The influence of cross-border mobility on the COVID-19 epidemic in Nordic countries.

Restrictions of cross-border mobility are typically used to prevent an emerging disease from entering a country in order to slow down its spread. However, such interventions can come with a significant societal cost and should thus be based on careful analysis and quantitative understanding on their effects. To this end, we model the influence of cross-border mobility on the spread of COVID-19 during 2020 in the neighbouring Nordic countries of Denmark, Finland, Norway and Sweden. We investigate the immediate impact of cross-border travel on disease spread and employ counterfactual scenarios to explore the cumulative effects of introducing additional infected individuals into a population during the ongoing epidemic. Our results indicate that the effect of inter-country mobility on epidemic growth is non-negligible essentially when there is sizeable mobility from a high prevalence country or countries to a low prevalence one. Our findings underscore the critical importance of accurate data and models on both epidemic progression and travel patterns in informing decisions related to inter-country mobility restrictions.

Collaborative nowcasting of COVID-19 hospitalization incidences in Germany.

Real-time surveillance is a crucial element in the response to infectious disease outbreaks. However, the interpretation of incidence data is often hampered by delays occurring at various stages of data gathering and reporting. As a result, recent values are biased downward, which obscures current trends. Statistical nowcasting techniques can be employed to correct these biases, allowing for accurate characterization of recent developments and thus enhancing situational awareness. In this paper, we present a preregistered real-time assessment of eight nowcasting approaches, applied by independent research teams to German 7-day hospitalization incidences during the COVID-19 pandemic. This indicator played an important role in the management of the outbreak in Germany and was linked to levels of non-pharmaceutical interventions via certain thresholds. Due to its definition, in which hospitalization counts are aggregated by the date of case report rather than admission, German hospitalization incidences are particularly affected by delays and can take several weeks or months to fully stabilize. For this study, all methods were applied from 22 November 2021 to 29 April 2022, with probabilistic nowcasts produced each day for the current and 28 preceding days. Nowcasts at the national, state, and age-group levels were collected in the form of quantiles in a public repository and displayed in a dashboard. Moreover, a mean and a median ensemble nowcast were generated. We find that overall, the compared methods were able to remove a large part of the biases introduced by delays. Most participating teams underestimated the importance of very long delays, though, resulting in nowcasts with a slight downward bias. The accompanying prediction intervals were also too narrow for almost all methods. Averaged over all nowcast horizons, the best performance was achieved by a model using case incidences as a covariate and taking into account longer delays than the other approaches. For the most recent days, which are often considered the most relevant in practice, a mean ensemble of the submitted nowcasts performed best. We conclude by providing some lessons learned on the definition of nowcasting targets and practical challenges.

Bayesian nowcasting with leading indicators applied to COVID-19 fatalities in Sweden.

The real-time analysis of infectious disease surveillance data is essential in obtaining situational awareness about the current dynamics of a major public health event such as the COVID-19 pandemic. This analysis of e.g., time-series of reported cases or fatalities is complicated by reporting delays that lead to under-reporting of the complete number of events for the most recent time points. This can lead to misconceptions by the interpreter, for instance the media or the public, as was the case with the time-series of reported fatalities during the COVID-19 pandemic in Sweden. Nowcasting methods provide real-time estimates of the complete number of events using the incomplete time-series of currently reported events and information about the reporting delays from the past. In this paper we propose a novel Bayesian nowcasting approach applied to COVID-19-related fatalities in Sweden. We incorporate additional information in the form of time-series of number of reported cases and ICU admissions as leading signals. We demonstrate with a retrospective evaluation that the inclusion of ICU admissions as a leading signal improved the nowcasting performance of case fatalities for COVID-19 in Sweden compared to existing methods.

Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies.

Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics.

In Vivo Bioconcentration of 10 Anionic Surfactants in Rainbow Trout Explained by In Vitro Data on Partitioning and S9 Clearance.

