Towards participatory multi-modeling for policy support across domains and scales: a systematic procedure for integral multi-model design (preprint)

Policymaking for complex challenges such as pandemics necessitates the consideration of intricate implications across multiple domains and scales. Computational models can support policymaking, but a single model is often insufficient for such multidomain and scale challenges. Multi-models comprising several interacting computational models at different scales or relying on different modeling paradigms offer a potential solution. Such multi-models can be assembled from existing computational models (i.e., integrated modeling) or be designed conceptually as a whole before their computational implementation (i.e., integral modeling). Integral modeling is particularly valuable for novel policy problems, such as those faced in the early stages of a pandemic, where relevant models may be unavailable or lack standard documentation. Designing such multi-models through an integral approach is, however, a complex task requiring the collaboration of modelers and experts from various domains. In this collaborative effort, modelers must precisely define the domain knowledge needed from experts and establish a systematic procedure for translating such knowledge into a multi-model. Yet, these requirements and systematic procedures are currently lacking for multi-models that are both multiscale and multi-paradigm. We address this challenge by introducing a procedure for developing multi-models with an integral approach based on clearly defined domain knowledge requirements derived from literature. We illustrate this procedure using the case of school closure policies in the Netherlands during the COVID-19 pandemic, revealing their potential implications in the short and long term and across the healthcare and educational domains. The requirements and procedure provided in this article advance the application of integral multi-modeling for policy support in multiscale and multidomain contexts.

Drug Discovery in Low Data Regimes: Leveraging a Computational Pipeline for the Discovery of Novel SARS-CoV-2 Nsp14-MTase Inhibitors (preprint)

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to significant global morbidity and mortality. A crucial viral protein, the non-structural protein 14 (nsp14), catalyzes the methylation of viral RNA and plays a critical role in viral genome replication and transcription. Due to the low mutation rate in the nsp region among various SARS-CoV-2 variants, nsp14 has emerged as a promising therapeutic target. However, discovering potential inhibitors remains a challenge. In this work, we introduce a computational pipeline for the rapid and efficient identification of potential nsp14 inhibitors by leveraging virtual screening and the NCI open compound collection, which contains 250,000 freely available molecules for researchers worldwide. The introduced pipeline provides a cost-effective and efficient approach for early-stage drug discovery by allowing researchers to evaluate promising molecules without incurring synthesis expenses. Our pipeline successfully identified seven promising candidates after experimentally validating only 40 compounds. Notably, we discovered NSC620333, a compound that exhibits a strong binding affinity to nsp14 with a dissociation constant of 427 {+/-} 84 nM. In addition, we gained new insights into the structure and function of this protein through molecular dynamics simulations. We identified new conformational states of the protein and determined that residues Phe367, Tyr368, and Gln354 within the binding pocket serve as stabilizing residues for novel ligand interactions. We also found that metal coordination complexes are crucial for the overall function of the binding pocket. Lastly, we present the solved crystal structure of the nsp14-MTase complexed with SS148, a potent inhibitor of methyltransferase activity at the nanomolar level (IC50 value of 70 {+/-} 6 nM). Our computational pipeline accurately predicted the binding pose of SS148, demonstrating its effectiveness and potential in accelerating drug discovery efforts against SARS-CoV-2 and other emerging viruses.

Folding@home: Achievements from over 20 years of citizen science herald the exascale era.

Simulations of biomolecules have enormous potential to inform our understanding of biology but require extremely demanding calculations. For over 20 years, the Folding@home distributed computing project has pioneered a massively parallel approach to biomolecular simulation, harnessing the resources of citizen scientists across the globe. Here, we summarize the scientific and technical advances this perspective has enabled. As the project's name implies, the early years of Folding@home focused on driving advances in our understanding of protein folding by developing statistical methods for capturing long-timescale processes and facilitating insight into complex dynamical processes. Success laid a foundation for broadening the scope of Folding@home to address other functionally relevant conformational changes, such as receptor signaling, enzyme dynamics, and ligand binding. Continued algorithmic advances, hardware developments such as graphics processing unit (GPU)-based computing, and the growing scale of Folding@home have enabled the project to focus on new areas where massively parallel sampling can be impactful. While previous work sought to expand toward larger proteins with slower conformational changes, new work focuses on large-scale comparative studies of different protein sequences and chemical compounds to better understand biology and inform the development of small-molecule drugs. Progress on these fronts enabled the community to pivot quickly in response to the COVID-19 pandemic, expanding to become the world's first exascale computer and deploying this massive resource to provide insight into the inner workings of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and aid the development of new antivirals. This success provides a glimpse of what is to come as exascale supercomputers come online and as Folding@home continues its work.

