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  1. Article ; Online: Challenges and opportunities in controlling mosquito-borne infections.

    Ferguson, Neil M

    Nature

    2018  Volume 559, Issue 7715, Page(s) 490–497

    Abstract: Mosquito-borne diseases remain a major cause of morbidity and mortality across the tropical regions. Despite much progress in the control of malaria, malaria-associated morbidity remains high, whereas arboviruses-most notably dengue-are responsible for a ...

    Abstract Mosquito-borne diseases remain a major cause of morbidity and mortality across the tropical regions. Despite much progress in the control of malaria, malaria-associated morbidity remains high, whereas arboviruses-most notably dengue-are responsible for a rising burden of disease, even in middle-income countries that have almost completely eliminated malaria. Here I discuss how new interventions offer the promise of considerable future reductions in disease burden. However, I emphasize that intervention programmes need to be underpinned by rigorous trials and quantitative epidemiological analyses. Such analyses suggest that the long-term goal of elimination is more feasible for dengue than for malaria, even if malaria elimination would offer greater overall health benefit to the public.
    MeSH term(s) Animals ; Dengue/mortality ; Dengue/prevention & control ; Dengue/transmission ; Gene Drive Technology ; Goals ; Humans ; Incidence ; Malaria/mortality ; Malaria/prevention & control ; Malaria/transmission ; Mosquito Control/methods ; Mosquito Vectors/genetics ; Mosquito Vectors/microbiology ; Pest Control, Biological/methods ; Vaccines ; Wolbachia/pathogenicity
    Chemical Substances Vaccines
    Language English
    Publishing date 2018-07-25
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 120714-3
    ISSN 1476-4687 ; 0028-0836
    ISSN (online) 1476-4687
    ISSN 0028-0836
    DOI 10.1038/s41586-018-0318-5
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  2. Article ; Online: Deriving fine-scale models of human mobility from aggregated origin-destination flow data.

    Ciavarella, Constanze / Ferguson, Neil M

    PLoS computational biology

    2021  Volume 17, Issue 2, Page(s) e1008588

    Abstract: The spatial dynamics of epidemics are fundamentally affected by patterns of human mobility. Mobile phone call detail records (CDRs) are a rich source of mobility data, and allow semi-mechanistic models of movement to be parameterised even for resource- ... ...

    Abstract The spatial dynamics of epidemics are fundamentally affected by patterns of human mobility. Mobile phone call detail records (CDRs) are a rich source of mobility data, and allow semi-mechanistic models of movement to be parameterised even for resource-poor settings. While the gravity model typically reproduces human movement reasonably well at the administrative level spatial scale, past studies suggest that parameter estimates vary with the level of spatial discretisation at which models are fitted. Given that privacy concerns usually preclude public release of very fine-scale movement data, such variation would be problematic for individual-based simulations of epidemic spread parametrised at a fine spatial scale. We therefore present new methods to fit fine-scale mathematical mobility models (here we implement variants of the gravity and radiation models) to spatially aggregated movement data and investigate how model parameter estimates vary with spatial resolution. We use gridded population data at 1km resolution to derive population counts at different spatial scales (down to ∼ 5km grids) and implement mobility models at each scale. Parameters are estimated from administrative-level flow data between overnight locations in Kenya and Namibia derived from CDRs: where the model spatial resolution exceeds that of the mobility data, we compare the flow data between a particular origin and destination with the sum of all model flows between cells that lie within those particular origin and destination administrative units. Clear evidence of over-dispersion supports the use of negative binomial instead of Poisson likelihood for count data with high values. Radiation models use fewer parameters than the gravity model and better predict trips between overnight locations for both considered countries. Results show that estimates for some parameters change between countries and with spatial resolution and highlight how imperfect flow data and spatial population distribution can influence model fit.
    MeSH term(s) Cell Phone ; Computer Simulation ; Epidemics ; Humans ; Information Storage and Retrieval ; Kenya ; Models, Statistical ; Monte Carlo Method ; Namibia ; Population Dynamics ; Reproducibility of Results ; Sensitivity and Specificity ; Travel
    Language English
    Publishing date 2021-02-11
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1008588
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  3. 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
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  4. 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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  5. Article ; Online: Targeting vaccinations for the licensed dengue vaccine: Considerations for serosurvey design.

    Imai, Natsuko / Ferguson, Neil M

    PloS one

    2018  Volume 13, Issue 6, Page(s) e0199450

    Abstract: Background: The CYD-TDV vaccine was unusual in that the recommended target population for vaccination was originally defined not only by age, but also by transmission setting as defined by seroprevalence. WHO originally recommended countries consider ... ...

