Post-monsoon Period Research Articles

P-902. Etiology, Clinical Characteristics, Prognosis and Outcomes of Acute Central Nervous System Infections: A Prospective Study

Abstract Background Various pathogens can cause central nervous system (CNS) infections. Early recognition and treatment significantly improves outcomes. Clinical features and outcomes vary by etiology and clinical phenotype, making diagnosis challenging. We report a single-center experience emphasizing the clinical profile and prognostic factors of this entity. Methods We conducted a two-year prospective, observational study at a tertiary care center in Western India. Patients suspected to have CNS infections underwent a standardized workup that included neuroimaging and CSF polymerase chain reaction panel testing. Patients were followed throughout the admission. The outcomes recorded were duration of intensive care unit (ICU) stay, hospital stay, modified Rankin Scale (mRS) at discharge and mortality. Results We included 75 patients (53 male, 22 female). The mean age was 43±19 years. Most infections were viral (69%) – 40% encephalitis, 17% meningitis and 12% meningoencephalitis. Viral infections surged in the monsoon and post-monsoon period (Fig. 1). Tuberculous meningitis accounted for 16% cases, pyogenic meningitis for 7%, and cryptococcal meningitis for 5%. Mucor cerebritis and brain abscesses accounted for 3%. Presenting symptoms, CSF, and neuroimaging findings are listed in Fig. 2-4. Mortality was highest for cryptococcal meningitis (25%); followed by pyogenic meningitis (20%); and viral encephalitis and tuberculous meningitis (16.7% each). Increased risk of mortality was observed with: new-onset seizures (relative risk [RR] 3.58, 95% confidence intervals [CI] 1.03-12.45, p< 0.001); a Glasgow Coma Scale (GCS) < 8 (RR: 6.85, 95% CI 2.00-23.40, p=0.002); and the presence of dilated ventricles on imaging (RR: 5.25, 95% CI 1.99-13.82, p< 0.001). Increasing age correlated with a longer ICU stay (r=0.37, p< 0.001), hospital stay (r=0.33, p=0.002), and worse functional status at discharge reflected by a higher mRS (p=0.04). GCS at presentation correlated inversely with functional recovery reflected by the mRS at discharge (p< 0.001). CSF findings varying by etiology CSF findings varying by etiology Conclusion The etiology and prognosis of acute CNS infectious varies by region and season. A detailed history, thorough physical examination, neuroimaging and CSF analysis are vital as each provides diagnostic and prognostic information. Disclosures All Authors: No reported disclosures

Seasonal Bioaccumulation of Heavy Metals in the Gills of Lepturacanthus savala

This study investigated the seasonal bioaccumulation of seven heavy metals—lead (Pb), manganese (Mn), zinc (Zn), nickel (Ni), cadmium (Cd), chromium (Cr), and copper (Cu)—in the gills of Lepturacanthus savala at Station 1 from June 2022 to July 2023. The data were analyzed using one-way ANOVA to assess seasonal variations in metal concentrations during pre-monsoon, monsoon, and post-monsoon periods. The results revealed significant seasonal fluctuations, with Pb and Mn concentrations peaking during the monsoon season, reaching 2.1 µg/g and 1.41 µg/g, respectively, with p-values of 0.00 for both. Other metals such as Zn, Ni, Cd, Cr, and Cu showed minimal variation across seasons. These findings suggest that Pb and Mn bioaccumulate significantly during the monsoon, likely due to increased runoff, while other metals remain stable. This study emphasizes the importance of continuous monitoring of heavy metal bioaccumulation in marine species to assess potential environmental and public health risks.

