Hotspot Areas Research Articles

The physical and biogeochemical parameters along the coastal waters of Saudi Arabia during field surveys in summer, 2021

Abstract. During the last decades, the coastal areas of the Kingdom of Saudi Arabia, on the Red Sea and the Arabian Gulf, have been subjected to intense economic and industrial growth. As a result, it may be expected that the overall environmental status of Saudi Arabian coastal marine waters has been affected by human activities. As a consequence, adequate management of the Saudi Arabian coastal zone requires an assessment of how the various pressures within this zone impact the quality of seawater and sediments. To this end, environmental surveys were conducted over 15 hotspot areas (areas subject to environmental pressures) in the Saudi Arabian coastal zone of the Red Sea and over three hotspot areas in the Saudi Arabian waters of the Arabian Gulf. The survey in the Red Sea, conducted in June/July 2021, acquired measurements from hotspot areas spanning most of the Saudi coastline, extending from near the Saudi–Jordanian border in the north to Al Shuqaiq and Jizan Economic City (close to the Saudi–Yemen border) in the south. The survey in the Arabian Gulf, carried out in September 2021, included the areas of Al Khobar, Dammam and Ras Al Khair. The main objective of both cruises was to record the physical and biogeochemical parameters along the coastal waters of the kingdom, tracing the dispersion of contaminants related to specific pressures. Taken together, these cruises constitute the first multidisciplinary and geographically comprehensive study of contaminants within the Saudi Arabian coastal waters and sediments. The measurements acquired revealed the influence of various anthropogenic pressures on the coastal marine environment of Saudi Arabia and also highlighted a strong influence of hydrographic conditions on the distribution of biochemical properties in the Red Sea and the Arabian Gulf. The data can be accessed at SEANOE https://doi.org/10.17882/96463 (Abualnaja et al., 2023), whereas the details of the sampling stations are available at https://mcep.kaust.edu.sa/cruise-postings (last access: 25 March 2024). The dataset includes the parameters shown in Tables 1a, b and 2a.

Spatial distribution of zero-dose children in Ethiopia: evidence for a targeted intervention from a large-scale cross-sectional evaluation survey.

Ethiopia is the fourth leading contributor to the global total of zero-dose children (those who lack the first dose of diphtheria-tetanus-pertussis containing vaccine) and has substantial regional variations in zero-dose children. This study explored the spatial pattern of zero-dose children aged 12-35 months in Ethiopia. A survey was conducted in pastoralist regions, developing regions, newly-established regions, conflict-affected areas, underserved urban populations, hard-to-reach areas, internally displaced populations, and refugees. Spatial autocorrelation was measured using the Global Moran'sIstatistic. Getis-Ord Gi* statistics was applied to calculate the spatial variability of the high and low prevalence rates of zero-dose children. The spatial interpolation technique was also applied to estimate unknown values that fall between known values. Inverse distance weighting interpolation method was used to predict the risk of zero-dose children. ArcGIS version 10.8 was used for the spatial analysis. A total of 3,646 children aged 12-35 months were included in the study. The spatial distribution of zero-dose children in Ethiopia was non-random (Global Moran'sI = 0.178971, p < 0.001). According to the hotspot analysis, western, eastern and northern parts of Somali and western and central parts of Afar regions had the highest load of zero-dose children (hotspot areas) followed by the Northeastern part of Amhara and southeastern part of Oromia regions. On the other hand, Southern Nations, Nationalities, and Peoples, Sidama, and the Eastern part of the Southwest Ethiopia peoples regions were identified as cold spot areas. The spatial interpolation analysis corresponded with the hotspot analysis results where western and central parts of Afar and western, eastern and northern parts of Somali regions were identified as high-risk areas for zero-dose children. However, Addis Ababa, Dire Dawa, Harari, Southern Nations, Nationalities, and Peoples, Sidama, Southwest Ethiopia Peoples, and parts of Oromia were found to be low-risk areas for zero-dose children. The spatial analysis identified that zero-dose children had a significant spatial variation across the study areas. High clusters of zero-dose children were detected in Afar and Somali regions. Implementing routine and mop-up vaccination campaigns in the identified hotspot areas will help Ethiopia to improve coverage and reduce immunization inequalities.