Bioconcentration factors (BCFs) in rainbow trout were measured for 10 anionic surfactants with a range of alkyl chain lengths and different polar head groups. The BCFs ranged from 0.04 L kg-1 ww (for C10SO3) to 1370 L kg-1 ww (C16SO3). There was a strong correlation between the log BCF and log membrane lipid-water distribution ratio (DMLW, r2 = 0.96), and biotransformation was identified as the dominant elimination mechanism. The strong positive influence of DMLW on BCF was attributed to two phenomena: (i) increased partitioning from water into the epithelial membrane of the gill, leading to more rapid diffusion across this barrier and more rapid uptake, and (ii) increased sequestration of the surfactant body burden into membranes and other body tissues, resulting in lower freely dissolved concentrations available for biotransformation. Estimated whole-body in vivo biotransformation rate constants kB-BCF are within a factor three of rate constants estimated from S9 in vitro assays for six of the eight test chemicals for which kB-BCF could be determined. A model-based assessment indicated that the hepatic clearance rate of freely dissolved chemicals was similar for the studied surfactants. The dataset will be useful for evaluation of in silico and in vitro methods to assess bioaccumulation.

Changes in healthcare seeking and lifestyle in old aged individuals during COVID-19 lockdown in Germany: the population-based AugUR study.

BACKGROUND: Containment measures in the COVID-19 pandemic protected individuals at high risk, particularly individuals at old age, but little is known about how these measures affected health-related behavior of old aged individuals. We aimed to investigate the impact of the spring 2020 lockdown in Germany on healthcare-seeking and health-related lifestyle in the old aged and to identify susceptible subgroups. METHODS: We conducted a follow-up survey among the pre-pandemically well-characterized participants of our AugUR cohort study, residents in/around Regensburg aged 70+ years and relatively mobile. A self-completion questionnaire on current behavior, perceived changes, and SARS-Cov-2 infection was mailed in May 2020, shortly before contact restrictions ended. Pre-pandemic lifestyle and medical conditions were derived from previous study center visits. RESULTS: Among 1850 survey participants (73-98 years; net-response 89%), 74% were at increased risk for severe COVID-19 according to medical conditions; four participants reported SARS-CoV-2 infection (0.2%). Participants reported changes in behavior: 29% refrained from medical appointments, 14% increased TV consumption, 26% reported less physical activity, but no systematic increase of smoking or alcohol consumption. When comparing during- and pre-lockdown reports of lifestyle within participant, we found the same pattern as for the reported perceived changes. Women and the more educated were more susceptible to changes. Worse QOL was perceived by 38%. CONCLUSIONS: Our data suggest that the spring 2020 lockdown did not affect the lifestyle of a majority of the mobile old aged individuals, but the substantial proportions with decreased physical activity and healthcare-seeking are markers of collateral damage.

Analysis of the early COVID-19 epidemic curve in Germany by regression models with change points.

We analysed the coronavirus disease 2019 epidemic curve from March to the end of April 2020 in Germany. We use statistical models to estimate the number of cases with disease onset on a given day and use back-projection techniques to obtain the number of new infections per day. The respective time series are analysed by a trend regression model with change points. The change points are estimated directly from the data. We carry out the analysis for the whole of Germany and the federal state of Bavaria, where we have more detailed data. Both analyses show a major change between 9 and 13 March for the time series of infections: from a strong increase to a decrease. Another change was found between 25 March and 29 March, where the decline intensified. Furthermore, we perform an analysis stratified by age. A main result is a delayed course of the pandemic for the age group 80 + resulting in a turning point at the end of March. Our results differ from those by other authors as we take into account the reporting delay, which turned out to be time dependent and therefore changes the structure of the epidemic curve compared to the curve of newly reported cases.

Nowcasting the COVID-19 pandemic in Bavaria.

To assess the current dynamics of an epidemic, it is central to collect information on the daily number of newly diseased cases. This is especially important in real-time surveillance, where the aim is to gain situational awareness, for example, if cases are currently increasing or decreasing. Reporting delays between disease onset and case reporting hamper our ability to understand the dynamics of an epidemic close to now when looking at the number of daily reported cases only. Nowcasting can be used to adjust daily case counts for occurred-but-not-yet-reported events. Here, we present a novel application of nowcasting to data on the current COVID-19 pandemic in Bavaria. It is based on a hierarchical Bayesian model that considers changes in the reporting delay distribution over time and associated with the weekday of reporting. Furthermore, we present a way to estimate the effective time-varying case reproduction number Re(t) based on predictions of the nowcast. The approaches are based on previously published work, that we considerably extended and adapted to the current task of nowcasting COVID-19 cases. We provide methodological details of the developed approach, illustrate results based on data of the current pandemic, and evaluate the model based on synthetic and retrospective data on COVID-19 in Bavaria. Results of our nowcasting are reported to the Bavarian health authority and published on a webpage on a daily basis (https://corona.stat.uni-muenchen.de/). Code and synthetic data for the analysis are available from https://github.com/FelixGuenther/nc_covid19_bavaria and can be used for adaption of our approach to different data.

