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Introduction CD4 count is an important predictor of disease progression, opportunities infection, deaths, and to understand the time interval between initial HIV infection to the first diagnosis. However, baseline CD4 count and the time period between initial infection and the diagnosis amongst PLHIV in Bhutan never been evaluated. Methods This is a retrospective study of the diagnosed PLHIV from the existing data system from January 10 to 30, 2021. Out of 512 reported HIV cases, 488 of those who were more than or equal to 18 years old and had their CD4 count testing within 6 months before initiating ART were considered for analysis. Descriptive statistical analysis was used to analyze the characteristics of the study population and relationship were established using the χ 2 Test. We have sought ethics approval and waiver for informed consent as it is the retrospective study of the client's record. The client's confidentiality was ensured by removing all the identifiers. Results The mean CD4 was 345 cells/ml for males and females. Twenty‐five percent of the clients had CD4 counts below 200, 30%, between 200 and 349, 25% between 350 and 499, and 20% above 500 cells/ml. A larger number of males showed a CD4 count below 200 cells/ml while more females showed a CD4 count more than 500 cells/ml. The mean time interval between initial infection to the first diagnosis was 4 years in males and females. However, about one‐fourth were found to have been infected between 5 and 8 years before diagnosis and less than 10% were diagnosed within less than 1 year of infection. Conclusions The study revealed a late diagnosis of HIV infection in Bhutan thereby risking the transmission to the community and risk of severe disease and mortality. The upscaling of voluntary counseling and testing, medical screening, and alternative methods like community‐based testing including HIV Self Testing for early detection needs to be implemented in the country., Baseline CD4 count and the time interval between the initial HIV infection and diagnosis among PLHIV in Bhutan.

Previous studies suggest that climate change impacts significantly on the hydro-climatic processes within the Ganges–Brahmaputra–Meghna (GBM) River Basin (RB). This study examines the observed climate characteristics and potential strengths and limitations of three global high-resolution reanalyses and satellite remote-sensing products over the GBM RB for period 1980–2013 by (1) estimating trends and interannual variations of precipitation and temperature, and (2) isolating precipitation variations likely associated with El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The surface temperature trends show widespread warming across the basin with a maximum increase of 0.6 °C decade−1 over western Nepal and southern Tibet from 1980 to 2013. Rainfall changes from 1980 to 2013 indicate pronounced decline over high rainfall regions of northeast India, Bhutan, Nepal, and Bangladesh, especially from 1998 to 2013. Basin-wide averaged trends show rainfall decline of up to 39 mm decade−1 in June–August in the Brahmaputra–Meghna RB from 1998 to 2013. Temperature variability based on Principal Component Analysis indicates that the first mode is associated with sea surface temperature (SST) warming in the Arabian Sea and the western tropical Pacific Ocean, while the second mode appears to be significantly correlated to SST anomalies in the western (eastern) tropical Indian (Pacific) Ocean. ENSO and IOD events are found to significantly influence rainfall variability contributing to about 10–20% (ENSO) and 8–10% (IOD) of the annual rainfall, mainly over Bhutan, Nepal, Bangladesh, and north-eastern India. Among the three reanalysis products: European Centre for Medium-Range Weather Forecasts (ECMWF) retrospective analysis (ERA-Interim), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR), ERA-Interim (and MERRA) agrees well with the observed precipitation (temperature) data sets while, CFSR shows the least skills in representing the spatio-temporal variations of precipitation and temperature.

Several global and regional high-resolution precipitation products have been released over the past decade by combining precipitation estimates from various sources including satellite-based measurements and gauge-based observations. With relatively few validation studies over the Eastern Himalayan region, this study examined seasonal and interannual skills of four gridded precipitation products including the regional gauge-based APHRODITE (Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources) and three near-global satellite-based products: Tropical Rainfall Measuring Mission (TRMM), Climate Prediction Centre (CPC) MORPHing (CMORPH), and Climate Hazards Group InfraRed Precipitation (CHIRP) using in-situ rain gauge data from Bhutan for the period 1998–2012. Principal component analysis (PCA) was used to assess the dominant rainfall patterns over Bhutan. An attempt has also been made to correct precipitation biases in the satellite-only products using a gamma (γ)-based distribution approach. Results indicated that APHRODITE and satellite-based precipitation products were able to adequately capture the spatio-temporal patterns of rainfall variability over Bhutan. Extreme precipitation events and extreme drought periods were well captured with very good correlations (>0.5). APHRODITE and TRMM 3B43v7 were remarkably similar, whereas satellite-only products (CMORPH and CHIRP) highly underestimated (20–60% or 200–450 mm month−1) monsoon rainfall over Bhutan. While TRMM 3B43v7 still underestimated monsoon rainfall (by ∼25%), it has significantly improved the seasonal bias (by 20–40%) from its previous version (TRMM 3B43v6). CHIRP performed relatively better in the high rainfall regions but indicated very low correlations over mountainous regions and during the pre- and post-monsoon season. The bias correction approach indicated best results for TRMM 3B43v6 (up to 33%) in the Southern Foothills, whereas satellite-only products improved only moderately (5–20%).

Quantifying the amount of precipitation and its uncertainty is a challenging task all over the world, particularly over the African continent, where rain gauge (RG) networks are poorly distributed. In recent decades, several satellite remote sensing (SRS)-based precipitation products have become available with reasonable spatial and temporal resolutions to be applied in hydrological and climate studies. However, uncertainties of these products over Africa are largely unknown. In this study, the generalized ‘three-cornered-hat’ (TCH) method is applied to estimate uncertainties of gridded precipitation products over the entire African continent, without being dependent to the choice of a reference dataset. Six widely used SRS-based precipitation products (at monthly scales) were evaluated over the entire continent during the period of 2003–2010. The TCH results are further compared to those of the classical evaluation using the Global Precipitation Climatology Centre (GPCC) over entire Africa, as well as to the RG observations over the Greater Horn of Africa (GHA). Overall, for the study period (2003–2010), the TCH results indicate that the RG-merged products contain smaller error amplitudes compared to the satellite-only products, consistent with the GPCC-based evaluation. A multiple comparison procedure ranking, which was applied based on signal-to-noise ratios (SNRs), indicated that PERSIANN contains the highest SNR and thus suitable over most of Africa, followed by ARCv2, TRMM, CMORPH, TAMSAT, and GSMaP. To extract the main spatio-temporal variability of rainfall over Africa, complex empirical orthogonal function technique was applied, from which the extracted patterns of GPCC, TRMM, PERSIANN, and ARCv2 were found to be similar but different from those of TAMSAT, CMORPH, and GSMaP. Finally, the TCH and RG-based validation methods were found to provide similar evaluations for the SRS-only products (CMORPH and GSMaP) over GHA, with CMORPH emerging to be the most suitable product, consistent with previous studies.

Indazoles is an important class of heterocyclic compounds having a wide range of biological and pharmaceutical applications. There is enormous potential in the synthesis of novel heterocyclic systems to be used as building blocks for the next generation of pharmaceuticals as anti-bacterial, anti-depressant and anti-inflammatory. Fused aromatic 1H and 2H-indazoles are well recognized for anti-hypertensive and anti-cancer properties. The present review focuses on novel routes of their synthesis and various biological activities.