The common interests of health protection and the economy: evidence from scenario calculations of COVID-19 containment policies.

We develop a novel approach integrating epidemiological and economic models that allows data-based simulations during a pandemic. We examine the economically optimal opening strategy that can be reconciled with the containment of a pandemic. The empirical evidence is based on data from Germany during the SARS-CoV-2 pandemic. Our empirical findings reject the view that there is necessarily a conflict between health protection and economic interests and suggest a non-linear U-shape relationship: it is in the interest of public health and the economy to balance non-pharmaceutical interventions in a manner that further reduces the incidence of infections. Our simulations suggest that a prudent strategy that leads to a reproduction number of around 0.75 is economically optimal. Too restrictive policies cause massive economic costs. Conversely, policies that are too loose lead to higher death tolls and higher economic costs in the long run. We suggest this finding as a guide for policy-makers in balancing interests of public health and the economy during a pandemic.

Improving Public Health Policy by Comparing the Public Response during the Start of COVID-19 and Monkeypox on Twitter in Germany: A Mixed Methods Study.

Little is known about monkeypox public concerns since its widespread emergence in many countries. Tweets in Germany were examined in the first three months of COVID-19 and monkeypox to examine concerns and issues raised by the public. Understanding views and positions of the public could help to shape future public health campaigns. Few qualitative studies reviewed large datasets, and the results provide the first instance of the public thinking comparing COVID-19 and monkeypox. We retrieved 15,936 tweets from Germany using query words related to both epidemics in the first three months of each one. A sequential explanatory mixed methods research joined a machine learning approach with thematic analysis using a novel rapid tweet analysis protocol. In COVID-19 tweets, there was the selfing construct or feeling part of the emerging narrative of the spread and response. In contrast, during monkeypox, the public considered othering after the fatigue of the COVID-19 response, or an impersonal feeling toward the disease. During monkeypox, coherence and reconceptualization of new and competing information produced a customer rather than a consumer/producer model. Public healthcare policy should reconsider a one-size-fits-all model during information campaigns and produce a strategic approach embedded within a customer model to educate the public about preventative measures and updates. A multidisciplinary approach could prevent and minimize mis/disinformation.

In silico predicted therapy against chronic Staphylococcus aureus infection leads to bacterial clearance in vivo.

Staphylococcus aureus can lead to chronic infections and abscesses in internal organs including kidneys, which are associated with the expansion of myeloid-derived suppressor cells (MDSCs) and their suppressive effect on T cells. Here, we developed a mathematical model of chronic S. aureus infection that incorporates the T-cell suppression by MDSCs and suggests therapeutic strategies for S. aureus clearance. A therapeutic protocol with heat-killed S. aureus (HKSA) was quantified in silico and tested in vivo. Contrary to the conventional administration of heat-killed bacteria as vaccination prior to infection, we administered HKSA as treatment in chronically infected hosts. Our treatment eliminated S. aureus in kidneys of all chronically S. aureus-infected mice, reduced MDSCs, and reversed T-cell dysfunction by inducing acute inflammation during ongoing, chronic infection. This study is a guideline for a treatment protocol against chronic S. aureus infection and renal abscesses by repurposing heat-killed treatments, directed by mathematical modeling.

Testing and isolation to prevent overloaded healthcare facilities and reduce death rates in the SARS-CoV-2 pandemic in Italy.

Background: During the first wave of COVID-19, hospital and intensive care unit beds got overwhelmed in Italy leading to an increased death burden. Based on data from Italian regions, we disentangled the impact of various factors contributing to the bottleneck situation of healthcare facilities, not well addressed in classical SEIR-like models. A particular emphasis was set on the undetected fraction (dark figure), on the dynamically changing hospital capacity, and on different testing, contact tracing, quarantine strategies. Methods: We first estimated the dark figure for different Italian regions. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread, the model was optimized to fit data (infected, hospitalized, ICU, dead) published by the Italian Civil Protection. Results: We show that testing influenced the infection dynamics by isolation of newly detected cases and subsequent interruption of infection chains. The time-varying reproduction number (R t) in high testing regions decreased to <1 earlier compared to the low testing regions. While an early test and isolate (TI) scenario resulted in up to ~31% peak reduction of hospital occupancy, the late TI scenario resulted in an overwhelmed healthcare system. Conclusions: An early TI strategy would have decreased the overall hospital usage drastically and, hence, death toll (∼34% reduction in Lombardia) and could have mitigated the lack of healthcare facilities in the course of the pandemic, but it would not have kept the hospitalization amount within the pre-pandemic hospital limit.

