scholarly journals How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Konstantin D. Pandl ◽  
Scott Thiebes ◽  
Manuel Schmidt-Kraepelin ◽  
Ali Sunyaev

AbstractTo combat the COVID-19 pandemic, many countries around the globe have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective technology for contact tracing.

2020 ◽  
Author(s):  
Konstantin D. Pandl ◽  
Scott Thiebes ◽  
Manuel Schmidt-Kraepelin ◽  
Ali Sunyaev

AbstractTo combat the COVID-19 pandemic, many countries have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective option in its current setting.


2020 ◽  
Author(s):  
Adam Fowler

AbstractMobile contact tracing apps have been developed by many countries in response to the COVID-19 pandemic. Trials have focussed on unobserved population trials or staged scenarios aimed to simulate real life. No efficacy measure has been developed that assesses the fundamental ability of any proximity detection protocol to accurately detect, measure, and therefore assess the epidemiological risk that a mobile phone owner has been placed at. This paper provides a fair efficacy formula that can be applied to any mobile contact tracing app, using any technology, allowing it’s likely epidemiological effectiveness to be assessed. This paper defines such a formula and provides results for several simulated protocols as well as one real life protocol tested according to the standard methodology set out in this paper. The results presented show that protocols that use time windows greater than 30 seconds or that bucket their distance analogue (E.g. RSSI for Bluetooth) provide poor estimates of risk, showing an efficacy rating of less than 6%. The fair efficacy formula is shown in this paper to be able to be used to calculate the ‘Efficacy of contact tracing’ variable value as used in two papers on using mobile applications for contact tracing [6]. The output from the formulae in this paper, therefore, can be used to directly assess the impact of technology on the spread of a disease outbreak. This formula can be used by nations developing contact tracing applications to assess the efficacy of their applications. This will allow them to reassure their populations and increase the uptake of contact tracing mobile apps, hopefully having an effect on slowing the spread of COVID-19 and future epidemics.


Author(s):  
Nick Wilson ◽  
Michael G Baker ◽  
Martin Eichner

AbstractAimsWe aimed to estimate the risk of COVID-19 outbreaks associated with air travel from a country with a very low prevalence of COVID-19 infection (Australia) to a COVID-19-free country (New Zealand; [NZ]), along with the likely impact of various control measures for passengers and cabin crew.MethodsA stochastic version of the SEIR model CovidSIM v1.1, designed specifically for COVID-19 was utilized. It was populated with data for both countries and parameters for SARS-CoV-2 transmission and control measures. We assumed one Australia to NZ flight per day.ResultsWhen no interventions were in place, an outbreak of COVID-19 in NZ was estimated to occur after an average time of 1.7 years (95% uncertainty interval [UI]: 0.04-6.09). However, the combined use of exit and entry screening (symptom questionnaire and thermal camera), masks on aircraft and two PCR tests (on days 3 and 12 in NZ), combined with self-reporting of symptoms and contact tracing and mask use until the second PCR test, reduced this risk to one outbreak every 29.8 years (0.8 to 110). If no PCR testing was performed, but mask use was used by passengers up to day 15 in NZ, the risk was one outbreak every 14.1 years. However, 14 days quarantine (NZ practice in May 2020), was the most effective strategy at one outbreak every 34.1 years (0.06 to 125); albeit combined with exit screening and mask use on flights.ConclusionsPolicy-makers can require multi-layered interventions to markedly reduce the risk of importing the pandemic virus into a COVID-19-free nation via air travel. There is potential to replace 14-day quarantine with PCR testing or interventions involving mask use by passengers in NZ. However, all approaches require continuous careful management and evaluation.


