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  1. Article ; Online: Impact of proactive and reactive vaccination strategies for health-care workers against MERS-CoV: a mathematical modelling study.

    Laydon, Daniel J / Cauchemez, Simon / Hinsley, Wes R / Bhatt, Samir / Ferguson, Neil M

    The Lancet. Global health

    2023  Volume 11, Issue 5, Page(s) e759–e769

    Abstract: Background: Several vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers.: ... ...

    Abstract Background: Several vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers.
    Methods: Using data from the 2013-14 Saudi Arabia epidemic, we use a counterfactual analysis on inferred transmission trees (who-infected-whom analysis) to assess the potential impact of vaccination campaigns targeting health-care workers, as quantified by the proportion of cases or deaths averted. We investigate the conditions under which proactive campaigns (ie vaccinating in anticipation of the next outbreak) would outperform reactive campaigns (ie vaccinating in response to an unfolding outbreak), considering vaccine efficacy, duration of vaccine protection, effectiveness of animal reservoir control measures, wait (time between vaccination and next outbreak, for proactive campaigns), reaction time (for reactive campaigns), and spatial level (hospital, regional, or national, for reactive campaigns). We also examine the relative efficiency (cases averted per thousand doses) of different strategies.
    Findings: The spatial scale of reactive campaigns is crucial. Proactive campaigns outperform campaigns that vaccinate health-care workers in response to outbreaks at their hospital, unless vaccine efficacy has waned significantly. However, reactive campaigns at the regional or national levels consistently outperform proactive campaigns, regardless of vaccine efficacy. When considering the number of cases averted per vaccine dose administered, the rank order is reversed: hospital-level reactive campaigns are most efficient, followed by regional-level reactive campaigns, with national-level and proactive campaigns being least efficient. If the number of cases required to trigger reactive vaccination increases, the performance of hospital-level campaigns is greatly reduced; the impact of regional-level campaigns is variable, but that of national-level campaigns is preserved unless triggers have high thresholds.
    Interpretation: Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating only health-care workers, underlining the need for countries at risk of outbreaks to stockpile vaccines when available.
    Funding: UK Medical Research Council, UK National Institute for Health Research, UK Research and Innovation, UK Academy of Medical Sciences, The Novo Nordisk Foundation, The Schmidt Foundation, and Investissement d'Avenir France.
    MeSH term(s) Humans ; Middle East Respiratory Syndrome Coronavirus ; Vaccination ; Health Personnel ; Disease Outbreaks/prevention & control ; Epidemics/prevention & control
    Language English
    Publishing date 2023-04-14
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2723488-5
    ISSN 2214-109X ; 2214-109X
    ISSN (online) 2214-109X
    ISSN 2214-109X
    DOI 10.1016/S2214-109X(23)00117-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: The impact of health inequity on regional variation of COVID-19 transmission in England

    Rawson, Thomas / Hinsley, Wes / Sonabend, Raphael / Semenova, Elizaveta / Cori, Anne / Ferguson, Neil M

    medRxiv

    Abstract: Considerable spatial heterogeneity has been observed in COVID-19 transmission across administrative regions of England throughout the pandemic. This study investigates what drives these differences. We constructed a probabilistic case count model for 306 ...

    Abstract Considerable spatial heterogeneity has been observed in COVID-19 transmission across administrative regions of England throughout the pandemic. This study investigates what drives these differences. We constructed a probabilistic case count model for 306 administrative regions of England across 95 weeks, fit using a Bayesian evidence synthesis framework. We include the mechanistic impact of acquired immunity, of spatial exportation of cases, and 16 spatially-varying socio-economic, socio-demographic, health, and mobility variables. Model comparison assesses the relative contributions of these respective mechanisms. We find that regionally-varying and time-varying differences in week-to-week transmission were definitively associated with differences in: time spent at home, variant-of-concern proportion, and adult social care funding. However, model comparison demonstrates that the mechanistic impact of these terms was of negligible impact compared to the role of spatial exportation between regions. While these results confirm the impact of some, but not all, measures of regional inequity in England, our work corroborates the finding that observed differences in regional disease transmission during the pandemic were predominantly driven by underlying epidemiological factors rather than the demography and health inequity between regions.
    Keywords covid19
    Language English
    Publishing date 2024-04-22
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2024.04.20.24306121
    Database COVID19

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  3. Article ; Online: Misclassification bias in estimating clinical severity of SARS-CoV-2 variants - Authors' reply.

