scholarly journals A modelling framework to assess the likely effectiveness of facemasks in combination with ‘lock-down’ in managing the COVID-19 pandemic

2020 ◽  
Vol 476 (2238) ◽  
pp. 20200376 ◽  
Author(s):  
Richard O. J. H. Stutt ◽  
Renata Retkute ◽  
Michael Bradley ◽  
Christopher A. Gilligan ◽  
John Colvin
Keyword(s):  
Mobile Apps ◽  
Population Level ◽  
Disease Spread ◽  
Contact Tracing ◽  
Lower Efficiency ◽  
The Public ◽  
Molecular Tests ◽  
Modelling Framework ◽  
Increased Risk ◽  
The Impact

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’.

scholarly journals What do users think of the UK’s three COVID-19 contact-tracing apps? A comparative analysis

2021 ◽  
Vol 28 (1) ◽  
pp. e100320
Author(s):  
Vahid Garousi ◽  
David Cutting
Keyword(s):  
Mobile Apps ◽  
Analysis Data ◽  
End Users ◽  
Contact Tracing ◽  
User Reviews ◽  
The Public ◽  
Engineering Teams ◽  
Technical Issues ◽  
The Uk ◽  
The Right

ObjectivesOur goal was to gain insights into the user reviews of the three COVID-19 contact-tracing mobile apps, developed for the different regions of the UK: ‘NHS COVID-19’ for England and Wales, ‘StopCOVID NI’ for Northern Ireland and ‘Protect Scotland’ for Scotland. Our two research questions are (1) what are the users’ experience and satisfaction levels with the three apps? and (2) what are the main issues (problems) that users have reported about the apps?MethodsWe assess the popularity of the apps and end users’ perceptions based on user reviews in app stores. We conduct three types of analysis (data mining, sentiment analysis and topic modelling) to derive insights from the combined set of 25 583 user reviews of the aforementioned three apps (submitted by users until the end of 2020).ResultsResults show that end users have been generally dissatisfied with the apps under study, except the Scottish app. Some of the major issues that users have reported are high battery drainage and doubts on whether apps are really working.DiscussionTowards the end of 2020, the much-awaited COVID-19 vaccines started to be available, but still, analysing the users’ feedback and technical issues of these apps, in retrospective, is valuable to learn the right lessons to be ready for similar circumstances in future.ConclusionOur results show that more work is needed by the stakeholders behind the apps (eg, apps’ software engineering teams, public-health experts and decision makers) to improve the software quality and, as a result, the public adoption of these apps. For example, they should be designed to be as simple as possible to operate (need for usability).

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
Keyword(s):  
Disease Spread ◽  
Contact Tracing ◽  
Behavioral Characteristics ◽  
Policy Makers ◽  
Detection Range ◽  
Proximity Detection ◽  
Effective Technology ◽  
Different Types ◽  
Effectiveness And Efficiency ◽  
The Impact

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.

scholarly journals 368. Clinical Characteristics of Hospitalized COVID-19 American Indian Patients in Rural Arizona

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S253-S254
Author(s):  
Amy Nham ◽  
Ryan M Close
Keyword(s):  
American Indians ◽  
Median Number ◽  
Clinic Visit ◽  
Contact Tracing ◽  
Shortness Of Breath ◽  
Early Referral ◽  
Increased Risk ◽  
Wbc Count ◽  
The Impact ◽  
D Dimer

