Utilising urgent computing to tackle the spread of mosquito-borne diseases

TL;DR

This paper presents the integration of a mosquito-borne disease spread model with the VESTEC urgent computing system, enabling health professionals to better simulate and respond to outbreaks using high-performance computing and advanced visualization.

Contribution

It introduces a novel integration of epidemiological modeling with an urgent computing ecosystem to facilitate wider adoption by health and disaster response professionals.

Findings

Enhanced visualization and analytics for disease spread modeling

Seamless HPC integration supports rapid simulations

Facilitates wider adoption by epidemiologists and disaster responders

Abstract

It is estimated that around 80\% of the world's population live in areas susceptible to at-least one major vector borne disease, and approximately 20% of global communicable diseases are spread by mosquitoes. Furthermore, the outbreaks of such diseases are becoming more common and widespread, with much of this driven in recent years by socio-demographic and climatic factors. These trends are causing significant worry to global health organisations, including the CDC and WHO, and-so an important question is the role that technology can play in addressing them. In this work we describe the integration of an epidemiology model, which simulates the spread of mosquito-borne diseases, with the VESTEC urgent computing ecosystem. The intention of this work is to empower human health professionals to exploit this model and more easily explore the progression of mosquito-borne diseases. Traditionally in the domain of the few research scientists, by leveraging state of the art visualisation and analytics techniques, all supported by running the computational workloads on HPC machines in a seamless fashion, we demonstrate the significant advantages that such an integration can provide. Furthermore we demonstrate the benefits of using an ecosystem such as VESTEC, which provides a framework for urgent computing, in supporting the easy adoption of these technologies by the epidemiologists and disaster response professionals more widely.