Climate uncertainty and vulnerability of urban flooding associated with regional risk using multi-criteria analysis in Mumbai, India.

The study made a comprehensive effort to examine climatic uncertainties at both yearly and monthly scales, along with mapping flood risks based on different land use categories. Recent studies have progressively been engrossed in demonstrating regional climate variations and associated flood probability to maintain the geo-ecological balance at micro to macro-regions. To carry out this investigation, various historical remote sensing record, reanalyzed and in-situ data sets were acquired with a high level of spatial precision using the Google Earth Engine (GEE) web-based remote sensing platform. Non-parametric techniques and multi-layer integration methods were then employed to illustrate the fluctuations in climate factors alongside creating maps indicating the susceptibility to floods. The study reveals an increased pattern in LST (Land Surface Temperature) (0.03 °C/year), albeit marginal declined in southern coastal regions (-0.15 °C/year) along with uneven rainfall patterns (1.42 mm/year). Moreover, long-term LULC change estimation divulges increased trends of urbanization (16.4 km2/year) together with vegetation growth (8.7 km2/year) from 2002 to 2022. Furthermore, this inquiry involves numerous environmental factors that influence the situation (elevation data, topographic wetness index, drainage density, proximity to water bodies, slope, and soil properties) as well as socio-economic attributes (population) to assess flood risk areas through the utilization of Analytical Hierarchy Process and overlay methods with assigned weights. The outcomes reveal nearly 55 percent of urban land is susceptible to flood in 2022, which were 45 and 37 percent in 2012 and 2002 separately. Additionally, 106 km2 of urban area is highly susceptible to inundation, whereas vegetation also occupies a significant proportion (52 km2). This thorough exploration offers a significant chance to formulate flood management and mitigation strategies tailored to specific regions during the era of climate change.

Evaluating hotspots for stormwater harvesting through participatory sensing.

Geographic Information Systems have been widely accepted to manage and manipulate spatial data associated with the hydrologic response of a watershed. Due to climate change and drought impacts, there is a need to conserve freshwater resources, which can be accomplished by introducing the concept of stormwater harvesting. Apart from hotspot identification and site screening, several economic, social, cultural, environmental aspects need to be considered before finalizing the suitable site for stormwater harvesting. The shortlisted sites are commonly ranked by considering various parameters, i.e. water demand, availability of stormwater and distance to end-use locations, which relate to economic aspects. In the present study, socio-environmental considerations are also constituted by adopting a web-GIS based approach. The geospatial datasets and metadata associated with the study area are organized as a repository in the open source database server (PostgreSQL/PostGIS), which is further assessed and analyzed by using GeoServer. This technique publishes the geospatial datasets to the public domain websites that can be accessed and visualized around the clock and across the world. This will help stakeholders gather and store responses from water planners and inhabitants, while minimizing the time and cost associated with field visits for collecting individual responses. In this respect, a questionnaire is prepared that includes queries associated with site selection and the responses are gathered from various institutions, water professionals, stakeholders and residents. Once the responses are collected, the Analytic Hierarchy Process has been implemented to compute the relative weights of each criterion with respect to the responses collected. The weights thus obtained assisted the planners in deciding the suitable stormwater harvesting site for Dehradun city in India. In context to responses gathered the sites 'B' and 'D' are given the maximum weightage to be the suitable sites in the study region. Also, the socio-environmental criteria such as 'community acceptance', 'recreational activities' and 'need for water reuse' have gathered the maximum weightage from the responses for the specific sites. Hence, the proposed methodology demonstrated how water professionals, civilians, planners, stakeholders and public can be included as participants in water-related decision making processes.

Spatial landscape model to characterize biological diversity using R statistical computing environment.

Due to urbanization and population growth, the degradation of natural forests and associated biodiversity are now widely recognized as a global environmental concern. Hence, there is an urgent need for rapid assessment and monitoring of biodiversity on priority using state-of-art tools and technologies. The main purpose of this research article is to develop and implement a new methodological approach to characterize biological diversity using spatial model developed during the study viz. Spatial Biodiversity Model (SBM). The developed model is scale, resolution and location independent solution for spatial biodiversity richness modelling. The platform-independent computation model is based on parallel computation. The biodiversity model based on open-source software has been implemented on R statistical computing platform. It provides information on high disturbance and high biological richness areas through different landscape indices and site specific information (e.g. forest fragmentation (FR), disturbance index (DI) etc.). The model has been developed based on the case study of Indian landscape; however it can be implemented in any part of the world. As a case study, SBM has been tested for Uttarakhand state in India. Inputs for landscape ecology are derived through multi-criteria decision making (MCDM) techniques in an interactive command line environment. MCDM with sensitivity analysis in spatial domain has been carried out to illustrate the model stability and robustness. Furthermore, spatial regression analysis has been made for the validation of the output.

Correlation of HIV/AIDS prevalence with social, economic and demographic measures in Andhra Pradesh, India.

In this study, the spatial distribution of HIV/AIDS is investigated with several socioeconomic variables. Results of exploratory analysis of correlations have been reported between the prevalence of HIV/AIDS as it is the dependent variable against a range of socioeconomic and demographic measures in Andhra Pradesh, India. The state ranks among the top six states for HIV prevalence in the country. This study offers an insight to the distribution of HIV prevalence and the potential impacts of the epidemic on the high-, medium- and low-risk groups determined through cluster analyses of population and cumulative HIV infections. The impacts have been addressed through selective social and economic measures as HIV/AIDS is considered more of a social epidemic. These results help in identifying factors that are contributing more towards the spread of HIV and so guide policies to counteract dominant factors in order to control the disease. Future investigations are necessary to elucidate characterization of the rates of infection according to gender, age groups and regions.

Health GIS and HIV/AIDS studies: Perspective and retrospective.

GIS (Geographic Information System) is a useful tool that aids and assists in health research, health education, planning, monitoring and evaluation of health programmes that are meant to control and eradicate certain life threatening diseases and epidemics. HIV/AIDS is one such epidemic that poses a serious challenge and threatens the overall human welfare. This communication is an attempt to link and understand the health scenario in a GIS context with emphasis on HIV/AIDS. Various GIS based functionalities for health studies and their scope in analyzing and controlling epidemiological diseases are explored. Overall scenario of the spread of HIV/AIDS around the world is presented along with the Indian perspective. Finally, we conclude with the general management problems, issues and challenges related to HIV/AIDS prevailing in India.

Comparative evaluation of cefpodoxime versus cefixime in children with lower respiratory tract infections.

OBJECTIVE: The emergence of penicillin and macrolide resistant strains, responsible for Acute Lower Respiratory Tract Infections in children has offered third generation cephalosporins the platform to perform. The aim of the present study was to evaluate two third generation oral cephalosporins for their empirical use in community acquired lower respiratory tract infections in pediatric patients. An assessment of the clinical cure and bacteriological eradication rates and an overall tolerability was made. METHODS: It was a prospective, open, comparative, multicentric study. 776 children (Mean age 10 years) with LRTIs were included and randomly allotted to two groups respectively. A total of 396 children were given cefpodoxime susp 5 mg/kg b.i.d. and 380 patients on cefixime 4 mg/kg b.i.d. for 10-14 days. RESULTS: At the end of therapy, the clinical success with cefpodoxime was 97% as against 86.8% with cefixime. Bacterial eradication was 93.4% with cefpodoxime and 82.9% with cefixime. CONCLUSION: Cefpodoxime has been found to be a well-tolerated and superior alternative to cefixime synergistically documenting the extended spectrum of activity.