6 research outputs found
A Bayesian spatial-temporal model for prevalence estimation of a VRE outbreak in a tertiary care hospital.
BACKGROUND
There was a nosocomial outbreak of vancomycin-resistant enterococci (VRE) in our hospital from 1.1.2018 to 31.7.2020. The goals of the study were to describe weekly prevalence, and to identify possible effects of the introduction of selected infection control measures.
METHODS
We performed a room centric analysis of 12 floors (243 rooms) of the main hospital building, including data on 37,558 patients over 22,072 person weeks for the first two years of the outbreak (2018-19). Poisson Bayesian hierarchical models were fitted to estimate prevalence per room and week, including both spatial and temporal random effects terms.
RESULTS
Exploratory data analysis revealed significant variability in prevalence between departments and floors, along with sporadic spatial and temporal clustering during colonization "flare-ups". The oncology department experienced slightly higher prevalence over the 104 week study period (adjusted prevalence ratio (aPR) 4.8 [2.6, 8.9], p<0.001, compared to general medicine), as did both the cardiac surgery (aPR 3.8 [2.0, 7.3], p<0.001) and abdominal surgery departments (aPR 3.7 [1.8, 7.6], p<0.001). Estimated peak prevalence was reached in July 2018, at which point a number of new infection control measures (including the daily disinfection of rooms and room cleaning with UV light upon patient discharge) were introduced that resulted in a decreasing prevalence (aPR=0.89 per week, 95% CI [0.87, 0.91], p<0.001).
CONCLUSION
Relatively straightforward, but personnel-intensive cleaning with disinfectants and UV light provided tangible benefits in getting the outbreak under control. Despite additional complexity, Bayesian Hierarchical Models provide a more flexible platform for studying transmission dynamics
Accuracy of serological testing for SARS-CoV-2 antibodies: first results of a large mixed-method evaluation study.
BACKGROUND
Serological immunoassays that can identify protective immunity against SARS-CoV-2 are needed to adapt quarantine measures, assess vaccination responses, and evaluate donor plasma. To date, however, the utility of such immunoassays remains unclear. In a mixed-design evaluation study, we compared the diagnostic accuracy of serological immunoassays that are based on various SARS-CoV-2 proteins and assessed the neutralizing activity of antibodies in patient sera.
METHODS
Consecutive patients admitted with confirmed SARS-CoV-2 infection were prospectively followed alongside medical staff and biobank samples from winter 2018/2019. An in-house enzyme-linked immunosorbent assay utilizing recombinant receptor-binding domain (RBD) of the SARS-CoV-2 spike protein was developed and compared to three commercially available enzyme-linked immunosorbent assays (ELISAs) targeting the nucleoprotein (N), the S1 domain of the spike protein (S1) and a lateral flow immunoassay (LFI) based on full-length spike protein. Neutralization assays with live SARS-CoV-2 were performed.
RESULTS
One-thousand four-hundred and seventy-seven individuals were included comprising 112 SARS-CoV-2 positives (defined as a positive real-time PCR result; prevalence 7.6%). IgG seroconversion occurred between day 0 and day 21. While the ELISAs showed sensitivities of 88.4% for RBD, 89.3% for S1, and 72.9% for N protein, the specificity was above 94% for all tests. Out of 54 SARS-CoV-2 positive individuals, 96.3% showed full neutralization of live SARS-CoV-2 at serum dilutions ≥1:16, while none of the 6 SARS-CoV-2 negative sera revealed neutralizing activity.
CONCLUSIONS
ELISAs targeting RBD and S1 protein of SARS-CoV-2 are promising immunoassays which shall be further evaluated in studies verifying diagnostic accuracy and protective immunity against SARS-CoV-2