• Bento Lab

    Ecology & evolution of infectious diseases

    Why do some pathogen introductions lead to outbreaks while others fade out?

    We study what allows infections to establish, recur, and persist in human and animal populations. Our approach begins with ecological theory: how differences among hosts, interactions between populations, and changing environments produce the disease patterns we observe.

    We develop mathematical models to test explanations for those patterns against epidemiological, ecological, and genomic data. We also make predictions and examine how prevention changes transmission.

  • Research

    What determines the fate of an introduction?

    We follow infections from their early establishment to their longer-term dynamics. The themes below connect those outcomes with the distribution of immunity, environmental and evolutionary change, and the feedback between behavior and transmission. We study different infections to test questions that extend beyond any one disease.

    An introduction can lead to a growing outbreak or a transmission chain that ends. We study how host populations, pathogen biology, and environmental conditions change the likelihood of these outcomes, with vectors contributing where relevant. Even when conditions permit an outbreak to grow, early transmission can end by chance.
  • Research Themes

    Our research is organized around the questions below. We investigate them across different infections, using each system to test ideas about how disease dynamics arise and change. We turn hypotheses about transmission into models and compare their predictions with observations. This requires accounting for how infections are recorded as well as how they spread. Where we develop forecasts, we evaluate predictions against observations that were not used to produce them.

    Section image

    Establishment and persistence

    What allows transmission to take hold, and what sustains it over time?

    We investigate why some introductions end after a few infections while others generate outbreaks. We also ask how movement between populations and seasonal change affect longer-term circulation, and how to distinguish continued local transmission from repeated introductions.

    Section image

    Immunity and population structure

    When do population averages conceal local transmission risk?

    We study how the distribution of immunity and the organization of contacts shape transmission. Working across schools, communities, and larger populations, we ask which scales reveal susceptible groups and how their connections affect the consequences of an introduction.

    Section image

    Environmental change and pathogen evolution

    How do changing environments and pathogen populations alter disease dynamics?

    We investigate how climate, habitat, and land use influence transmission, and how pathogen lineages emerge and spread. By linking ecological analyses with genomic evidence, we ask when environmental and evolutionary processes provide separate explanations for disease patterns and when they interact.
    Section image

    Behavior and disease dynamics

    How do responses to infection change the course of an epidemic?

    We study how perceived risk and practical constraints influence contact patterns and preventive behavior. Our models examine the resulting feedback: behavior changes exposure, while changing disease conditions influence subsequent decisions.
  • 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.

    Section image
    Oropouche dynamics in the Americas

    Eco-evo models

    Section image
    Measles dynamics in the Americas

    Susceptibility landscape and risk metrics of measles

    Section image

    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

    Section image

    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

    Section image

    Alpha and Beta CoVs spillover risk

    Spillover risk surveillance- big brown bats in Colorado

    In collaboration with Rebekah Kading

    Section image

    Disease spreading modeling through social and genomic data of SARS-CoV-2 in the United States

    Integrating parallel data streams

    In collaboration with Carla Mavian

    Section image

    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

    Section image

    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

    Section image

    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 

    Section image
    Investigating the spread of mosquito-borne diseases in complex urban environments

    Mathematical models for MBDs

  • Selected Publications

    For a complete and more recent list of publications check my google scholar. Brief description below with links for the publications

    Section image

    Ecological and demographic drivers of Oropouche virus transmission

    Hua, Alexander et al Nature Health 2026

    Why does transmission intensify in some places and seasons?
    We investigate how environmental conditions and population characteristics shape Oropouche transmission, using models to connect local variation with broader epidemic patterns.
    Section image

    County, district and community-level measles transmission in the United States in 2013-2025

    How does the scale of observation change our understanding of outbreak risk?
    We examine how vaccination coverage and susceptibility vary among schools, districts, and counties, and what those differences imply for local measles transmission.

