Shuttleworth, Joe

Joe is a Civil Engineer with a background in numerical modelling of water systems with Arup in London, UK. He was trained at the Universities of Cardiff, Exeter and California and worked for a time in academia researching large scale flood dynamics. Recently his work has focussed on environmental monitoring of water systems for public health and he leads Arup's work the the UK government into Wastewater Based Epidemiology partnering with government agency, private indusrty and leading UK based academics.

Titles from this speaker

Description: The role of hydraulic models in Wastewater Based Epidemiology: Opportunities and...

The role of hydraulic models in Wastewater Based Epidemiology: Opportunities and Limitations

Abstract

Wastewater analysis for SARS-CoV-2 RNA has been underway in various locations across the world since early 2020 and is a rapidly expanding area of research. There is a limited understanding of the behaviour of viruses within the sewer network. However, it is likely that the virus is subject to a range of biotic and abiotic factors which may influence its persistence and transit time within the network . Understanding this behaviour is key in developing sampling strategies which underpin an effective Wastewater Based Epidemiology (WBE) health surveillance system. Developing this understanding requires answers to a number of core questions, namely:

•Does the virus follow conservative flow regimes?
•Does the virus degrade in the sewer environment?
• How long does the virus persist in the network?
•What are the impacts of re-entrainment after weather events?

A better knowledge of these factors would allow better interpretation sample results in the context of the environmental conditions, which will also create the foundation for being able to triangulate and track the sources of viral outbreaks.

In the UK over 90% of the water and wastewater networks are representing in hydraulic models. These models have been built over the past 10 – 15 years and have been subject to millions of pounds of investment to ensure they are fit for purpose and accurate. These models have the potential to be a key tool in an effective WBE program if used in the right way. To date, development has primarily been focused on flooding, which is the core driver in the UK, and less so on the representation of water quality parameters.

Method

Through this study we worked to assess how well these models could be used to represented viral transport in sewer network, as well as identify any potential limitations.

To do this we worked in two catchments, each with different properties to deploy an enveloped viral marker at known places into the sewer network and then tracking its appearance at various locations. This work was complemented with the conservative flow fluorescent dye tracer, rhodamine-WT. We followed these tracers through the use of an autosamplers in the network over 17 days. Using these results, we then calibrated a hydraulic model (with contaminant transport processes) to understand the key parameters which influence transport (degradation rate, flow rate, rainfall, pipe material and roughness).

The models use the Innovyze Infoworks ICM modelling platform. In all cities the models were 'cut down' to represent only the major network with inflow files at junctions, as in Figure 1. This was done to increase the speed of the models.

In order to ensure accuracy these cut down models are checked against the full model to make sure there are no differences. The conditions on the sampling days were then re-created by adding any rainfall and inputting the markers at the upstream manhole, representing it as coliform.

Results

The different catchments each highlighted different challenges and opportunities. In the first there was a pumping station in between the input location and the sampling point. This meant that initially the model under predicted the travel time by over 4 hours. To counter this the impact of the pump was derived by including its operational controls. After this was done the time of travel matched that of the experiments closely, as seen in Figure 2. In our simulations we ran a number of scenarios with different T90 decay times. In Figure 2 it can be seen that a T90 of 10 – 12 hours most accurately matches the experiments. This influences the design of a sampling strategy or interpretation of the result to incorporate this decay of the virus.

In the second catchment there was a single straight run of pipe, with no significant hydraulic structures. However, we were unable to recreate the travel time accurately, as shown in Figure 3.

The models use a standard Dry Weather Flow day based upon when they were originally verified. We compared velocity measurements taken on the day of the experiments to the validation day and there was a large differential. This may be explained by changing water usage during Covid altering the flow patterns in the sewer, as was suggested by the flow monitor at the outlet point, as shown in Figure 4.

