The gravity model is often used in predicting the spread of influenza. We use the data of influenza A (H1N1) to check the model’s performance and validation, in order to determine the scope of its application. In this article, we proposed to model the pattern of global spread of the virus via a few important socio-economic indicators. We applied the epidemic gravity model for modelling the virus spread globally through the estimation of parameters of a generalized linear model. We compiled the daily confirmed cases of influenza A (H1N1) in each country as reported to the WHO and each state in the USA, and established the model to describe the relationship between the confirmed cases and socio-economic factors such as population size, per capita gross domestic production (GDP), and the distance between the countries/states and the country where the first confirmed case was reported (i.e., Mexico). The covariates we selected for the model were all statistically significantly associated with the global spread of influenza A (H1N1). However, within the USA, the distance and GDP were not significantly associated with the number of confirmed cases. The combination of the gravity model and generalized linear model provided a quick assessment of pandemic spread globally. The gravity model is valid if the spread period is long enough for estimating the model parameters. Meanwhile, the distance between donor and recipient communities has a good gradient. Besides, the spread should be at the early stage if a single source is taking into account.

Background: There is increasing concern regarding the potential adverse health effects of air pollution, particularly hazardous air pollutants (HAPs). However, quantifying exposure to these pollutants is problematic. Objective: Our goal was to explore the utility of kriging, a spatial interpolation method, for exposure assessment in epidemiologic studies of HAPs. We used benzene as an example and compared census tract-level kriged predictions to estimates obtained from the 1999 U.S. EPA National Air Toxics Assessment (NATA), Assessment System for Population Exposure Nationwide (ASPEN) model. Methods: Kriged predictions were generated for 649 census tracts in Harris County, Texas using estimates of annual benzene air concentrations from 17 monitoring sites operating in Harris and surrounding counties from 1998 to 2000. Year 1999 ASPEN modeled estimates were also obtained for each census tract. Spearman rank correlation analyses were performed on the modeled and kriged benzene levels. Weighted kappa statistics were computed to assess agreement between discretized kriged and modeled estimates of ambient air levels of benzene. Results: There was modest correlation between the predicted and modeled values across census tracts. Overall, 56.2%, 40.7%, 31.5% and 28.2% of census tracts were classified as having 'low', 'medium-low', 'medium-high' and 'high' ambient air levels of benzene, respectively, comparing predicted and modeled benzene levels. The weighted kappa statistic was 0.26 (95% confidence interval (CI) = 0.20, 0.31), indicating poor agreement between the two methods. Conclusions: There was a lack of concordance between predicted and modeled ambient air levels of benzene. Applying methods of spatial interpolation for assessing exposure to ambient air pollutants in health effect studies is hindered by the placement and number of existing stationary monitors collecting HAP data. Routine monitoring needs to be expanded if we are to use these data to better assess environmental health risks in the future.

Coronary flow capacity (CFC) is associated with an observed 10-year survival probability for individual patients before and after actual revascularization for comparison to virtual hypothetical ideal complete revascularization. Stress myocardial perfusion (mL/min/g) and coronary flow reserve (CFR) per pixel were quantified in 6979 coronary artery disease (CAD) subjects using Rb-82 positron emission tomography (PET) for CFC maps of artery-specific size-severity abnormalities expressed as percent left ventricle with prospective follow-up to define survival probability per-decade as fraction of 1.0. Severely reduced CFC in 6979 subjects predicted low survival probability that improved by 42% after revascularization compared with no revascularization for comparable severity (P = .0015). For 283 pre-and-post-procedure PET pairs, severely reduced regional CFC-associated survival probability improved heterogeneously after revascularization (P < .001), more so after bypass surgery than percutaneous coronary interventions (P < .001) but normalized in only 5.7%; non-severe baseline CFC or survival probability did not improve compared with severe CFC (P = .00001). Observed CFC-associated survival probability after actual revascularization was lower than virtual ideal hypothetical complete post-revascularization survival probability due to residual CAD or failed revascularization (P < .001) unrelated to gender or microvascular dysfunction. Severely reduced CFC in 2552 post-revascularization subjects associated with low survival probability also improved after repeat revascularization compared with no repeat procedures (P = .025). Severely reduced CFC and associated observed survival probability improved after first and repeat revascularization compared with no revascularization for comparable CFC severity. Non-severe CFC showed no benefit. Discordance between observed actual and virtual hypothetical post-revascularization survival probability revealed residual CAD or failed revascularization. Coronary flow capacity (CFC) and survival prediction after revascularization: physiological basis and clinical implications. CFC maps in one view before (upper row) and after revascularization (lower row) show residual diffuse coronary artery disease (CAD), stenosis, and incomplete or inappropriate revascularization as examples from 283 pre-post-revascularization positron emission tomography (PET) pairs. The 10-year survival probability is determined as a fraction of one for normal CFC (all red) by the proportional distribution of regional size-severity CFC abnormalities. The individual observed survival probabilities for each CFC map before and after actual coronary revascularization are listed below each CFC map. The virtual survival probability predicted for the baseline CFC map after virtual theoretical ideal complete revascularization is listed in the lowest (3rd) row for each case. The plots show the observed survival probability of 6979 PET cases with and without severely reduced CFC with and without non-randomized revascularization followed over 12 years as the database from which individual survival probability is determined by multi-variable CFC components by Cox regression modelling. LAD, left anterior descending coronary artery; LCx, left circumflex artery; RCA, right coronary artery.

Objectives: The potential gains in life expectancy of the US population by the partial and total elimination of deaths from HIV/AIDS were compared with that of deaths from heart disease and malignant neoplasms. Methods: The data from the 1992 advanced mortality report and detailed information provided by the National Center for Health Statistics were analysed by using the partial multiple decrement life-table technique. Results: For the total population of the United States in 1992, the gains in future life expectancy through the elimination of deaths from HIV/AIDS, heart disease and malignant neoplasms were 0.34, 3.25 and 3.21 years, respectively. The gains in life expectancy in those of working age (15–64 years) through the elimination of deaths from these three causes of deaths were 0.20, 0.40 and 0.55 years, respectively. Race/sex-specific calculations indicate that the total elimination of deaths from HIV/AIDS, heart disease and malignant neoplasms in white men of working age resulted in increased life expectancy of 0.28, 0.54 and 0.53, respectively, whereas the corresponding figures for black men were 0.82, 0.90 and 0.76 years, respectively. Although the impact of the elimination of the other causes remained relatively stable from 1987 to 1992, the potential gains in life expectancy for black men of working age by eliminating HIV/AIDS rose from 0.36 years in 1987 to 0.82 years in 1992. For the total US population of working age, the elimination of HIV/AIDS deaths resulted in increased life expectancy similar to that observed for a 50% reduction of heart disease or malignant neoplasms, whereas among black men of working age, the increased years of life expectancy from the elimination of HIV/AIDS deaths were virtually the same as those observed for the elimination of heart disease or malignant neoplasms. Conclusions: The potential gains in life expectancy by reduction of deaths from heart disease and malignant neoplasms are more heavily influenced by increasing years after the working ages (15–64 years), whereas the potential gains in life expectancy by reducing deaths from HIV/AIDS make a greater contribution to those of working age. Hence, in terms of the economic costs and benefits, these results indicate that in evaluating policy issues regarding allocation of research funds, studies of life expectancy are far more important than the simple approach which allocates funds on the basis of the number of deaths due to various diseases.