LoCKAmp: lab-on-PCB technology for <3 minute virus genetic detection.

The recent COVID-19 outbreak highlighted the need for lab-on-chip diagnostic technology fit for real-life deployment in the field. Existing bottlenecks in multistep analytical microsystem integration and upscalable, standardized fabrication techniques delayed the large-scale deployment of lab-on-chip solutions during the outbreak, throughout a global diagnostic test shortage. This study presents a technology that has the potential to address these issues by redeploying and repurposing the ubiquitous printed circuit board (PCB) technology and manufacturing infrastructure. We demonstrate the first commercially manufactured, miniaturised lab-on-PCB device for loop-mediated isothermal amplification (LAMP) genetic detection of SARS-CoV-2. The system incorporates a mass-manufactured, continuous-flow PCB chip with ultra-low cost fluorescent detection circuitry, rendering it the only continuous-flow µLAMP platform with off-the-shelf optical detection components. Ultrafast, SARS-CoV-2 RNA amplification in wastewater samples was demonstrated within 2 min analysis, at concentrations as low as 17 gc µL-1. We further demonstrate our device operation by detecting SARS-CoV-2 in 20 human nasopharyngeal swab samples, without the need for any RNA extraction or purification. This renders the presented miniaturised nucleic-acid amplification-based diagnostic test the fastest reported SARS-CoV-2 genetic detection platform, in a practical implementation suitable for deployment in the field. This technology can be readily extended to the detection of alternative pathogens or genetic targets for a very broad range of applications and matrices. LoCKAmp lab-on-PCB chips are currently mass-manufactured in a commercial, ISO-compliant PCB factory, at a small-scale production cost of £2.50 per chip. Thus, with this work, we demonstrate a high technology-readiness-level lab-on-chip-based genetic detection system, successfully benchmarked against standard analytical techniques both for wastewater and nasopharyngeal swab SARS-CoV-2 detection.

Challenges in realising the potential of wastewater-based epidemiology to quantitatively monitor and predict the spread of disease.

Researchers around the world have demonstrated correlations between measurements of SARS-CoV-2 RNA in wastewater (WW) and case rates of COVID-19 derived from direct testing of individuals. This has raised concerns that wastewater-based epidemiology (WBE) methods might be used to quantify the spread of this and other diseases, perhaps faster than direct testing, and with less expense and intrusion. We illustrate, using data from Scotland and the USA, the issues regarding the construction of effective predictive models for disease case rates. We discuss the effects of variation in, and the problem of aligning, public health (PH) reporting and WW measurements. We investigate time-varying effects in PH-reported case rates and their relationship to WW measurements. We show the lack of proportionality of WW measurements to case rates with associated spatial heterogeneity. We illustrate how the precision of predictions is affected by the level of aggregation chosen. We determine whether PH or WW measurements are the leading indicators of disease and how they may be used in conjunction to produce predictive models. The prospects of using WW-based predictive models with or without ongoing PH data are discussed.