Real-time tracking of self-reported symptoms to predict potential COVID-19

Study of Postacute Sequelae of COVID-19 Using Digital Wearables: Protocol for a Prospective Longitudinal Observational Study

BACKGROUND

Postacute sequelae of COVID-19 (PASC) remain understudied in nonhospitalized patients. Digital wearables allow for a continuous collection of physiological parameters such as respiratory rate and oxygen saturation that have been predictive of disease trajectories in hospitalized patients.

OBJECTIVE

This protocol outlines the design and procedures of a prospective, longitudinal, observational study of PASC that aims to identify wearables-collected physiological parameters that are associated with PASC in patients with a positive diagnosis.

METHODS

This is a single-arm, prospective, observational study of a cohort of 550 patients, aged 18 to 65 years, male or female, who own a smartphone or a tablet that meets predetermined Bluetooth version and operating system requirements, speak English, and provide documentation of a positive COVID-19 test issued by a health care professional within 5 days before enrollment. The primary end point is long COVID-19, defined as ≥1 symptom at 3 weeks beyond the first symptom onset or positive diagnosis, whichever comes first. The secondary end point is chronic COVID-19, defined as ≥1 symptom at 12 weeks beyond the first symptom onset or positive diagnosis. Participants must be willing and able to consent to participate in the study and adhere to study procedures for 6 months.

RESULTS

The first patient was enrolled in October 2021. The estimated year for publishing the study results is 2025.

CONCLUSIONS

This is a fully decentralized study investigating PASC using wearable devices to collect physiological parameters and patient-reported outcomes. The study will shed light on the duration and symptom manifestation of PASC in nonhospitalized patient subgroups and is an exemplar of the use of wearables as population-level monitoring health tools for communicable diseases.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04927442; https://clinicaltrials.gov/study/NCT04927442.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/57382.

Machine learning predictive modeling of the persistence of post-Covid19 disorders: Loss of smell and taste as case studies

The worldwide health crisis triggered by the novel coronavirus (COVID-19) epidemic has resulted in an extensive variety of symptoms in people who have been infected, the most prevalent disorders of which are loss of smell and taste senses. In some patients, these disorders might occasionally last for several months and can strongly affect patients' quality of life. The COVID-19-related loss of taste and smell does not presently have a particular therapy. However, with the help of an early prediction of these disorders, healthcare providers can direct the patients to control these symptoms and prevent complications by following special procedures. The purpose of this research is to develop a machine learning (ML) model that can predict the occurrence and persistence of post-COVID-19-related loss of smell and taste abnormalities. In this study, we used our dataset to describe the symptoms, functioning, and disability of 413 verified COVID-19 patients. In order to prepare accurate classification models, we combined several ML algorithms, including logistic regression, k-nearest neighbors, support vector machine, random forest, extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). The accuracy of the loss of taste model was 91.5 % with an area-under-cure (AUC) of 0.94, and the accuracy of the loss of smell model was 95 % with an AUC of 0.97. Our proposed modelling framework can be utilized by hospitals experts to assess these post-COVID-19 disorders in the early stages, which supports the development of treatment strategies.

Feasibility of wearable sensor signals and self-reported symptoms to prompt at-home testing for acute respiratory viruses in the USA (DETECT-AHEAD): a decentralised, randomised controlled trial

BACKGROUND

Early identification of an acute respiratory infection is important for reducing transmission and enabling earlier therapeutic intervention. We aimed to prospectively evaluate the feasibility of home-based diagnostic self-testing of viral pathogens in individuals prompted to do so on the basis of self-reported symptoms or individual changes in physiological parameters detected via a wearable sensor.

METHODS

DETECT-AHEAD was a prospective, decentralised, randomised controlled trial carried out in a subpopulation of an existing cohort (DETECT) of individuals enrolled in a digital-only observational study in the USA. Participants aged 18 years or older were randomly assigned (1:1:1) with a block randomisation scheme stratified by under-represented in biomedical research status. All participants were offered a wearable sensor (Fitbit Sense smartwatch). Participants in groups 1 and 2 received an at-home self-test kit (Alveo be.well) for two acute respiratory viral pathogens: SARS-CoV-2 and respiratory syncytial virus. Participants in group 1 could be alerted through the DETECT study app to take the at-home test on the basis of changes in their physiological data (as detected by our algorithm) or due to self-reported symptoms; those in group 2 were prompted via the app to self-test only due to symptoms. Group 3 served as the control group, without alerts or home testing capability. The primary endpoints, assessed on an intention-to-treat basis, were the number of acute respiratory infections presented (self-reported) and diagnosed (electronic health record), and the number of participants using at-home testing in groups 1 and 2. This trial is registered with ClinicalTrials.gov, NCT04336020.

FINDINGS

Between Sept 28 and Dec 30, 2021, 450 participants were recruited and randomly assigned to group 1 (n=149), group 2 (n=151), or group 3 (n=150). 179 (40%) participants were male, 264 (59%) were female, and seven (2%) identified as other. 232 (52%) were from populations historically under-represented in biomedical research. 118 (39%) of the 300 participants in groups 1 and 2 were prompted to self-test, with 61 (52%) successfully completing self-testing. Participants were prompted to home-test more frequently due to symptoms (41 [28%] in group 1 and 51 [34%] in group 2) than due to detected physiological changes (26 [17%] in group 1). Significantly more participants in group 1 received alerts to test than did those in group 2 (67 [45%] vs 51 [34%]; p=0·047). Of the 61 individuals who were prompted to test and successfully did so, 19 (31%) tested positive for a viral pathogen-all for SARS-CoV-2. The individuals diagnosed as positive for SARS-CoV-2 in the electronic health record were eight (5%) in group 1, four (3%) in group 2, and two (1%) in group 3, but it was difficult to confirm if they were tied to symptomatic episodes documented in the trial. There were no adverse events.

INTERPRETATION

In this direct-to-participant trial, we showed early feasibility of a decentralised programme to prompt individuals to use a viral pathogen diagnostic test based on symptoms tracked in the study app or physiological changes detected using a wearable sensor. Barriers to adequate participation and performance were also identified, which would need to be addressed before large-scale implementation.

FUNDING

Janssen Pharmaceuticals.

Histopathology of the Tongue in a Hamster Model of COVID-19

Objective

With altered sense of taste being a common symptom of coronavirus disease 2019 (COVID-19), our objective was to investigate the presence and distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) within the tongue over the course of infection.

Methods

Golden Syrian hamsters were inoculated intranasally with SARS-CoV-2 and tongues were collected at 2, 3, 5, 8, 17, 21, 35, and 42 days post-infection (dpi) for analysis. In order to test for gross changes in the tongue, the papillae of the tongue were counted. Paraffin-embedded thin sections of the tongues were labeled for the presence of SARS-CoV-2 antigen.

Results

There was no difference in fungiform or filiform papillae density throughout the course of infection. SARS-CoV-2 antigen was observed in the circumvallate papillae taste buds (3-35 dpi) and autonomic ganglia (5-35 dpi), as well as in the serous and mucous salivary glands of the posterior tongue (2-42 dpi).

Conclusion

The presence and distribution of SARS-CoV-2 suggest that the virus could cause taste disturbance by infecting the circumvallate taste buds. This effect could be exacerbated by a diminished secretion of saliva caused by infection of the serous salivary glands and the autonomic ganglia which innervate them.

Uncovering hidden and complex relations of pandemic dynamics using an AI driven system

The COVID-19 pandemic continues to challenge healthcare systems globally, necessitating advanced tools for clinical decision support. Amidst the complexity of COVID-19 symptomatology and disease severity prediction, there is a critical need for robust decision support systems to aid healthcare professionals in timely and informed decision-making. In response to this pressing demand, we introduce BayesCovid, a novel decision support system integrating Bayesian network models and deep learning techniques. BayesCovid automates data preprocessing and leverages advanced computational methods to unravel intricate patterns in COVID-19 symptom dynamics. By combining Bayesian networks and Bayesian deep learning models, BayesCovid offers a comprehensive solution for uncovering hidden relationships between symptoms and predicting disease severity. Experimental validation demonstrates BayesCovid 's high prediction accuracy (83.52-98.97%). Our work represents a significant stride in addressing the urgent need for clinical decision support systems tailored to the complexities of managing COVID-19 cases. By providing healthcare professionals with actionable insights derived from sophisticated computational analysis, BayesCovid aims to enhance clinical decision-making, optimise resource allocation, and improve patient outcomes in the ongoing battle against the COVID-19 pandemic.

Reduced olfactory bulb volume accompanies olfactory dysfunction after mild SARS-CoV-2 infection

Despite its high prevalence, the determinants of smelling impairment in COVID-19 remain not fully understood. In this work, we aimed to examine the association between olfactory bulb volume and the clinical trajectory of COVID-19-related smelling impairment in a large-scale magnetic resonance imaging (MRI) analysis. Data of non-vaccinated COVID-19 convalescents recruited within the framework of the prospective Hamburg City Health Study COVID Program between March and December 2020 were analyzed. At baseline, 233 participants underwent MRI and neuropsychological testing as well as a structured questionnaire for olfactory function. Between March and April 2022, olfactory function was assessed at follow-up including quantitative olfactometric testing with Sniffin' Sticks. This study included 233 individuals recovered from mainly mild to moderate SARS-CoV-2 infections. Longitudinal assessment demonstrated a declining prevalence of self-reported olfactory dysfunction from 67.1% at acute infection, 21.0% at baseline examination and 17.5% at follow-up. Participants with post-acute self-reported olfactory dysfunction had a significantly lower olfactory bulb volume at baseline than normally smelling individuals. Olfactory bulb volume at baseline predicted olfactometric scores at follow-up. Performance in neuropsychological testing was not significantly associated with the olfactory bulb volume. Our work demonstrates an association of long-term self-reported smelling dysfunction and olfactory bulb integrity in a sample of individuals recovered from mainly mild to moderate COVID-19. Collectively, our results highlight olfactory bulb volume as a surrogate marker that may inform diagnosis and guide rehabilitation strategies in COVID-19.

