Q40 - Remotely Controlled Continuous Surveillance of Viral RNAs in Wastewater via LoRa Network

Introduction: : The effective management of infectious diseases depends on accurate monitoring of viral presence within populations. Traditional diagnostic methods, such as testing symptomatic individuals, often miss asymptomatic carriers, limiting public health responses and delaying outbreak containment. Wastewater-based epidemiology (WBE) offers a scalable alternative by analyzing wastewater for viral RNA shed by infected individuals, providing a community-level snapshot of infection trends. WBE has shown strong correlation with clinical testing data and can offer early warnings of surges up to two weeks in advance. However, current WBE workflows remain labor-intensive, relying on manual grab-sample collection, cold-chain transport to prevent RNA degradation, and centralized laboratory analysis using Polymerase Chain Reaction (PCR) or sequencing protocols. These steps introduce logistical bottlenecks that constrain the scalability and timeliness of public health responses.
To address these limitations, we developed an integrated, scalable networked nucleic acid testing (NAT) platform for real-time SARS-CoV-2 RNA surveillance in raw wastewater (Figure 1a). The battery-powered analyzer autonomously performs on-site Reverse Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) assays, wirelessly transmits results via long-range radio (LoRa) to the cloud. Multiple analyzers can be deployed long-term across different locations, enabling spatiotemporal tracking without dependence on manual sample collection or centralized processing. The modular system architecture (Figure 1b) includes end nodes performing RT-LAMP and wireless transmission, gateways for data aggregation, cloud storage, and an interactive dashboard for real-time monitoring and remote system control. This approach significantly enhances the scalability, deployment flexibility, and operational efficiency of WBE, offering a transformative tool for rapid infectious disease surveillance and outbreak mitigation.

Materials and

Methods: : Figure 2a presents an exploded render of the analyzer (168×70×80 mm), designed for autonomous wastewater surveillance with eight parallel NAT chambers. The 3D-printed housing features a hinged lid; the base holds control electronics, while the top integrates the heating block, spectral sensors, and microfluidic cartridge. Figure 2b outlines the electronics and control architecture, including embedded computing, temperature regulation, fluorescence detection, geotagging, wireless communication, and automated sample intake via piezo-pumps (mp6-hyb). Powered by 192 Wh external battery; the analyzer consumes ~5.2 Wh per test and ~16 Wh/day on standby, supporting ~8 days of operation on a single charge. Components were designed in SolidWorks and Eagle CAD, with PCBs fabricated by OSH Park, the housing 3D printed using ABS on a MakerBot MethodX, and the heating block machined by Protolabs.
Figure 2c shows the cartridge, which draws wastewater via piezo-pump suction. The U-shaped channel encounters a semicircular isolation chamber to meter 10 μL into an underlying cylindrical chamber preloaded with RT-LAMP reagents. We previously validated this dispensing mechanism and cartridge design, and the piezo-pump’s performance has also been characterized. Other prior studies have independently demonstrated that SARS-CoV-2 can be reliably detected from 5–10 μL raw wastewater inputs in 25 μL RT-LAMP reactions.
The RT-LAMP mix comprised NEB isothermal buffer (1×), SARS-CoV-2 N-gene primers (IDT), betaine (0.6 M), MgSO₄ (5 mM), SYTO-9 dye (3 µM), dNTPs (1.4 mM), Bst 2.0 DNA polymerase (0.4 U/µL), WarmStart reverse-transcriptase (0.3 U/µL), 10 µL sample, and PCR-grade water to 25 µL total. Reactions ran at ~64 °C.

Results, Conclusions, and Discussions:: To demonstrate system functionality, mock RT-LAMP assays were run with serial dilutions of purified SARS-CoV-2 RNA (10⁴–10 cp/rxn), with amplification curves and time-to-positive values shown in Figures 3a and 3b. An R² of 0.84 was observed, supporting moderate linearity and reliable qualitative detection. Given reported viral loads in wastewater (~10 copies/µL), using 10 µL input per reaction (~100 copies) aligns with real-world testing needs, demonstrating suitability for decentralized wastewater surveillance.
To ensure reliable node-gateway communication, each node transmits two LoRa message types: (1) data messages with 8-channel RFU values and timestamps at 20-second intervals, and (2) meta messages containing GPS location and status. Each message includes a node ID and message type header. A gateway decodes and uploads messages to Google Firestore using the Firebase Admin SDK. The Google Firestore (NoSQL) structure (Figure 3c) includes a parent “Nodes” collection, where each document tracks node status and hosts a sub-collection of real-time experiment data. We achieved >99% packet delivery under simulated message collision conditions (data not shown), confirming robust data transmission and accurate reconstruction of amplification curves. A Node.js + HTML dashboard (hosted at https://aneksh-ionat.web.app/) enables geographic and temporal data visualization. It includes map-based tracking (Figure 3d) with color-coded analyzers showing cumulative and 7-day positivity rates, as well as line plots of daily positivity (Figure 3e). Users can view real-time or historical RFU traces (Figure 3f), trigger new experiments, or receive alerts for cartridge or battery servicing.
In summary, this work demonstrates a fully integrated, proof-of-concept networked NAT system that enables real-time, on-site molecular testing with cloud-based spatiotemporal data aggregation. The system supports decentralized deployment and automated public health surveillance without the need for centralized labs. While validation was performed using mock samples under controlled conditions, future efforts will focus on real-world wastewater testing, integrating viral load pre-concentration for low-copy samples, and improving cartridge usability through redesigns with internally switchable channels. Additional work will also evaluate long-term reagent stability under field conditions. Together, these advancements will help transition the system from prototype to deployable tool for scalable, efficient, and real-time molecular monitoring in public health settings.

Acknowledgements and/or References (Optional):: This work was partially supported by the National Science Foundation (2319913). Any opinions, findings, conclusions, or recommendations expressed in this work are those of the authors and should not be construed to represent any official US Government determination or policy.