I'm the Director of Science @ The Rockefeller Foundation. 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 with a focus on climate change & health. 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). I hold a faculty position @ Indiana University since 2019.
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.
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).
My 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. At Rockefeller we focus on a co-creation models with partners from several parts of the globe.
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
Mathematical models for MBDs
In collaboration with Marco Ajelli & others
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
Wastewater surveillance of pathogens can inform public health responses
Diamond et al 2022 Nature Medicine
Ash et al Nature comms 2022
Designing isolation guidelines for COVID-19 patients with rapid antigen tests
Jeong et al Nat comms 2022
Global effects of delays in detection of COVID-19
nearing submission (available upon request)
The Bento Lab @ Rockefeller Foundation
Get to know us & join us!
Kaithlyn Jonhson Postdoc
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 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)
Links to selected coverage of our work
Ana I Bento © 2019 | Background image R code adapted from data imaginist