Long COVID: From olfactory dysfunctions to viral Parkinsonism

Neurological and psychiatric complications continue to be a public health concern in long coronavirus disease 2019 (COVID-19). This varies from olfactory dysfunctions such as parosmia to cognitive and emotional challenges. Historically, the surge of neurological disorders followed the viral pandemics, for example, the emergence of Encephalitis Lethargica after the outbreak of Spanish Influenza. During and after COVID-19 infection, the problems associated with the sense of smell and the reports of affected olfactory and limbic brain areas are leading to a growing concern about the similarity with the symptoms and the pattern of degeneration observed at the onset of Parkinson's disease and Alzheimer's disease. These reports reveal the essentiality of long-term studies of olfactory and cognitive functions in the post-COVID era and the experiments using animal models to dissect the neural basis of these complications. In this manuscript, we summarize the research reporting the potential correlation between neurological disorders and viral pandemic outbreaks with a historical perspective. Further, we discuss the studies providing evidence of neurodegeneration due to severe acute respiratory syndrome coronavirus 2 infection by focusing on viral Parkinsonism.

Long-COVID impacts taste and olfactory in individuals with substance use disorder: A retrospective cohort study from the TriNetX US Collaborative Networks

Substance use disorder (SUD) exacerbates the impact of Long-COVID, particularly increasing the risk of taste and olfactory disorders. Analyzing retrospective cohort data from TriNetX and over 33 million records (Jan 2020-Dec 2022), this study focused on 1,512,358 participants, revealing that SUD significantly heightens the likelihood of experiencing taste disturbances and anosmia in Long-COVID sufferers. Results indicated that individuals with SUD face a higher incidence of sensory impairments compared to controls, with older adults and women being particularly vulnerable. Smokers with SUD were found to have an increased risk of olfactory and taste dysfunctions. The findings underscore the importance of early screening, diagnosis, and interventions for Long-COVID patients with a history of SUD, suggesting a need for clinicians to monitor for depression and anxiety linked to sensory dysfunction for comprehensive care.

Assessment of smell disturbances 6 months after COVID-19 in Polish population

Considering the frequency and severity of olfactory disorders associated with SARS-CoV-2 infection, attention to the olfactory loss has expanded. The aim of our study was to assess of smell disturbances 6 months after COVID-19. The study population consisted of 2 groups: 196 Post-COVID-19 patients who were hospitalized because of COVID-19, control sample-130 patients without reported smell disorders from general population-Bialystok PLUS study. People from both groups were asked to participate in the Sniffin Sticks Test (half year after the disease). Sniffin Sticks Test consisted of 12 standardized smell samples. The participant's test score was counted based on correct scent recognition. Middle/older age was related with lower likelihood of olfaction recovery. The biggest differences in recognition of particular fragrances were observed for: orange and lemon, lemon and coffee (p.adj < 0.001). Patients had the greatest problem in assessing smell of lemon. The comparison of scores between Delta, Omicron, Wild Type, Wild Type Alpha waves showed statistically significant difference between Delta and Wild Type waves (p = 0.006). Duration of the disease (r = 0.218), age (r = -0.253), IL-6 (r = -0.281) showed significant negative correlations with the score. Statistically significant variables in the case of smell disorders were Omicron wave (CI = 0.045-0.902; P = 0.046) and Wild Type wave (CI = 0.135-0.716; P = 0.007) compared to Delta wave reference. Moreover, patients with PLT count below 150 000/μl had greater olfactory disorders than those with PLT count over 150 000/μl. There are: smell differences between post-COVID-19 patients and healthy population; statistically significant difference between Delta and Wild Type waves in Post-COVID-19 group in score of the Sniffin Sticks Test. Smell disturbances depend on the age, cognitive impairments, clinical characteristics of the COVID-19 disease and sex of the patient.

Comparative Performance of COVID-19 Test Methods in Healthcare Workers during the Omicron Wave

The COVID-19 pandemic presents unique requirements for accessible, reliable testing, and many testing platforms and sampling techniques have been developed over the course of the pandemic. Not all test methods have been systematically compared to each other or a common gold standard, and the performance of tests developed in the early epidemic have not been consistently re-evaluated in the context of new variants. We conducted a repeated measures study with adult healthcare workers presenting for SARS-CoV-2 testing. Participants were tested using seven testing modalities. Test sensitivity was compared using any positive PCR test as the gold standard. A total of 325 individuals participated in the study. PCR tests were the most sensitive (saliva PCR 0.957 ± 0.048, nasopharyngeal PCR 0.877 ± 0.075, oropharyngeal PCR 0.849 ± 0.082). Standard nasal rapid antigen tests were less sensitive but roughly equivalent (BinaxNOW 0.613 ± 0.110, iHealth 0.627 ± 0.109). Oropharyngeal rapid antigen tests were the least sensitive (BinaxNOW 0.400 ± 0.111, iHealth brands 0.311 ± 0.105). PCR remains the most sensitive testing modality for the diagnosis of COVID-19 and saliva PCR is significantly more sensitive than oropharyngeal PCR and equivalent to nasopharyngeal PCR. Nasal AgRDTs are less sensitive than PCR but have benefits in convenience and accessibility. Saliva-based PCR testing is a viable alternative to traditional swab-based PCR testing for the diagnosis of COVID-19.

Defining the Subtypes of Long COVID and Risk Factors for Prolonged Disease: Population-Based Case-Crossover Study

BACKGROUND

There have been over 772 million confirmed cases of COVID-19 worldwide. A significant portion of these infections will lead to long COVID (post-COVID-19 condition) and its attendant morbidities and costs. Numerous life-altering complications have already been associated with the development of long COVID, including chronic fatigue, brain fog, and dangerous heart rhythms.

OBJECTIVE

We aim to derive an actionable long COVID case definition consisting of significantly increased signs, symptoms, and diagnoses to support pandemic-related clinical, public health, research, and policy initiatives.

METHODS

This research employs a case-crossover population-based study using International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) data generated at Veterans Affairs medical centers nationwide between January 1, 2020, and August 18, 2022. In total, 367,148 individuals with ICD-10-CM data both before and after a positive COVID-19 test were selected for analysis. We compared ICD-10-CM codes assigned 1 to 7 months following each patient's positive test with those assigned up to 6 months prior. Further, 350,315 patients had novel codes assigned during this window of time. We defined signs, symptoms, and diagnoses as being associated with long COVID if they had a novel case frequency of ≥1:1000, and they significantly increased in our entire cohort after a positive test. We present odds ratios with CIs for long COVID signs, symptoms, and diagnoses, organized by ICD-10-CM functional groups and medical specialty. We used our definition to assess long COVID risk based on a patient's demographics, Elixhauser score, vaccination status, and COVID-19 disease severity.

RESULTS

We developed a long COVID definition consisting of 323 ICD-10-CM diagnosis codes grouped into 143 ICD-10-CM functional groups that were significantly increased in our 367,148 patient post-COVID-19 population. We defined 17 medical-specialty long COVID subtypes such as cardiology long COVID. Patients who were COVID-19-positive developed signs, symptoms, or diagnoses included in our long COVID definition at a proportion of at least 59.7% (268,320/449,450, based on a denominator of all patients who were COVID-19-positive). The long COVID cohort was 8 years older with more comorbidities (2-year Elixhauser score 7.97 in the patients with long COVID vs 4.21 in the patients with non-long COVID). Patients who had a more severe bout of COVID-19, as judged by their minimum oxygen saturation level, were also more likely to develop long COVID.

CONCLUSIONS

An actionable, data-driven definition of long COVID can help clinicians screen for and diagnose long COVID, allowing identified patients to be admitted into appropriate monitoring and treatment programs. This long COVID definition can also support public health, research, and policy initiatives. Patients with COVID-19 who are older or have low oxygen saturation levels during their bout of COVID-19, or those who have multiple comorbidities should be preferentially watched for the development of long COVID.

Courage in Decision Making: A Mixed-Methods Study of COVID-19 Vaccine Uptake in Women of Reproductive Age in the U.K

COVID-19 vaccination rates are lower in women of reproductive age (WRA), including pregnant/postpartum women, despite their poorer COVID-19-related outcomes. We evaluated the vaccination experiences of 3568 U.K. WRA, including 1983 women (55.6%) experiencing a pandemic pregnancy, recruited through the ZOE COVID Symptom Study app. Two staggered online questionnaires (Oct-Dec 2021: 3453 responders; Aug-Sept 2022: 2129 responders) assessed reproductive status, COVID-19 status, vaccination, and attitudes for/against vaccination. Descriptive analyses included vaccination type(s), timing relative to age-based eligibility and reproductive status, vaccination delay (first vaccination >28 days from eligibility), and rationale, with content analysis of free-text comments. Most responders (3392/3453, 98.2%) were vaccinated by Dec 2021, motivated by altruism, vaccination supportiveness in general, low risk, and COVID-19 concerns. Few declined vaccination (by Sept/2022: 20/2129, 1.0%), citing risks (pregnancy-specific and longer-term), pre-existing immunity, and personal/philosophical reasons. Few women delayed vaccination, although pregnant/postpartum women (vs. other WRA) received vaccination later (median 3 vs. 0 days after eligibility, p < 0.0001). Despite high uptake, concerns included adverse effects, misinformation (including from healthcare providers), ever-changing government advice, and complex decision making. In summary, most women in this large WRA cohort were promptly vaccinated, including pregnant/post-partum women. Altruism and community benefit superseded personal benefit as reasons for vaccination. Nevertheless, responders experienced angst and received vaccine-related misinformation and discouragement. These findings should inform vaccination strategies in WRA.

