Spatial Quantification of the Population Exposed to Cryptococcus neoformans and Cryptococcus gattii Species Complexes in Europe: Estimating the Immunocompetent and HIV/AIDS Patients Under Risk

Cryptococcus is an important fungal pathogen worldwide, causing serious clinical manifestations that can affect immunocompetent patients and can be particularly severe for immunocompromised patients. The Cryptococcus gattii s.s. (AFLP4/VGI), Cryptococcus tetragattii (AFLP/VGIV), Cryptococcus neoformans, and Cryptococcus deneoformans have been isolated from both clinical and environmental sources in Europe. We aim to quantify the people in Europe and the entire Mediterranean area who are under risk associated with each of the three fungal pathogens in a spatially explicit way, generating a series of maps and population statistics per country. Niche modeling was applied to estimate the potential distribution of each fungal pathogen, then these models were overlapped with a map of population density to estimate risk levels. The potential number of people per risk level and per country was quantified using a map of population count per pixel. Prevalence of HIV per country was also included in the analysis to quantify the HIV-infected population under potential risk. People under risk associated with exposure to C. gattii species (C. gattii s.s. and C. tetragattii) reached 137.65 million, whereas those exposed to C. neoformans and C. deneoformans were 268.58 and 360.78 million people, respectively. More than a half million HIV-infected patients are exposed to each of the two species of the C. neoformans species complex, and more than 200,000 to the C. gattii species complex. The present results can be useful for public health planning by European governments, focusing on the provision of inputs for a “screen-and-treat” approach, availability of medical resources, and continuous monitoring programs in risk zones.     

Protecting From Malware Obfuscation Attacks Through Adversarial Risk Analysis

Malware constitutes a major global risk affecting millions of users each year. Standard algorithms in detection systems perform insufficiently when dealing with malware passed through obfuscation tools. We illustrate this studying in detail an open source metamorphic software, making use of a hybrid framework to obtain the relevant features from binaries. We then provide an improved alternative solution based on adversarial risk analysis which we illustrate describe with an example.     

On the estimation of the Lorenz curve under complex sampling designs

Statistical Methods & Applications - This paper focuses on the estimation of the concentration curve of a finite population, when data are collected according to a complex sampling design with...     

On Decomposing Net Final Values: Eva,Sva and Shadow Project

A decomposition model of Net Final Values (NFV), named Systemic Value Added (SVA), is proposed for decision-making purposes, based on a systemic approach introduced in Magni [Magni, C. A. (2003), Bulletin of Economic Research 55(2), 149–176; Magni, C. A. (2004) Economic Modelling 21, 595–617]. The model translates the notion of excess profit giving formal expression to a counterfactual alternative available to the decision maker. Relations with other decomposition models are studied, among which Stewart’s [Stewart, G.B. (1991), The Quest for Value: The EVA™ Management Guide, Harper Collins, Publishers Inc]. The index here introduced differs from Stewart’s Economic Value Added (EVA) in that it rests on a different interpretation of the notion of excess profit and is formally connected with the EVA model by means of a shadow project. The SVA is formally and conceptually threefold, in that it is economic, financial, accounting-flavoured. Some results are offered, providing sufficient and necessary conditions for decomposing NFV. Relations between a project’s SVA and its shadow project’s EVA are shown, all results of Pressacco and Stucchi [Pressacco, F. and Stucchi, P. (1997), Rivista di Matematica per le Scienze Economiche e Sociali 20, 165–185] are proved by making use of the systemic approach and the shadow counterparts of those results are also shown.     

Large Sample Properties of Matching Estimators for Average Treatment Effects

Matching estimators for average treatment effects are widely used in evaluation research despite the fact that their large sample properties have not been established in many cases. The absence of formal results in this area may be partly due to the fact that standard asymptotic expansions do not apply to matching estimators with a fixed number of matches because such estimators are highly nonsmooth functionals of the data. In this article we develop new methods for analyzing the large sample properties of matching estimators and establish a number of new results. We focus on matching with replacement with a fixed number of matches. First, we show that matching estimators are not N^1/2‐consistent in general and describe conditions under which matching estimators do attain N^1/2‐consistency. Second, we show that even in settings where matching estimators are N^1/2‐consistent, simple matching estimators with a fixed number of matches do not attain the semiparametric efficiency bound. Third, we provide a consistent estimator for the large sample variance that does not require consistent nonparametric estimation of unknown functions. Software for implementing these methods is available in Matlab, Stata, and R.     

Adversity-hope hypothesis: Air pollution raises lottery demand in China

Journal of Risk and Uncertainty - The empirical literature points to a stylized phenomenon of increased demand for hope following adversity. Clotfelter and Cook (1989) suggest that hope is a key...     

Markers of unsustainable gambling for early detection of at-risk online gamblers

In this work we propose novel markers for identifying at-risk gamblers based on the concept of sustainability. The first hypothesis here verified is that problematic gamblers oscillate between intervals of increasing wager size followed by rapid drops, probably because they exceed their economic sustainability limits. Due to the non-periodic nature of these fluctuations, the proposed marker detects a certain occurring feature, such as a rapid drop in wager size, over a wide range of fluctuation periods, drop sizes and shapes. The second marker, counting the number of games the gambler is involved in, aims at predicting possible consequences of an exceeding amount of time dedicated to gambling, that ultimately causes social and relational breakdowns. In the experimental phase we demonstrate how the adoption of these markers allows for identifying larger segments of high- and medium-risk gamblers with respect to previous research on actual betting behaviours.     

The Distribution of Wealth and Fiscal Policy in Economies With Finitely Lived Agents

We study the dynamics of the distribution of wealth in an overlapping generation economy with finitely lived agents and intergenerational transmission of wealth. Financial markets are incomplete, exposing agents to both labor and capital income risk. We show that the stationary wealth distribution is a Pareto distribution in the right tail and that it is capital income risk, rather than labor income, that drives the properties of the right tail of the wealth distribution. We also study analytically the dependence of the distribution of wealth—of wealth inequality in particular—on various fiscal policy instruments like capital income taxes and estate taxes, and on different degrees of social mobility. We show that capital income and estate taxes can significantly reduce wealth inequality, as do institutions favoring social mobility. Finally, we calibrate the economy to match the Lorenz curve of the wealth distribution of the U.S. economy.