Impact of comorbidity on patients with COVID-19 in India: A nationwide analysis
by Priya Singh, Yogendra Bhaskar, Pulkit Verma, Shweta Rana, Prabudh Goel, Sujeet Kumar, Krushna Chandra Gouda, Harpreet Singh
Background: The emergence of coronavirus disease (COVID-19) as a global pandemic has resulted in the loss of many lives and a significant decline in global economic losses. Thus, for a large country like India, there is a need to comprehend the dynamics of COVID-19 in a clustered way.
Objective: To evaluate the clinical characteristics of patients with COVID-19 according to age, gender, and preexisting comorbidity. Patients with COVID-19 were categorized according to comorbidity, and the data over a 2-year period (1 January 2020 to 31 January 2022) were considered to analyze the impact of comorbidity on severe COVID-19 outcomes.
Methods: For different age/gender groups, the distribution of COVID-19 positive, hospitalized, and mortality cases was estimated. The impact of comorbidity was assessed by computing incidence rate (IR), odds ratio (OR), and proportion analysis.
Results: The results indicated that COVID-19 caused an exponential growth in mortality. In patients over the age of 50, the mortality rate was found to be very high, ~80%. Moreover, based on the estimation of OR, it can be inferred that age and various preexisting comorbidities were found to be predictors of severe COVID-19 outcomes. The strongest risk factors for COVID-19 mortality were preexisting comorbidities like diabetes (OR: 2.39; 95% confidence interval (CI): 2.31–2.47; p < 0.0001), hypertension (OR: 2.31; 95% CI: 2.23–2.39; p < 0.0001), and heart disease (OR: 2.19; 95% CI: 2.08–2.30; p < 0.0001). The proportion of fatal cases among patients positive for COVID-19 increased with the number of comorbidities.
Conclusion: This study concluded that elderly patients with preexisting comorbidities were at an increased risk of COVID-19 mortality. Patients in the elderly age group with underlying medical conditions are recommended for preventive medical care or medical resources and vaccination against COVID-19.
Extreme rainfall event analysis over the state of Himachal Pradesh in India
by K. C. Gouda, Sudhansu S. Rath, Nidhi Singh, Sayanta Ghosh & Renu Lata
Extreme rainfall events (EREs) are very localized and intense events witnessing heavy rainfall resulting in flash floods and landslides in the Himalayan region. The trend of EREs in the state of Himachal Pradesh shows an increasing trend, so in this study, an attempt is being made for quantifying the climatological feature of these EREs in the state of Himachal Pradesh in the western Himalayan mountain region. Multi-source observed datasets for the long-term period, i.e., 1901 to 2020, are considered for the analysis. The climatology analysis indicates that northern and southern parts of Himachal Pradesh receive comparatively more rainfall, and the state witnessed a decreasing trend of the rainfall in the current decade. The classifications of these EREs in terms of monsoon and non-monsoon with a different threshold of daily rainfall are being analyzed, and it is found that almost 90% of extreme events are observed in the monsoon season. The zone centered around 32.5° N and 76.25° E seems to be the hotspot for the frequent EREs in the mountainous state. The spatial analysis of the ERE trend also indicated that almost 40% of the state witnesses the heavy rainfall throughout the years. This observational study will surely help in understanding the dynamics of these EREs in the higher altitude regions and can be used for hydro-meteorological disaster management and mitigation.
