epidemix-An interactive multi-model application for teaching and visualizing infectious disease transmission

Mathematical models of disease transmission are used to improve our understanding of patterns of infection and to identify factors influencing them. During recent public and animal health crises, such as pandemic influenza, Ebola, Zika, foot-and-mouth disease, models have made important contributions in addressing policy questions, especially through the assessment of the trajectory and scale of outbreaks, and the evaluation of control interventions. However, their mathematical formulation means that they may appear as a “black box” to those without the appropriate mathematical background. This may lead to a negative perception of their utility for guiding policy, and generate expectations, which are not in line with what these models can deliver. It is therefore important for policymakers, as well as public health and animal health professionals and researchers who collaborate with modelers and use results generated by these models for policy development or research purpose, to understand the key concepts and assumptions underlying these models. The software application epidemix (http://shinyapps.rvc.ac.uk) presented here aims to make mathematical models of disease transmission accessible to a wider audience of users. By developing a visual interface for a suite of eight models, users can develop an understanding of the impact of various modelling assumptions – especially mixing patterns – on the trajectory of an epidemic and the impact of control interventions, without having to directly deal with the complexity of mathematical equations and programming languages. Models are compartmental or individual-based, deterministic or stochastic, and assume homogeneous or heterogeneous-mixing patterns (with the probability of transmission depending on the underlying structure of contact networks, or the spatial distribution of hosts). This application is intended to be used by scientists teaching mathematical modelling short courses to non-specialists – including policy makers, public and animal health professionals and students – and wishing to develop hands-on practicals illustrating key concepts of disease dynamics and control

Pricing and Hedging Asian Basket Options with Quasi-Monte Carlo Simulations

In this article we consider the problem of pricing and hedging high-dimensional Asian basket options by Quasi-Monte Carlo simulation. We assume a Black-Scholes market with time-dependent volatilities and show how to compute the deltas by the aid of the Malliavin Calculus, extending the procedure employed by Montero and Kohatsu-Higa (2003). Efficient path-generation algorithms, such as Linear Transformation and Principal Component Analysis, exhibit a high computational cost in a market with time-dependent volatilities. We present a new and fast Cholesky algorithm for block matrices that makes the Linear Transformation even more convenient. Moreover, we propose a new-path generation technique based on a Kronecker Product Approximation. This construction returns the same accuracy of the Linear Transformation used for the computation of the deltas and the prices in the case of correlated asset returns while requiring a lower computational time. All these techniques can be easily employed for stochastic volatility models based on the mixture of multi-dimensional dynamics introduced by Brigo et al. (2004).Comment: 16 page

The Bismut-Elworthy-Li type formulae for stochastic differential equations with jumps

Consider jump-type stochastic differential equations with the drift, diffusion and jump terms. Logarithmic derivatives of densities for the solution process are studied, and the Bismut-Elworthy-Li type formulae can be obtained under the uniformly elliptic condition on the coefficients of the diffusion and jump terms. Our approach is based upon the Kolmogorov backward equation by making full use of the Markovian property of the process.Comment: 29 pages, to appear in Journal of Theoretical Probabilit

Multidimensional Quasi-Monte Carlo Malliavin Greeks

We investigate the use of Malliavin calculus in order to calculate the Greeks of multidimensional complex path-dependent options by simulation. For this purpose, we extend the formulas employed by Montero and Kohatsu-Higa to the multidimensional case. The multidimensional setting shows the convenience of the Malliavin Calculus approach over different techniques that have been previously proposed. Indeed, these techniques may be computationally expensive and do not provide flexibility for variance reduction. In contrast, the Malliavin approach exhibits a higher flexibility by providing a class of functions that return the same expected value (the Greek) with different accuracies. This versatility for variance reduction is not possible without the use of the generalized integral by part formula of Malliavin Calculus. In the multidimensional context, we find convenient formulas that permit to improve the localization technique, introduced in Fourni\'e et al and reduce both the computational cost and the variance. Moreover, we show that the parameters employed for variance reduction can be obtained \textit{on the flight} in the simulation. We illustrate the efficiency of the proposed procedures, coupled with the enhanced version of Quasi-Monte Carlo simulations as discussed in Sabino, for the numerical estimation of the Deltas of call, digital Asian-style and Exotic basket options with a fixed and a floating strike price in a multidimensional Black-Scholes market.Comment: 22 pages, 6 figure

Antibiotic resistance gene sharing networks and the effect of dietary nutritional content on the canine and feline gut resistome

As one of the most densely populated microbial communities on Earth, the gut microbiota serves as an important reservoir of antibiotic resistance genes (ARGs), referred to as the gut resistome. Here, we investigated the association of dietary nutritional content with gut ARG diversity and composition, using publicly available shotgun metagenomic sequence data generated from canine and feline fecal samples. Also, based on network theory, we explored ARG-sharing patterns between gut bacterial genera by identifying the linkage structure between metagenomic assemblies and their functional genes obtained from the same data

