PIPP Phase I: Advancing Environmental Surveillance for Pandemic Prediction in Remote and Resource Poor Settings

Grand Challenge: Leveraging Environmental Surveillance to Predict Emerging Diseases in Low Resource Settings Pathogens with pandemic potential, like Ebola, HIV, and avian influenza, frequently emerge in impoverished or remote settings with limited healthcare infrastructure. While environmental surveillance is an appealing and potentially cost-effective means of identifying pathogens, the implementation of surveillance strategies in “hotspot” settings is suboptimal at best and often completely unfeasible. Thus, the grand challenge of this PIPP project is to overcome the obstacles preventing efficient environmental surveillance through innovative, multidisciplinary solutions. We frame our investigation into the following three Provocative Questions: Provocative Question 1: How can we efficiently identify disease clusters concerning for emerging pathogens, particularly in communities with limited healthcare infrastructure? (Lead: Keck) Identification of disease clusters is challenged by healthcare access, limited diagnostic capacity of the healthcare system, and weak public health surveillance and health informatics systems. Disease clusters are recognized late or not at all increasing the potential for epidemic and pandemic spread. Opportunities to overcome these existing barriers and improve the timely identification of disease clusters include: 1) engaging community health workers and their frontline hyperlocal knowledge; 2) training of clinicians and public health teams; and 3) provision of context appropriate reporting mechanisms. Digital epidemiology, including data from healthcare information technology, mobile health apps, social media, and wearables is making slow inroads into impoverished settings and offers rich data for disease cluster detection. Prompt recognition of disease clusters would support targeted environmental surveillance to determine disease etiology and spread. Provocative Question 2: How can we perform verifiable measurements on difficult samples in minimal-resource environments? (Lead: Berry) Once a sampling location is identified, samples must be collected, preserved, and analyzed in an efficient manner to ensure the fidelity of the data. Environmental samples are particularly difficult to process because: 1) Pathogen biomarkers are diluted by the sample matrix and therefore exist at very low concentrations; 2) Many key biomarkers are extremely labile (e.g., viral RNA); 3) The sample matrix is often non- homogenous and may vary with time. Thus, there is an unmet need for technologies that can collect, concentrate, stabilize, and preserve analytes. These technologies may or may not be directly integrated with downstream analysis processes (e.g., PCR, ELISA, NGS). Provocative Question 3: How can we translate raw data into actionable public health guidance? (Lead: Scotch) Public health action must be informed by timely and accurate results and information. There are tremendous challenges in properly sequencing, integrating, and analyzing viral genetic data for describing and quantifying pathogens in a population. This entails development of metagenomic pipelines for assembly and analysis of high-throughput sequencing (HTS) data to identify single nucleotide variants (SNVs) that might represent specific variants, subtypes, or strains of pathogenic viruses. Despite the complexity of such a bioinformatics pipeline, it must include a visualization or graphical user interface component that accurately and clearly presents the results to stakeholders outside of the domain. Data visualization and graphical user interfaces must be developed with contextual design and behavioral science principles that include end-user feedback to optimize data usefulness and avoid misinterpretations that could lead to inappropriate and ill-advised interventions. SARS-CoV-2 Wastewater Surveillance as a Model System: All three PIs have experience building and optimizing environmental surveillance pipelines, as a part of the global effort to combat SARS-CoV-2. As a part of an NIH- funded RADx-rad grant, Drs. Keck and Berry have developed a network of key stakeholders (engineers, clinicians, environmental scientists, local health departments, educators, wastewater treatment plant operators, etc.) focused on the identification of COVID-19 outbreaks in Appalachian Kentucky via wastewater and environmental surveillance. Additionally, they have developed custom protocols to concentrate and preserve viral RNA in a small van-based lab. Dr. Scotch is a principal investigator on a separate RADx-rad SARS-CoV-2 wastewater project focused on the development of a bioinformatics pipeline for wastewater genomics using samples from across the United States. Partnership Building in PIPP Phase 1: While we have taken initial steps towards addressing some of the challenges raised by our Provocative Questions, we acknowledge the need for a diverse multi-institution, multi- national partnership of researchers and other stakeholders to innovate and create new and improved environmental surveillance strategies for pandemic prediction. Therefore, in addition to continuing the evolution of our own efforts beyond SARS-CoV-2, we propose the formation of a Pandemic Environmental Surveillance Alliance. The Alliance has the goals of 1) multidisciplinary team building; 2) generating novel pilot research projects and preliminary data through pilot project grants; and 3) disseminating knowledge and training through seminars and workshops.