Woody Species Composition, Structure, and Status of Regeneration in Pugnido Forest, Gambella Region, Western Ethiopia.

Ethiopia is a biodiversity hotspot area with a high concentration of plant species that play countless roles in ecosystem resilience and mitigating the effects of climate change. However, forest resources are degrading at an alarming rate due to different anthropogenic factors. Pugnido Forest, which is among Ethiopia's greatest woodland sections, also faced a similar challenge. Thus, this study was intended to assess the composition, structure, and regeneration status of woody plant species in Pugnido Forest, West Ethiopia. Eighty main plots sized 20 × 20 m were sampled systematically on six east-west-oriented line transects, which are parallel to each other and 500 m apart. At the four corners and the center of the main plots, five subplots sized 2 m × 2 m were laid to collect seedling and sapling information. Individual woody species were identified and then recorded per plot. The forest structure and regeneration status data were recorded and analyzed using structural parameters. Communities were identified via cluster analysis. A comparison of diversity and composition among communities was made using the Shannon-Wiener diversity and Sorensen's similarity coefficients, respectively. A total of 106 woody species included in 40 families were documented. Fabaceae stands first in the species-rich family (23.6%), and Moraceae stands second (8.5%). Overall Shannon-Wiener diversity and evenness of species were 4.41 and 0.93, respectively. Four communities were generated from cluster analysis. Sorensen's similarity value among communities ranged from 42% to 59%. The forest's density and basal area were 5298.8 stems·ha-1 and 82.5 m2·ha-1, respectively. The trend in frequency and density classes showed a decreasing number of species towards higher classes. Diameter at breast height (DBH), height, and basal area analyses revealed a normal J-shaped pattern. Several species had a smaller importance value index (IVI) value. Density ratios of juveniles to adult plants indicated good regeneration status. Species with small IVI values and few or no seedlings require conservation priority. Top priority must be given to conserving species with low IVI values and few or no seedlings.

Impact of first medical contact-teams on the quality of prehospital care of emergency patients in a hot-spot area of a major city

Zusammenfassung Hintergrund Niedrigprioritäre Hilfeersuchen – sogenannte Low-code-Einsätze – machen einen erheblichen Teil der Einsätze im Rettungsdienst in sogenannten Hotspot-Arealen einer Großstadt aus. Ziel unserer Arbeit war es, die im Rahmen des Projekts „Altstadtwache Düsseldorf“ angewendete Dringlichkeitseinschätzung von Erstversorgungstrupps zu bewerten, eine mögliche Fehleinschätzung zu erfassen und die Auswirkungen auf die Versorgungsqualität zu untersuchen. Material und Methoden Im Rahmen des Projekts wurde begleitend eine prospektive monozentrische Beobachtungsstudie durchgeführt. Es wurden Erstversorgungstrupps (EVT) eingesetzt, die zentral stationiert waren und parallel zum Regelrettungsdienst alarmiert wurden. Einsatzzeiten waren die zu erwartenden Hochfrequenzphasen an Frei- und Samstagen von 19 bis 1 Uhr des Folgetags. Der Erhebungszeitraum erstreckte sich über drei Monate von 12/2022 bis 02/2023. Ergebnisse Im Untersuchungszeitraum von 12/2022 bis 02/2023 wurden 257 Einsätze im Hotspot-Areal der Düsseldorfer Altstadt disponiert. 85 Einsätze wurden ausgeschlossen. Von den 162 Primäreinsätzen waren 10 Fehleinsätze (6 %). Aus der Grundpopulation wurden zwei Gruppen gebildet. Gruppe A waren 83 (55 %) Patienten, die ins Krankenhaus transportiert wurden. Häufigstes Transportmittel war der KTW, der eigens hierfür vorgehalten wurde, mit 44 (29 %) Transporten, gefolgt von RTW-Transporten mit 32 (21 %). Schlussfolgerung Durch die korrekte Einschätzung der Erkrankungs- oder Verletzungsschwere können höherwertige Rettungsmittel des Regelrettungsdiensts in den Abendstunden von Wochenenden durch sinnvollen Einsatz eines Krankentransportwagens oder anderer Versorgungsstrukturen geschont und die Arbeitsbelastung durch Bagatelleinsätze in Hotspot-Arealen verhindert werden. Graphic abstract

Geospatial variation of exclusive breastfeeding and its determinants among mothers of infants under 6 months in Ethiopia: spatial and geographical weighted regression analysis

BackgroundExclusive breastfeeding (EBF) is a major public health problem in Ethiopia. However, the spatial variation of EBF and the associated factors have not been studied as much as we have...

The spatiotemporal epidemiological study on human brucellosis in shenyang, China from 2013 to 2022

BackgroundEpidemiological characteristics of human brucellosis (HB) have changed over the last decade. In this study, we depicted the spatiotemporal features of HB in Shenyang, China, from 2013 to 2022 and the objective was to visualise spatiotemporal patterns and identify high-risk regions with the purpose to provide evidence for HB prevention and control. MethodsWe performed an observational epidemiological study using HB data obtained from the National Notifiable Disease Reporting System (NNDRS). Joinpoint regression analysis was employed to determine the changing trends in the annual incidence. A vector boundary map of Shenyang was used to visualise spatial distribution. Spatial autocorrelation was identified using both global and local Moran's autocorrelation coefficients, while hotspot areas were determined using the Getis-Ord statistic. ResultsA combined sum of 4103 HB cases were analysed, and the average level of annual incidence of HB was 5.52 per 100,000. The incidence of HB showed obvious seasonality, with a notable peak observed from April to July (summer peak). The annual incidence in Shenyang has been on the rise since 2013, with an annual percentage change (APC) of 6.39% (95%CI 1.29%, 12.39%). Xinmin County exhibited the most elevated average annual incidence rate, with Faku County ranking second. The average annual incidence in rural areas exhibited a significantly greater disparity compared to suburban areas (P < 0.001), whereas the incidence rate in suburban areas demonstrated a significantly higher contrast when compared to urban areas (P < 0.001). A clustered distribution of the annual incidence of HB was observed for all years from 2013 to 2022. Abnormally high values were found in suburban areas, and no abnormally high values were found after 2017. The low-low clustering areas were found in urban as well as suburban areas from 2013 to 2022. Hotspots (P < 0.05) were located in rural areas, while cold spots (P < 0.05) were found in both urban and suburban areas. Since 2020, there have been no hotspots in Shenyang. ConclusionsRural areas are high-risk areas for HB and may be key to controlling HB epidemics. Although the annual incidence of HB in rural areas has increased, owing to the stability of spatial relationships and the disappearance of hotspots, there is little possibility of outbreaks; however, stricter monitoring should be applied in rural areas to prevent the emergence of new transmission routes.

Establishment and assessment of a variable-area parameterized model of microchannel for high temperature uniformity

Maintaining temperature uniformity of the device is a crucial factor in reducing the risk of local overheating and ensuring high performance stability. In this paper, we proposed a novel inner-fin microchannel (IFMC) cooling system based on the ideas of variable density microstructures and local densification design principles, and further established a parameterized model between the inner-fin height and heating condition for improving the temperature uniformity. The numerical simulation studies indicated the IFMC heat sink can maintain a high temperature uniformity under uniform and non-uniform heat flux densities. The maximum temperature different on heating surface (ΔT) of the IFMC heat sink is less than 2.6 K when the inlet velocity varies between 0.8 m/s and 1.4 m/s under uniform heat flux density. The ΔT with one hotspot and two hotspot areas is 2.03 K and 1.75 K when the heat flux densities of the hotspot and background area on the heating surface are 300 W/cm2 and 150 W/cm2, respectively. Moreover, the standard deviation of temperature (SDT) on the heating surface of the IFMC structure is much lower than that of the traditional microchannel (TMC) structure at the same inlet flow rate, with a decrease rate of over 96.05 %. These studies can provide reference for further design and development of equipment cooling systems with high temperature uniformity.

