Brief description: 

No scientific answer explains spatial variability underlying spread and mortality of this pandemic. Predictive modeling using artificial intelligence and Big Data techniques running in the cloud, would allow us to squeeze a huge range of data to uncover and get an accurate view of the underlying and interplaying factors, some of which are territorial variables not even considered yet. The solution consists of advanced modeling tool which, after appropriate validation, becomes a predictive tool based on different environmental, climate, air pollution and demographic variables as inputs.

Main Features: 

This project builds on Cloud Computing and Big Data. Thanks to a serverless application and Machine Learning techniques, a high-resolution spatial predictive model will be developed, endowed with numerous explaining socio-territorial variables (ranging from air pollution to comorbility drivers). The purpose is to build a planning tool capable of predicting mortality risk of this pandemic useful for public health protection and resources management. This tool will be implemented through WebMapping applications that help to understand at a glance the spatial patterns of the target variables.

Areas of Application: 

Health

Market Trends and Opportunities: 

Hospital collapse and health service saturation are worrying outcomes of the pandemic. Infection and mortality rate of this disease are highly variable geographically. Risk prevention is relevant because no clear knowledge of spatial patterns of COVID-19 infection spread and prevalence is available. Providing to competent authorities with a robust tool to predict mortality risks at local populations is very helpful. Informed decision making, public warnings, and specially logistics response improvement, are needed to manage future outbreaks of this pandemic, saving lives and monetary costs, and avoiding unnecessary changes of citizen normal lives.

Customer Benefits: 

Human life is priceless. Every life counts. This tool serves the authorities for management of the pandemic, avoiding hospital overload and, therefore, decreasing mortality rate in Spanish population. Benefits to 47,100,395 inhabitants of Spain (23,089,389 men and 24,011,006 women), 10,720,777 of which are aged people, 65 years old or higher. Other benefits would be general reductions in health service expenses, improvement of confinement plans, and more effective control of economic slowdown.

Technological novelty: 

Tool deployment to other countries or regions is possible, through an improvement in the account of cloud services and data acquisition/processing from other countries. Allows a more comprehensive and accurate technology which can support incremental number of data/variables as inputs immediately.

Workflow: 
Published
COVID-19 Logistics

Owner

Gonzalo Barranco
Spain
Type: 
Other
Contact: 
BDV Reference categories: 
Data Analytics
Markets: 
COVID-19
Readiness Level: