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Article

Preparing for COVID-2x: Urban Planning Needs to Regard Urological Wastewater as an Invaluable Communal Public Health Asset and Not as a Burden

Institute for Land, Water and Society, Charles Sturt University, Albury, NSW 2640, Australia
Submission received: 27 July 2021 / Revised: 14 September 2021 / Accepted: 26 September 2021 / Published: 1 October 2021
(This article belongs to the Special Issue The Post-COVID Urbanism)

Abstract

:
Prior to the COVID-19 pandemic, the analysis of urological wastewater had been a matter of academic curiosity and community-wide big-picture studies looking at drug use or the presence of select viruses such as Hepatitis. The COVID-19 pandemic saw systematic testing of urological wastewater emerge as a significant early detection tool for the presence of SARS-CoV-2 in a community. Even though the pandemic still rages in all continents, it is time to consider the post-pandemic world. This paper posits that urban planners should treat urological wastewater as a communal public health asset and that future sewer design should allow for stratified multi-order sampling.

1. Introduction

Soon after its existence became public in late January 2020, COVID-19, the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [1], rapidly developed into a global pandemic, affecting every continent. As the year 2020 merged into 2021, several countries have experienced a second and even a third wave of infections [2]. At each national level, and even at the sub-national level, governments engaged in measures to curb or at least slow the progress of COVID-19 and to ensure that the public health system was not overwhelmed by cases requiring hospitalization. With its rapid spread and cross-sectorial impact, the COVID-19 pandemic has proven to be a social and economic disruptor on a global scale not seen since the ‘Spanish flu’ pandemic of 1918–19 that took between 17.4 and 50 million lives [3]. At the time of proofing (on 29 September 2021), 232.3 million people had been infected on all continents in all but seven countries, with a global death toll of 4.76 million [4].
COVID-19 is not a ‘Black Swan’ event, as the emergence of a coronavirus was predicted by public health professionals [5], following the outbreaks of SARS in 2004 [6] and MERS in 2012 [7]. Moreover, it is unlikely to be the last as other zoonotic coronaviruses related to SARS-CoV-2 are currently in existence in various host species [8] and some of these coronaviruses are almost certain to emerge as yet another major threat to humans [9]. It is predictable from an epidemiological point of view that another zoonotic coronavirus will manifest itself in the foreseeable future as an epidemic or even pandemic [10].
As the vaccines are being administered to reduce the severity of infection by SARS-CoV-2 and the spread of the COVID-19 pandemic, attention is moving to consider the future make-up of studying [11], working [12], and leisure [13,14]. In the planning sphere, attention has focused on the future of commuting [15], urban design [16], and public spaces [17], as well as the design of residential architecture [18].
Likewise, urban design and planning needs to focus on what lessons the COVID-19 pandemic provides the post-pandemic world. Given that other zoonotic coronaviruses are effectively ‘waiting in the wings,’ the profession cannot afford to continue to carry out business as usual. This paper will review the literature on sewerage testing for the successful detection of SARS-CoV-2 fragments and will advance some suggestions for future urban planning and design.

2. Sewage Testing as a Diagnostic Tool for Public Health

Humans excrete traces a wide range of chemical substances that the person has ingested, inhaled or injected, including medication and legal and illicit drugs. On an individual level, this has been used to detect doping in elite sports [19], and drug use in the workplace [20]. On a community level, sewage epidemiology utilizes the concentration of target drugs and/or their metabolites in urological wastewater, either at select points of the sewer system, or as influent at centralized wastewater treatment plants, and extrapolates the concentration of these in the wastewater in relation to the population size served by sewer system/treatment plants to calculate the per-capita rate of drug use or medication uptake.

2.1. Testing Sewage for the Detection of Drugs and Pathogens

The testing of sewage effluent has become a major instrument in the toolkit of public health professionals. It has been widely used as a means of detecting the use of illicit drugs in a population per se [21,22,23,24,25,26,27], to assess changes in drug usage over time [28], and to provide evidence of drug use at select facilities [29] or events [30,31,32]. In addition, sewage testing allows us to estimate uses of other detectable substances/their metabolites for general public health assessments. Urological waste water testing has been used to assess the use of depressants as well as antidepressants [33], nicotine (as a proxy for smoking) [34,35], alcohol [35], and select diseases such as gout [36]. It has been used to determine the usage of a range of medication [37], such as antibiotics [38], and decongestants [38], as well medication for other disorders such as ADHD (e.g., Ritalin) [39], Urological waste water testing allowed health authorities to assess the uptake of antiviral treatments (e.g., Tamilflu) during H1N1 influenza pandemics [38,40].
Importantly, it has also been used as a means of early detection of the presence and prevalence of pathogens, such as typhoid [41], salmonella [42], tuberculosis [43], antibiotics-resistant bacteria [44]. Urological waste water testing has been successfully utilised to detect not only the presence and prevalence of specific viruses such as poliomyelitis [45] hepatitis-A [46,47] and influenza A (H1N1) [48], but more specifically of a wide range of virus types, such as adenovirus [47,49], Coxsackievirus [47,50,51], echovirus [47,50,51], herpesvirus [52], norovirus [53] and rotavirus [53].
Epidemiological studies have noted the utility of urological waste water testing to detect the presence of viruses causing Zika [54,55,56], West Nile fever [57], dengue fever [56,58,59] and yellow fever [56].
The quality of the resultant data is both subject to methodological considerations such as sampling locations [60], as well as bio-decay and degradation in the sewer system [35,60,61]. Common to these studies was, for the most part, a community-wide focus.

2.2. Sewage Testing as a Diagnostic Tool for the Presence of SARS-CoV-2

The ability to determine the presence of coronavirus (fragments) is urological wast water had been demonstrated for a considerable time [62], including SARS [63]. While sewage testing was a diagnostic quantitative tool for public health professionals, it was largely relegated to academic curiosity and big-picture studies. This changed dramatically in February 2020 when COVID-19 had been declared a pandemic. Since then, the sewage testing for fragments of the SARS-CoV-2 has been successfully deployed and proven in value as an early detection tool and employed by public health authorities throughout Europe including Belgium [64], England [65], France [66], Germany [67], Hungary [68], Italy [69], the Netherlands [70], Russia [71], Spain [72,73], Switzerland [74], and Turkey [75,76], The same technique was also employed in other parts of the globe such as Hong Kong [77], Israel [78,79], India [80], Pakistan [81], Saudi Arabia [82], Brazil [83,84], Chile [85], Mexico [86], the USA [87,88] and Australia [89,90].
A critical public health benefit derived from this approach is that sewage testing also provided the ability to identify the presence of SARS-CoV-2 before it presented in a clinical setting [72], and that it further allows to identify socially stratified trends in infection that otherwise would have gone undetected due to differential attendance at individual swab testing due to (communal or personal) socio-economic reasons or geographic realities (e.g., dispersed settlement) [83,91,92,93]. A further critical public health benefit of continued, longitudinal testing regimes is that it allows public health officials to track the emergence and geographical spread of new virus strains [65].
While a range of sampling and processing protocols has been developed and described in the literature [79,81,86,88,94,95], there is little critical literature on appropriate sampling strategies. Numerous studies comment on their sampling locations, but do not discuss the underlying rationale for the sampling strategy [79,81,83]. It has been argued, however, that all sampling strategies must be based on and adjusted to local realities rather than being generic or off the shelf [92].