Transmission tree of the highly pathogenic avian influenza (H5N1) epidemic in Israel, 2015

The transmission tree of the Israeli 2015 epidemic of highly pathogenic avian influenza (H5N1) was modelled by combining the spatio-temporal distribution of the outbreaks and the genetic distance between virus isolates. The most likely successions of transmission events were determined and transmission parameters were estimated. It was found that the median infectious pressure exerted at 1 km was 1.59 times (95% CI 1.04, 6.01) and 3.54 times (95% CI 1.09, 131.75) higher than that exerted at 2 and 5 km, respectively, and that three farms were responsible for all seven transmission events. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13567-016-0393-2) contains supplementary material, which is available to authorized users

Practising co-production and interdisciplinarity: Challenges and implications for one health research

We review the nature of interdisciplinary research in relation to One Health, a perspective on human-animal health which would appear to merit close interdisciplinary cooperation to inform public health policy. We discuss the relationship between biological sciences, epidemiology and the social sciences and note that interdisciplinary work demands attention be given to a range of often neglected epistemological and methodological issues. Epidemiologists may sometimes adopt social science techniques as “bolt-ons”1 to their research without having a complete understanding of how the social sciences work. The paper introduces a range of social science concepts and applies them to the challenges of understanding and practicing participatory and local epidemiology. We consider the problem of co-production of knowledge about One Health and zoonotic diseases in relation to funding structures, working in large international teams and explore some of the often-neglected realities of working across disciplines and cultures. We do this in part by applying the concept of value-chain to the research process

Patterns of Avian Influenza A (H5) and A (H9) virus infection in backyard, commercial broiler and layer chicken farms in Bangladesh

In order to control Highly Pathogenic Avian Influenza (HPAI) H5N1 and Low Pathogenic Avian Influenza (LPAI) H9N2 virus spread in endemically infected countries, a detailed understanding of infection patterns is required. We conducted cross‐sectional studies in Bangladesh in 2016 and 2017, on 144 backyard, 106 broiler and 113 layer chicken farms. Although all sampled birds were negative for H5 virus by RT‐PCR, H5 antibodies were detected in unvaccinated birds on all three farming systems. Higher H5 antibody prevalence was observed in ducks raised on backyard farms, 14.2% (95% CI: 10.0%–19.8%), compared to in‐contact backyard chickens, 4.2% (95% CI: 2.8%–6.1%). The H5 antibody prevalence was lower in broiler chickens, 1.5% (95% CI: 0.9%–2.5%), compared to layer chickens, 7.8% (95% CI: 6.1%–9.8%). H9 viruses were detected by RT‐PCR in 0.5% (95% CI: 0.2%–1.3%) and 0.6% (95% CI: 0.3%–1.5%) of broilers and layers, respectively, and in 0.2% (95% CI: 0.0%–1.2%) of backyard chickens. Backyard chickens and ducks showed similar H9 antibody prevalence, 16.0% (95% CI: 13.2%–19.2%) and 15.7% (95% CI: 11.3%–21.4%), which was higher compared to layers, 5.8% (95% CI: 4.3%–7.6%), and broilers, 1.5% (95% CI: 0.9%–2.5%). Over the course of a production cycle, H5 and H9 antibody prevalence increased with the age of backyard and layer chickens. Usually, multiple ducks within a flock were H5 antibody positive, in contrast to backyard chickens, broilers and layers where only individual birds within flocks developed H5 antibodies. Our findings highlight low virus circulation in healthy chickens of all production systems in Bangladesh, which is in contrast to high virus circulation reported from live bird markets. Data generated in this project can be used to adopt risk‐based surveillance approaches in different chicken production systems in Bangladesh and to inform mathematical models exploring HPAI infection dynamics in poultry from the source of production

Some considerations concerning the challenge of incorporating social variables into epidemiological models of infectious disease transmission

Incorporation of ‘social’ variables into epidemiological models remains a challenge. Too much detail and models cease to be useful; too little and the very notion of infection —a highly social process in human populations—may be considered with little reference to the social. The French sociologist Emile Durkheim proposed that the scientific study of society required identification and study of ‘social currents.’ Such ‘currents’ are what we might today describe as ‘emergent properties,’ specifiable variables appertaining to individuals and groups, which represent the perspectives of social actors as they experience the environment in which they live their lives. Here we review the ways in which one particular emergent property, hope, relevant to a range of epidemiological situations, might be used in epidemiological modelling of infectious diseases in human populations. We also indicate how such an approach might be extended to include a range of other potential emergent properties to repre