    Nyberg, Tommy / Ferguson, Neil M / Blake, Joshua / Hinsley, Wes / Bhatt, Samir / De Angelis, Daniela / Thelwall, Simon / Presanis, Anne M

    Lancet (London, England)

    2022  Volume 400, Issue 10355, Page(s) 809–810

    MeSH term(s) COVID-19 ; Humans ; SARS-CoV-2/genetics
    Language English
    Publishing date 2022-09-07
    Publishing country England
    Document type Letter ; Comment
    ZDB-ID 3306-6
    ISSN 1474-547X ; 0023-7507 ; 0140-6736
    ISSN (online) 1474-547X
    ISSN 0023-7507 ; 0140-6736
    DOI 10.1016/S0140-6736(22)01432-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Data pipelines in a public health emergency: The human in the machine.

    Gaythorpe, Katy A M / Fitzjohn, Rich G / Hinsley, Wes / Imai, Natsuko / Knock, Edward S / Perez Guzman, Pablo N / Djaafara, Bimandra / Fraser, Keith / Baguelin, Marc / Ferguson, Neil M

    Epidemics

    2023  Volume 43, Page(s) 100676

    Abstract: In an emergency epidemic response, data providers supply data on a best-faith effort to modellers and analysts who are typically the end user of data collected for other primary purposes such as to inform patient care. Thus, modellers who analyse ... ...

    Abstract In an emergency epidemic response, data providers supply data on a best-faith effort to modellers and analysts who are typically the end user of data collected for other primary purposes such as to inform patient care. Thus, modellers who analyse secondary data have limited ability to influence what is captured. During an emergency response, models themselves are often under constant development and require both stability in their data inputs and flexibility to incorporate new inputs as novel data sources become available. This dynamic landscape is challenging to work with. Here we outline a data pipeline used in the ongoing COVID-19 response in the UK that aims to address these issues. A data pipeline is a sequence of steps to carry the raw data through to a processed and useable model input, along with the appropriate metadata and context. In ours, each data type had an individual processing report, designed to produce outputs that could be easily combined and used downstream. Automated checks were in-built and added as new pathologies emerged. These cleaned outputs were collated at different geographic levels to provide standardised datasets. Finally, a human validation step was an essential component of the analysis pathway and permitted more nuanced issues to be captured. This framework allowed the pipeline to grow in complexity and volume and facilitated the diverse range of modelling approaches employed by researchers. Additionally, every report or modelling output could be traced back to the specific data version that informed it ensuring reproducibility of results. Our approach has been used to facilitate fast-paced analysis and has evolved over time. Our framework and its aspirations are applicable to many settings beyond COVID-19 data, for example for other outbreaks such as Ebola, or where routine and regular analyses are required.
    MeSH term(s) Humans ; COVID-19/epidemiology ; Public Health ; Reproducibility of Results ; Disease Outbreaks
    Language English
    Publishing date 2023-03-08
    Publishing country Netherlands
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2467993-8
    ISSN 1878-0067 ; 1755-4365
    ISSN (online) 1878-0067
    ISSN 1755-4365
    DOI 10.1016/j.epidem.2023.100676
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Efficacy profile of the CYD-TDV dengue vaccine revealed by Bayesian survival analysis of individual-level phase III data.

    Laydon, Daniel J / Dorigatti, Ilaria / Hinsley, Wes R / Nedjati-Gilani, Gemma / Coudeville, Laurent / Ferguson, Neil M

    eLife

    2021  Volume 10

    Abstract: Background: Sanofi-Pasteur's CYD-TDV is the only licensed dengue vaccine. Two phase three trials showed higher efficacy in seropositive than seronegative recipients. Hospital follow-up revealed increased hospitalisation in 2-5- year-old vaccinees, where ...