On the differences between mega- and meta-imputation and analysis exemplified on the genetics of age-related macular degeneration.

While current genome-wide association analyses often rely on meta-analysis of study-specific summary statistics, individual participant data (IPD) from multiple studies increase options for modeling. When multistudy IPD is available, however, it is unclear whether this data is to be imputed and modeled across all participants (mega-imputation and mega-analysis) or study-specifically (meta-imputation and meta-analysis). Here, we investigated different approaches toward imputation and analysis using 52,189 subjects from 25 studies of the International Age-related Macular Degeneration (AMD) Genomics Consortium including, 16,144 AMD cases and 17,832 controls for association analysis. From 27,448,454 genetic variants after 1,000-Genomes-based imputation, mega-imputation yielded ~400,000 more variants with high imputation quality (mostly rare variants) compared to meta-imputation. For AMD signal detection (P < 5 × 10-8 ) in mega-imputed data, most loci were detected with mega-analysis without adjusting for study membership (40 loci, including 34 known); we considered these loci genuine, since genetic effects and P-values were comparable across analyses. In meta-imputed data, we found 31 additional signals, mostly near chromosome tails or reference panel gaps, which disappeared after accounting for interaction of whole-genome amplification (WGA) with study membership or after excluding studies with WGA-participants. For signal detection with multistudy IPD, we recommend mega-imputation and mega-analysis, with meta-imputation followed by meta-analysis being a computationally appealing alternative.

Outcome of Psychoanalytic and Cognitive-Behavioural Long-Term Therapy with Chronically Depressed Patients: A Controlled Trial with Preferential and Randomized Allocation.

OBJECTIVE: For chronic depression, the effectiveness of brief psychotherapy has been limited. This study is the first comparing the effectiveness of long-term cognitive-behavioural therapy (CBT) and long-term psychoanalytic therapy (PAT) of chronically depressed patients and the effects of preferential or randomized allocation. METHODS: A total of 252 adults met the inclusion criteria (aged 21-60 years, major depression, dysthymia, double depression for at least 24 months, Quick Inventory of Depressive Symptoms [QIDS] >9, Beck Depression Inventory II [BDI] >17, informed consent, not meeting exclusion criteria). Main outcome measures were depression self-rating (BDI) and rating (clinician-rated QIDS [QIDS-C]) by independent, treatment-blinded clinicians. Full remission rates (BDI ≤12, QIDS-C ≤5) were calculated. An independent center for data management and biostatistics analyzed the treatment effects and differences using linear mixed models (multilevel models and hierarchical models). RESULTS: The average BDI declined from 32.1 points by 12.1 points over the first year and 17.2 points over 3 years. BDI overall mean effect sizes increased from d = 1.17 after 1 year to d = 1.83 after 3 years. BDI remission rates increased from 34% after 1 year to 45% after 3 years. QIDS-C overall effect sizes increased from d = 1.56 to d = 2.08, and remission rates rose from 39% after 1 year to 61% after 3 years. We found no significant differences between PAT and CBT or between preferential and randomized allocation. CONCLUSIONS: Psychoanalytic as well as cognitive-behavioural long-term treatments lead to significant and sustained improvements of depressive symptoms of chronically depressed patients exceeding effect sizes of other international outcome studies.

Response misclassification in studies on bilateral diseases.