3. Contemporary Sewage and Wastewater Management

The majority of sewage systems in towns and communities are a historic legacy of the nineteenth and early twentieth century [96]. The main sewers in London, for example, date to the Victorian era [97,98], as do the sewers of New York [99]. The sewer systems were originally designed for smaller communities, each with their own treatment plant. As the communities expanded and merged, so grew the complexity of sewage management with the development of centralized sewage treatment plants and an associated demand for sewage pumping stations.
The contemporary sewage and wastewater management encompasses a mixture of legacy sewer networks, network upgrades carried out in the latter part of the twentieth century, and newly developed networks or network extensions in newly developed suburbs on the urban fringe. At an individual level, terrain complexity and in particular settlement dispersion affect the optimization of wastewater infrastructures as gravity driven sewers are cheaper and thus the preferred option [100]. When deciding on the extension of existing sewer networks or the creation of new treatment plants, best practice approaches tend to balance the benefits of the shortest path against the economic return of maintaining centralization [100].
Until the outbreak of COVID-19, little consideration was given to a systematic, large-scale and continuous sewage sampling.

4. Planning

Numerous governments are concerned with the impact of the repeated lockdowns and extended restrictions in movements and sizes of public gatherings on their national economy [101,102].To prop up the construction sector, some countries have embarked on economic stimulus packages that encompass wage subsidies and spending on public infrastructure development and upgrades [103,104,105], as well as subsidization of the building of private homes, the bulk of which will be built in new housing estates. A significant variable to be considered here is that even though economic depreciation is commonly set at 30 years [106], sewer networks have a relatively high average life-span of about 80 years [100] compared to domestic new builds (25–50 years) [107,108] or water treatment plants (25 years) [100]. Consequently, unless lessons from the COVID-19 pandemic are embedded into the design of these new builds, such as private dwellings [18], this spate of new builds will create an encumbering legacy, rather than a future-focused investment.

4.1. Concepts

Conceptually, most communities cognitively still consider sewage as waste and thus a burden that needs to be speedily removed [109]. Yet, as the preceding discussion (Section 2.2) has shown, sewage is a public health asset. Source separation in sewage systems, i.e., separating domestic greywater (derived from shower and laundry) from domestic blackwater (derived from toilet wastewater) has been advocated in some countries [110]. Not only do the injected volumes (and thus the resulting treatment costs) differ between grey- and blackwater, but, source separation also allows for increased water re-use and recovery of energy and nutrients from wastewater [111,112,113]. In a pandemic situation, the dilution of blackwater effluent will be less in source separated systems, thus increasing the detectability of low virus loads.
In Australia, for example, housing developments and housing subdivisions are connected to existing sewers subject to the stipulations of the Sewerage Code of Australia [114,115,116]. Of these, only the Pressure Sewerage Code makes any reference to sampling points, but does not specify their patterning or their design.
Conceptually, blackwater sampling points should be structured hierarchically to allow for flexible responses with increasing granularity of results (Figure 1). The first order sampling at the inflow to the sewage treatment/wastewater management plant allows for community level testing. Second order sampling would occur at sewage nodes at the confluence of a suburb cluster. Third order sampling then increases granularity to the level of suburbs, while fourth order sampling can bring the granularity to the level groups of streets. Where required, a fifth order sampling can occur at small complexes such as retirement homes, apartment blocks and high rises (Figure 1). In smaller communities, second order sampling would be omitted, and sampling would occur at the inflow to the sewage treatment/wastewater management plant (first order) and then at sewage nodes delineating individual suburbs (third order).
In the current scenario of COVID-19, testing occurs at the inflow to sewerage works and, if virus fragments are detected, additional sampling and testing occurs upstream to identify the presence of SARS-CoV-2 at the suburb level. The current sampling regimes usually do not allow for retrospective testing, yet this is a valuable tool to understand how long a pathogen has been circulating in the community.

4.2. Sampling Framework

In a practical sense, first order sampling and testing should occur on a regular basis, as soon as diagnostic kits are available. Upstream sampling would commence once a disease has manifested itself on a wider scale at a location within the country or state (but not necessarily yet at the community, or an epidemic has been identified in the country or other countries where there is potential that might seed in the country in question and then spread through communities. The sampling regime, including frequency, will need to be defined by epidemiologists and will vary from disease to disease. Critical here is that physical infrastructure has been put in place to facilitate such sampling and that sewerage management authorities embrace the necessity of sampling.
Ideally, if so determined by epidemiologists, sampling could occur daily at all sampling points, regardless of order, but at least at third order level, with samples stored on site (see below). Depending on staffing and funding levels, fifth order sampling can be omitted at the expense of granularity or can be carried out at longer intervals at the expense of immediacy. Figure 2 exemplifies a third order (star) and fourth order (dots) sewer network.
Such multi-order sampling will inevitably result in a considerable volume of samples that will need to be collected, transported to a sample archive, and stored there for potential analysis. Such centralized processes can pose a considerable strain on the system, especially in larger communities. More apposite would be a decentralized design where samples are stored, under correctly refrigerated conditions, at the sampling location itself and are only moved to the analytical laboratory if and when required.
Any sample collection and retention pattern is governed by the incubation period of coronaviruses causing respiratory infections or other pathogens (as required). At the present pandemic, with the current strains of SARS-CoV-2, these range, depending on the strain, from as low as two to about fourteen days. It is desirable to implement a collections regime that allows for retrospective analysis. Thus it may be desirable that daily sample collection and retention occurs on a rolling 21-day pattern, with retention of a weekly sample for an additional three weeks. Combined, this would extend the window of a retrospective analysis to six weeks. Any given sampling location, therefore, will only need to allow for cold storage of 24 samples.
To increase temporal granularity, a storage capacity of 31 samples would allow for twice-daily collection for one week, the retention of daily samples for the two weeks before that and weekly retention for the three weeks prior. From an epidemiological perspective, it is important to be able to reconstruct how long a virus has been circulating undetected in a given community. Such sample retention regimes allow for focused retrospective assessment once virus fragments have been detected at first order level. The sampling regimes will be determined by the epidemiological community and will, inevitably vary depending on the pathogen.

4.3. Ensuring Future Testing Capacity

There are three components to ensure future testing capacity: (i) the design of sewer networks in new housing estates; (ii) ensuring ready access to the sewer lines for manual or automated sampling and finally (iii) retrofitting of existing sewer networks.

4.3.1. Design of Sewer Networks in New Housing Estates

First and foremost, in order to future proof post-pandemic communities, government authorities need to become proactive and embrace urological wastewater as an invaluable communal public health asset. This has two consequences, longer-term strategic planning and the passing of legislation at the state level and regulations at the local government level. At present, at least in the Australian situation, too much of the thinking of urban expansion revolves on short-term, piecemeal opening up of housing estates rather than development trajectories that allow for the conceptualizing of larger, hierarchical networks. Once individual housing estates are being proposed, all new housing estate developments should be required to design and build hierarchically based, uniquely branched sewer networks that allow for well circumscribed fourth and fifth order sampling. As land developers tend to prioritise company profits over community welfare, there is a need to develop legislation and executing regulations that compel developers to include such sampling chambers in their subdivision designs. As the costs will, inevitably, be passed onto the purchasers of building allotments, any such legislative change needs to be accompanied by public awareness campaigns.