    Abstract Background: Sanofi-Pasteur's CYD-TDV is the only licensed dengue vaccine. Two phase three trials showed higher efficacy in seropositive than seronegative recipients. Hospital follow-up revealed increased hospitalisation in 2-5- year-old vaccinees, where serostatus and age effects were unresolved.
    Methods: We fit a survival model to individual-level data from both trials, including year 1 of hospital follow-up. We determine efficacy by age, serostatus, serotype and severity, and examine efficacy duration and vaccine action mechanism.
    Results: Our modelling indicates that vaccine-induced immunity is long-lived in seropositive recipients, and therefore that vaccinating seropositives gives higher protection than two natural infections. Long-term increased hospitalisation risk outweighs short-lived immunity in seronegatives. Independently of serostatus, transient immunity increases with age, and is highest against serotype 4. Benefit is higher in seropositives, and risk enhancement is greater in seronegatives, against hospitalised disease than against febrile disease.
    Conclusions: Our results support vaccinating seropositives only. Rapid diagnostic tests would enable viable 'screen-then-vaccinate' programs. Since CYD-TDV acts as a silent infection, long-term safety of other vaccine candidates must be closely monitored.
    Funding: Bill & Melinda Gates Foundation, National Institute for Health Research, UK Medical Research Council, Wellcome Trust, Royal Society.
    Clinical trial number: NCT01373281 and NCT01374516.
    MeSH term(s) Adolescent ; Bayes Theorem ; Child ; Child, Preschool ; Dengue/pathology ; Dengue/prevention & control ; Dengue Vaccines/adverse effects ; Dengue Vaccines/immunology ; Dengue Virus/classification ; Humans ; Models, Biological ; Serogroup ; Survival Analysis
    Chemical Substances Dengue Vaccines
    Language English
    Publishing date 2021-07-02
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2687154-3
    ISSN 2050-084X ; 2050-084X
    ISSN (online) 2050-084X
    ISSN 2050-084X
    DOI 10.7554/eLife.65131
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Modelling the impact of the tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns.

    Laydon, Daniel J / Mishra, Swapnil / Hinsley, Wes R / Samartsidis, Pantelis / Flaxman, Seth / Gandy, Axel / Ferguson, Neil M / Bhatt, Samir

    BMJ open

    2021  Volume 11, Issue 4, Page(s) e050346

    Abstract: Objective: To measure the effects of the tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.7 variant of concern.: Design: This is a modelling study combining estimates of ...

    Abstract Objective: To measure the effects of the tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.7 variant of concern.
    Design: This is a modelling study combining estimates of real-time reproduction number
    Setting: The UK at lower tier local authority (LTLA) level. 310 LTLAs were included in the analysis.
    Primary and secondary outcome measures: Reduction in real-time reproduction number
    Results: Nationally, transmission increased between July and late September, regional differences notwithstanding. Immediately prior to the introduction of the tier system,
    Conclusions: The relatively small effect sizes found in this analysis demonstrate that interventions at least as stringent as tier 3 are required to suppress transmission, especially considering more transmissible variants, at least until effective vaccination is widespread or much greater population immunity has amassed.
    MeSH term(s) Bayes Theorem ; COVID-19 ; Communicable Disease Control ; Humans ; Pandemics ; SARS-CoV-2 ; United Kingdom/epidemiology
    Language English
    Publishing date 2021-04-22
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2599832-8
    ISSN 2044-6055 ; 2044-6055
    ISSN (online) 2044-6055
    ISSN 2044-6055
    DOI 10.1136/bmjopen-2021-050346
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Exploring relationships between drought and epidemic cholera in Africa using generalised linear models.

    Charnley, Gina E C / Kelman, Ilan / Green, Nathan / Hinsley, Wes / Gaythorpe, Katy A M / Murray, Kris A

    BMC infectious diseases

    2021  Volume 21, Issue 1, Page(s) 1177

    Abstract: Background: Temperature and precipitation are known to affect Vibrio cholerae outbreaks. Despite this, the impact of drought on outbreaks has been largely understudied. Africa is both drought and cholera prone and more research is needed in Africa to ... ...