Relationship of height and intensity of low-level jet stream with Indian summer monsoon rainfall
by Smrati Purwar, V. Rakesh, Ajay Bankar & G. N. Mohapatra
A strong equatorial flow at lower troposphere exists over the Indian Ocean plays a crucial role in modulating the Indian Summer Monsoon Rainfall (ISMR) referred as monsoon low-level jet (MLLJ). The variation in strength and height of MLLJ can provide an important lead in predicting the variations in ISMR. The variability of MLLJ is examined using the fifth-generation ECMWF (European Centre for Medium-Range Weather Forecasts) reanalysis ERA-5; National Centers for Environmental Prediction-Climate Forecast System Reanalysis (NCEP-CFSR)/Climate Forecast System, version 2 (CFSv2); the Modern-Era Retrospective Analysis for Research and Application, version-2 (MERRA-2); and radiosonde data during 40-year period (1979–2018). The results suggest that there is an increasing trend in MLLJ strength during July and September, but a decreasing trend is observed during August. The MLLJ height showed an increasing trend in all the data sets. Significant interannual oscillations in MLLJ strength and height are observed with a prominent periodicity of 2–3 years. The ISMR over Western Ghats region and central India showed strong positive correlation with the MLLJ strength as well as height except during August. It is noted that the influence of the MLLJ on rainfall over the Indian landmass is stronger during the onset and withdrawal phases of monsoon. The increasing trend in MLLJ height indicated the possibility of increase in rainfall over many regions in India especially Western Ghat and Central India.
Source: https://doi.org/10.1007/s00704-022-04301-3
Exacerbation of Indian Summer Monsoon Breaks by the Indirect Effect of Regional Dust Aerosols
by
Sajani Surendran, K. V. Ajay Anand, Suraj Ravindran and K Rajendran
Abstract
Evaluation of century-long simulations of the Community Earth System Model (CESM) reveals model fidelity in capturing characteristics of aerosols, clouds, convection, rainfall and circulation over India associated with the active/break phase with wetter/drier than average rainfall within the summer monsoon season. During the breaks, aerosols build up over central India due to desert dust transported from the west by anomalous circulation, the trapping of dust emissions from the Thar-desert and the increased aerosol lifetime in dry conditions. Break spells exhibit reduced cloud effective radius and enhanced lower atmospheric warming over central India as potential evidence for the indirect effect induced by dust aerosols. Consistently, break spells intensify in CESM simulation with increased loading of dust aerosols. The indirect effect of dust aerosols in warming the atmosphere and exacerbating the severity of breaks is conspicuous in simulations forced with the indirect effect of aerosols alone, both for present-day and pre-industrial periods.
Source:
https://onlinelibrary.wiley.com/share/author/NKGRJEJN3M4KRQEVDZVE?target=10.1029/2022GL101106
Supplementary Information Source:
Assessing the impact of modified LULC on extreme hydrological event over a complex terrain: A case study for kodagu 2018 flood event
by Sumana Sarkar and S.Himesh
Abstract
The livelihoods and biodiversity in the Kodagu district of Karnataka are greatly altered by the growing urbanization through huge deforestation. The changes in the Land Use and Land Cover (LULC) patterns have important implications on the heavy rainfall activity due to significant alterations in the spatial distribution of existing land-surface properties. Hence, in order to make region (like Kodagu) more climate resilient; it is utmost important to construct a novel coupled framework for hydro-meteorological prediction to assess the impact of changing LULC (degradation of forest cover owing to urban expansion) on extreme rainfall events. Only a well-calibrated, validated, and optimized coupled high-resolution hydrological-atmospheric modelling system can be one of the best tools to study such complex problems. Thus in the present study, we have enhanced the forecasting capability of the state-of-the-art Weather Research and Forecasting (WRF) model by coupling with a physically based, fully distributed, WRF-Hydro. The evaluation of the proposed model configurations (stand-alone and coupled mode) is done with respect to two LULC datasets (USGS, 1992: less urbanized scenario and ISRO, 2017: more urbanized scenario) to explore the underlying causes and hydrological responses behind the 2018 Kodagu flood event. The simulations have been contended with both the stand-alone and coupled WRF/WRF-hydro models with different LULC datasets and a comparative evaluation have been carried out. The simulated variables (rainfall, runoff, surface fluxes, and peak stream discharge) are evaluated and compared with observation to assess the impact of changing LULC pattern during the flood event.
Source: https://www.sciencedirect.com/science/article/abs/pii/S1364682622001341
- Association of winter vegetation activity across the indo-gangetic plain with the subsequent Indian summer monsoon rainfall
- Seismic hazard potential of Kachchh paleo-rift basin of Indian craton from seismic and geodetic strain rates
- Sea surface temperature variations partitioned through multiple seasonal cycles
- Weather integrated malaria prediction system using Bayesian structural time series model for northeast states of India
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