Wastewater-integrated pathogen surveillance dashboards enable real-time, transparent, and interpretable public health risk assessment and dissemination
Nosihle S Msomi, Joshua I. Levy, Nathaniel L. Matteson, Nkosenhle Ndlovu, Phindile Ntuli, Adam Baer, Dylan Pilz, Victor Mabasa, Sipho Gwala, Natasha Singh, Kathleen Subramoney, Emmanuel Phalane, Mokgaetji Macheke, Mantshali Motloung, Thabo Mangena, Lethabo Monametsi, Lebohang Rabotapi, Sibonginkosi Maposa, Amanda Birmingham, Mark Zeller, Smruthi Karthikeyan, Peter De Hoff, Simon R. Harris, Rob Knight, Louise C. Laurent, Kristian G. Andersen, Kerrigan McCarthy, Mukhlid Yousif
Abstract
Timely pathogen surveillance and reporting is essential for effective public health guidance. Web dashboards have become a key tool for communicating public health information to stakeholders, health care workers, and the broader community. Over the SARS-CoV-2 pandemic, wastewater surveillance has increasingly been incorporated into public health workflows for outbreak monitoring and response, enabling community-representative and low-cost monitoring to supplement clinical surveillance. However, the methods used for visualization and dissemination of clinical and wastewater surveillance data differ across programs, and best practices are yet to be defined. In this work, we demonstrate data workflows and dashboards used to perform wastewater-based public health surveillance in tandem with clinical data across local and national scales, leveraging custom-built, reproducible, and open-source software. Using a centralized data aggregation and analysis hub approach, we establish multiple data pipelines for data storage, wrangling, and standardized analyses, and deploy custom-built web dashboards that allow for immediate public release. We find that our approach is effective across scales, computing architectures, and dissemination strategies, and provides an adaptable model to incorporate additional pathogens and epidemiological data.