Misclassification in binary outcomes can severely bias effect estimates of regression models when the models are naively applied to error-prone data. Here, we discuss response misclassification in studies on the special class of bilateral diseases. Such diseases can affect neither, one, or both entities of a paired organ, for example, the eyes or ears. If measurements are available on both organ entities, disease occurrence in a person is often defined as disease occurrence in at least one entity. In this setting, there are two reasons for response misclassification: (a) ignorance of missing disease assessment in one of the two entities and (b) error-prone disease assessment in the single entities. We investigate the consequences of ignoring both types of response misclassification and present an approach to adjust the bias from misclassification by optimizing an adequate likelihood function. The inherent modelling assumptions and problems in case of entity-specific misclassification are discussed. This work was motivated by studies on age-related macular degeneration (AMD), a disease that can occur separately in each eye of a person. We illustrate and discuss the proposed analysis approach based on real-world data of a study on AMD and simulated data.

Quantification of Retrograde Blood Flow in the Descending Aorta Using Transesophageal Echocardiography in Comparison to 4D Flow MRI.

BACKGROUND: Retrograde diastolic blood flow in the proximal descending aorta (DAo), which connects plaques ≥4 mm thickness with brain-supplying arteries, has previously been identified as a possible source of brain embolism. Currently, only 4D flow MRI is able to visualize and quantify potential retrograde embolization pathways in the DAo in-vivo. Hence, it was our aim to test if the extent of retrograde flow could be estimated by routine 2D transesophageal echocardiography (TEE). METHODS: Forty-eight acute stroke patients were prospectively included and they underwent Doppler examinations of the transition zone between the aortic arch and the DAo using a 20 mm 2D sample volume in longitudinal section at 90-140° Doppler angle during routine TEE. Velocity-time-integrals (VTI) were studied for antegrade and retrograde velocities and the ratio (VTIratio) was calculated and correlated with the length of retrograde pathlines at that site, which were visualized using 4D flow MRI at 3-Tesla. A receiver operating characteristic (ROC) curve was used to evaluate a threshold value of VTIratio in differentiating large (≥3 cm) from small (<3 cm) retrograde flow extent. RESULTS: At the TEE measurement site, the mean VTIratio was 0.53 ± 0.16 and the mean length of retrograde pathlines reaching back into the aortic arch was 3.1 ± 1.4 cm. VTIratio was an independent predictor of retrograde pathline length (r = 0.44; p = 0.002). ROC analysis identified a VTIratio threshold value of 0.6012 with a sensitivity of 0.5, a specificity of 0.92, and positive and negative predictive values of 0.84 and 0.68, respectively. Accordingly, 11 (22.91%) patients had a VTIratio cutoff value ≥0.6012 and corresponding retrograde pathline length ≥3 cm in 4D flow MRI. CONCLUSIONS: TEE allows predicting the length of retrograde pathlines. Hence, it may offer a cost-effective way to investigate independent predictors of DAo flow reversal in large-scale studies. However, TEE is only of limited value as a screening tool for high retrograde flow in a clinical setting, as only ∼23% of patients can be spared 4D flow MRI, which remains indispensable for the exact assessment of individual embolization pathways from plaques of the DAo in-vivo.

Prevalence of potential retrograde embolization pathways in the proximal descending aorta in stroke patients and controls.

BACKGROUND: Retrograde diastolic blood flow in the proximal descending aorta (DAo) connecting complex plaques (≥4 mm thick) with brain-supplying supra-aortic arteries may constitute a source of stroke. Yet, data only from high-risk populations (cryptogenic stroke patients with aortic atheroma≥3 mm) regarding the prevalence of this potential stroke mechanism are available. We aimed to quantify the frequency of this mechanism in unselected patients with cryptogenic stroke after routine diagnostics and controls without a history of stroke. METHODS: 88 patients (67 stroke patients, 21 cardiac controls) were prospectively included. 3D T1-weighted bright blood MRI of the aorta was applied for the detection of complex DAo atheroma. ECG-triggered and navigator-gated 4D flow MRI allowed measuring time-resolved 3D blood flow in vivo. Potential retrograde embolization pathways were defined as the co-occurrence of complex plaques and retrograde blood flow in the DAo reaching the outlet of (a) the left subclavian artery, (b) the left common carotid artery, or/and (c) the brachiocephalic trunk. The frequency of these pathways was analyzed by importing 2D plaque images into 3D blood flow visualization software. RESULTS: Complex DAo plaques were more frequent in stroke patients (44 in 31/67 patients (46.3%) vs. 5 in 4/21 controls (19.1%); p=0.039), especially in older patients (29/46 (63.04%) patients≥60 years of age with 41 plaques vs. 2/21 (9.14%) patients<60 years of age with 3 plaques; p<0.001). Contrary to our assumption, retrograde diastolic blood flow at the DAo occurred in every patient irrespective of the existence of plaques with a similar extent in both groups (26±14 vs. 32±18 mm; p=0.114). Therefore, only the higher prevalence of complex DAo plaques in stroke patients resulted in a three times higher frequency of potential retrograde embolization pathways compared to controls (22/67 (32.8%) vs. 2/21 (9.5%) controls; p=0.048). CONCLUSIONS: This study revealed that retrograde flow in the descending aorta is a common phenomenon not only in stroke patients. The existence of potential retrograde embolization pathways depends mainly on the occurrence of complex plaques in the area 0 to ∼30 mm behind the outlet of the left subclavian artery, which is exposed to flow reversal. In conclusion, we have shown that the frequency of potential retrograde embolization pathways was significantly higher in stroke patients suggesting that this mechanism may play a role in retrograde brain embolism.

