Pre-Emptive Low Cost Social Distancing and Enhanced Hygiene Implemented before Local COVID-19 Transmission Could Decrease the Number and Severity of Cases.

2020 ◽  
Author(s):  
Craig Dalton ◽  
Stephen Corbett ◽  
Anthea Katelaris
Keyword(s):  
Low Cost ◽  
Social Distancing

Low-Cost Social Distancing Alerting Wrist Band Device

2021 ◽  
Author(s):  
K S Souparnika ◽  
R Nehha Mariam ◽  
Sreya Jayan ◽  
Hridya Harikumar ◽  
Shruti ◽  
...  
Keyword(s):  
Low Cost ◽  
Social Distancing

Sustained reductions in online search interest for communicable eye and other conditions during the COVID-19 Pandemic: An Infodemiology Study (Preprint)

2021 ◽  
Author(s):  
Michael S. Deiner ◽  
Gerami D. Seitzman ◽  
Stephen D. McLeod ◽  
James Chodosh ◽  
Thomas M. Lietman ◽  
...  
Keyword(s):  
Large Scale ◽  
Communicable Disease ◽  
Low Cost ◽  
A Priori ◽  
Volume Data ◽  
Exact Tests ◽  
Online Search ◽  
P Values ◽  
Social Distancing ◽  
Wide Range

BACKGROUND At the start of the COVID 19 pandemic, we found reduced numbers of google searches for the term conjunctivitis. We hypothesized that physical distancing during COVID-10 reduced the spread of contagious eye disease. Here we test this hypothesis a year later, expanding to include other communicable conditions. OBJECTIVE Determine if reduction in USA searches for terms related to conjunctivitis and other common communicable diseases occurred in spring-winter of the COVID-19 pandemic, and compare this outcome to terms representing non-communicable conditions, COVID-19, and to seasonality. METHODS Weekly relative search frequency volume data from Google trends for 68 search terms in English for the USA, were obtained for the weeks of March 2011 through February 2021. Terms were classified a priori as 16 terms related to COVID-19, 29 terms representing communicable conditions and 23 terms representing control non-communicable conditions. To reduce bias, all analyses were conducted while masked to term names, classifications and locations. To test for the significance of changes during the pandemic, we detrended and compared post-pandemic values to that expected based on pre-pandemic trends, per season, computing 1 and 2 sided P-values. We then compared these P-values between term groups using Wilcoxon rank-sum and Fisher exact tests to assess if non-COVID terms representing communicable disease were more likely to show significant reductions in search in 2020-21 than terms not representing such disease. We also assessed any relationship between a term’s seasonality and reduced search for it in 2020-21 seasons. P-values were subjected to FDR correction prior to reporting. Data were then unmasked. RESULTS Terms representing conjunctivitis and other communicable conditions had sustained reduced search in the first 4 seasons of the 2020-2021 COVID-19 pandemic, compared to prior years. In comparison, search for non-communicable condition terms was significantly less reduced (Wilcoxon and Fisher’s Exact Tests, P < 0.001; summer, autumn, winter). A significant correlation was also found between reduced search for a term in 2020-21 and seasonality of that term (Theil-Sen, P < 0.001; summer, autumn, winter). COVID-19 related conditions were significantly elevated compared to prior years, and influenza-related terms were significantly lower than prior years in winter 2020-21 (P < 0.0001). CONCLUSIONS We demonstrate the low-cost and unbiased use of online search data to study how a wide range of conditions may be affected by large-scale interventions or events such as social distancing during the COVID-19 pandemic. Our findings support emerging clinical evidence implicating social distancing and the COVID-19 pandemic in the reduction of communicable disease. They also agree with elevation of ocular conditions suggested to be linked to COVID-19 infection or behavioral changes such as mask-wearing. CLINICALTRIAL Not applicable

scholarly journals Modelling elevator traffic with social distancing in a university classroom building

2020 ◽  
Vol 42 (1) ◽  
pp. 82-97
Author(s):  
David Swinarski
Keyword(s):  
Low Cost ◽  
Discrete Event ◽  
Practical Application ◽  
Negative Effects ◽  
Social Distancing ◽  
Event Based