    Abstract Background: The CYD-TDV vaccine was unusual in that the recommended target population for vaccination was originally defined not only by age, but also by transmission setting as defined by seroprevalence. WHO originally recommended countries consider vaccination against dengue with CYD-TDV vaccine in geographic settings only where prior infection with any dengue serotype, as measured by seroprevalence, was >170% in the target age group. Vaccine was not recommended in settings where seroprevalence was <50%. Test-and-vaccinate strategies suggested following new analysis by Sanofi will still require age-stratified seroprevalence surveys to optimise age-group targeting. Here we address considerations for serosurvey design in the context of vaccination program planning.
    Methods: To explore how the design of seroprevalence surveys affects estimates of transmission intensity, 100 age-specific seroprevalence surveys were simulated using a beta-binomial distribution and a simple catalytic model for different combinations of age-range, survey size, transmission setting, and test sensitivity/specificity. We then used a Metropolis-Hastings Markov Chain Monte-Carlo algorithm to estimate the force of infection from each simulated dataset.
    Results: Sampling from a wide age-range led to more accurate estimates than merely increasing sample size in a narrow age-range. This finding was consistent across all transmission settings. The optimum test sensitivity and specificity given an imperfect test differed by setting with high sensitivity being important in high transmission settings and high specificity important in low transmission settings.
    Conclusions: When assessing vaccination suitability by seroprevalence surveys, countries should ensure an appropriate age-range is sampled, considering epidemiological evidence about the local burden of disease.
    MeSH term(s) Adolescent ; Adult ; Child ; Child, Preschool ; Computer Simulation ; Dengue/epidemiology ; Dengue/immunology ; Dengue/transmission ; Dengue Vaccines/immunology ; Humans ; Infant ; Infant, Newborn ; Licensure ; Models, Biological ; Probability ; Sensitivity and Specificity ; Seroepidemiologic Studies ; Surveys and Questionnaires ; Vaccination ; Young Adult
    Chemical Substances Dengue Vaccines
    Language English
    Publishing date 2018-06-26
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0199450
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  6. Article ; Online: Seasonal and inter-annual drivers of yellow fever transmission in South America.

    Hamlet, Arran / Gaythorpe, Katy A M / Garske, Tini / Ferguson, Neil M

    PLoS neglected tropical diseases

    2021  Volume 15, Issue 1, Page(s) e0008974

    Abstract: In the last 20 years yellow fever (YF) has seen dramatic changes to its incidence and geographic extent, with the largest outbreaks in South America since 1940 occurring in the previously unaffected South-East Atlantic coast of Brazil in 2016-2019. While ...

    Abstract In the last 20 years yellow fever (YF) has seen dramatic changes to its incidence and geographic extent, with the largest outbreaks in South America since 1940 occurring in the previously unaffected South-East Atlantic coast of Brazil in 2016-2019. While habitat fragmentation and land-cover have previously been implicated in zoonotic disease, their role in YF has not yet been examined. We examined the extent to which vegetation, land-cover, climate and host population predicted the numbers of months a location reported YF per year and by each month over the time-period. Two sets of models were assessed, one looking at interannual differences over the study period (2003-2016), and a seasonal model looking at intra-annual differences by month, averaging over the years of the study period. Each was fit using hierarchical negative-binomial regression in an exhaustive model fitting process. Within each set, the best performing models, as measured by the Akaike Information Criterion (AIC), were combined to create ensemble models to describe interannual and seasonal variation in YF. The models reproduced the spatiotemporal heterogeneities in YF transmission with coefficient of determination (R2) values of 0.43 (95% CI 0.41-0.45) for the interannual model and 0.66 (95% CI 0.64-0.67) for the seasonal model. For the interannual model, EVI, land-cover and vegetation heterogeneity were the primary contributors to the variance explained by the model, and for the seasonal model, EVI, day temperature and rainfall amplitude. Our models explain much of the spatiotemporal variation in YF in South America, both seasonally and across the period 2003-2016. Vegetation type (EVI), heterogeneity in vegetation (perhaps a proxy for habitat fragmentation) and land cover explain much of the trends in YF transmission seen. These findings may help understand the recent expansions of the YF endemic zone, as well as to the highly seasonal nature of YF.
    MeSH term(s) Agriculture ; Climate ; Humans ; Seasons ; South America/epidemiology ; Yellow Fever/epidemiology ; Yellow Fever/transmission
    Language English
    Publishing date 2021-01-11
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2429704-5
    ISSN 1935-2735 ; 1935-2735
    ISSN (online) 1935-2735
    ISSN 1935-2735
    DOI 10.1371/journal.pntd.0008974
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  7. Article ; Online: Measuring Vaccine Efficacy Against Infection and Disease in Clinical Trials: Sources and Magnitude of Bias in Coronavirus Disease 2019 (COVID-19) Vaccine Efficacy Estimates.

