116 research outputs found

    Development of hybrid immunity during a period of high incidence of Omicron infections.

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    Seroprevalence and the proportion of people with neutralizing activity (functional immunity) against SARS-CoV-2 variants were high in early 2022. In this prospective, population- based, multi-region cohort study, we assessed the development of functional and hybrid immunity (induced by vaccination and infection) in the general population during this period of high incidence of infections with Omicron variants. We randomly selected and assessed individuals aged ≥16 years from the general population in southern (n = 739) and north-eastern (n = 964) Switzerland in March 2022. We assessed them again in June/July 2022, supplemented with a random sample from western (n = 850) Switzerland. We measured SARS-CoV-2 specific IgG antibodies and SARS-CoV-2 neutralizing antibodies against three variants (ancestral strain, Delta, Omicron). Seroprevalence remained stable from March 2022 (97.6%, n = 1894) to June/July 2022 (98.4%, n = 2553). In June/July, the percentage of individuals with neutralizing capacity against ancestral strain was 94.2%, against Delta 90.8% and against Omicron 84.9%, and 50.6% developed hybrid immunity. Individuals with hybrid immunity had highest median levels of anti-spike IgG antibodies titres [4518 World Health Organization units per millilitre (WHO U/mL)] compared with those with only vaccine- (4304 WHO U/mL) or infection- (269 WHO U/mL) induced immunity, and highest neutralization capacity against ancestral strain (hybrid: 99.8%, vaccinated: 98%, infected: 47.5%), Delta (hybrid: 99%, vaccinated: 92.2%, infected: 38.7%) and Omicron (hybrid: 96.4%, vaccinated: 79.5%, infected: 47.5%). This first study on functional and hybrid immunity in the Swiss general population after Omicron waves showed that SARS-CoV-2 has become endemic. The high levels of antibodies and neutralization support the emerging recommendations of some countries where booster vaccinations are still strongly recommended for vulnerable persons but less so for the general population

    A Direct Comparison of Two Densely Sampled HIV Epidemics: The UK and Switzerland

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    Phylogenetic clustering approaches can elucidate HIV transmission dynamics. Comparisons across countries are essential for evaluating public health policies. Here, we used a standardised approach to compare the UK HIV Drug Resistance Database and the Swiss HIV Cohort Study while maintaining data-protection requirements. Clusters were identified in subtype A1, B and C pol phylogenies. We generated degree distributions for each risk group and compared distributions between countries using Kolmogorov-Smirnov (KS) tests, Degree Distribution Quantification and Comparison (DDQC) and bootstrapping. We used logistic regression to predict cluster membership based on country, sampling date, risk group, ethnicity and sex. We analysed >8,000 Swiss and >30,000 UK subtype B sequences. At 4.5% genetic distance, the UK was more clustered and MSM and heterosexual degree distributions differed significantly by the KS test. The KS test is sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss dataset removed the difference. Only heterosexuals varied based on the DDQC, due to UK male heterosexuals who clustered exclusively with MSM. Their removal eliminated this difference. In conclusion, the UK and Swiss HIV epidemics have similar underlying dynamics and observed differences in clustering are mainly due to different population sizes

    Assessing Predicted HIV-1 Replicative Capacity in a Clinical Setting

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    HIV-1 replicative capacity (RC) provides a measure of within-host fitness and is determined in the context of phenotypic drug resistance testing. However it is unclear how these in-vitro measurements relate to in-vivo processes. Here we assess RCs in a clinical setting by combining a previously published machine-learning tool, which predicts RC values from partial pol sequences with genotypic and clinical data from the Swiss HIV Cohort Study. The machine-learning tool is based on a training set consisting of 65000 RC measurements paired with their corresponding partial pol sequences. We find that predicted RC values (pRCs) correlate significantly with the virus load measured in 2073 infected but drug naïve individuals. Furthermore, we find that, for 53 pairs of sequences, each pair sampled in the same infected individual, the pRC was significantly higher for the sequence sampled later in the infection and that the increase in pRC was also significantly correlated with the increase in plasma viral load and with the length of the time-interval between the sampling points. These findings indicate that selection within a patient favors the evolution of higher replicative capacities and that these in-vitro fitness measures are indicative of in-vivo HIV virus load

    The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing.

