A Ugandan child with an unexplained encephalitis was investigated using viral metagenomics. Several sequences from all segments of a novel orthobunyavirus were found. The S-segment, used for typing, showed 41% amino acid diversity to its closest relative. The virus was named Ntwetwe virus, after the hometown of the patient.

Human parechoviruses (HPeVs), a poorly studied genus within the Picornaviridae family, are classified into 19 genotypes of which HPeV1 and HPeV3 are the most often detected. HPeV1 VP1 C terminus contains an arginine-glycine-aspartic acid (RGD) motif and has been shown to depend on the host cell surface αV integrins (αV ITGs) and heparan sulfate (HS) for entry. HPeV3 lacks this motif and the receptors remain unknown. HPeVs can be detected in patient nasopharyngeal and stool samples, and infection is presumed to occur after respiratory or gastro-intestinal transmission. HPeV pathogenesis is poorly understood as there are no animal models and previous studies have been conducted in immortalized monolayer cell cultures which do not adequately represent the characteristics of human tissues. To bridge this gap, we determined the polarity of infection, replication kinetics, and cell tropism of HPeV1 and HPeV3 in the well-differentiated human airway epithelial (HAE) model. We found the HAE cultures to be permissive for HPeVs. Both HPeV genotypes infected the HAE preferentially from the basolateral surface while the progeny virus was shed toward the apical side. Confocal microscopy revealed the target cell type to be the p63+ basal cells for both viruses, αV ITG and HS blocking had no effect on the replication of either virus, and transcriptional profiling suggested that HPeV3 infection induced stronger immune activation than HPeV1. Genotype-specific host responses may contribute to the differences in pathogenesis and clinical outcomes associated with HPeV1 and HPeV3.

Background We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death.

25The response of pathophysiological research to emerging epidemics often occurs 26 after the epidemic and, as a consequence, has little to no impact on improving 27 patient outcomes or on developing high-quality evidence to inform clinical 28 management strategies during the epidemic. Rapid and informed guidance of 29 epidemic (research) responses to severe infectious disease outbreaks requires quick 30 compilation and integration of existing pathophysiological knowledge. As a case 31 study we chose the Zika virus (ZIKV) outbreak that started in 2015 to develop a 32 proof-of-concept knowledge repository. To extract data from available sources and 33 build a computationally tractable and comprehensive molecular interaction map we 34 applied generic knowledge management software for literature mining, expert 35 knowledge curation, data integration, reporting and visualisation. A multi-disciplinary 36 team of experts, including clinicians, virologists, bioinformaticians and knowledge 37 management specialists, followed a pre-defined workflow for rapid integration and 38 evaluation of available evidence. While conventional approaches usually require 39 months to comb through the existing literature, the initial ZIKV KnowledgeBase 40 (ZIKA KB) was completed within a few weeks. Recently we updated the ZIKA KB 41 with additional curated data from the large amount of literature published since 2016 42 and made it publicly available through a web interface together with a step-by-step 43 guide to ensure reproducibility of the described use case (S4). In addition, a detailed 44 online user manual is provided to enable the ZIKV research community to generate 45 hypotheses, share knowledge, identify knowledge gaps, and interactively explore 46 and interpret data (S5). A workflow for rapid response during outbreaks was 47 threats. The resulting structured biological knowledge is a helpful tool for 50 computational data analysis and generation of predictive models and opens new 51 avenues for infectious disease research. 52 53 Availability: www.zikaknowledgebase.eu 54 55 Funding 56 European Commission's Seventh Framework Research Programme project 57 PREPARE (FP7-Health n°602525) and ZIKALLIANCE (MK, H2020; No 734548). 58 59 Author summary 60 During the recent ZIKV outbreak there was little information about the interactions 61 between Zika virus and the host, however, the massive research response lead to a 62 steep increase in the number of relevant publications within a very short period of 63 time. At the time, there was no structured and comprehensive database available for 64 integrated molecular and physiological data and knowledge about ZIKV infection. 65through the massive amount of existing literature. In addition to providing 74 background information for research, scientific publications can be processed to 75 transform textual information into complex networks, which can be integrated with 76 existing knowledge resources to suggest novel hypotheses that potentially contribute 77 to innovative infectious disease r...