Social distancing standards implemented during the COVID-19 pandemic may have negative effects on vertical traffic. We describe a model and use it to predict the elevator traffic under social distancing in a university classroom building, and study the effects of four interventions aimed at improving this traffic. Discrete event-based simulation is used to study whether the lift group meets the forecasted demand when the car capacity is restricted far below its ordinary value to accommodate social distancing. Four low-cost interventions are simulated alone and in combination to quantify the improvements they offer. All four interventions show some improvement, and the combination of all four interventions gives the greatest improvement. Practical application: Implementing social distancing standards may disproportionately lower the car capacity relative to the building population and thus negatively affect vertical traffic. Building managers seeking to implement low-cost measures to improve elevator traffic under these conditions may look to the percentage improvements described here to aid them in selecting interventions appropriate to their buildings.

scholarly journals CIR-Based Device-Free People Counting via UWB Signals

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3296
Author(s):  
Mauro De Sanctis ◽  
Aleandro Conte ◽  
Tommaso Rossi ◽  
Simone Di Domenico ◽  
Ernestina Cianca
Keyword(s):  
Impulse Response ◽  
Low Cost ◽  
Singular Values ◽  
Low Complexity ◽  
Channel Impulse Response ◽  
Communication Signals ◽  
People Counting ◽  
Social Distancing ◽  
Crowd Density Estimation ◽  
Crowd Density

The outbreak of COVID-19 has resulted in many different policies being adopted across the world to reduce the spread of the virus. These policies include wearing surgical masks, hand hygiene practices, increased social distancing and full country-wide lockdown. Specifically, social distancing involves keeping a certain distance from others and avoiding gathering together in large groups. Automatic crowd density estimation is a technological solution that could help in guaranteeing social distancing by reducing the probability that two persons in a public area come in close proximity to each other while moving around. This paper proposes a novel low complexity RF sensing system for automatic people counting based on low cost UWB transceivers. The proposed system is based on an ordinary classifier that exploits features extracted from the channel impulse response of UWB communication signals. Specifically, features are extracted from the sorted list of singular values obtained from the singular value decomposition applied to the matrix of the channel impulse response vector differences. Experimental results achieved in two different environments show that the proposed system is a promising candidate for future automatic crowd density monitoring systems.

scholarly journals COVID-19 modeling and non-pharmaceutical interventions in an outpatient dialysis unit

2021 ◽  
Vol 17 (7) ◽  
pp. e1009177
Author(s):  
Hankyu Jang ◽  
Philip M. Polgreen ◽  
Alberto M. Segre ◽  
Sriram V. Pemmaraju
Keyword(s):  
Attack Rate ◽  
Low Cost ◽  
Substantial Reduction ◽  
Symptomatic Patient ◽  
Physical Distance ◽  
Healthcare Personnel ◽  
Worst Case ◽  
Dialysis Unit ◽  
Social Distancing ◽  
Pharmaceutical Interventions

This paper describes a data-driven simulation study that explores the relative impact of several low-cost and practical non-pharmaceutical interventions on the spread of COVID-19 in an outpatient hospital dialysis unit. The interventions considered include: (i) voluntary self-isolation of healthcare personnel (HCPs) with symptoms; (ii) a program of active syndromic surveillance and compulsory isolation of HCPs; (iii) the use of masks or respirators by patients and HCPs; (iv) improved social distancing among HCPs; (v) increased physical separation of dialysis stations; and (vi) patient isolation combined with preemptive isolation of exposed HCPs. Our simulations show that under conditions that existed prior to the COVID-19 outbreak, extremely high rates of COVID-19 infection can result in a dialysis unit. In simulations under worst-case modeling assumptions, a combination of relatively inexpensive interventions such as requiring surgical masks for everyone, encouraging social distancing between healthcare professionals (HCPs), slightly increasing the physical distance between dialysis stations, and—once the first symptomatic patient is detected—isolating that patient, replacing the HCP having had the most exposure to that patient, and relatively short-term use of N95 respirators by other HCPs can lead to a substantial reduction in both the attack rate and the likelihood of any spread beyond patient zero. For example, in a scenario with R0 = 3.0, 60% presymptomatic viral shedding, and a dialysis patient being the infection source, the attack rate falls from 87.8% at baseline to 34.6% with this intervention bundle. Furthermore, the likelihood of having no additional infections increases from 6.2% at baseline to 32.4% with this intervention bundle.

