TY  - JOUR
AU  - Guzzi, Pietro H
AU  - Tradigo, Giuseppe
AU  - Veltri, Pierangelo
PY  - 2021
DA  - 2021/3/9
TI  - Regional Resource Assessment During the COVID-19 Pandemic in Italy: Modeling Study
JO  - JMIR Med Inform
SP  - e18933
VL  - 9
IS  - 3
KW  - COVID-19
KW  - data analysis
KW  - ICU
KW  - management
KW  - intensive care unit
KW  - pandemic
KW  - outbreak
KW  - infectious disease
KW  - resource
KW  - planning
AB  - Background: COVID-19 has been declared a worldwide emergency and a pandemic by the World Health Organization. It started in China in December 2019, and it rapidly spread throughout Italy, which was the most affected country after China. The pandemic affected all countries with similarly negative effects on the population and health care structures. Objective: The evolution of the COVID-19 infections and the way such a phenomenon can be characterized in terms of resources and planning has to be considered. One of the most critical resources has been intensive care units (ICUs) with respect to the infection trend and critical hospitalization. Methods: We propose a model to estimate the needed number of places in ICUs during the most acute phase of the infection. We also define a scalable geographic model to plan emergency and future management of patients with COVID-19 by planning their reallocation in health structures of other regions. Results: We applied and assessed the prediction method both at the national and regional levels. ICU bed prediction was tested with respect to real data provided by the Italian government. We showed that our model is able to predict, with a reliable error in terms of resource complexity, estimation parameters used in health care structures. In addition, the proposed method is scalable at different geographic levels. This is relevant for pandemics such as COVID-19, which has shown different case incidences even among northern and southern Italian regions. Conclusions: Our contribution can be useful for decision makers to plan resources to guarantee patient management, but it can also be considered as a reference model for potential upcoming waves of COVID-19 and similar emergency situations. 
SN  - 2291-9694
UR  - https://medinform.jmir.org/2021/3/e18933
UR  - https://doi.org/10.2196/18933
UR  - http://www.ncbi.nlm.nih.gov/pubmed/33629957
DO  - 10.2196/18933
ID  - info:doi/10.2196/18933
ER  -