Microbiology & Immunology - Research Publications

Permanent URI for this collection

http://hdl.handle.net/11343/226

Filters

2020 2
Reset filters

Settings
Statistics
Citations
Author: Howden, Benjamin × Start date: 2020 × Type: Preprint ×

Search Results

Now showing 1 - 2 of 2
  • Item
    Thumbnail Image
    Evaluation of serological tests for SARS-CoV-2: Implications for serology testing in a low-prevalence setting
    Bond, K ; Nicholson, S ; Ming Lim, S ; Karapanagiotidis, T ; Williams, E ; Johnson, D ; Hoang, T ; Sia, C ; Purcell, D ; R Lewin, S ; Catton, M ; P Howden, B ; A Williamson, D ( 2020)

    Background

    Robust serological assays are essential for long-term control of the COVID-19 pandemic. Many recently released point-of-care (PoCT) serological assays have been distributed with little pre-market validation.

    Methods

    Performance characteristics for five PoCT lateral flow devices approved for use in Australia were compared to a commercial enzyme immunoassay (ELISA) and a recently described novel surrogate virus neutralisation test (sVNT).

    Results

    Sensitivities for PoCT ranged from 51.8% (95% CI 43.1 to 60.4%) to 67.9% (95% CI 59.4–75.6%), and specificities from 95.6% (95% CI 89.2–98.8%) to 100.0% (95% CI 96.1–100.0%). Overall ELISA sensitivity for either IgA or IgG detection was 67.9% (95% CI 59.4–75.6), increasing to 93.8% (95% CI 85.0–98.3%) for samples > 14 days post symptom onset. Overall, sVNT sensitivity was 60.9% (95% CI 53.2–68.4%), rising to 91.2%% (95% CI 81.8–96.7%) for samples collected > 14 days post-symptom onset, with a specificity 94.4% (95% CI 89.2–97.5%),

    Conclusion

    Performance characteristics for COVID-19 serological assays were generally lower than those reported by manufacturers. Timing of specimen collection relative to onset of illness or infection is crucial in the reporting of performance characteristics for COVID-19 serological assays. The optimal algorithm for implementing serological testing for COVID-19 remains to be determined, particularly in low-prevalence settings.
  • Item
    Thumbnail Image
    Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria
    Gorrie, C ; Da Silva, AG ; Ingle, D ; Higgs, C ; Seemann, T ; Stinear, T ; Williamson, D ; Kwong, J ; Grayson, L ; Sherry, N ; Howden, B ( 2020-09-25)
    Background: Pairwise single nucleotide polymorphisms (SNPs) are a cornerstone for genomic approaches to multidrug-resistant organisms (MDROs) transmission inference in hospitals. However, the impact of key analysis parameters on these inferences has not been systematically analysed. Methods: We conducted a multi-hospital 15-month prospective study, sequencing 1537 MDRO genomes for comparison; methicillin-resistant Staphylococcus aureus , vancomycin-resistant Enterococcus faecium , and extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae . We systematically assessed the impact of sample and reference genome diversity, masking of prophage and regions of recombination, cumulative genome analysis compared to a three-month sliding-window, and the comparative effects each of these had when applying a SNP threshold for inferring likely transmission (≤15 SNPs for S. aureus , ≤25 for other species). Findings: Across the species, using a reference genome of the same sequence type provided a greater degree of pairwise SNP resolution, compared to species and outgroup-reference alignments that typically resulted in inflated SNP distances and the possibility of missed transmission events. Omitting prophage regions had minimal impacts, however, omitting recombination regions a highly variable effect, often inflating the number of closely related pairs. Estimating pairwise SNP distances was more consistent using a sliding-window than a cumulative approach. Interpretation: The use of a closely-related reference genome, without masking of prophage or recombination regions, and a sliding-window for isolate inclusion is best for accurate and consistent MDRO transmission inference. The increased stability and resolution provided by these approaches means SNP thresholds for putative transmission inference can be more reliably applied among diverse MDROs. Funding: This work was supported by the Melbourne Genomics Health Alliance (funded by the State Government of Victoria, Department of Health and Human Services, and the ten member organizations); an National Health and Medical Research Council (Australia) Partnership grant (GNT1149991) and individual grants from National Health and Medical Research Council (Australia) to NLS (GNT1093468), JCK (GNT1008549) and BPH (GNT1105905).