Piero Poletti

TL;DR: A data-driven global stochastic epidemic model is used to analyze the spread of the Zika virus (ZIKV) in the Americas and it can be potentially used as a template for the analysis of future mosquito-borne epidemics.

TL;DR: A model is proposed which couples an SIR model with selection of behaviours driven by imitation dynamics that can explain "asymmetric waves", i.e., infection waves whose rising and decaying phases differ in slope.

TL;DR: It is highlighted that spontaneous behavioral changes in the population, not accounted by the large majority of influenza transmission models, can not be neglected to correctly inform public health decisions, and individual choices can drastically affect the epidemic spread, by altering timing, dynamics and overall number of cases.

TL;DR: The results show that an epidemic can be controlled by performing a timely intervention, even if the transmission potential of Chikungunya virus is sensibly high, and confirm the increasing risk of tropical vector–borne diseases in temperate climate countries, as a consequence of globalization.

TL;DR: The COVID-19 outbreak in Italy showed a clustering onset similar to the one in Wuhan, China, supporting the importance of combined non-pharmacological control measures.