Who
I'm an assistant professor at Cornell University Vet School. I lead a team of transdisciplinary researchers to shape, develop and coordinate integrative research into how data-driven modeling can end current and prevent future pandemics.. I'm a disease ecologist with a focus on ecology and evolution of infectious diseases. I earned my Ph.D. in Ecology & Evolution at Silwood Park, Imperial College London. After a MRC postdoctoral fellowship (2013-2015) @ Imperial College, Infectious Diseases Epidemiology Department, I took a postdoctoral position @ the Odum School of Ecology, UGA, on the ecology & evolution of vaccine preventable childhood diseases (2015-2019). Prior to joining Cornell, I was faculty at IU SPH (2019-2023), and while on extended sabattical, I took a position at Rockefeller Foundation (2022-2023) as Director of Science.
What
I am building a transdisciplinary research program that leverages mathematical and computational modeling, machine learning, and data science to identify the eco-evolutionary, demographic, and environmental drivers of pathogen emergence, persistence, and spread. My lab focuses on the ecology of infectious diseases in humans and other animals. Our research agenda seeks to understand the dynamics of biological populations and epidemics, focusing on how to bring experimental and observational data together with mathematical theory. Tackling biological questions of public application and importance. The majority of my body of work has been on vaccine preventable diseases dynamics, with a view to understanding fundamental processes in ecology and evolution. The lab ongoing research falls into the following themes: (i) pathogen evolution and phylodynamics; (ii) seasonal disease transmission; (iii) anthropogenic effects (e.g. vaccines); (iv) adaptive behavior.
Why
I'm fascinated by trying to understand the frequency, magnitude and shape of seasonal disease dynamics and the effects of population heterogeneity. Primarily, identifying evolutionary, ecological and demographic drivers of (re-) emergence and seasonality of infectious disease systems, with the aim of informing vaccination and other control public health policies. Scaling up individual-level interactions to understand the population-level outcomes (e.g., the evolution of virulence or immune evasion).
How
At the Bento Lab our approach is to develop theoretical models to understand how human and other animal systems behave generally, while simultaneously seeking to confront and validate models with data and make predictions. We use a combination of mathematical modelling, phylodynamics approaches and cutting-edge statistical inference techniques. We focus on developing coupled models (epi-econ, evo-eco) to holistically understand a system. With these methods we are able to make quantitative, testable predictions and confront process-based models with parallel data streams. This is the central premise of my lab's research program and the common thread of our work.
Selected ongoing projects
A selection of projects our lab is involved is based on understanding long-term data on spatio-temporal incidence patterns of microparasitic infections such as pertussis and measles. In addition, Some new projects on COVID-19 and schistosomiasis. We formalize scientific hypotheses as mathematical models to make precise predictions and powerful inference.
Adaptive behavior and disease transmission
Integrative Epi-economic framework to understand adaptive changes in behavior and transmission consequences
In collaboration with Dan Kaffine Akhil Rao & Antonio Bento
Evolution of resistance to Schistosomiasis
Investigating population structure and differential transmission potential in snail populations in Senegal.
In collaboration with Jason Rohr, Maurine Neiman & Curt Lively
Alpha and Beta CoVs spillover risk
Spillover risk surveillance- big brown bats in Colorado
In collaboration with Rebekah Kading
Disease spreading modeling through social and genomic data of SARS-CoV-2 in the United States
Integrating paralel data streams
In collaboration with Carla Mavian
Bacterial Evolutionary Signatures
We are developing holistic mechanistic models of pertussis evolution for countries under different vaccine regimes
In collaboration with Andy Preston, Matthew Hahn & Michael Weigand
Tick borne emergence
Using Indiana as an Early Warning System for tick expansion in the Midwest. Phylogeographic analysis of tick and pathogen diversity and disease dynamics
In collaboration with Karo Oomodior, Keith Clay, Curt Lively & Ellen Ketterson
Evolution of antiviral resistance
Computationally test the hypothesis that increased HA binding avidity is associated with increased rates of Oseltamivir resistance.
In collaboration with Sam Scarpino
Mathematical models for MBDs
In collaboration with Marco Ajelli & others
Selected Publications
For a complete list of publications check my google scholar. Brief description below with links for the publications
Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data
Manica et al 2023 Epidemiology & Infection
Genomic epidemiology sheds light on the recent spatio-temporal dynamics of Yellow Fever virus and the spatial corridor that fueled its ongoing emergence in southern Brazil
Giovanetti et al 2023 MedRxiv
Wastewater surveillance of pathogens can inform public health responses
Diamond et al 2022 Nature Medicine
Ash et al Nature comms 2022
Model-based evaluation of alternative reactive class closure strategies against COVID-19
Liu et al 2022 Nature comms
Designing isolation guidelines for COVID-19 patients with rapid antigen tests
Jeong et al Nat comms 2022
Vaccinations Against COVID-19 May Have Averted Up To 140,000 Deaths In The United States
Gupta et al 2021 Health Affairs
Daniels et al JAMA Cardio. 2021
Global effects of delays in detection of COVID-19
nearing submission (available upon request)
Information Seeking Responses to News of Local COVID-19 Cases: Evidence from Internet Search Data
Bento et al PNAS 2020
Effects of mitigation strategies on COVID-19 averted cases in Sichuan, China
Liu et al. Plos Comp Bio 2020
COVID-19 incidence in the county increased on average by a statistically significant 0.024 per thousand residents
Andersen et al. 2020
Evolutionary consequences of feedbacks between within-host competition and disease control
Greischar et al. JID 2020
Inferring Timing of Infection Using Within-host SARS-CoV-2 Infection Dynamics Model: Are “Imported Cases” Truly Imported?
Ejima et al medRviv 2020
Core pertussis transmission groups in England and Wales: A tale of two eras
Bento et al. 2018. Vaccine
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
Finnie et al. 2016. Epidemics
A review of epidemiological parameters from Ebola outbreaks to inform early public health decision-making
Garnier et al. 2017
Exploration of the power of routine surveillance data to assess the impacts of industry-led badger culling on bovine tuberculosis incidence in cattle herds
van Kerkove et al. 2015. Scientific Data
Multiple pathways mediate the effects of climate change on maternal reproductive traits in a red deer population
Donnelly et al. 2015. Veterinary Record
The Bento Lab
Get to know us & join us!
Ana Bento
PI
Yun Tao
Research Scientist
Agastya Mondal
Analyst
Engineer & product developer
Mina Parastarn
Engineer
Cate Heine
Analyst
Margot
Mascot
Kaithlyn Jonhson Postdoc
Zachary Susswein
Analyst
Maria Litvinova Former Postdoc
Seth Edmunds Former Phd Student
Varun Rao Former PhD Student
Teaching | Mentoring | Workshops
I have been fortunate to create and teach a variety of classes and mentor several outstanding undergraduate and MSc. and Ph.D. students.
Three unifying principles guide my teaching and mentoring approach:
(i) combining foundational principles with practical application
(ii) guided active learning
(iii) quantitative reasoning
I have also organized NSF funded workshops on addressing complex systems problems
These are examples of some courses I have designed and or taught:
2022 NSF funded transdisciplinary workshop
Introduction to Scientific Computing
Statistics and Computing in R for Ecologists and Epidemiologists (Indiana University- Bloomington
Computational Modeling
Computational Modeling ECOL 8540 - applied to infectious disease systems (May 2018 @ IDEAS, UGA)
Introduction to modelling
Introduction to modelling with R - apply population models (2017 @ Odum School of Ecology)
R code along workshop
Introduction to modelling with R - based on a course i designed while at UGA
WHO
Technical Advisory Group for educational institutions and COVID-19
BIG Ten
Member of the Epi- Core cardiac registry for COVID-19
US Track & Field
Epidemiologist in the COVID-19 advisory group
PAHO
Develop federated data sharing & modeling
FIOCRUZ
Early Warning Tools for emerging pathogens
Media Coverage
Links to selected coverage of our work
Ana I Bento © 2019 | Background image R code adapted from data imaginist