Enhancing Seedling Performance Direct Seeded Rice Under Anaerobic Germination Condition by Seed Invigoration

In an effort to address labor scarcity and enhance the cropping index in tidal swamp areas, farmers utilize direct seeding techniques. However, flooded conditions due to tides and ebb can hinder seed germination. This study aimed to obtain the best invigoration treatment for improving seedling establishment and growth in South Sumatra's tidal swamp hotspots. In the first part of the study, 19 different seed treatments were tested on the swamp rice variety, Inpara 9, in a greenhouse. These treatments included hardening, priming, thermal treatment, and controls. Soluble sugar content and α-amylase activities of treated seeds were analyzed in the lab. The results showed that the invigorated seeds outperformed the control group in terms of seedling growth and development when they were planted directly in the ground under both anaerobic germination (AG) and anaerobic germination with extra FeSO4 added to the soil (AG+Fe) conditions. All treated seeds also exhibited higher soluble sugar and α-amylase activities. A follow-up experiment in a hotspot area assessed the effectiveness of the top nine seed treatments from the first experiment under AG conditions. The flooded level was managed at around 10 cm during the experiment and Inpara-9 was the variety planted. All invigorated seeds exhibited superior seedling establishment and growth compared to the control on in-situ swampy land. Hardening using Trichoderma yielded the highest seedling establishment and performance, indicated by greater root and shoot dry weight than other treatments, followed by hardening with Methylobacterium td-J7 and Methylobacterium td-tpb3.

Leveraging social capital for educational resilience in conflict: The impact of community behaviors on educational access in pre-Taliban ruling Afghanistan

This study investigates the role of communities in fostering resilience within the education sector amid conflict. By emphasizing the importance of collective community behaviors fostered by the cultivation of interpersonal connections in social capital, the study estimates the impact of community behaviors on the access to primary and lower secondary education in Afghanistan. Using the Geographic Information System (GIS) for battles in Afghanistan, the study conducted hotspot analysis and identified intensified conflict areas (hotspots), base areas, and relatively safe areas (coldspots) across Afghanistan as of 2014. Authors then estimated the determinants of community behaviors for access to education in each area with multi-level logit analysis using individual and community levels' information in the Afghanistan Living Conditions Survey (ALCS) 2014 collected from 20,700 households. The findings indicate that among the four community behaviors, gender-related behaviors within the community notably enhanced girls' access to education in hotspot areas. Similarly, security-related atmosphere facilitated improved access to education for both girls and boys, irrespective of the conflict intensity, and community behaviors against child labor also improved boys' access to education. However, classical educational assistance program was effective only in relatively safe areas. These findings illuminate the role of community social capital in fortifying the educational sector's resilience, providing a foundation for the development of effective education policies and support mechanisms in conflict situation.

GIS-based analysis to assess biogas energy potential as support for manure management in Southern Italy

Anaerobic digestion can provide a valuable aid to manure management while producing renewable energy. Biogas production is highly dependent on the size and composition of livestock farms, and the availability of fresh manure can vary throughout the year, limiting reliable assessment of potential production. The aim of this study is to develop an affordable GIS-based analysis to support manure management, based on a highly detailed livestock farm database. Databases refer to the years 2013 and 2019 and report the herd consistency and the age of each class head. Kernel density (KD) was used to identify emerging hotspot areas with potentially high concentrations of nitrogen applied to the field. Three KD classification methods were compared: defined interval (DI) into 3 classes (0-170, 170-340, &gt; 340 kg N/ha), quantile (Q) and natural break (NB). The results show that the DI and NB areas correspond to 40 % and 84 % of the total N of buffalo origin in the Campania region, with a N surplus in the hotspot areas localized in nitrate vulnerable zones of 55 and 6 % respectively. The biogas produced from 50 % of the buffalo manure in these areas generates sufficient energy to allow the removal of the N surplus.

