Beach-level 24-hour forecasts of Florida red tide-induced respiratory irritation

TL;DR

This study develops and compares two models, wind-based and Hawkes process, to forecast red tide-related respiratory irritation levels at Florida beaches, achieving around 84% accuracy and aiding public health responses.

Contribution

Introduces and evaluates two novel beach-level 24-hour forecast models for red tide respiratory irritation, demonstrating their effectiveness across multiple beaches.

Findings

Wind-based model achieves 84% accuracy at half the beaches.

Hawkes process model achieves 81% accuracy at most beaches.

Model performance varies by beach, highlighting the importance of localized data.

Abstract

An accurate forecast of the red tide respiratory irritation level would improve the lives of many people living in areas affected by algal blooms. Using a decades-long database of daily beach conditions, two conceptually different models to forecast the respiratory irritation risk level one day ahead of time are trained. One model is wind-based, using the current days' respiratory level and the predicted wind direction of the following day. The other model is a probabilistic self-exciting Hawkes process model. Both models are trained on beaches in Florida during 2011-2017 and applied to the red tide bloom during 2018-2019. For beaches where there is enough historical data to develop a model, the model which performs best depends on the beach. The wind-based model is the most accurate at half the beaches, correctly predicting the respiratory risk level on average about 84% of the time. The Hawkes model is the most accurate (81% accuracy) at nearly all of the remaining beaches.