Prevalence and risk of hepatitis E virus infection in the HIV population of Nepal

Background: Infection with the hepatitis E virus (HEV) can cause acute hepatitis in endemic areas in immune-competent hosts, as well as chronic infection in immune-compromised subjects in non-endemic areas. Most studies assessing HEV infection in HIV-infected populations have been performed in developed countries that are usually affected by HEV genotype 3. The objective of this study is to measure the prevalence and risk of acquiring HEV among HIV-infected individuals in Nepal. Methods: We prospectively evaluated 459 Human Immunodeficiency Virus (HIV)-positive individuals from Nepal, an endemic country for HEV, for seroprevalence of HEV and assessed risk factors associated with HEV infection. All individuals were on antiretroviral therapy and healthy blood donors were used as controls. Results: We found a high prevalence of HEV IgG (39.4%) and HEV IgM (15.3%) in HIV-positive subjects when compared to healthy HIV-negative controls: 9.5% and 4.4%, respectively (OR: 6.17, 95% CI 4.42-8.61, p \u3c 0.001 and OR: 3.7, 95% CI 2.35-5.92, p \u3c 0.001, respectively). Individuals residing in the Kathmandu area showed a significantly higher HEV IgG seroprevalance compared to individuals residing outside of Kathmandu (76.8% vs 11.1%, OR: 30.33, 95% CI 18.02-51.04, p = 0.001). Mean CD4 counts, HIV viral load and presence of hepatitis B surface antigen correlated with higher HEV IgM rate, while presence of hepatitis C antibody correlated with higher rate of HEV IgG in serum. Overall, individuals with HEV IgM positivity had higher levels of alanine aminotransferase (ALT) than IgM negative subjects, suggesting active acute infection. However, no specific symptoms for hepatitis were identified. Conclusion: HIV-positive subjects living in Kathmandu are at higher risk of acquiring HEV infection as compared to the general population and to HIV-positive subjects living outside Kathmandu

Immense Industrialization And Their Air Prominent Pollutants Effect On Urban Air Quality Index

On the basis of the reported air quality index (API) and air pollutant monitoring data obtained at the Peshawar over the last seven years, the characteristics of air quality prominent pollutants and variation of the average annual concentrations of SO2, NO2total suspended particulate (TSP) fine particulates (PM10) CO and dust fall in Peshawar City were analyzed. Results showed that SO2and NO2were the prominent pollutants in the ambient air environment of Peshawar City. Of the prominent pollutants TSP accounted for nearly 63 % SO2, 32.8 ppb NO2, 147 ppb of CH4 , 13.8 ppb of CO, 94.5µg/m3of MC and 0.60 ppb of O3respectively in 2013. NO2to SO2 comparison ratio initially declined to 39.3 in 2009 and then starts to increase to 42.5 in 2010 while in 2013 reached upto 44.8 and O3 to SO2 ratio in the last year of observation, the ratio drop to 0.01830 µg/m3. Concentrations of air pollutants have shown a upward trend in recent years but they are generally worse than ambient air quality standards for EPA-USA, Pak and EU. SO2and NOx pollution were still serious impling that waste gas pollution from all kinds of vehicles had become a significant problem for environmental protection in Peshawar. The possible causes of worsening air quality were also discussed in this paper

Prevalence and risk of hepatitis e virus infection in the HIV population of Nepal

Background: Infection with the hepatitis E virus (HEV) can cause acute hepatitis in endemic areas in immune-competent hosts, as well as chronic infection in immune-compromised subjects in non-endemic areas. Most studies assessing HEV infection in HIV-infected populations have been performed in developed countries that are usually affected by HEV genotype 3. The objective of this study is to measure the prevalence and risk of acquiring HEV among HIV-infected individuals in Nepal. Methods: We prospectively evaluated 459 Human Immunodeficiency Virus (HIV)-positive individuals from Nepal, an endemic country for HEV, for seroprevalence of HEV and assessed risk factors associated with HEV infection. All individuals were on antiretroviral therapy and healthy blood donors were used as controls. Results: We found a high prevalence of HEV IgG (39.4%) and HEV IgM (15.3%) in HIV-positive subjects when compared to healthy HIV-negative controls: 9.5% and 4.4%, respectively (OR: 6.17, 95% CI 4.42-8.61, p < 0.001 and OR: 3.7, 95% CI 2.35-5.92, p < 0.001, respectively). Individuals residing in the Kathmandu area showed a significantly higher HEV IgG seroprevalance compared to individuals residing outside of Kathmandu (76.8% vs 11.1%, OR: 30.33, 95% CI 18.02-51.04, p = 0.001). Mean CD4 counts, HIV viral load and presence of hepatitis B surface antigen correlated with higher HEV IgM rate, while presence of hepatitis C antibody correlated with higher rate of HEV IgG in serum. Overall, individuals with HEV IgM positivity had higher levels of alanine aminotransferase (ALT) than IgM negative subjects, suggesting active acute infection. However, no specific symptoms for hepatitis were identified. Conclusions: HIV-positive subjects living in Kathmandu are at higher risk of acquiring HEV infection as compared to the general population and to HIV-positive subjects living outside Kathmandu