Spatio-Temporal Evolution Characteristics and Influencing Factors of INGO Activities in Myanmar

Myanmar is among the regions with the most frequent activities of International Non-Government Organizations (INGOs). Analyzing the spatio-temporal patterns of these activities holds crucial importance for optimizing organizational coordination and enhancing governmental oversight. This study focuses on the spatio-temporal evolution characteristics and influencing factors of INGO activities in Myanmar from 2010 to 2021, utilizing spatial autocorrelation and regression analysis. The results show that the number of INGOs in Myanmar has shown a gradual slowdown in growth trends, with the number of activities exhibiting a wave-like pattern, primarily driven by spontaneous activities of INGOs. The spatial distribution of INGO activities in Myanmar is concentrated in the southern plains, with the core located in Yangon, Naypyitaw, and Loilen. Furthermore, there is significant spatial polarization in the hotspot area of INGO acticities. The hotspots followed an evolutionary path from “South Myanmar” to “North Myanmar” and then back to “South Myanmar”. INGO activities in Myanmar are more focused on the local economic level, urbanization level, medical level, education level, and total population size, providing the necessary support and services for the local society and making up for the “government malfunction” and “market malfunction”.

Assessment and prediction of human-elephant conflict hotspots in the human-dominated area of Rajaji-Corbett landscape, Uttarakhand, India

Understanding the dynamics that drive human-wildlife conflict and identifying potential mitigation solutions requires understanding the spatial patterns of conflict. The juxtaposition of ecological preservation and economic growth has led to increased conflicts between humans and Asian elephants Elephas maximus in the Rajaji-Corbett landscape of Uttarakhand, India, where the conversion of elephant habitat to agricultural land have increased over the last several decades. We investigated the predictors influencing household-level human-elephant conflicts (HECs) using binomial Generalized Linear Models (GLMs) collected from semi-structured questionnaire-based surveys of 266 households in the human-wildlife interface next to protected areas. Further, we modelled the landscape predictors that influence the spatial distribution of HECs by collecting occurrence data of HECs in 25 km2 grid units (N = 1473 grids) using Maxent software. We discovered that HECs are directly influenced by the diversity of major and minor crops planted and the proximity to agricultural land (conflicts decreased with increasing distance from the agricultural land). We also observed that the probability of HECs decreased with increasing elevation, increase in road networks, and with increasing slope in the study area; while HECs increased with increase in human population. We discovered that nearly one-fifth of areas sampled (3606.87 km2) in the Rajaji-Corbett landscape were at high risk of HEC, especially flat, agrarian areas where most people reside. Farmers in the susceptible risk areas identified by our study could lessen the likelihood of crop damage and HEC incidents by cultivating highly profitable alternative crops that are less attractive to elephants. Additionally, implementing mobile-based Early Warning System in high HEC hotspot areas could mitigate crop raiding and potentially reduce the occurrence of HECs. The findings of our study can assist policymakers and park management in designing landscape-scale human-wildlife conflict mitigation strategies tailored to identified conflict hotspots.

Predicting sediment yield and locating hotspot areas in the Hamesa watershed of Ethiopia for effective watershed management

Abstract Locating hotspots and assessing sediment accumulation are crucial aspects of water body management. The primary aim of this study was to examine sediment yield in the Hamesa watershed utilizing the Soil and Water Assessment Tool (SWAT) model and to propose best management practices. The basin was divided into 15 sub-basins, with 103 hydrological response units at the outlet of the Hamesa watershed. Simulation was conducted using meteorological and spatial data. Monthly streamflow and sediment data were calibrated for the period from 2000 to 2010 and validated for the period from 2011 to 2015 using the SWAT Uncertainty Calibration Program Sequential Uncertainty Fit (SUFI-2). Model performance was assessed using metrics including the coefficient of determination (R2), Nash–Sutcliffe model efficiency, observation standard deviation ratio, and percentage bias, which demonstrated very good results in both calibration and validation periods. The average annual sediment production in the Hamesa watershed was estimated at 9,800 t/year. Nine out of 15 affected sub-basins were categorized as producing moderate to very high sediment content (4.54–12.82 t/ha/year) and were chosen for sediment reduction scenarios. This study will play a significant role in managing impacted watersheds affected by soil erosion.

Low Measles Vaccination Coverage and Spatial Analysis of High Measles Vaccination Dropout in Ethiopia's Underprivileged Areas.

