<https://www.nature.com/articles/s41746-022-00582-0>
[...]
As shown in Fig. 1
<https://www.nature.com/articles/s41746-022-00582-0#Fig1>, a public
health strategy is proposed for infectious disease surveillance using
toilets fitted with a stool collection and analysis system that performs
fully automated and passive diagnostics. A smart toilet platform, namely
“_Co_rona_v_irus: _I_ntegrated _D_iagnostic (COV-ID) toilet” would
consist of a mountable bidet-style attachment equipped with modules for
automated faecal sample collection and processing, faecal RNA isolation
and detection with in situ ultrafast nucleic acid amplification tests
(NAAT), and effective sanitisation methods. COV-ID toilets can be
installed in highly trafficked, public areas ranging from shopping malls
and sporting arenas to schools and hospitals. While a person sits down
to use the toilet, they can scan a Quick Response (QR) code to consent
to COVID-19 stool testing. If permitted, the COV-ID toilet will detect
defecation events and automatically sample and test the stool for
COVID-19. Test results are reported in minutes—to the individual’s
smartphone, if desired, and to an anonymized tracing system. The
individual with a positive result will be provided with information to
determine quarantine protocols and further confirmatory testing. The
tracing system can be linked to the existing Bluetooth^® contact tracing
systems implemented by Apple^12
<https://www.nature.com/articles/s41746-022-00582-0#ref-CR12> and
Google^13 <https://www.nature.com/articles/s41746-022-00582-0#ref-CR13>
for COVID-19 exposure notifications. A network of COV-ID toilets could
also augment and refine maps of COVID-19 prevalence, and provide more
real-time information to guide decisions about travel. The same testing
principles can also be applied to other infectious diseases with
faecal–oral transmission, such as norovirus or bacteria related to
gastroenteritis like Shigella, to help prevent and control outbreaks in
real time.
The prerequisites for successful deployment of COV-ID toilets in diverse
communities are: (1) A fast turn-around time, ideally within 15 min from
sample-to-answer. In this regard, ultrafast NAAT are preferred to
shortening the turn-around time of conventional NAAT methods (e.g. PCR)
from a couple of hours down to 8–15 min^14
<https://www.nature.com/articles/s41746-022-00582-0#ref-CR14>,15
<https://www.nature.com/articles/s41746-022-00582-0#ref-CR15>,16
<https://www.nature.com/articles/s41746-022-00582-0#ref-CR16>,17
<https://www.nature.com/articles/s41746-022-00582-0#ref-CR17> . In
addition, multiplexed and parallel runs of COVID-19 detection in the
system can ensure immediate toilet availability to other users. (2) Full
automation from sample acquisition to signal generation must be
performed in the background in order not to interfere with normal human
behaviour on the toilet. This automation will maintain high user
compliance and lower human intervention. (3) To provide a hygienic
environment and eliminate cross-contamination between tests, rigorous
sanitation/sterilisation (e.g. ultraviolet steriliser) has to be
performed on the analytical devices and on the surface of the toilet.
(4) As an Internet of Things (IoT) device, the COV-ID toilet should be
securely connected to a centralised network, which enables active
communication with users and intra-network surveillance. (5) While the
user may elect to provide identifying information such as a cell phone
number in order to receive their own test results, the results must be
de-identified prior to upload to the tracing network in order to
maintain the user’s privacy.
Other important biological/clinical data can be obtained by the COV-ID
toilet. Body temperature and oxygen saturation, which are known to be
critical parameters of COVID-19 infection, can be obtained by
integrating temperature and photoplethysmography sensors into the toilet
seat^18 <https://www.nature.com/articles/s41746-022-00582-0#ref-CR18> .
Stool morphology analysis can identify diarrhoea, which is a potential
symptom of COVID-19. This feature can be easily adopted from a previous
smart toilet study with deep learning and computer vision^19
<https://www.nature.com/articles/s41746-022-00582-0#ref-CR19>,20
<https://www.nature.com/articles/s41746-022-00582-0#ref-CR20> . By
collecting other supplementary data (temperature, oxygen saturation, and
stool morphology) in tandem with COVID-19 stool testing, the COV-ID
toilet may enable comprehensive profiling of COVID-19 infection.
[...]
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