Imperial College London

MissLucyWilliams

Faculty of MedicineSchool of Public Health

Research Postgraduate
 
 
 
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Contact

 

lucy.williams19 Website

 
 
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Location

 

Building E - Sir Michael UrenWhite City Campus

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Summary

 

Publications

Publication Type
Year
to

6 results found

Williams LR, Ferguson NM, Donnelly CA, Grassly NCet al., 2022, Measuring vaccine efficacy against infection and disease in clinical trials: sources and magnitude of bias in COVID-19 vaccine efficacy estimates, Clinical Infectious Diseases, Vol: 75, Pages: e764-e773, ISSN: 1058-4838

BACKGROUND: Phase III trials have estimated COVID-19 vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections. METHODS: We developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic and any SARS͏CoV2 infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections. RESULTS: VE against asymptomatic infection measured by PCR or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias towards underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4 to 77.1) and 70.9% (95% UI 49.8 to 80.7) respectively. CONCLUSIONS: Multiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.

Journal article

Williams L, Marongiu A, Filippidis F, Heinzkill M, Reilly G, van Troostenburg A, Haubrich R, Ramroth Het al., 2021, Analyses of patient reported outcomes for appropriately tailoring to the needs of HIV-1 patient focus groups, Publisher: WILEY, Pages: 104-105, ISSN: 1464-2662

Conference paper

Imai N, Hogan AB, Williams L, Cori A, Mangal TD, Winskill P, Whittles LK, Watson OJ, Knock ES, Baguelin M, Perez-Guzman PN, Gaythorpe KAM, Sonabend R, Ghani AC, Ferguson NMet al., 2021, Interpreting estimates of coronavirus disease 2019 (COVID-19) vaccine efficacy and effectiveness to inform simulation studies of vaccine impact: a systematic review, Wellcome Open Research, Vol: 6, Pages: 185-185

<ns3:p><ns3:bold>Background:</ns3:bold> The multiple efficacious vaccines authorised for emergency use worldwide represent the first preventative intervention against coronavirus disease 2019 (COVID-19) that does not rely on social distancing measures. The speed at which data are emerging and the heterogeneities in study design, target populations, and implementation make it challenging to interpret and assess the likely impact of vaccine campaigns on local epidemics. We reviewed available vaccine efficacy and effectiveness studies to generate working estimates that can be used to parameterise simulation studies of vaccine impact.</ns3:p><ns3:p> <ns3:bold>Methods:</ns3:bold> We searched MEDLINE, the World Health Organization’s Institutional Repository for Information Sharing, medRxiv, and vaccine manufacturer websites for studies that evaluated the emerging data on COVID-19 vaccine efficacy and effectiveness. Studies providing an estimate of the efficacy or effectiveness of a COVID-19 vaccine using disaggregated data against SARS-CoV-2 infection, symptomatic disease, severe disease, death, or transmission were included. We extracted information on study population, variants of concern (VOC), vaccine platform, dose schedule, study endpoints, and measures of impact. We applied an evidence synthesis approach to capture a range of plausible and consistent parameters for vaccine efficacy and effectiveness that can be used to inform and explore a variety of vaccination strategies as the COVID-19 pandemic evolves.</ns3:p><ns3:p> <ns3:bold>Results:</ns3:bold> Of the 602 articles and reports identified, 53 were included in the analysis. The availability of vaccine efficacy and effectiveness estimates varied by vaccine and were limited for VOCs. Estimates for non-primary endpoints such as effectiveness against infection and onward transmission were sparse. Synthesised estimates were relatively consistent

Journal article

Williams LR, Ferguson NM, Donnelly CA, Grassly NCet al., 2021, Measuring vaccine efficacy against infection and disease in clinical trials: sources and magnitude of bias in COVID-19 vaccine efficacy estimates, Publisher: Cold Spring Harbor Laboratory

Background Phase III trials have estimated COVID-19 vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections.Methods We developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic and any SARS-CoV-2 infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections.Results VE against asymptomatic infection measured by PCR or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias towards underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4 to 77.1) and 70.9% (95% UI 49.8 to 80.7) respectively.Conclusion Multiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.

Working paper

Williams L, Marongiu A, Reilly G, Heinzkill M, Haubrich R, Castles R, Filippidis F, Ramroth Het al., 2020, Improving methods for patient-reported outcome (PRO) analyses in observational HIV studies, HIV Glasgow, 2020.

Poster

Che Q, Yang M, Wang X, Yang Q, Rose Williams L, Yang H, Zou J, Zeng K, Zhu Y, Chen Y, Chen Het al., 2019, Influence of physicochemical properties of metal modified ZSM-5 catalyst on benzene, toluene and xylene production from biomass catalytic pyrolysis, Bioresource Technology, Vol: 278, Pages: 248-254, ISSN: 0960-8524

Biomass catalytic pyrolysis with various metals (Zn, Fe, Ca, Ce and La) modified ZSM-5 catalysts were analyzed, in order to investigate the relationship between the physicochemical properties of catalysts and the benzene, toluene and xylene (BTX) products. Results revealed that the BTX products were positively correlated with the strong acid site contents of the catalysts. Appropriate amount (0.5–4 wt%) of loaded Zn species increased the strong acid site contents of the catalysts as well as BTX yields, and the highest yield of BTX was observed under Zn loading amount of 2 wt%. While excessive metal loading amount (10 wt%) decreased both the acidity and the physical properties of the catalyst, resulting in poor diffusion of reactants and products in the channel and decreased the BTX yield. It is recommended that ZSM-5 catalyst with higher strong acid site content and pore volume should be used for BTX production.

Journal article

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