Conclusion

The key conclusion from the work is that it is possible to represent an enveloped virus in the sewer network through the use of hydraulic models. Both in terms of travel time and decay rate. However, using the models 'off the shelf' can lead to large inaccuracies as the models may not be validated/ developed with the intention for use in water quality modelling or water usage has changed during Covid with home working to the point at which the models are no longer representative. In these conditions having flow measurements recorded at the same time as sample extraction can lead to more certainty around the outputs/ results and allow for the models to be adapted to match reality.

If the models are fully validated it is possible to use the water quality modules to represent the virus transport with a T90 decay rate of 10-14 hours. This means that sampler coverage needs to ensure that areas outside of this distance from a sampler need to be covered by additional in-network samplers to represent SARS-CoV-2 prevalence. Or include scaling factors to incorporate the likely decay of the virus.
The transport of the virus is conservative (via advection), as a result if the key parameter of interest is travel time this can be calculated based on only knowledge of the network configuration and the flow rates. However, the models are still required to explore the relationship with decay rates.

Future work

The opportunity to represent other health markers and chemicals is being explored as well as whether these models can be run in real time and integrate real time sample data to track the sources of infection in communities.

The following conference paper was presented at the Public Health and Water Conference & Wastewater Disease Surveillance Summit in Cincinnati, OH, March 21-24, 2022.

SpeakerShuttleworth, Joe

Presentation time

13:30:00

13:45:00

Session time

13:30:00

15:00:00

SessionExploring the Role of Various Models in Wastewater-Based Surveillance to Evaluate Epidemiological Control Strategies

Session number4

Session locationDuke Energy Convention Center, Cincinnati, Ohio

TopicModeling, Pathogens, Risk Management

Author(s)

