classified into four age groups. Table2 illustrates the detection rates of respiratory viruses in different age groups. Prior to and during COVID-19, the overall positive rate peaked at 19.94% and 23.15%, respectively, within the 112 month age group. These rates exhibited a descending trend with increasing age of the enrolled children. Compared to the period before COVID-19, the total positive rates within the 012 month age group were significantly higher during the pandemic (p<0.05), while significant differences were not noted in other age groups (Table S1).
The dominant viruses varied across the different age groups. Before and during COVID-19, although all seven viruses were not detected in each age group, RSV remained the most prevalent among those under 7 years. In 20182019, PIV-3 was the second most dominant virus in the <3 years age group, while ADV held this position in the 37 years age group. In 20202022, PIV-3 was the second most dominant virus in the <1 year age group, while Flu A took this place in the 17 years age group. Notably, the RSV detection rate among different age groups was higher in 20202022 than in 20182019, especially among infants (p<0.001).
Table3 provides an overview of the positive sample detection for each virus across different months before and during COVID-19. In general, the prevalence of respiratory viruses demonstrated higher rates during winter compared to other seasons, with total positive rates of 30.90% and 33.24% before COVID-19 and during the pandemic, respectively. In contrast to the equivalent period preceding COVID-19, the total positive rates during winter in the COVID-19 era exhibited no significant difference (p>0.05). During 20202022, the total positive rates during spring and summer seasons significantly decreased (p<0.05), increased significantly in autumn (p<0.05).
Figure2 further illustrates that both before and during COVID-19, the RSV-positive rate during winter was notably higher than in other seasons (p<0.05). During COVID-19, Flu A exhibited a higher positive rate (2.61%) in summer, contrasting with the higher rate (3.05%) in winter before the pandemic. Conversely, the PIV3 positive rate during the summer of the pandemic (0.3%) was lower than that during the same period before COVID-19 (5.76%).
Seasonal distribution trends of respiratory virus infection in hospitalized children with acute respiratory infection, 20182019 and 20202022
