Participatory modelling to support decision making in water management under uncertainty: Two comparative case studies in the Guadiana river basin, Spain.

A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each others views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.

Phylodynamic modelling of foot-and-mouth disease virus sequence data

The under-reporting of cases of infectious diseases is a substantial impediment to the control and management of infectious diseases in both epidemic and endemic contexts. Information about infectious disease dynamics can be recovered from sequence data using time-varying coalescent approaches, and phylodynamic models have been developed in order to reconstruct demographic changes of the numbers of infected hosts through time. In this study I have demonstrated the general concordance between empirically observed epidemiological incidence data and viral demography inferred through analysis of foot-and-mouth disease virus VP1 coding sequences belonging to the CATHAY topotype over large temporal and spatial scales. However a more precise and robust relationship between the effective population size (

Sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution

Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.

Effects of flooding of the River Paraná on the temporal activity of Anopheles (Nyssorhynchus) darlingi Root (Diptera: Culicidae), at the border state of Mato Grosso do Sul and São Paulo, Brazil

INTRODUCTION: Study of the temporal activity of malaria vectors during the implantation of a hydroelectric power station on the River Paraná, intended to generate electrical energy. The river separates the States of São Paulo and Mato Grosso do Sul, in Brazil. The objective was to verify whether alterations occurred in the wealth and diversity indices of Anopheles, following two successive floods, extended to the temporal activity and nycthemeral rhythm followed over a five year period. METHODS: Mosquito capture was performed monthly using the Human Attraction Technique and Shannon Traps. The first, executed for 24h, provided the nycthemeral rhythm and the second, lasting 15h, permitted the tracking of Anopheles during the two floods. RESULTS: The bimodal pattern of Anopheles darlingi defined before these floods was modified throughout the environment interventions. The same effect had repercussions on the populations of An albitarsis s.l., An triannulatus and An galvaoi. Activity prior to twilight was less affected by the environment alterations. CONCLUSIONS: The dam construction provoked changes in Anopheles temporal activity patterns, permitting classification of the area as an ecologically steady and unstable situation. Differences observed in Anopheles behavior due to the capture methods revealed the influence of solo and multiple attractiveness inside the populations studied.

Variants of temporal defeasible logics for modelling norm modifications

This paper proposes some variants of Temporal Defeasible Logic (TDL) to reason about normative modifications. These variants make it possible to differentiate cases in which, for example, modifications at some time change legal rules but their conclusions persist afterwards from cases where also their conclusions are blocked.

Molecular characterization of the Hepatitis B virus genotypes in Colombia: A Bayesian inference on the genotype F

Hepatitis B is a worldwide health problem affecting about 2 billion people and more than 350 million are chronic carriers of the virus. Nine HBV genotypes (A to I) have been described. The geographical distribution of HBV genotypes is not completely understood due to the limited number of samples from some parts of the world. One such example is Colombia, in which few studies have described the HBV genotypes. In this study, we characterized HBV genotypes in 143 HBsAg-positive volunteer blood donors from Colombia. A fragment of 1306 bp partially comprising HBsAg and the DNA polymerase coding regions (S/POL) was amplified and sequenced. Bayesian phylogenetic analyses were conducted using the Markov Chain Monte Carlo (MCMC) approach to obtain the maximum clade credibility (MCC) tree using BEAST v.1.5.3. Of all samples, 68 were positive and 52 were successfully sequenced. Genotype F was the most prevalent in this population (77%) - subgenotypes F3 (75%) and Fib (2%). Genotype G (7.7%) and subgenotype A2 (15.3%) were also found. Genotype G sequence analysis suggests distinct introductions of this genotype in the country. Furthermore, we estimated the time of the most recent common ancestor (TMRCA) for each HBV/F subgenotype and also for Colombian F3 sequences using two different datasets: (i) 77 sequences comprising 1306 bp of S/POL region and (ii) 283 sequences comprising 681 bp of S/POL region. We also used two other previously estimated evolutionary rates: (i) 2.60 x 10(-4) s/s/y and (ii) 1.5 x 10(-5) s/s/y. Here we report the HBV genotypes circulating in Colombia and estimated the TMRCA for the four different subgenotypes of genotype F. (C) 2010 Elsevier B.V. All rights reserved.

