COVID-19: a novel method to monitor the pandemic evolution
The study of Politecnico di Milano analyses trend of calls to 112 to provide territory-specific alerts
The Politecnico di Milano developed a novel data-driven method that shows how it is possible to use the geo-localized information of the calls to the medical emergency number (112) and subsequent ambulance dispatches, relevant to respiratory problems, to monitor the COVID-19 evolutionon a certain region.
The paper, published on the ISPRS International Journal of Geo-Information, focuses on the Lombardy region, Italy, subdivided in districts of 100.000 residents. Thanks to the collaboration of the Agenzia Regionale Emergenza Urgenza (AREU) that has provided the data, it has been shown how COVID-19 was most probably already diffused in the Lombardy region well before the diagnosis of the first official patient in Codogno on February 21, 2020.
In particular, in the district including Codogno, the beginning of the pandemic diffusion has been identified on February 16, while in the districts including Nembro and Alzano Lombardo (characterized by the highest mortality increase in respect to the previous year) the beginning of the pandemic has been estimated between Feb 14 and Feb 16.
The developed method is applicable to other regions, and shows the potential of the analysis of indirect data generated by citizens’ action (the calls to 112 or ambulance dispatches) easily available every day in respect to the official data, based on the number of official positive cases, constrained to the number of performed tests and possible delays for their analysis.
On the basis of these results, further study is on-going to determine how to generate a territory-specific alert indication, based on the trend of the previous days, to highlight to decision-makers possible geographically localized situations that could need particular attention.
This study is part of the research conducted within an inter-doctoral PhD grant in Biomedical Engineering funded by Politecnico di Milano and assigned to Ing. Lorenzo Gianquintieri, under the supervision of Prof. Enrico Caiani (Electronics, Information and Bioengineering Dpt.) and of Prof. Maria Brovelli (Civil and Environmental Engineering Dpt.).
Gianquintieri, L.; Brovelli, M.A.; Pagliosa, A.; Dassi, G.; Brambilla, P.M.; Bonora, R.; Sechi, G.M.; Caiani, E.G.
Mapping Spatiotemporal Diffusion of COVID-19 in Lombardy (Italy) on the Base of Emergency Medical Services Activities.
ISPRS Int. J. Geo-Inf. 2020, 9, 639.
The paper and the images are licensed under a Creative Commons Attribution 4.0 International License