Modelling dependence in a ratemaking procedure with multivariate Poisson regression models

When actuaries face with the problem of pricing an insurance contract that contains different types of coverage, such as a motor insurance or homeowner's insurance policy, they usually assume that types of claim are independent. However, this assumption may not be realistic: several studies have shown that there is a positive correlation between types of claim. Here we introduce different regression models in order to relax the independence assumption, including zero-inflated models to account for excess of zeros and overdispersion. These models have been largely ignored to multivariate Poisson date, mainly because of their computational di±culties. Bayesian inference based on MCMC helps to solve this problem (and also lets us derive, for several quantities of interest, posterior summaries to account for uncertainty). Finally, these models are applied to an automobile insurance claims database with three different types of claims. We analyse the consequences for pure and loaded premiums when the independence assumption is relaxed by using different multivariate Poisson regression models and their zero-inflated versions.

Morphological aspects of the myocarditis and myositis in Calomys callosus experimentally infected with Trypanosoma cruzi: fibrogenesis and spontaneous regression of fibrosis

Calomys callosus a wild rodent, is a natural host of Trypanosoma cruzi. Twelve C. callosus were infected with 10(5) trypomastigotes of the F strain (a myotropic strain) of T. cruzi. Parasitemia decreased on the 21 st day becoming negative around the 40th day of infection. All animals survived but had positive parasitological tests, until the end of the experiment. The infected animals developed severe inflammation in the myocardium and skeletal muscle. This process was pronounced from the 26 th to the 30th day and gradually subsided from the 50 th day becoming absent or residual on the 64 th day after infection. Collagen was identified by the picro Sirius red method. Fibrogenesis developed early, but regression of fibrosis occurred between the 50th and 64th day. Ultrastructural study disclosed a predominance of macrophages and fibroblasts in the inflammatory infiltrates, with small numbers of lymphocytes. Macrophages had active phagocytosis and showed points of contact with altered muscle cells. Different degrees of matrix expansion were present, with granular and fibrilar deposits and collagen bundles. These alterations subsided by the 64th days. Macrophages seem to be the main immune effector cell in the C. callosus model of infection with T. cruzi. The mechanisms involved in the rapid fibrogenesis and its regression deserve further investigation.

The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.

The snail hosts of schistosomiasis: some evolutionary and ecological perspectives in relation to control

Despite opportunities for radiation provided by spatio-temporal isolation, the basic morphological plan of pulmonate snails has remained conservative. In consequence of the resulting dearth of morphological characters and their plasticity, there is a case for using biochemical characters such as exogenous chemicals released by the snails (e.g. amino acids) and their chemoreception niche as taxonomic aids to classify snails of medical importance. As these same chemicals are used by snails to distinguish conspecifics they could also be used as "environmental antibodies" in controlled release formulations (CRF's) designed to remove target snails in a specific, cost-effective and ecologically acceptable manner. The snails, surface-living bacteria, algae and macrophytic plants are considered as co-evolved, interactive modular systems with strong mutualistic elements. Recently, anthropogenic perturbations such as deforestation, and damming of flowing waters, have benefited these modules whereas others such as river canalization, acid deposition, accumulation of pesticide residues and eutrophication have harmed them. Research is needed to elucidate the factors which limit the growth of snails in primitive habitats, uninfluenced by man, as well as in those subject to harmful anthropogenic factors. The understanding thus gained could be applied to develop cost-effective primary health care strategies to reduce or prevent transmission of schistosomiasis and other water related diseases.

Evolutionary and convergence stability for continuous phenotypes in finite populations derived from two-allele models.