4.3.2. Ensuring Ready Access to the Sewer Lines

At present, sampling is possible by accessing laterals, utility holes (‘manholes’), sewerage pump stations, and of course at the inflow at the treatment plants. While these, theoretically, provide access, this is cumbersome since the majority of access points, such as utility holes and inspection holes as laterals are designed for occasional maintenance access than daily sampling. The installation or retrofitting of automated sampling is possible but difficult for channel systems.
To facilitate ready and, when required, continual sampling, new developments which require the establishment of sewerage networks should include a sampling chamber at each second, third and fourth order node, as well as at selected fifth order nodes, such as retirement villages, high-rise developments or apartment blocks. Such sampling chambers should allow for easy keyed access to an underground space that provides access to the sewer line for effortless automated or manual in-line sampling and be large enough to provide storage space for sample collection including cold storage for 50 samples in a small refrigerator.

4.3.3. Retrofitting of Existing Sewer Networks

Without doubt, this will be the most difficult component of future proofing post-pandemic communities. Here, we need to distinguish between old, historic netweorks and those that are more recent. As the example of an existing development shown in Figure 2 shows, not all developments provide fully and uniquely branched networks. In these cases, fourth and fifth order sampling points can be retrofitted, but may result in some low granularity for some homes.
There can be no doubt that the construction of sampling chambers at second, third, fourth and select fifth order nodes will represent considerable costs for the developer of new estates and will require considerable investment for communities to retrofit existing systems. In this context it needs to be considered that the economic cost of the COVID-19 pandemic has been considerable [117], with evidence that the costs were higher where community lockdowns were delayed due to political inaction [118,119] or due to lack of early detection [120], with a concomitant cost of human life [121]. This cost, let alone the possibly preventable loss of human life, far outweighs the cost of installing sampling chambers in new developments and the retrofitting of existing systems where feasible.

5. Outlook

The COVID-19 pandemic not only has laid bare the vulnerabilities of modern society living in high density housing, it has also shown that sewage testing proved to be a diagnostic tool for the presence of SARS-CoV-2 well before it manifested itself in clinical settings. Urban planners will need to focus their attention on the post-pandemic world, which includes a reconsideration of approaches to domestic housing design, public transport and urban recreational greenspaces. While these have high visibility, it will be the humble, underground sewer system that will provide a detection and early working system when the next epidemic or pandemic develops.
Urban planners, as well as their communities’ political leaders, are required to engage in a cognitive shift and to consider sewage and blackwater wastewater as an invaluable communal public health asset rather than as a burden of waste that needs to be speedily removed.

Funding

This research received no external funding.

Conflicts of Interest

The author declares no conflict of interest.

