# Understanding climate-sensitive tick development and diapause with a structured population model

## TL;DR

This paper introduces a model to understand how ticks develop and enter diapause in response to climate factors, helping predict their spread and disease risk.

## Contribution

A novel structured population model that integrates temperature and photoperiod effects on tick development and diapause.

## Key findings

- The model successfully replicates nymph development under laboratory conditions.
- Photoperiod and temperature are key drivers of tick development and seasonal activity.
- The model can predict tick behavior under variable field weather conditions.

## Abstract

Tick-borne diseases have become a growing public health concern globally. As climate change reshapes the environment, tick populations are expected to expand into previously unsuitable areas, further increasing human exposure to ticks and the pathogens they transmit. Understanding the environmental factors that sustain tick populations is crucial for enhancing prevention and control measures.

This study presents a multi-process structured population model that simulates nymph activity, development, and diapause in response to temperature and photoperiod. By integrating laboratory data and meteorological variables, the model captures the role of photoperiod in regulating diapause and the influence of temperature on development rates.

With this model, we propose a mechanism to better understand how short- and long-day conditions synchronize nymph development, highlighting the importance of repeated sensing of external conditions for maintaining behavioral strategies to optimize fitness under changing environmental conditions. The model successfully replicates nymph development observed in laboratory conditions and extends to field applications, predicting seasonal activity under variable weather conditions.

By providing a mechanistic understanding of tick phenology, our model establishes a foundation for assessing the impacts of climate on tick populations. The insights gained can inform public health tools and strategies, contributing to the mitigation of tick-borne disease risks in a changing environment.