Comparative assessment of groundwater quality in Kokrajhar, India

A study was carried out to analyse and compare the quality of groundwater in Kokrajhar during the pre- and post-monsoon seasons. Kokrajhar is experiencing a significant population growth and urbanisation. Groundwater is vital for the daily activities and consumption of the local population. In order to meet the needs of the local population, it is crucial to evaluate the quality of groundwater. The study involved the collection of groundwater samples from 20 different locations during the pre- and post-monsoon periods. Tests were conducted on groundwater samples to analyse 10 different test parameters. Sample points were located using geographical information system (GIS) and contour maps were generated to represent different test parameters. The assessment of groundwater quality was determined using two different methodologies: the Weighted Arithmetic Index (WAI) method and the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method. The results obtained by both methods were compared. Minor to significant variations in various test parameters were observed during analysis of pre- and post-monsoon groundwater samples.

Influence of climatic conditions on particulate emissions in mixed traffic conditions across various pavement types

Non-exhaust emissions containing particulate matter (PM), as indicated by PM2.5 and PM10, poses significant health, environmental, and climatic risks. This study investigates the impact of temperature and humidity on PM concentrations across different pavement types (asphalt and cement concrete) under mixed traffic conditions. Utilizing a sensor based portable air quality monitor, air quality data were collected over multiple seasons, encompassing winter, pre-monsoon, monsoon, and post-monsoon periods. The results reveal a strong correlation between PM levels and meteorological conditions, with higher temperatures and lower humidity contributing to elevated PM concentrations, particularly during the pre-monsoon season. Conversely, monsoon rains effectively reduce PM levels. The study also highlights the variations in the PM2.5/PM10 ratio between pavement types, with cement concrete showing a consistently higher ratio, indicating a greater prevalence of fine particulates. These findings underscore the necessity of season-specific air quality management strategies, considering the influence of both pavement type and environmental factors on PM emissions.

Assessing flooding extent and potential exposure to river pollution from urbanizing peripheral rivers within Greater Dhaka watershed

Greater Dhaka area is home to large industrial clusters that are driving economic growth and the poverty reduction efforts of Bangladesh. These clusters are located around peripheral rivers- Turag, Buriganga, Dhaleswari, Balu, Shitalakhya, Bangshi, and Tongi-Khal, which are important for water transport, environment, and eco-systems where flooding of floodplains in monsoon is an integral part. The urban and industrial growth stressing natural resources has led to severe degradation of the rivers and floodplains, affecting the livelihoods, health, and well-being of the people. Monsoon-time exposure to polluted water is yet to be studied and addressed scientifically. This study looked into the water quality and flooding situation of Greater Dhaka for two successive monsoons through extensive river sampling coupled with the estimation of flooded area and exposed population using remote sensing tools. Sentinel 1’s Synthetic Aperture Radar (SAR) images are used for flood mapping considering cost-effectiveness and its advantages for data-scarce regions. The estimated population exposed to flooding was over 668,000 in 2019, and this number increased by 1.53 times in 2020, totaling over one million. During the monsoon and post-monsoon periods of 2019 and 2020, Buriganga, Tongi Khal, and Balu were consistently in poor condition. The lowest water quality index (WQI) was observed in Balu during the monsoon of 2019 (32.28), post-monsoon of 2019 (35.71), and post-monsoon of 2020 (29.58). The lowest WQI during the monsoon of 2020 was recorded in Tongi Khal (35.75). Among the four districts, Dhaka and Gazipur were the most affected by floods in terms of inundation area and exposed population. Our study indicates that most rivers remain in poor condition during the monsoon when exposure is also high. This highlights the need for policymakers to take monsoon exposure seriously and design appropriate interventions.

Pollution Sensitivity and Resistance Assessment of Native Ornamental Plants for Landscaping in Various Factories