References

  1. WHO. Naming the Coronavirus Disease (COVID-19) and the Virus That Causes It. Available online: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/naming-the-coronavirus-disease-(covid-2019)-and-the-virus-that-causes-it (accessed on 10 August 2020).
  2. Ritchie, H.; Ortiz-Ospina, E.; Beltekian, D.; Mathieu, E.; Hasell, J.; Macdonald, B.; Giattino, C.; Roser, M. Coronavirus (COVID-19) Cases. Our World in Data. Available online: https://ourworldindata.org/covid-cases (accessed on 25 January 2021).
  3. Spreeuwenberg, P.; Kroneman, M.; Paget, J. Reassessing the global mortality burden of the 1918 influenza pandemic. Am. J. Epidemiol. 2018, 187, 2561–2567. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Gutiérrez, P.; Clarke, S.; Kirk, A. Covid world map: Which countries have the most coronavirus cases and deaths? Guardian 2021. Available online: https://www.theguardian.com/world/2021/jun/11/covid-world-map-which-countries-have-the-most-coronavirus-vaccinations-cases-and-deaths (accessed on 11 June 2021).
  5. Inayatullah, S. Neither A Black Swan Nor A Zombie Apocalypse: The Futures Of A World With The COVID-19 Coronavirus. J. Futures Stud. 2020. Available online: https://jfsdigital.org/2020/03/18/neither-a-black-swan-nor-a-zombie-apocalypse-the-futures-of-a-world-with-the-covid-19-coronavirus/ (accessed on 25 January 2021).
  6. Goh, K.-T.; Cutter, J.; Heng, B.-H.; Ma, S.; Koh, B.K.; Kwok, C.; Toh, C.-M.; Chew, S.-K. Epidemiology and control of SARS in Singapore. Ann. Acad. Med. Singap. 2006, 35, 301. [Google Scholar] [PubMed]
  7. Cunha, C.B.; Opal, S.M. Middle East respiratory syndrome (MERS) A new zoonotic viral pneumonia. Virulence 2014, 5, 650–654. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Ye, Z.-W.; Yuan, S.; Yuen, K.-S.; Fung, S.-Y.; Chan, C.-P.; Jin, D.-Y. Zoonotic origins of human coronaviruses. Int. J. Biol. Sci. 2020, 16, 1686. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Wang, L.-F.; Anderson, D.E.; Mackenzie, J.S.; Merson, M.H. From Hendra to Wuhan: What has been learned in responding to emerging zoonotic viruses. Lancet 2020, 395, e33–e34. [Google Scholar] [CrossRef] [Green Version]
  10. Peeri, N.C.; Shrestha, N.; Rahman, M.S.; Zaki, R.; Tan, Z.; Bibi, S.; Baghbanzadeh, M.; Aghamohammadi, N.; Zhang, W.; Haque, U. The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: What lessons have we learned? Int. J. Epidemiol. 2020, 49, 717–726. [Google Scholar] [CrossRef] [Green Version]
  11. Neuwirth, L.S.; Jović, S.; Mukherji, B.R. Reimagining higher education during and post-COVID-19: Challenges and opportunities. J. Adult Contin. Educ. 2020. [Google Scholar] [CrossRef]
  12. Kramer, A.; Kramer, K.Z. The potential impact of the Covid-19 pandemic on occupational status, work from home, and occupational mobility. J. Vocat. Behav. 2020, 119, 103442. [Google Scholar] [CrossRef]
  13. Haywood, K.M. A post-COVID future: Tourism community re-imagined and enabled. Tour. Geogr. 2020, 22, 599–609. [Google Scholar] [CrossRef]
  14. Spennemann, D.H.R.; Whitsed, R. The impact of COVID-19 on the Australian outdoor recreation industry from the perspective of practitioners. J. Sust. Tour. 2021, 100445. [Google Scholar] [CrossRef]
  15. Musselwhite, C.; Avineri, E.; Susilo, Y. Editorial JTH 16–The Coronavirus Disease COVID-19 and implications for transport and health. J. Transp. Health 2020, 16, 100853. [Google Scholar] [CrossRef]
  16. Bereitschaft, B.; Scheller, D. How Might the COVID-19 Pandemic Affect 21st Century Urban Design, Planning, and Development? Urban Sci. 2020, 4, 56. [Google Scholar] [CrossRef]
  17. Honey-Rosés, J.; Anguelovski, I.; Chireh, V.K.; Daher, C.; Konijnendijk van den Bosch, C.; Litt, J.S.; Mawani, V.; McCall, M.K.; Orellana, A.; Oscilowicz, E. The impact of COVID-19 on public space: An early review of the emerging questions–design, perceptions and inequities. Cities Health 2020, 1–17. [Google Scholar] [CrossRef]
  18. Spennemann, D.H.R. Residential Architecture in a post-pandemic world: Implications of COVID-19 for new construction and for adapting heritage buildings. J. Green Build. 2021, 16, 199–215. [Google Scholar] [CrossRef]
  19. Thevis, M.; Geyer, H.; Sigmund, G.; Schänzer, W. Sports drug testing: Analytical aspects of selected cases of suspected, purported, and proven urine manipulation. J. Pharm. Biomed. Anal. 2012, 57, 26–32. [Google Scholar] [CrossRef]
  20. Macdonald, S.; Hall, W.; Roman, P.; Stockwell, T.; Coghlan, M.; Nesvaag, S. Testing for cannabis in the work-place: A review of the evidence. Addiction 2010, 105, 408–416. [Google Scholar] [CrossRef] [PubMed]
  21. Thomas, K.V.; Bijlsma, L.; Castiglioni, S.; Covaci, A.; Emke, E.; Grabic, R.; Hernández, F.; Karolak, S.; Kasprzyk-Hordern, B.; Lindberg, R.H. Comparing illicit drug use in 19 European cities through sewage analysis. Sci. Total Environ. 2012, 432, 432–439. [Google Scholar] [CrossRef] [Green Version]
  22. Van Nuijs, A.L.; Mougel, J.-F.; Tarcomnicu, I.; Bervoets, L.; Blust, R.; Jorens, P.G.; Neels, H.; Covaci, A. Sewage epidemiology—a real-time approach to estimate the consumption of illicit drugs in Brussels, Belgium. Environ. Int. 2011, 37, 612–621. [Google Scholar] [CrossRef] [PubMed]
  23. Khan, U.; van Nuijs, A.L.N.; Li, J.; Maho, W.; Du, P.; Li, K.; Hou, L.; Zhang, J.; Meng, X.; Li, X.; et al. Application of a sewage-based approach to assess the use of ten illicit drugs in four Chinese megacities. Sci. Total Environ. 2014, 487, 710–721. [Google Scholar] [CrossRef]
  24. Daughton, C.G. Illicit Drugs: Contaminants in the Environment and Utility in Forensic Epidemiology. In Reviews of Environmental Contamination and Toxicology; Whitacre, D.M., Ed.; Springer: New York, NY, USA, 2011; Volume 210, pp. 59–110. [Google Scholar] [CrossRef]
  25. Irvine, R.J.; Kostakis, C.; Felgate, P.D.; Jaehne, E.J.; Chen, C.; White, J.M. Population drug use in Australia: A wastewater analysis. Forensic Sci. Int. 2011, 210, 69–73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Prichard, J.; Lai, F.Y.; Kirkbride, P.; Bruno, R.; Ort, C.; Carter, S.; Hall, W.; Gartner, C.; Thai, P.; Mueller, J. Measuring drug use patterns in Queensland through wastewater analysis. Trends Issues Crime Crim. Justice 2012, 442, 1–8. [Google Scholar]
  27. Zuccato, E.; Chiabrando, C.; Castiglioni, S.; Bagnati, R.; Fanelli, R. Estimating community drug abuse by wastewater analysis. Environ. Health Perspect. 2008, 116, 1027–1032. [Google Scholar] [CrossRef] [Green Version]
