• Rene S Hendriksen, Oksana Lukjancenko, Patrick Munk, Mathis H Hjelmsø, Jennifer R Verani, Eric Ng'eno, Godfrey Bigogo, Samuel Kiplangat, Traoré Oumar, Lasse Bergmark, Timo Röder, John C Neatherlin, Onyango Clayton, Tine Hald, Susanne Karlsmose, Sünje J Pamp, Barry Fields, Joel M Montgomery, and Frank M Aarestrup.
• National Food Institute, WHO Collaborating Center for Antimicrobial Resistance in Foodborne Pathogens and Genomics and European Union Reference Laboratory for Antimicrobial Resistance, Technical University of Denmark, Kgs. Lyngby, Denmark.
• Plos One. 2019 Jan 1; 14 (10): e0222531.

BackgroundWorldwide, the number of emerging and re-emerging infectious diseases is increasing, highlighting the importance of global disease pathogen surveillance. Traditional population-based methods may fail to capture important events, particularly in settings with limited access to health care, such as urban informal settlements. In such environments, a mixture of surface water runoff and human feces containing pathogenic microorganisms could be used as a surveillance surrogate.MethodWe conducted a temporal metagenomic analysis of urban sewage from Kibera, an urban informal settlement in Nairobi, Kenya, to detect and quantify bacterial and associated antimicrobial resistance (AMR) determinants, viral and parasitic pathogens. Data were examined in conjunction with data from ongoing clinical infectious disease surveillance.ResultsA large variation of read abundances related to bacteria, viruses, and parasites of medical importance, as well as bacterial associated antimicrobial resistance genes over time were detected. Significant increased abundances were observed for a number of bacterial pathogens coinciding with higher abundances of AMR genes. Vibrio cholerae as well as rotavirus A, among other virus peaked in several weeks during the study period whereas Cryptosporidium spp. and Giardia spp, varied more over time.ConclusionThe metagenomic surveillance approach for monitoring circulating pathogens in sewage was able to detect putative pathogen and resistance loads in an urban informal settlement. Thus, valuable if generated in real time to serve as a comprehensive infectious disease agent surveillance system with the potential to guide disease prevention and treatment. The approach may lead to a paradigm shift in conducting real-time global genomics-based surveillance in settings with limited access to health care.

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