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    The increasing availability of "real-world" data in the form of written text holds promise for deepening our understanding of societal and health-related challenges. Textual data constitute a rich source of information, allowing the capture of lived experiences through a broad range of different sources of information (eg, content and emotional tone). Interviews are the "gold standard" for gaining qualitative insights into individual experiences and perspectives. However, conducting interviews on a large scale is not always feasible, and standardized quantitative assessment suitable for large-scale application may miss important information. Surveys that include open-text assessments can combine the advantages of both methods and are well suited for the application of natural language processing (NLP) methods. While innovations in NLP have made large-scale text analysis more accessible, the analysis of real-world textual data is still complex and requires several consecutive steps. We developed and subsequently examined the utility and scientific value of an NLP pipeline for extracting real-world experiences from textual data to provide guidance for applied researchers. We applied the NLP pipeline to large-scale textual data collected by the Swiss Multiple Sclerosis (MS) registry. Such textual data constitute an ideal use case for the study of real-world text data. Specifically, we examined 639 text reports on the experienced impact of the first COVID-19 lockdown from the perspectives of persons with MS. The pipeline has been implemented in Python and complemented by analyses of the "Linguistic Inquiry and Word Count" software. It consists of the following 5 interconnected analysis steps: (1) text preprocessing; (2) sentiment analysis; (3) descriptive text analysis; (4) unsupervised learning-topic modeling; and (5) results interpretation and validation. A topic modeling analysis identified the following 4 distinct groups based on the topics participants were mainly concerned with: "contacts/communication;" "social environment;" "work;" and "errands/daily routines." Notably, the sentiment analysis revealed that the "contacts/communication" group was characterized by a pronounced negative emotional tone underlying the text reports. This observed heterogeneity in emotional tonality underlying the reported experiences of the first COVID-19-related lockdown is likely to reflect differences in emotional burden, individual circumstances, and ways of coping with the pandemic, which is in line with previous research on this matter. This study illustrates the timely and efficient applicability of an NLP pipeline and thereby serves as a precedent for applied researchers. Our study thereby contributes to both the dissemination of NLP techniques in applied health sciences and the identification of previously unknown experiences and burdens of persons with MS during the pandemic, which may be relevant for future treatment

    Factors associated with time from first-symptoms to diagnosis and treatment initiation of Multiple Sclerosis in Switzerland.

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    Recent studies emphasise the importance of timely diagnosis and early initiation of disease-modifying treatment in the long-term prognosis of multiple sclerosis. The objective of this study was to investigate factors associated with extended time to diagnosis and time to disease-modifying treatment initiation in the Swiss Multiple Sclerosis Registry. We used retrospective data (diagnoses 1996-2017) of the survey-based Swiss Multiple Sclerosis Registry and fitted logistic regression models (extended time to diagnosis ≥2 years from first symptoms, extended time to disease-modifying treatment initiation ≥1 year from diagnosis) with demographic and a priori defined variables. Our study, based on 996 persons with multiple sclerosis, suggests that 40% had an extended time to diagnosis, and extended time to disease-modifying treatment initiation was seen in 23%. Factors associated with extended time to diagnosis were primary progressive multiple sclerosis (odds ratio (OR) 5.09 (3.12-8.49)), diagnosis setting outside of hospital (neurologist (private practice) OR 1.54 (1.16-2.05)) and more uncommon first symptoms (per additional symptom OR 1.17 (1.06-1.30)). Older age at onset (per additional 5 years OR 0.84 (0.78-0.90)) and gait problems (OR 0.65 (0.47-0.89)) or paresthesia (OR 0.72 (0.54-0.95)) as first symptoms were associated with shorter time to diagnosis. Extended time to disease-modifying treatment initiation was associated with older age at diagnosis (per additional 5 years OR 1.18 (1.09-1.29)). In more recent years, time to diagnosis and time to disease-modifying treatment initiation tended to be shorter. Even in recent periods, substantial and partially systematic variation regarding time to diagnosis and time to disease-modifying treatment initiation remains. With the emerging paradigm of early treatment, the residual variation should be monitored carefully

