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

Jäckle, Sonja; Alpers, Rieke; Kühne, Lisa; Schumacher, Jakob; Geisler, Benjamin; Westphal, Max

doi:10.3233/shti220799

Cited by 3 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The underlying distribution in the infection period model was a lognormal distribution for the incubation time [ 4 , 15 ]. For the simulation, the mean parameter μ and the SD parameter σ for a reasonable lognormal distribution were calculated using the lognormal distribution properties for the median μ* and mean E (X), namely, μ* = e μ and .…”

Section: Methodsmentioning

confidence: 99%

“…The illness period of contact persons was modeled using a gamma distribution of the serial interval [ 4 , 16 ]. For this use case, we used the articles from the literature review that reported the mean E ( X ) and SD ( X ) of the serial interval.…”

Section: Methodsmentioning

confidence: 99%

“…For modeling the infectious period, only one study was available that directly used a gamma distribution [ 4 , 17 ]. For comparability across the use cases, we calculated the mean and SD of that gamma distribution, as described previously, and defined their own ranges to test them using a similar size as in the illness period use case.…”

Section: Methodsmentioning

confidence: 99%

“…Table 1 lists the values for the childcare setting; for the school class, we used default values of P ( K >0)=0.12 and E ( K | K >0)=1.77 in the EsteR toolkit and conducted the sensitivity analysis for P ( K >0) in the range from 0.05-0.21 and for E ( K | K >0) in the range from 1-8. In both settings, the ranges of the transmission probability were based on the reported 95% CIs [ 4 , 18 ].…”

Section: Methodsmentioning

confidence: 99%

“…For each use case, a statistical model was developed based on the COVID-19 properties reported in the literature. The entire toolkit was already introduced in detail in the article by Jäckle et al [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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

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.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

OralDentalSoft: Open-Source Web Application for Dental Office Management

Burbano,

Estévez,

Llerena

et al. 2024

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

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

Alpers¹,

Kühne²,

Truong³

et al. 2022

Preprint

View full text Add to dashboard Cite

BACKGROUND In the COVID-19 pandemic, local health authorities are responsible for managing and reporting the current cases in Germany. Since March 2020, the employees had to focus on the pandemic. In the EsteR project, we implemented existing and newly developed statistical models in decision support tools to assist the work in the local health authorities. OBJECTIVE The two main goals of this work are investigating the stability of the answers provided by our statistical tools regarding model parameters and evaluating the usability and applicability of our web application. METHODS For the model stability assessment, a sensitivity analysis was carried out for all five statistical models. The default parameters of our models and the ranges the parameters were tested in were based on a prior literature review on COVID-19 properties. For the usability evaluation of the web application, cognitive walkthroughs and focus group interviews were conducted with employees of two different local health authorities. RESULTS The simulation results showed that some statistical models are more sensitive to changes in their parameters than others. For each of the single person use cases we were able to find an area where we rate the respective model to be stable, whereas for the group use cases the stability highly depends on the user inputs. The cognitive walkthroughs and the focus group interview disclosed that the user interface had to be simplified and more information was needed as guidance. In general, the testers rated the web application as helpful, especially for new employees. CONCLUSIONS This evaluation study allowed for a refinement of our toolkit. With the simulations, we identified suitable model parameters and analyzed how stable the statistical models are regarding changes in their parameters. Furthermore, the web application was improved with the results of the cognitive walkthroughs and focus group interviews.

show abstract

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

Cited by 3 publications

References 16 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

OralDentalSoft: Open-Source Web Application for Dental Office Management

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

Contact Info

Product

Resources

About