Using SCENTinel® to predict SARS-CoV-2 infection: insights from a community sample during dominance of Delta and Omicron variants

Introduction

Based on a large body of previous research suggesting that smell loss was a predictor of COVID-19, we investigated the ability of SCENTinel®, a newly validated rapid olfactory test that assesses odor detection, intensity, and identification, to predict SARS-CoV-2 infection in a community sample.

Methods

Between April 5, 2021, and July 5, 2022, 1,979 individuals took one SCENTinel® test, completed at least one physician-ordered SARS-CoV-2 PCR test, and endorsed a list of self-reported symptoms.

Results

Among the of SCENTinel® subtests, the self-rated odor intensity score, especially when dichotomized using a previously established threshold, was the strongest predictor of SARS-CoV-2 infection. SCENTinel® had high specificity and negative predictive value, indicating that those who passed SCENTinel® likely did not have a SARS-CoV-2 infection. Predictability of the SCENTinel® performance was stronger when the SARS-CoV-2 Delta variant was dominant rather than when the SARS-CoV-2 Omicron variant was dominant. Additionally, SCENTinel® predicted SARS-CoV-2 positivity better than using a self-reported symptom checklist alone.

Discussion

These results indicate that SCENTinel® is a rapid assessment tool that can be used for population-level screening to monitor abrupt changes in olfactory function, and to evaluate spread of viral infections like SARS-CoV-2 that often have smell loss as a symptom.

Incidence of long COVID and associated psychosocial characteristics in a large U.S. city

PURPOSE

Persistent residual effects from Coronavirus Disease-2019 (COVID-19) have been observed with varying definitions of "Long COVID" and little comprehensive examination. This study examined the incidence and psychosocial correlates of Long COVID using different definitions.

METHODS

Data were analyzed from a citywide sample of 3595 adults with lab-confirmed cases of COVID-19 that were surveyed over 3 months. Rates of Long COVID were examined in terms of Post-Acute COVID (PAC), defined as at least one symptom lasting for 4 weeks, and three levels of Post-COVID Syndrome (PCS) that included experiencing at least one symptom for 3 months (PCS-1), experiencing three or more symptoms for 3 months (PCS-2), or experiencing at least one of the same symptoms for 3 months (PCS-3).

RESULTS

Among the 686 participants who completed baseline, 1-month, and 3-month follow-up assessments, 75.7% had PAC, 55.0% had PSC-1, 26.5% had PSC-2, and 19.0% had PSC-3. Comparing participants with PAC and PSC-3 in the total sample with inverse probability weighting, multivariable analyses revealed being female, Asian or Native American, greater reported longlines, and less social support were predictive of PCS-3.

CONCLUSION

Residual effects of COVID-19 are very common and nearly one-fifth of our sample met the most restrictive definition of Long COVID warranting concern as a public health issue. Some demographic and social factors may predispose some adults to Long COVID, which should be considered for prevention and population health.

What does artificial intelligence mean in rheumatology?

Intelligence is the ability of humans to learn from experiences to ascribe conscious weights and unconscious biases to modulate their outputs from given inputs. Transferring this ability to computers is artificial intelligence (AI). The ability of computers to understand data in an intelligent manner is machine learning. When such learning is with images and videos, which involves deeper layers of artificial neural networks, it is described as deep learning. Large language models are the latest development in AI which incorporate self-learning into deep learning through transformers. AI in Rheumatology has immense potential to revolutionize healthcare and research. Machine learning could aid clinical diagnosis and decision-making, and deep learning could extend this to analyze images of radiology or positron emission tomography scans or histopathology images to aid a clinician's diagnosis. Analysis of routinely obtained patient data or continuously collected information from wearables could predict disease flares. Analysis of high-volume genomics, transcriptomics, proteomics, or metabolomics data from patients could help identify novel markers of disease prognosis. AI might identify newer therapeutic targets based on in-silico modelling of omics data. AI could help automate medical administrative work such as inputting information into electronic health records or transcribing clinic notes. AI could help automate patient education and counselling. Beyond the clinic, AI has the potential to aid medical education. The ever-expanding capabilities of AI models bring along with them considerable ethical challenges, particularly related to risks of misuse. Nevertheless, the widespread use of AI in Rheumatology is inevitable and a progress with great potential.

Intrinsic factors behind long COVID: IV. Hypothetical roles of the SARS-CoV-2 nucleocapsid protein and its liquid-liquid phase separation

When the SARS-CoV-2 virus infects humans, it leads to a condition called COVID-19 that has a wide spectrum of clinical manifestations, from no symptoms to acute respiratory distress syndrome. The virus initiates damage by attaching to the ACE-2 protein on the surface of endothelial cells that line the blood vessels and using these cells as hosts for replication. Reactive oxygen species levels are increased during viral replication, which leads to oxidative stress. About three-fifths (~60%) of the people who get infected with the virus eradicate it from their body after 28 days and recover their normal activity. However, a large fraction (~40%) of the people who are infected with the virus suffer from various symptoms (anosmia and/or ageusia, fatigue, cough, myalgia, cognitive impairment, insomnia, dyspnea, and tachycardia) beyond 12 weeks and are diagnosed with a syndrome called long COVID. Long-term clinical studies in a group of people who contracted SARS-CoV-2 have been contrasted with a noninfected matched group of people. A subset of infected people can be distinguished by a set of cytokine markers to have persistent, low-grade inflammation and often self-report two or more bothersome symptoms. No medication can alleviate their symptoms efficiently. Coronavirus nucleocapsid proteins have been investigated extensively as potential drug targets due to their key roles in virus replication, among which is their ability to bind their respective genomic RNAs for incorporation into emerging virions. This review highlights basic studies of the nucleocapsid protein and its ability to undergo liquid-liquid phase separation. We hypothesize that this ability of the nucleocapsid protein for phase separation may contribute to long COVID. This hypothesis unlocks new investigation angles and could potentially open novel avenues for a better understanding of long COVID and treating this condition.

COVID-19 Virus Structural Details: Optical and Electrochemical Detection

The increasing viral species have ruined people's health and the world's economy. Therefore, it is urgent to design bio-responsive materials to provide a vast platform for detecting a different family's passive or active virus. One can design a reactive functional unit for that moiety based on the particular bio-active moieties in viruses. Nanomaterials as optical and electrochemical biosensors have enabled better tools and devices to develop rapid virus detection. Various material science platforms are available for real-time monitoring and detecting COVID-19 and other viral loads. In this review, we discuss the recent advances of nanomaterials in developing the tools for optical and electrochemical sensing COVID-19. In addition, nanomaterials used to detect other human viruses have been studied, providing insights for developing COVID-19 sensing materials. The basic strategies for nanomaterials develop as virus sensors, fabrications, and detection performances are studied. Moreover, the new methods to enhance the virus sensing properties are discussed to provide a gateway for virus detection in variant forms. The study will provide systematic information and working of virus sensors. In addition, the deep discussion of structural properties and signal changes will offer a new gate for researchers to develop new virus sensors for clinical applications.

Incidence and psychiatric predictors of Long COVID beyond 3 months in a city-wide community sample in Texas

BACKGROUND

Studies have emerged about a syndrome of persistent symptoms of Coronavirus Disease-2019 (COVID-19) infection called 'Long COVID', which have mostly focused on the first 3 months. This study examined rates and predictors of Long COVID symptoms lasting beyond 3 months (termed Long2 COVID).

METHODS

A longitudinal cohort study using a population-based sample of 511 adults in San Antonio, Texas with laboratory-confirmed cases of COVID-19 were assessed for Long2 COVID. Inverse probability weighting was used.

RESULTS

In the sample, 19.18-59.10% met criteria for Long2 COVID depending on the definition. In general, Long COVID symptoms decreased after 3 months with the notable exception of an observed increase in loss of taste and smell. White Hispanic (adjusted odds ratio (aOR) = 7.66; 95% confidence interval (CI) = 1.78, 32.87) background and baseline depression symptoms (aOR = 1.30; 95% CI = 1.03, 1.65) were predictive of Long2 COVID. Long2 COVID was also associated with greater anxiety symptoms 6 months after onset of COVID-19.

CONCLUSIONS

A sizable proportion report COVID-19 symptoms lasting more than 3 months and some symptoms even increased over time. Adults who are Hispanic white adults or have depression may be at greater risk for Long2 COVID. Further research is needed on why some adults experience Long COVID and how to reduce the duration of illness.

Evaluation of taste score and fungiform papillae quantification using digital image analysis in COVID-19 patients with smell and taste dysfunction

Background

The COVID-19 pandemic which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a major global health crisis in recent years. Despite this, there have been few studies that have utilized reliable methods to assess changes in taste and smell perception. Therefore, our study aims at the number of fungiform papillae and objective measures of taste perception relationship among COVID-19 patients with olfactory and gustatory disorders.

Materials and Methods

This was a cross-sectional analytical study in which 57 COVID-19 patients were recruited who confirmed the dysfunction of taste and smell. Objective assessment of the sense of taste was evaluated using four different standardized solution preparations, and the scores were given according to the patient's statements. Digitalized quantification of fungiform papillae was counted. The data were analyzed with the Pearson's correlation coefficient using the SPSS version. 23 [Licensed JSSAHER, Mysuru, Karnataka, India], and the level of significance was set at <0.001.