    A step beyond the hygiene hypothesis-immune-mediated classes determined in a population-based study.

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    Comorbidity patterns of childhood infections, atopic diseases, and adverse childhood experiences (ACE) are related to immune system programming conditions. The aim of this study was to make a step beyond the hygiene hypothesis and to comprehensively classify these patterns with latent class analysis (LCA). A second aim was to characterize the classes by associations with immunological, clinical, and sociodemographic variables. LCA was applied to data from the CoLaus|PsyCoLaus study (N = 4874, age range 35-82 years) separately for men and women. It was based on survey information on chickenpox, measles, mumps, rubella, herpes simplex, pertussis, scarlet fever, hay fever, asthma, eczema, urticaria, drug allergy, interparental violence, parental maltreatment, and trauma in early childhood. Subsequently, we examined how immune-mediated classes were reflected in leukocyte counts, inflammatory markers (IL-1β, IL-6, TNF-α, hsCRP), chronic inflammatory diseases, and mental disorders, and how they differed across social classes and birth cohorts. LCA results with five classes were selected for further analysis. Latent classes were similar in both sexes and were labeled according to their associations as neutral, resilient, atopic, mixed (comprising infectious and atopic diseases), and ACE class. They came across with specific differences in biomarker levels. Mental disorders typically displayed increased lifetime prevalence rates in the atopic, the mixed, and the ACE classes, and decreased rates in the resilient class. The same patterns were apparent in chronic inflammatory diseases, except that the ACE class was relevant specifically in women but not in men. This is the first study to systematically determine immune-mediated classes that evolve early in life. They display characteristic associations with biomarker levels and somatic and psychiatric diseases occurring later in life. Moreover, they show different distributions across social classes and allow to better understand the mechanisms beyond the changes in the prevalence of chronic somatic and psychiatric diseases

    Ambiguous Nucleotide Calls From Population-based Sequencing of HIV-1 are a Marker for Viral Diversity and the Age of Infection

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    The fraction of ambiguous nucleotide calls in bulk sequencing of human immunodeficiency virus type 1 (HIV-1) carries important information on viral diversity and the age of infection. In particular, a fraction of ambiguous nucleotides of >.5% provides evidence against a recent infection event <1 year ago

    Minor Protease Inhibitor Mutations at Baseline Do Not Increase the Risk for a Virological Failure in HIV-1 Subtype B Infected Patients

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    BACKGROUND: Minor protease inhibitor (PI) mutations often exist as polymorphisms in HIV-1 sequences from treatment-naïve patients. Previous studies showed that their presence impairs the antiretroviral treatment (ART) response. Evaluating these findings in a larger cohort is essential. METHODS: To study the impact of minor PI mutations on time to viral suppression and time to virological failure, we included patients from the Swiss HIV Cohort Study infected with HIV-1 subtype B who started first-line ART with a PI and two nucleoside reverse transcriptase inhibitors. Cox regression models were performed to compare the outcomes among patients with 0 and ≥ 1 minor PI mutation. Models were adjusted for baseline HIV-1 RNA, CD4 cell count, sex, transmission category, age, ethnicity, year of ART start, the presence of nucleoside reverse transcriptase inhibitor mutations, and stratified for the administered PIs. RESULTS: We included 1199 patients of whom 944 (78.7%) received a boosted PI. Minor PI mutations associated with the administered PI were common: 41.7%, 16.1%, 4.7% and 1.9% had 1, 2, 3 or ≥ 4 mutations, respectively. The time to viral suppression was similar between patients with 0 (reference) and ≥ 1 minor PI mutation (multivariable hazard ratio (HR): 1.1 [95% confidence interval (CI): 1.0-1.3], P = .196). The time to virological failure was also similar (multivariable HR:.9 [95% CI:.5-1.6], P = .765). In addition, the impact of each single minor PI mutation was analyzed separately: none was significantly associated with the treatment outcome. CONCLUSIONS: The presence of minor PI mutations at baseline has no effect on the therapy outcome in HIV infected individuals

