Chilean Avian flu and its marine impacts: an online Statistical Process Control task

TL;DR

This paper analyzes the spread of HPAI H5N1 avian flu along the South American Pacific coast, using statistical models and an online tool to support government decision-making and identify hotspot regions.

Contribution

It introduces a Bayesian spatiotemporal model and an online statistical control tool for monitoring avian flu impacts in Chile.

Findings

Identified hotspot regions with high mortality rates.

Tracked the evolution of avian flu over time.

Provided a decision-support tool for authorities.

Abstract

The rapid spread of the HPAI H5N1 virus, responsible for the Avian Flu, is causing a great catastrophe on the South American Pacific coast (especially in the south of Peru and north of Chile). Although very little attention has been delivered to this pandemic, it presents a tremendous lethal rate, though the number of infected humans is relatively low. Towards monitoring and statistical control, this work shows the Chilean national statistics from the year 2023, and presents the developed online tool for supporting the government's decision-making. Additionally, a Bayesian hierarchical spatiotemporal model was used to model the joint analysis of the weekly registered animal including spatial covariates as well as specific and shared spatial effects that take into account the potential autocorrelation between the HPAI H5N1 virus per Region. Our findings allow us to identify the hot-spot areas with high amounts of dead bodies (mostly pinnipeds and penguins) and their evolution over time.