Observed trends and changes in daily temperature and precipitation extremes over the Koshi river basin

The Koshi river basin is a sub-basin of the Ganges shared among China, Nepal, and India. The river system has a high potential for investment in hydropower development and for irrigation in downstream areas. The upper part of the basin contains a substantial reserve of freshwater in the form of snow and glaciers. Climate variability, climate change, and climate extremes might impact on these reserves, and in turn impact on systems that support livelihoods, such as agriculture, biodiversity and related ecosystem services. Climatological variability and trends over the Koshi river basin were studied using RClimDex. Daily temperature data (20 stations) and precipitation data (50 stations) from 1975 to 2010 were used in the analysis. The results show that the frequency and intensity of weather extremes are increasing. The daily maximum temperature (TXx) increased by 0.1 °C decade−1 on average between 1975 and 2010 and the minimum (TNn) by 0.3 °C decade−1. The number of warm nights increased at all stations. Most of the extreme temperature indices showed a consistently different pattern in the mountains than in the Indo-Gangetic plains, although not all results were statistically significant. The warm days (TX90p), warm nights (TN90p), warm spell duration (WSDI), and diurnal temperature range (DTR) increased at most of the mountain stations; whereas monthly maximum and minimum values of daily maximum temperature, TX90p, cool nights (TN10p), WSDI, cold spell duration indicator (CSDI), DTR decreased at the stations in the Indo-Gangetic plains, while the number of cold days increased. There was an increase in total annual rainfall and rainfall intensity, although no clear long-term linear trend, whereas the number of consecutive dry days increased at almost all stations. The results indicate that the risk of extreme climate events over the basin is increasing, which will increase people's vulnerability and has strong policy implications

Projected changes in climate over the Indus river basin using a high resolution regional climate model (PRECIS)

A regional climate modelling system, the Providing REgional Climates for Impacts Studies developed by the Hadley Centre for Climate Prediction and Research, has been used to study future climate change scenarios over Indus basin for the impact assessment. In this paper we have examined the three Quantifying Uncertainty in Model Predictions simulations selected from 17-member perturbed physics ensemble generated using Hadley Centre Coupled Module. The climate projections based on IPCC SRES A1B scenario are analysed over three time slices, near future (2011-2040), middle of the twenty first century (2041-2070), and distant future (2071-2098). The baseline simulation (1961-1990) was evaluated with observed data for seasonal and spatial patterns and biases. The model was able to resolve features on finer spatial scales and depict seasonal variations reasonably well, although there were quantitative biases. The model simulations suggest a non-uniform change in precipitation overall, with an increase in precipitation over the upper Indus basin and decrease over the lower Indus basin, and little change in the border area between the upper and lower Indus basins. A decrease in winter precipitation is projected, particularly over the southern part of the basin. Projections indicate greater warming in the upper than the lower Indus, and greater warming in winter than in the other seasons. The simulations suggest an overall increase in the number of rainy days over the basin, but a decrease in the number of rainy days accompanied by an increase in rainfall intensity in the border area between the upper and lower basins, where the rainfall amount is highest

Widespread Climate Change in the Himalayas and Associated Changes in Local Ecosystems

Background: Climate change in the Himalayas, a biodiversity hotspot, home of many sacred landscapes, and the source of eight largest rivers of Asia, is likely to impact the well-being of $\sim$20% of humanity. However, despite the extraordinary environmental, cultural, and socio-economic importance of the Himalayas, and despite their rapidly increasing ecological degradation, not much is known about actual changes in the two most critical climatic variables: temperature and rainfall. Nor do we know how changes in these parameters might impact the ecosystems including vegetation phenology. Methodology/Principal Findings: By analyzing temperature and rainfall data, and NDVI (Normalized Difference Vegetation Index) values from remotely sensed imagery, we report significant changes in temperature, rainfall, and vegetation phenology across the Himalayas between 1982 and 2006. The average annual mean temperature during the 25 year period has increased by 1.5$^\circ$C with an average increase of 0.06$^\circ$C yr$^{−1}$. The average annual precipitation has increased by 163 mm or 6.52 mmyr$^{−1}$. Since changes in temperature and precipitation are immediately manifested as changes in phenology of local ecosystems, we examined phenological changes in all major ecoregions. The average start of the growing season (SOS) seems to have advanced by 4.7 days or 0.19 days yr$^{−1}$ and the length of growing season (LOS) appears to have advanced by 4.7 days or 0.19 days yr$^{−1}$, but there has been no change in the end of the growing season (EOS). There is considerable spatial and seasonal variation in changes in climate and phenological parameters. Conclusions/Significance: This is the first time that large scale climatic and phenological changes at the landscape level have been documented for the Himalayas. The rate of warming in the Himalayas is greater than the global average, confirming that the Himalayas are among the regions most vulnerable to climate change

Transitional Probability-Based Model for HPV Clearance in HIV-1-Positive Adolescent Females