Folding@home: achievements from over twenty years of citizen science herald the exascale era (preprint)

Simulations of biomolecules have enormous potential to inform our understanding of biology but require extremely demanding calculations. For over twenty years, the Folding@home distributed computing project has pioneered a massively parallel approach to biomolecular simulation, harnessing the resources of citizen scientists across the globe. Here, we summarize the scientific and technical advances this perspective has enabled. As the project's name implies, the early years of Folding@home focused on driving advances in our understanding of protein folding by developing statistical methods for capturing long-timescale processes and facilitating insight into complex dynamical processes. Success laid a foundation for broadening the scope of Folding@home to address other functionally relevant conformational changes, such as receptor signaling, enzyme dynamics, and ligand binding. Continued algorithmic advances, hardware developments such as GPU-based computing, and the growing scale of Folding@home have enabled the project to focus on new areas where massively parallel sampling can be impactful. While previous work sought to expand toward larger proteins with slower conformational changes, new work focuses on large-scale comparative studies of different protein sequences and chemical compounds to better understand biology and inform the development of small molecule drugs. Progress on these fronts enabled the community to pivot quickly in response to the COVID-19 pandemic, expanding to become the world's first exascale computer and deploying this massive resource to provide insight into the inner workings of the SARS-CoV-2 virus and aid the development of new antivirals. This success provides a glimpse of what's to come as exascale supercomputers come online, and Folding@home continues its work.

Menopause care delivery in the time of COVID-19: evaluating the acceptability of telehealth services for women with early and usual age menopause.

OBJECTIVES: This study aimed to explore women's and clinician's experiences and acceptability of telehealth use within a specialized multidisciplinary menopause service during the COVID-19 pandemic. METHODS: In-depth qualitative semi-structured interviews were analyzed via thematic inductive approaches. Telehealth acceptability was guided by the Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies (NASSS) framework. RESULTS: A heterogeneous group of 18 women who had attended the menopause service and six clinicians (gynecologists and endocrinologists) were interviewed. The majority of women and clinicians perceived telehealth as an acceptable way to deliver menopause care. Benefits of telehealth delivery were identified; themes centered around convenience, greater access to care and improved safety. Telehealth challenges included perceived impacts on personalized quality of care, patient-related logistical issues and system/organizational-related issues. A hybrid flexible delivery model combining telehealth and face-to-face care was recommended, following the easing of COVID-19 restrictions. Improvements to support embedding and adaptation of telehealth into routine care were described. CONCLUSION: In this study, telehealth was viewed as acceptable, supporting the ongoing delivery of a hybrid service model of telehealth and face-to-face menopause care. The findings provide valuable information to improve the menopause service to meet the needs of women during the ongoing current pandemic and beyond.

The Interim Case Fatality Rate (ICFR) of the COVID-19 Pandemic for Europe and the United States from March 1, 2020 to August 15, 2021. Does the ICFR Regress to the Final CFR?

OBJECTIVE: The true case fatality rate (CFR) of a disease outbreak can only be ascertained after all cases and deaths have been tabulated at the end of the epidemic. We define a metric, the interim case fatality rate (ICFR) which is the incremental change in the ratio of cases to deaths. To examine longitudinal changes in the ICFR of the COVID-19 pandemic and to evaluate the likelihood that the ICFR can predict the final CFR. METHODS: Publicly available databases were used to gather data on the number of cases and deaths in Europe and the United States (USA). These data were gathered over the period from Mar.1, 2020 to Aug. 15, 2021, on four regions of the USA and four regions of Europe on a bi-weekly basis. Statistical methods were utilized to evaluate changes over the final month of the study (July 15, 2021 to August 15, 2021). Stability of the ICFR was based on acceptance of the null hypothesis that no significant difference (p>0.05) was observed over that period. RESULTS: In all regions studied, the early months of the pandemic were marked by very high ICFRs. By late 2020, these began to stabilize at levels well below 5%. During the final month of the study, only one (Northeast USA) of the eight regions evaluated showed a statistically significant difference in ICFR. Mean ICFR projections, based on weighted values of cases are 1.8% (95% CI: 1.2% to 2.3%) for the USA and 2.1% (95% CI: 1.5% 2.7% for Europe. CONCLUSION: After an early peak, very little change was observed in the ICFR, and by summer 2021, the rates had stabilized. Weighted ICFR for all regions may well reflect the final ICFR.

