Home

Erice MathCompEpi 2018 – From August 28 to September 5 2018 @ Erice (Italy)

Aims of the Conference

The mathematical and computational modelling of the spread of infectious diseases is a research field in applied mathematics that in the same time was both able to give an impetum to various areas of the dynamical systems theory and mathematical analysis, and to give an important contribution to the biological and epidemiological understanding of the spread of these diseases.

Indeed, Mathematical and Computational Epidemiology (MCE) has not only an important theoretical value per se. Indeed, it has and it will have, in the near future, a deep impact on the life of citizens. National as well as Inter-National health authorities adopt routinely in the practice methodologies and concept that were born in the field of MCE for assisting public Health decisions and policies. A major example is provided by the huge advancement in modelling and prediction on pandemic threats, and related preparedness plans for disease containment/mitigation. This influence in biomedicine is unparalleled in any other fields of mathematical biology, with the possible exception of intra-host virus dynamics, whose models partly derive from those of MCE.

Thus, modelling could become one of the most important tools to shape contemporary Local and Global Public Health Policies.  However, although the point of view of Public Health Sciences and Policies (PHSP) is often quite unusual for mathematician and physicists, in this Conference we want to stress that it will be increasingly important for new generations of math modellers.

Qualitative and statistical features of temporal and spatio-temporal patterns of the spread of infectious diseases are well-known in PHSP. However, in PHSP the mechanistic links between the onset of patterns and basic contagion, recurrent social phenomena, mobility & demographic phenomena etc.. are less known, as for how to act on these links to control the disease spread. Generations of theoretical investigators worked and are working to elucidate these links, by many innovative approaches. The Challenge is to transform a conceptual tools and big-data based investigations into practical solutions for PH.

One of greatest challenges in modern MCE is finding ways to take into the account new complexity layers often ignored. A major critical issue is human mobility at the various scales. Understanding human mobility is the clue for predicting pandemics travelling and defining mitigation measures. Far from being an idealized random walk, as in fist spatial models, and also far from subdiffusive motion of molecules in a cell, modern human mobility challenges our modelling capabilities and data acquisition.

On the other hand human behaviour and its relationship with the available information on the evolution of the epidemics, is another unsettled issue. for example, is a prevailing issue needed to model, for example, the pseudo-rational objection to vaccinations and the response to pandemic threats.

The aim of this international Conference is twofold.

The first aim is to illustrate the major current areas of research in CME and of its interplay with PHSP. This will be done by means of a series of outstanding invited lectures focused on the personal research of outstanding scientists. Models of various degrees of complexity are synergistically interplaying in this discipline. They are both needed and complementary, and in this Conference will be both present.

The second and major aim, in line with the great tradition of the International Centre “Ettore Majorana”, is to foster learning by frank peer-to-peer discussion between invited speakers and other researchers, junior investigators as well as PhD students, which can submit contributed talks and posters.

Dialog without Frontiers is at the basis of Science.

 

———————————————————————————————

The Conference will be held in Erice, Italy, at the “E. Majorana” Centre for Scientific Culture

This is the 70th Conference of the International School of Mathematics “G. Stampacchia”, the second on Mathematical and Computational Epidemiology.