    Factors associated with COVID-19 non-vaccination in Switzerland: a nationwide study

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    Objectives: We compared socio-demographic characteristics, health-related variables, vaccination-related beliefs and attitudes, vaccination acceptance, and personality traits of individuals who vaccinated against COVID-19 and who did not vaccinate by December 2021. Methods: This cross-sectional study used data of 10,642 adult participants from the Corona Immunitas eCohort, an age-stratified random sample of the population of several cantons in Switzerland. We used multivariable logistic regression models to explore associations of vaccination status with socio-demographic, health, and behavioral factors. Results: Non-vaccinated individuals represented 12.4% of the sample. Compared to vaccinated individuals, non-vaccinated individuals were more likely to be younger, healthier, employed, have lower income, not worried about their health, have previously tested positive for SARS-CoV-2 infection, express lower vaccination acceptance, and/or report higher conscientiousness. Among non-vaccinated individuals, 19.9% and 21.3% had low confidence in the safety and effectiveness of SARS-CoV-2 vaccine, respectively. However, 29.1% and 26.7% of individuals with concerns about vaccine effectiveness and side effects at baseline, respectively vaccinated during the study period. Conclusion: In addition to known socio-demographic and health-related factors, non-vaccination was associated with concerns regarding vaccine safety and effectiveness

    Changes in socioeconomic resources and mental health after the second COVID-19 wave (2020-2021): a longitudinal study in Switzerland

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    BACKGROUND: During the 2020/2021 winter, the labour market was under the impact of the COVID-19 pandemic. Changes in socioeconomic resources during this period could have influenced individual mental health. This association may have been mitigated or exacerbated by subjective risk perceptions, such as perceived risk of getting infected with SARS-CoV-2 or perception of the national economic situation. Therefore, we aimed to determine if changes in financial resources and employment situation during and after the second COVID-19 wave were prospectively associated with depression, anxiety and stress, and whether perceptions of the national economic situation and of the risk of getting infected modified this association. METHODS: One thousand seven hundred fifty nine participants from a nation-wide population-based eCohort in Switzerland were followed between November 2020 and September 2021. Financial resources and employment status were assessed twice (Nov2020-Mar2021, May-Jul 2021). Mental health was assessed after the second measurement of financial resources and employment status, using the Depression, Anxiety and Stress Scale (DASS-21). We modelled DASS-21 scores with linear regression, adjusting for demographics, health status, social relationships and changes in workload, and tested interactions with subjective risk perceptions. RESULTS: We observed scores above thresholds for normal levels for 16% (95%CI = 15-18) of participants for depression, 8% (95%CI = 7-10) for anxiety, and 10% (95%CI = 9-12) for stress. Compared to continuously comfortable or sufficient financial resources, continuously precarious or insufficient resources were associated with worse scores for all outcomes. Increased financial resources were associated with higher anxiety. In the working-age group, shifting from full to part-time employment was associated with higher stress and anxiety. Perceiving the Swiss economic situation as worrisome was associated with higher anxiety in participants who lost financial resources or had continuously precarious or insufficient resources. CONCLUSION: This study confirms the association of economic stressors and mental health during the COVID-19 pandemic and highlights the exacerbating role of subjective risk perception on this association
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