Nitric oxide controls proliferation of Leishmania major by inhibiting the recruitment of permissive host cells.

Nitric oxide (NO) is an important antimicrobial effector but also prevents unnecessary tissue damage by shutting down the recruitment of monocyte-derived phagocytes. Intracellular pathogens such as Leishmania major can hijack these cells as a niche for replication. Thus, NO might exert containment by restricting the availability of the cellular niche required for efficient pathogen proliferation. However, such indirect modes of action remain to be established. By combining mathematical modeling with intravital 2-photon biosensors of pathogen viability and proliferation, we show that low L. major proliferation results not from direct NO impact on the pathogen but from reduced availability of proliferation-permissive host cells. Although inhibiting NO production increases recruitment of these cells, and thus pathogen proliferation, blocking cell recruitment uncouples the NO effect from pathogen proliferation. Therefore, NO fulfills two distinct functions for L. major containment: permitting direct killing and restricting the supply of proliferation-permissive host cells.

Assessment of effective mitigation and prediction of the spread of SARS-CoV-2 in Germany using demographic information and spatial resolution.

Non-pharmaceutical interventions (NPIs) are important to mitigate the spread of infectious diseases as long as no vaccination or outstanding medical treatments are available. We assess the effectiveness of the sets of non-pharmaceutical interventions that were in place during the course of the Coronavirus disease 2019 (Covid-19) pandemic in Germany. Our results are based on hybrid models, combining SIR-type models on local scales with spatial resolution. In order to account for the age-dependence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we include realistic prepandemic and recently recorded contact patterns between age groups. The implementation of non-pharmaceutical interventions will occur on changed contact patterns, improved isolation, or reduced infectiousness when, e.g., wearing masks. In order to account for spatial heterogeneity, we use a graph approach and we include high-quality information on commuting activities combined with traveling information from social networks. The remaining uncertainty will be accounted for by a large number of randomized simulation runs. Based on the derived factors for the effectiveness of different non-pharmaceutical interventions over the past months, we provide different forecast scenarios for the upcoming time.

Correction: Repertoire characterization and validation of gB-specific human IgGs directly cloned from humanized mice vaccinated with dendritic cells and protected against HCMV.

[This corrects the article DOI: 10.1371/journal.ppat.1008560.].

Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures.

BACKGROUND: SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. METHODS: We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. RESULTS: The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2-3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. CONCLUSIONS: The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.

An Adaptive Control Scheme for Interleukin-2 Therapy.

Regulatory T cells (Treg) are suppressor cells that control self-reactive and excessive effector conventional T helper cell (Tconv) responses. Breakdown of the balance between Tregs and Tconvs is a hallmark of autoimmune and inflammatory diseases. Interleukin-2 (IL-2) is a growth factor for both populations and subtle leverage to restore the healthy immune balance in IL-2 therapy. By using a mechanistic mathematical model, we introduced an adaptive control strategy to design the minimal therapeutic IL-2 dosage required to increase and stabilize Treg population and restrict inflammatory response. This adaptive protocol allows for dose adjustments based on the feedback of the immune kinetics of the patient. Our simulation results showed that a minimal Treg population was required to restrict the transient side effect of IL-2 injections on the effector Tconv response. In silico results suggested that a combination of IL-2 and adoptive Treg transfer therapies can limit this side effect.

Mathematical Model Shows How Sleep May Affect Amyloid-ß Fibrillization.