BACKGROUND: HIV-1-positive patients clear the human papillomavirus (HPV) infection less frequently than HIV-1-negative. Datasets for estimating HPV clearance probability often have irregular measurements of HPV status and risk factors. A new transitional probability-based model for estimation of probability of HPV clearance was developed to fully incorporate information on HIV-1-related clinical data, such as CD4 counts, HIV-1 viral load (VL), highly active antiretroviral therapy (HAART), and risk factors (measured quarterly), and HPV infection status (measured at 6-month intervals). METHODOLOGY AND FINDINGS: Data from 266 HIV-1-positive and 134 at-risk HIV-1-negative adolescent females from the Reaching for Excellence in Adolescent Care and Health (REACH) cohort were used in this study. First, the associations were evaluated using the Cox proportional hazard model, and the variables that demonstrated significant effects on HPV clearance were included in transitional probability models. The new model established the efficacy of CD4 cell counts as a main clearance predictor for all type-specific HPV phylogenetic groups. The 3-month probability of HPV clearance in HIV-1-infected patients significantly increased with increasing CD4 counts for HPV16/16-like (p<0.001), HPV18/18-like (p<0.001), HPV56/56-like (p = 0.05), and low-risk HPV (p<0.001) phylogenetic groups, with the lowest probability found for HPV16/16-like infections (21.60±1.81% at CD4 level 200 cells/mm(3), p<0.05; and 28.03±1.47% at CD4 level 500 cells/mm(3)). HIV-1 VL was a significant predictor for clearance of low-risk HPV infections (p<0.05). HAART (with protease inhibitor) was significant predictor of probability of HPV16 clearance (p<0.05). HPV16/16-like and HPV18/18-like groups showed heterogeneity (p<0.05) in terms of how CD4 counts, HIV VL, and HAART affected probability of clearance of each HPV infection. CONCLUSIONS: This new model predicts the 3-month probability of HPV infection clearance based on CD4 cell counts and other HIV-1-related clinical measurements

The impact of highly active antiretroviral therapy on prevalence and incidence of cervical human papillomavirus infections in HIV-positive adolescents

Abstract Background The implementation of highly active antiretroviral therapy (HAART) among HIV-positive patients results in immune reconstitution, slower progression of HIV disease, and a decrease in the occurrence of opportunistic infections. However, the impact of HAART on cervical human papillomavirus (HPV) infection, clearance, and persistence in high-risk adolescents remains controversial. Methods HIV-positive and high-risk HIV-negative female adolescents were enrolled in the Reaching for Excellence in Adolescent Care and Health (REACH) longitudinal cohort study. At each semi-annual clinical visit, cervical lavage samples were tested for 30 HPV types. Type-specific and carcinogenic risk-specific HPV prevalence and incidence were compared in 373 eligible participants: 146 HIV-negative female adolescents with a median follow-up of 721.5 [IQR: 483-1301] days and 227 HIV-positive female adolescents. Of the 227 HIV-positive participants, a fixed set (n = 100) were examined both before and after HAART initiation; 70 were examined only before HAART initiation; and 57 were examined only after HAART initiation, with overall median follow-up of 271 [IQR: 86.5-473] and 427.25 [IQR: 200-871] days respectively for before and after HAART initiation. Results Of the 373 eligible participants, 262 (70%) were infected with at least one type of HPV at baseline, and 78 of the remaining 111 (70%) became infected with at least one type of HPV by the end of the study. Overall, the incidence and prevalence of HPV types 58, 53/66, 68/70, and 31/33/35 were much higher than the established carcinogenic and HPV vaccine types 16 and 18, especially in HIV-positive females both before and after HAART initiation. Baseline prevalence for individual high-risk HPV types ranged, depending on type, from 0.7-10%, 1-17%, and 1-18% in the HIV-negative group, the HIV-positive before HAART initiation group, and the HIV-positive after HAART initiation group, respectively. Likewise, the incidence ranged, depending on HPV type, from 0.64-9.83 cases/100 PY, 3.00-12.80 cases/100 PY, and 1.49-17.05 cases/100 PY in the three groups, respectively. The patterns of each HPV type infection, clearance, and persistence did not differ considerably before or after the introduction of HAART and were clearly independent of CD4+ change within the short post-HAART follow-up period. Conclusions HAART did not immediately affect the incidence of type-specific HPV infections within a short-period follow-up; however, future studies are warranted in larger populations to evaluate HAART's impact over longer periods

Allocating HIV Prevention Funds in the United States: Recommendations from an Optimization Model

