ABSTRACT
To support the pediatric intensive care unit with the COVID-19 pandemic, we followed a user-centered design process to create a dashboard in a context where direct access to users was impossible. To this end, we applied contextual inquiry, user interview, requirement definition, iterative design with user validation and usability testing in a remote fashion. Being unable to be physically present at the hospital limited our understanding of the context of use, extended the duration of the study and limited the number of interviews and testing sessions. However, we were able to benefit from the experience of our team members, adopt an efficient decision-making method to select appropriate requirements and use remote moderated usability testing to conform our design process to an aggressive timeline. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
This study aimed to identify an appropriate simple mathematical model to fit the number of coronavirus disease 2019 (COVID-19) cases at the national level for the early portion of the pandemic, before significant public health interventions could be enacted. The total number of cases for the COVID-19 epidemic over time in 28 countries was analysed and fit to several simple rate models. The resulting model parameters were used to extrapolate projections for more recent data. While the Gompertz growth model (mean R2 = 0.998) best fit the current data, uncertainties in the eventual case limit introduced significant model errors. However, the quadratic rate model (mean R2 = 0.992) fit the current data best for 25 (89%) countries as determined by R2 values of the remaining models. Projection to the future using the simple quadratic model accurately forecast the number of future total number of cases 50% of the time up to 10 days in advance. Extrapolation to the future with the simple exponential model significantly overpredicted the total number of future cases. These results demonstrate that accurate future predictions of the case load in a given country can be made using this very simple model.
Subject(s)
COVID-19/diagnosis , Logistic Models , Models, Theoretical , COVID-19/epidemiology , Europe/epidemiology , Humans , Pandemics/prevention & controlABSTRACT
As the coronavirus disease 2019 (COVID-19) pandemic second wave is emerging, it is of the upmost importance to screen the population immunity in order to keep track of infected individuals. Consequently, immunoassays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high specificity and positive predictive values are needed to obtain an accurate epidemiological picture. As more data accumulate about the immune responses and the kinetics of neutralizing-antibody (nAb) production in SARS-CoV-2-infected individuals, new applications are forecast for serological assays such as nAb activity prediction in convalescent-phase plasma from recovered patients. This multicenter study, involving six hospital centers, determined the baseline clinical performances, reproducibility, and nAb level correlations of 10 commercially available immunoassays. In addition, three lateral-flow chromatography assays were evaluated, as these devices can be used in logistically challenged areas. All assays were evaluated using the same patient panels in duplicate, thus enabling accurate comparison of the tests. Seven immunoassays examined in this study were shown to have excellent specificity (98 to 100%) and good to excellent positive predictive values (82 to 100%) when used in a low (5%)-seroprevalence setting. We observed sensitivities as low as 74% and as high as 95% at ≥15 days after symptom onset. The determination of optimized cutoff values through receiver operating characteristic (ROC) curve analyses had a significant impact on the diagnostic resolution of several enzyme immunoassays by increasing the sensitivity significantly without a large trade-off in specificity. We found that spike-based immunoassays seem to be better correlates of nAb activity. Finally, the results reported here will add to the general knowledge of the interlaboratory reproducibility of clinical performance parameters of immunoassays and provide new evidence about nAb activity prediction.