Results

In terms of altered or reduced taste and smell, male patients exhibited a higher incidence compared to females. Compared to the sour taste, a substantial number of COVID-19 patients have displayed a notable decrease in their ability to taste sweet, salty, and bitter flavors. However, a statistically significant positive correlation was observed between taste scores and fungiform papillae density (r = 0.518, P < 0.001).

Conclusion

Our Study demonstrated that the quantitative evaluation of taste perception and the count of fungiform papillae can serve as important indicators of SARS-CoV-2 infection, and could potentially help in the early detection and treatment of COVID-19 patients, as reduced taste function is a significant marker of the disease.

Vaccine Effectiveness against SARS-CoV-2 Infection during the Circulation of Alpha, Delta, or Omicron Variants: A Retrospective Cohort Study in a Tertiary Hospital in Serbia

The COVID-19 pandemic prompted rapid vaccine development and deployment worldwide. Despite widespread vaccination efforts, understanding the effectiveness of vaccines in hospitalized patients remains a critical concern. This retrospective cohort study, conducted at a tertiary healthcare centre in Serbia, tracked patients hospitalized during different waves of COVID-19 variants-Alpha, Delta, and Omicron. Data collection included demographics, comorbidities, symptoms, and vaccination status. Among 3593 patients, those with prior exposure to COVID-19 cases or hospital treatment showed higher positivity rates. Symptom prevalence varied across waves, with coughs persisting. Patients without chronic diseases were more frequent among those testing negative. Vaccine effectiveness varied, with Sinopharm demonstrating a 45.6% effectiveness initially and Pfizer-BioNTech showing an effectiveness of up to 74.8% within 0-84 days after the second dose. Mixed-dose strategies, notably Sinopharm as a primary dose followed by a Pfizer-BioNTech booster, suggested increased protection. Despite substantial vaccination availability, a significant portion of hospitalized patients remained unvaccinated. This study underscores the dynamic nature of vaccine effectiveness and advocates for booster strategies to address evolving challenges in combating COVID-19, particularly in hospitalized patients.

An intra-oral flavor detection task in freely moving mice

Flavor plays a critical role in the pleasure of food. Flavor research has mainly focused on human subjects and revealed that many brain regions are involved in flavor perception. However, animal models for elucidating the mechanisms of neural circuits are lacking. Herein, we demonstrate the use of a novel behavioral task in which mice are capable of flavor detection. When the olfactory pathways of the mice were blocked, they could not perform the task. However, behavioral accuracy was not affected when the gustatory pathway was blocked by benzocaine. These results indicate that the mice performed this detection task mainly based on the olfaction. We conclude that this novel task can contribute to research on the neural mechanisms of flavor perception.

Exploring Nursing Care for Patients With COVID-19 Using International Classification for Nursing Practice-Based Nursing Records

This study explored nursing care topics for patients with the coronavirus disease 2019 admitted to the wards and intensive care units using International Classification for Nursing Practice-based nursing narratives. A total of 256630 nursing statements from 555 adult patients admitted from December 2019 to June 2022 were extracted from the clinical data warehouse. The International Classification for Nursing Practice concepts mapped to 301 unique nursing statements that accounted for the top 90% of all cumulative nursing narratives were used for analysis. The standardized number of nursing statements for each concept was calculated according to the types of nursing care and compared between the two groups. The most documented topics were related to infection; physical symptoms such as sputum, cough, dyspnea, and shivering; and vital signs including blood oxygen saturation and body temperature. Nurses in the intensive care units frequently documented concepts related to the directly monitored and assessed physical signs such as consciousness, pupil reflex, and skin integrity, whereas nurses in wards documented more concepts related to symptoms patients complained. This study showed that the International Classification for Nursing Practice-based nursing records can be used as source of information to identify nursing care for patients with coronavirus disease 19.

Acute and persistent symptoms of COVID-19 infection in school-aged children: a retrospective study from China

BACKGROUND

The long-term sequelae of Coronavirus disease 2019 (COVID-19) in children are unclear. We investigated COVID-19 symptoms in school-aged children to determine their impact on patients and their families.

METHODS

This cross-sectional study, conducted on February 25-28, 2023, selected a representative kindergarten and 9-year school from Shenzhen, China. There were randomly two classes each for the 12 grades from kindergarten to junior high school. The school-aged children were aged 3-16 years. Literate parents completed an online questionnaire related to their children's COVID-19 symptoms since December 1, 2022. Descriptive statistics were computed as necessary. Univariate and multivariable linear regression analyses were performed, and variables with a p-value < 0.05 were considered to have a significant association with the subjective feeling scores for COVID-19 infection.

RESULTS

We included 936 school-aged children, with a COVID-19 infection rate of 68.5%. The prevalence of LC 28 (illness with symptoms lasting for 28 days) was 3.4%. During acute infection, the median number of the 641 children's symptoms was 3.0 (IQR: 1.0-5.0) and the median score of subjective feelings was 15.0 (IQR: 11.0-24.5). The top three symptoms were fever, cough/expectoration, and rhinobyon. Age of 13-16 years (adjusted beta: 3.60, 95% CI: 0.32-6.88) and comorbidities (adjusted beta: 3.47, 95% CI: 1.20-5.73) were independently associated with higher subjective feelings (p < 0.05). The top three characteristics associated with LC 28 were alopecia (33.3%, 5/15), cognitive dysfunction (29.2%, 7/24), and emotional problem (28.6%, 6/21).

CONCLUSIONS

Children with COVID-19 have a short duration of symptoms and milder symptoms, so they can self-medicate to minimize hospital crowding. Children with basic diseases require prompt attention. Although LC 28 is uncommon in children, mental and psychological problems after COVID-19 recovery should not be ignored.

Use of Telehealth Information for Early Detection: Insights From the COVID-19 Pandemic

Objectives. To examine whether the addition of telehealth data to existing surveillance infrastructure can improve forecasts of cases and mortality. Methods. In this observational study, we compared accuracy of 14-day forecasts using real-time data available to the National Syndromic Surveillance Program (standard forecasts) to forecasts that also included telehealth information (telehealth forecasts). The study was performed in a national telehealth service provider in 2020 serving 50 US states and the District of Columbia. Results. Among 10.5 million telemedicine encounters, 169 672 probable COVID-19 cases were diagnosed by 5050 clinicians, with a rate between 0.79 and 47.8 probable cases per 100 000 encounters per day (mean = 8.37; SD = 10.75). Publicly reported case counts ranged from 0.5 to 237 916 (mean: 53 913; SD = 47 466) and 0 to 2328 deaths (mean = 1035; SD = 550) per day. Telehealth-based forecasts improved 14-day case forecasting accuracy by 1.8 percentage points to 30.9% (P = .06) and mortality forecasting by 6.4 percentage points to 26.9% (P < .048). Conclusions. Modest improvements in forecasting can be gained from adding telehealth data to syndromic surveillance infrastructure. (Am J Public Health. 2024;114(2):218-225. https://doi.org/10.2105/AJPH.2023.307499).

The Multisystem Impact of Long COVID: A Comprehensive Review

(1) Background: COVID-19 was responsible for the latest pandemic, shaking and reshaping healthcare systems worldwide. Its late clinical manifestations make it linger in medical memory as a debilitating illness over extended periods. (2) Methods: the recent literature was systematically analyzed to categorize and examine the symptomatology and pathophysiology of Long COVID across various bodily systems, including pulmonary, cardiovascular, gastrointestinal, neuropsychiatric, dermatological, renal, hematological, and endocrinological aspects. (3) Results: The review outlines the diverse clinical manifestations of Long COVID across multiple systems, emphasizing its complexity and challenges in diagnosis and treatment. Factors such as pre-existing conditions, initial COVID-19 severity, vaccination status, gender, and age were identified as influential in the manifestation and persistence of Long COVID symptoms. This condition is highlighted as a debilitating disease capable of enduring over an extended period and presenting new symptoms over time. (4) Conclusions: Long COVID emerges as a condition with intricate multi-systemic involvement, complicating its diagnosis and treatment. The findings underscore the necessity for a nuanced understanding of its diverse manifestations to effectively manage and address the evolving nature of this condition over time.

The predictive role of symptoms in COVID-19 diagnostic models: A longitudinal insight

To investigate the symptoms of SARS-CoV-2 infection, their dynamics and their discriminatory power for the disease using longitudinally, prospectively collected information reported at the time of their occurrence. We have analysed data from a large phase 3 clinical UK COVID-19 vaccine trial. The alpha variant was the predominant strain. Participants were assessed for SARS-CoV-2 infection via nasal/throat PCR at recruitment, vaccination appointments, and when symptomatic. Statistical techniques were implemented to infer estimates representative of the UK population, accounting for multiple symptomatic episodes associated with one individual. An optimal diagnostic model for SARS-CoV-2 infection was derived. The 4-month prevalence of SARS-CoV-2 was 2.1%; increasing to 19.4% (16.0%-22.7%) in participants reporting loss of appetite and 31.9% (27.1%-36.8%) in those with anosmia/ageusia. The model identified anosmia and/or ageusia, fever, congestion, and cough to be significantly associated with SARS-CoV-2 infection. Symptoms' dynamics were vastly different in the two groups; after a slow start peaking later and lasting longer in PCR+ participants, whilst exhibiting a consistent decline in PCR- participants, with, on average, fewer than 3 days of symptoms reported. Anosmia/ageusia peaked late in confirmed SARS-CoV-2 infection (day 12), indicating a low discrimination power for early disease diagnosis.