The present study was conducted during 2023–2024 and the data was recorded during post monsoon period (January– February, 2024) to assess the performance of ten native ornamental plants under different pollutants of seven factory sites along with a control in Rayalaseema region of Andhra Pradesh, India, for recommending in green belt development under multiple polluted sites. The data recorded for various parameters under study showed that among the plants tested, Cordyline terminalis at Control site i.e. College of Horticulture reported maximum values for canopy spread (59.54 cm2), leaf extract pH (7.49) and total chlorophyll content (3.86 mg g-1), while it recorded maximum values for ascorbic acid content (13.00 mg g-1), relative water content (89.54%), proline content (9.19 µmoles g-1) and superoxide dismutase activity (4.23 O.D. min-1 g-1) at APMDC factory site. Barleria cristata recorded superior values for Stomatal Index (33.40%) at College of Horticulture (control site) and Chlorophyll stability index (98.04%) at polluted site of APMDC. Phenol content was reported highest in Ixora coccinea (18.96 mg 100 g-1) at mining site (APMDC). Nyctanthus arbor-tristis at APMDC site had reported maximum value for Dust capturing capacity (0.31 mg cm-2). The Data on specific leaf weight showed non significance difference. Cordyline terminalis with superior biochemical traits showed higher Air Pollution Tolerance Index (APTI) values (21.86) at APMDC mining site while, Nyctanthus arbor-tristis with an Anticipated Performance Index (API) grade of 5 has been assessed as a very good performer under polluted sites.

Hydrochemical Dynamics and Water Quality Assessment of the Ramsar-Listed Ghodaghodi Lake Complex: Unveiling the Water-Environment Nexus

Human activities and climate change increasingly threaten wetlands worldwide, yet their hydrochemical properties and water quality are often inadequately studied. This research focused on the Ghodaghodi Lake Complex (GLC) and associated lakes in Nepal, a Ramsar-listed site known for its biodiversity and ecological significance. The study was conducted to assess seasonal water quality, investigate the factors influencing hydrochemistry, and assess the lakes’ suitability for irrigation. Forty-nine water samples were collected from the GLC in pre-monsoon and post-monsoon periods. Nineteen physicochemical parameters, such as dissolved oxygen (DO), total dissolved solids (TDS), and major ions (calcium ‘Ca2+’, magnesium ‘Mg2+’, and bicarbonate ‘HCO3−’), were analyzed using standard on-site and laboratory methods. Statistical methods, including analysis of variance (ANOVA), T-tests, and hydrochemical diagrams, e.g., Piper, were adopted to explore spatial and seasonal variations in water quality, revealing significant fluctuations in key hydrochemical indicators. Results showed marked seasonal differences, with pre-monsoon TDS levels averaging 143.1 mg/L compared to 78.9 mg/L post-monsoon, underscoring evaporation and dilution effects. The hydrochemical analysis identified Ca2+-HCO3− as the dominant water type, highlighting the influence of carbonate weathering on GLC’s water composition. Gibbs, mixing, and Piper diagram analysis supported these findings, confirming the predominance of HCO3−, with Ca2+ and Mg2+ as the main cations. Additionally, sodium adsorption ratio (SAR) values were consistently below 1, confirming excellent irrigation quality. These findings provided critical data for policymakers and stakeholders, supporting sustainable wetland management and aligning with the United Nations’ Sustainable Development Goals relevant to environmental conservation, i.e., clean water and life on land.

Psychological health declined during the post-monsoon season in communities impacted by sea-level rise in Bangladesh

Sea level rise affects the long-term psychological health of coastal communities. However, research on long-term and seasonal impacts on vulnerable communities’ psychological health is limited. Here, we explore the effect of sea-level rise on the psychological health of the coastal population in Satkhira and Khulna districts of southwest Bangladesh across two seasons: before monsoon (March to April) and post-monsoon months (October to November) in 2021. We leveraged the longitudinal research that involved 1144 participants. We collected data on psychological health using established scales for distress, depression, anxiety, and stress and also measured environmental factors and resource losses. Results indicate that psychological health, particularly distress, depression, anxiety, and stress, increased during the post-monsoon months in communities more vulnerable to sea-level rise. Highly vulnerable communities showed increased psychological distress post-monsoon. Environmental stressors and resource loss escalated during the post-monsoon period, especially in moderate and highly vulnerable communities. Our findings emphasize the urgent need for targeted support and resilience-building interventions in affected communities to alleviate the psychological health impacts of sea-level rise.