Author(s):  
Richard O. J. H. Stutt ◽  
Renata Retkute ◽  
Michael Bradley ◽  
Christopher A. Gilligan ◽  
John Colvin

COVID-19 is characterized by an infectious pre-symptomatic period, when newly infected individuals can unwittingly infect others. We are interested in what benefits facemasks could offer as a non-pharmaceutical intervention, especially in the settings where high-technology interventions, such as contact tracing using mobile apps or rapid case detection via molecular tests, are not sustainable. Here, we report the results of two mathematical models and show that facemask use by the public could make a major contribution to reducing the impact of the COVID-19 pandemic. Our intention is to provide a simple modelling framework to examine the dynamics of COVID-19 epidemics when facemasks are worn by the public, with or without imposed ‘lock-down’ periods. Our results are illustrated for a number of plausible values for parameter ranges describing epidemiological processes and mechanistic properties of facemasks, in the absence of current measurements for these values. We show that, when facemasks are used by the public all the time (not just from when symptoms first appear), the effective reproduction number, R e , can be decreased below 1, leading to the mitigation of epidemic spread. Under certain conditions, when lock-down periods are implemented in combination with 100% facemask use, there is vastly less disease spread, secondary and tertiary waves are flattened and the epidemic is brought under control. The effect occurs even when it is assumed that facemasks are only 50% effective at capturing exhaled virus inoculum with an equal or lower efficiency on inhalation. Facemask use by the public has been suggested to be ineffective because wearers may touch their faces more often, thus increasing the probability of contracting COVID-19. For completeness, our models show that facemask adoption provides population-level benefits, even in circumstances where wearers are placed at increased risk. At the time of writing, facemask use by the public has not been recommended in many countries, but a recommendation for wearing face-coverings has just been announced for Scotland. Even if facemask use began after the start of the first lock-down period, our results show that benefits could still accrue by reducing the risk of the occurrence of further COVID-19 waves. We examine the effects of different rates of facemask adoption without lock-down periods and show that, even at lower levels of adoption, benefits accrue to the facemask wearers. These analyses may explain why some countries, where adoption of facemask use by the public is around 100%, have experienced significantly lower rates of COVID-19 spread and associated deaths. We conclude that facemask use by the public, when used in combination with physical distancing or periods of lock-down, may provide an acceptable way of managing the COVID-19 pandemic and re-opening economic activity. These results are relevant to the developed as well as the developing world, where large numbers of people are resource poor, but fabrication of home-made, effective facemasks is possible. A key message from our analyses to aid the widespread adoption of facemasks would be: ‘my mask protects you, your mask protects me’.


Author(s):  
Gary W. Anderson ◽  
Anthony Breitzman

The National Institute of Standards and Technology’s (NIST’s) mission is to “promote U.S. innovation and industrial competitiveness.” To meet this mission, NIST scientists produce a great variety of scientific and technical outputs. This paper presents results from a novel effort to measure usage and impact of a more complete set of outputs, including patents, publications, research data, software, reference materials, and a variety of additional formal and informal scientific outputs. This effort captures a significantly broader set of scientific outputs than traditional citation analysis which typically examines patent-to-patent citations or more recently patent-to-(peer-reviewed) paper citations. This may be of significant importance to NIST as NIST scientists produce a wide variety of scientific and technical outputs beyond patents and papers. Our results indicate that metrics that solely rely on patents issued to NIST inventors understate NIST’s true impact on invention and do not capture usage of much of NIST’s scientific output by other inventors. Thus, identifying the magnitude and varied usage of different types of NIST outputs represents a significant improvement in NIST impact metrics. The results clearly indicate that different companies, industries and technologies rely on different types of NIST outputs. Therefore, reliance on a limited set of technology transfer tools by either researchers or policy makers creates a risk that NIST knowledge and capabilities will not be transferred to and adopted by businesses and other organizations. Finally, the data developed here suggest a number of new technology transfer metrics that promote shared technology transfer responsibilities and may focus attention on activities that increase the impact of current research without fundamentally altering the infrastructural character of this research.


2019 ◽  
Vol 28 (1) ◽  
pp. 2-6
Author(s):  
Nigel Edwards

Purpose The purpose of this paper is to provide a summary of some of the lessons about implementing different types of integrated care. Design/methodology/approach The author used evidence from the author’s own evaluations and the findings of other researchers to identify some important lessons for policy makers and practitioners. Findings The author identifies eight high-level lessons which may be of interest to policy makers and practitioners working in the field. Research limitations/implications The lessons outlined in the paper provide only a starting point for those designing interventions or evaluation. Practical implications The changes required to implement integrated care are complex and are embedded in a complex context. Change of this type is difficult and generally takes longer to deliver than expected. The evaluation of these models often requires longer than is often available and needs to focus on the impact on the whole system rather than narrow measures, e.g. hospital utilisation. Originality/value This is a viewpoint paper synthesising evidence from the English pilot programmes in integrated care.