Performance and explainability of feature selection-boosted tree-based classifiers for COVID-19 detection

In this paper, we evaluate the performance and analyze the explainability of machine learning models boosted by feature selection in predicting COVID-19-positive cases from self-reported information. In essence, this work describes a methodology to identify COVID-19 infections that considers the large amount of information collected by the University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS). More precisely, this methodology performs a feature selection stage based on the recursive feature elimination (RFE) method to reduce the number of input variables without compromising detection accuracy. A tree-based supervised machine learning model is then optimized with the selected features to detect COVID-19-active cases. In contrast to previous approaches that use a limited set of selected symptoms, the proposed approach builds the detection engine considering a broad range of features including self-reported symptoms, local community information, vaccination acceptance, and isolation measures, among others. To implement the methodology, three different supervised classifiers were used: random forests (RF), light gradient boosting (LGB), and extreme gradient boosting (XGB). Based on data collected from the UMD-CTIS, we evaluated the detection performance of the methodology for four countries (Brazil, Canada, Japan, and South Africa) and two periods (2020 and 2021). The proposed approach was assessed in terms of various quality metrics: F1-score, sensitivity, specificity, precision, receiver operating characteristic (ROC), and area under the ROC curve (AUC). This work also shows the normalized daily incidence curves obtained by the proposed approach for the four countries. Finally, we perform an explainability analysis using Shapley values and feature importance to determine the relevance of each feature and the corresponding contribution for each country and each country/year.

Alpha-lipoic acid does not improve olfactory training results in olfactory loss due to COVID-19: a double-blind randomized trial

OBJECTIVES

Olfactory loss is a recognized long-term dysfunction after Coronavirus Disease 2019 (COVID-19) infection. This investigation aimed to assess the effect of alpha-lipoic acid as an adjuvant treatment of olfactory training on the improvement of smell loss in post-COVID-19 patients.

METHODS

This randomized controlled trial included 128 adult outpatients who had persistent smell loss for more than 3-months after COVID-19 infection. The participants were randomly allocated into two groups: the intervention treatment group, which received alpha-lipoic acid associated to olfactory training, and comparison treatment group, which received placebo pills associated to olfactory training. The participants were followed-up for 12-weeks. Olfactory dysfunction was assessed in terms of Visual Analog Scale (VAS), and the Connecticut Chemosensory Clinical Research Center (CCCRC) test for the Brazilian population.

RESULTS

A total of 100 participants completed the follow-up period and were analyzed in this study. Both groups have improved CCCRC score (p = 0.000), olfactory threshold (p = 0.000), identification score (p = 0.000) and VAS score (p = 0.000) after 12-weeks follow-up. No significant differences were determined between the intervention and comparison treatment groups in CCCRC score (p = 0.63), olfactory threshold (p = 0.50), identification score (p = 0.96) and VAS score (p = 0.97). In all these criteria, comparison treatment group went slightly worse. At the endpoint of the study, the frequency of anosmia reduced to 2% in the intervention treatment group and to 7.8% in the comparison treatment group. Also, 16.8% of the intervention group' subjects, and 15.7% of comparison treatment group's patients reached normosmia.

CONCLUSIONS

Overall, there was a strongly significant difference in olfactory function between baseline and endpoint for both groups. However, based on the lack of significant difference between the intervention treatment and the comparison treatment groups in terms of olfactory changes, our study appoints that the alpha-lipoic acid is not better than olfactory training alone to treat olfactory loss after COVID-19.

LEVEL OF EVIDENCE

Level 2.

Long-term effects of extreme smoke exposure on COVID-19: A cohort study

BACKGROUND

In 2014, the Hazelwood coalmine fire shrouded the regional Australian town of Morwell in smoke and ash for 6 weeks. One of the fire's by-products, PM2.5 , is associated with an increased risk of COVID-19 and severe disease. However, it is unclear whether the effect persisted for years after exposure. In this study, we surveyed a cohort established prior to the pandemic to determine whether PM2.5 from the coalmine fire increased long-term vulnerability to COVID-19 and severe disease.

METHODS

From August to December 2022, 612 members of the Hazelwood Health Study's adult cohort, established in 2016/17, participated in a follow-up survey that included standardized items to capture COVID-19 cases, as well as questions about hospitalization and vaccinations. Associations were evaluated in crude and adjusted logistic regression models.

RESULTS

A total of 268 (44%) participants self-reported or met symptom criteria for having had COVID-19 at least once. All models found a positive association, with odds of COVID-19 increasing by between 4% and 30% for a 10 μg/m3 increase in coalmine fire-related PM2.5 exposure. However, the association was significant in only 2 of the 18 models. There were insufficient hospitalizations to examine severity (n = 7; 1%).

CONCLUSION

The findings are inconclusive on the effect of coalmine fire-related PM2.5 exposure on long-term vulnerability to COVID-19. Given the positive association that was robust to modelling variations as well as evidence for a causal mechanism, it would be prudent to treat PM2.5 from fire events as a long-term risk factor until more evidence accumulates.

Effects of genetics on odor perception: Can a quick smell test effectively screen everyone?

SCENTinel, a rapid smell test designed to screen for olfactory disorders, including anosmia (no ability to smell an odor) and parosmia (distorted sense of smell), measures 4 components of olfactory function: detection, intensity, identification, and pleasantness. Each test card contains one of 9 odorant mixtures. Some people born with genetic insensitivities to specific odorants (i.e. specific anosmia) may fail the test if they cannot smell an odorant but otherwise have a normal sense of smell. However, using odorant mixtures has largely been found to prevent this from happening. To better understand whether genetic differences affect SCENTinel test results, we asked genetically informative adult participants (twins or triplets, N = 630; singletons, N = 370) to complete the SCENTinel test. A subset of twins (n = 304) also provided a saliva sample for genotyping. We examined data for differences between the 9 possible SCENTinel odors; effects of age, sex, and race on SCENTinel performance, test-retest variability; and heritability using both structured equation modeling and SNP-based statistical methods. None of these strategies provided evidence for specific anosmia for any of the odors, but ratings of pleasantness were, in part, genetically determined (h2 = 0.40) and were nominally associated with alleles of odorant receptors (e.g. OR2T33 and OR1G1; P < 0.001). These results provide evidence that using odorant mixtures protected against effects of specific anosmia for ratings of intensity but that ratings of pleasantness showed effects of inheritance, possibly informed by olfactory receptor genotypes.

Coronavirus infection and systemic inflammatory reaction syndrome

OBJECTIVE

Aim: The purpose of this study was a clinical approbation of the Kometad drug (international non-proprietary name sodium colistimethate), an antibiotic from the polymyxin group in patients with severe course of confirmed сoronavirus infection in the intensive care unit of the Branch of the I. Zhekenova Municipal Clinical Infectious Diseases Hospital..

PATIENTS AND METHODS

Materials and Methods: The methodology is based on both theoretical and empirical methods of scientific cognition. During the study, the features of the Coronavirus infection and the inflammatory reaction syndrome were considered, which became quite a big problem during the pandemic.

RESULTS

Results: The main indications for the tested drug and the consequences of its use for one age group were also determined.

CONCLUSION

Conclusions: The conclusion was made about the positive dynamics of the patients' health status, and recommendations were given for further research in this area. The practical significance of this study lies in the first clinical approbation of the Kometad drug, which can be used in medicine to reduce the severity of the systemic inflammatory reaction syndrome and improve the patient's health as a result of the disease of Coronavirus infection, after further clinical trials of the drug with different age groups of patients.

Symptom-based scoring technique by machine learning to predict COVID-19: a validation study

BACKGROUND

Coronavirus disease 2019 (COVID-19) surges, such as that which occurred when omicron variants emerged, may overwhelm healthcare systems. To function properly, such systems should balance detection and workloads by improving referrals using simple yet precise and sensitive diagnostic predictions. A symptom-based scoring system was developed using machine learning for the general population, but no validation has occurred in healthcare settings. We aimed to validate a COVID-19 scoring system using self-reported symptoms, including loss of smell and taste as major indicators.

METHODS

A cross-sectional study was conducted to evaluate medical records of patients admitted to Dr. Sardjito Hospital, Yogyakarta, Indonesia, from March 2020 to December 2021. Outcomes were defined by a reverse-transcription polymerase chain reaction (RT-PCR). We compared the symptom-based scoring system, as the index test, with antigen tests, antibody tests, and clinical judgements by primary care physicians. To validate use of the index test to improve referral, we evaluated positive predictive value (PPV) and sensitivity.

RESULTS

After clinical judgement with a PPV of 61% (n = 327/530, 95% confidence interval [CI]: 60% to 62%), confirmation with the index test resulted in the highest PPV of 85% (n = 30/35, 95% CI: 83% to 87%) but the lowest sensitivity (n = 30/180, 17%, 95% CI: 15% to 19%). If this confirmation was defined by either positive predictive scoring or antigen tests, the PPV was 92% (n = 55/60, 95% CI: 90% to 94%). Meanwhile, the sensitivity was 88% (n = 55/62, 95% CI: 87% to 89%), which was higher than that when using only antigen tests (n = 29/41, 71%, 95% CI: 69% to 73%).

CONCLUSIONS

The symptom-based COVID-19 predictive score was validated in healthcare settings for its precision and sensitivity. However, an impact study is needed to confirm if this can balance detection and workload for the next COVID-19 surge.

