<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. [...]