scholarly journals Making Sense of Algorithms: Relational Perception of Contact Tracing and Risk Assessment during COVID-19

2020 ◽  
Author(s):  
Chuncheng Liu ◽  
Ross Graham
Keyword(s):  
Risk Assessment ◽  
Contact Tracing ◽  
Making Sense

scholarly journals Making sense of algorithms: Relational perception of contact tracing and risk assessment during COVID-19

2021 ◽  
Vol 8 (1) ◽  
pp. 205395172199521
Author(s):  
Chuncheng Liu ◽  
Ross Graham
Keyword(s):  
Public Health ◽  
Risk Assessment ◽  
Contact Tracing ◽  
Making Sense ◽  
Trade Offs ◽  
The Social ◽  
Citizen Data ◽  
Relational Interactions ◽  
Depth Interviews ◽  
Chinese Public

Governments and citizens of nearly every nation have been compelled to respond to COVID-19. Many measures have been adopted, including contact tracing and risk assessment algorithms, whereby citizen whereabouts are monitored to trace contact with other infectious individuals in order to generate a risk status via algorithmic evaluation. Based on 38 in-depth interviews, we investigate how people make sense of Health Code ( jiankangma), the Chinese contact tracing and risk assessment algorithmic sociotechnical assemblage. We probe how people accept or resist Health Code by examining their ongoing, dynamic, and relational interactions with it. Participants display a rich variety of attitudes toward privacy and surveillance, ranging from fatalism to the possibility of privacy to trade-offs for surveillance in exchange for public health, which is mediated by the perceived effectiveness of Health Code and changing views on the intentions of institutions who deploy it. We show how perceived competency varies not just on how well the technology works, but on the social and cultural enforcement of various non-technical aspects like quarantine, citizen data inputs, and cell reception. Furthermore, we illustrate how perceptions of Health Code are nested in people’s broader interpretations of disease control at the national and global level, and unexpectedly strengthen the Chinese authority’s legitimacy. None of the Chinese public, Health Code, or people’s perceptions toward Health Code are predetermined, fixed, or categorically consistent, but are co-constitutive and dynamic over time. We conclude with a theorization of a relational perception and methodological reflections to study algorithmic sociotechnical assemblages beyond COVID-19.

scholarly journals Making Sense of Algorithms: Relational Perception of Contact Tracing and Risk Assessment during COVID-19

2020 ◽  
Author(s):  
Chuncheng Liu ◽  
Ross Graham
Keyword(s):  
Risk Assessment ◽  
Social Life ◽  
Input Data ◽  
Contact Tracing ◽  
Individual Factors ◽  
Making Sense ◽  
Data Collection And Analysis ◽  
Key Sites ◽  
Relational Interactions ◽  
Over Time

Governments, institutions, and citizens of nearly every nation have been compelled to respond to COVID-19. Many measures have been adopted, including contact tracing and risk assessment, whereby citizen whereabouts are constantly monitored to trace contact with other infectious individuals and isolate contagious parties via algorithmic evaluation of their risk status. This paper investigates how citizens make sense of Health Code (jiankangma), the contact tracing and risk assessment algorithm in China. We probe how people accept or resist the algorithm by examining their ongoing, dynamic, and relational interactions with it over time. By seeking a deeper, iterative understanding of how individuals accept or resist the algorithm, our data unearths three key sites of concern. First, how understandings of algorithmic surveillance shape and are shaped by notions of privacy, including fatalism towards the possibility of true privacy in China and a trade-off narrative between privacy and twin imperatives of public and economic health. Second, how trust in the algorithm is mediated by the perceived competency of the technology, the veracity of input data, and well-publicized failures in both data collection and analysis. Third, how the implementation of Health Code in social life alters beliefs about the algorithm, such as its further role after COVID-19 passes, or contradictory and disorganized enforcement measures upon risk assessment. Chinese citizens make sense of Health Code in a relational fashion, whereby users respond very differently to the same sociotechnical assemblage based upon social and individual factors.

scholarly journals Two cases of imported respiratory diphtheria in Edinburgh, Scotland, October 2019

2020 ◽  
Vol 148 ◽  
Author(s):  
Lucy Li ◽  
Daniella Ross ◽  
Katherine Hill ◽  
Sarah Clifford ◽  
Louise Wellington ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Corynebacterium Diphtheriae ◽  
High Index ◽  
Contact Tracing ◽  
Emerging Infections ◽  
Diphtheria Antitoxin ◽  
History Of ◽  
Risk Areas ◽  
High Index Of Suspicion