    Section image

    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

    Section image

    Early risk-assessment of pathogen genomic variants emergence

    Susswein et al 2023 MedRxiv

    Section image

    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

    Section image

    Wastewater surveillance of pathogens can inform public health responses

    Diamond et al 2022 Nature Medicine

    Section image

    Disease-economy trade-offs under alternative pandemic control strategies

    Ash et al Nature comms 2022

    Section image

    Model-based evaluation of alternative reactive class closure strategies against COVID-19

    Liu et al 2022 Nature comms

     

    Section image

    Designing isolation guidelines for COVID-19 patients with rapid antigen tests

    Jeong et al Nat comms 2022

    Section image

    Vaccinations Against COVID-19 May Have Averted Up To 140,000 Deaths In The United States

    Gupta et al 2021 Health Affairs

    Section image

    Revisiting the guidelines for ending isolation for COVID-19 patients

    Jeong et al 2021 eLife

    Section image

    Prevalence of Clinical and Subclinical Myocarditis in Competitive Athletes With Recent SARS-CoV-2 Infection. Results From the Big Ten COVID-19 Cardiac Registry

    Daniels et al JAMA Cardio. 2021

    Section image

    HIV cases during the COVID-19 pandemic in Japan

    Ejima et al JAIDS 2021

    Section image

    Global effects of delays in detection of COVID-19

    nearing submission

    Section image

    Estimation of the incubation period of COVID-19 using viral load data

    Ejima et al. Epidemics 2021

    Section image

    Information Seeking Responses to News of Local COVID-19 Cases: Evidence from Internet Search Data

    Bento et al PNAS 2020

    Section image

    Effects of mitigation strategies on COVID-19 averted cases in Sichuan, China

    Liu et al. Plos Comp Bio 2020

    Section image

    COVID-19 incidence in the county increased on average by a statistically significant 0.024 per thousand residents

    Andersen et al. 2020

    medRxiv

    Section image

    Evolutionary consequences of feedbacks between within-host competition and disease control

    Greischar et al. JID 2020

    Section image

    Tracking public and private response to the covid-19 epidemic

    Gupta et al. NBER 2020

    Section image

    Inferring Timing of Infection Using Within-host SARS-CoV-2 Infection Dynamics Model: Are “Imported Cases” Truly Imported?

    Ejima et al medRviv 2020

    Section image

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

     

    Bento et al. 2018. Vaccine

    Section image

    Maternal pertussis immunisation: clinical gains and epidemiological legacy

    Bento, King & Rohani. 2017. Eurosurveillance

    Section image

    Forecasting epidemiological consequences of maternal immunization

    Bento & Rohani 2016. Clinical Infectious Diseases

    Section image

    EpiJSON: A unified data-format for epidemiology

    Finnie et al. 2016. Epidemics

    Section image

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

    Garnier et al. 2017

    Section image

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

    van Kerkove et al. 2015. Scientific Data

    Section image

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

    Donnelly et al. 2015. Veterinary Record

    Section image

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

    Stopher, Bento et al 2014 Ecology

     

     

  • Our team

    Get to know us & join us!

    Section image

    Ana Bento

    PI

     

    Section image

    Tijs Alleman Postdoc

    Section image

    Elvira D'Bastiani Postdoc

    Section image

    Sebastían Llanos-Soto

    Postdoc

    Section image

    Yining Sun

    PhD Student

     

    Section image

    Herman Zhang

    MPH Student

    Section image

    Sore Ajagbe

    UG Student

    Section image

    Sanjana Bajaj

    UG Student

    Section image

    Allison Tang

    UG Student

  • Former Team Members

    Get to know us & join us!

    Section image

    Zack Susswein

    Researcher

    now Scientist @CDC, CFA

    Section image

    Kaytlin Jonhson

    Postdoc

    now Assist Prof @ LSTMH

    Section image

    Siyu Chen

    Postdoc

    Coming soon :)

  • Section image

    Join the Bento Lab

    We welcome inquiries from prospective postdoctoral researchers and students interested in infectious disease ecology, mathematical modeling, and pathogen evolution.

    Send your CV and a short description of the questions you would like to investigate. Include your anticipated timing and whether you are seeking a funded position or support with a fellowship application.

