ABSTRACT
Considering sex as a biological variable in modern digital health solutions, we investigated sex-specific differences in the trajectory of four physiological parameters across a COVID-19 infection. A wearable medical device measured breathing rate, heart rate, heart rate variability, and wrist skin temperature in 1163 participants (mean age = 44.1 years, standard deviation [SD]=5.6; 667 [57%] females). Participants reported daily symptoms and confounders in a complementary app. A machine learning algorithm retrospectively ingested daily biophysical parameters to detect COVID-19 infections. COVID-19 serology samples were collected from all participants at baseline and follow-up. We analysed potential sex-specific differences in physiology and antibody titres using multilevel modelling and t-tests. Over 1.5 million hours of physiological data were recorded. During the symptomatic period of infection, men demonstrated larger increases in skin temperature, breathing rate and heart rate as well as larger decreases in heart rate variability than women. The COVID-19 infection detection algorithm performed similarly well for men and women. Our study belongs to the first research to provide evidence for differential physiological responses to COVID-19 between females and males, highlighting the potential of wearable technology to inform future precision medicine approaches. This work has received support from the Princely House of the Principality of Liechtenstein, the government of the Principality of Liechtenstein, the Hanela Foundation in Switzerland, and the Innovative Medicines Initiative (IMI) 2 Joint Undertaking under grant agreement No 101005177. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA.
Subject(s)
COVID-19 , Learning Disabilities , Severe Acute Respiratory SyndromeABSTRACT
Background: During and after mild (no hospitalization) or moderate (hospitalization without ICU) SARS-CoV-2 infections, a wide range of symptoms, including neurological disorders have been reported. It is, however, unknown if these neurological symptoms are associated with brain injury and whether brain injury and related symptoms also emerge in patients suffering from Long-COVID. Neuronal biomarkers such as serum neurofilament light chain and glial fibrillary acidic protein can be used to elucidate neuro-axonal and astroglial injuries. We therefore investigated whether these biomarkers are associated with the COVID-19 infection status (mild-to-moderate), the associated symptoms and Long-COVID. Methods: From 146 individuals of the general population with a post-acute, mild-to-moderate SARS-CoV-2 infection, serum neurofilament light chain (sNfL; marker of intra-axonal neuronal injury) and serum glial fibrillary acidic protein (sGFAP; marker of astrocytic activation/injury) were measured. Samples were taken before, during and after (five and ten months) a SARS-CoV-2 infection. Individual symptoms and Long-COVID status were assessed using questionnaires. Results: Neurological symptoms were described for individuals after a mild and moderate COVID-19 infection, however, serum markers of brain injury (sNfL/sGFAP) did not change after an infection (sNfL: P = 0.74; sGFAP: P = 0.24) and were not associated with headache (P = 0.51), fatigue (P = 0.93), anosmia (P = 0.77) and ageusia (P = 0.47). In participants with Long-COVID, sGFAP (P = 0.038), but not sNfL (P = 0.58) significantly increased but was not associated with neurological symptoms. Conclusion: Neurological symptoms in individuals after a mild-to-moderate SARS-CoV-2 infection with and without Long-COVID were not associated with brain injury, although there was some astroglial injury observed in Long-COVID patients. Funding: The COVI-GAPP study received grants from the Innovative Medicines Initiative (IMI grant agreement number 101005177), the Princely House of Liechtenstein, the government of the Principality of Liechtenstein, and the Hanela Foundation (Switzerland). None of the funders played a role in the study design, data collection, data analysis, data interpretation, writing of the report, or decision to publish.
Subject(s)
Infections , Headache , Fatigue , Severe Acute Respiratory Syndrome , Chemical and Drug Induced Liver Injury , Olfaction Disorders , Nervous System Diseases , Bone Cysts , COVID-19 , Ageusia , Brain Diseases , Basal Ganglia DiseasesABSTRACT
Background: Health care workers (HCW) are heavily exposed to SARS-CoV-2 from the beginning of the pandemic. We aimed to analyze risk factors for SARS-CoV-2 seroconversion among HCW with a special emphasis on the respective healthcare institutions’ recommendation regarding the use of FFP-2 masks. Methods: We recruited HCW from 13 health care institutions (HCI) with different mask policies (type IIR surgical face masks vs. FFP-2 masks) in Southeastern Switzerland (canton of Grisons). Sera of participants were analyzed for the presence of SARS-CoV-2 antibodies six months apart, after the first and during the second pandemic wave using an electro-chemiluminescence immunoassay (ECLIA, Roche Diagnostics). We captured risk factors for SARS-CoV-2 infection by using an online questionnaire at both time points. The effects of individual COVID-19 exposure, regional incidence and FFP-2 mask policy on the probability of seroconversion were evaluated with univariable and multivariable logistic regression. Results: SARS-CoV-2 antibodies were detected in 99 of 2794 (3.5%) HCW at baseline and in 376 of 2315 (16.2%) participants six months later. In multivariable analyses the strongest association for seroconversion was exposure to a household member with known COVID-19 (aOR: 19.82, 95% CI: 8.11-48.43, p<0.001 at baseline and aOR: 8.68, 95% CI: 6.13-12.29, p<0.001 at follow-up). Significant occupational risk factors at baseline included exposure to COVID-19 patients (aOR: 2.79, 95% CI: 1.28-6.09, p=0.010) and to SARS-CoV-2 infected co-workers (aOR: 2.50, 95% CI: 1.52-4.12, p<0.001). At follow up six months later, non-occupational exposure to SARS-CoV-2 infected individuals (aOR: 2.54, 95% CI: 1.66-3.89 p<0.001) and the local COVID-19 incidence of the corresponding HCI (aOR: 1.98, 95% CI: 1.30-3.02, p=0.001) were associated with seroconversion. The healthcare institutions’ mask policy (surgical masks vs. FFP-2 masks) did not affect seroconversion rates of HCW during the first and the second pandemic wave. Conclusion: Contact with SARS-CoV-2 infected household members was the most important risk factor for seroconversion among HCW. The strongest occupational risk factor was exposure to COVID-19 patients. During this pandemic, with heavy non-occupational exposure to SARS-CoV-2, the mask policy of HCIs did not affect the seroconversion rate of HCWs.