  28. Ort, C.; Van Nuijs, A.L.; Berset, J.D.; Bijlsma, L.; Castiglioni, S.; Covaci, A.; de Voogt, P.; Emke, E.; Fatta-Kassinos, D.; Griffiths, P. Spatial differences and temporal changes in illicit drug use in Europe quantified by wastewater analysis. Addiction 2014, 109, 1338–1352. [Google Scholar] [CrossRef]
  29. Brewer, A.J.; Banta-Green, C.J.; Ort, C.; Robel, A.E.; Field, J. Wastewater testing compared with random urinalyses for the surveillance of illicit drug use in prisons. Drug Alcohol Rev. 2016, 35, 133–137. [Google Scholar] [CrossRef] [Green Version]
  30. Foppe, K.S.; Hammond-Weinberger, D.R.; Subedi, B. Estimation of the consumption of illicit drugs during special events in two communities in Western Kentucky, USA using sewage epidemiology. Sci. Total Environ. 2018, 633, 249–256. [Google Scholar] [CrossRef]
  31. Benaglia, L.; Udrisard, R.; Bannwarth, A.; Gibson, A.; Béen, F.; Lai, F.Y.; Esseiva, P.; Delémont, O. Testing wastewater from a music festival in Switzerland to assess illicit drug use. Forensic Sci. Int. 2020, 309, 110148. [Google Scholar] [CrossRef]
  32. Lai, F.Y.; Thai, P.K.; O’Brien, J.; Gartner, C.; Bruno, R.; Kele, B.; Ort, C.; Prichard, J.; Kirkbride, P.; Hall, W.; et al. Using quantitative wastewater analysis to measure daily usage of conventional and emerging illicit drugs at an annual music festival. Drug Alcohol Rev. 2013, 32, 594–602. [Google Scholar] [CrossRef] [Green Version]
  33. Mackuľak, T.; Birošová, L.; Gál, M.; Bodík, I.; Grabic, R.; Ryba, J.; Škubák, J. Wastewater analysis: The mean of the monitoring of frequently prescribed pharmaceuticals in Slovakia. Environ. Monit. Assess. 2016, 188, 1–12. [Google Scholar] [CrossRef] [PubMed]
  34. Zheng, Q.-D.; Lin, J.-G.; Pei, W.; Guo, M.-X.; Wang, Z.; Wang, D.-G. Estimating nicotine consumption in eight cities using sewage epidemiology based on ammonia nitrogen equivalent population. Sci. Total Environ. 2017, 590–591, 226–232. [Google Scholar] [CrossRef]
  35. Banks, A.P.W.; Lai, F.Y.; Mueller, J.F.; Jiang, G.; Carter, S.; Thai, P.K. Potential impact of the sewer system on the applicability of alcohol and tobacco biomarkers in wastewater-based epidemiology. Drug Test. Anal. 2018, 10, 530–538. [Google Scholar] [CrossRef] [PubMed]
  36. Ahmed, F.; Tscharke, B.; O’Brien, J.; Thompson, J.; Samanipour, S.; Choi, P.; Li, J.; Mueller, J.F.; Thomas, K. Wastewater-based estimation of the prevalence of gout in Australia. Sci. Total Environ. 2020, 715, 136925. [Google Scholar] [CrossRef]
  37. Moll, D.M.; Frick, E.A.; Henderson, A.K.; Furlong, E.T.; Meyer, M.T. Presence of pharmaceuticals in treated wastewater effluent and surface water supply systems, metropolitan Atlanta, Georgia, July–September 1999. In Proceedings of the 2nd International Conference on Pharmaceuticals and Endocrine Disrupting Chemicals in Water, Minneapolis, MN, USA, 9–11 October 2001. [Google Scholar]
  38. Singer, A.C.; Järhult, J.D.; Grabic, R.; Khan, G.A.; Lindberg, R.H.; Fedorova, G.; Fick, J.; Bowes, M.J.; Olsen, B.; Söderström, H. Intra-and inter-pandemic variations of antiviral, antibiotics and decongestants in wastewater treatment plants and receiving rivers. PLoS ONE 2014, 9, e108621. [Google Scholar] [CrossRef]
  39. Burgard, D.A.; Fuller, R.; Becker, B.; Ferrell, R.; Dinglasan-Panlilio, M. Potential trends in Attention Deficit Hyperactivity Disorder (ADHD) drug use on a college campus: Wastewater analysis of amphetamine and ritalinic acid. Sci. Total Environ. 2013, 450, 242–249. [Google Scholar] [CrossRef] [PubMed]
  40. Leknes, H.; Sturtzel, I.E.; Dye, C. Environmental release of oseltamivir from a Norwegian sewage treatment plant during the 2009 influenza A (H1N1) pandemic. Sci. Total Environ. 2012, 414, 632–638. [Google Scholar] [CrossRef] [PubMed]
  41. Shinohara, N.; Tanaka, H.; Saito, T.; Deguchi, J.; Soda, K.; Sonoda, S.; Sugiyama, T.; Ishimaru, Y. Surveillance for typhoid fever in Matsuyama city during 1974-1981 and detection of Salmonella typhi in sewage and river waters. Jpn. J. Med Sci. Biol. 1983, 36, 191–197. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Yanagimoto, K.; Yamagami, T.; Uematsu, K.; Haramoto, E. Characterization of Salmonella isolates from wastewater treatment plant influents to estimate unreported cases and infection sources of salmonellosis. Pathogens 2020, 9, 52. [Google Scholar] [CrossRef] [Green Version]
  43. Cai, L.; Zhang, T. Detecting human bacterial pathogens in wastewater treatment plants by a high-throughput shotgun sequencing technique. Environ. Sci. Technol. 2013, 47, 5433–5441. [Google Scholar] [CrossRef]
  44. Huijbers, P.M.; Flach, C.-F.; Larsson, D.J. A conceptual framework for the environmental surveillance of antibiotics and antibiotic resistance. Environ. Int. 2019, 130, 104880. [Google Scholar] [CrossRef]
  45. Nakamura, T.; Hamasaki, M.; Yoshitomi, H.; Ishibashi, T.; Yoshiyama, C.; Maeda, E.; Sera, N.; Yoshida, H. Environmental surveillance of poliovirus in sewage water around the introduction period for inactivated polio vaccine in Japan. Appl. Environ. Microbiol. 2015, 81, 1859–1864. [Google Scholar] [CrossRef] [Green Version]
  46. Smith, D.B.; Paddy, J.O.; Simmonds, P. The use of human sewage screening for community surveillance of hepatitis E virus in the UK. J. Med. Virol. 2016, 88, 915–918. [Google Scholar] [CrossRef] [Green Version]
  47. Filipidou, A.; Parasidis, T.; Alexandropoulou, I.; Stavrou, E.; Karlou, K.; Vantarakis, A. Detection of Infectious Pathogenic Viruses in Untreated and Treated Wastewater Samples from An Urbanised Area. Int. J. Infect. Dis. 2008, 12, e104. [Google Scholar] [CrossRef] [Green Version]
  48. Heijnen, L.; Medema, G. Surveillance of influenza A and the pandemic influenza A (H1N1) 2009 in sewage and surface water in the Netherlands. J. Water Health 2011, 9, 434–442. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Amdiouni, H.; Faouzi, A.; Fariat, N.; Hassar, M.; Soukri, A.; Nourlil, J. Detection and molecular identification of human adenoviruses and enteroviruses in wastewater from Morocco. Lett. Appl. Microbiol. 2012, 54, 359–366. [Google Scholar] [CrossRef] [PubMed]
  50. Battistone, A.; Buttinelli, G.; Bonomo, P.; Fiore, S.; Amato, C.; Mercurio, P.; Cicala, A.; Simeoni, J.; Foppa, A.; Triassi, M. Detection of enteroviruses in influent and effluent flow samples from wastewater treatment plants in Italy. Food Environ. Virol. 2014, 6, 13–22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  51. Pennino, F.; Nardone, A.; Montuori, P.; Aurino, S.; Torre, I.; Battistone, A.; Delogu, R.; Buttinelli, G.; Fiore, S.; Amato, C. Large-scale survey of human enteroviruses in wastewater treatment plants of a metropolitan area of southern Italy. Food Environ. Virol. 2018, 10, 187–192. [Google Scholar] [CrossRef]
