Epidemiological impact of a large number of false negative SARS-CoV-2 test results in South West England during September and October 2021.

During September and October 2021, a substantial number of Polymerase Chain Reaction (PCR) tests in England processed at a single laboratory were incorrectly reported as negative. We estimate the number of false negative test results issued and investigate the epidemiological impact of this incident. We estimate the number of COVID-19 cases that would have been reported had the sensitivity of the laboratory test procedure not dropped for the period 2 September to 12 October. In addition, by making comparisons between the most affected local areas and comparator populations, we estimate the number of additional infections, cases, hospitalisations and deaths that could have occurred as a result of increased transmission due to false negative test results.We estimate that around 39,000 tests may have been false negatives during this period and, as a direct result of this incident, the most affected areas in the South-West of England could have experienced between 6000 and 34,000 additional reportable cases, with a central estimate of around 24,000 additional reportable cases. Using modelled relationships between key variables, we estimate that this central estimate could have translated to approximately 55,000 additional infections.Each false negative likely led to around 1.5 additional infections. The incident is likely to have had a measurable impact on cases and infections in the affected areas in the South-West of England. IMPACT STATEMENT: These results indicate the significant negative impact of incorrect testing on COVID outcomes; and make a substantial contribution to understanding the impact of testing systems and the need to ensure high accuracy in testing and reporting of results.

Unifying Amplitude and Phase Analysis: A Compositional Data Approach to Functional Multivariate Mixed-Effects Modeling of Mandarin Chinese.

Mandarin Chinese is characterized by being a tonal language; the pitch (or F0) of its utterances carries considerable linguistic information. However, speech samples from different individuals are subject to changes in amplitude and phase, which must be accounted for in any analysis that attempts to provide a linguistically meaningful description of the language. A joint model for amplitude, phase, and duration is presented, which combines elements from functional data analysis, compositional data analysis, and linear mixed effects models. By decomposing functions via a functional principal component analysis, and connecting registration functions to compositional data analysis, a joint multivariate mixed effect model can be formulated, which gives insights into the relationship between the different modes of variation as well as their dependence on linguistic and nonlinguistic covariates. The model is applied to the COSPRO-1 dataset, a comprehensive database of spoken Taiwanese Mandarin, containing approximately 50,000 phonetically diverse sample F0 contours (syllables), and reveals that phonetic information is jointly carried by both amplitude and phase variation. Supplementary materials for this article are available online.