A novel deterministic forecast model for COVID-19 epidemic based on a single ordinary integro-differential equation

Enrico De Micheli of the Biophysics Institute of Genova participated in a Italo-German collaboration, with Felix Koehler-Rieper and Claudius Roehl, which has led to a new hybrid approach to deterministic modelling of COVID-19 epidemic.
The model dynamics is described by a single prognostic variable, the number of cumulative diagnosed cases, satisfying an integro-differential equation. All the unknown parameters of the model are described by a single time-dependent function k(t) that can be obtained from the available data. Comparison with classical compartmental models, such as SIR, shows that k(t) can be interpreted as an effective reproduction number. Extrapolated values of k(t) can then be inserted in the model to make forecasts. The model has been preliminarly applied to several worldwide countries as well as to all the regions of Italy.
Graphical results of data analysis can be visualized through the links below.
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GRAPHS AND DATA ANALYSIS
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Countries

ItalyGermany
United States of AmericaSpainUnited KingdomFranceRussia
TurkeyBelgiumSwitzerlandNetherlandsSweden
IranBelarusBrazilCanada
ChileEcuadorIndiaMexico
PakistanPeruSaudi ArabiaSingapore

Regions of Italy

LiguriaLombardia
ToscanaSiciliaP.A. TrentoPiemonte
VenetoEmilia-RomagnaAbruzzoBasilicata
P.A. BolzanoCalabriaCampaniaFriuli Venezia Giulia
LazioMarcheMolisePuglia
SardegnaUmbriaValle d’Aosta