  52. McCall, C.; Wu, H.; Miyani, B.; Xagoraraki, I. Identification of multiple potential viral diseases in a large urban center using wastewater surveillance. Water Res. 2020, 184, 116160. [Google Scholar] [CrossRef]
  53. Santiso-Bellón, C.; Randazzo, W.; Pérez-Cataluña, A.; Vila-Vicent, S.; Gozalbo-Rovira, R.; Muñoz, C.; Buesa, J.; Sanchez, G.; Rodríguez Díaz, J. Epidemiological surveillance of norovirus and rotavirus in sewage (2016–2017) in Valencia (Spain). Microorganisms 2020, 8, 458. [Google Scholar] [CrossRef] [Green Version]
  54. Gourinat, A.-C.; O’Connor, O.; Calvez, E.; Goarant, C.; Dupont-Rouzeyrol, M. Detection of Zika virus in urine. Emerg. Infect. Dis. 2015, 21, 84. [Google Scholar] [CrossRef]
  55. Muirhead, A.; Zhu, K.; Brown, J.; Basu, M.; Brinton, M.A.; Costa, F.; Hayat, M.J.; Stauber, C.E. Zika Virus RNA persistence in sewage. Environ. Sci. Technol. Lett. 2020, 7, 659–664. [Google Scholar] [CrossRef]
  56. Chandra, F.; Lee, W.L.; Armas, F.; Leifels, M.; Gu, X.; Chen, H.; Wuertz, S.; Alm, E.J.; Thompson, J. Persistence of Dengue (Serotypes 2 and 3), Zika, Yellow Fever, and Murine Hepatitis Virus RNA in Untreated Wastewater. Environ. Sci. Technol. Lett. 2021, 8, 785–791. [Google Scholar] [CrossRef]
  57. Barzon, L.; Pacenti, M.; Franchin, E.; Pagni, S.; Martello, T.; Cattai, M.; Cusinato, R.; Palù, G. Excretion of West Nile virus in urine during acute infection. J. Infect. Dis. 2013, 208, 1086–1092. [Google Scholar] [CrossRef] [Green Version]
  58. Hirayama, T.; Mizuno, Y.; Takeshita, N.; Kotaki, A.; Tajima, S.; Omatsu, T.; Sano, K.; Kurane, I.; Takasaki, T. Detection of dengue virus genome in urine by real-time reverse transcriptase PCR: A laboratory diagnostic method useful after disappearance of the genome in serum. J. Clin. Microbiol. 2012, 50, 2047–2052. [Google Scholar] [CrossRef] [Green Version]
  59. Mizuno, Y.; Kotaki, A.; Harada, F.; Tajima, S.; Kurane, I.; Takasaki, T. Confirmation of dengue virus infection by detection of dengue virus type 1 genome in urine and saliva but not in plasma. Trans. R. Soc. Trop. Med. Hyg. 2007, 101, 738–739. [Google Scholar] [CrossRef] [PubMed]
  60. Thai, P.K.; O’Brien, J.; Jiang, G.; Gernjak, W.; Yuan, Z.; Eaglesham, G.; Mueller, J.F. Degradability of creatinine under sewer conditions affects its potential to be used as biomarker in sewage epidemiology. Water Res. 2014, 55, 272–279. [Google Scholar] [CrossRef]
  61. Li, J.; Gao, J.; Thai, P.K.; Mueller, J.F.; Yuan, Z.; Jiang, G. Transformation of Illicit Drugs and Pharmaceuticals in Sewer Sediments. Environ. Sci. Technol. 2020, 54, 13056–13065. [Google Scholar] [CrossRef] [PubMed]
  62. Gundy, P.M.; Gerba, C.P.; Pepper, I.L. Survival of coronaviruses in water and wastewater. Food Environ. Virol. 2009, 1, 10–14. [Google Scholar] [CrossRef] [Green Version]
  63. Wang, X.-W.; Li, J.-S.; Guo, T.-K.; Zhen, B.; Kong, Q.-X.; Yi, B.; Li, Z.; Song, N.; Jin, M.; Xiao, W.-J. Concentration and detection of SARS coronavirus in sewage from Xiao Tang Shan Hospital and the 309th Hospital. J. Virol. Methods 2005, 128, 156–161. [Google Scholar] [CrossRef] [PubMed]
  64. Izquierdo-Lara, R.; Elsinga, G.; Heijnen, L.; Munnink, B.B.O.; Schapendonk, C.M.; Nieuwenhuijse, D.; Kon, M.; Lu, L.; Aarestrup, F.M.; Lycett, S. Monitoring SARS-CoV-2 circulation and diversity through community wastewater sequencing, the netherlands and belgium. Emerg. Infect. Dis. 2021, 27, 1405. [Google Scholar] [CrossRef] [PubMed]
  65. Wilton, T.; Bujaki, E.; Klapsa, D.; Majumdar, M.; Zambon, M.; Fritzsche, M.; Mate, R.; Martin, J. Rapid increase of SARS-CoV-2 variant B. 1.1. 7 detected in sewage samples from England between October 2020 and January 2021. Msystems 2021, 6, e00353-21. [Google Scholar] [CrossRef] [PubMed]
  66. Lesté-Lasserre, C. Coronavirus found in Paris sewage points to early warning system. Science 2020. [Google Scholar] [CrossRef]
  67. Westhaus, S.; Weber, F.-A.; Schiwy, S.; Linnemann, V.; Brinkmann, M.; Widera, M.; Greve, C.; Janke, A.; Hollert, H.; Wintgens, T. Detection of SARS-CoV-2 in raw and treated wastewater in Germany–suitability for COVID-19 surveillance and potential transmission risks. Sci. Total Environ. 2021, 751, 141750. [Google Scholar] [CrossRef] [PubMed]
  68. Róka, E.; Khayer, B.; Kis, Z.; Kovács, L.B.; Schuler, E.; Magyar, N.; Málnási, T.; Oravecz, O.; Pályi, B.; Pándics, T. Ahead of the second wave: Early warning for COVID-19 by wastewater surveillance in Hungary. Sci. Total Environ. 2021, 786, 147398. [Google Scholar] [CrossRef] [PubMed]
  69. La Rosa, G.; Iaconelli, M.; Mancini, P.; Ferraro, G.B.; Veneri, C.; Bonadonna, L.; Lucentini, L.; Suffredini, E. First detection of SARS-CoV-2 in untreated wastewaters in Italy. Sci. Total Environ. 2020, 736, 139652. [Google Scholar] [CrossRef] [PubMed]
  70. Medema, G.; Heijnen, L.; Elsinga, G.; Italiaander, R.; Brouwer, A. Presence of SARS-Coronavirus-2 RNA in sewage and correlation with reported COVID-19 prevalence in the early stage of the epidemic in the Netherlands. Environ. Sci. Technol. Lett. 2020, 7, 511–516. [Google Scholar] [CrossRef]
  71. Kuryntseva, P.; Karamova, K.; Fomin, V.; Selivanovskaya, S.; Galitskaya, P. A simplified approach to monitoring the COVID-19 epidemiologic situation using waste water analysis and its application in Russia. medRxiv 2020. [Google Scholar] [CrossRef]
  72. Chavarria-Miró, G.; Anfruns-Estrada, E.; Martínez-Velázquez, A.; Vázquez-Portero, M.; Guix, S.; Paraira, M.; Galofré, B.; Sánchez, G.; Pintó, R.M.; Bosch, A. Time evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater during the first pandemic wave of COVID-19 in the metropolitan area of Barcelona, Spain. Appl. Environ. Microbiol. 2021, 87, e02750-20. [Google Scholar] [CrossRef]
  73. Randazzo, W.; Cuevas-Ferrando, E.; Sanjuán, R.; Domingo-Calap, P.; Sánchez, G. Metropolitan wastewater analysis for COVID-19 epidemiological surveillance. Int. J. Hyg. Environ. Health 2020, 230, 113621. [Google Scholar] [CrossRef]
  74. Jahn, K.; Dreifuss, D.; Topolsky, I.; Kull, A.; Ganesanandamoorthy, P.; Fernandez-Cassi, X.; Bänziger, C.; Stachler, E.; Fuhrmann, L.; Jablonski, K.P. Detection of SARS-CoV-2 variants in Switzerland by genomic analysis of wastewater samples. medRxiv 2021. [Google Scholar] [CrossRef]
  75. Kocamemi, B.A.; Kurt, H.; Hacioglu, S.; Yarali, C.; Saatci, A.M.; Pakdemirli, B. First data-set on SARS-CoV-2 detection for Istanbul wastewaters in Turkey. medRxiv 2020. [Google Scholar] [CrossRef]
