Representation for Evolution of Epidemic Models

Creating a representation capable of generating personal contact networks that are most likely to exhibit specific epidemic behavior is difficult due to the inherit volatility of an epidemic and the numerous parameters accompanying the problem. To surpass these hurdles, evolutionary algorithms are used to create a generative solution which generates personal contact networks, modeling human populations, to satisfy the epidemic duration and epidemic profile matching problems. This representation is entitled the Local THADS-N representation. Two new operators are added to the original THADS-N system, and tested with a traditional parameter sweep and a parameter selection method known as point packing on nine epidemic profiles. Additionally, a new epidemic model is implemented in order to allow for lost immunity within a population thus increasing the length of an epidemic.Natural Sciences and Engineering Research Council of Canada (NSERC

Modelling of Vaccination Strategies for Epidemics using Evolutionary Computation

Personal contact networks that represent social interactions can be used to identify who can infect whom during the spread of an epidemic. The structure of a personal contact network has great impact upon both epidemic duration and the total number of infected individuals. A vaccine, with varying degrees of success, can reduce both the length and spread of an epidemic, but in the case of a limited supply of vaccine a vaccination strategy must be chosen, and this has a significant effect on epidemic behaviour.In this study we consider four different vaccination strategies and compare their effects upon epidemic duration and spread. These are random vaccination, high degree vaccination, ring vaccination, and the base case of no vaccination. All vaccinations are applied as the epidemic progresses, as opposed to in advance. The strategies are initially applied to static personal contact networks that are known ahead of time. They are then applied to personal contact networks that are evolved as the vaccination strategy is applied. When any form of vaccination is applied, all strategies reduce both duration and spread of the epidemic. When applied to a static network, random vaccination performs poorly in terms of reducing epidemic duration in comparison to strategies that take into account connectivity of the network. However, it performs surprisingly well when applied on the evolved networks, possibly because the evolutionary algorithm is unable to take advantage of a fixed strategy

Parameter selection for modeling of epidemic networks

The accurate modeling of epidemics on social contact networks is difficult due to the variation between different epidemics and the large number of parameters inherent to the problem. To reduce complexity, evolutionary computation is used to create a generative representation of the epidemic model. Previous gains from the use of local, verses global, operators are further explored to better balance exploration and exploitation of the genetic algorithm. A typical parameter study is conducted to test this new local operator and the new method of point packing is utilized as a proof of concept to perform a better search of the parameter space. All experiments from both approaches are tested against nine epidemic profiles. The point-packing driven parameter search demonstrates that the algorithm parameters interact substantially and in a non-linear fashion, and also shows that the good parameter settings are problem specific.Natural Sciences and Engineering Research Council of Canad

Evolving the Curve

Evolutionary algorithms are used to generate personal contact networks, modelling human populations, that are most likely to match a given epidemic profile. The Susceptible-Infected-Removed (SIR) model is used and also expanded upon to allow for an extended period of infection, termed the SIIR model. The networks generated for each of these models are thoroughly evaluated for their ability to match nine different epidemic profiles. The addition of the SIIR model showed that the model of infection has an impact on the networks generated. For the SIR and SIIR models, these differences were relatively minor in most cases.Natural Sciences and Engineering Research Council of Canad

Pandemic: A Graph Evolution Story

The Graph Evolution Tool (GET)was built to generate personal contact networks representing who can infect whom within a community. The tool is expanded in order to permit an infection scheme which divides the community into different districts, thus permitting within-district and between-district infections. The evolutionary algorithm comprising GET is expanded upon to simulate communities which include 512 individuals in up to eight districts, initially infecting one person in one district and spreading through a community. The overall goal is to generate communities that will maximize the length of an epidemic. The problem associated with adequately exploring the numerous parameters accompanying evolutionary algorithms is addressed using a point packing and insight from previous work. The Susceptible-Infected-Removed (SIR)model of infection was chosen as it provides a sufficient balance of simplicity and complexity for the problem

Implications of the 2740 Ma Cote Gold Au(-Cu) deposit for Archean gold metallogeny and porphyry Au deposit formation in the Archean Swayze greenstone belt, northern Ontario

International audienceOre-deposit models, which are fundamental to mineral exploration, result from integrating robust field observations with high-quality mineral-chemical-isotopic data. New discoveries departing from current models demand explanation, and in some cases new deposit models result (e.g., IOCG). The recent (2009/2010) discovery of the Cote Gold Au(-Cu) deposit in the Archean Swayze greenstone belt, northern Ontario, challenges the age-restricted view of porphyry Cu-Au models. The +8 Moz Au deposit is hosted by a subvolcanic tonalite-diorite intrusive complex where magmatic-hydrothermal breccia bodies occur. Gold mineralization, of disseminated-, fracture-and vein-types, is spatially associated with hydrothermal biotite and muscovite alteration that is similar to potassic and phyllic alteration, respectively, in porphyry-type settings. A robust program involving core logging and field mapping with structural analysis integrated with detailed petrographic studies, geochronology, lithogeochemistry, isotopes, and fluid inclusion studies (microthermometry and evaporate mound SEM-EDS analysis) was used to assess the deposit's origin. That the age of host rocks (U-Pb zircon, titanite) and timing of alteration (U-Pb titanite) and mineralization (Re-Os molybdenite) centre on 2740 Ma and pre-dates the age of regional deformation (ca. 2680 Ma), in addition to the co-spatial nature of mineralization and alteration, suggests a magmatic-hydrothermal connection. Structural analysis of auriferous quartz veins also indicates a relationship to the intrusive centre versus regional deformation, which is further supported by a 2740 Ma molybdenite age for one such gold-mineralized vein. Fluid-chemical data indicates fluid mixing with ?34S (py, cpy, moly = 0 ± 1‰) and fluid inclusions (mixed H2O-CO2 fluid (XCO2=0.10); Na-K-CaFe -Mn-Cl-F-S chemistry) suggesting a magmatic fluid reservoir whereas ?18O (qtz = 7-12‰) also indicates a possible seawater contribution. These observations are best reconciled with a deposit model involving Au(-Cu) mineralization originating from exsolution of magmatic fluids from a high-level, hydrous intermediate magma in the same manner as models for younger porphyry analogues

Metabolomic analysis revealed differences between bovine cloned embryos with contrasting development abilities

Metabolomic analysis revealed differences between bovine cloned embryos with contrasting development abilities. 31. Colloque Scientifique de l'AET