A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic

Abstract

The COVID-19 epidemic hit Italy particularly hard, yielding the implementation of strict national lockdown rules. Previous modelling studies at the national level overlooked the fact that Italy is divided into administrative regions which can independently oversee their own share of the Italian National Health Service. Here, we show that heterogeneity between regions is essential to understand the spread of the epidemic and to design effective strategies to control the disease. We model Italy as a network of regions and parameterize the model of each region on real data spanning over two months from the initial outbreak. We confirm the effectiveness at the regional level of the national lockdown strategy and propose coordinated regional interventions to prevent future national lockdowns, while avoiding saturation of the regional health systems and mitigating impact on costs. Our study and methodology can be easily extended to other levels of granularity to support policy- and decision-makers.

High‐Resolution Agent‐Based Modeling of COVID‐19 Spreading in a Small Town

“…Computational models are powerful tools for understanding novel epidemics and evaluating the effectiveness of potential countermeasures. [ 12–16 ] Agent‐based models (ABMs) are a class of computational models that provide a high‐resolution—both temporal and spatial—representation of the epidemic at the individual level. [ 4,17–21 ] These models afford consideration of multiple physical locations, such as businesses or schools, as well as unique features of communities, like human behavioral trends or local mobility patterns.…”

A simple but complex enough θ-SIR type model to be used with COVID-19 real data. Application to the case of Italy

“…Concerning the particular case of Italy, some studies have dealt with its particular situation, such as [10] , [11] , [12] and [13] . It is important to note that all the models presented in these works only serve the particular case of Italy, and are not general models applicable to other countries.…”

“…In [11] , the distribution in terms of mobility is also studied through a network of the different Italian regions. It is confirmed the effectiveness at a regional level of the national lockdown strategy and proposed coordinated regional interventions to prevent future national lockdowns.…”

Emergent effects of contact tracing robustly stabilize outbreaks

“…SIR (Susceptible-Infected-Resistance) models and other models have been used to understand COVID-19 dynamics [4,5,[7][8][9]. Substantial progress was made predicting the basic reproduction number (Ro) [10], and strategies to flatten the curve [11][12][13][14][15].…”