The imaginative dimension of digital disinformation: Fake news, political trolling, and the entwined crises of Covid-19 and inter-Asian racism in a postcolonial city

This article uses the concept of the ?imaginative dimension of digital disinformation? to explore how inter-Asian racism in a postcolonial city matters to the way people engage with racially tinged Covid-19 digital disinformation. It pays attention to two key socialities that fake news and political trolling online seek to weaponise people's existing social narratives as well as their relationally embedded practices of media consumption. Drawing on 15 life story interviews with locals from the Philippines capital of Manila, this article characterises their interpretations of online disinformation campaigns that aim to amplify their shared social narrative of resentment towards China and bank on their communicative practices surrounding this. It also aims to show the value of empirical research that possesses a transnational sensibility in assessing the interpretive and social dynamics surrounding such racist Covid-19 digital disinformation.

Mental health experiences during a COVID19-tailored weight management programme: A qualitative study

Background: Previous research reports a lack of mental health support in weight management services. Evidence suggests that adults with overweight or obesity are at a greater risk of mental ill-health during the COVID-19 pandemic than those without a pre-existing condition, amplifying the need for mental health support. With usual support services limited due to COVID-restrictions, an acceptance-based programme (SWiM-C: Supporting Weight Management during COVID-19) was developed to remotely support adults with overweight or obesity with weight management and mental health. There is limited evidence showing how effectively acceptance-based weight management programmes support mental health, especially when delivered remotely. We aimed to explore mental health experiences during SWiM-C and looked to identify how SWiM-C could be optimised to better support mental health. Methods: Twenty participants and four providers took part in semi-structured telephone interviews. Participant interviews explored programme acceptability, SWiM-C benefits and disadvantages, and mental health experiences. Provider interviews explored experiences of supporting participants (including supporting mental health), programme acceptability, training and support, and their overall role in SWiM-C. Data for each group were analysed separately and then narratively integrated. Reflexive thematic analysis was used to identify patterns of meaning across the dataset relevant to mental health experiences. Results: Analysis of the SWiM-C participant dataset resulted in themes exploring pre-existing beliefs about mental health/weight management, factors influencing mental health, how the impacts of mental health were managed, and adaptations to optimise SWiM-C. Analysis of the provider dataset is due to commence shortly, with study completion anticipated by August 2021. Conclusions: We explore the mental health experiences of adults with overweight or obesity participating in the SWiM-C study. Specifically, we study the complexity of factors influencing mental health, the various impacts of mental health, and the degree of support from the SWiM-C programme. Findings may provide direction for health professionals, policymakers, and researchers by identifying how and where steps can be taken to better support mental health.

COVID-19 and Sickle Cell Disease in the Province of Quebec: Morbidity and Mortality Rates Derived from the Provincial Registry

