Smart toilets for monitoring COVID-19 surges: passive diagnostics and public health.
Ontology highlight
ABSTRACT:
SUBMITTER: Ge TJ
PROVIDER: S-EPMC8967843 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature
Publications
Smart toilets for monitoring COVID-19 surges: passive diagnostics and public health.
Ge T Jessie TJ Chan Carmel T CT Lee Brian J BJ Liao Joseph C JC Park Seung-Min SM
NPJ digital medicine 20220330 1
Similar Datasets
Project description:The incredible spread rate of coronavirus disease 2019 (COVID-19) outbreak has shocked the world. More than ever before, this dramatic scenario proved the significance of diagnostics as a cornerstone to make life-saving decisions. In this context, novel diagnostics that generates smart data leading to superior strategies for treatment, control, surveillance, prediction, prevention, and management of pandemic diseases is vital. Herein, we discuss the characteristics that should be met by COVID-19 diagnostics to become smart diagnostics enabled by industry 4.0 especially Internet of Things (IoT). The challenges ahead and our recommendations for moving faster from pure diagnostics toward smart diagnostics of COVID-19 and other possible epidemic/pandemic diseases are also outlined. An IoT-Fog-Cloud model based on smartphones as IoT gateways for smart diagnostics with unified strategies for data collection/transmission/interpretation is also proposed to integrate new digital technologies into a single platform for smarter decisions. Last but not least, we believe that "smart diagnostics" is a perspective that should be realized sooner before we encounter a pandemic far worse than the present one.
| S-EPMC8247766 | biostudies-literature
Project description: Not available
| S-EPMC8385050 | biostudies-literature
Project description:During 2020-2021, the COVID-19 pandemic exposed significant vulnerabilities in hospital safety, with oxygen-related fires and explosions occurring at twice the usual rate. This highlighted insufficient preparedness for increased oxygen therapy demands and the associated risks of oxygen-enriched atmospheres. This study aimed to develop and test a smart monitoring system to detect increased oxygen concentrations in hospital environments, mitigating the risk of fires. Based on Internet of Things (IoT) technology, the system includes wireless sensors that measure oxygen levels at regular intervals and transmit the data to a database. Alerts are sent to hospital staff via short message service and e-mail when oxygen levels exceed predefined thresholds. The sensors were deployed in an intensive care unit and were validated through real-time measurements under hospital conditions. The system demonstrated high accuracy (±1%) in monitoring oxygen concentrations with low power consumption (345 µA for oxygen concentration measurements taken every minute). Notifications reliably informed staff of oxygen level thresholds, enabling timely interventions. The proposed IoT-based smart monitoring system is a cost-effective and efficient solution for improving safety in medical environments.
| S-EPMC11761048 | biostudies-literature
Project description:The COVID-19 pandemic has triggered instabilities in various aspects of daily life. This includes economic, social, financial, and health crisis. In addition, the COVID-19 pandemic with the evolution of different virus strains such as delta and omicron has led to frequent global lockdowns. These lockdowns have caused disruption of trade activities that in turn have led to the shortage of medical supplies, especially personal protective equipment's (PPE's). Health-care workers (HCW's) have been at the forefront of the fight against this pandemic and are responsible for saving millions of lives worldwide. However, the PPE's available to HCW's in the form of face shields and face masks only provide face and eye protection without encapsulating the ability to continuously monitor vital COVID-19 parameters including body temperature, heart rate, and SpO2. Hence, in this study, we propose the design and utilization of a PPE in the form of smart face shield. The device has been integrated with the MAX30102 sensor for measuring the heart rate and oxygen saturation (SpO2) and the DS18B20 body temperature measuring sensor. The readings of these sensors are analyzed by a NodeMCU ESP8266 and measurements are displayed on a laptop screen. Also, the Wi-Fi module of NodeMCU ESP8266 enables compatibility with the ThingSpeak mobile application and permits HCW's and patients recovering from COVID-19 to keep a track of their physiological parameters. Overall, this PPE has been observed to provide reliable readings and the results indicate that the designed prototype can be used for monitoring COVID-19 essential parameters.
| S-EPMC9527148 | biostudies-literature
Project description:ObjectivesThe COVID-19 pandemic has led to a change in people's volunteering behaviours; participation has increased in informal volunteering (giving unpaid help to those who are not a relative) while decreasing in formal volunteering (unpaid help to groups or clubs). There is an interest from stakeholders who have experienced increased participation in maintaining the positive patterns of volunteering, aligning with National Health Service (NHS) objectives and realising benefits in a wider public health context. This research uses a local COVID-19 public health volunteering programme case study to explore the volunteer's journey and perspective using volunteers' reported experiences to consider the potential for volunteer retention and role expansion into other public health issues beyond the COVID-19 pandemic.MethodsRecruitment was undertaken by Birmingham City Council Public Health Team via the COVID-19 Community Champions programme mailing list. Semi-structured focus group discussions, one-to-one interviews and email interviews were conducted with volunteers. Data were analysed through directed thematic analysis using an iteratively developed coding frame.ResultsData were collected from three focus group discussions, four interviews, and one email interview involving a total of 16 participants. Six themes were identified: volunteer motivations and expectations; volunteer management; programme organisation; feeling valued; continued need for role, and interest in new responsibilities.ConclusionOur findings indicate that the factors which are conducive to volunteer recruitment, retention and re-purposing were: maintaining the original terms of engaging with the volunteering opportunity (including retaining the original brief and remit), adjusting these through consultative processes with an emphasis on seeking permission from the volunteers already involved and ensuring a reliable and consistent management and support structure. While some of the learning is specific to the local volunteer programme in question and the context of the COVID-19 pandemic, there are lessons that can be generalised to other scenarios and settings.