The evolution of a quantitative phenotype is often envisioned as a trait substitution sequence where mutant alleles repeatedly replace resident ones. In infinite populations, the invasion fitness of a mutant in this two-allele representation of the evolutionary process is used to characterize features about long-term phenotypic evolution, such as singular points, convergence stability (established from first-order effects of selection), branching points, and evolutionary stability (established from second-order effects of selection). Here, we try to characterize long-term phenotypic evolution in finite populations from this two-allele representation of the evolutionary process. We construct a stochastic model describing evolutionary dynamics at non-rare mutant allele frequency. We then derive stability conditions based on stationary average mutant frequencies in the presence of vanishing mutation rates. We find that the second-order stability condition obtained from second-order effects of selection is identical to convergence stability. Thus, in two-allele systems in finite populations, convergence stability is enough to characterize long-term evolution under the trait substitution sequence assumption. We perform individual-based simulations to confirm our analytic results.

Immunological system and Schistosoma mansoni: co-evolutionary immunobiology. What is the eosinophil role in parasite-host relationship?

Schistosomes, ancestors and recent species, have pervaded many hosts and several phylogenetic levels of immunity, causing an evolutionary pressure to eosinophil lineage expression and response. Schistosoma mansoni adult worms have capitalized on the apparent adversity of living within the mesenteric veins, using the dispersion of eggs and antigens to other tissues besides intestines to set a systemic activation of several haematopoietic lineages, specially eosinophils and monocytes/macrophages. This activation occurs in bone marrow, spleen, liver, lymph nodes, omental and mesenteric milky spots (activation of the old or primordial and recent or new lymphomyeloid tissue), increasing and making easy the migration of eosinophils, monocytes and other cells to the intestinal periovular granulomas. The exudative perigranulomatous stage of the periovular reaction, which present hystolitic characteristics, is then exploited by the parasites, to release the eggs into the intestinal lumen. The authors hypothesize here that eosinophils, which have a long phylogenic story, could participate in the parasite - host co-evolution, specially with S. mansoni, operating together with monocytes/ macrophages, upon parasite transmission.

Mixture of bivariate Poisson regression models with an application to insurance

In a recent paper Bermúdez [2009] used bivariate Poisson regression models for ratemaking in car insurance, and included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. In the present paper, we revisit this model in order to consider alternatives. We propose a 2-finite mixture of bivariate Poisson regression models to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, we show that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Additionally, we describe a model in which the mixing proportions are dependent on covariates when modelling the way in which each individual belongs to a separate cluster. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to the same automobile insurance claims data set as used in Bermúdez [2009] and it is shown that the modelling of the data set can be improved considerably.

An algorithm for semi-infinite polynomial optimization

"Vegeu el resum a l'inici del document del fitxer adjunt."

Evolutionary Control of Infectious Disease: Prospects for Vectorborne and Waterborne Pathogens

Evolutionary theory may contribute to practical solutions for control of disease by identifying interventions that may cause pathogens to evolve to reduced virulence. Theory predicts, for example, that pathogens transmitted by water or arthropod vectors should evolve to relatively high levels of virulence because such pathogens can gain the evolutionary benefits of relatively high levels of host exploitation while paying little price from host illness. The entrance of Vibrio cholerae into South America in 1991 has generated a natural experiment that allows testing of this idea by determining whether geographic and temporal variations in toxigenicity correspond to variation in the potential for waterborne transmission. Preliminary studies show such correspondences: toxigenicity is negatively associated with access to uncontaminated water in Brazil; and in Chile, where the potential for waterborne transmission is particularly low, toxigenicity of strains declined between 1991 and 1998. In theory vector-proofing of houses should be similarly associated with benignity of vectorborne pathogens, such as the agents of dengue, malaria, and Chagas' disease. These preliminary studies draw attention to the need for definitive prospective experiments to determine whether interventions such as provisioning of uncontaminated water and vector-proofing of houses cause evolutionary reductions in virulence

