Discovering disease-causing pathogens in resource-scarce Southeast Asia using a global metagenomic pathogen monitoring system

Understanding the regional pathogen landscape and surveillance of emerging pathogens is key to mitigating epidemics. Challenges lie in resource-scarce settings, where outbreaks are likely to emerge, but where laboratory diagnostics and bioinformatics capacity are limited. Using unbiased metagenomic next generation sequencing (mNGS), we identified a variety of vector-borne, zoonotic and emerging pathogens responsible for undifferentiated fevers in a peri-urban population in Cambodia. From March 2019 to October 2020, we enrolled 473 febrile patients aged 6 months to 65 years of age presenting to a large peri-urban hospital in Cambodia. We collected sera and prepared sequencing libraries from extracted pathogen RNA for unbiased metagenomic sequencing and subsequent bioinformatic analysis on the global cloud-based platform, IDseq. We employed multivariate Bayesian models to evaluate specific pathogen risk causing undifferentiated febrile illness. mNGS identified vector-borne pathogens as the largest clinical category with dengue virus (124/489) as the most abundant pathogen. Underappreciated zoonotic pathogens such as Plasmodium knowlesi, leptospirosis, and co-infecting HIV were also detected. Early detection of chikungunya virus presaged a larger national outbreak of more than 6,000 cases. Pathogen-agnostic mNGS investigation of febrile persons in resource-scarce Southeast Asia is feasible and revealing of a diverse pathogen landscape. Coordinated and ongoing unbiased mNGS pathogen surveillance can better identify the breadth of endemic, zoonotic or emerging pathogens and deployment of rapid public health response.