Abstract Background American Indians have an increased risk of serious complications from COVID-19 due to the high prevalence of comorbidities such as diabetes, heart disease, obesity, and asthma. To date, there has been limited analysis of COVID-19 in the AI population. This study describes the characteristics of hospitalized COVID-19 patients from a well-defined AI population in eastern Arizona. Additionally, we explored the impact of early referral via contact tracing versus those who self-presented. Methods Retrospective chart reviews were completed for patients hospitalized for COVID from March 29 to May 16, 2020. Summary statistics were used to describe demographics, symptoms, pre-existing conditions, and hospitalization data. Results We observed 447 laboratory-confirmed cases of COVID-19, resulting in 71 (15.9%) hospitalizations over a 7-week period and a hospitalization rate of 159 per 1,000 persons. Of the 50 hospitalizations reviewed sequentially, 56% were female, median age of 55 (IQR 44–65). Median number of days hospitalized was 4 (2–6), with 16% requiring intensive care unit support, 15% intubated, 12% readmitted, and 10% deceased. 67% had an epidemiological link, and 32% had an emergency department or outpatient clinic visit within 7 days of hospitalization. All patients were symptomatic; the most common symptoms were cough (90%), shortness of breath (78%), and subjective fever (66%). 86% of patients had a pre-existing condition; the most common pre-existing conditions were diabetes (66%), obesity (58%), and hypertension (52%, Figure 1). All patients had elevated LDH, 94% had elevated CRP, 86% had elevated d-dimer, and 40% had lymphopenia; only 10% had an elevated WBC count and 26% had thrombocytopenia (Table 1). 26% of the patients were referred in by the tracing team (Table 2). Analysis of 500 hospitalizations will be available in October 2020. Conclusion Most AI patients hospitalized had a pre-existing condition, symptoms of cough or shortness of breath, and elevated LDH, CRP, and d-dimer. More research is needed to understand the patterns of COVID-19 related disease in vulnerable populations, like AI/AN, and to examine the utility of early referral by contact tracing teams in rural settings which may guide future tracing strategies. Disclosures All Authors: No reported disclosures

scholarly journals Efficacy of contact tracing for the containment of the 2019 novel coronavirus (COVID-19)

2020 ◽  
pp. jech-2020-214051 ◽  
Author(s):  
Matt J Keeling ◽  
T Deirdre Hollingsworth ◽  
Jonathan M Read
Keyword(s):  
Close Contact ◽  
Control Measure ◽  
Disease Outbreaks ◽  
Contact Tracing ◽  
Public Health Response ◽  
Central Public Health ◽  
Increased Risk ◽  
Novel Coronavirus ◽  
The Uk ◽  
The Impact

ObjectiveContact tracing is a central public health response to infectious disease outbreaks, especially in the early stages of an outbreak when specific treatments are limited. Importation of novel coronavirus (COVID-19) from China and elsewhere into the UK highlights the need to understand the impact of contact tracing as a control measure.DesignDetailed survey information on social encounters from over 5800 respondents is coupled to predictive models of contact tracing and control. This is used to investigate the likely efficacy of contact tracing and the distribution of secondary cases that may go untraced.ResultsTaking recent estimates for COVID-19 transmission we predict that under effective contact tracing less than 1 in 6 cases will generate any subsequent untraced infections, although this comes at a high logistical burden with an average of 36 individuals traced per case. Changes to the definition of a close contact can reduce this burden, but with increased risk of untraced cases; we find that tracing using a contact definition requiring more than 4 hours of contact is unlikely to control spread.ConclusionsThe current contact tracing strategy within the UK is likely to identify a sufficient proportion of infected individuals such that subsequent spread could be prevented, although the ultimate success will depend on the rapid detection of cases and isolation of contacts. Given the burden of tracing a large number of contacts to find new cases, there is the potential the system could be overwhelmed if imports of infection occur at a rapid rate.

Pluvial flood catastrophe modelling: a trans-disciplinary approach.

2020 ◽  
Author(s):  
Konstantinos Karagiorgos ◽  
Daniel Knos ◽  
Jan Haas ◽  
Sven Halldin ◽  
Barbara Blumenthal ◽  
...  
Keyword(s):  
Risk Management ◽  
Flood Risk ◽  
Urban Areas ◽  
Insurance Industry ◽  
Integrated Approach ◽  
Effective Prevention ◽  
The Public ◽  
Modelling Framework ◽  
Catastrophe Modelling ◽  
The Impact

