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The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe with about 2.2 million confirmed cases and more than 150,000 deaths as of April 17, 2020. In this work, mathematical models are used to reproduce data of the early evolution of the COVID-19 outbreak in Germany, taking into account the effect of actual and hypothetical non-pharmaceutical interventions. Systems of differential equations of SEIR type are extended to account for undetected infections, stages of infection, and age groups. The models are calibrated on data until April 5. Data from April 6 to 14 are used for model validation. We simulate different possible strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually the number of fatalities. Our results suggest that a partial (and gradual) lifting of introduced control measures could soon be possible if accompanied by further increased testing activity, strict isolation of detected cases, and reduced contact to risk groups.

Menstruation has long been framed primarily as a hygiene issue, with mainstream products and public messaging emphasizing concealment and disposal of menstrual blood (MB). This has contributed to a culture of silence in which conversations about menstrual health have been marginalized in public and clinical settings. Recent international guidance, including the World Health Organization's call to reframe menstruation as a health issue, underscores the need for more open discourse. Simultaneously, social media has become a prominent space where menstruating individuals share experiences, seek advice, and challenge stigma. The resurgence of reusable menstrual products has increased users' direct observation of MB, prompting questions about variations in color, texture, and smell. These developments highlight growing curiosity about MB yet reveal persistent information gaps regarding how MB is understood outside the clinical setting. This study aimed to examine how MB is represented in social media discourse and to explore individuals' perceptions of MB's potential use as a diagnostic tool. We conducted a cross-sectional, convergent mixed methods social listening study combining qualitative content analysis, social network analysis, sentiment analysis, and descriptive statistical analysis. Data were collected from TikTok (ByteDance), Facebook (Meta), Instagram (Meta), and Reddit using Mention and Apify. Between February 1 and 28, 2025, 6263 posts and videos were extracted using 3 strategies-group searches, hashtag searches, and social listening alerts. All data were anonymized, and demographic information was unavailable. After removing duplicates, non-English content, images, and posts without reference to blood, 349 posts were included. Coding followed a multistep deductive process in Atlas.ti. All posts were assigned with quotations, which were designated with one or more codes. Network analysis examined associations between appearance descriptors and reported health conditions. Sentiment analysis assessed perceptions of MB-based diagnostics. Among the included posts (n=349), most originated from Reddit and Facebook. Seeking help (154/349, 44.1%) was the most common type of post. Appearance descriptions (n=243 posts) focused on color, particularly brown, bright red, pink, and black; consistency, particularly coagulation; and smell, mainly unpleasant. Network analysis linked specific colors and textures to perceived conditions, including miscarriage, endometriosis, hormonal changes, polycystic ovary syndrome (PCOS), and infections. Discussion of MB as a diagnostic tool (n=80 posts) was less frequent but included predominantly positive quotations (110/115, 95.7%), emphasizing accessibility, noninvasiveness, and home-based sampling. Concerns (19/115, 16.5%) focused on inclusivity, stigma, and bodily autonomy. This study demonstrates that social media serves as an important source for discussion on MB-related topics and highlights a gap between public information needs and the available scientific evidence. The findings also indicate a strong interest in MB characteristics and support further research into its diagnostic potential. To our knowledge, this is the first study to analyze social media discussions on MB characteristics and its diagnostic potential.

Despite intensive research since the emergence of SARS-CoV-2, it has remained unclear precisely which components of the early immune response protect against the development of severe COVID-19. Here, we perform a comprehensive immunogenetic and virologic analysis of nasopharyngeal and peripheral blood samples obtained during the acute phase of infection with SARS-CoV-2. We find that soluble and transcriptional markers of systemic inflammation peak during the first week after symptom onset and correlate directly with upper airways viral loads (UA-VLs), whereas the contemporaneous frequencies of circulating viral nucleocapsid (NC)-specific CD4 + and CD8 + T cells correlate inversely with various inflammatory markers and UA-VLs. In addition, we show that high frequencies of activated CD4 + and CD8 + T cells are present in acutely infected nasopharyngeal tissue, many of which express genes encoding various effector molecules, such as cytotoxic proteins and IFN-γ. The presence of IFNG mRNA-expressing CD4 + and CD8 +  T cells in the infected epithelium is further linked with common patterns of gene expression among virus-susceptible target cells and better local control of SARS-CoV-2. Collectively, these results identify an immune correlate of protection against SARS-CoV-2, which could inform the development of more effective vaccines to combat the acute and chronic illnesses attributable to COVID-19. Authors carry out an immunogenetic and virologic analysis of nasopharyngeal and peripheral blood samples, finding that early nucleocapsid-specific T cell responses associate with control of SARS-CoV-2 in the upper airways and reduced systemic inflammation before seroconversion.