Deposition of amyloid-ß (Aß) fibers in the extracellular matrix of the brain is a ubiquitous feature associated with several neurodegenerative disorders, especially Alzheimer's disease (AD). Although many of the biological aspects that contribute to the formation of Aß plaques are well addressed at the intra- and intercellular levels in short timescales, an understanding of how Aß fibrillization usually starts to dominate at a longer timescale despite the presence of mechanisms dedicated to Aß clearance is still lacking. Furthermore, no existing mathematical model integrates the impact of diurnal neural activity as emanated from circadian regulation to predict disease progression due to a disruption in the sleep-wake cycle. In this study, we develop a minimal model of Aß fibrillization to investigate the onset of AD over a long timescale. Our results suggest that the diseased state is a manifestation of a phase change of the system from soluble Aß (sAß) to fibrillar Aß (fAß) domination upon surpassing a threshold in the production rate of sAß. By incorporating the circadian rhythm into our model, we reveal that fAß accumulation is crucially dependent on the regulation of the sleep-wake cycle, thereby indicating the importance of good sleep hygiene in averting AD onset. We also discuss potential intervention schemes to reduce fAß accumulation in the brain by modification of the critical sAß production rate.

Repertoire characterization and validation of gB-specific human IgGs directly cloned from humanized mice vaccinated with dendritic cells and protected against HCMV.

Human cytomegalovirus (HCMV) causes serious complications to immune compromised hosts. Dendritic cells (iDCgB) expressing granulocyte-macrophage colony-stimulating factor, interferon-alpha and HCMV-gB were developed to promote de novo antiviral adaptive responses. Mice reconstituted with a human immune system (HIS) were immunized with iDCgB and challenged with HCMV, resulting into 93% protection. Immunization stimulated the expansion of functional effector memory CD8+ and CD4+ T cells recognizing gB. Machine learning analyses confirmed bone marrow T/CD4+, liver B/IgA+ and spleen B/IgG+ cells as predictive biomarkers of immunization (≈87% accuracy). CD8+ and CD4+ T cell responses against gB were validated. Splenic gB-binding IgM-/IgG+ B cells were sorted and analyzed at a single cell level. iDCgB immunizations elicited human-like IgG responses with a broad usage of various IgG heavy chain V gene segments harboring variable levels of somatic hypermutation. From this search, two gB-binding human monoclonal IgGs were generated that neutralized HCMV infection in vitro. Passive immunization with these antibodies provided proof-of-concept evidence of protection against HCMV infection. This HIS/HCMV in vivo model system supported the validation of novel active and passive immune therapies for future clinical translation.

PD-1 Blockade Aggravates Epstein-Barr Virus+ Post-Transplant Lymphoproliferative Disorder in Humanized Mice Resulting in Central Nervous System Involvement and CD4+ T Cell Dysregulations.

Post-transplant lymphoproliferative disorder (PTLD) is one of the most common malignancies after solid organ or allogeneic stem cell transplantation. Most PTLD cases are B cell neoplasias carrying Epstein-Barr virus (EBV). A therapeutic approach is reduction of immunosuppression to allow T cells to develop and combat EBV. If this is not effective, approaches include immunotherapies such as monoclonal antibodies targeting CD20 and adoptive T cells. Immune checkpoint inhibition (ICI) to treat EBV+ PTLD was not established clinically due to the risks of organ rejection and graft-versus-host disease. Previously, blockade of the programmed death receptor (PD)-1 by a monoclonal antibody (mAb) during ex vivo infection of mononuclear cells with the EBV/M81+ strain showed lower xenografted lymphoma development in mice. Subsequently, fully humanized mice infected with the EBV/B95-8 strain and treated in vivo with a PD-1 blocking mAb showed aggravation of PTLD and lymphoma development. Here, we evaluated vis-a-vis in fully humanized mice after EBV/B95-8 or EBV/M81 infections the effects of a clinically used PD-1 blocker. Fifteen to 17 weeks after human CD34+ stem cell transplantation, Nod.Rag.Gamma mice were infected with two types of EBV laboratory strains expressing firefly luciferase. Dynamic optical imaging analyses showed systemic EBV infections and this triggered vigorous human CD8+ T cell expansion. Pembrolizumab administered from 2 to 5 weeks post-infections significantly aggravated EBV systemic spread and, for the M81 model, significantly increased the mortality of mice. ICI promoted Ki67+CD30+CD20+EBER+PD-L1+ PTLD with central nervous system (CNS) involvement, mirroring EBV+ CNS PTLD in humans. PD-1 blockade was associated with lower frequencies of circulating T cells in blood and with a profound collapse of CD4+ T cells in lymphatic tissues. Mice treated with pembrolizumab showed an escalation of exhausted T cells expressing TIM-3, and LAG-3 in tissues, higher levels of several human cytokines in plasma and high densities of FoxP3+ regulatory CD4+ and CD8+ T cells in the tumor microenvironment. We conclude that PD-1 blockade during acute EBV infections driving strong CD8+ T cell priming decompensates T cell development towards immunosuppression. Given the variety of preclinical models available, our models conferred a cautionary note indicating that PD-1 blockade aggravated the progression of EBV+ PTLD.