Shuttleworth, Joe

Author(s)J. Shuttleworth1; V. Williams2; O. Bailey3

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Mar 2022

DOI10.2175/193864718825158300

Volume / Issue

Content sourcePublic Health and Water Conference

Word count13

Wastewater-based Epidemiology in Wales: From COVID-19 to One Health Monitoring

Abstract

Background Wastewater-based epidemiology (WBE) offers real-time public health insights by detecting pathogens, chemicals, and pharmaceuticals in communities. The 'One Health' principle acknowledges that human, animal, and environmental health are interconnected. WBE plays a crucial role in One Health by monitoring contaminants from all these sources. For infectious diseases, WBE can signal outbreaks before clinical symptoms arise, enabling swift action that benefits both humans and animals. It also tracks antimicrobial resistance genes, informing policy makers, veterinarians and medical professionals about resistance spread. By identifying environmental pollutants, WBE aids in environmental health oversight, identifying issues affecting both wildlife and humans. During the COVID-19 pandemic, the Welsh National Wastewater Monitoring Program was launched to trace disease spread. It offered an early warning system, detecting outbreaks before clinical signs appeared. Post-pandemic, its scope widened to cover markers of One Health, aiming to monitor other diseases, antimicrobial resistance, and other contaminants. The program, a collaborative effort involving Bangor and Cardiff Universities, Welsh water companies, Public Health Wales, The London Data Company & Arup, aimed to inform Welsh policy and benefit its citizens. Methods The Welsh National Wastewater Monitoring program sampled 47 wastewater-treatment works (WWtW) across the country, capturing approximately 75-80% of the national population (Figure 1). Sites were chosen based on their geographical coverage and population density, enabling a coherent and systematic approach to decision making at a local and national level. Sampling was facilitated through access and arrangements with the local water utilities, Welsh Water and Hafren Dyfrdwy. The sites were sampled 5 days per week over two years, since March 2020, with 24-hour composite samples collected and transported under refrigeration to the North Wales central processing laboratory, where they were evaluated. The wastewater samples were and processed, with the liquid fraction taken and assessed for the presence of SARS-CoV-2, Human Norovirus, Human Respiratory Syncytial Virus (RSV) and Polio. The solid fraction of the sample was then tested for the presence of antimicrobial resistance genes which were analysed by partners at Cardiff University. Results & Discussion This study over two years provided both operational guidance to the Welsh Government In real-time, the program advanced WBE research for One Health applications by analyzing wastewater for infectious diseases and AMR. This validated data reliability by correlating with sources like the UK's ONS COVID-19 Infection Survey (CIS). Fluctuations in COVID-19 were linked to lockdowns, national events, and holidays. COVID-19 data collected using WBE as validated against the CIS. This was widely considered a highly reliable source of COVID-19 infection prevalence data, individually sampling approximately 1% of the population for each data point. The wastewater data was observed to follow a similar correlative pattern to the CIS and was continued beyond the survey. This was the longest reported study used to detect COVID-19 variants using metagenomics from wastewater samples at a population level. It highlighted the prevalence of different strains and the rise of the Omicron variant BA.21 (Figure 3). It further identified the variability in variant detection with time and demonstrated how multiple variants were always circulating in the population. As the wastewater sequencing reported a week ahead of clinical sequenced cases, policymakers were provided an early indication of potential variants of concern (VOCs). Gaps in the data were generally associated with reduced reliability of the data due to insufficient viral detection in the samples, these were often attributed to periods with low viral circulation within the community such as the summer period. Beyond COVID-19 the potential for WBE extends to monitoring for other infectious diseases, both of humans and animals. Furthermore, with the infrastructure provided by the labs, sampling different sites by environmental monitoring provides the opportunity for a holistic approach to health. This was demonstrated in Wales, by monitoring different infectious diseases in the population in addition to AMR, which was a challenge faced by both human and animal populations in the country. Studying the prevalence of other infectious diseases in wastewater confirms this approach could be expanded to measure other health threats. The program studied the prevalence of NoVGI, NoVGII as human noroviruses, enterovirus-1 as a marker for Polio, influenza-A as a marker for the common flu and RSV prevalence in the population (Figure 4). Conclusions The water industry as strategic leaders on this idea can enable and support the data driven approach of harnessing WBE as a proactive means to monitor, predict, and respond to heath threats in our interconnected world. Applying the lessons learned in Wales, enables global monitoring of multiple One Health markers. This data supports the notion that WBE turns sewage into solutions, enabling us to harnessing wastewater as a valuable stream of data can help improve the health of livestock, communities, and ecosystems. When scaled across different catchments, countries and communities.

Wastewater-Based Epidemiology (WBE) is pivotal for public health, offering insights into pathogens, chemicals, and pharmaceuticals. By monitoring human, animal, and environmental sources, WBE supports a 'One Health' approach. During COVID-19, the Welsh National Wastewater Monitoring Program used WBE for early virus detection. Supported by universities and government, it now monitors One Health markers, infectious diseases, and antimicrobial resistance.

SpeakerBarochia, Bhavik

Presentation time

13:30:00

13:45:00

Session time

13:30:00

15:00:00

SessionInternational Experience: Safeguarding Our Shared Water Resources

Session number415

Session locationRoom 346

TopicAdvanced Level, Disinfection and Public Health, Microconstituents and Contaminants of Emerging Concern (Non-PFAS), Municipal Wastewater Treatment Design, Water Reuse and Reclamation

Author(s)

Barochia, Bhavik, Doyle, Tom, Shuttleworth, Joe, Perry, William, Durance, Isabel, Farkas, Kata, Cross, Gareth, Grimsley, Jasmine, Weightman, Andrew, Williams, Vikki, Jones, Davey

Author(s)B.D. Barochia1, T. Doyle2, J. Shuttleworth3, W.B. Perry4, I. Durance4, K. Farkas5, G. Cross6, J. Grimsley7, A.J. Weightman8, V. Williams2, D. Jones5

Author affiliation(s)1Arup, England, 2Arup, 3arup, NY, 4Cardiff University, 5Bangor University, Wales, 6Welsh Government, 7The London Data Company, England, 8Cardiff University, Wales

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2024

DOI10.2175/193864718825159629

Volume / Issue

Content sourceWEFTEC

Word count11