scholarly journals Evaluation of epidemiological risk using contact tracing open data (Preprint)

10.2196/28947 ◽  
2021 ◽  
Author(s):  
Stefano Piotto ◽  
Luigi Di Biasi ◽  
Francesco Marrafino ◽  
Simona Concilio
Keyword(s):  
Open Data ◽  
Contact Tracing ◽  
Epidemiological Risk

scholarly journals Evaluation of epidemiological risk using contact tracing open data (Preprint)

2021 ◽  
Author(s):  
Simona Concilio ◽  
Luigi Di Biasi ◽  
Francesco Marrafino ◽  
Simona Concilio
Keyword(s):  
Data Analysis ◽  
Open Data ◽  
Real Data ◽  
Security And Privacy ◽  
Contact Tracing ◽  
The Road ◽  
Pearson Coefficient ◽  
Epidemiological Risk ◽  
Contact Data ◽  
Ct Data

BACKGROUND During the 2020s, there was extensive debate about the possible use of contact tracing (CT) for SARS-CoV-2 pandemic containment, and concerns have been raised about data security and privacy. Little has been said about the effectiveness of CT. In this work, we present a real data analysis of a CT experiment conducted in Italy for eight months involving more than 100,000 users. OBJECTIVE We discuss the technical and health aspects of a centralized approach. We show the correlation between the acquired contact data and the number of positives to SARS-CoV-2. We analyze CT data to define population behavior, and we show the potential application of real contact tracing data. METHODS CT data were collected, analyzed, and evaluated on the basis of the duration, persistence and frequency of contacts over several months of observation. A statistical test was conducted to determine whether there is a correlation between indices of behavior calculated from the data and the number of new infections in the population (new positives). RESULTS We evidence a correlation between a weighted measure of contacts with the new positives to the virus (Pearson coefficient = 0.86), paving the road to a better and more accurate data analysis and spread prediction. CONCLUSIONS The data are used to determine the most relevant epidemiological parameters and can be used to develop an agent-based system to simulate the effect of restrictions and vaccinations. Finally, we demonstrated the system's ability to identify the physical locations where the probability of infection is highest. All data collected are available to the scientific community for further analysis.

scholarly journals Application-Based COVID-19 Micro-Mobility Solution for Safe and Smart Navigation in Pandemics

2021 ◽  
Vol 10 (8) ◽  
pp. 571
Author(s):  
Sumit Mishra ◽  
Nikhil Singh ◽  
Devanjan Bhattacharya
Keyword(s):  
Data Analysis ◽  
Routing Algorithm ◽  
Open Data ◽  
Route Planning ◽  
Contact Tracing ◽  
Residential Areas ◽  
Environment Exposure ◽  
Micro Mobility ◽  
Spatial System ◽  
Mobility Solution

Short distance travel and commute being inevitable, safe route planning in pandemics for micro-mobility, i.e., cycling and walking, is extremely important for the safety of oneself and others. Hence, we propose an application-based solution using COVID-19 occurrence data and a multi-criteria route planning technique for cyclists and pedestrians. This study aims at objectively determining the routes based on various criteria on COVID-19 safety of a given route while keeping the user away from potential COVID-19 transmission spots. The vulnerable spots include places such as a hospital or medical zones, contained residential areas, and roads with a high connectivity and influx of people. The proposed algorithm returns a multi-criteria route modeled on COVID-19-modified parameters of micro-mobility and betweenness centrality considering COVID-19 avoidance as well as the shortest available safe route for user ease and shortened time of outside environment exposure. We verified our routing algorithm in a part of Delhi, India, by visualizing containment zones and medical establishments. The results with COVID-19 data analysis and route planning suggest a safer route in the context of the coronavirus outbreak as compared to normal navigation and on average route extension is within 8%–12%. Moreover, for further advancement and post-COVID-19 era, we discuss the need for adding open data policy and the spatial system architecture for data usage, as a part of a pandemic strategy. The study contributes new micro-mobility parameters adapted for COVID-19 and policy guidelines based on aggregated contact tracing data analysis maintaining privacy, security, and anonymity.

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.

