# FluMod - Center for the Multiscale Modeling of Pandemic and seasonal Flu Prevention and Control

> **NIH ALLCDC U01** · NORTHEASTERN UNIVERSITY · 2020 · $371,721

## Abstract

PROJECT SUMMARY
In this proposal we plan to contribute addressing the above foundational and operational
challenges by advancing the science of influenza modeling and contributing novel methods and
data sources that will increase the accuracy and availability of seasonal and pandemic influenza
models. To address these challenges, we plan to build on the unique mechanistic spatially
structured modeling approaches developed by our consortium, that includes stochastic
metapopulation models and fully developed agent-based models nested together in our global
epidemic and mobility modeling (GLEAM) approach.
The objective of this project is to generate novel and actionable scientific insights from
dynamic transmission models of influenza transmission that effectively integrate key
socio-demographic indicators of the focus population, as well as a wide spectrum of
pharmaceutical and non-pharmaceutical interventions. Our proposed work in specific aim 1
(A1) will leverage our global modeling (from the global to local scale) framework that can be used
to explore the multi-year impact of influenza vaccination, antiviral prophylaxis/treatment, and
community mitigation during influenza seasons and pandemics. Our specific aim 2 (A2) will focus
on using high quality data to model heterogeneous transmission drivers and novel contact pattern
stratifications that will allow us to guide mitigation strategies and prioritization for interventions. In
our Aim 3 (A3) we will use artificial intelligence approaches to identify interventions that are
particularly synergistic and well-suited to particular epidemic scenarios, for seasonal and
pandemic influenza. Our overarching goal is to provide a modeling portfolio with flexible and
innovative mathematical and computational approaches. We aim to address several questions
commonly asked about seasonal and pandemic influenza and match these with analytical
methods and outbreak projections. The modeling and data developed in this project can help
facilitate and justify transparent public health decisions, while contributing to the definition of
standard methods for model selection and validation. Finally, our influenza modeling platform can
also benefit the broader network of modeling teams and can be used to improve result sharing
and harmonization of modeling approaches.

## Key facts

- **NIH application ID:** 10071782
- **Project number:** 1U01IP001137-01
- **Recipient organization:** NORTHEASTERN UNIVERSITY
- **Principal Investigator:** Alessandro Vespignani
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2020
- **Award amount:** $371,721
- **Award type:** 1
- **Project period:** 2020-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10071782

## Citation

> US National Institutes of Health, RePORTER application 10071782, FluMod - Center for the Multiscale Modeling of Pandemic and seasonal Flu Prevention and Control (1U01IP001137-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10071782. Licensed CC0.

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