    Abstract Background: Temperature and precipitation are known to affect Vibrio cholerae outbreaks. Despite this, the impact of drought on outbreaks has been largely understudied. Africa is both drought and cholera prone and more research is needed in Africa to understand cholera dynamics in relation to drought.
    Methods: Here, we analyse a range of environmental and socioeconomic covariates and fit generalised linear models to publicly available national data, to test for associations with several indices of drought and make cholera outbreak projections to 2070 under three scenarios of global change, reflecting varying trajectories of CO
    Results: The best-fit model implies that drought is a significant risk factor for African cholera outbreaks, alongside positive effects of population, temperature and poverty and a negative effect of freshwater withdrawal. The projections show that following stringent emissions pathways and expanding sustainable development may reduce cholera outbreak occurrence in Africa, although these changes were spatially heterogeneous.
    Conclusions: Despite an effect of drought in explaining recent cholera outbreaks, future projections highlighted the potential for sustainable development gains to offset drought-related impacts on cholera risk. Future work should build on this research investigating the impacts of drought on cholera on a finer spatial scale and potential non-linear relationships, especially in high-burden countries which saw little cholera change in the scenario analysis.
    MeSH term(s) Africa/epidemiology ; Cholera/epidemiology ; Disease Outbreaks ; Droughts ; Epidemics ; Humans ; Linear Models
    Language English
    Publishing date 2021-11-22
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041550-3
    ISSN 1471-2334 ; 1471-2334
    ISSN (online) 1471-2334
    ISSN 1471-2334
    DOI 10.1186/s12879-021-06856-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Author Correction: Epidemiological drivers of transmissibility and severity of SARS-CoV-2 in England.

    Perez-Guzman, Pablo N / Knock, Edward / Imai, Natsuko / Rawson, Thomas / Elmaci, Yasin / Alcada, Joana / Whittles, Lilith K / Thekke Kanapram, Divya / Sonabend, Raphael / Gaythorpe, Katy A M / Hinsley, Wes / FitzJohn, Richard G / Volz, Erik / Verity, Robert / Ferguson, Neil M / Cori, Anne / Baguelin, Marc

    Nature communications

    2023  Volume 14, Issue 1, Page(s) 8099

    Language English
    Publishing date 2023-12-07
    Publishing country England
    Document type Published Erratum
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-44062-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Epidemiological drivers of transmissibility and severity of SARS-CoV-2 in England.

    Perez-Guzman, Pablo N / Knock, Edward / Imai, Natsuko / Rawson, Thomas / Elmaci, Yasin / Alcada, Joana / Whittles, Lilith K / Thekke Kanapram, Divya / Sonabend, Raphael / Gaythorpe, Katy A M / Hinsley, Wes / FitzJohn, Richard G / Volz, Erik / Verity, Robert / Ferguson, Neil M / Cori, Anne / Baguelin, Marc

    Nature communications

    2023  Volume 14, Issue 1, Page(s) 4279

    Abstract: As the SARS-CoV-2 pandemic progressed, distinct variants emerged and dominated in England. These variants, Wildtype, Alpha, Delta, and Omicron were characterized by variations in transmissibility and severity. We used a robust mathematical model and ... ...

    Abstract As the SARS-CoV-2 pandemic progressed, distinct variants emerged and dominated in England. These variants, Wildtype, Alpha, Delta, and Omicron were characterized by variations in transmissibility and severity. We used a robust mathematical model and Bayesian inference framework to analyse epidemiological surveillance data from England. We quantified the impact of non-pharmaceutical interventions (NPIs), therapeutics, and vaccination on virus transmission and severity. Each successive variant had a higher intrinsic transmissibility. Omicron (BA.1) had the highest basic reproduction number at 8.3 (95% credible interval (CrI) 7.7-8.8). Varying levels of NPIs were crucial in controlling virus transmission until population immunity accumulated. Immune escape properties of Omicron decreased effective levels of immunity in the population by a third. Furthermore, in contrast to previous studies, we found Alpha had the highest basic infection fatality ratio (2.9%, 95% CrI 2.7-3.2), followed by Delta (2.2%, 95% CrI 2.0-2.4), Wildtype (1.2%, 95% CrI 1.1-1.2), and Omicron (0.7%, 95% CrI 0.6-0.8). Our findings highlight the importance of continued surveillance. Long-term strategies for monitoring and maintaining effective immunity against SARS-CoV-2 are critical to inform the role of NPIs to effectively manage future variants with potentially higher intrinsic transmissibility and severe outcomes.
    MeSH term(s) Humans ; SARS-CoV-2/genetics ; Bayes Theorem ; COVID-19/epidemiology ; England/epidemiology
    Language English
    Publishing date 2023-07-17
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-39661-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Quantifying the effect of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study.