Signatures of T and B Cell Development, Functional Responses and PD-1 Upregulation After HCMV Latent Infections and Reactivations in Nod.Rag.Gamma Mice Humanized With Cord Blood CD34+ Cells.

Human cytomegalovirus (HCMV) latency is typically harmless but reactivation can be largely detrimental to immune compromised hosts. We modeled latency and reactivation using a traceable HCMV laboratory strain expressing the Gaussia luciferase reporter gene (HCMV/GLuc) in order to interrogate the viral modulatory effects on the human adaptive immunity. Humanized mice with long-term (more than 17 weeks) steady human T and B cell immune reconstitutions were infected with HCMV/GLuc and 7 weeks later were further treated with granulocyte-colony stimulating factor (G-CSF) to induce viral reactivations. Whole body bio-luminescence imaging analyses clearly differentiated mice with latent viral infections vs. reactivations. Foci of vigorous viral reactivations were detectable in liver, lymph nodes and salivary glands. The number of viral genome copies in various tissues increased upon reactivations and were detectable in sorted human CD14+, CD169+, and CD34+ cells. Compared with non-infected controls, mice after infections and reactivations showed higher thymopoiesis, systemic expansion of Th, CTL, Treg, and Tfh cells and functional antiviral T cell responses. Latent infections promoted vast development of memory CD4+ T cells while reactivations triggered a shift toward effector T cells expressing PD-1. Further, reactivations prompted a marked development of B cells, maturation of IgG+ plasma cells, and HCMV-specific antibody responses. Multivariate statistical methods were employed using T and B cell immune phenotypic profiles obtained with cells from several tissues of individual mice. The data was used to identify combinations of markers that could predict an HCMV infection vs. reactivation status. In spleen, but not in lymph nodes, higher frequencies of effector CD4+ T cells expressing PD-1 were among the factors most suited to distinguish HCMV reactivations from infections. These results suggest a shift from a T cell dominated immune response during latent infections toward an exhausted T cell phenotype and active humoral immune response upon reactivations. In sum, this novel in vivo humanized model combined with advanced analyses highlights a dynamic system clearly specifying the immunological spatial signatures of HCMV latency and reactivations. These signatures can be merged as predictive biomarker clusters that can be applied in the clinical translation of new therapies for the control of HCMV reactivation.

Characterization of CTLA4 Trafficking and Implications for Its Function.

CTLA4 is an essential negative regulator of T-cell immune responses and a key checkpoint regulating autoimmunity and antitumor responses. Genetic mutations resulting in quantitative defects in the CTLA4 pathway are also associated with the development of immune dysregulation syndromes in humans. It has been proposed that CTLA4 functions to remove its ligands CD80 and CD86 from opposing cells by a process known as transendocytosis. A quantitative characterization of CTLA4 synthesis, endocytosis, degradation, and recycling and how these affect its function is currently lacking. In a combined in vitro and in silico study, we developed a mathematical model and identified these trafficking parameters. Our model predicts optimal ligand removal in an intermediate affinity range. The intracellular CTLA4 pool as well as fast internalization, recovery of free CTLA4 from internalized complexes, and recycling is critical for sustained functionality. CD80-CTLA4 interactions are predicted to dominate over CD86-CTLA4. Implications of these findings in the context of control of antigen-presenting cells by regulatory T cells and of pathologic genetic deficiencies are discussed. The presented mathematical model can be reused in the community beyond these questions to better understand other trafficking receptors and study the impact of CTLA4 targeting drugs.

Foxp3+ regulatory T-cell homeostasis quantitatively differs in murine peripheral lymph nodes and spleen.