<p>Pluvial floods are one of the most significant natural hazards in Europe causing severe damage to urban areas. Following the projected increase in extreme precipitation and the ongoing urbanization, these events play an important role in the ongoing flood risk management discussion and provoke serious risk to the public as well as to the insurance sector. However, this type of flood, remains a poorly documented phenomenon. To address this gap, Swedish Pluvial Modelling Analysis and Safety Handling (SPLASH) project aims to develop new methods and types of data that improve the possibility to value flood risk in Swedish municipalities by collaboration between different disciplines.</p><p>SPLASH project allows to investigating the impact of heavy precipitation along the entire risk modelling chain, ultimate needed for effective prevention. This study presents a pluvial flood catastrophe modelling framework to identify and assess hazard, exposure and vulnerability in urban context. An integrated approach is adopted by incorporating ‘rainfall-damage’ patterns, flood inundation modelling, vulnerability tools and risk management. The project is developed in the ‘OASIS Loss Modelling Framework’ platform, jointly with end-users from the public sector and the insurance industry.</p><p>The Swedish case study indicates that the framework presented can be considered as an important decision making tool, by establishing an area for collaboration between academia; insurance businesses and rescue services, to reduce long-term disaster risk in Sweden.</p>

scholarly journals A fair efficacy formula for assessing the effectiveness of contact tracing applications

2020 ◽  
Author(s):  
Adam Fowler
Keyword(s):  
Mobile Applications ◽  
Mobile Apps ◽  
Time Windows ◽  
Real Life ◽  
Contact Tracing ◽  
Proximity Detection ◽  
Epidemiological Risk ◽  
Efficacy Measure ◽  
Impact Of Technology ◽  
The Impact

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.

scholarly journals Protective impacts of household-based tuberculosis contact tracing are robust across endemic incidence levels and community contact patterns

2021 ◽  
Vol 17 (2) ◽  
pp. e1008713 ◽  
Author(s):  
Joshua Havumaki ◽  
Ted Cohen ◽  
Chengwei Zhai ◽  
Joel C. Miller ◽  
Seth D. Guikema ◽  
...  
Keyword(s):  
Population Level ◽  
Contact Tracing ◽  
Spatially Explicit Model ◽  
Household Transmission ◽  
Contact Patterns ◽  
Social Mixing ◽  
High Incidence ◽  
Community Transmission ◽  
The Impact ◽  
The Relationship

There is an emerging consensus that achieving global tuberculosis control targets will require more proactive case finding approaches than are currently used in high-incidence settings. Household contact tracing (HHCT), for which households of newly diagnosed cases are actively screened for additional infected individuals is a potentially efficient approach to finding new cases of tuberculosis, however randomized trials assessing the population-level effects of such interventions in settings with sustained community transmission have shown mixed results. One potential explanation for this is that household transmission is responsible for a variable proportion of population-level tuberculosis burden between settings. For example, transmission is more likely to occur in households in settings with a lower tuberculosis burden and where individuals mix preferentially in local areas, compared with settings with higher disease burden and more dispersed mixing. To better understand the relationship between endemic incidence levels, social mixing, and the impact of HHCT, we developed a spatially explicit model of coupled household and community transmission. We found that the impact of HHCT was robust across settings of varied incidence and community contact patterns. In contrast, we found that the effects of community contact tracing interventions were sensitive to community contact patterns. Our results suggest that the protective benefits of HHCT are robust and the benefits of this intervention are likely to be maintained across epidemiological settings.

scholarly journals It's Not the Flu: Popular Perceptions of the Impact of COVID-19 in the U.S.

2021 ◽  
Vol 12 ◽  
Author(s):  
Laura Niemi ◽  
Kevin M. Kniffin ◽  
John M. Doris
Keyword(s):  
Causes Of Death ◽  
Severe Disease ◽  
Moral Values ◽  
Health Impacts ◽  
Contact Tracing ◽  
Automobile Accidents ◽  
The Public ◽  
Seasonal Flu ◽  
The Impact ◽  
Testing Protocols

Messaging from U.S. authorities about COVID-19 has been widely divergent. This research aims to clarify popular perceptions of the COVID-19 threat and its effects on victims. In four studies with over 4,100 U.S. participants, we consistently found that people perceive the threat of COVID-19 to be substantially greater than that of several other causes of death to which it has recently been compared, including the seasonal flu and automobile accidents. Participants were less willing to help COVID-19 victims, who they considered riskier to help, more contaminated, and more responsible for their condition. Additionally, politics and demographic factors predicted attitudes about victims of COVID-19 above and beyond moral values; whereas attitudes about the other kinds of victims were primarily predicted by moral values. The results indicate that people perceive COVID-19 as an exceptionally severe disease threat, and despite prosocial inclinations, do not feel safe offering assistance to COVID-19 sufferers. This research has urgent applied significance: the findings are relevant to public health efforts and related marketing campaigns working to address extended damage to society and the economy from the pandemic. In particular, efforts to educate the public about the health impacts of COVID-19, encourage compliance with testing protocols and contact tracing, and support safe, prosocial decision-making and risk assessment, will all benefit from awareness of these findings. The results also suggest approaches, such as engaging people's stable values rather than their politicized perspectives on COVID-19, that may reduce stigma and promote cooperation in response to pandemic threats.