Abstract We report two cases of respiratory toxigenic Corynebacterium diphtheriae infection in fully vaccinated UK born adults following travel to Tunisia in October 2019. Both patients were successfully treated with antibiotics and neither received diphtheria antitoxin. Contact tracing was performed following a risk assessment but no additional cases were identified. This report highlights the importance of maintaining a high index of suspicion for re-emerging infections in patients with a history of travel to high-risk areas outside Europe.

scholarly journals A Bayesian network model for personalised COVID19 risk assessment and contact tracing

2020 ◽  
Author(s):  
Norman E Fenton ◽  
Scott McLachlan ◽  
Peter Lucas ◽  
Kudakwashe Dube ◽  
Graham A Hitman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Bayesian Network ◽  
Social Interactions ◽  
Probabilistic Model ◽  
Personal Information ◽  
Contact Tracing ◽  
Smartphone App ◽  
Bayesian Network Model ◽  
The Uk

AbstractConcerns about the practicality and effectiveness of using Contact Tracing Apps (CTA) to reduce the spread of COVID19 have been well documented and, in the UK, led to the abandonment of the NHS CTA shortly after its release in May 2020. We present a causal probabilistic model (a Bayesian network) that provides the basis for a practical CTA solution that addresses some of the concerns and which has the advantage of minimal infringement of privacy. Users of the model can provide as much or little personal information as they wish about relevant risk factors, symptoms, and recent social interactions. The model then provides them feedback about the likelihood of the presence of asymptotic, mild or severe COVID19 (past, present and projected). When the model is embedded in a smartphone app, it can be used to detect new outbreaks in a monitored population and identify outbreak locations as early as possible. For this purpose, the only data needed to be centrally collected is the probability the user has COVID19 and the GPS location.

scholarly journals Pilot evaluation of risk assessment and enhanced protocols regarding contacts at an international professional golf event

2021 ◽  
Vol 7 (3) ◽  
pp. e001127
Author(s):  
Patrick G Robinson ◽  
Andrew Murray ◽  
Volker Sheer ◽  
Graeme Close ◽  
Denis F Kinane
Keyword(s):  
Risk Assessment ◽  
Pilot Study ◽  
High Risk ◽  
Disease Transmission ◽  
Low Risk ◽  
Contact Tracing ◽  
Sporting Events ◽  
Medical Surveillance ◽  
Rt Pcr ◽  
Antigen Testing

ObjectivesThe aim of this study was to assess whether a risk assessment and managed risk approach to contact tracing was practical and feasible at the Gran Canaria Lopesan Open 2021 and could inform further pilot work regarding disease transmission during elite sporting events.MethodsThis prospective cohort study included all international attendees. All participants required a minimum of one negative reverse transcriptase PCR (RT-PCR) test prior to travelling to each tournament. High-risk contacts were isolated for 10 days. Moderate-risk contacts received education regarding enhanced medical surveillance, had daily rapid antigen testing for 5 days, with RT-PCR day 5, mandated mask use and access to outside space for work purposes only. Low-risk contacts received rapid antigen testing every 48 hours and PCR testing on day 5.ResultsA total of 550 persons were accredited and were required to undergo RT-PCR testing before the event. Two of these tests were positive (0.36%). Of these, case 1 had 1 high, 23 moderate and 48 low-risk contacts. Case 2 did not have any significant travel history within 2 days of positive test and had one high-risk contact. There were no further positive tests on site in the wider cohort of attendees, from a total of 872 RT-PCR and 198 rapid antigen tests.ConclusionsThis pilot study showed it is practical, feasible and well accepted to provide enhanced (daily) virus testing and risk-mitigating measures at a professional golf event. Further study is required to assess the efficacy of these interventions; however, no transmission was found in this pilot study.

scholarly journals Algorithms in Action: Reassembling Contact Tracing and Risk Assessment during the Covid-19 Pandemic in China

2020 ◽  
Author(s):  
Chuncheng Liu
Keyword(s):  
Risk Assessment ◽  
Optimal Algorithm ◽  
Contact Tracing ◽  
Local Networks ◽  
Social Actors ◽  
Invisible Work ◽  
State And Society ◽  
Dialectical Relationship ◽  
Everyday Resistance ◽  
Human Actors