Genetic Risk Score Analysis Supports a Joint View of Two Classification Systems for Age-Related Macular Degeneration.

Purpose: The purpose of this study was to evaluate the utility of combining the Clinical Classification (CC) and the Three Continent age-related macular degeneration (AMD) Consortium Severity Scale (3CACSS) for classification of AMD. Methods: In two independent cross-sectional datasets of our population-based AugUR study (Altersbezogene Untersuchungen zur Gesundheit der Universität Regensburg), we graded AMD via color fundus images applying two established classification systems (CC and 3CACSS). We calculated the genetic risk score (GRS) across 50 previously identified variants for late AMD, its association via logistic regression, and area under the curve (AUC) for each AMD stage. Results: We analyzed 2188 persons aged 70 to 95 years. When comparing the two classification systems, we found a distinct pattern: CC "age-related changes" and CC "early AMD" distinguished individuals with 3CACSS "no AMD"; 3CACSS "mild/moderate/severe early AMD" stages, and distinguished CC "intermediate AMD". This suggested a 7-step scale combining the 2 systems: (i) "no AMD", (ii) "age-related changes", (iii) "very early AMD", (i.e. CC "early"), (iv) "mild early AMD", (v) "moderate early AMD", (vi) "severe early AMD", and (vii) "late AMD". GRS association and diagnostic accuracy increased stepwise by increased AMD severity in the 7-step scale and by increased restriction of controls (e.g. for CC "no AMD without age-related changes": AUC = 55.1%, 95% confidence interval [CI] = 51.6, 58.6, AUC = 62.3%, 95% CI = 59.1, 65.6, AUC = 63.8%, 95% CI = 59.3, 68.3, AUC = 78.1%, 95% CI = 73.6, 82.5, AUC = 82.2%, 95% CI = 78.4, 86.0, and AUC = 79.2%, 95% CI = 75.4, 83.0). A stepwise increase was also observed by increased drusen size and area. Conclusions: The utility of a 7-step scale is supported by our clinical and GRS data. This harmonization and full data integration provides an immediate simplification over using either CC or 3CACSS and helps to sharpen the control group.

Population-based study of the durability of humoral immunity after SARS-CoV-2 infection.

SARS-CoV-2 antibody quantity and quality are key markers of humoral immunity. However, there is substantial uncertainty about their durability. We investigated levels and temporal change of SARS-CoV-2 antibody quantity and quality. We analyzed sera (8 binding, 4 avidity assays for spike-(S-)protein and nucleocapsid-(N-)protein; neutralization) from 211 seropositive unvaccinated participants, from the population-based longitudinal TiKoCo study, at three time points within one year after infection with the ancestral SARS-CoV-2 virus. We found a significant decline of neutralization titers and binding antibody levels in most assays (linear mixed regression model, p<0.01). S-specific serum avidity increased markedly over time, in contrast to N-specific. Binding antibody levels were higher in older versus younger participants - a difference that disappeared for the asymptomatic-infected. We found stronger antibody decline in men versus women and lower binding and avidity levels in current versus never-smokers. Our comprehensive longitudinal analyses across 13 antibody assays suggest decreased neutralization-based protection and prolonged affinity maturation within one year after infection.