Unraveling preference heterogeneity in willingness-to-pay for enhanced road safety: A hybrid approach of machine learning and quantile regression

Investing in road safety enhancement programs highly depends on the economic valuation of road traffic accidents and their outcomes. Such evaluation underpins road safety interventions in cost-benefit analysis. To this end, understanding and modeling public willingness-to-pay for enhanced road safety have received significant attention in the past few decades. However, despite considerable modeling efforts, some issues still persist in earlier studies, namely, (i) using standard regression approaches that assume a homogeneous impact of explanatory variables on willingness-to-pay, not accounting for heterogeneity, and depends on a priori distribution of the dependent variable, and (ii) the absence of higher-order interactions from models, leading to omitted variable bias and erroneous model inferences. To overcome this critical research gap, our study proposes a new modeling framework, integrating a machine learning technique (decision tree) to identify a priori relationships for higher-order interactions and a quantile regression model to account for heterogeneity along the entire range of willingness-to-pay. The proposed framework examines the determinants of willingness-to-pay for enhanced road safety using a sample of car drivers from Peshawar, Pakistan. Modeling results indicate that variables not significant in a linear model become significant at specific quantiles of the willingness-to-pay distribution. Further, including higher-order interactions among the explanatory variables provides additional insights into the complex relationship between willingness-to-pay and its determinants. In addition, willingness-to-pay for fatal and severe injury risk reductions is estimated at different quartiles and used to calculate the values of corresponding risk reductions. Overall, the proposed framework provides a better understanding of public sensitivities to willingness-to-pay for enhanced road safety.</p

Understanding and modeling willingness-to-pay for public policies to enhance road safety: A perspective from Pakistan

Evaluating road safety improvements becomes important because it can assist policymakers in allocating economic resources to improve safety and implementing effective policy interventions. As such, this study aims to estimate the value of road safety risk measures using a new modeling approach for willingness-to-pay (WTP). Specifically, this study integrates a machine learning technique (decision tree) with a correlated random parameters Tobit with heterogeneity-in-means model. The decision tree identifies a priori relationships for higher-order interactions, while the model captures unobserved heterogeneity and the correlation between random parameters. The proposed modeling framework examines the determinants of public WTP for improving road safety using a sample of car drivers from Peshawar, Pakistan. WTP for fatal and severe injury risk reductions is estimated and used to calculate the values of corresponding risk reductions, which can be used for monetizing the cost of road traffic crashes in the country. Modeling results reveal that most respondents are willing to contribute to road safety improvement policies. Further, the model also uncovers significant heterogeneity in WTP corresponding to the safer perception of the overall road infrastructure and perceived risk of accident involvement. Systematic preference heterogeneity is also found in the model by including higher-order interactions, providing additional insights into the complex relationship of WTP with its determinants. Further, the marginal effects of explanatory variables indicate different sensitivities toward WTP, which can help to quantify the impacts of these variables on both the probability and magnitude of WTP. Overall, the proposed modeling framework has a twofold contribution. First, the modeling framework provides valuable insights into the determinants of public WTP, mainly when the heterogeneous effects of variables are interactive. Second, its implementation and consequent findings shall help prioritize different road safety policies/projects by better understanding public sensitivity to WTP.</p

Antibacterial Activities of Transition Metal complexes of Mesocyclic Amidine 1,4-diazacycloheptane (DACH)

The titled compound 1,4-diazacycloheptane have vibrational freedom which allows it to coordinate to metal through 1st and 4th positions. Copper (II) and Nickel (II) complexes of DACH were prepared and characterized through UV-Visible, FT-IR, elemental analyses, conductance, and magnetic susceptibilities and compared to the results published in Inorg. Chem., 8(3), 528 (1969). The prepared complexes bearing different coordinating or non-coordinating anions were screened against four different pathogenic bacterial strains to study anionic effect on antibacterial activity. The MIC values of all the compounds suggest that [Cu(DACH)2Br2] is almost inactive against the tested microbes except Staph aureus. Rest of the metal complexes are active at their respective MIC values