A prospective natural history study of post acute sequalae of COVID-19 using digital wearables: Study protocol

Background

Post-acute sequelae of COVID-19 (PASC) is characterized by having 1 + persistent, recurrent, or emergent symptoms post the infection's acute phase. The duration and symptom manifestation of PASC remain understudied in nonhospitalized patients. Literature on PASC is primarily based on data from hospitalized patients where clinical indicators such as respiratory rate, heart rate, and oxygen saturation have been predictive of disease trajectories. Digital wearables allow for a continuous collection of such physiological parameters. This protocol outlines the design, aim, and procedures of a natural history study of PASC using digital wearables.

Methods

This is a single-arm, prospective, natural history study of a cohort of 550 patients, ages 18 to 65 years old, males or females who own a smartphone and/or a tablet that meets pre-determined Bluetooth version and operating system requirements, speak English, and provide documentation of a positive COVID-19 test issued by a healthcare professional or organization within 5 days before enrollment. The study aims to identify wearables collected physiological parameters that are associated with PASC in patients with a positive diagnosis. The primary endpoint is long COVID-19, defined as ≥ 1 symptom at 3 weeks beyond first symptom onset or positive diagnosis, whichever comes first. The secondary endpoint is chronic COVID-19, defined as ≥ 1 symptom at 12 weeks beyond first symptom onset or positive diagnosis. We hypothesize that physiological parameters collected via wearables are associated with self-reported PASC. Participants must be willing and able to consent to participate in the study and adhere to study procedures for six months.

Discussion

This is a fully decentralized study investigating PASC using wearable devices to collect physiological parameters and patient-reported outcomes. Given evidence on key demographics and risk profiles associated with PASC, the study will shed light on the duration and symptom manifestation of PASC in nonhospitalized patient subgroups and is an exemplar of use of wearables as population-level monitoring health tools for communicable diseases.

Trial registration

ClinicalTrials.gov NCT04927442.

SARS-CoV-2 infection following booster vaccination: Illness and symptom profile in a prospective, observational community-based case-control study

BACKGROUND

Booster COVID-19 vaccines have shown efficacy in clinical trials and effectiveness in real-world data against symptomatic and severe illness. However, some people still become infected with SARS-CoV-2 following a third (booster) vaccination. This study describes the characteristics of SARS-CoV-2 illness following a third vaccination and assesses the risk of progression to symptomatic disease in SARS-CoV-2 infected individuals with time since vaccination.

METHODS

This prospective, community-based, case-control study used data from UK-based, adult (≥18 years) users of the COVID Symptom Study mobile application, self-reporting a first positive COVID-19 test between June 1, 2021 and April 1, 2022. To describe the characteristics of SARS-CoV-2 illness following a third vaccination, we selected cases and controls who had received a third and second dose of monovalent vaccination against COVID-19, respectively, and reported a first positive SARS-CoV-2 test at least 7 days after most recent vaccination. Cases and controls were matched (1:1) based on age, sex, BMI, time between first vaccination and infection, and week of testing. We used logistic regression models (adjusted for age, sex, BMI, level of social deprivation and frailty) to analyse associations of disease severity, overall disease duration, and individual symptoms with booster vaccination status. To assess for potential waning of vaccine effectiveness, we compared disease severity, duration, and symptom profiles of individuals testing positive within 3 months of most recent vaccination (reference group) to profiles of individuals infected between 3 and 4, 4-5, and 5-6 months, for both third and second dose. All analyses were stratified by time period, based on the predominant SARS-CoV-2 variant at time of infection (Delta: June 1, 2021-27 Nov, 2021; Omicron: 20 Dec, 2021-Apr 1, 2022).

FINDINGS

During the study period, 50,162 (Delta period) and 162,041 (Omicron) participants reported a positive SARS-CoV-2 test. During the Delta period, infection following three vaccination doses was associated with lower odds of long COVID (symptoms≥ 4 weeks) (OR=0.83, CI[0.50-1.36], p < 0.0001), hospitalisation (OR=0.55, CI[0.39-0.75], p < 0.0001) and severe symptoms (OR=0.36, CI[0.27-0.49], p < 0.0001), and higher odds of asymptomatic infection (OR=3.45, CI[2.86-4.16], p < 0.0001), compared to infection following only two vaccination doses. During the Omicron period, infection following three vaccination doses was associated with lower odds of severe symptoms (OR=0.48, CI[0.42-0.55], p < 0.0001). During the Delta period, infected individuals were less likely to report almost all individual symptoms after a third vaccination. During the Omicron period, individuals were less likely to report most symptoms after a third vaccination, except for upper respiratory symptoms e.g. sneezing (OR=1.40, CI[1.18-1.35], p < 0.0001), runny nose (OR=1.26, CI[1.18-1.35], p < 0.0001), sore throat (OR=1.17, CI[1.10-1.25], p < 0.0001), and hoarse voice (OR=1.13, CI[1.06-1.21], p < 0.0001), which were more likely to be reported. There was evidence of reduced vaccine effectiveness during both Delta and Omicron periods in those infected more than 3 months after their most recent vaccination, with increased reporting of severe symptoms, long duration illness, and most individual symptoms.

INTERPRETATION

This study suggests that a third dose of monovalent vaccine may reduce symptoms, severity and duration of SARS-CoV-2 infection following vaccination. For Omicron variants, the third vaccination appears to reduce overall symptom burden but may increase upper respiratory symptoms, potentially due to immunological priming. There is evidence of waning vaccine effectiveness against progression to symptomatic and severe disease and long COVID after three months. Our findings support ongoing booster vaccination promotion amongst individuals at high risk from COVID-19, to reduce severe symptoms and duration of illness, and health system burden. Disseminating knowledge on expected symptoms following booster vaccination may encourage vaccine uptake.

Bayesian monitoring of COVID-19 in Sweden

In an effort to provide regional decision support for the public healthcare, we design a data-driven compartment-based model of COVID-19 in Sweden. From national hospital statistics we derive parameter priors, and we develop linear filtering techniques to drive the simulations given data in the form of daily healthcare demands. We additionally propose a posterior marginal estimator which provides for an improved temporal resolution of the reproduction number estimate as well as supports robustness checks via a parametric bootstrap procedure. From our computational approach we obtain a Bayesian model of predictive value which provides important insight into the progression of the disease, including estimates of the effective reproduction number, the infection fatality rate, and the regional-level immunity. We successfully validate our posterior model against several different sources, including outputs from extensive screening programs. Since our required data in comparison is easy and non-sensitive to collect, we argue that our approach is particularly promising as a tool to support monitoring and decisions within public health. Significance: Using public data from Swedish patient registries we develop a national-scale computational model of COVID-19. The parametrized model produces valuable weekly predictions of healthcare demands at the regional level and validates well against several different sources. We also obtain critical epidemiological insights into the disease progression, including, e.g., reproduction number, immunity and disease fatality estimates. The success of the model hinges on our novel use of filtering techniques which allows us to design an accurate data-driven procedure using data exclusively from healthcare demands, i.e., our approach does not rely on public testing and is therefore very cost-effective.

Olfactory dysfunction among patients with COVID-19

OBJECTIVES

To assess the frequency of olfactory dysfunction (OD) among individuals afflicted with coronavirus disease of 2019 (COVID-19).

METHODS

A comprehensive literature search was carried out across several bibliographical databases (PubMed, Scopus, Google Scholar, and Web of Science) to extract publications in the English language between January 2020 and December 2021 to report the incidence of OD alone or together with gustatory dysfunction (GD) among COVID-19 patients.

RESULTS

Based on eligibility criteria, 84 articles were included from 27 countries, comprising 36,903 patients, of whom 58.1% were females. The generality rates of olfactory impairment alone was 34.60% and in conjunction with GD was 11.36%. Patients with OD were subclassified into various categories, and the prevalence of anosmia was 20.85%, 5.04% for hyposmia, 8.88% for anosmia or hyposmia, 1.84% for parosmia, 0.78% for phantosmia, and 0.02% for hyperosmia, among COVID-19 patients.

CONCLUSION

Clinical features associated with OD, either isolated or in combination with GD, are common in patients with COVID-19 and consider important signs of COVID-19 that may guide clinicians in the early phase of the disease.PROSPERO Reg. No.: 417296.

Otolaryngology-Specific Symptoms May Be Highly Observed in Patients With a History of Covid-19 Infection After Inactivated Coronavirus Vaccination

OBJECTIVE

To evaluate the otolaryngology-specific symptoms that occur after receiving the Covid-19 vaccine and its possible side effects in patients who had Covid-19 infection in the last 6 months before the vaccination.

PATIENTS AND METHODS

The study comprised 3383 health care workers who were vaccinated against Covid 19. After excluding, the study was conducted with 1710 (51%) participants who agreed to answer the study questions. The participants were divided into 2 groups according to the history of Covid-19 positivity in the last 6 months before vaccination. The presence of symptoms related to otolaryngology practice, including cough, nasal congestion, rhinorrhea, sore throat, hearing loss, dizziness, loss of smell, loss of taste, ear pressure, and facial paralysis was recorded.

RESULTS

The mean age of the study population was 35.79 ± 10.2 (19-71) years and 1454 (85%) of the patients had a history of Covid-19 infection in the last 6 months. Regarding otolaryngology-related symptoms, the most common complaints were rhinorrhea (4.4%), sore throat (3.2%), and nasal congestion (2.9%). The presence of smell and taste loss, nasal congestion, rhinorrhea, sore throat, and hearing loss was significantly more common in patients with a history of Covid-19 infection.

CONCLUSIONS

The patients with a history of Covid-19 disease might have otolaryngology-specific symptoms more commonly than those without a history of Covid-19 disease in the last 6 months before vaccination.