Variation characteristics and the influences of urbanization on hourly intense precipitation before and after monsoon onset over the Pearl River Delta.

The distinct spatiotemporal characteristics of the hourly intense precipitation (HIP) over the Pearl River Delta (PRD) and the impact of urbanization before and after the monsoon onset from 1972 to 2021 have been investigated using the hourly rain gauge data, nighttime lights data, and land use data. The results show a significant decreasing trend of HIP during the pre-monsoon onset period and a notable increasing trend during the post-monsoon onset period over the past five decades. However, compared to rural areas, rapid urbanization in the PRD after the mid-1990s weakens the HIP reduction, especially in the inland cities of PRD before the onset of the monsoon and enhances the HIP increase, particularly in the southeast inland and west coast cities after the onset of the monsoon. After rapid urbanization, the peak time of HIP has been postponed from 14 LST to 17 LST during the pre-monsoon onset period. HIP tends to occur more frequently in urban areas in the morning (10-12 LST) and evening (19-24 LST) compared to rural areas. In contrast, the impact of urbanization on the diurnal variation of HIP is not obvious during the post-monsoon period, despite higher frequencies of HIP occurring during the daytime (10-15 LST) in the urban areas after rapid urbanization. These findings provide valuable insights for forecasting HIP in urban agglomerations.

Multivariate statistical and hydrogeochemical analysis of seasonal groundwater quality variations in coastal villages of Trivandrum district, south India

This study attempts a detailed assessment of the quality of groundwater in the coastal region of Trivandrum District, Kerala where groundwater is the main source of drinking water. Forty groundwater samples were collected during the pre-monsoon and post-monsoon periods. The collected samples were analyzed for physical properties such as electrical conductivity (EC), pH, total dissolved solids (TDS), and total hardness, along with chemical properties, including major cations (Ca2⁺, Mg2⁺, Na⁺, K⁺) and anions (Cl⁻, SO₄2⁻, HCO₃⁻, NO₃⁻). The analysis of groundwater quality reveals significant spatial and seasonal variations caused by both natural and manmade influences. Water Quality Index (WQI), hydrogeochemical plots, and Principal Component Analysis (PCA) were used to analyses the data. The results show that Vakkom, Kazhakottam, Veli-Attipara, and Pozhiyoor show significant deterioration, and areas such as Varkala, Ayroor, and Edava generally maintain good water quality. The Water Quality Index (WQI) assessment indicates that approximately 22.5% of the studied area falls under excellent quality, while 17.5% is classified as poor. The WHO standard and BSI standards were used to derive the WQI. Principal Component Analysis (PCA) identified electrical conductivity, total dissolved solids, and total hardness as the primary factors affecting groundwater quality, explaining 65.17% and 61.03% of the total variance in the pre-monsoon and post-monsoon periods, respectively. Hydrochemical plots collaborate these results, emphasize the influence of rock-water interactions as the main geochemical process, further compounded by pollution from agricultural runoff and urban development. These findings highlight the need for sustainable groundwater management strategies in coastal communities. Effective measures, including pollution mitigation, sustainable agricultural practice, proper waste management, and preservation of freshwater ecosystems, are essential for ensuring the sustainability of groundwater resources.

Application of geospatial and machine learning algorithms to predict (under certain limitations) the quality of groundwater used for irrigation purposes

ABSTRACT The main objective of the present study is to evaluate groundwater quality for irrigation purposes in the central-western part of Haryana state (India). For this, 272 groundwater samples were collected during the pre- and post-monsoon periods in 2022. Several indices, including SAR, PI, Na%, KR, magnesium adsorption ratio (MAR), and IWQI were derived. The results of SAR, Na%, and KR values indicate that the groundwater is generally suitable for irrigation. On the other hand, PI and MAR exceeded the established limits, primarily showing issues related to salinity and magnesium content in the groundwater. Furthermore, according to the IWQI classification, 47.06 and 25% of the total collected samples fell under the ‘severe restriction for irrigation’ category during the pre-monsoon and post-monsoon periods, respectively. Spatial variation maps indicate that water quality in the western portion of the study area is unsuitable for irrigation during both periods. Three ML algorithms, namely RF, SVM, and XGBoost were integrated and validated to predict the IWQI. The results revealed that the XGBoost with random search achieves the best prediction performances. The approaches established in this study have been confirmed to be cost-effective and feasible for groundwater quality, using hydrochemical parameters as input variables, and highly beneficial for water resource planning and management.