Introduction Approximately 1500 people live with sickle cell disease (SCD) in the province of Quebec, Canada. Public health has recognized these patients as immunocompromised. SCD patients may be at higher risk of developing severe COVID-19 infection due to their underlying pro-inflammatory and thrombogenic state, splenic dysfunction and secondary organopathies. Descriptions about disease severity and mortality rates in SCD vary widely. From the SECURE-SCD registry, Mucalo et al. recently reported a 0.3% and 4.7% mortality rate in children and adults, respectively. In the French registry, Arlet and colleagues reported a 2.4% death rate among those hospitalized with COVID-19 and SCD, not different from the general population. As a result, the COVID-19 morbidity and mortality rates among the SCD population remain uncertain. Objectives The primary objectives of our study are to describe the epidemiology, baseline characteristics and clinical outcomes of SCD patients with COVID-19 infection in the province of Quebec. In addition, we aim to identify risk factors for hospitalization and severe forms of COVID-19. Methods We built a web-based SCD-COVID-19 registry regrouping 7 adult and 4 paediatric tertiary care hospitals in the province of Quebec in June 2020. All SCD patients with a confirmed SARS-CoV-2 infection by PCR test were included in the study. We compared the prevalence of infection and hospitalization rates of SCD patients to the general population of Quebec using the epidemiological data from the INSPQ (National Institute of Public Health of Quebec) public database. We retrospectively analyzed data included between March 11, 2020 to March 1, 2021. Relative risk was calculated using bilateral association measures (exact fisher, mid-p or chi-squared tests, as appropriate) to compare the incidence of infection and hospitalization of SCD patients to the population of Quebec and to assess risk factors of hospitalization among SCD patients. Results During the first 12 months of the pandemic, 74 patients were included in the registry. The male to female ratio was 1:1.12. Median age was 23 years, ranging from 8 months to 68 years old. SS-Sbeta 0 genotypes were present in 51% of cases, while 49% were SC or Sbeta +. The majority of patients were on disease modifying therapy: 54% were on hydroxyurea and 17.5% on exchange transfusion therapy. The incidence of reported COVID-19 infection was significantly higher in SCD patients compared to the general population (4.9% vs. 3.5% p=0,002) (Table 1). Even more strikingly, SCD had rate of hospitalization 10-times greater than the general population (33.8 vs 3.2%, p<0,001). Nevertheless, the risk of admission to the intensive care unit was similar between SCD patients and the general population (24.0% vs. 24.1%, p=0.99). No death was recorded amongst SCD patients with COVID-19 compared to a death rate in the general population in Quebec of less than 70 years old of 48-78 for 100 000 infections (male-female). A history of acute chest syndrome (ACS) in the last year (OR 2.6 [1.5-4.6], p=0.04) and arterial hypertension (OR 3.3 [2.3-4.8], p=0.01) were associated with a higher risk of hospitalization (Table 2). On the other hand, there was no statistically significant association with age, sex, genotype, ABO blood group, baseline SCD therapy, or other comorbidities (chronic renal disease, obesity, pulmonary hypertension, chronic lung disease and previous admission to ICU) in our cohort. Conclusions Similar to other reports, we found that SCD patients were at much greater risk of hospitalization compared to the general population. We however found no increased risk of mortality or disease complication. This contrasts with results from other registries. A history of ACS and hypertension were associated with a higher risk of hospitalization. Whether social determinants of health could explain some of the outcome variability between different countries merit further investigation. Furthermore, we believe that registries are critical to monitor the impact of preventive measures. As vacci ation is ongoing, it will be important to consider its impact on hospitalization and death rate among SCD population. Recruitment to the registry is ongoing and updated data will be presented at the meeting. [Formula presented] Disclosures: Soulieres: BMS: Membership on an entity's Board of Directors or advisory committees;Novartis: Research Funding. Forté: Novartis: Honoraria;Canadian Hematology Society: Research Funding;Pfizer: Research Funding.

Evaluation of the automated LIAISON® SARS-CoV-2 TrimericS IgG assay for the detection of circulating antibodies.

OBJECTIVES: COVID-19 has brought about tests from many manufacturers. While molecular and rapid antigen tests are targeted for early diagnosis, immunoassays have a larger role in epidemiological studies, understanding longitudinal immunity, and in vaccine development and response. METHODS: The performance of the LIAISON® SARS-CoV-2 TrimericS IgG assay was evaluated against the Beckman ACCESS SARS-CoV-2 IgG assay in New Mexico, and against the Siemens ADVIA Centaur COV2G assay in New York. Discordant samples were parsed using a microneutralization assay. RESULTS: A SARS-CoV-2 antibody positivity rate of 23.8% was observed in the samples tested in New York (September 2020), while in the same month the positivity rate was 1.5% in New Mexico. Positive and negative agreement were 67.6% (95% CI 49.5-82.6%) and 99.8% (95% CI 99.5-99.9%), respectively, with the Beckman test, and 98.0% (95% CI 95.7-99.3%) and 94.8% (95% CI 93.4-96.0%), respectively, with the Siemens test. Receiver operating characteristic analysis for the detection of SARS-CoV-2 antibodies discloses an AUC, area under the curve, of 0.996 (95% CI 0.992-0.999) for the LIAISON® SARS-CoV-2 TrimericS IgG assay. The criterion associated to the Youden Index was determined to be >12.9 kAU/L with a sensitivity of 99.44% and a specificity of 99.82%. CONCLUSIONS: The LIAISON® SARS-CoV-2 TrimericS IgG assay is highly sensitive and specific. The balance of these parameters, without emphasis on high specificity alone, is particularly important when applied to high prevalence populations, where a highly sensitive assay will result in reporting a lower number of false negative subjects.

Citizen Scientists Create an Exascale Computer to Combat COVID-19

The SARS-CoV-2/COVID-19 pandemic continues to threaten global health and socioeconomic stability. Experiments have revealed snapshots of many of the viral components but remain blind to moving parts of these molecular machines. To capture these essential processes, over a million citizen scientists have banded together through the Folding@home distributed computing project to create the world's first Exascale computer and simulate protein dynamics. An unprecedented 0.1 seconds of simulation of the viral proteome reveal how the spike complex uses conformational masking to evade an immune response, conformational changes implicated in the function of other viral proteins, and 'cryptic' pockets that are absent in experimental snapshots. These structures and mechanistic insights present new targets for the design of therapeutics. This living document will be updated as we perform further analysis and make the data publicly accessible.

SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome.

SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression and replication that depend on the structure and dynamics of its constituent proteins. Many protein structures have been solved, but far less is known about their relevant conformational changes. To address this challenge, over a million citizen scientists banded together through the Folding@home distributed computing project to create the first exascale computer and simulate 0.1 seconds of the viral proteome. Our adaptive sampling simulations predict dramatic opening of the apo spike complex, far beyond that seen experimentally, explaining and predicting the existence of 'cryptic' epitopes. Different spike variants modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also discover dramatic conformational changes across the proteome, which reveal over 50 'cryptic' pockets that expand targeting options for the design of antivirals. All data and models are freely available online, providing a quantitative structural atlas.

The global emergence of a novel Streptococcus suis clade associated with human infections.

Streptococcus suis, a ubiquitous bacterial colonizer in pigs, has recently extended host range to humans, leading to a global surge of deadly human infections and three large outbreaks since 1998. To better understand the mechanisms for the emergence of cross-species transmission and virulence in human, we have sequenced 366 S. suis human and pig isolates from 2005 to 2016 and performed a large-scale phylogenomic analysis on 1,634 isolates from 14 countries over 36 years. We show the formation of a novel human-associated clade (HAC) diversified from swine S. suis isolates. Phylogeographic analysis identified Europe as the origin of HAC, coinciding with the exportation of European swine breeds between 1960s and 1970s. HAC is composed of three sub-lineages and contains several healthy-pig isolates that display high virulence in experimental infections, suggesting healthy-pig carriers as a potential source for human infection. New HAC-specific genes are identified as promising markers for pathogen detection and surveillance. Our discovery of a human-associated S. suis clade provides insights into the evolution of this emerging human pathogen and extend our understanding of S. suis epidemics worldwide.

Design and synthesis of pyrazolone-based compounds as potent blockers of SARS-CoV-2 viral entry into the host cells.

SARS-CoV-2 are enveloped positive-stranded RNA viruses that replicate in the cytoplasm. It relies on the fusion of their envelope with the host cell membrane to deliver their nucleocapsid into the host cell. The spike glycoprotein (S) mediates virus entry into cells via the human Angiotensin-converting enzyme 2 (hACE2) protein located on many cell types and tissues' outer surface. This study, therefore, aimed to design and synthesize novel pyrazolone-based compounds as potential inhibitors that would interrupt the interaction between the viral spike protein and the host cell receptor to prevent SARS-CoV 2 entrance into the cell. A series of pyrazolone compounds as potential SARS-CoV-2 inhibitors were designed and synthesized. Employing computational techniques, the inhibitory potentials of the designed compounds against both spike protein and hACE2 were evaluated. Results of the binding free energy from the in-silico analysis, showed that three compounds (7i, 7k and 8f) and six compounds (7b, 7h, 7k, 8d, 8g, and 8h) showed higher and better binding high affinity to SARS-CoV-2 Sgp and hACE-2, respectively compared to the standard drugs cefoperazone (CFZ) and MLN-4760. Furthermore, the outcome of the structural analysis of the two proteins upon binding of the inhibitors showed that the two proteins (SARS-CoV-2 Sgp and hACE-2) were stable, and the structural integrity of the proteins was not compromised. This study suggests pyrazolone-based compounds might be potent blockers of the viral entry into the host cells.

A scientometric overview of CORD-19.

As the COVID-19 pandemic unfolds, researchers from all disciplines are coming together and contributing their expertise. CORD-19, a dataset of COVID-19 and coronavirus publications, has been made available alongside calls to help mine the information it contains and to create tools to search it more effectively. We analyse the delineation of the publications included in CORD-19 from a scientometric perspective. Based on a comparison to the Web of Science database, we find that CORD-19 provides an almost complete coverage of research on COVID-19 and coronaviruses. CORD-19 contains not only research that deals directly with COVID-19 and coronaviruses, but also research on viruses in general. Publications from CORD-19 focus mostly on a few well-defined research areas, in particular: coronaviruses (primarily SARS-CoV, MERS-CoV and SARS-CoV-2); public health and viral epidemics; molecular biology of viruses; influenza and other families of viruses; immunology and antivirals; clinical medicine. CORD-19 publications that appeared in 2020, especially editorials and letters, are disproportionately popular on social media. While we fully endorse the CORD-19 initiative, it is important to be aware that CORD-19 extends beyond research on COVID-19 and coronaviruses.