Leveraging Polio GIS platforms in the African Region for mitigating Covid-19 contact tracing challenges (Preprint)

2020 ◽  
Author(s):  
Godwin Ubong Akpan ◽  
Isah Mohammed Bello ◽  
Kebba Touray ◽  
Reuben Ngofa ◽  
Daniel Oyaole ◽  
...  
Keyword(s):  
Data Collection ◽  
Real Time ◽  
Critical Role ◽  
Open Data ◽  
Contact Tracing ◽  
Quality Data ◽  
Time Data ◽  
Outbreak Response ◽  
African Region ◽  
Health Crisis

BACKGROUND The growth of the novel coronavirus 2019 (COVID-19) pandemic in Africa is an urgent public health crisis. Estimated models project over 150,000 deaths and 4,600,000 hospitalizations in the first year of disease in the absence of adequate interventions. Electronic contact tracing, therefore, offers a critical role in decreasing COVID-19 transmission; yet if not conducted properly can rapidly become a bottleneck for synchronized data collection, case detection, and case management. While the continent is currently reporting relatively low COVID-19 cases, digitized contact tracing mechanisms are necessary for standardizing real-time reporting of new chains of infection to quickly reverse growing trends and halt the pandemic. OBJECTIVE The aim of this study is describing an effective contact tracing smartphone app developed with expertise and experience gained from the numerous digital apps that the Polio programme has used to successfully support disease surveillance and immunization assessment in the African Region. A secondary objective is to describe how we leveraged Polio GIS resources to enhance existing contact tracing solutions to be more efficient through the connection to real-time data visualization platforms. METHODS We propose the use of a hybrid Open Data Kit (ODK) electronic COVID-19 contact registra- tion form that automates contacts and follow-ups. A proof-of-concept form on ODK has been developed that integrates collected contact tracing information from multiple platforms to generate an interactive regional dashboard to monitor the COVID-19 response. Analytics outputs extrapolate key outbreak response indi- cators such as timeliness, completeness and outcomes of contact tracing including new positive cases. This system allows multiple outbreak outputs to be monitored including sources of new infection for immediate response with minimal disruption to existing contact tracing tools. RESULTS Standardized electronic registration of COVID-19 contacts and follow-up using ODK has en- hanced monitoring of contact tracing. Countries and communities have increased their capacity to track COVID-19 cases and contacts in the general population quickly based on the onset of signs or symptoms. Registered contacts for contact tracing are matched to their respective cases more efficiently and for con- tacts that can engage in self-reporting, the anonymity of self-reporting. The country-specific results suggest that higher adoption rates of the tools may result in better quality data on the pandemic and elicited better decisions for a response. CONCLUSIONS Our proposed contact tracing solution which uses ODK based tools on smartphones and visualization bridge systems presents a scalable and easy to implement solution, that collects and aggregates good quality contact data with geographic information that can help make spatial based decisions and preserves privacy while demonstrating the potential to help make better decisions in response to an epidemic or pandemic outbreak. This application has been applied to the current COVID-19 pandemic and can also be used for other epidemics or pandemics in the future, to achieve quality data collection for better decision making.

scholarly journals Importance of adequate COVID-19 case definitions in the SARS-CoV-2 pandemic

2021 ◽  
Author(s):  
Isaac Núñez ◽  
Yanink Caro-Vega ◽  
Pablo F. Belaunzarán-Zamudio
Keyword(s):  
Mexico City ◽  
Open Data ◽  
Case Definition ◽  
Contact Tracing ◽  
Suspected Case ◽  
Case Definitions ◽  
Probable Case ◽  
Mexican Government ◽  
Antigen Tests ◽  
Low Sensitivity

Background: Epidemiologic case definitions serve a myriad of purposes during a pandemic, including contact tracing and monitoring disease trends. It is unknown how any COVID-19 case definition fares against the current gold standard of molecular or antigen tests. Methods: We calculated the diagnostic properties of five COVID-19 definitions (three of the Mexican government and two of the WHO) using open data of suspected COVID-19 cases in Mexico City from March 24th 2020 until January 31st 2021. Results: All 1,632,420 people included in the analysis met the WHO suspected case definition (sensitivity 100%, specificity 0%). The WHO probable case definition was met by 1.4%, while the first and second Mexican suspected case had sensitivities of 61 and 62% and specificities of 58 and 62%, respectively. Confirmed case by epidemiological contact had a low sensitivity (33%) but slightly higher specificity (77%). Conclusions: Case definitions should maximize sensitivity, especially in a high-transmission area such as Mexico City. The WHO suspected case definition has the potential for detecting most symptomatic cases. We underline the need for routine evaluation of case definitions as new evidence arises to maximize their usefulness.

scholarly journals Where to learn to flatten the curve: a modelling study

2021 ◽  
Author(s):  
Matthew J Silk ◽  
Simon Carrignon ◽  
R. Alexander Bentley ◽  
Nina H Fefferman
Keyword(s):  
Social Norms ◽  
Communication Networks ◽  
Disease Risk ◽  
Physical Layer ◽  
Physical Contact ◽  
Disease Spread ◽  
Contact Tracing ◽  
Accurate Information ◽  
Epidemiological Risk ◽  
Perceived Social Norms