  • Section image

    Let's collaborate on a future-forward project

  • 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:

    Pandemic Prevention Preparedeness and Response (3PR)

    Systems approaches to pandemics from environemental circulation to human outbreaks

    Moving towards a holistic transdisciplinary view to Ecology and Evolution of Infectious Diseases                       

    2022 NSF funded transdisciplinary workshop

    Public Health Surveillance and Monitoring

    E 250 @ Indiana University

    Introduction to Scientific Computing

    Statistics and Computing in R for Ecologists and Epidemiologists (Indiana University- Bloomington

    R bootcamp

    Self guided workshops

    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

  • Blog posts

    The hidden map of measles risk: why zooming in changed everything

    ⇣ link in photo

  • Advisory Modeling & Policy-related work

     

    1

    WHO

    Technical Advisory Group for educational institutions and COVID-19

    2

    BIG Ten

    Member of the Epi- Core cardiac registry for COVID-19

    3

    US Track & Field

    Epidemiologist in the COVID-19 advisory group

    4

    PAHO

    Develop federated data sharing & modeling

    5

    FIOCRUZ

    Early Warning Tools for emerging pathogens

  • Section image
  • Bento Lab values

    In our lab, we differ in many ways, from where we come from geographically and socioeconomically to how we live and identify. What we share is a commitment to making our communities more diverse, equitable, inclusive, and just, and to creating a space where we all feel safe, welcomed, respected, celebrated, and empowered, not in spite of but because of our differences. We strive for excellence as scholars, as scientists, as teachers, and as members of our communities, which include our lab group, our department, our university, our fields of study, our scientific societies, and our city, Ithaca, NY. We can achieve excellence only by including, listening to, and advocating for individuals representing a diversity of races, ethnicities, educational and socioeconomic backgrounds, sexual orientations, gender identities, abilities, ages, religious beliefs, and immigration experiences.

    We recognize the deep-seated inequity of our society, of academia, and of science and the perpetuation of systemic racism, sexism, homophobia, xenophobia, ableism, and other exclusionary, discriminatory, and hateful practices that have made academia and science inaccessible, hostile, and unsafe for many. We understand that responsibility for change lies with all of us. We commit to effecting change by:

    • Informing our actions by educating ourselves on systemic exclusion and oppression in our communities
    • Investing in recruiting and mentoring trainees from marginalized groups
    • Committing to equitable and inclusive hiring practices
    • Improving our work environment to remove barriers and accommodate every person
    • Reserving time for discussing concerns about inclusivity and safety, rewarding open dialogue with appropriate changes, and respecting anonymity
    • Defending the expansion of “excellence” to include skills, efforts, and experiences that have been historically undervalued and discouraged
    • Making thoughtful, equitable decisions about who we choose to work with, invite, nominate, and cite
    • Seeking opportunities to learn and acknowledge the historical context of our field (the good and the ugly) and to teach marginalized perspectives in the classroom
    • Actively contributing to increasing diversity, equity and inclusion in our department
    • Addressing actions or words that do not uphold our lab values and supporting one another in working towards our goals as a lab

     

    ~ The Bento Lab, 1/1/2024. This is a living outline of our values and guidelines. We will revisit it annually to determine if we’re acting in a manner that prioritizes our values and revise it to reflect changes in our community.

     

  • Socials

     

     

    Section image
    Section image
    Section image
    Section image
    Section image
    Section image
  • Media Coverage

    Links to selected coverage of our work

    Manuscripts & other results

    See excerpts interviews here , The Guardian, StatNews, wtiu, Expresso (Portugal), wfiu, LEO, wtiu, IU, WSJ (for coverage on collaborative work), FOX59, WTFIU, WSJ, Reuters, KHN, MSNBC, NYT, THE, FOX59, ERI, TODAY show, NYT, NIA, Sinclair, Saloon, Forbes, FactCheck

    Women in Ecology

    Nature Ecology & Evolution

    AJPH Podcast

    Recording available here

    Cornell Podcast

    Recording available here