Higher Infection Risk among Health Care Workers and Lower Risk among Smokers Persistent across SARS-CoV-2 Waves-Longitudinal Results from the Population-Based TiKoCo Seroprevalence Study.

SARS-CoV-2 seroprevalence was reported as substantially increased in medical personnel and decreased in smokers after the first wave in spring 2020, including in our population-based Tirschenreuth Study (TiKoCo). However, it is unclear whether these associations were limited to the early pandemic and whether the decrease in smokers was due to reduced infection or antibody response. We evaluated the association of occupation and smoking with period-specific seropositivity: for the first wave until July 2020 (baseline, BL), the low infection period in summer (follow-up 1, FU1, November 2020), and the second/third wave (FU2, April 2021). We measured binding antibodies directed to SARS-CoV-2 nucleoprotein (N), viral spike protein (S), and neutralizing antibodies at BL, FU1, and FU2. Previous infection, vaccination, smoking, and occupation were assessed by questionnaires. The 4181 participants (3513/3374 at FU1/FU2) included 6.5% medical personnel and 20.4% current smokers. At all three timepoints, new seropositivity was higher in medical personnel with ORs = 1.99 (95%-CI = 1.36-2.93), 1.41 (0.29-6.80), and 3.17 (1.92-5.24) at BL, FU1, and FU2, respectively, and nearly halved among current smokers with ORs = 0.47 (95%-CI = 0.33-0.66), 0.40 (0.09-1.81), and 0.56 (0.33-0.94). Current smokers compared to never-smokers had similar antibody levels after infection or vaccination and reduced odds of a positive SARS-CoV-2 result among tested. Our data suggest that decreased seroprevalence among smokers results from fewer infections rather than reduced antibody response. The persistently higher infection risk of medical staff across infection waves, despite improved means of protection over time, underscores the burden for health care personnel.

Comparative Immunogenicity of COVID-19 Vaccines in a Population-Based Cohort Study with SARS-CoV-2-Infected and Uninfected Participants.

To assess vaccine immunogenicity in non-infected and previously infected individuals in a real-world scenario, SARS-CoV-2 antibody responses were determined during follow-up 2 (April 2021) of the population-based Tirschenreuth COVID-19 cohort study comprising 3378 inhabitants of the Tirschenreuth county aged 14 years or older. Seronegative participants vaccinated once with Vaxzevria, Comirnaty, or Spikevax had median neutralizing antibody titers ranging from ID50 = 25 to 75. Individuals with two immunizations with Comirnaty or Spikevax had higher median ID50s (of 253 and 554, respectively). Regression analysis indicated that both increased age and increased time since vaccination independently decreased RBD binding and neutralizing antibody levels. Unvaccinated participants with detectable N-antibodies at baseline (June 2020) revealed a median ID50 of 72 at the April 2021 follow-up. Previously infected participants that received one dose of Vaxzevria or Comirnaty had median ID50 to 929 and 2502, respectively. Individuals with a second dose of Comirnaty given in a three-week interval after the first dose did not have higher median antibody levels than individuals with one dose. Prior infection also primed for high systemic IgA levels in response to one dose of Comirnaty that exceeded IgA levels observed after two doses of Comirnaty in previously uninfected participants. Neutralizing antibody levels targeting the spike protein of Beta and Delta variants were diminished compared to the wild type in vaccinated and infected participants.

Incidence, progression and risk factors of age-related macular degeneration in 35-95-year-old individuals from three jointly designed German cohort studies.