The Centers for Disease Control and Prevention (CDC) had an annual budget of approximately $327 million to fund health departments and community-based organizations for core HIV testing and prevention programs domestically between 2001 and 2006. Annual HIV incidence has been relatively stable since the year 2000 [1] and was estimated at 48,600 cases in 2006 and 48,100 in 2009 [2]. Using estimates on HIV incidence, prevalence, prevention program costs and benefits, and current spending, we created an HIV resource allocation model that can generate a mathematically optimal allocation of the Division of HIV/AIDS Prevention’s extramural budget for HIV testing, and counseling and education programs. The model’s data inputs and methods were reviewed by subject matter experts internal and external to the CDC via an extensive validation process. The model projects the HIV epidemic for the United States under different allocation strategies under a fixed budget. Our objective is to support national HIV prevention planning efforts and inform the decision-making process for HIV resource allocation. Model results can be summarized into three main recommendations. First, more funds should be allocated to testing and these should further target men who have sex with men and injecting drug users. Second, counseling and education interventions ought to provide a greater focus on HIV positive persons who are aware of their status. And lastly, interventions should target those at high risk for transmitting or acquiring HIV, rather than lower-risk members of the general population. The main conclusions of the HIV resource allocation model have played a role in the introduction of new programs and provide valuable guidance to target resources and improve the impact of HIV prevention efforts in the United States

High-Risk Cervical Human Papillomavirus Infections among Human Immunodeficiency Virus-Positive Women in the Bahamas

Background\ud \ud High-risk (HR) HPV genotypes other than 16 and 18 have been detected in a significant proportion of immunocompromised females. We aim to evaluate the frequency of HR HPV genotypes in a population of HIV-positive Caribbean women.\ud Methods\ud \ud One hundred sixty-seven consecutive, non-pregnant, HIV-positive females ≥18 years were recruited in this study. Each participant received a vaginal examination, PAP smear, and completed a questionnaire. DNA was extracted for HPV testing in 86 patients.\ud Results\ud \ud Mean age was 39.1 years for women positive for HR HPV and 43.1 years for women negative for HR HPV (P value = 0.040). 78% (130/167) of the women had HR HPV infections; the prevalence of abnormal cervical cytology was 38% among women who were HR HPV-positive compared to women who were HR HPV-negative (22%). Fifty-one percent of the 86 women with available genotype carried infections with HPV 16 and/or HPV 18; genotypes of unknown risk were also frequently observed. Women who had a CD4+ count of ≤200 had 7 times increased odds of carrying HR HPV infection in comparison to women with CD4+>200.\ud Conclusions\ud \ud HR HPV infections in HIV infected females may consist of more than just HPV 16 and 18, but also HPV 52 and 58. Further studies are needed to determine whether HPV 52 and 58 play a significant role in the development of cervical cytological abnormalities in HIV+ women

Statistical Inference for Multi-Pathogen Systems

There is growing interest in understanding the nature and consequences of interactions among infectious agents. Pathogen interactions can be operational at different scales, either within a co-infected host or in host populations where they co-circulate, and can be either cooperative or competitive. The detection of interactions among pathogens has typically involved the study of synchrony in the oscillations of the protagonists, but as we show here, phase association provides an unreliable dynamical fingerprint for this task. We assess the capacity of a likelihood-based inference framework to accurately detect and quantify the presence and nature of pathogen interactions on the basis of realistic amounts and kinds of simulated data. We show that when epidemiological and demographic processes are well understood, noisy time series data can contain sufficient information to allow correct inference of interactions in multi-pathogen systems. The inference power is dependent on the strength and time-course of the underlying mechanism: stronger and longer-lasting interactions are more easily and more precisely quantified. We examine the limitations of our approach to stochastic temporal variation, under-reporting, and over-aggregation of data. We propose that likelihood shows promise as a basis for detection and quantification of the effects of pathogen interactions and the determination of their (competitive or cooperative) nature on the basis of population-level time-series data

Measurement of the Forward-Backward Asymmetry in the B -> K(*) mu+ mu- Decay and First Observation of the Bs -> phi mu+ mu- Decay

We reconstruct the rare decays $B^+ \to K^+\mu^+\mu^-$, $B^0 \to K^{*}(892)^0\mu^+\mu^-$, and $B^0_s \to \phi(1020)\mu^+\mu^-$ in a data sample corresponding to $4.4 {\rm fb^{-1}}$ collected in $p\bar{p}$ collisions at $\sqrt{s}=1.96 {\rm TeV}$ by the CDF II detector at the Fermilab Tevatron Collider. Using $121 \pm 16$ $B^+ \to K^+\mu^+\mu^-$ and $101 \pm 12$ $B^0 \to K^{*0}\mu^+\mu^-$ decays we report the branching ratios. In addition, we report the measurement of the differential branching ratio and the muon forward-backward asymmetry in the $B^+$ and $B^0$ decay modes, and the $K^{*0}$ longitudinal polarization in the $B^0$ decay mode with respect to the squared dimuon mass. These are consistent with the theoretical prediction from the standard model, and most recent determinations from other experiments and of comparable accuracy. We also report the first observation of the $B^0_s \to \phi\mu^+\mu^- decay and measure its branching ratio${\mathcal{B}}(B^0_s \to \phi\mu^+\mu^-) = [1.44 \pm 0.33 \pm 0.46] \times 10^{-6}$using$27 \pm 6$signal events. This is currently the most rare$B^0_s$ decay observed.Comment: 7 pages, 2 figures, 3 tables. Submitted to Phys. Rev. Let