Regulatory T (Treg) cells are essential for maintaining self-tolerance and modulating inflammatory immune responses. Treg cells either develop within the thymus or are converted from CD4(+) naive T (Tnaive) cells in the periphery. The Treg-cell population size is tightly controlled and Treg-cell development and homeostasis have been intensively studied; however, quantitative information about mechanisms of peripheral Treg-cell homeostasis is lacking. Here we developed the first mathematical model of peripheral Treg-cell homeostasis, incorporating secondary lymphoid organs as separate entities and encompassing factors determining the size of the Treg-cell population, namely thymic output, homeostatic proliferation, peripheral conversion, transorgan migration, apoptosis, and the Tnaive-cell population. Quantitative data were collected by monitoring Tnaive-cell homeostasis and Treg-cell rebound after selective in vivo depletion of Treg cells. Our model predicted the previously unanticipated possibility that Treg cells regulate migration of Tnaive cells between spleen and peripheral lymph nodes (LNs), whereas migration of Treg cells between these organs can largely be neglected. Furthermore, our simulations suggested that peripheral conversion significantly contributed to the maintenance of the Treg-cell population, especially in LNs. Hence, we provide the first estimation of the peripheral Treg-cell conversion rate and propose additional facets of Treg-cell-mediated immune regulation that may previously have escaped attention.

A signal integration model of thymic selection and natural regulatory T cell commitment.

The extent of TCR self-reactivity is the basis for selection of a functional and self-tolerant T cell repertoire and is quantified by repeated engagement of TCRs with a diverse pool of self-peptides complexed with self-MHC molecules. The strength of a TCR signal depends on the binding properties of a TCR to the peptide and the MHC, but it is not clear how the specificity to both components drives fate decisions. In this study, we propose a TCR signal-integration model of thymic selection that describes how thymocytes decide among distinct fates, not only based on a single TCR-ligand interaction, but taking into account the TCR stimulation history. These fates are separated based on sustained accumulated signals for positive selection and transient peak signals for negative selection. This spans up the cells into a two-dimensional space where they are either neglected, positively selected, negatively selected, or selected as natural regulatory T cells (nTregs). We show that the dynamics of the integrated signal can serve as a successful basis for extracting specificity of thymocytes to MHC and detecting the existence of cognate self-peptide-MHC. It allows to select a self-MHC-biased and self-peptide-tolerant T cell repertoire. Furthermore, nTregs in the model are enriched with MHC-specific TCRs. This allows nTregs to be more sensitive to activation and more cross-reactive than conventional T cells. This study provides a mechanistic model showing that time integration of TCR-mediated signals, as opposed to single-cell interaction events, is needed to gain a full view on the properties emerging from thymic selection.

A mathematical model of immune activation with a unified self-nonself concept.

The adaptive immune system reacts against pathogenic nonself, whereas it normally remains tolerant to self. The initiation of an immune response requires a critical antigen(Ag)-stimulation and a critical number of Ag-specific T cells. Autoreactive T cells are not completely deleted by thymic selection and partially present in the periphery of healthy individuals that respond in certain physiological conditions. A number of experimental and theoretical models are based on the concept that structural differences discriminate self from nonself. In this article, we establish a mathematical model for immune activation in which self and nonself are not distinguished. The model considers the dynamic interplay of conventional T cells, regulatory T cells (Tregs), and IL-2 molecules and shows that the renewal rate ratio of resting Tregs to naïve T cells as well as the proliferation rate of activated T cells determine the probability of immune stimulation. The actual initiation of an immune response, however, relies on the absolute renewal rate of naïve T cells. This result suggests that thymic selection reduces the probability of autoimmunity by increasing the Ag-stimulation threshold of self reaction which is established by selection of a low number of low-avidity autoreactive T cells balanced with a proper number of Tregs. The stability analysis of the ordinary differential equation model reveals three different possible immune reactions depending on critical levels of Ag-stimulation: a subcritical stimulation, a threshold stimulation inducing a proper immune response, and an overcritical stimulation leading to chronic co-existence of Ag and immune activity. The model exhibits oscillatory solutions in the case of persistent but moderate Ag-stimulation, while the system returns to the homeostatic state upon Ag clearance. In this unifying concept, self and nonself appear as a result of shifted Ag-stimulation thresholds which delineate these three regimes of immune activation.