A Metagenomic Biosurveillance Network for Emerging Infectious Diseases: A Simulation-Based Model

In this article, we propose a metagenomic next-generation sequencing (mNGS) system for symptomatic clinical respiratory disease samples in Israel to enable detection early enough to contain novel pathogen outbreaks, limit international spread and expedite countermeasure development. We built an open-source, interactive SEIR (susceptible, exposed, infectious, recovered)-based model extending the work of Sharma et al (2023) for 7 representative known respiratory pathogens with pandemic potential, aiming to estimate costs and detection time for the identification of a novel respiratory pathogen in Israel through a network of mNGS monitoring in hospitals. We find that a novel pathogen with SARS-CoV-2-like characteristics could be detected within 68 days (interquartile range [IQR]: 53 to 80) after the first 2 emergency department presentations and 213 (IQR: 94 to 429) total infections across Israel. This surveillance system would cost US$24 million annually over 10 years when implemented in Israel's 6 largest hospitals, covering 37% of the population. Our open-source interactive model allows policymakers and experts to explore different system configurations and their associated tradeoffs between cost, detection speed, and population coverage.