    Imai, Natsuko / Rawson, Thomas / Knock, Edward S / Sonabend, Raphael / Elmaci, Yasin / Perez-Guzman, Pablo N / Whittles, Lilith K / Kanapram, Divya Thekke / Gaythorpe, Katy A M / Hinsley, Wes / Djaafara, Bimandra A / Wang, Haowei / Fraser, Keith / FitzJohn, Richard G / Hogan, Alexandra B / Doohan, Patrick / Ghani, Azra C / Ferguson, Neil M / Baguelin, Marc /
    Cori, Anne

    The Lancet. Public health

    2023  Volume 8, Issue 3, Page(s) e174–e183

    Abstract: Background: The UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3 weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the SARS-CoV-2 alpha ...

    Abstract Background: The UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3 weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the SARS-CoV-2 alpha variant prompted the UK to extend the interval between doses to 12 weeks. In this study, we aimed to quantify the effect of delaying the second vaccine dose in England.
    Methods: We used a previously described model of SARS-CoV-2 transmission, calibrated to COVID-19 surveillance data from England, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data, using a Bayesian evidence-synthesis framework. We modelled and compared the epidemic trajectory in the counterfactual scenario in which vaccine doses were administered 3 weeks apart against the real reported vaccine roll-out schedule of 12 weeks. We estimated and compared the resulting numbers of daily infections, hospital admissions, and deaths. In sensitivity analyses, we investigated scenarios spanning a range of vaccine effectiveness and waning assumptions.
    Findings: In the period from Dec 8, 2020, to Sept 13, 2021, the number of individuals who received a first vaccine dose was higher under the 12-week strategy than the 3-week strategy. For this period, we estimated that delaying the interval between the first and second COVID-19 vaccine doses from 3 to 12 weeks averted a median (calculated as the median of the posterior sample) of 58 000 COVID-19 hospital admissions (291 000 cumulative hospitalisations [95% credible interval 275 000-319 000] under the 3-week strategy vs 233 000 [229 000-238 000] under the 12-week strategy) and 10 100 deaths (64 800 deaths [60 200-68 900] vs 54 700 [52 800-55 600]). Similarly, we estimated that the 3-week strategy would have resulted in more infections compared with the 12-week strategy. Across all sensitivity analyses the 3-week strategy resulted in a greater number of hospital admissions. In results by age group, the 12-week strategy led to more hospitalisations and deaths in older people in spring 2021, but fewer following the emergence of the delta variant during summer 2021.
    Interpretation: England's delayed-second-dose vaccination strategy was informed by early real-world data on vaccine effectiveness in the context of limited vaccine supplies in a growing epidemic. Our study shows that rapidly providing partial (single-dose) vaccine-induced protection to a larger proportion of the population was successful in reducing the burden of COVID-19 hospitalisations and deaths overall.
    Funding: UK National Institute for Health Research; UK Medical Research Council; Community Jameel; Wellcome Trust; UK Foreign, Commonwealth and Development Office; Australian National Health and Medical Research Council; and EU.
    MeSH term(s) Humans ; Aged ; Infant ; COVID-19 Vaccines ; COVID-19 ; Bayes Theorem ; Seroepidemiologic Studies ; Australia ; SARS-CoV-2 ; England
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2023-02-09
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2468-2667
    ISSN (online) 2468-2667
    DOI 10.1016/S2468-2667(22)00337-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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