In response to the emergence of SARS-CoV-2 variants of concern, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info, a platform that currently tracks over 40 million combinations of Pango lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials and the general public. We describe the interpretable visualizations available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data and the server infrastructure that enables widespread data dissemination via a high-performance API that can be accessed using an R package. We show how outbreak.info can be used for genomic surveillance and as a hypothesis-generation tool to understand the ongoing pandemic at varying geographic and temporal scales.In December 2019, a series of cases of pneumonia of unknown origin appeared in Wuhan, China and on 7 January 2020, the virus responsible for the diseases was identified as a novel coronavirus, SARS-CoV-2 (ref. 1 ). The first SARS-CoV-2 genome was made publicly available on 10 January 2020 (refs. 2,3 ). Since then, the global scientific community, through an unprecedented effort, has sequenced and shared over 11 million genomes through GISAID (https://gisaid.org/), as of May 2022 (ref. 4 ). To keep track of the evolving genetic diversity of SARS-CoV-2, Rambaut
The emergence of SARS-CoV-2 variants has prompted the need for near real-time genomic surveillance to inform public health interventions. In response to this need, the global scientific community, through unprecedented effort, has sequenced over 7 million genomes as of December 2021. The extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info, a platform that can be used to track over 40 million combinations of PANGO lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials, and the general public. We describe the data pipelines that enable the scalable ingestion and standardization of heterogeneous data on SARS-CoV-2 variants, the server infrastructure that enables the dissemination of the processed data, and the client-side applications that provide intuitive visualizations of the underlying data.
To combat the ongoing COVID-19 pandemic, scientists have been conducting research at breakneck speeds, producing over 52,000 peer reviewed articles within the first 12 months. In contrast, a little over 1,000 peer reviewed articles were published within the first 12 months of the SARS-CoV-1 pandemic starting in 2002. In addition to publications, there has also been an upsurge in clinical trials to develop vaccines and treatments, scientific protocols to study SARS-CoV-2, methodology for epidemiological modeling, and datasets spanning molecular studies to social science research. One of the largest challenges has been keeping track of the vast amounts of newly generated disparate data and research that exist in independent repositories. To address this issue, we developed outbreak.info, which provides a standardized, searchable interface of heterogeneous data resources on COVID-19 and SARS-CoV-2. Unifying metadata from 14 data repositories, we have assembled a collection of over 200,000 publications, clinical trials, datasets, protocols, and other resources as of October 2021. We used a rigorous schema to enforce a consistent format across different data sources and resource types, and linked related resources where possible. This enables users to quickly retrieve information across data repositories, regardless of resource type or repository location. Outbreak.info also combines the combined research library with spatiotemporal genomics data on SARS-CoV-2 variants and epidemiological data on COVID-19 cases and deaths. The web interface provides interactive visualizations and reports to explore the unified data and generate hypotheses. In addition to providing a web interface, we also publish the data we have assembled and standardized in a high performance public API and an R package. Finally, we discuss the challenges inherent in combining metadata from scattered and heterogeneous resources and provide recommendations to streamline this process to aid scientific research.
A simplified model of solar power in the Venus environment is developed, in which the solar intensity, solar spectrum, and temperature as a function of altitude is applied to a model ofphotovoltaic performance, incorporating the temperature and intensity dependence of the open-circuit voltage and the temperature dependence of the bandgap and spectral response of tbe cell. We use this model to estimate the performance of solar cells for both the surface of Venus and for atmospheric probes at altitudes from the surface up to 60 km. The model shows that photovoltaic cells will produce power even at the surface of Venus. Nomenclature CFF GaAs GalnPzSolar cell curve fill factor (dimensionless) the semiconductor gallium arsenide, used for solar cells the ternary semiconductor gallium-indium phosphide, used as the top (wide bandgap) subcell of dualand triple-junction solar cells Ge he lifo I(A.
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