Publications by authors named "C Wymant"
The ability to predict HIV-1 resistance to broadly neutralizing antibodies (bnAbs) will increase bnAb therapeutic benefits. Machine learning is a powerful approach for such prediction. One challenge is that some HIV-1 subtypes in currently available training datasets are underrepresented, which likely affects models' generalizability across subtypes.
View Article and Find Full Text PDFUnderstanding the drivers of respiratory pathogen spread is challenging, particularly in a timely manner during an ongoing epidemic. In this work, we present insights that we obtained using daily data from the National Health Service COVID-19 app for England and Wales and that we shared with health authorities in almost real time. Our indicator of the reproduction number () was available days earlier than other estimates, with an innovative capability to decompose () into contact rates and probabilities of infection.
View Article and Find Full Text PDFArticle Synopsis
- A study analyzed 7 million contacts recorded by the National Health Service COVID-19 app in England and Wales to evaluate the likelihood of SARS-CoV-2 transmission after exposure.
- The research found that longer exposures at greater distances had similar risk levels to shorter exposures at closer distances, and the chance of transmission increased steadily with longer exposure duration.
- Households, though representing only 6% of contacts, were responsible for 40% of transmissions, suggesting that tailored public health strategies based on digital contact tracing could effectively manage outbreaks.
The NHS COVID-19 app was launched in England and Wales in September 2020, with a Bluetooth-based contact tracing functionality designed to reduce transmission of SARS-CoV-2. We show that user engagement and the app's epidemiological impacts varied according to changing social and epidemic characteristics throughout the app's first year. We describe the interaction and complementarity of manual and digital contact tracing approaches.
View Article and Find Full Text PDFBackground: Next-generation sequencing (NGS) is gradually replacing Sanger sequencing (SS) as the primary method for HIV genotypic resistance testing. However, there are limited systematic data on comparability of these methods in a clinical setting for the presence of low-abundance drug resistance mutations (DRMs) and their dependency on the variant-calling thresholds.
Methods: To compare the HIV-DRMs detected by SS and NGS, we included participants enrolled in the Swiss HIV Cohort Study (SHCS) with SS and NGS sequences available with sample collection dates ≤7 days apart.