Wastewater-based surveillance models for COVID-19: A focused review on spatio-temporal models

The evident shedding of the SARS-CoV-2 RNA particles from infected individuals into the wastewater opened up a tantalizing array of possibilities for prediction of COVID-19 prevalence prior to symptomatic case identification through community testing. Many countries have therefore explored the use of wastewater metrics as a surveillance tool, replacing traditional direct measurement of prevalence with cost-effective approaches based on SARS-CoV-2 RNA concentrations in wastewater samples. Two important aspects in building prediction models are: time over which the prediction occurs and space for which the predicted case numbers is shown. In this review, our main focus was on finding mathematical models which take into the account both the time-varying and spatial nature of wastewater-based metrics into account. We used six main characteristics as our assessment criteria: i) modelling approach; ii) temporal coverage; iii) spatial coverage; iv) sample size; v) wastewater sampling method; and vi) covariates included in the modelling. The majority of studies in the early phases of the pandemic recognized the temporal association of SARS-CoV-2 RNA concentration level in wastewater with the number of COVID-19 cases, ignoring their spatial context. We examined 15 studies up to April 2023, focusing on models considering both temporal and spatial aspects of wastewater metrics. Most early studies correlated temporal SARS-CoV-2 RNA levels with COVID-19 cases but overlooked spatial factors. Linear regression and SEIR models were commonly used (n = 10, 66.6 % of studies), along with machine learning (n = 1, 6.6 %) and Bayesian approaches (n = 1, 6.6 %) in some cases. Three studies employed spatio-temporal modelling approach (n = 3, 20.0 %). We conclude that the development, validation and calibration of further spatio-temporally explicit models should be done in parallel with the advancement of wastewater metrics before the potential of wastewater as a surveillance tool can be fully realised.

Long-term symptom profiles after COVID-19 vs other acute respiratory infections: an analysis of data from the COVIDENCE UK study

Background

Long COVID is a well recognised, if heterogeneous, entity. Acute respiratory infections (ARIs) due to other pathogens may cause long-term symptoms, but few studies compare post-acute sequelae between SARS-CoV-2 and other ARIs. We aimed to compare symptom profiles between people with previous SARS-CoV-2 infection, people with previous non-COVID-19 ARIs, and contemporaneous controls, and to identify clusters of long-term symptoms.

Methods

COVIDENCE UK is a prospective, population-based UK study of ARIs in adults. We analysed data for 16 potential long COVID symptoms and health-related quality of life (HRQoL), reported between January 21 and February 15, 2021, by participants unvaccinated against SARS-CoV-2. We classified participants as having previous SARS-CoV-2 infection or previous non-COVID-19 ARI (≥4 weeks prior) or no reported ARI. We compared symptoms by infection status using logistic and fractional regression, and identified symptom clusters using latent class analysis (LCA). This study is registered with ClinicalTrials.gov, NCT04330599.

Findings

We included 10,171 participants (1311 [12.9%] with SARS-CoV-2 infection, 472 [4.6%] with non-COVID-19 ARI). Both types of infection were associated with increased prevalence/severity of most symptoms and decreased HRQoL compared with no infection. Participants with SARS-CoV-2 infection had increased odds of problems with taste/smell (odds ratio 19.74, 95% CI 10.53-37.00) and lightheadedness or dizziness (1.74, 1.18-2.56) compared with participants with non-COVID-19 ARIs. Separate LCA models identified three symptom severity groups for each infection type. In the most severe groups (representing 22% of participants for both SARS-CoV-2 and non-COVID-19 ARI), SARS-CoV-2 infection presented with a higher probability of problems with taste/smell (probability 0.41 vs 0.04), hair loss (0.25 vs 0.16), unusual sweating (0.38 vs 0.25), unusual racing of the heart (0.43 vs 0.33), and memory problems (0.70 vs 0.55) than non-COVID-19 ARI.

Interpretation

Both SARS-CoV-2 and non-COVID-19 ARIs are associated with a wide range of symptoms more than 4 weeks after the acute infection. Research on post-acute sequelae of ARIs should extend from SARS-CoV-2 to include other pathogens.

Funding

Barts Charity.

Comparison of the clinical characteristics of SARS-CoV-2 Delta (B.1.617.2) and Omicron (B.1.1.529) infected patients from a single hospitalist service

BACKGROUND

While existing evidence suggests less severe clinical manifestations and lower mortality are associated with the Omicron variant as compared to the Delta variant. However, these studies fail to control for differences in health systems facilities and providers. By comparing patients hospitalized on a single medical service during the Delta and Omicron surges we were able to conduct a more accurate comparison of the two varaints' clinical manifestations and outcomes.

METHODS

We conducted a prospective study of 364 Omicron (BA.1) infected patients on a single hospitalist service and compared these findings to a retrospective analysis of 241 Delta variant infected patients managed on the same service. We examined differences in symptoms, laboratory measures, and clinical severity between the two variants and assessed potential risk drivers for case mortality.

FINDINGS

Patients infected with Omicron were older and had more underlying medical conditions increasing their risk of death. Although they were less severely ill and required less supplemental oxygen and dexamethasone, in-hospital mortality was similar to Delta cases, 7.14% vs. 4.98% for Delta (q-value = 0.38). Patients older than 60 years or with immunocompromised conditions had much higher risk of death during hospitalization, with estimated odds ratios of 17.46 (95% CI: 5.05, 110.51) and 2.80 (1.03, 7.08) respectively. Neither vaccine history nor variant type played a significant role in case fatality. The Rothman score, NEWS-2 score, level of neutrophils, level of care, age, and creatinine level at admission were highly predictive of in-hospital death.

INTERPRETATION

In hospitalized patients, the Omicron variant is less virulent than the Delta variant but is associated with a comparable mortality. Clinical and laboratory features at admission are informative about the risk of death.

A double-blinded randomised controlled trial of vitamin A drops to treat post-viral olfactory loss: study protocol for a proof-of-concept study for vitamin A nasal drops in post-viral olfactory loss (APOLLO)

BACKGROUND

Smell loss is a common problem with an estimated 5% of the population having no functioning sense of smell. Viral causes of smell loss are the second most common cause and the coronavirus (COVID-19) pandemic is estimated to have caused 20,000 more people this year to have a lasting loss of smell. Isolation, depression, anxiety, and risk of danger from hazards such as toxic gas and spoiled food are all negative impacts. It also affects appetite with weight loss/gain in two-thirds of those affected. Phantosmia or smell distortion can also occur making most foods seem unpalatable. Smell training has been tried with good results in the immediate post-viral phase. Evidence behind treatment with steroids has not shown to have proven effectiveness. With this, a key problem for patients and their clinicians is the lack of proven effective therapeutic treatment options. Based on previous studies, there is some evidence supporting the regenerative potential of retinoic acid, the metabolically active form of vitamin A in the regeneration of olfactory receptor neurons. It is based on this concept that we have chosen vitamin A as our study comparator.

AIM

To undertake a two-arm randomised trial of intranasally delivered vitamin A vs no intervention to determine proof of concept.

METHODS/DESIGN

The study will compare 10,000 IU once daily Vitamin A self-administered intranasal drops versus peanut oil drops (placebo) delivered over 12 weeks in patients with post-viral olfactory loss. Potentially eligible patients will be recruited from the Smell & Taste Clinic and via the charity Fifth Sense. They will be invited to attend the Brain Imaging Centre at the University of East Anglia on two occasions, 3 months apart. If they meet the eligibility criteria, they will be consented to enter the study and randomised to receive vitamin A drops or no treatment in a 2:1 ratio. MRI scanning will enable volumetric measurement of the OB and ROS; fMRI will then be conducted using an olfactometer to deliver pulsed odours-phenethylalcohol (rose-like) and hydrogen sulphide (rotten eggs). Participants will also perform a standard smell test at both visits as well as complete a quality-of-life questionnaire. Change in OB volume will be the primary outcome measure.

DISCUSSION

We expect the outputs of this study to enable a subsequent randomised controlled trial of Vitamin A versus placebo. With PPI input we will make the outputs publicly available using journals, conferences, and social media via Fifth Sense. We have already prepared a draft RCT proposal in partnership with the Norwich Clinical Trials Unit and plan to develop this further in light of the findings.

TRIAL REGISTRATION

ISRCTN registry 39523. Date of registration in the primary registry: 23rd February 2021.

Understanding olfactory dysfunction in the COVID-19 era: insights from a cross-sectional survey of the Saudi community

Background and objectives

COVID-19 has emerged as a public health emergency caused by the coronavirus 2 (SARS-CoV2). However, only a few studies have reported that anosmia is an early predictor of COVID-19. Therefore, this study aimed to assess the current level of knowledge regarding smell dysfunction in COVID-19 era in Saudi community.

Materials and methods

An online survey was conducted using Survey Monkeys in Saudi Arabia. The survey was distributed through Twitter and WhatsApp. The questionnaire included individuals' demographic information, such as sex, age, residence, income, and qualifications, as well as their knowledge of the early symptoms of COVID-19. ANOVA and Mann-Whitney U-test were conducted to analyze the data. There were twelve items on knowledge dimensions which were assessed through five-point Likert scale.

Results

In total, 809 respondents completed the questionnaire. Among them, 658 (81.3%) had no knowledge of how sudden loss of or change in the sense of smell can be the only symptom of COVID-19. However, most participants, 738 (91.2%), knew that fever was a symptom of COVID-19. Similarly, 707 (87.4%) and 772 (95.5%) participants knew that cough and shortness of breath were the major symptoms of COVID-19, respectively. In addition, 395 (48.3%) participants had no information regarding taste changes as a symptom of COVID-19. Notably, participants who were female, married, or diagnosed with COVID-19 had significantly greater knowledge of smell-related issues due to COVID-19 than males, unmarried, and healthy/those without COVID-19.