Mathematical modelling of schistosomiasis japonica: comparison of control strategies in the People's Republic of China

We present the first mathematical model on the transmission dynamics of Schistosoma japonicum. The work extends Barbour's classic model of schistosome transmission. It allows for the mammalian host heterogeneity characteristic of the S. japonicum life cycle, and solves the problem of under-specification of Barbour's model by the use of Chinese data we are collecting on human-bovine transmission in the Poyang Lake area of Jiangxi Province in China. The model predicts that in the lake/marshland areas of the Yangtze River basin: (1) once-early mass chemotherapy of humans is little better than twice-yearly mass chemotherapy in reducing human prevalence. Depending on the heterogeneity of prevalence within the population, targeted treatment of high prevalence groups, with lower overall coverage, can be more effective than mass treatment with higher overall coverage. Treatment confers a short term benefit only, with prevalence rising to endemic levels once chemotherapy programs are stopped (2) depending on the relative contributions of bovines and humans, bovine treatment can benefit humans almost as much as human treatment. Like human treatment, bovine treatment confers a short-term benefit. A combination of human and bovine treatment will dramatically reduce human prevalence and maintains the reduction for a longer period of time than treatment of a single host, although human prevalence rises once treatment ceases; (3) assuming 75% coverage of bovines, a bovine vaccine which acts on worm fecundity must have about 75% efficacy to reduce the reproduction rate below one and ensure mid-term reduction and long-term elimination of the parasite. Such a vaccination program should be accompanied by an initial period of human treatment to instigate a short-term reduction in prevalence, following which the reduction is enhanced by vaccine effects; (4) if the bovine vaccine is only 45% efficacious (the level of current prototype vaccines) it will lower the endemic prevalence, but will not result in elimination. If it is accompanied by an initial period of human treatment and by a 45% improvement in human sanitation or a 30% reduction in contaminated water contact by humans, elimination is then possible. (C) 2002 Elsevier Science B.V. All rights reserved.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

SEROLOGICAL DETECTION OF HEPATITIS A VIRUS IN FREE-RANGING NEOTROPICAL PRIMATES (Sapajus spp., Alouatta caraya) FROM THE PARANÁ RIVER BASIN, BRAZIL

Nonhuman primates are considered as the natural hosts of Hepatitis A virus (HAV), as well as other pathogens, and can serve as natural sentinels to investigate epizootics and endemic diseases that are of public health importance. During this study, blood samples were collected from 112 Neotropical primates (NTPs) (Sapajus nigritus and S. cay, n = 75; Alouatta caraya, n = 37) trap-captured at the Paraná River basin, Brazil, located between the States of Paraná and Mato Grosso do Sul. Anti-HAV IgG antibodies were detected in 4.5% (5/112) of NTPs, specifically in 6.7% (5/75) of Sapajus spp. and 0% (0/37) of A. caraya. In addition, all samples were negative for the presence of IgM anti-HAV antibodies. These results suggest that free-ranging NTPs were exposed to HAV within the geographical regions evaluated.

Effects of flooding of the River Paraná on the temporal activity of Anopheles (Nyssorhynchus) darlingi Root (Diptera: Culicidae), at the border state of Mato Grosso do Sul and São Paulo, Brazil