scholarly journals Design and Development of an Automated Monitored Hand Hygiene System to Curb Infection Spread in Institutional Settings during COVID-19 Pandemic

2020 ◽  
Author(s):  
Ashish Karn ◽  
Rithvik Kanchi ◽  
Shashank Singh Deo
Keyword(s):  
Hand Hygiene ◽  
Low Cost ◽  
Educational Interventions ◽  
Design And Development ◽  
Social Distancing ◽  
Institutional Settings ◽  
Current Scenario ◽  
Infection Spread

Considering the current scenario of Coronavirus outbreak and the post-pandemic situation, the need of a robust hand hygiene program assumes utmost importance, particularly in institutional settings such as education and healthcare. As different nations all across the globe lift the lockdown restrictions and as life springs back to normalcy, organizations, in order to quell the apprehensions and concerns of its workers, may have to institute newer paradigms to curb infection and generate awareness. Prior reported research shows that although an adequately designed health hygiene system may be helpful in curbing the infection spread, a major issue stems from the lack of adherence, by a section of individuals in any institution. In such a situation, it becomes absolutely imperative to track the compliance by different individuals, so that educational interventions may be targeted for the concerned group of workers. Further, currently, no low-cost compact systems exist that can provide for the hand hygiene requirements for a group of people, which are “touch-free”, automated and which are monitored. To bridge this gap, we propose the design and development of an automated monitored hand hygiene system to curb infection spread in institutional settings. It is designed in such a way that it would provide for hand sanitization of four people at a time per machine, simultaneously ensuring social distancing between them. The proposed product will not only reduce the apprehensions of the workers in an institutions by providing for solutions to curb infection spread, but will also be economical and aesthetically compact to be deployed at multiple locations within an organization, thus providing for a much safer workplace during the post-lockdown phase.

scholarly journals College campuses and COVID-19 mitigation: clinical and economic value

2020 ◽  
Author(s):  
Elena Losina ◽  
Valia Leifer ◽  
Lucia Millham ◽  
Christopher Panella ◽  
Emily P. Hyle ◽  
...  
Keyword(s):  
Low Cost ◽  
Economic Value ◽  
Cost Effective ◽  
Quality Adjusted Life Year ◽  
College Campuses ◽  
Mitigation Strategies ◽  
Routine Laboratory ◽  
Social Distancing ◽  
College And University ◽  
Quality Adjusted Life

Background: Decisions around US college and university operations will affect millions of students and faculty amidst the COVID-19 pandemic. We examined the clinical and economic value of different COVID-19 mitigation strategies on college campuses. Methods: We used the Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation that tracks infections accrued by students and faculty, accounting for community transmissions. Outcomes include infections, $/infection-prevented, and $/quality-adjusted-life-year ($/QALY). Strategies included extensive social distancing (ESD), masks, and routine laboratory tests (RLT). We report results per 5,000 students (1,000 faculty) over one semester (105 days). Results: Mitigation strategies reduced COVID-19 cases among students (faculty) from 3,746 (164) with no mitigation to 493 (28) with ESD and masks, and further to 151 (25) adding RLTq3 among asymptomatic students and faculty. ESD with masks cost $168/infection-prevented ($49,200/QALY) compared to masks alone. Adding RLTq3 ($10/test) cost $8,300/infection-prevented ($2,804,600/QALY). If tests cost $1, RLTq3 led to a favorable cost of $275/infection-prevented ($52,200/QALY). No strategies without masks were cost-effective. Conclusion: Extensive social distancing with mandatory mask-wearing could prevent 87% of COVID-19 cases on college campuses and be very cost-effective. Routine laboratory testing would prevent 96% of infections and require low cost tests to be economically attractive.

scholarly journals Suraksha: Low Cost Device to Maintain Social Distancing during CoVID-19