COVID-19 has been spreading widely since January 2020, prompting the implementation of non-pharmaceutical interventions and vaccinations to prevent overwhelming the healthcare system. Our study models four waves of the epidemic in Munich over two years using a deterministic, biology-based mathematical model of SEIR type that incorporates both non-pharmaceutical interventions and vaccinations. We analyzed incidence and hospitalization data from Munich hospitals and used a two-step approach to fit the model parameters: first, we modeled incidence without hospitalization, and then we extended the model to include hospitalization compartments using the previous estimates as a starting point. For the first two waves, changes in key parameters, such as contact reduction and increasing vaccinations, were enough to represent the data. For wave three, the introduction of vaccination compartments was essential. In wave four, reducing contacts and increasing vaccinations were critical parameters for controlling infections. The importance of hospitalization data was highlighted, as it should have been included as a crucial parameter from the outset, along with incidence, to avoid miscommunication with the public. The emergence of milder variants like Omicron and a significant proportion of vaccinated people has made this fact even more evident.

Adaptive immune responses to structural proteins of the virion play a crucial role in protection against coronavirus disease 2019 (COVID-19). We therefore studied T cell responses against multiple SARS-CoV-2 structural proteins in a large cohort using a simple, fast, and high-throughput approach. An automated interferon gamma release assay (IGRA) for the Nucleocapsid (NC)-, Membrane (M)-, Spike-C-terminus (SCT)-, and N-terminus-protein (SNT)-specific T cell responses was performed using fresh whole blood from study subjects with convalescent, confirmed COVID-19 (n = 177, more than 200 days post infection), exposed household members (n = 145), and unexposed controls (n = 85). SARS-CoV-2-specific antibodies were assessed using Elecsys  Anti-SARS-CoV-2 (Ro-N-Ig) and Anti-SARS-CoV-2-ELISA (IgG) (EI-S1-IgG). 156 of 177 (88%) previously PCR confirmed cases were still positive by Ro-N-Ig more than 200 days after infection. In T cells, most frequently the M-protein was targeted by 88% seropositive, PCR confirmed cases, followed by SCT (85%), NC (82%), and SNT (73%), whereas each of these antigens was recognized by less than 14% of non-exposed control subjects. Broad targeting of these structural virion proteins was characteristic of convalescent SARS-CoV-2 infection; 68% of all seropositive individuals targeted all four tested antigens. Indeed, anti-NC antibody titer correlated loosely, but significantly with the magnitude and breadth of the SARS-CoV-2-specific T cell response. Age, sex, and body mass index were comparable between the different groups. SARS-CoV-2 seropositivity correlates with broad T cell reactivity of the structural virus proteins at 200 days after infection and beyond. The SARS-CoV-2-IGRA can facilitate large scale determination of SARS-CoV-2-specific T cell responses with high accuracy against multiple targets.

SARS-CoV-2 vaccine breakthrough infections frequently occurred even before the emergence of Omicron variants. Yet, relatively little is known about the impact of vaccination on SARS-CoV-2-specific T cell and antibody response dynamics upon breakthrough infection. We have therefore studied the dynamics of CD4 and CD8 T cells targeting the vaccine-encoded Spike and the non-encoded Nucleocapsid antigens during breakthrough infections (BTI, n=24) and in unvaccinated control infections (non-BTI, n=30). Subjects with vaccine breakthrough infection had significantly higher CD4 and CD8 T cell responses targeting the vaccine-encoded Spike during the first and third/fourth week after PCR diagnosis compared to non-vaccinated controls, respectively. In contrast, CD4 T cells targeting the non-vaccine encoded Nucleocapsid antigen were of significantly lower magnitude in BTI as compared to non-BTI. Hence, previous vaccination was linked to enhanced T cell responses targeting the vaccine-encoded Spike antigen, while responses against the non-vaccine encoded Nucleocapsid antigen were significantly attenuated.

Objectives Although a growing share of the population in many countries has been vaccinated against the SARS-CoV-2 virus to different degrees, social distancing and hygienic non-pharmaceutical interventions still play a substantial role in containing the pandemic. The goal of this study was to investigate which factors are correlated with a higher compliance with these regulations in the context of a cohort study in the city of Munich, southern Germany, during the summer of 2020, i.e. after the first lockdown phase. Methods Using self-reported compliance with six regulations and personal hygiene rules (washing hands, avoiding touching face, wearing a mask, keeping distance, avoiding social gatherings, avoiding public spaces) we extracted two compliance factor scores, namely compliance with personal hygiene measures and compliance with social distancing regulations . Using linear and logistic regressions, we estimated the correlation of several socio-demographic and risk perception variables with both compliance scores. Results Risk aversion proved to be a consistent and significant driver of compliance across all compliance behaviors. Furthermore, being female, being retired and having a migration background were positively associated with compliance with personal hygiene regulations, whereas older age was related with a higher compliance with social distancing regulations. Generally, socioeconomic characteristics were not related with compliance, except for education, which was negatively related with compliance with personal hygiene measures. Conclusions Our results suggest that for a targeted approach to improve compliance with measures to prevent SARS-CoV-2 infection, special attention should be given to younger, male and risk-prone individuals.

