Center for Viral Systems Biology- Outbreak.info
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 3U19AI135995-09S1
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Key facts
Disease
Disease XStart & end year
20262028Known Financial Commitments (USD)
$406,008Funder
National Institutes of Health (NIH)Principal Investigator
ASSOCIATE PROFESSOR Kristian AndersenResearch Location
United States of AmericaLead Research Institution
SCRIPPS RESEARCH INSTITUTE, THEResearch Priority Alignment
N/A
Research Category
Epidemiological studiesResearch Subcategory
Disease surveillance & mappingSpecial Interest Tags
N/AStudy Type
Non-ClinicalClinical Trial Details
N/ABroad Policy Alignment
PendingAge Group
Not ApplicableVulnerable Population
Not applicableOccupations of Interest
Not applicable
Abstract
Summary Timely detection and interpretation of rapidly evolving pathogens with pandemic potential requires integrated, real-time surveillance frameworks that extend beyond traditional genomic monitoring. We previously developed outbreak.info to track the epidemiology, evolution, and scientific literature of outbreak pathogens, and recent events, including the emergence of highly pathogenic avian influenza A(H5N1) clade 2.3.4.4b in a new mammalian reservoir, underscore the need for more flexible, scalable tools that can assess both viral evolution and functional risk as outbreaks unfold. Here, we propose to continue developing and expanding outbreak.info into a pathogen-agnostic outbreak intelligence framework that supports real-time functional surveillance of emerging and endemic pathogens of high relevance to human health. This framework integrates large-scale genomic data with functional and literature-derived information by ingesting data from open, U.S.-based resources, including NCBI GenBank, the Sequence Read Archive, PubMed, and the NIAID Data Ecosystem. By combining traditional genomic surveillance with in vitro, in silico, and literature-based functional data, outbreak.info will enable the assessment of viral evolution, phenotypic change, and risk across both host-level and population-level contexts, including individual infections and aggregate sources such as wastewater and milk. The proposed framework consists of automated genomic data ingestion and analysis pipelines, tools for genotype-to-phenotype prediction and functional classification, and real-time analyses, visualizations, and reporting delivered through outbreak.info. Together, these components provide a flexible, scalable early warning system designed to support rapid detection and interpretation of emerging viral phenotypes with pandemic potential.