Helping track and reduce COVID-19 infections in Northeast Brazil
A combination of thermal drones, artificial intelligence, and mathematical modeling is helping scientists track and reduce the spread of COVID-19 in Northeast Brazil: one of a series of ongoing, innovative coronavirus research initiatives being carried out by UCL and scientists in Brazil.
Working with scientists at Pernambuco Institute for Risk & Disaster Reduction (IRRD-PE) and the COVID SGIS initiative, which are affiliated with Federal University of Pernambuco, they have developed sophisticated prediction and mapping tools using AI machine-learning which, combined with thermal drone imaging and COVID-infection hospital data, is enabling the team to predict where the virus will spread next. This information gives early warning to public health authorities and local communities.
To accomplish this goal the IRRD-PE cooperates closely with the Pernambuco State Government and the state capital's City of Recife Council.
Professor Kostkova, of the UCL IRDR Center for Digital Public Health in Emergencies, who is formally advising the IRRD-PE, has been working with the UFPE on developing early-warning tools, using mobile surveillance technology, to predict the movements and dynamics of mosquito populations in Northeast Brazil in order to combat Zika virus.
"Our specific objective is to ensure that all data from geolocation mapping, mass gatherings estimates from thermal drone cameras, and lab confirmed cases of COVID-19 infection, are effectively used in almost real-time," she said.
According to researchers the unique modeling tool they have developed is rapidly gaining international recognition.
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