In breast cancer radiotherapy, substantial radiation exposure of organs other than the treated breast cannot be avoided, potentially inducing second primary cancer or heart disease. While distant organs and large parts of nearby ones receive doses in the mGy–Gy range, small parts of the heart, lung and bone marrow often receive doses as high as 50 Gy. Contemporary treatment planning allows for considerable flexibility in the distribution of this exposure. To optimise treatment with regards to long-term health risks, evidence-based risk estimates are required for the entire broad range of exposures. Here, we thus propose an approach that combines data from medical and epidemiological studies with different exposure conditions. Approximating cancer induction as a local process, we estimate organ cancer risks by integrating organ-specific dose–response relationships over the organ dose distributions. For highly exposed organ parts, specific high-dose risk models based on studies with medical exposure are applied. For organs or their parts receiving relatively low doses, established dose–response models based on radiation-epidemiological data are used. Joining the models in the intermediate dose range leads to a combined, in general non-linear, dose response supported by data over the whole relevant dose range. For heart diseases, a linear model consistent with high- and low-dose studies is presented. The resulting estimates of long-term health risks are largely compatible with rate ratios observed in randomised breast cancer radiotherapy trials. The risk models have been implemented in a software tool PASSOS that estimates long-term risks for individual breast cancer patients.

This study analyzes immune responses to SARS-CoV-2 vaccination and infection, including asymptomatic cases, focusing on infection risks during the Omicron wave, particularly among high-risk healthcare workers. In the KoCo-Impf study, we monitored 6088 vaccinated participants in Munich aged 18 and above. From 13 May to 31 July 2022, 2351 participants were follow-uped. Logistic regression models evaluated primary, secondary, and breakthrough infections (BTIs). Roche Elecsys® Anti-SARS-CoV-2 assays detected prior infections (via anti-Nucleocapsid antibodies) and assessed vaccination/infection impact (via anti-Spike antibodies) using dried blood spots. Our findings revealed an anti-Nucleocapsid seroprevalence of 44.1%. BTIs occurred in 38.8% of participants, with reinfections in 48.0%. Follow-up participation was inversely associated with current smoking and non-vaccination, while significantly increasing with age and receipt of three vaccine doses. Larger household sizes and younger age increased infection risks, whereas multiple vaccinations and older age reduced them. Household size and specific institutional subgroups were risk factors for BTIs. The anti-Nucleocapsid value prior to the second infection was significantly associated with reinfection risk. Institutional subgroups influenced all models, underscoring the importance of tailored outbreak responses. The KoCo-Impf study underscores the importance of vaccination, demographic factors, and institutional settings in understanding SARS-CoV-2 infection risks during the Omicron wave.

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), and SARS-CoV-2 has been linked to changes in DNA methylation (DNAm) patterns. Studies focused on post-SARS-CoV-2 infection and DNAm have been mainly carried out among severe COVID-19 cases or without distinguishing the severity of cases. However, investigations into mild and asymptomatic cases after SARS-CoV-2 infection are limited. In this study, we analyzed DNAm patterns of mild and asymptomatic cases seven months after SARS-CoV-2 infection in a household setting by conducting epigenome-wide association studies (EWAS). Results We identified DNAm changes at 42 CpG sites associated with anti-SARS-CoV-2 antibody levels. We additionally report EWAS between COVID-19 cases and controls, with the case status being confirmed by either an antibody test or a PCR test. The EWAS with an antibody test case definition identified 172 CpG sites to be differentially methylated, while the EWAS with a PCR test case definition identified 502 CpG sites. Two common sites, namely cg17126990 (annotated to AFAP1L2 ) and cg25483596 (annotated to PC ), were identified to be hypermethylated across the three EWAS. Both CpG sites have been reported to be involved in molecular pathways after SARS-CoV-2 infection. While AFAP1L2 has been found to be upregulated after SARS-CoV-2 infection, the pyruvate carboxylase (PC) activity seems to be affected by SARS-CoV-2 infection resulting in changes to the host cell metabolism. Additionally, an EWAS to assess persistent health restrictions among PCR-confirmed cases showed 40 CpG sites to be differentially methylated. Conclusions We detected associations between DNAm in individuals who had asymptomatic and mild SARS-CoV-2 infections as compared to their household controls. These findings contribute to our understanding of the molecular consequences of SARS-CoV-2 infection observed months after infection.