2020 ◽  
Author(s):  
Sashmita Raghav ◽  
Gayathri Vijay ◽  
Peddu Sai Harika ◽  
A Venkateswara Rao ◽  
Athira Gopinath ◽  
...  
Keyword(s):  
Low Cost ◽  
Social Distancing

scholarly journals SIMONIC: IoT Based Quarantine Monitoring System for Covid-19

2021 ◽  
Vol 21 (2) ◽  
pp. 112
Author(s):  
Vita Awalia Mardiana ◽  
Mochamad Mardi Martadinata ◽  
Galih Nugraha Nurkahfi ◽  
Arumjeni Mitayani ◽  
Dayat Kurniawan ◽  
...  
Keyword(s):  
Monitoring System ◽  
Negative Impact ◽  
Mobile Apps ◽  
Human Life ◽  
Low Cost ◽  
Low Complexity ◽  
Integrated System ◽  
Contact Tracing ◽  
Social Distancing ◽  
Set Up

COVID-19, which has become a global pandemic since March 2020, has tremendously affected human life globally. The negative impact of COVID-19 affects societies in almost all aspects. Implementing quarantine monitoring, also social distancing, and contact tracing are a series of processes that can suppress the new infected COVID-19 cases in various countries. Prior works have proposed different monitoring systems to assist the monitoring of individuals in quarantines, as well as many methods are offered for social distancing and contact tracing. These methods focus on one function to provide a reliable system. In this paper, we propose IoT-based quarantine monitoring by implementing a geofence equipped with social distancing features to offer an integrated system that provides more benefits than one system carrying one particular function. We propose a system consisting of a low cost, low complexity, and reusable wristband design and mobile apps to support the quarantine monitoring system. For the geofencing, we propose a GPS-based geofence system that was developed by taking advantage of the convenience offered by the Traccar application. Meanwhile, we add the notification for social distancing feature with adaptive distance measurement RSSI-based set up in the android application. Based on the experiment we did to validate the system, in terms of wristband-to-smartphone communication, scanning interval in smartphone and advertising interval in wristband is best to set in 7 s for both. For social distancing notification and geofence, we measure the system performance through precision, recall, accuracy, and F-measure.

scholarly journals Global projections of lives saved from COVID-19 with universal mask use

2020 ◽  
Keyword(s):  
Low Cost ◽  
Health Benefits ◽  
Health Impacts ◽  
Transmission Model ◽  
Reference Scenario ◽  
Economic Costs ◽  
Social Distancing ◽  
Time Period ◽  
Economic Downturns ◽  
The Difference

ABSTRACTBACKGROUNDSocial distancing mandates (SDM) have reduced health impacts from COVID-19 but also resulted in economic downturns that have led many nations to relax SDM. Until deployment of an efficacious and equitable vaccine, intervention options to reduce COVID-19 mortality and minimize restrictive SDM are sought by society.METHODSA susceptible-exposed-infectious-recovered (SEIR) deterministic transmission model was parameterized with data on reported deaths, cases, and select covariates to predict infections and deaths from COVID-19 through March 01, 2021. We explore three scenarios: a “non-adaptive” scenario where neither mask use or SDM adapt to changing conditions, a “reference” where current national levels of mask use are maintained and SDM reintroduced when deaths rise, and an increase in mask use to 95% coverage levels (“universal mask”). We reviewed published studies to set priors on the magnitude of reduction in transmission through increasing mask use.RESULTSMask use was estimated at 59.0% of people globally on October 19, 2020. Universal mask use could avert 733,310 deaths (95% UI 385,981 to 1,107,759) between October 27, 2020 and March 01, 2021, the difference between the predicted 2.95 million deaths (95% UI 2.70 to 3.35) in the reference scenario and 2.22 million deaths (95% UI 2.00 to 2.45) in the universal mask scenario over this time period.CONCLUSIONSThe cumulative toll of the COVID-19 pandemic could be substantially reduced by the universal adoption of masks before the availability of a vaccine. This low-cost, low-barrier policy, whether customary or mandated, has enormous health benefits with presumed marginal economic costs.

Sign in / Sign up

Export Citation Format

Share Document