A Statistical Model to Assess Risk for Supporting COVID-19 Quarantine Decisions

Jäckle, Sonja; Röger, Elias; Dicken, Volker; Geisler, Benjamin; Schumacher, Jakob; Westphal, Max

doi:10.3390/ijerph18179166

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…In the group quarantine use case, the 2 parameters α and β needed for the beta binomial prior distribution were determined based on the probability P ( K >0) that at least one person was infected and the conditional mean number of infected persons in the case of transmission E ( K | K >0) [ 76 ]. The web application provides a calculation of the probability of no further infections in 2 settings: a childcare group and a school class.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study

Alpers¹,

Kühne²,

Truong³

et al. 2023

JMIR Form Res

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Background During the COVID-19 pandemic, local health authorities were responsible for managing and reporting current cases in Germany. Since March 2020, employees had to contain the spread of COVID-19 by monitoring and contacting infected persons as well as tracing their contacts. In the EsteR project, we implemented existing and newly developed statistical models as decision support tools to assist in the work of the local health authorities. Objective The main goal of this study was to validate the EsteR toolkit in two complementary ways: first, investigating the stability of the answers provided by our statistical tools regarding model parameters in the back end and, second, evaluating the usability and applicability of our web application in the front end by test users. Methods For model stability assessment, a sensitivity analysis was carried out for all 5 developed statistical models. The default parameters of our models as well as the test ranges of the model parameters were based on a previous literature review on COVID-19 properties. The obtained answers resulting from different parameters were compared using dissimilarity metrics and visualized using contour plots. In addition, the parameter ranges of general model stability were identified. For the usability evaluation of the web application, cognitive walk-throughs and focus group interviews were conducted with 6 containment scouts located at 2 different local health authorities. They were first asked to complete small tasks with the tools and then express their general impressions of the web application. Results The simulation results showed that some statistical models were more sensitive to changes in their parameters than others. For each of the single-person use cases, we determined an area where the respective model could be rated as stable. In contrast, the results of the group use cases highly depended on the user inputs, and thus, no area of parameters with general model stability could be identified. We have also provided a detailed simulation report of the sensitivity analysis. In the user evaluation, the cognitive walk-throughs and focus group interviews revealed that the user interface needed to be simplified and more information was necessary as guidance. In general, the testers rated the web application as helpful, especially for new employees. Conclusions This evaluation study allowed us to refine the EsteR toolkit. Using the sensitivity analysis, we identified suitable model parameters and analyzed how stable the statistical models were in terms of changes in their parameters. Furthermore, the front end of the web application was improved with the results of the conducted cognitive walk-throughs and focus group interviews regarding its user-friendliness.

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Section: Methodsmentioning

confidence: 99%

Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study

Alpers¹,

Kühne²,

Truong³

et al. 2023

JMIR Form Res

Self Cite

View full text Add to dashboard Cite

show abstract

“…The statistical model used for this tool as well as all necessary parameters are described in [18] and has been specified for certain situations such as school classes or children daycare centers, which are the most common use cases in local health authorities. Beside PCR tests, antigen tests can be considered, which have been used more frequently since the beginning of 2021.…”

Section: Risk Assessment For Group Quarantinementioning

confidence: 99%

EsteR – A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities

Jäckle

Alpers

Kühne

et al. 2022

Studies in Health Technology and Informatics

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In Germany, the current COVID-19 cases are managed and reported by the local health authorities. The workload of their employees during the pandemic is high, especially in periods of high infection numbers. In this work a decision support toolkit for local health authorities is introduced. A demonstrator web application was developed with the R Shiny framework and is publicly accessible online. It contains five separate tools based on statistical models for specific use cases and corresponding questions of COVID-19 cases and their contacts. The underlying statistical methods have been implemented in a new open-source R package. The toolkit has the potential to support local health authorities’ employees in their daily work. A simulated-based validation of the statistical models and a usability evaluation of the demonstrator application in a user study will be carried out in the future.

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Use of clinical data to augment healthcare worker contact tracing during the COVID-19 pandemic

Hong

Herigon

Uptegraft

et al. 2021

Journal of the American Medical Informatics Association

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Objective This work examined the secondary use of clinical data from the electronic health record (EHR) for screening our healthcare worker (HCW) population for potential exposures to patients with coronavirus disease 2019. Materials and Methods We conducted a cross-sectional study at a free-standing, quaternary care pediatric hospital comparing first-degree, patient-HCW pairs identified by the hospital’s COVID-19 contact tracing team (CTT) to those identified using EHR clinical event data (EHR Report). The primary outcome was the number of patient-HCW pairs detected by each process. Results Among 233 patients with COVID-19, our EHR Report identified 4,116 patient-HCW pairs, including 2,365 (30.0%) of the 7,890 pairs detected by the CTT. The EHR Report also revealed 1,751 pairs not identified by the CTT. The highest number of patient-HCW pairs per patient was detected in the inpatient care venue. Nurses comprised the most frequently identified HCW role overall. Conclusion Automated methods to screen HCWs for potential exposure to patients with COVID-19 using clinical event data from the EHR are likely to improve epidemiologic surveillance by contact tracing programs and represent a viable and readily available strategy which should be considered by other institutions.

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A Statistical Model to Assess Risk for Supporting COVID-19 Quarantine Decisions

Cited by 4 publications

References 12 publications

Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study

Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study

EsteR – A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities

Use of clinical data to augment healthcare worker contact tracing during the COVID-19 pandemic

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