Background: Individual behavioural decisions are responses to both a persons perceived social norms and could be driven by both their physical and social environment. In the context of the COVID-19 pandemic, these environments correspond to epidemiological risk from contacts and the social construction of risk by communication within networks of friends. Understanding when, and under which circumstances, each modality of influence can foster the widespread adoption of protective behaviours is critical for shaping useful, practical public health messaging that will best enhance the public response. Methods: We use a multiplex network approach to explore how information from both physical contact and social communication networks is driving a mitigating behavioural response to disease risk. Findings: We show that maintaining focus on awareness of risk in each individuals physical layer contacts promotes the greatest reduction in disease spread, but only when an individual is aware of the symptoms of a non-trivial proportion of their physical contacts (approximately 20% or more). Information from the communication layer was less useful when these connections matched less well with physical contacts and contributed little in combination with accurate information from the physical layer. Interpretation: We conclude that maintaining social focus on local outbreak status will allow individuals to structure their perceived social norms appropriately and respond more rapidly when risk increases. Finding ways to relay accurate local information from trusted community leaders could improve mitigation even where more intrusive/costly strategies, such as contact-tracing, are not possible.

scholarly journals An e-registry for household contacts exposed to multidrug resistant TB in Mongolia

2020 ◽  
Author(s):  
Kush Naker ◽  
Katherine M Gaskell ◽  
Munhjargal Dorjravdan ◽  
Naranzul Daamba ◽  
Chrissy h Roberts ◽  
...  
Keyword(s):  
National Level ◽  
Open Data ◽  
Multidrug Resistant ◽  
Clinic Visit ◽  
Contact Tracing ◽  
Electronic Data Collection ◽  
Household Contacts ◽  
Promising Tool ◽  
Resistant Tuberculosis ◽  
Mdr Tb

Abstract Background: The WHO recommends that individuals exposed to persons with multidrug resistant tuberculosis (MDRTB) should be screened for active TB and followed up for two years to detect and treat secondary cases early. Resource prioritisation means this is rarely undertaken and where it is performed it is usually using a paper-based record, without collation of data. Electronic data collection into a web-based registry offers the opportunity for simplified and systematic TB contact surveillance with automatic synthesis of data at local, regional and national level. This pilot study was designed to explore the feasibility of usage of a novel e-registry tool and explore obstacles and facilitating factors to implementation. Methods: In parallel with their paper records, seven dispensaries in Ulaanbaatar, Mongolia collected standardized data electronically using Open Data Kit (ODK). Patients with MDRTB and their contacts were recruited during a single clinic visit. Staff and patients were interviewed to gain insights into acceptability and to identify areas for improvement. Results: 70 household contacts of 32 MDR-TB index patients were recruited. 7/70 contacts (10%) traced had active TB at the time they were recruited to the e-registry. Paper registry satisfaction was low; 88% of staff preferred the e-registry as it was perceived as faster and more secure. Patients and their contacts were generally supportive of the e-registry; however, a significant minority 10/42 (24%) of index cases who were invited, declined to participate in the e-registry, with data security cited as their top concern. Conclusion: E-registries are a promising tool for MDRTB contact tracing, but their acceptability amongst patients should not be taken for granted.

scholarly journals SARS-CoV-2 viral RNA load dynamics in the nasopharynx of infected children

2021 ◽  
Vol 149 ◽  
Author(s):  
K. Q. Kam ◽  
K. C. Thoon ◽  
M. Maiwald ◽  
C. Y. Chong ◽  
H. Y. Soong ◽  
...  
Keyword(s):  
Viral Load ◽  
Upper Airway ◽  
Contact Tracing ◽  
Transmission Potential ◽  
Cycle Threshold ◽  
Viral Loads ◽  
Asymptomatic Children ◽  
Epidemiological Risk ◽  
Symptom Status ◽  
Mean Cycle

Abstract It is important to understand the temporal trend of the paediatric severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load to estimate the transmission potential of children in schools and communities. We determined the differences in SARS-CoV-2 viral load dynamics between nasopharyngeal samples of infected asymptomatic and symptomatic children. Serial cycle threshold values of SARS-CoV-2 from the nasopharynx of a cohort of infected children were collected for analysis. Among 17 infected children, 10 (58.8%) were symptomatic. Symptomatic children, when compared to asymptomatic children, had higher viral loads (mean cycle threshold on day 7 of illness 28.6 vs. 36.7, P = 0.02). Peak SARS-CoV-2 viral loads occurred around day 2 of illness in infected children. Although we were unable to directly demonstrate infectivity, the detection of significant amount of virus in the upper airway of asymptomatic children suggest that they have the potential to shed and transmit SARS-CoV-2. Our study highlights the importance of contact tracing and screening for SARS-CoV-2 in children with epidemiological risk factors regardless of their symptom status, in order to improve containment of the virus in the community, including educational settings.

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