2020 ◽  
pp. 0958305X2093768
Author(s):  
Jun Wen ◽  
Xinxin Zhao ◽  
Quan-Jing Wang ◽  
Chun-Ping Chang

This study first investigates different types of sanctions on energy security by employing data from a panel of target countries covering the period 1996–2014 and using the panel fixed effect model. Our evidence indicates that international sanctions do significantly negatively influence the energy security of target countries in some cases. Specifically, unilateral sanctions, U.S. sanctions, economic sanctions, and the intensity of sanctions have a significantly negative impact on energy security. However, plurilateral sanctions, EU sanctions, UN sanctions, and non-economic sanctions have no significant impact on the energy security of target countries. The results of endogeneity concerns are also consistent with the results of the basic regression analysis. Overall, our empirical findings merit particular attention from policy makers of target countries to ensure their energy security when facing international sanctions.


2021 ◽  
Vol 47 (78) ◽  
pp. 297-299
Author(s):  
Robert Ladouceur ◽  
Howard Shaffer ◽  
Paige Shaffer ◽  
Lucie Baillargeon

As people around the world experience a devastating pandemic, it is critical that policy-makers consider the methodological and measurement issues that might be associated with coronavirus disease 2019 (COVID-19) public health indicators. This commentary uses four primary variables to illustrate measurement and methodological issues that can complicate comparisons between jurisdictions. Jurisdiction refers to a variety of geographic areas, such as a country, a state, or a province/territory. These variables play a critical role in determining how we understand the trajectory of disease spread. These variables also contribute to our understanding of prevention strategies and their associated efficacy, reflecting the impact of COVID-19 on hospitals. It is critical for public health stakeholders and the public to recognize that these four simple variables can vary substantially across jurisdictions.


2021 ◽  
Vol 17 (6) ◽  
pp. e1009058
Author(s):  
Edward M. Hill ◽  
Benjamin D. Atkins ◽  
Matt J. Keeling ◽  
Louise Dyson ◽  
Michael J. Tildesley

As part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated. We use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create ‘COVID-secure’ workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics. The progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels. In the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread.


2020 ◽  
Author(s):  
Tyler M Yasaka ◽  
Brandon M Lehrich ◽  
Ronald Sahyouni

BACKGROUND The novel coronavirus disease 2019 (COVID-19) pandemic is an urgent public health crisis, with epidemiologic models predicting severe consequences, including high death rates, if the virus is permitted to run its course without any intervention or response. Contact tracing using smartphone technology is a powerful tool that may be employed to limit disease transmission during an epidemic or pandemic; yet, contact tracing apps present significant privacy concerns regarding the collection of personal data such as location. OBJECTIVE The aim of this study is to develop an effective contact tracing smartphone app that respects user privacy by not collecting location information or other personal data. METHODS We propose the use of an anonymized graph of interpersonal interactions to conduct a novel form of contact tracing and have developed a proof-of-concept smartphone app that implements this approach. Additionally, we developed a computer simulation model that demonstrates the impact of our proposal on epidemic or pandemic outbreak trajectories across multiple rates of adoption. RESULTS Our proof-of-concept smartphone app allows users to create “checkpoints” for contact tracing, check their risk level based on their past interactions, and anonymously self-report a positive status to their peer network. Our simulation results suggest that higher adoption rates of such an app may result in a better controlled epidemic or pandemic outbreak. CONCLUSIONS Our proposed smartphone-based contact tracing method presents a novel solution that preserves privacy while demonstrating the potential to suppress an epidemic or pandemic outbreak. This app could potentially be applied to the current COVID-19 pandemic as well as other epidemics or pandemics in the future to achieve a middle ground between drastic isolation measures and unmitigated disease spread.


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