scholarly journals Impact of contact tracing on COVID-19 mortality: An impact evaluation using surveillance data from Colombia

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0246987
Author(s):  
Andres I. Vecino-Ortiz ◽  
Juliana Villanueva Congote ◽  
Silvana Zapata Bedoya ◽  
Zulma M. Cucunuba
Keyword(s):  
Fixed Effects ◽  
Contact Tracing ◽  
Supply Side ◽  
Fixed Effects Model ◽  
Surveillance Strategy ◽  
Middle Income ◽  
The Public ◽  
Middle Income Countries ◽  
The Impact ◽  
Crucial Part

Background Contact tracing is a crucial part of the public health surveillance toolkit. However, it is labor-intensive and costly to carry it out. Some countries have faced challenges implementing contact tracing, and no impact evaluations using empirical data have assessed its impact on COVID-19 mortality. This study assesses the impact of contact tracing in a middle-income country, providing data to support the expansion and optimization of contact tracing strategies to improve infection control. Methods We obtained publicly available data on all confirmed COVID-19 cases in Colombia between March 2 and June 16, 2020. (N = 54,931 cases over 135 days of observation). As suggested by WHO guidelines, we proxied contact tracing performance as the proportion of cases identified through contact tracing out of all cases identified. We calculated the daily proportion of cases identified through contact tracing across 37 geographical units (32 departments and five districts). Further, we used a sequential log-log fixed-effects model to estimate the 21-days, 28-days, 42-days, and 56-days lagged impact of the proportion of cases identified through contact tracing on daily COVID-19 mortality. Both the proportion of cases identified through contact tracing and the daily number of COVID-19 deaths are smoothed using 7-day moving averages. Models control for the prevalence of active cases, second-degree polynomials, and mobility indices. Robustness checks to include supply-side variables were performed. Results We found that a 10 percent increase in the proportion of cases identified through contact tracing is related to COVID-19 mortality reductions between 0.8% and 3.4%. Our models explain between 47%-70% of the variance in mortality. Results are robust to changes of specification and inclusion of supply-side variables. Conclusion Contact tracing is instrumental in containing infectious diseases. Its prioritization as a surveillance strategy will substantially impact reducing deaths while minimizing the impact on the fragile economic systems of lower and middle-income countries. This study provides lessons for other LMIC.

An Exploration of Resilience and Values in the Co-Design of Sociotechnical Systems

2016 ◽  
Vol 3 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Balbir S. Barn ◽  
Ravinder Barn
Keyword(s):  
Information Systems ◽  
Mobile Apps ◽  
Systems Design ◽  
Systems Development ◽  
End User ◽  
Youth Justice ◽  
The Public ◽  
Reflection Model ◽  
The Uk ◽  
The Impact

The notion of resilience is becoming an important consideration in addressing the needs of vulnerable individuals and groups in the public sector. In Information Systems development, resilience has often been treated as a non-functional requirement such as scalability and little or no work has aimed at building resilience in end-users through systems development. Sociotechnical approaches while not specifically addressing resilience, have strived for a balance between technology and humans. While there are many variants of sociotechnical approaches, in this paper the authors introduce a refinement of the value sensitive action-reflection model used in co-design, first introduced by Yoo et al, that recognises the tension between values and resilience. The authors report on their activities of using this approach for a project aimed at developing mobile apps for promoting better engagement between young people in conflict with the law and their case workers in the UK youth justice system. They examine the ambiguity created when designer and stakeholder prompts change their role and purpose during the co-design process and discuss the impact of this on resilience building for the end-user and the possible implications for Information Systems design processes.

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