# Impacts of phenology on disease transmission dynamics

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2024 · $580,899

## Abstract

The proposed projects are a comprehensive effort to rigorously investigate the contribution of phenology -
or seasonal activity - to pathogen transmission dynamics using 3 widespread zoonotic pathogens carried 
by black-legged ticks. Variation in seasonal activity patterns and life-history events, which are well 
documented in species inhabiting temperate regions, can result in dramatic population dynamics including 
population extinctions or explosions. Phenological variation across time and geography also alters the 
frequency and strength of inter-species interactions and thus opportunities for pathogen transmission, 
which likely has profound impacts on pathogen transmission dynamics and human disease risk. Despite 
the likely importance to public health, the consequences of phenological variation on disease transmission 
dynamics remain notably under-studied in many complex zoonotic disease systems. The tick-borne 
disease system in North America provides the ideal system to determine the impact of phenology on 
pathogen transmission dynamics both theoretically and empirically. We will build and evaluate solvable 
analytical models, computational models, and advanced statistical models, all of which explicitly 
incorporate tick seasonal activity, and validate these models with empirical data from natural field sites. 
The proposed projects will (1) determine the quantitative impact of different phenological scenarios on the 
transmission dynamics of, and thus disease risk from, 3 human pathogens, (2) empirically evaluate model 
predictions, and (3) identify specific phenological and environmental features that result in different 
transmission dynamic outcomes among pathogen species. We will develop 3 modeling frameworks to 
investigate the impact of phenology on transmission dynamics, identify and quantify phenological and 
environmental drivers of transmission dynamics in 3 important human pathogens, and empirically validate 
the outcomes of the theoretical and statistical models. Empirical validation of both the phenological drivers 
and model predictions is essential not only for public health management but also to identify mechanistic 
processes driving these patterns. The proposed research provides both theoretical and empirical 
frameworks to investigate the impact of phenology on transmission dynamics in the multitude of disease 
systems involving multiple host species or life-stages from insect-vectored plant pathogens to pathogens 
with multi-host life-cycles.

## Key facts

- **NIH application ID:** 10895568
- **Project number:** 5R01AI181007-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Dustin Brisson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $580,899
- **Award type:** 5
- **Project period:** 2023-08-01 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10895568

## Citation

> US National Institutes of Health, RePORTER application 10895568, Impacts of phenology on disease transmission dynamics (5R01AI181007-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10895568. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*