Development of the health and economic consequences of smoking interactive model

Objective-To describe the health and economic consequences of smoking model, a user friendly, web based tool, designed to estimate the health and economic outcomes associated with smoking and the benefits of smoking cessation. Results-An overview of the development of the model equations and user interface is given, and data from the UK are presented as an example of the model outputs. These results show that a typical smoking cessation strategy costs approximately pound 1200 per life year saved and pound 22 000 per death averted. Conclusions-The model successfully captures the complexity required to model smoking behaviour and associated mortality, morbidity, and health care costs. Furthermore, the interface provides the results in a simple and flexible way so as to be useful to a variety of audiences and to simulate a variety of smoking cessation methods

The burden of non communicable diseases in developing countries

Background: By the dawn of the third millennium, non communicable diseases are sweeping the entire globe, with an increasing trend in developing countries where, the transition imposes more constraints to deal with the double burden of infective and non-infective diseases in a poor environment characterised by ill-health systems. By 2020, it is predicted that these diseases will be causing seven out of every 10 deaths in developing countries. Many of the non communicable diseases can be prevented by tackling associated risk factors. Methods: Data from national registries and international organisms are collected, compared and analyzed. The focus is made on the growing burden of non communicable diseases in developing countries. Results: Among non communicable diseases, special attention is devoted to cardiovascular diseases, diabetes, cancer and chronic pulmonary diseases. Their burden is affecting countries worldwide but with a growing trend in developing countries. Preventive strategies must take into account the growing trend of risk factors correlated to these diseases. Conclusion: Non communicable diseases are more and more prevalent in developing countries where they double the burden of infective diseases. If the present trend is maintained, the health systems in low-and middle-income countries will be unable to support the burden of disease. Prominent causes for heart disease, diabetes, cancer and pulmonary diseases can be prevented but urgent (preventive) actions are needed and efficient strategies should deal seriously with risk factors like smoking, alcohol, physical inactivity and western diet

Estimation of COVID-19 spread curves integrating global data and borrowing information

Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. The rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. There are no drugs or other therapeutics approved by the US Food and Drug Administration to prevent or treat COVID-19: information on the disease is very limited and scattered even if it exists. This motivates the use of data integration, combining data from diverse sources and eliciting useful information with a unified view of them. In this paper, we propose a Bayesian hierarchical model that integrates global data for real-time prediction of infection trajectory for multiple countries. Because the proposed model takes advantage of borrowing information across multiple countries, it outperforms an existing individual country-based model. As fully Bayesian way has been adopted, the model provides a powerful predictive tool endowed with uncertainty quantification. Additionally, a joint variable selection technique has been integrated into the proposed modeling scheme, which aimed to identify possible country-level risk factors for severe disease due to COVID-19

A Globally Consistent Framework for Reliability-based Trade Statistics Reconciliation in the Presence of an Entrepôt

This paper develops a mathematicla programming model to reconcile trade statistics subject to a set of global consistency conditions in the presence of an entrepot. Initial data reliability serves a key function for governing the magnitude of adjustment. Through a two-stage optimization procedure, the adjusted trade statistics are achived as solutions to a system of simultaneous equations that minimize a quadratic penalty function. As an empirical illustration, the model is applied to reconcile the 2004 trade statistics reported by China, Hong Kong, and their major trading partners, initialized with detailed estimates of bilateral trade flows, re-export markups, cif/fob ratios and data reliability indexes.trade statistics reconciliation, entrepot trade, data reliability, global consistency

The UK's Global Health Respiratory Network: Improving respiratory health of the world's poorest through research collaborations.

Respiratory disorders are responsible for considerable morbidity, health care utilisation, societal costs and approximately one in five deaths worldwide [1-4]. Yet, despite this substantial health and societal burden – which particularly affects the world’s poorest populations and as such is a major contributor to global health inequalities – respiratory disorders have historically not received the policy priority they warrant. For example, despite causing an estimated 1000 deaths per day, less than half of the world’s countries collect data on asthma prevalence (http://www.globalasthmareport.org/). This is true for both communicable and non-communicable respiratory disorders, many of which are either amenable to treatment or preventable

The Heckscher-Ohlin Model and the Network Structure of International Trade

This paper estimates for 28 product groups a characteristic parameter that reflects the topological structure of its trading network. Using these estimates, it then describes how the structure of international trade has evolved during the 1980-2000 period. Thereafter, it demonstrates the importance of networks in international trade by explicitly accounting for their scaling properties when testing the prediction of the Heckscher-Ohlin model that factor endowment differentials determine bilateral trade flows. The results suggest that differences in factor endowments increase bilateral trade in goods that are traded in "dispersed" networks. For goods that are traded in "concentrated" networks, factor endowment differentials are less important.Networks, international trade, gravity model

The opportunity cost of negative screening in socially responsible investing

This paper investigates the impact of negative screening on the investment universe as well as on financial performance. We come up with a novel identification process and as such depart from mainstream socially responsible investing literature by concentrating on individual firms’ conduct and by studying a much wider range of issues. Firstly, we study the size and financial performance of fourteen potentially controversial issues: abortion, adult entertainment, alcohol, animal testing, contraceptives, controversial weapons, fur, gambling, genetic engineering, meat, nuclear power, pork, (embryonic) stem cells, and tobacco. We investigate an international sample of more than 1,600 stocks for more than twenty years. We then analyze the impact of applying negative screens to a market portfolio. Our findings suggest that the choice for negative screening strategies does matter for the size of the investment universe as well as for risk-adjusted return performance. Investing in controversial stocks in many cases results in additional risk-adjusted returns, whereas excluding them may reduce financial performance. These findings suggest that there are opportunity costs to negative screening.Publisher PDFPeer reviewe

Comparing Strategies to Prevent Stroke and Ischemic Heart Disease in the Tunisian Population: Markov Modeling Approach Using a Comprehensive Sensitivity Analysis Algorithm.

Background. Mathematical models offer the potential to analyze and compare the effectiveness of very different interventions to prevent future cardiovascular disease. We developed a comprehensive Markov model to assess the impact of three interventions to reduce ischemic heart diseases (IHD) and stroke deaths: (i) improved medical treatments in acute phase, (ii) secondary prevention by increasing the uptake of statins, (iii) primary prevention using health promotion to reduce dietary salt consumption. Methods. We developed and validated a Markov model for the Tunisian population aged 35–94 years old over a 20-year time horizon. We compared the impact of specific treatments for stroke, lifestyle, and primary prevention on both IHD and stroke deaths. We then undertook extensive sensitivity analyses using both a probabilistic multivariate approach and simple linear regression (metamodeling). Results. The model forecast a dramatic mortality rise, with 111,134 IHD and stroke deaths (95% CI 106567 to 115048) predicted in 2025 in Tunisia. The salt reduction offered the potentially most powerful preventive intervention that might reduce IHD and stroke deaths by 27% (−30240 [−30580 to −29900]) compared with 1% for medical strategies and 3% for secondary prevention. The metamodeling highlighted that the initial development of a minor stroke substantially increased the subsequent probability of a fatal stroke or IHD death. Conclusions. The primary prevention of cardiovascular disease via a reduction in dietary salt consumption appeared much more effective than secondary or tertiary prevention approaches. Our simple but comprehensive model offers a potentially attractive methodological approach that might now be extended and replicated in other contexts and populations