  76. Kocamemi, B.A.; Kurt, H.; Sait, A.; Kadi, H.; Sarac, F.; Aydin, I.; Saatci, A.M.; Pakdemirli, B. Nationwide SARS-CoV-2 Surveillance Study for Sewage and Sludges of Wastewater Treatment Plants in Turkey. medRxiv 2020. [Google Scholar] [CrossRef]
  77. Xu, X.; Zheng, X.; Li, S.; Lam, N.S.; Wang, Y.; Chu, D.K.; Poon, L.L.; Tun, H.M.; Peiris, M.; Deng, Y. The first case study of wastewater-based epidemiology of COVID-19 in Hong Kong. Sci. Total Environ. 2021, 790, 148000. [Google Scholar] [CrossRef]
  78. Or, I.B.; Yaniv, K.; Shagan, M.; Ozer, E.; Erster, O.; Mendelson, E.; Mannasse, B.; Shirazi, R.; Kramarsky-Winter, E.; Nir, O. Regressing SARS-CoV-2 sewage measurements onto COVID-19 burden in the population: A proof-of-concept for quantitative environmental surveillance. medRxiv 2020. [Google Scholar] [CrossRef]
  79. Yaniv, K.; Shagan, M.; Lewis, Y.E.; Kramarsky-Winter, E.; Weil, M.; Indenbaum, V.; Elul, M.; Erster, O.; Brown, A.S.; Mendelson, E. City-level SARS-CoV-2 sewage surveillance. Chemosphere 2021, 283, 131194. [Google Scholar] [CrossRef]
  80. Kumar, M.; Patel, A.K.; Shah, A.V.; Raval, J.; Rajpara, N.; Joshi, M.; Joshi, C.G. First proof of the capability of wastewater surveillance for COVID-19 in India through detection of genetic material of SARS-CoV-2. Sci. Total Environ. 2020, 746, 141326. [Google Scholar] [CrossRef]
  81. Yaqub, T.; Nawaz, M.; Shabbir, M.Z.; Ali, M.A.; Altaf, I.; Raza, S.; Shabbir, M.A.B.; Ashraf, M.A.; Aziz, S.Z.; Cheema, S.Q. A longitudinal survey for genome-based identification of SARS-CoV-2 in sewage water in selected lockdown areas of Lahore city, Pakistan; a potential approach for future smart lockdown strategy. medRxiv 2020. [Google Scholar] [CrossRef]
  82. Alahdal, H.M.; Ameen, F.; AlYahya, S.; Sonbol, H.; Khan, A.; Alsofayan, Y.; Alahmari, A. Municipal wastewater viral pollution in Saudi Arabia: Effect of hot climate on COVID-19 disease spreading. Environ. Sci. Pollut. Res. 2021, 1–8. [Google Scholar] [CrossRef]
  83. Mota, C.R.; Bressani-Ribeiro, T.; Araújo, J.C.; Leal, C.D.; Leroy-Freitas, D.; Machado, E.C.; Espinosa, M.F.; Fernandes, L.; Leão, T.L.; Chamhum-Silva, L. Assessing spatial distribution of COVID-19 prevalence in Brazil using decentralised sewage monitoring. Water Res. 2021, 202, 117388. [Google Scholar] [CrossRef] [PubMed]
  84. Fongaro, G.; Stoco, P.H.; Souza, D.S.M.; Grisard, E.C.; Magri, M.E.; Rogovski, P.; Schörner, M.A.; Barazzetti, F.H.; Christoff, A.P.; de Oliveira, L.F.V. The presence of SARS-CoV-2 RNA in human sewage in Santa Catarina, Brazil, November 2019. Sci. Total Environ. 2021, 778, 146198. [Google Scholar] [CrossRef] [PubMed]
  85. Ampuero, M.; Valenzuela, S.; Valiente-Echeverría, F.; Soto-Rifo, R.; Barriga, G.P.; Chnaiderman, J.; Rojas, C.; Guajardo-Leiva, S.; Díez, B.; Gaggero, A. SARS-CoV-2 Detection in Sewage in Santiago, Chile—Preliminary results. medRxiv 2020. [Google Scholar] [CrossRef]
  86. Carrillo-Reyes, J.; Barragán-Trinidad, M.; Buitrón, G. Surveillance of SARS-CoV-2 in sewage and wastewater treatment plants in Mexico. J. Water Process Eng. 2021, 40, 101815. [Google Scholar] [CrossRef]
  87. Peccia, J.; Zulli, A.; Brackney, D.E.; Grubaugh, N.D.; Kaplan, E.H.; Casanovas-Massana, A.; Ko, A.I.; Malik, A.A.; Wang, D.; Wang, M. SARS-CoV-2 RNA concentrations in primary municipal sewage sludge as a leading indicator of COVID-19 outbreak dynamics. medRxiv 2020. [Google Scholar] [CrossRef]
  88. Larsen, D.A.; Wigginton, K.R. Tracking COVID-19 with wastewater. Nat. Biotechnol. 2020, 38, 1151–1153. [Google Scholar] [CrossRef]
  89. Ahmed, W.; Angel, N.; Edson, J.; Bibby, K.; Bivins, A.; O’Brien, J.W.; Choi, P.M.; Kitajima, M.; Simpson, S.L.; Li, J. First confirmed detection of SARS-CoV-2 in untreated wastewater in Australia: A proof of concept for the wastewater surveillance of COVID-19 in the community. Sci. Total Environ. 2020, 728, 138764. [Google Scholar] [CrossRef]
  90. Black, J.; Aung, P.; Nolan, M.; Roney, E.; Poon, R.; Hennessy, D.; Crosbie, N.D.; Deere, D.; Jex, A.R.; John, N. Epidemiological evaluation of sewage surveillance as a tool to detect the presence of COVID-19 cases in a low case load setting. Sci. Total Environ. 2021, 786, 147469. [Google Scholar] [CrossRef]
  91. Aslan, A.; Shah, G.; Sittaramane, V.; Shankar, P. Sewage Monitoring in Rural Communities: A Powerful Strategy for COVID-19 Surveillance. J. Environ. Health 2020, 83, 8–10. [Google Scholar]
  92. Calabria de Araujo, J.; Gavazza, S.; Leao, T.L.; Florencio, L.; da Silva, H.P.; Albuquerque, J.d.O.; de Lira Borges, M.A.; de Oliveira Alves, R.B.; Rodrigues, R.H.A.; dos Santos, E.B. SARS-CoV-2 sewage surveillance in low-income countries: Potential and challenges. J. Water Health 2021, 19, 1–19. [Google Scholar] [CrossRef]
  93. Panchal, D.; Prakash, O.; Bobde, P.; Pal, S. SARS-CoV-2: Sewage surveillance as an early warning system and challenges in developing countries. Environ. Sci. Pollut. Res. 2021, 28, 22221–22240. [Google Scholar] [CrossRef] [PubMed]
  94. Michael-Kordatou, I.; Karaolia, P.; Fatta-Kassinos, D. Sewage analysis as a tool for the COVID-19 pandemic response and management: The urgent need for optimised protocols for SARS-CoV-2 detection and quantification. J. Environ. Chem. Eng. 2020, 8, 104306. [Google Scholar] [CrossRef] [PubMed]
  95. Sharma, D.K.; Nalavade, U.P.; Kalgutkar, K.; Gupta, N.; Deshpande, J.M. SARS-CoV-2 detection in sewage samples: Standardization of method & preliminary observations. Indian J. Med. Res. 2021, 153, 159. [Google Scholar] [PubMed]
  96. De Feo, G.; Antoniou, G.; Fardin, H.F.; El-Gohary, F.; Zheng, X.Y.; Reklaityte, I.; Butler, D.; Yannopoulos, S.; Angelakis, A.N. The historical development of sewers worldwide. Sustainability 2014, 6, 3936–3974. [Google Scholar] [CrossRef] [Green Version]
  97. Sunderland, D. ‘A monument to defective administration’? The London Commissions of Sewers in the early nineteenth century. Urban Hist. 1999, 26, 349–372. [Google Scholar] [CrossRef]
  98. Cook, G.C. Construction of London’s Victorian sewers: The vital role of Joseph Bazalgette. Postgrad. Med. J. 2001, 77, 802. [Google Scholar] [CrossRef]
  99. Goldman, J.A. Building New York’s Sewers: Developing Mechanisms of Urban Management; Purdue University Press: West Lafayette, IN, USA, 1997. [Google Scholar]
  100. Eggimann, S.; Truffer, B.; Maurer, M. To connect or not to connect? Modelling the optimal degree of centralisation for wastewater infrastructures. Water Res. 2015, 84, 218–231. [Google Scholar] [CrossRef] [Green Version]