A comprehensive analysis of groundwater quality: Geospatial and multivariate approaches in Dindigul District, Tamil Nadu, India

This study focuses on a comprehensive analysis of groundwater quality by integrating hydrogeochemical, geospatial, Multivariate Statistical Approaches (MSA), and water quality indices (WQI), along with visualization techniques, in the Dindigul district of Tamil Nadu, India. A total of 69 water samples, collected during pre-monsoon (PRM) and post-monsoon (POM) periods by the Public Works Department, Tharamani, were analyzed for major cations (Na+, Ca+, Mg+, K+), anions (Cl-, SO4-, HCO3-, NO3-), and various physical and chemical parameters such as pH, Total Dissolved Solids (TDS), and Electrical Conductivity (EC). The Water Quality Index (WQI) for Bureau of Indian Standard was calculated to assess water quality for drinking purposes. PRM samples showed poorer water quality due to ion dilution and agricultural influence compared to POM samples. The WQI revealed that 3.4 % of the PRM area had excellent water quality, 40.72 % good, 35.54 % poor, 18.41 % very poor, and 1.91 % unsuitable for drinking. In the POM period, 6.34 % of the area was classified as excellent, 51.03 % good, 40.09 % poor, 2.45 % very poor, and 0.08 % unsuitable. Irrigation water quality indices, including Sodium Percentage (Na%), Sodium Adsorption Ratio (SAR), Kelly's Ratio (KR), Magnesium Hazard (MH), Residual Sodium Carbonate (RSC), and Permeability Index (PI), were also computed to identify suitable zones for sustainable agriculture. Correlation analysis indicated significant positive relationships between TDS and other parameters, like Bicarbonate, Total Hardness, Chloride, and EC during PRM, and Sulphate, Total Hardness, Calcium, Chloride, Sodium, and EC during POM, suggesting that TDS is a key indicator of water quality variations in both periods.

Seasonal vertical accretion in different hydro-geomorphic environments of Indian Sundarban: Assessing the role of mangroves in mitigating sea level rise impacts

The Indian Sundarban, renowned for its unique hydro-geomorphic diversity, faces rising threats from sea level rise, necessitating an examination of the spatio-temporal variation of vertical accretion and the role played by mangroves in mitigating these impacts. As such, fifteen transects were chosen across buffer and transition zones of Indian Sundarban, each equipped with 4–6 sedimentation pins, to gauge accretion rates in premonsoon, monsoon, and postmonsoon season during period March 2020 to March 2022, considering diverse hydro-geomorphic attributes. The vertical accretion rate exhibits a curvilinear pattern, ascending from the lower seafront zone towards the middle of the estuarine region, reaching a peak, and subsequently declining towards the upper estuarine zones. Specifically, in the seafront zone, the yearly mean accretion (focusing solely on accretion and excluding subsidence) ranges between 5 and 10 mm/year, while in the middle estuarine region, it increases to an average of 38.1 ± 9.44 mm/year. However, in the upper zone, the yearly mean accretion decreases slightly to approximately 17.71 ± 9.54 mm/year. Similar patterns are observed when considering the distance from the riverfront to the interior of the mangrove zones. Seasonal analysis demonstrates that the postmonsoon period exhibits the highest accretion, followed by the premonsoon season, while the monsoon tends to be erosional in nature. Mangrove zonation, and subsequent distribution of root height, root diameter, root density, tree density, tree basal area, inundation frequency, current speed, variation in suspended sediment concentration were identified as influential factors affecting vertical accretion rates. Based on multiple regression analysis, root density, inundation frequency, and tree density demonstrated moderate-positive correlations with vertical accretion, whereas distance from the riverfront, root height, and root diameter displayed negative correlations. This study enhances our understanding of the intricate processes behind vertical accretion in the Sundarban, offering valuable insights for future research and advancing discussions on the broader implications of climate change in coastal regions.

