• Hello!

    I'm Ana Bento

    Postdoctoral Research Associate

    CEID - University of Georgia

  • Who

    I'm a population ecologist with a focus on infectious diseases. I earned my Ph.D. in Ecology and Evolution at Silwood Park, Imperial College London under the supervision of Prof. Mick Crawley. After a MRC postdoctoral fellowship with Prof. Christl Donnelly, at Imperial College, Infectious Diseases Epidemiology Department, I accepted a postdoctoral position at the Odum School of Ecology, UGA, to work with Prof. Pejman Rohani on the ecology immunology and evolution of vaccine preventable childhood diseases.


    I'm fascinated by trying to understand the frequency, magnitude and shape of seasonal disease dynamics and the effects of heterogeneity in a population. Primarily, identifying ecological, demographic and evolutionary drivers of seasonality of infectious disease systems, with the aim of informing vaccination and other control public health policies.


    I focus on vaccine preventable diseases dynamics, with a view to understanding fundamental processes in ecology and evolution. My ongoing research falls into the following themes: (i) time series analysis of big data; (ii) seasonal disease transmission; (iii) maternal immunization; (iv) effects of vaccines; and (v) phylodynamics and pathogen evolution.


    I use a combination of mathematical modelling, data analysis and cutting-edge statistical inference techniques to understand the ecology and evolution of infectious diseases of humans and population dynamics of wildlife. With these methods I am able to make precise, quantitative, testable predictions and confront process-based models with data. This is the central premise of my research program and the common thread of my work.

  • Ongoing projects

    A selection of projects I'm involved in -Much of my current research is based on understanding long-term data on spatio-temporal incidence patterns of microparasitic infections such as pertussis, measles and bovine tuberculosis. In my work, I formalize scientific hypotheses as mathematical models to make precise predictions and powerful inference.

    Bacterial Phylodynamics

    Despite high routine vaccination coverage, pertussis has become the most prevalent vaccine-preventable disease in many countries, since the 1990s. While a plethora of candidate explanations for this resurgence remain hotly debated, two main ideas focus on vaccine driven bacterial adaptation and on the change from whole cell to acellular vaccines. We employ generalized linear models within a Bayesian coalescent framework to formally tests drivers of evolution in Bordetella pertussis populations, and the role of allele shifts in the resurgence of pertussis.

    In collaboration with Pejman Rohani & Aaron King

    Vaccine hesitancy

    Vaccine hesitancy poses a clear barrier to covering the last mile in global disease eradication efforts for VPDs such as measles and pertussis. In this ongoing project we aim to characterize disease dynamics and vaccine coverage, estimate the epidemiological impact of vaccine hesitancy, and identify the spatial scale of herd immunity.

    Ecology of pertussis

    Formulation of mathematical models to confront them with age stratified incidence data to learn about the mechanisms that operate in the dynamics of infectious diseases and the consequences of vaccination policies. Currently, I'm using England & Wales incidence times series of pertussis for different vaccine eras.

    Impact of maternal vaccination

    The historical pertussis literature indicates that maternal vaccination may potentially lead to a reduction in the efficacy of routine infant immunization. We studied the possible downstream consequences of maternal immunization.

    In collaboration with Pejman Rohani & Aaron King

    Influenza viral attributes

    Emergence and pathogenesis of influenza viruses, with a focus on identification of attributes which influence tropism, pathogenicity, and evolution of influenza viruses.

    In collaboration with Jasmina Luczo, Mark Tompkins & Pejman Rohani

    Within herd dynamics

    Epidemiological impact of control & immunisation activities on within-herd bovine tuberculosis outbreaks

    In collaboration with Christl Donnelly

    Antiviral Influenza

    Computationally test the hypothesis that increased HA binding avidity is associated with increased rates of Oseltamivir resistance.

    In collaboration with Sam Scarpino & Deven Gokhale

    Environmental drivers of plant-herbivore dynamics

    In temperate regions the seasonal pattern of plant productivity and senescence is influenced strongly by the prevailing weather. For herbivores the onset of spring is particularly important for survival and growth, while subsequent plant production will potentially influence lactation and recovery of body mass before the next breeding season.

    In collaboration with Mick Crawley, Josephine Pemberton, Steve Albon & Dan Nussey

  • Selected Publications

    Core pertussis transmission groups in England and Wales: A tale of two eras

    Bento et al. 2018. Vaccine

    A simulation study on the relative role of age groups under diering pertussis transmission scenarios

    Bento et al. 2018. BioRxiv

    Epidemiological impact of control and immunisation activities on within-herd bovine tuberculosis outbreaks

    Bento & Donnelly. 2018. accepted (available upon request)

    Maternal pertussis immunisation: clinical gains and epidemiological legacy

    Bento, King & Rohani. 2017. Eurosurveillance

    Forecasting epidemiological consequences of maternal immunization

    Bento & Rohani 2016. Clinical Infectious Diseases

    Physiological proteins in resource-limited herbivores experiencing a population die-off

    Garnier, Bento et al. 2017

    EpiJSON: A unifed data-format for epidemiology

    Finnie, Bento et al. 2016. Epidemics

    A review of epidemiological parameters from Ebola outbreaks to inform early public health decision-making

    Bento et al. 2015. Nature Scientific Data

    Exploration of the power of routine surveillance data to assess the impacts of industry-led badger culling on bovine tuberculosis incidence in cattle herds

    Bento et al. 2015. Veterinary Record

    Multiple pathways mediate the effects of climate change on maternal reproductive traits in a red deer population

    Stoffer, Bento et al. 2014. Ecology

    B. pertussis epidemiology, transmission & evolution in the vaccine era

    Bento, King & Rohani. nearing submission (available upon request)

    Won't you be my neighbor?

    Bento et al. in prep (available upon request)

    Warming and vegetation community dynamics in a wild red deer population

    Bento et al. nearing submission (available upon request)

    Spring temperature and rain mediate summer growth in the Park Grass experiment

    Bento et al. nearing submission (available upon request)

    Climatic effects of plant productivity and herbivore performance in St Kilda

    Bento et al. nearing submission (available upon request)

  • Teaching

    I have been fortunate to create and teach a variety of classes and mentor several outstanding undergraduate and MSc students.


    Three unifying principles guide my teaching and mentoring approach:

    (i) combining foundational principles with practical application

    (ii) guided active learning

    (iii) quantitative reasoning


    These are some courses I have designed and or taught:

    Machine learning

    Introduction to machine learning with R (2018 @ Odum School of Ecology)

    Computational Modeling

    Computational Modeling Workshop (May 2018 @ IDEAS, UGA)

    Introduction to modelling

    Introduction to modelling with R (2017 @ Odum School of Ecology)

    Mathematical Models

    Introduction to Mathematical Models Epidemiology and Control of Infectious Diseases (2013-2014 @ Infectious Disease Epi. Dept Imperial)

    Generalised Linear Modeling in R

    Statistics and Computing in R (2009-2012 @ Silwood Park Imperial)

  • Check out my latest updates!

    I tweet about disease & evolutionary ecology, science & data viz.