OBJECTIVE: To estimate age-related macular degeneration (AMD) incidence/progression across a wide age range. METHODS AND ANALYSIS: AMD at baseline and follow-up (colour fundus imaging, Three Continent AMD Consortium Severity Scale, 3CACSS, clinical classification, CC) was assessed for 1513 individuals aged 35-95 years at baseline from three jointly designed population-based cohorts in Germany: Kooperative Gesundheitsforschung in der Region Augsburg (KORA-Fit, KORA-FF4) and Altersbezogene Untersuchungen zur Gesundheit der Universität Regensburg (AugUR) with 18-year, 14-year or 3-year follow-up, respectively. Baseline assessment included lifestyle, metabolic and genetic markers. We derived cumulative estimates, rates and risk factor association for: (1) incident early AMD, (2) incident late AMD among no AMD at baseline (definition 1), (3) incident late AMD among no/early AMD at baseline (definition 2), (4) progression from early to late AMD. RESULTS: Incidence/progression increased by age, except progression in 70+-year old. We observed 35-55-year-old with 3CACSS-based early AMD who progressed to late AMD. Predominant risk factor for incident late AMD definition 2 was early AMD followed by genetics and smoking. When separating incident late AMD definition 1 from progression (instead of combined as incident late AMD definition 2), estimates help judge an individual's risk based on age and (3CACSS) early AMD status: for example, for a 65-year old, 3-year late AMD risk with no or early AMD is 0.5% or 7%, 3-year early AMD risk is 3%; for an 85-year old, these numbers are 0.5%, 21%, 12%, respectively. For CC-based 'early/intermediate' AMD, incidence was higher, but progression was lower. CONCLUSION: We provide a practical guide for AMD risk for ophthalmology practice and healthcare management and document a late AMD risk for individuals aged <55 years.

Time Trend in SARS-CoV-2 Seropositivity, Surveillance Detection- and Infection Fatality Ratio until Spring 2021 in the Tirschenreuth County-Results from a Population-Based Longitudinal Study in Germany.

Herein, we provide results from a prospective population-based longitudinal follow-up (FU) SARS-CoV-2 serosurveillance study in Tirschenreuth, the county which was hit hardest in Germany in spring 2020 and early 2021. Of 4203 individuals aged 14 years or older enrolled at baseline (BL, June 2020), 3546 participated at FU1 (November 2020) and 3391 at FU2 (April 2021). Key metrics comprising standardized seroprevalence, surveillance detection ratio (SDR), infection fatality ratio (IFR) and success of the vaccination campaign were derived using the Roche N- and S-Elecsys anti-SARS-CoV-2 test together with a self-administered questionnaire. N-seropositivity at BL was 9.2% (1st wave). While we observed a low new seropositivity between BL and FU1 (0.9%), the combined 2nd and 3rd wave accounted for 6.1% new N-seropositives between FU1 and FU2 (ever seropositives at FU2: 15.4%). The SDR decreased from 5.4 (BL) to 1.1 (FU2) highlighting the success of massively increased testing in the population. The IFR based on a combination of serology and registration data resulted in 3.3% between November 2020 and April 2021 compared to 2.3% until June 2020. Although IFRs were consistently higher at FU2 compared to BL across age-groups, highest among individuals aged 70+ (18.3% versus 10.7%, respectively), observed differences were within statistical uncertainty bounds. While municipalities with senior care homes showed a higher IFR at BL (3.0% with senior care home vs. 0.7% w/o), this effect diminished at FU2 (3.4% vs. 2.9%). In April 2021 (FU2), vaccination rate in the elderly was high (>77.4%, age-group 80+).

Physical Activity, Incidence, and Progression of Age-Related Macular Degeneration: A Multicohort Study.

PURPOSE: To investigate the impact of physical activity (PA) on the incidence or progression of age-related macular degeneration (AMD) in the general population. DESIGN: Meta-analysis of longitudinal cohort studies. METHODS: We included 14,630 adults with no or early AMD at baseline from 7 population-based studies and examined associations of PA with AMD incidence and progression using multistate models (MSM) per study and subsequent random effects meta-analysis. Age effects were assessed using meta-regression. The main outcome measure was the hazard ratio (HR) for incident early or progression to late AMD. RESULTS: At baseline, mean age was 60.7 ± 6.9 to 76.4 ± 4.3 years, and prevalence of early AMD was 7.7% (range, 3.6%-16.9%) between cohorts. During follow-up, 1461 and 189 events occurred for early and late AMD, respectively. In meta-analyses, no or low to moderate PA (high PA as reference) was associated with an increased risk for incident early AMD (HR, 1.19; 95% CI, 1.01-1.40; P = .04), but not for late AMD. In subsequent meta-regression, we found no association of age with the effect of PA on incident AMD. CONCLUSIONS: Our study suggests high levels of PA to be protective for the development of early AMD across several population-based cohort studies. Our results establish PA as a modifiable risk factor for AMD and inform further AMD prevention strategies to reduce its public health impact.