    Williams, Lucy R / Ferguson, Neil M / Donnelly, Christl A / Grassly, Nicholas C

    Clinical infectious diseases : an official publication of the Infectious Diseases Society of America

    2021  Volume 75, Issue 1, Page(s) e764–e773

    Abstract: Background: Phase III trials have estimated coronavirus disease 2019 (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 ... ...

    Abstract Background: Phase III trials have estimated coronavirus disease 2019 (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 severe acute respiratory syndrome coronavirus 2 (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 polymerase chain reaction (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 toward 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] 38.4-77.1) and 70.9% (95% UI 49.8-80.7), 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.
    MeSH term(s) Ad26COVS1 ; Asymptomatic Infections ; Bias ; COVID-19/prevention & control ; COVID-19 Vaccines ; Humans ; SARS-CoV-2 ; Vaccine Efficacy
    Chemical Substances Ad26COVS1 (JT2NS6183B) ; COVID-19 Vaccines
    Language English
    Publishing date 2021-10-25
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1099781-7
    ISSN 1537-6591 ; 1058-4838
    ISSN (online) 1537-6591
    ISSN 1058-4838
    DOI 10.1093/cid/ciab914
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  8. Book: Statistical aspects of BSE and vCJD

    Donnelly, Christl A. / Ferguson, Neil M.

    models for epidemics

    (Monographs on statistics and applied probability ; 84)

    2000  

    Author's details Christl A. Donnelly ; Neil M. Ferguson
    Series title Monographs on statistics and applied probability ; 84
    Collection
    Language English
    Size 229 S. : graph. Darst.
    Publisher Chapman & Hall/CRC
    Publishing place Boca Raton u.a.
    Publishing country United States
    Document type Book
    HBZ-ID HT011146150
    ISBN 0-8493-0386-9 ; 978-0-8493-0386-9
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    2002 A 1409 order for loan Magazin

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  9. Article ; Online: Systematic selection between age and household structure for models aimed at emerging epidemic predictions.

    Pellis, Lorenzo / Cauchemez, Simon / Ferguson, Neil M / Fraser, Christophe

    Nature communications

    2020  Volume 11, Issue 1, Page(s) 906

    Abstract: Numerous epidemic models have been developed to capture aspects of human contact patterns, making model selection challenging when they fit (often-scarce) early epidemic data equally well but differ in predictions. Here we consider the invasion of a ... ...

    Abstract Numerous epidemic models have been developed to capture aspects of human contact patterns, making model selection challenging when they fit (often-scarce) early epidemic data equally well but differ in predictions. Here we consider the invasion of a novel directly transmissible infection and perform an extensive, systematic and transparent comparison of models with explicit age and/or household structure, to determine the accuracy loss in predictions in the absence of interventions when ignoring either or both social components. We conclude that, with heterogeneous and assortative contact patterns relevant to respiratory infections, the model's age stratification is crucial for accurate predictions. Conversely, the household structure is only needed if transmission is highly concentrated in households, as suggested by an empirical but robust rule of thumb based on household secondary attack rate. This work serves as a template to guide the simplicity/accuracy trade-off in designing models aimed at initial, rapid assessment of potential epidemic severity.
    MeSH term(s) Age Factors ; Communicable Diseases, Emerging/epidemiology ; Communicable Diseases, Emerging/transmission ; Epidemics/statistics & numerical data ; Family Characteristics ; Humans ; Models, Statistical
    Keywords covid19
    Language English
    Publishing date 2020-02-14
    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/s41467-019-14229-4
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  10. Article ; Online: Vaccines can save children with non-preventable diseases - Authors' reply.

    Gaythorpe, Katy A M / Toor, Jaspreet / Echeverria-Londono, Susy / Li, Xiang / Ferguson, Neil M

    Lancet (London, England)

    2021  Volume 397, Issue 10291, Page(s) 2251

    MeSH term(s) Child ; Humans ; Vaccines
    Chemical Substances Vaccines
    Language English
    Publishing date 2021-06-09
    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(21)01015-1
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