Daniel Stocks | University of Bristol (original) (raw)
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Papers by Daniel Stocks
medRxiv (Cold Spring Harbor Laboratory), Feb 9, 2024
Introduction: Future COVID-19 vaccine programmes need to take into account the variable responses... more Introduction: Future COVID-19 vaccine programmes need to take into account the variable responses elicited by different vaccines and their waning protection over time. Existing descriptions of antibody response to COVID-19 vaccination convey limited information about the mechanisms of antibody production and maintenance. Methods: We describe the antibody dynamics elicited by COVID-19 vaccination with two biologically-motivated mathematical models of antibody production by plasma cells and subsequent decay. We fit the models using Markov Chain Monte Carlo to seroprevalence data from 14,602 uninfected individuals collected via the primary care network in England between May 2020 and September 2022. We ensure our models are structurally and practically identifiable when using antibody data alone. We analyse the effect of age, vaccine type, number of doses, and the interval between doses on antibody production and longevity of response. Results: We find evidence that individuals over 35 years of age who received a second dose of ChAdOx1-S generate a persistent antibody response suggestive 1 .
We investigate the impact of vaccination and asymptomatic testing uptake on SARS- CoV-2 transmiss... more We investigate the impact of vaccination and asymptomatic testing uptake on SARS- CoV-2 transmission in a university student population using a stochastic compartmental model. We find that the magnitude and timing of outbreaks is highly variable depending on the transmissibility of the most dominant strain of SARS CoV-2 and under different vaccine uptake levels and efficacies. When delta is the dominant strain, low level interventions (no asymptomatic testing, 30% vaccinated with a vaccine that is 80% effective at reducing infection) lead to 53-71% of students become infected during the first term. Asymptomatic testing is most useful when vaccine uptake is low: when 30% of students are vaccinated, 90% uptake of asymptomatic testing leads to almost half the case numbers. With high interventions (90% using asymptomatic testing, 90% vaccinated) cumulative incidence is 7-9%, with around 80% of these cases estimated to be asymptomatic. However, under emergence of a new variant that is at...
Contact tracing is an important tool for controlling the spread of infectious diseases, including... more Contact tracing is an important tool for controlling the spread of infectious diseases, including COVID-19. Here, we investigate the spread of COVID-19 and the effectiveness of contact tracing in a university population, using a data-driven ego-centric network model constructed with social contact data collected during 2020 and similar data collected in 2010. We find that during 2020, university staff and students consistently reported fewer social contacts than in 2010, however those contacts occurred more frequently and were of longer duration. We find that contact tracing in the presence of social distancing is less impactful than without social distancing. By combining multiple data sources, we show that University-aged populations are likely to develop asymptomatic COVID-19 infections. We find that asymptomatic index cases cannot be reliably back-traced through contact tracing and consequently transmission in their social network is not significantly reduced through contact tra...
medRxiv (Cold Spring Harbor Laboratory), Feb 9, 2024
Introduction: Future COVID-19 vaccine programmes need to take into account the variable responses... more Introduction: Future COVID-19 vaccine programmes need to take into account the variable responses elicited by different vaccines and their waning protection over time. Existing descriptions of antibody response to COVID-19 vaccination convey limited information about the mechanisms of antibody production and maintenance. Methods: We describe the antibody dynamics elicited by COVID-19 vaccination with two biologically-motivated mathematical models of antibody production by plasma cells and subsequent decay. We fit the models using Markov Chain Monte Carlo to seroprevalence data from 14,602 uninfected individuals collected via the primary care network in England between May 2020 and September 2022. We ensure our models are structurally and practically identifiable when using antibody data alone. We analyse the effect of age, vaccine type, number of doses, and the interval between doses on antibody production and longevity of response. Results: We find evidence that individuals over 35 years of age who received a second dose of ChAdOx1-S generate a persistent antibody response suggestive 1 .
We investigate the impact of vaccination and asymptomatic testing uptake on SARS- CoV-2 transmiss... more We investigate the impact of vaccination and asymptomatic testing uptake on SARS- CoV-2 transmission in a university student population using a stochastic compartmental model. We find that the magnitude and timing of outbreaks is highly variable depending on the transmissibility of the most dominant strain of SARS CoV-2 and under different vaccine uptake levels and efficacies. When delta is the dominant strain, low level interventions (no asymptomatic testing, 30% vaccinated with a vaccine that is 80% effective at reducing infection) lead to 53-71% of students become infected during the first term. Asymptomatic testing is most useful when vaccine uptake is low: when 30% of students are vaccinated, 90% uptake of asymptomatic testing leads to almost half the case numbers. With high interventions (90% using asymptomatic testing, 90% vaccinated) cumulative incidence is 7-9%, with around 80% of these cases estimated to be asymptomatic. However, under emergence of a new variant that is at...
Contact tracing is an important tool for controlling the spread of infectious diseases, including... more Contact tracing is an important tool for controlling the spread of infectious diseases, including COVID-19. Here, we investigate the spread of COVID-19 and the effectiveness of contact tracing in a university population, using a data-driven ego-centric network model constructed with social contact data collected during 2020 and similar data collected in 2010. We find that during 2020, university staff and students consistently reported fewer social contacts than in 2010, however those contacts occurred more frequently and were of longer duration. We find that contact tracing in the presence of social distancing is less impactful than without social distancing. By combining multiple data sources, we show that University-aged populations are likely to develop asymptomatic COVID-19 infections. We find that asymptomatic index cases cannot be reliably back-traced through contact tracing and consequently transmission in their social network is not significantly reduced through contact tra...