INTRODUCTION: Study of the temporal activity of malaria vectors during the implantation of a hydroelectric power station on the River Paraná, intended to generate electrical energy. The river separates the States of São Paulo and Mato Grosso do Sul, in Brazil. The objective was to verify whether alterations occurred in the wealth and diversity indices of Anopheles, following two successive floods, extended to the temporal activity and nycthemeral rhythm followed over a five year period. METHODS: Mosquito capture was performed monthly using the Human Attraction Technique and Shannon Traps. The first, executed for 24h, provided the nycthemeral rhythm and the second, lasting 15h, permitted the tracking of Anopheles during the two floods. RESULTS: The bimodal pattern of Anopheles darlingi defined before these floods was modified throughout the environment interventions. The same effect had repercussions on the populations of An albitarsis s.l., An triannulatus and An galvaoi. Activity prior to twilight was less affected by the environment alterations. CONCLUSIONS: The dam construction provoked changes in Anopheles temporal activity patterns, permitting classification of the area as an ecologically steady and unstable situation. Differences observed in Anopheles behavior due to the capture methods revealed the influence of solo and multiple attractiveness inside the populations studied.

Serological evidence for Saint Louis encephalitis virus in free-ranging New World monkeys and horses within the upper Paraná River basin region, Southern Brazil

Introduction Saint Louis encephalitis virus (SLEV) primarily occurs in the Americas and produces disease predominantly in humans. This study investigated the serological presence of SLEV in nonhuman primates and horses from southern Brazil. Methods From June 2004 to December 2005, sera from 133 monkeys (Alouatta caraya, n=43; Sapajus nigritus, n=64; Sapajus cay, n=26) trap-captured at the Paraná River basin region and 23 blood samples from farm horses were obtained and used for the serological detection of a panel of 19 arboviruses. All samples were analyzed in a hemagglutination inhibition (HI) assay; positive monkey samples were confirmed in a mouse neutralization test (MNT). Additionally, all blood samples were inoculated into C6/36 cell culture for viral isolation. Results Positive seroreactivity was only observed for SLEV. A prevalence of SLEV antibodies in sera was detected in Alouatta caraya (11.6%; 5/43), Sapajus nigritus (12.5%; 8/64), and S. cay (30.8%; 8/26) monkeys with the HI assay. Of the monkeys, 2.3% (1/42) of A. caraya, 6.3% 94/64) of S. nigritus, and 15.4% (4/26) of S. cay were positive for SLEV in the MNT. Additionally, SLEV antibodies were detected by HI in 39.1% (9/23) of the horses evaluated in this study. Arboviruses were not isolated from any blood sample. Conclusions These results confirmed the presence of SLEV in nonhuman primates and horses from southern Brazil. These findings most likely represent the first detection of this virus in nonhuman primates beyond the Amazon region. The detection of SLEV in animals within a geographical region distant from the Amazon basin suggests that there may be widespread and undiagnosed dissemination of this disease in Brazil.

Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.

Temporal distribution of dengue virus serotypes in Colombian endemic area and dengue incidence: re-introduction of dengue-3 associated to mild febrile illness and primary infection

We have investigated the temporal distribution of dengue (DEN) virus serotypes in the department (state) of Santander, Colombia, in relation to dengue incidence, infection pattern, and severity of disease. Viral isolation was attended on a total of 1452 acute serum samples collected each week from 1998 to 2004. The infection pattern was evaluated in 596 laboratory-positive dengue cases using an IgG ELISA, and PRNT test. The dengue incidence was documented by the local health authority. Predominance of DEN-1 in 1998 and DEN-3 re-introduction and predominance in 2001-2003 coincided with outbreaks. Predominance of DEN-2 in 2000-2001 coincided with more dengue hemorrhagic fever (DHF). DEN-4 was isolated in 2000-2001 and 2004 but was not predominant. There was an annual increase of primary dengue infections (from 13.7 to 81.4%) that correlated with frequency of DEN-3 (r = 0.83; P = 0.038). From the total number of primary dengue infections DEN-3 (81.3%) was the most frequent serotype. DHF was more frequent in DEN-2 infected patients than in DEN-3 infected patients: 27.5 vs 10.9% (P < 0.05). DEN-3 viruses belonged to subtype C (restriction site-specific-polymerase chain reaction) like viruses isolated in Sri-Lanka and other countries in the Americas. Our findings show the importance of continuous virological surveillance to identify the risk factors of dengue epidemics and severity.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.