During the Covid-19 pandemic, technologies such as contact tracing and risk assessment algorithms are widely used. While debates are heated about the optimal algorithm designs with respect to their effectiveness and ethics, little is known about how the algorithms are deployed, experienced, challenged, and reshaped in society. Combining in-depth interviews, media articles, and policy documents, this study examines how Health Code, the Chinese contact tracing and risk assessment algorithm, is assembled, disassembled, and reassembled in society. I argue for a conceptualization of algorithms as sociotechnical assemblages with the involvement of diverse human and non-human actors, which are constantly in action. I first explore the intensive and invisible work and infrastructures that enable Health Code to be enacted. However, these assembly attempts are consistently challenged in differing situations and destabilized Health Code from time to time. Health Code reassembles under the diverse yet unintended engagements of social actors, local networks, and power relations, which creates multiple Health Codes at different periods of time and social localities. I also examine how people game and bypass the algorithm’s surveillance as forms of everyday resistance. These findings go beyond the current technical debates and bring a more dynamic, nuanced, and realistic depicture of algorithms’ operation and power. Lastly, I explore how algorithms contribute to a new dialectical relationship between state and society, and how this relationship reshapes the mechanism of surveillance, inequality, and citizenship in this digital age.

scholarly journals Privacy-Preserving Contact Tracing and Public Risk Assessment Using Blockchain for COVID-19 Pandemic

2020 ◽  
Vol 3 (3) ◽  
pp. 58-63
Author(s):  
Paulo Valente Klaine ◽  
Lei Zhang ◽  
Bingpeng Zhou ◽  
Yao Sun ◽  
Hao Xu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Privacy Preserving ◽  
Contact Tracing ◽  
Public Risk

scholarly journals Propagation of a hospital-associated cluster of COVID-19 in Malaysia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Diane Woei-Quan Chong ◽  
Vivek Jason Jayaraj ◽  
Chiu-Wan Ng ◽  
I-Ching Sam ◽  
Mas Ayu Said ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Whole Genome Sequencing ◽  
Healthcare Worker ◽  
Genome Sequencing ◽  
Control Measures ◽  
Contact Tracing ◽  
Infection Prevention And Control ◽  
Whole Genome ◽  
Epidemiological Investigation ◽  
Hospital Population

Abstract Background Hospitals are vulnerable to COVID-19 outbreaks. Intrahospital transmission of the disease is a threat to the healthcare systems as it increases morbidity and mortality among patients. It is imperative to deepen our understanding of transmission events in hospital-associated cases of COVID-19 for timely implementation of infection prevention and control measures in the hospital in avoiding future outbreaks. We examined the use of epidemiological case investigation combined with whole genome sequencing of cases to investigate and manage a hospital-associated cluster of COVID-19 cases. Methods An epidemiological investigation was conducted in a University Hospital in Malaysia from 23 March to 22 April 2020. Contact tracing, risk assessment, testing, symptom surveillance, and outbreak management were conducted following the diagnosis of a healthcare worker with SARS-CoV-2 by real-time PCR. These findings were complemented by whole genome sequencing analysis of a subset of positive cases. Results The index case was symptomatic but did not fulfill the initial epidemiological criteria for routine screening. Contact tracing suggested epidemiological linkages of 38 cases with COVID-19. Phylogenetic analysis excluded four of these cases. This cluster included 34 cases comprising ten healthcare worker-cases, nine patient-cases, and 15 community-cases. The epidemic curve demonstrated initial intrahospital transmission that propagated into the community. The estimated median incubation period was 4.7 days (95% CI: 3.5–6.4), and the serial interval was 5.3 days (95% CI: 4.3–6.5). Conclusion The study demonstrated the contribution of integrating epidemiological investigation and whole genome sequencing in understanding disease transmission in the hospital setting. Contact tracing, risk assessment, testing, and symptom surveillance remain imperative in resource-limited settings to identify and isolate cases, thereby controlling COVID-19 outbreaks. The use of whole genome sequencing complements field investigation findings in clarifying transmission networks. The safety of a hospital population during this COVID-19 pandemic may be secured with a multidisciplinary approach, good infection control measures, effective preparedness and response plan, and individual-level compliance among the hospital population.

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