  101. Spennemann, D.H.R.; Parker, M. Hitting the ‘Pause’ Button: What does COVID tell us about the future of heritage sounds? Noise Mapp. 2020, 7, 265–275. [Google Scholar] [CrossRef]
  102. Storen, R.; Corrigan, N. COVID-19: A chronology of state and territory government announcements (up until 30 June 2020). In Parliamentary Library Research Paper Series 2020–21; Parliamentary Library, Commonwealth of Australia: Canberra, Australia, 2020. [Google Scholar]
  103. Siddik, M.N.A. Economic stimulus for COVID-19 pandemic and its determinants: Evidence from cross-country analysis. Heliyon 2020, 6, e05634. [Google Scholar] [CrossRef]
  104. Elgin, C.; Basbug, G.; Yalaman, A. Economic policy responses to a pandemic: Developing the COVID-19 economic stimulus index. Covid Econ. 2020, 1, 40–53. [Google Scholar]
  105. Wong, J.; Wong, N. The economics and accounting for COVID-19 wage subsidy and other government grants. Pac. Account. Rev. 2021, 33, 199–211. [Google Scholar] [CrossRef]
  106. Risch, E.; Gutierrez, O.; Roux, P.; Boutin, C.; Corominas, L. Life cycle assessment of urban wastewater systems: Quantifying the relative contribution of sewer systems. Water Res. 2015, 77, 35–48. [Google Scholar] [CrossRef] [Green Version]
  107. Monteiro, H.; Fernandez, J.E.; Freire, F. Comparative life-cycle energy analysis of a new and an existing house: The significance of occupant’s habits, building systems and embodied energy. Sustain. Cities Soc. 2016, 26, 507–518. [Google Scholar] [CrossRef]
  108. Wuyts, W.; Miatto, A.; Sedlitzky, R.; Tanikawa, H. Extending or ending the life of residential buildings in Japan: A social circular economy approach to the problem of short-lived constructions. J. Clean. Prod. 2019, 231, 660–670. [Google Scholar] [CrossRef]
  109. Öberg, G.; Merlinsky, M.G.; LaValle, A.; Morales, M.; Tobias, M.M. The notion of sewage as waste: A study of infrastructure change and institutional inertia in Buenos Aires, Argentina and Vancouver, Canada. Ecol. Soc. 2014, 19. [Google Scholar] [CrossRef] [Green Version]
  110. Otterpohl, R.; Braun, U.; Oldenburg, M. Innovative technologies for decentralised wastewater management in urban and peri-urban areas. Ber. -Wassergute Und Abfallwirtsch. Tech. Univ. Munch. Berichtsh. 2002, 173, 109–126. [Google Scholar] [CrossRef]
  111. Kjerstadius, H.; Haghighatafshar, S.; Davidsson, Å. Potential for nutrient recovery and biogas production from blackwater, food waste and greywater in urban source control systems. Environ. Technol. 2015, 36, 1707–1720. [Google Scholar] [CrossRef] [PubMed]
  112. Kujawa-Roeleveld, K.; Zeeman, G. Anaerobic Treatment in Decentralised and Source-Separation-Based Sanitation Concepts. Rev. Environ. Sci. Bio/Technol. 2006, 5, 115–139. [Google Scholar] [CrossRef]
  113. Skambraks, A.-K.; Kjerstadius, H.; Meier, M.; Davidsson, Å.; Wuttke, M.; Giese, T. Source separation sewage systems as a trend in urban wastewater management: Drivers for the implementation of pilot areas in Northern Europe. Sustain. Cities Soc. 2017, 28, 287–296. [Google Scholar] [CrossRef]
  114. Water Services Association of Australia. Sewerage Code of Australia; WSA 02-2002; Water Services Association of Australia: Melbourne, Australia; Sydney, Australia, 2002. [Google Scholar]
  115. Water Services Association of Australia. Gravity Sewerage Code of Australia; WSA 02-2014; Water Services Association of Australia: Melbourne, Australia; Sydney, Australia, 2014. [Google Scholar]
  116. Water Services Association of Australia. Pressure Sewerage Code of Australia; WSA 07-2007; Water Services Association of Australia: Melbourne, Australia; Sydney, Australia, 2007. [Google Scholar]
  117. Mandel, A.; Veetil, V. The economic cost of COVID lockdowns: An out-of-equilibrium analysis. Econ. Disasters Clim. Chang. 2020, 4, 431–451. [Google Scholar] [CrossRef] [PubMed]
  118. Magli, A.C.; d’Onofrio, A.; Manfredi, P. Deteriorated Covid19 control due to delayed lockdown resulting from strategic interactions between Governments and oppositions. medRxiv 2020. [Google Scholar] [CrossRef]
  119. Lasaulce, S.; Varma, V.S.; Morarescu, C.; Siying, L. How efficient are the lockdown measures taken for mitigating the Covid-19 epidemic? medRxiv 2020. [Google Scholar] [CrossRef]
  120. López-Valcárcel, B.G.; Vallejo-Torres, L. The costs of COVID-19 and the cost-effectiveness of testing. Appl. Econ. Anal. 2021, 29. [Google Scholar] [CrossRef]
  121. Balmford, B.; Annan, J.D.; Hargreaves, J.C.; Altoè, M.; Bateman, I.J. Cross-country comparisons of COVID-19: Policy, politics and the price of life. Environ. Resour. Econ. 2020, 76, 525–551. [Google Scholar] [CrossRef]
Figure 1. Conceptual example of hierarchical clustering of sampling points.
Figure 1. Conceptual example of hierarchical clustering of sampling points.
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Figure 2. Conceptual example of retrofitting stratified sampling points to an existing development in Albury, NSW, Australia. (A) Aerial image; (B) street and contour map; (C) existing sewerage net-work color coded to show subnetworks; (D) suggested interception and sampling points (aerial photograph, base map and sewer alignment based on data derived from the Albury City Mapping Portal).
Figure 2. Conceptual example of retrofitting stratified sampling points to an existing development in Albury, NSW, Australia. (A) Aerial image; (B) street and contour map; (C) existing sewerage net-work color coded to show subnetworks; (D) suggested interception and sampling points (aerial photograph, base map and sewer alignment based on data derived from the Albury City Mapping Portal).
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Spennemann, D.H.R. Preparing for COVID-2x: Urban Planning Needs to Regard Urological Wastewater as an Invaluable Communal Public Health Asset and Not as a Burden. Urban Sci. 2021, 5, 75. https://0-doi-org.brum.beds.ac.uk/10.3390/urbansci5040075

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Spennemann DHR. Preparing for COVID-2x: Urban Planning Needs to Regard Urological Wastewater as an Invaluable Communal Public Health Asset and Not as a Burden. Urban Science. 2021; 5(4):75. https://0-doi-org.brum.beds.ac.uk/10.3390/urbansci5040075

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Spennemann, Dirk H. R. 2021. "Preparing for COVID-2x: Urban Planning Needs to Regard Urological Wastewater as an Invaluable Communal Public Health Asset and Not as a Burden" Urban Science 5, no. 4: 75. https://0-doi-org.brum.beds.ac.uk/10.3390/urbansci5040075

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