# The Environmental and Human Factors that Determine Ixodes scapularis-borne Diseases Incidence

> **NIH NIH F31** · UNIVERSITY OF PENNSYLVANIA · 2020 · $38,185

## Abstract

Project Summary
Vector-borne diseases (VBDs) are the most common types of emerging and re-emerging infectious diseases in
the world. VBD epidemics have been increasing over recent decades, with tickborne diseases having doubled
in the last decade in the United States. Despite the increase in public health burden, over 80% of vector-control
organizations lack preventative capabilities. Understanding the interplay between the environment, vectors,
pathogens, and humans that expedite disease spread remains a challenge. The overarching goal of this
project is to identify the key environmental and human drivers that have led to the emergence of VBDs.
Current models that predict tickborne disease risk have oversimplified the process by focusing only on the
vector, i.e. risk of tick exposure. A human’s risk of infection is not only a function of entomological risk but also
of factors inherent to the individual including behavior or characteristics that increase susceptibility to disease.
This project proposes a novel approach to tickborne disease prediction by developing a comprehensive model
that incorporate pathogen population dynamics and human factors to predict disease risk.
This study will investigate several pathogens vectored by the black-legged tick (Ixodes scapularis): Borrelia
burgdorferi (Lyme disease), Anaplasma phagocytophilum (human granulocytic anaplasmosis), and Babesia
microti (babesiosis). The central hypothesis is that the prediction of tickborne disease risk can be improved by
using sophisticated statistical methods to identify environmental drivers that impact pathogen population
dynamics while incorporating human demographic characteristics. The hypothesis will be addressed in the
following aims: (1) Determine the current and historical population dynamic patterns of pathogens vectored by
I. scapularis to predict pathogen distribution; (2) Determine the association between human characteristics and
tick-borne disease risk in order to develop an improved spatial disease risk model. This model will allow the
identification and quantification of factors that are associated with the emergence of tickborne diseases in New
York State, which is geographically advantageous because it is representative of much of the natural
environment that ticks encounter in the northeastern US including rapid and recent changes in climate and
landscapes. The results of this project will be used to develop a public disease warning system that will use
contemporary and future climate forecasts to monitor tick populations and predict potential disease outbreaks
for areas with vulnerable populations. With climate forecasts predicting an increase in 2-3°C in temperature by
2100, there is uncertainty in how diseases will shift and a warning system will allow preparation accordingly.
At the completion of the proposed research project, the applicant will have acquired the following skillsets
through intensive, interdisciplinary mentorship: big data analysis, ad...

## Key facts

- **NIH application ID:** 10018461
- **Project number:** 5F31AI133871-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Tam Minh Tran
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $38,185
- **Award type:** 5
- **Project period:** 2019-09-01 → 2021-05-17

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10018461

## Citation

> US National Institutes of Health, RePORTER application 10018461, The Environmental and Human Factors that Determine Ixodes scapularis-borne Diseases Incidence (5F31AI133871-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10018461. Licensed CC0.

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