2,127 research outputs found

    Health cycles and health transitions

    Get PDF
    We study the dynamics of poverty and health in a model of endogenous growth and rational health behavior. Population health depends on the prevalence of infectious diseases that can be avoided through costly prevention. The incentive to do so comes from the negative effects of ill health on the quality and quantity of life. The model can generate a poverty trap where infectious diseases cycle between high and low prevalence. These cycles originate from the rationality of preventive behavior in contrast to the predator-prey dynamics of epidemiological models. We calibrate the model to reflect sub-Saharan Africa's recent economic recovery and analyze policy alternatives. Unconditional transfers are found to improve welfare relative to conditional health-based transfers: at low income levels, income growth (quality of life) is valued more than improvements to health (quantity of life)

    Parameter Identification in a Tuberculosis Model for Cameroon

    Get PDF
    A deterministic model of tuberculosis in Cameroon is designed and analyzed with respect to its transmission dynamics. The model includes lack of access to treatment and weak diagnosis capacity as well as both frequency-and density-dependent transmissions. It is shown that the model is mathematically well-posed and epidemiologically reasonable. Solutions are non-negative and bounded whenever the initial values are non-negative. A sensitivity analysis of model parameters is performed and the most sensitive ones are identified by means of a state-of-the-art Gauss-Newton method. In particular, parameters representing the proportion of individuals having access to medical facilities are seen to have a large impact on the dynamics of the disease. The model predicts that a gradual increase of these parameters could significantly reduce the disease burden on the population within the next 15 years.IMU Berlin Einstein Foundation Progra

    Dynamics of Information Diffusion and Social Sensing

    Full text link
    Statistical inference using social sensors is an area that has witnessed remarkable progress and is relevant in applications including localizing events for targeted advertising, marketing, localization of natural disasters and predicting sentiment of investors in financial markets. This chapter presents a tutorial description of four important aspects of sensing-based information diffusion in social networks from a communications/signal processing perspective. First, diffusion models for information exchange in large scale social networks together with social sensing via social media networks such as Twitter is considered. Second, Bayesian social learning models and risk averse social learning is considered with applications in finance and online reputation systems. Third, the principle of revealed preferences arising in micro-economics theory is used to parse datasets to determine if social sensors are utility maximizers and then determine their utility functions. Finally, the interaction of social sensors with YouTube channel owners is studied using time series analysis methods. All four topics are explained in the context of actual experimental datasets from health networks, social media and psychological experiments. Also, algorithms are given that exploit the above models to infer underlying events based on social sensing. The overview, insights, models and algorithms presented in this chapter stem from recent developments in network science, economics and signal processing. At a deeper level, this chapter considers mean field dynamics of networks, risk averse Bayesian social learning filtering and quickest change detection, data incest in decision making over a directed acyclic graph of social sensors, inverse optimization problems for utility function estimation (revealed preferences) and statistical modeling of interacting social sensors in YouTube social networks.Comment: arXiv admin note: text overlap with arXiv:1405.112

    Numerical optimal control for HIV prevention with dynamic budget allocation

    Full text link
    This paper is about numerical control of HIV propagation. The contribution of the paper is threefold: first, a novel model of HIV propagation is proposed; second, the methods from numerical optimal control are successfully applied to the developed model to compute optimal control profiles; finally, the computed results are applied to the real problem yielding important and practically relevant results.Comment: Submitted pape

    Using neutral cline decay to estimate contemporary dispersal: a generic tool and its application to a major crop pathogen

    Get PDF
    Dispersal is a key parameter of adaptation, invasion and persistence. Yet standard population genetics inference methods hardly distinguish it from drift and many species cannot be studied by direct mark-recapture methods. Here, we introduce a method using rates of change in cline shapes for neutral markers to estimate contemporary dispersal. We apply it to the devastating banana pest Mycosphaerella fijiensis, a wind-dispersed fungus for which a secondary contact zone had previously been detected using landscape genetics tools. By tracking the spatio-temporal frequency change of 15 microsatellite markers, we find that σ, the standard deviation of parent–offspring dispersal distances, is 1.2 km/generation1/2. The analysis is further shown robust to a large range of dispersal kernels. We conclude that combining landscape genetics approaches to detect breaks in allelic frequencies with analyses of changes in neutral genetic clines offers a powerful way to obtain ecologically relevant estimates of dispersal in many species

    Health Cycles and Health Transitions

    Get PDF
    We study the dynamics of poverty and health in a model of endogenous growth and rational health behavior. Population health depends on the prevalence of infectious diseases that can be avoided through costly prevention. The incentive to do so comes from the negative effects of ill health on the quality and quantity of life. The model can generate a poverty trap where infectious diseases cycle between high and low prevalence. These cycles originate from the rationality of preventive behavior in contrast to the predator–prey dynamics of epidemiological models. We calibrate the model to reflect sub-Saharan Africa's recent economic recovery and analyze policy alternatives. Unconditional transfers are found to improve welfare relative to conditional health-based transfers: at low income levels, income growth (quality of life) is valued more than improvements to health (quantity of life).Spanish Ministerio de Economia y Competitividad (Grant ECO2012-36719)
    corecore