Development of prediction models for upper and lower respiratory and gastrointestinal tract infections using social network parameters in middle-aged and older persons -The Maastricht Study.

The ability to predict upper respiratory infections (URI), lower respiratory infections (LRI), and gastrointestinal tract infections (GI) in independently living older persons would greatly benefit population and individual health. Social network parameters have so far not been included in prediction models. Data were obtained from The Maastricht Study, a population-based cohort study (N = 3074, mean age (±s.d.) 59.8 ± 8.3, 48.8% women). We used multivariable logistic regression analysis to develop prediction models for self-reported symptomatic URI, LRI, and GI (past 2 months). We determined performance of the models by quantifying measures of discriminative ability and calibration. Overall, 953 individuals (31.0%) reported URI, 349 (11.4%) LRI, and 380 (12.4%) GI. The area under the curve was 64.7% (95% confidence interval (CI) 62.6-66.8%) for URI, 71.1% (95% CI 68.4-73.8) for LRI, and 64.2% (95% CI 61.3-67.1%) for GI. All models had good calibration (based on visual inspection of calibration plot, and Hosmer-Lemeshow goodness-of-fit test). Social network parameters were strong predictors for URI, LRI, and GI. Using social network parameters in prediction models for URI, LRI, and GI seems highly promising. Such parameters may be used as potential determinants that can be addressed in a practical intervention in older persons, or in a predictive tool to compute an individual's probability of infections.

SARS-CoV-2 cellular and humoral responses in vaccine-naive individuals during the first two waves of COVID-19 infections in the southern region of The Netherlands: a cross-sectional population-based study.

With the emergence of highly transmissible variants of concern, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still poses a global threat of coronavirus disease 2019 (COVID-19) resurgence. Cellular responses to novel variants are more robustly maintained than humoral responses, and therefore, cellular responses are of interest in assessing immune protection against severe disease in the population. We aimed to assess cellular responses to SARS-CoV-2 at the population level. IFNγ (interferon γ) responses to wild-type SARS-CoV-2 were analyzed using an ELISpot assay in vaccine-naive individuals with different humoral responses: Ig (IgM and/or IgG) seronegative (n = 90) and seropositive (n = 181) with low (<300 U/mL) or high (≥300 U/mL) humoral responses to the spike receptor binding domain (anti-S-RBD). Among the seropositive participants, 71.3% (129/181) were IFNγ ELISpot positive, compared to 15.6% (14/90) among the seronegative participants. Common COVID-19 symptoms such as fever and ageusia were associated with IFNγ ELISpot positivity in seropositive participants, whereas no participant characteristics were associated with IFNγ ELISpot positivity in seronegative participants. Fever and/or dyspnea and anti-S-RBD levels were associated with higher IFNγ responses. Symptoms of more severe disease and higher anti-S-RBD responses were associated with higher IFNγ responses. A significant proportion (15.6%) of seronegative participants had a positive IFNγ ELISpot. Assessment of cellular responses may improve estimates of the immune response to SARS-CoV-2 in the general population. IMPORTANCE: Data on adaptive cellular immunity are of interest to define immune protection against severe acute respiratory syndrome coronavirus 2 in a population, which is important for decision-making on booster-vaccination strategies. This study provides data on associations between participant characteristics and cellular immune responses in vaccine-naive individuals with different humoral responses.

COVID-19 pandemic response in the Meuse-Rhine Euroregion: methods, participation and recommendations of a longitudinal cross-border study.

BACKGROUND: Comparative data collection in transborder areas can contribute to informed decision making processes when dealing with borderless health threats such as pandemics, and thus help minimize the negative health effects for its citizens. To examine the pandemic response over time and the impact of infectious disease control in a cross-border setting, a prospective longitudinal study was conducted in the border area between Germany, Belgium and the Netherlands. In the spring of 2021, a random sample of 26,925 adult citizens selected from governmental registries was invited to collect a blood sample at home for SARS-CoV-2 antibody testing and to fill in an online questionnaire on attitudes and behaviour towards infection prevention measures, cross-border mobility, social network and support, COVID-19 self-reported infection(s) and symptoms, vaccination, general self-reported health and socio-demographics. In autumn 2021, participants were invited for a follow-up round. An online tool was developed to coordinate fieldwork procedures, real-time monitoring of participation and consultation of antibody test results. Furthermore, a helpdesk in all three languages for participants' support was set up. RESULTS: In the first round, 6,006 citizens in the Meuse-Rhine Euroregion participated. 15.3% of the invited citizens on the Belgian side of the border participated. In the Netherlands and Germany this was respectively 27% and 23.7%. In the follow-up round 4,286 (71.4%) citizens participated for the second time. The participation rate was highest in the age group 50-69 years and lowest in > 80 in all sub regions of the Meuse-Rhine Euroregion. More women participated than men. Overall, more blood samples were returned than completed questionnaires. In total, 3,344 citizens in the Meuse-Rhine Euroregion completed all components of participation in both rounds. CONCLUSIONS: The collection of comparative data can help better assess the pandemic response and the impact of infectious disease control in a cross-border area. Recommendations for a longitudinal cross-border study include a centralized online environment, mapping out potential challenges related to national regulations in the preparation phase and organizing regional coordination centres to create more familiarity and trust towards the involved organisations.

Augmented Lagrange methods for quasi-incompressible materials--applications to soft biological tissue.

Arterial walls in the healthy physiological regime are characterized by quasi-incompressible, anisotropic, hyperelastic material behavior. Polyconvex material functions representing such materials typically incorporate a penalty function to account for the incompressibility. Unfortunately, the penalty will affect the conditioning of the stiffness matrices. For high penalty parameters, the performance of iterative solvers will degrade, and when direct solvers are used, the quality of the solutions will deteriorate. In this paper, an augmented Lagrange approach is used to cope with the quasi-incompressibility condition. Here, the penalty parameter can be chosen much smaller, and as a consequence, the arising linear systems of equations have better properties. An improved convergence is then observed for the finite element tearing and interconnecting-dual primal domain decomposition method, which is used as an iterative solver. Numerical results for an arterial geometry obtained from ultrasound imaging are presented.