Subject(s)
HIV Seropositivity , COVID-19ABSTRACT
In February 2021, in response to emergence of more transmissible SARS-CoV-2 virus variants, the Canton Grisons launched a unique RNA mass testing program targeting the labour force in local businesses. Employees were offered weekly tests free of charge and on a voluntary basis. If tested positive, they were required to self-isolate for ten days and their contacts were subjected to daily testing at work. Thereby, the quarantine of contact persons could be waved. Here, we evaluate the effects of the testing program on the tested cohorts. We examined 121'364 test results from 27'514 participants during February-March 2021. By distinguishing different cohorts of employees, we observe a noticeable decrease in the test positivity rate and a statistically significant reduction in the associated incidence rate over the considered period. The reduction in the latter ranges between 18\%-50\%. The variability is partly explained by different exposures to exogenous infection sources (e.g., contacts with visiting tourists or cross-border commuters). Our analysis provides the first empirical evidence that applying repetitive mass testing to a real population over an extended period of time can prevent spread of COVID-19 pandemic. However, to overcome logistic, uptake, and adherence challenges it is important that the program is carefully designed and that disease incursion from the population outside of the program is considered and controlled.
Subject(s)
COVID-19 , Fractures, StressABSTRACT
In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now coined B.1.1.7. Based on the UK data and later additional data from other countries, a transmission advantage of around 40-80% was estimated for this variant. In Switzerland, since spring 2020, we perform whole genome sequencing of SARS-CoV-2 samples obtained from a large diagnostic lab (Viollier AG) on a weekly basis for genomic surveillance. The lab processes SARS-CoV-2 samples from across Switzerland. Based on a total of 7631 sequences obtained from samples collected between 14.12.2020 and 11.02.2021 at Viollier AG, we determine the relative proportion of the B.1.1.7 variant on a daily basis. In addition, we use data from a second lab (Dr Risch) screening all their samples for the B.1.1.7 variant. These two datasets represent 11.5 % of all SARS-CoV-2 confirmed cases across Switzerland during the considered time period. They allow us to quantify the transmission advantage of the B.1.1.7 variant on a national and a regional scale. Taking all our data and estimates together, we propose a transmission advantage of 49-65% of B.1.1.7 compared to the other circulating variants. Further, we estimate the effective reproductive number through time for B.1.1.7 and the other variants, again pointing to a higher transmission rate of B.1.1.7. In particular, for the time period 01.01.2021-17.01.2021, we estimate an average reproductive number for B.1.1.7 of 1.28 [1.07-1.49] while the estimate for the other variants is 0.83 [0.63-1.03], based on the total number of confirmed cases and our Viollier sequencing data. Switzerland tightened measures on 18.01.2021. A comparison of the empirically confirmed case numbers up to 20.02.2021 to a very simple model using the estimates of the reproductive number from the first half of January provides indication that the rate of spread of all variants slowed down recently. In summary, the dynamics of increase in frequency of B.1.1.7 is as expected based on the observations in the UK. Our plots are available online and constantly updated with new data to closely monitor the changes in absolute numbers.