Conclusion

This study revealed that the Saudi population has an fairly good level of knowledge regarding common COVID-19 symptoms as more than 90% of the participants understood symptoms of COVID-19, but less acceptable knowledge regarding smell and taste dysfunction as more than 80% had no knowledge of change in olfactory and taste function was due to COVID-19.

How long is Long-COVID? Symptomatic improvement between 12 and 18 months in a prospective cohort study

INTRODUCTION

COVID-19 infection can precede, in a proportion of patients, a prolonged syndrome including fatigue, exercise intolerance, mood and cognitive problems. This study aimed to describe the profile of fatigue-related, exercise-related, mood-related and cognitive-related outcomes in a COVID-19-exposed group compared with controls.

METHODS

113 serving UK Armed Forces participants were followed up at 5, 12 (n=88) and 18 months (n=70) following COVID-19. At 18 months, 56 were in the COVID-19-exposed group with 14 matched controls. Exposed participants included hospitalised (n=25) and community (n=31) managed participants. 43 described at least one of the six most frequent symptoms at 5 months: fatigue, shortness of breath, chest pain, joint pain, exercise intolerance and anosmia. Participants completed a symptom checklist, patient-reported outcome measures (PROMs), the National Institute for Health cognitive battery and a 6-minute walk test (6MWT). PROMs included the Fatigue Assessment Scale (FAS), Generalised Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9) and Patient Checklist-5 (PCL-5) for post-traumatic stress.

RESULTS

At 5 and 12 months, exposed participants presented with higher PHQ-9, PCL-5 and FAS scores than controls (ES (effect size) ≥0.25, p≤0.04). By 12 months, GAD-7 was not significantly different to controls (ES <0.13, p=0.292). Remaining PROMs lost significant difference by 18 months (ES ≤0.11, p≥0.28). No significant differences in the cognitive scales were observed at any time point (F=1.96, p=0.167). At 5 and 12 months, exposed participants recorded significantly lower distances on the 6MWT (ηp 2≥0.126, p<0.01). 6MWT distance lost significant difference by 18 months (ηp 2<0.039, p>0.15).

CONCLUSIONS

This prospective cohort-controlled study observed adverse outcomes in depression, post-traumatic stress, fatigue and submaximal exercise performance up to 12 months but improved by 18-month follow-up, in participants exposed to COVID-19 compared with a matched control group.

Smell, taste and chemesthesis disorders in patients with the SARS-CoV-2 during Omicron variant pandemic in China

Chemosensory disorders (including smell, taste and chemesthesis) are among the established symptoms of COVID-19 infection; however, new data indicate that the changes in chemosensory sensation caused by COVID-19 may differ among populations and COVID-19 variants. To date, few studies have focused on the influence of the SARS-CoV-2 Omicron variant on qualitative changes and quantitative reductions in chemosensory function in China. We conducted a cross-sectional study of patients with COVID-19 caused by the Omicron variant, to investigate the prevalence of chemosensory disorders and chemosensory function before and during infection, using an online questionnaire. A total of 1245 patients with COVID-19 completed the survey. The prevalence rates of smell, taste, and chemesthesis disorders were 69.2%, 67.7%, and 31.4%, respectively. Our data indicate that sex, age, smoking, and COVID-19-related symptoms, such as lack of appetite, dyspnea, and fatigue, may be associated with chemosensory disorders during COVID-19. Self-rating of chemosensory function revealed that patients experienced a general decline in smell, taste, and chemesthesis function. Further longitudinal research studies are needed to generate additional data based on objective assessment and investigate the factors influencing chemosensory function in COVID-19.

Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician

BACKGROUND

Artificial intelligence (AI), machine learning and deep learning (including generative AI) are increasingly being investigated in the context of research and management of human infection.

OBJECTIVES

We summarise recent and potential future applications of AI and its relevance to clinical infection practice.

METHODS

1617 PubMed results were screened, with priority given to clinical trials, systematic reviews and meta-analyses. This narrative review focusses on studies using prospectively collected real-world data with clinical validation, and on research with translational potential, such as novel drug discovery and microbiome-based interventions.

RESULTS

There is some evidence of clinical utility of AI applied to laboratory diagnostics (e.g. digital culture plate reading, malaria diagnosis, antimicrobial resistance profiling), clinical imaging analysis (e.g. pulmonary tuberculosis diagnosis), clinical decision support tools (e.g. sepsis prediction, antimicrobial prescribing) and public health outbreak management (e.g. COVID-19). Most studies to date lack any real-world validation or clinical utility metrics. Significant heterogeneity in study design and reporting limits comparability. Many practical and ethical issues exist, including algorithm transparency and risk of bias.

CONCLUSIONS

Interest in and development of AI-based tools for infection research and management are undoubtedly gaining pace, although the real-world clinical utility to date appears much more modest.

Harnessing digital technology for COVID-19 response in Uganda: lessons and implications for future public health emergencies

COVID-19 was one of the greatest disruptors of the 21st century, causing significant morbidity and mortality globally. Countries around the world adopted digital technologies and innovations to support the containment of the pandemic. This study explored the use of digital technology and barriers to its utilisation in responding to COVID-19 and sustaining essential health services in Uganda to inform response to future public health emergencies in low-resource settings. We reviewed published and grey literature on the use of digital technology in Uganda's response from March 2020 to April 2021 and conducted interviews with key informants. We thematically synthesised and summarised information on digital technology use as well as related challenges. During the COVID-19 response, digital technology was used in testing, contact tracing and surveillance, risk communication, supportive supervision and training, and maintenance of essential health services. The challenges with technology use were the disparate digital tools and health information systems leading to duplication of effort; limited access and coverage of digital tools, poor data quality; inaccessibility of data and an inability to support data manipulation, analysis and visualisation. Moreover, the inherent inadequate technology support systems such as poor internet and electricity infrastructure in some areas posed challenges of inequity. The harnessing of technology was key in supporting the COVID-19 response in Uganda. However, gaps existed in access, adoption, harmonisation, evaluation, sustainability and scale up of technology options. These issues should be addressed in preparedness efforts to foster technology adoption and application in public health emergencies with a focus on equity.

Mechanisms of SARS-CoV-2-associated anosmia

Anosmia, the loss of the sense of smell, is one of the main neurological manifestations of COVID-19. Although the SARS-CoV-2 virus targets the nasal olfactory epithelium, current evidence suggests that neuronal infection is extremely rare in both the olfactory periphery and the brain, prompting the need for mechanistic models that can explain the widespread anosmia in COVID-19 patients. Starting from work identifying the non-neuronal cell types that are infected by SARS-CoV-2 in the olfactory system, we review the effects of infection of these supportive cells in the olfactory epithelium and in the brain and posit the downstream mechanisms through which sense of smell is impaired in COVID-19 patients. We propose that indirect mechanisms contribute to altered olfactory system function in COVID-19-associated anosmia, as opposed to neuronal infection or neuroinvasion into the brain. Such indirect mechanisms include tissue damage, inflammatory responses through immune cell infiltration or systemic circulation of cytokines, and downregulation of odorant receptor genes in olfactory sensory neurons in response to local and systemic signals. We also highlight key unresolved questions raised by recent findings.

Post-COVID-19 syndrome management: Utilizing the potential of dietary polysaccharides

The COVID-19 pandemic has caused significant global impact, resulting in long-term health effects for many individuals. As more patients recover, there is a growing need to identify effective management strategies for ongoing health concerns, such as post-COVID-19 syndrome, characterized by persistent symptoms or complications beyond several weeks or months from the onset of symptoms. In this review, we explore the potential of dietary polysaccharides as a promising approach to managing post-COVID-19 syndrome. We summarize the immunomodulatory, antioxidant, antiviral, and prebiotic activities of dietary polysaccharides for the management of post-COVID-19 syndrome. Furthermore, the review investigates the role of polysaccharides in enhancing immune response, regulating immune function, improving oxidative stress, inhibiting virus binding to ACE2, balancing gut microbiota, and increasing functional metabolites. These properties of dietary polysaccharides may help alleviate COVID-19 symptoms, providing a promising avenue for effective treatment strategies.

Home Monitoring for Fever: An Inexpensive Screening Method to Prevent Household Spread of COVID-19

The COVID-19 pandemic surge has exceeded testing capacities in many parts of the world. We investigated the effectiveness of home temperature monitoring for early identification of COVID-19 patients.

Study Design –

We compared home temperature measurements from a convenience sample of 1180 individuals who reported being test positive for SARS-CoV-2 to an age, sex, and location matched control group of 1249 individuals who had not tested positive.

Methods –

All individuals monitored their temperature at home using an electronic smartphone thermometer that relayed temperature measurements and symptoms to a centralized cloud based, de-identified data bank.

Results -

Individuals varied in the number of times they monitored their temperature. When temperature was monitored for over 72 hours fever (≥ 37.6°C or 99.7°F or a change in temperature of ≥ 1°C or 1.8°F) was detected in 73% of test positive individuals, a sensitivity comparable to rapid SARS-CoV-2 antigen tests. When compared to our control group the specificity of fever for COVID-19 was 0.70. However, when fever was combined with complaints of loss of taste and smell, difficulty breathing, fatigue, chills, diarrhea, or stuffy nose the odds ratio of having COVID-19 was sufficiently high as to obviate the need to employ RTPCR or antigen testing to screen for and isolate coronavirus infected cases.

Conclusions -

Our findings suggest that home temperature monitoring could serve as an inexpensive convenient screen for the onset of COVID-19, encourage earlier isolation of potentially infected individuals, and more effectively reduce the spread of infection in closed spaces.