| S-EPMC10642819 | biostudies-literature
Project description:COVID-19 Health Surveillance FVG
| PRJEB46661 | ENA
Project description:Following the April 16, 2020 release of the Opening Up America Again guidelines for relaxing coronavirus disease 2019 (COVID-19) social distancing policies, local leaders are concerned about future pandemic waves and lack robust strategies for tracking and suppressing transmission. Here, we present a strategy for triggering short-term shelter-in-place orders when hospital admissions surpass a threshold. We use stochastic optimization to derive triggers that ensure hospital surges will not exceed local capacity and lockdowns are as short as possible. For example, Austin, Texas-the fastest-growing large city in the United States-has adopted a COVID-19 response strategy based on this method. Assuming that the relaxation of social distancing increases the risk of infection sixfold, the optimal strategy will trigger a total of 135 d (90% prediction interval: 126 d to 141 d) of sheltering, allow schools to open in the fall, and result in an expected 2,929 deaths (90% prediction interval: 2,837 to 3,026) by September 2021, which is 29% of the annual mortality rate. In the months ahead, policy makers are likely to face difficult choices, and the extent of public restraint and cocooning of vulnerable populations may save or cost thousands of lives.
| S-EPMC7443931 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic challenges societies in unknown ways, and individuals experience a substantial change in their daily lives and activities. Our study aims to describe these changes using population-based self-reported data about social and health behavior in a random sample of the Swiss population during the COVID-19 pandemic. The aim of the present article is two-fold: First, we want to describe the study methodology. Second, we want to report participant characteristics and study findings of the first survey wave to provide some baseline results for our study.MethodsOur study design is a longitudinal online panel of a random sample of the Swiss population. We measure outcome indicators covering general well-being, physical and mental health, social support, healthcare use and working state over multiple survey waves.ResultsFrom 8,174 contacted individuals, 2,026 individuals participated in the first survey wave which corresponds to a response rate of 24.8%. Most survey participants reported a good to very good general life satisfaction (93.3%). 41.4% of the participants reported a worsened quality of life compared to before the COVID-19 emergency and 9.8% feelings of loneliness.DiscussionThe COVID-19 Social Monitor is a population-based online survey which informs the public, health authorities, and the scientific community about relevant aspects and potential changes in social and health behavior during the COVID-19 emergency and beyond. Future research will follow up on the described study population focusing on COVID-19 relevant topics such as subgroup differences in the impact of the pandemic on well-being and quality of life or different dynamics of perceived psychological distress.
| S-EPMC7657546 | biostudies-literature
Project description:ObjectiveThis study investigates the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission potential in North Dakota, South Dakota, Montana, Wyoming, and Idaho from March 2020 through January 2021.MethodsTime-varying reproduction numbers, R t , of a 7-d-sliding-window and of non-overlapping-windows between policy changes were estimated using the instantaneous reproduction number method. Linear regression was performed to evaluate if per-capita cumulative case-count varied across counties with different population size or density.ResultsThe median 7-d-sliding-window R t estimates across the studied region varied between 1 and 1.25 during September through November 2020. Between November 13 and 18, R t was reduced by 14.71% (95% credible interval, CrI, [14.41%, 14.99%]) in North Dakota following a mask mandate; Idaho saw a 1.93% (95% CrI [1.87%, 1.99%]) reduction and Montana saw a 9.63% (95% CrI [9.26%, 9.98%]) reduction following the tightening of restrictions. High-population and high-density counties had higher per-capita cumulative case-count in North Dakota on June 30, August 31, October 31, and December 31, 2020. In Idaho, North Dakota, South Dakota, and Wyoming, there were positive correlations between population size and per-capita weekly incident case-count, adjusted for calendar time and social vulnerability index variables.ConclusionsR t decreased after mask mandate during the region's case-count spike suggested reduction in SARS-CoV-2 transmission.
| S-EPMC9794457 | biostudies-literature
Project description:The 2019 novel coronavirus disease emerged in China in late 2019-early 2020 and spread rapidly. China has been implementing emergency psychological crisis interventions to reduce the negative psychosocial impact on public mental health, but challenges exist. Public mental health interventions should be formally integrated into public health preparedness and emergency response plans.
| S-EPMC7323564 | biostudies-literature