Insights into the seasonal variation, distribution, composition and dynamics of microplastics in the Ganga River ecosystem of Varanasi City, Uttar Pradesh, India.

The current study explores the seasonal dynamics of microplastic (MP) pollution in the Ganga River of Varanasi City, Uttar Pradesh, India, focusing on water and sediment samples collected during pre-monsoon and post-monsoon periods. The analysis shows significant variations in MP occurrence, shape dynamics, color distribution, and size composition across diverse sampling sites. During the pre-monsoon season, MP concentrations ranged from 17 to 36 particles/L in water samples and 160 to 312 particles/kg in sediment, indicating a moderate to high level of contamination. Post-monsoon sampling showed higher MP concentrations at most sites, indicating the influence of seasonal hydrological changes on MP distribution. Shifts in MP shape dynamics were observed between seasons, with films, foams, fragments, and filaments showing variable distributions. Similarly, color variations in MPs exhibited site-specific patterns, with white, brown, blue, and other colors being predominant. These findings highlight the diverse sources and compositions of MPs in the river ecosystem, highlighting the complexity of MP pollution dynamics. Polymer-type distributions further elucidated the composition of MPs, with notable contributions from polyethylene terephthalate, rayon, polyester, and polyvinyl chloride. PCA analysis revealed significant shifts in particle size and shape distribution between pre-monsoon and post-monsoon periods in both water and sediment samples, with post-monsoon samples showing an increase in larger particles and filaments. These changes highlighted key factors driving the variance in microplastic contamination across different sites. The prevalence of these polymers features diverse sources of MP pollution, including textiles, packaging materials, and industrial waste. Ongoing monitoring and research are crucial to understanding its sources, distribution, and impact on river ecosystems, essential for protecting aquatic biodiversity and human health.

Inter-annual variability in the phytoplankton abundance and community structure of a tropical monsoonal estuary in response to variable monsoonal patterns

The study elucidates the inter-annual and seasonal variability in the phytoplankton abundance and community structure concurrent to variable rainfall patterns in Chettuva, a tropical monsoonal estuary along the southwest coast of India. The phytoplankton community exhibited statistically significant inter-annual variation with a 1.2-fold increase in abundance (av. 19.44 ×104cellsL−1) in 2021 in comparison with 2019 (av. 15.30 ×104cellsL−1). A total of 87 phytoplankton species were observed during the study, among which Bacillariophyceae dominated with 52 species, followed by Dinophyceae (20 species), and to a lesser extent by Chlorophyceae (11 species) and Cyanophyceae (2 species). Phytoplankton community structure also showed variation, with 71 species contributing to the diversity in 2021 and 62 species in 2019. Though Bacillariophycea dominated during both years, the community was more diverse in 2021comparatively a more saline year Biddulphia sp. Coscinodiscus sp., Cyclotella striata, Melosira sulcata, Pleurosigma sp., and Skeletonema costatum were the diatoms common to both the years, though with varied abundance. Dinophyceae did not show a conspicuous change in community structure in both years, with mostly the same species contributing to the total phytoplankton population but showed slight variation in abundance. Cyanophycea was observed exclusively during the year 2021. The abundance and community structure of the species varied from year to year, but they also changed seasonally, with lower numbers observed during the monsoon compared to the post-monsoon period in both years. CCA analysis identified two groups of phytoplankton assemblages in relation to the prevailing environmental conditions. The Group I species preferred lower temperature and salinity and elevated nutrient concentrations and they dominated during the monsoon season. Group II species preferred high saline well oxygenated, nutrient-poor waters and they dominated during the post-monsoon. Furthermore, the trophic state index analysis indicated mesotrophic conditions during the monsoon, while eutrophic conditions were observed in the post-monsoon period.