ABSTRACT
With the COVID-19 pandemic causing a global health crisis, accurate diagnosis is critical. Diagnosing acute disease relies on RT-PCR tests measuring the presence of SARS-CoV-2 in the sampled material but in patients with suspected COVID-19 with a negative RT-PCR result, measuring anti-viral antibodies can help clinicians identify infected individuals. Antibody testing can also determine if someone was previously infected and help to measure the prevalence of the virus in a community. A new study characterizes an assay measuring total antibodies – combined IgA, IgM, and IgG isotypes – against SARS-CoV-2. The assay, ECLIA, specifically measures antibodies against the S1 subunit of the viral spike, which carries the virus’s receptor binding domain. Researchers in Liechtenstein evaluated ECLIA in a population with 125 cases of confirmed SARS-CoV-2 infection and 1159 individuals without evidence of COVID-19. The results showed a test sensitivity of 97.6%, while the specificity was 99.8%. Antibody levels were highest in hospitalized patients and lower in symptomatic patients outside the hospital and those with asymptomatic infection. Following COVID-19, smokers developed lower antibody titers than non-smokers, whereas patients without fever had lower antibody titers than patients with fever. Following COVID-19, smokers developed lower antibody titers than non-smokers, whereas patients without fever had lower antibody titers than patients with fever suggesting that the assay may be able to test the association between clinical characteristics and antibody levels and help identify individuals with potential cross-reactivity to SARS-CoV-2.
Subject(s)
Acute Disease , Fever , COVID-19ABSTRACT
Several tests based on chemiluminescence immunoassay techniques have become available to test for SARS-CoV-2 antibodies. There is currently insufficient data on serology assay performance beyond 35 days after symptoms onset. We aimed to evaluate SARS-CoV-2 antibody tests on three widely used platforms. A chemiluminescent microparticle immunoassay (CMIA; Abbott Diagnostics, USA), a luminescence immunoassay (LIA; Diasorin, Italy), and an electrochemiluminescence immunoassay (ECLIA; Roche Diagnostics, Switzerland) were investigated. In a multi-group study, sensitivity was assessed in a group of participants with confirmed SARS-CoV-2 (n=145), whereas specificity was determined in two groups of participants without evidence of COVID-19 (i.e. healthy blood donors, n=191, and healthcare workers, n=1002). Receiver operating characteristic (ROC) curves, multilevel likelihood ratios (LR), and positive (PPV) and negative (NPV) predictive values were characterized. Finally, analytical specificity was characterized in samples with evidence of Epstein-Barr virus (EBV) (n=9), cytomegalovirus (CMV) (n=7) and endemic common cold coronavirus infections (n=12) taken prior to the current SARS-CoV-2 pandemic. The diagnostic accuracy was comparable in all three assays (AUC 0.98). Using the manufacturers cut-offs, the sensitivities were 90%, 95% confidence interval,[84,94] (LIA), 93% [88,96] (CMIA), and 96% [91,98] (ECLIA). The specificities were 99.5% [98.9,99.8](CMIA) 99.7% [99.3,99,9] (LIA) and 99.9% [99.5,99.98] (ECLIA). The LR at half of the manufacturers cut-offs were 60 (CMIA), 82 (LIA), and 575 (ECLIA) for positive and 0.043 (CMIA) and 0.035 (LIA, ECLIA) for negative results. ECLIA had higher PPV at low pretest probabilities than CMIA and LIA. No interference with EBV or CMV infection was observed, whereas endemic coronavirus in some cases provided signals in LIA and/or CMIA. Although the diagnostic accuracy of the three investigated assays is comparable, their performance in low-prevalence settings is different. Introducing gray zones at half of the manufacturers cut-offs is suggested, especially for orthogonal testing approaches that use a second assay for confirmation.
Subject(s)
COVID-19ABSTRACT
Knowledge of the sensitivities of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) antibody tests beyond 35 days after the clinical onset of COVID-19 is insufficient. We aimed to describe positivity rate of SARS-CoV-2 assays employing three different measurement principles over a prolonged period. Two hundred sixty-eight samples from 180 symptomatic patients with COVID-19 and a reverse transcription polymerase chain reaction (RT-PCR) test followed by serological investigation of SARS-CoV-2 antibodies were included.. We conducted three chemiluminescence (including electrochemiluminscence, ECLIA), four enzyme linked immunosorbent assay (ELISA), and one lateral flow immunoassay (LFIA) test formats. Positivity rates, as well as positive (PPV) and negative predictive values (NPV) were calculated for each week after the first clinical presentation for COVID-19. Furthermore, combinations of tests were assessed within an orthogonal testing approach employing two independent assays and predictive values were calculated. Heat maps were constructed to graphically illustrate operational test characteristics. During a follow-up period of more than 9 weeks, chemiluminescence assays and one ELISA IgG test showed stable positivity rates after the third week. With the exception of ECLIA, the PPVs of the other chemiluminescence assays were [≥]95% for COVID-19 only after the second week. ELISA and LFIA had somewhat lower PPVs. IgM exhibited insufficient predictive characteristics. An orthogonal testing approach provided PPVs [≥]95% for patients with a moderate pretest probability (e.g., symptomatic patients), even for tests with a low single test performance. After the second week, NPVs of all but IgM assays were [≥]95% for patients with low to moderate pretest probability. The confirmation of negative results using an orthogonal algorithm with another assay provided lower NPVs than the single assays. When interpreting results from SARS-CoV-2 tests, the pretest probability, time of blood draw and assay characteristics must be carefully considered. An orthogonal testing approach increases the accuracy of positive, but not negative, predictions.