Utilising urgent computing to tackle the spread of mosquito-borne diseasesShow others and affiliations
2021 (English)In: Proceedings of Urgenthpc 2021: The Third International Workshop On Hpc For Urgent Decision Making, Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 36-44Conference paper, Published paper (Refereed)
Abstract [en]
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.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. p. 36-44
Keywords [en]
Mosquito-borne diseases, urgent computing, HPC, disease simulation, epidemiology
National Category
Public Health, Global Health and Social Medicine
Identifiers
URN: urn:nbn:se:kth:diva-310051DOI: 10.1109/UrgentHPC54802.2021.00010ISI: 000758406900005Scopus ID: 2-s2.0-85124466277OAI: oai:DiVA.org:kth-310051DiVA, id: diva2:1646538
Conference
3rd International Workshop on HPC for Urgent Decision Making (UrgentHPC), NOV 19, 2021, St Louis, MO
Note
Part of proceedings: ISBN 978-1-6654-1130-1
QC 20220323
2022-03-232022-03-232025-02-20Bibliographically approved