Seasonal Dynamics and Avian Diversity along the Adyar Riverbank: Insights from a Year-Long Survey

The avian survey conducted along the Adyar Riverbank (Manapakkam) from January 2023 to December 2023 documented a total of 3120 individual birds across 75 species from 16 avian orders, highlighting the significant biodiversity within this urban ecosystem. This study aimed to assess seasonal variations in bird diversity and abundance, emphasizing the river’s role as an important habitat. The highest diversity was observed during winter, specifically in February 2023, with a diversity index of 296.80 and a Simpson’s index of 0.22. A total of 36 species and 636 individuals were recorded. In contrast, the lowest diversity was observed in summer, particularly in July 2023, with a diversity index of 29.29 and a Simpson’s index of 0.05, corresponding to 18 species and 114 individuals. The monsoon and post-monsoon periods exhibited a prominent increase in diversity due to the arrival of migratory species and improved habitat conditions. Important species recorded throughout the year included the Paddy Field Pipit, House Crow, and Rufous Treepie, while conservation-significant species such as the Black-headed Ibis and Spot-billed Pelican were also observed. Thus, the present study underscores the Adyar River’s ecological importance and highlights the need for continuous monitoring and targeted conservation efforts to maintain avian biodiversity in urban river ecosystems.

Influence of future climate scenarios using CMIP 5 data on malaria transmission in India

BackgroundVector-borne diseases, such as malaria, pose a significant global threat, and climatological factors greatly influence their intensity. Tropical countries, like India, are particularly vulnerable to such diseases, making accurate estimation of malaria risk crucial.MethodsThis study utilized the well-known Vector-borne Disease Community Model, VECTRI, developed by the International Centre for Theoretical Physics in Trieste. The model was implemented to estimate malaria’s Entomological Inoculation Rate (EIR). Future climatic prediction datasets, including CMIP 5 and population data sets, were used as inputs for the analysis. Three RCP scenarios are considered (Representative Concentration Pathways are climate change scenarios that project radiative forcing to 2100 due to future greenhouse gas concentrations). The projections covered the period from 1 Jan, 2020, to 31 Dec, 2029.ResultsThe estimated mean EIR for the years 2020–2029 ranged, and a significant decline in malaria risk was observed with all RCP 2.6, 4.5, and 8.5 scenarios. Each year 0.3 to 2.6 [min–max] EIR/person/day decline is observed with a strong decline in man rainfall ranging from 5 to 17 [min–max] mm/year and associated high temperatures ranging from 0.03 to 0.06 [min–max] °C/year. During the post-monsoon period, August to November were identified as highly prone to malaria transmission. Spatial analysis revealed that the east coast of India faced a higher vulnerability to malaria risk, which kept increasing through RCP scenarios. Thus, it is essential to exercise caution, especially in areas with heavy rainfall.ConclusionThis research provides valuable insights for policy-makers, highlighting the need to implement future strategies to mitigate malaria risk effectively. By utilizing these findings, appropriate measures can be taken to combat the threat posed by malaria and protect public health.

Prevalence of canine renal insufficiency: A decade-long retrospective study in and around Patna, Bihar