THE USE OF SIMULATIONS IN EVOLUTIONARY POPULATION GENETICS: APPLICATIONS ON HUMANS, OWLS AND VIRTUAL ORGANISMS

Summary (in English) Computer simulations provide a practical way to address scientific questions that would be otherwise intractable. In evolutionary biology, and in population genetics in particular, the investigation of evolutionary processes frequently involves the implementation of complex models, making simulations a particularly valuable tool in the area. In this thesis work, I explored three questions involving the geographical range expansion of populations, taking advantage of spatially explicit simulations coupled with approximate Bayesian computation. First, the neutral evolutionary history of the human spread around the world was investigated, leading to a surprisingly simple model: A straightforward diffusion process of migrations from east Africa throughout a world map with homogeneous landmasses replicated to very large extent the complex patterns observed in real human populations, suggesting a more continuous (as opposed to structured) view of the distribution of modern human genetic diversity, which may play a better role as a base model for further studies. Second, the postglacial evolution of the European barn owl, with the formation of a remarkable coat-color cline, was inspected with two rounds of simulations: (i) determine the demographic background history and (ii) test the probability of a phenotypic cline, like the one observed in the natural populations, to appear without natural selection. We verified that the modern barn owl population originated from a single Iberian refugium and that they formed their color cline, not due to neutral evolution, but with the necessary participation of selection. The third and last part of this thesis refers to a simulation-only study inspired by the barn owl case above. In this chapter, we showed that selection is, indeed, effective during range expansions and that it leaves a distinguished signature, which can then be used to detect and measure natural selection in range-expanding populations. Résumé (en français) Les simulations fournissent un moyen pratique pour répondre à des questions scientifiques qui seraient inabordable autrement. En génétique des populations, l'étude des processus évolutifs implique souvent la mise en oeuvre de modèles complexes, et les simulations sont un outil particulièrement précieux dans ce domaine. Dans cette thèse, j'ai exploré trois questions en utilisant des simulations spatialement explicites dans un cadre de calculs Bayésiens approximés (approximate Bayesian computation : ABC). Tout d'abord, l'histoire de la colonisation humaine mondiale et de l'évolution de parties neutres du génome a été étudiée grâce à un modèle étonnement simple. Un processus de diffusion des migrants de l'Afrique orientale à travers un monde avec des masses terrestres homogènes a reproduit, dans une très large mesure, les signatures génétiques complexes observées dans les populations humaines réelles. Un tel modèle continu (opposé à un modèle structuré en populations) pourrait être très utile comme modèle de base dans l'étude de génétique humaine à l'avenir. Deuxièmement, l'évolution postglaciaire d'un gradient de couleur chez l'Effraie des clocher (Tyto alba) Européenne, a été examiné avec deux séries de simulations pour : (i) déterminer l'histoire démographique de base et (ii) tester la probabilité qu'un gradient phénotypique, tel qu'observé dans les populations naturelles puisse apparaître sans sélection naturelle. Nous avons montré que la population actuelle des chouettes est sortie d'un unique refuge ibérique et que le gradient de couleur ne peux pas s'être formé de manière neutre (sans l'action de la sélection naturelle). La troisième partie de cette thèse se réfère à une étude par simulations inspirée par l'étude de l'Effraie. Dans ce dernier chapitre, nous avons montré que la sélection est, en effet, aussi efficace dans les cas d'expansion d'aire de distribution et qu'elle laisse une signature unique, qui peut être utilisée pour la détecter et estimer sa force.

Genetic Data Showing Evolutionary Links between Leishmania and Endotrypanum

Striking similarities at the morphological, molecular and biological levels exist between many trypanosomatids isolated from sylvatic insects and/or vertebrate reservoir hosts that make the identification of medically important parasites demanding. Some molecular data have pointed to the relationship between some Leishmania species and Endotrypanum, which has an important epidemiological significance and can be helpful to understand the evolution of those parasites. In this study, we have demonstrated a close genetic relationship between Endotrypanum and two new leishmanial species, L. (V.) colombiensis and L. (V.) equatorensis. We have used (a) numerical zymotaxonomy and (b) the variability of the internal transcribed spacers of the rRNA genes to examine relationships in this group. The evolutionary trees obtained revealed high genetic similarity between L. (V.) colombiensis, L. (V.) equatorensis and Endotrypanum, forming a tight cluster of parasites. Based on further results of (c) minicircle kDNA heterogeneity analysis and (d) measurement of the sialidase activity these parasites were also grouped together.