This retrospective study investigates the prevalence and epidemiological factors associated with renal insufficiency in dogs within Patna, Bihar, India. Out of 5,700 dogs with various illnesses, 317 were diagnosed with renal insufficiency, identified by serum creatinine levels exceeding 5 mg/dL. The study assessed the incidence of renal insufficiency across different demographics, including age, sex, breed, and season. The highest incidence was observed in dogs aged 8-10 years, with males showing a higher prevalence than females. Pomeranians (32.18%), Labrador Retrievers (25.55%), and German Shepherds (20.82%) were the most affected breeds. Seasonally, the post-monsoon period (September-November) exhibited the highest incidence (37.85%) of renal disorders. Laboratory investigations revealed significant haematological and biochemical alterations in affected dogs, including lower haemoglobin, total erythrocyte count, and packed cell volume, alongside elevated serum levels of blood urea nitrogen (BUN), creatinine, potassium, and phosphorus. Ultrasonography indicated decreased renal size and increased echogenicity in dogs with renal insufficiency. The study concludes that renal insufficiency in dogs is most prevalent in older males and certain breeds, particularly during the post-monsoon season. Regular monitoring of serum BUN and creatinine levels is recommended for early diagnosis and management of this condition.

Seasonal variability of microplastic contamination in marine fishes of the state of Gujarat, India.

Seasonal variation in microplastics abundance, occurrence, and distribution in pelagic and demersal fishes was observed in this study during December 2021 to November 2022. One hundred percent presence of microplastic in inedible (gut and gills) tissue, while 82% and 54% in edible tissue (muscle) of pelagic and demersal fishes respectively were seen. Post-monsoon period showed high prevalence of microplastics followed by monsoon and the least during pre-monsoon in both pelagic and demersal fishes. In pelagic fishes, the edible tissue had microplastics abundance of 1.56 to 13.34 numbers per 10g of tissue whereas inedible tissue had 3.36 to 16.67 numbers per 10g of tissue. In demersal fishes, the edible tissue had microplastics abundance of 1.04 to 5.26 numbers per 10g of tissue while it was 2.67 to 8.34 numbers per 10g of inedible tissue. There was significant variation in abundance of microplastic in edible and inedible tissue of all the fishes (Mann-Whitney test, p < 0.05). The most dominant microplastics size was 0.005-0.05mm followed by 0.05-0.5mm and the least of greater than 0.5mm in pelagic and demersal fishes respectively. Taking microplastic shape into consideration, the most dominant was fiber followed by fragment and the film in inedible tissue of all the fishes. The edible tissue of all the fishes had only fiber in them (100% occurrence). The dominance of blue color microplastics was observed followed by red, green, yellow, and orange at least in edible as well as inedible tissues of the fishes. More than 99% microplastics polymer observed in this study include polyethylene (PE), polypropylene (PP), and polystyrene (PS); only less than 1% was unidentified. This is the first study done on seasonal variation of microplastic in the marine fish population of Gujarat waters, Northeast Arabian Sea. The study highlights the nature of micro-pollutant in marine environments, emphasizing the need for comprehensive monitoring and management strategies.

Circulating serotypes and genotypes of dengue virus in North India: An observational study.

This study reports observation on circulating serotypes and genotypes of Dengue Virus in North India. Serum samples were obtained from suspected cases of dengue referred to the virus diagnostic laboratory during 2014 to 2022. All samples were tested for anti-dengue virus IgM antibodies and NS1Ag by ELISA. NS1Ag positive samples were processed for serotyping and genotyping. Total 41,476 dengue suspected cases were referred to the laboratory of which 12,292 (29.6%) tested positive. Anti-Dengue Virus IgM antibodies, NS1Ag, both IgM and NS1Ag, were positive in 7007 (57.4%); 3200 (26.0%) and 2085 (16.0%) cases respectively. Total 762 strains were serotyped during 9-year period. DENV-1, DENV-2, DENV-3 and DENV-4 serotypes were found in 79 (10.37%), 506 (66.40%), 151 (19.82%) and 26 (3.41%) cases respectively. DENV-1, DENV-2 and DENV-3 were in circulation throughout. Total 105 strains were genotyped. Genotype IV of DENV-1 serotype was circulating till 2014 which was later replaced by genotype V. A distinct seasonality with increase in number of cases in post-monsoon period was seen. DENV-1, DENV-2 and DENV-3 were found to be in circulation in North India. Predominant serotype/genotype changed at times, but not at regular intervals.