(1) Background: Measles remains a major cause of disease and death worldwide, especially in the World Health Organization African Region. This study aimed to estimate the coverage of measles vaccinations and map the spatial distribution of measles vaccination dropout in Ethiopia; (2) Methods: A cross-sectional survey was conducted in Ethiopia's underprivileged areas. The study included 3646 mothers/caregivers of children. ArcGIS for the spatial analysis, Global Moran's I statistic for spatial autocorrelation, and Getis-Ord Gi* statistics for hot spot analysis were applied; (3) Results: Overall, coverages of measles-containing-vaccine first- and second-doses were 67% and 35%, respectively. Developing regions had the lowest coverages of measles-containing-vaccine first- and second-doses, 46.4% and 21.2%, respectively. On average, the measles vaccination dropout estimate was 48.3%. Refugees had the highest measles vaccination dropout estimate (56.4%). The hot spot analysis detected the highest burden of measles vaccination dropout mainly in the northeastern parts of Ethiopia, such as the Afar Region's zones 1 and 5, the Amhara Region's North Gondar Zone, and peripheral areas in the Benishangul Gumuz Region's Assosa Zone; (4) Conclusions: The overall measles vaccination coverages were relatively low, and measles vaccination dropout estimates were high. Measles vaccination dropout hot spot areas were detected in the northeastern parts of Ethiopia.

VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy

Land use/cover change (LUCC) refers to the phenomenon of changes in the Earth’s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining the health of the Earth’s ecosystems. LUCC is a dynamic geographical process involving complex spatiotemporal dependencies. Existing LUCC simulation models suffer from insufficient spatiotemporal feature learning, and traditional cellular automaton (CA) models exhibit limitations in neighborhood effects. This study proposes a cellular automaton model based on spatiotemporal feature learning and hotspot area pre-allocation (VST-PCA). The model utilizes the video swin transformer to acquire transformation rules, enabling a more accurate capture of the spatiotemporal dependencies inherent in LUCC. Simultaneously, a pre-allocation strategy is introduced in the CA simulation to address the local constraints of neighborhood effects, thereby enhancing the simulation accuracy. Using the Chongqing metropolitan area as the study area, two traditional CA models and two deep learning-based CA models were constructed to validate the performance of the VST-PCA model. Results indicated that the proposed VST-PCA model achieved Kappa and FOM values of 0.8654 and 0.4534, respectively. Compared to other models, Kappa increased by 0.0322–0.1036, and FOM increased by 0.0513–0.1649. This study provides an accurate and effective method for LUCC simulation, offering valuable insights for future research and land management planning.

Species Diversity and Conservation of Typhlocybinae (Heteroptera: Cicadellidae) in China

Abstract Species diversity is undergoing rapid reductions globally. Identifying the causes underlying species diversity patterns and biodiversity hotspots is critical for developing conservation strategies. In this study, the 4,594 occurrence records of 854 Typhlocybinae (Heteroptera: Cicadellidae) species in China were used to investigate the factors affecting species richness and endemism patterns as well as identify species diversity hotspots to establish their conservation status. Generalized linear models and hierarchical partitioning were used to assess the effects of 6 environmental factors on species richness and endemism. Species diversity hotspots were obtained by integrating the 10 grids with highest levels of species richness and endemism; the conservation status of these hotspots was assessed via gap analysis. We found that species richness and endemism distribution of Typhlocybinae in China were heterogeneous, mainly concentrated in southern and central areas. The results also showed that plants were the most important environmental factors affecting species richness and endemism patterns, followed by niche conservatism. The 10 hotspots were identified; however, they were not fully protected by the existing nature reserves. This study highlights the importance of plants and niche conservatism in shaping species richness and endemism patterns of Typhlocybinae. Moreover, establishment of new nature reserves in hotspot areas with a conservation gap is required.

Spatial analysis of food and water-borne diseases in Ahmedabad, India: Implications for urban public health planning

Spatial analysis of infectious diseases can play an important role in mapping the spread of diseases and can support policy making at local level. Moreover, identification of disease clusters based on local geography and landscape forms the basis for disease control and prevention. Therefore, this study aimed to examine the spatial-temporal variations, hotspot areas, and potential risk factors of infectious diseases (including Viral Hepatitis, Typhoid and Diarrhea) in Ahmedabad city of India. We used Moran's I and Local Indicators of Spatial Association (LISA) mapping to detect spatial clustering of diseases. Spatial and temporal regression analysis was used to identify the association between disease incidence and spatial risk factors. The Moran's I statistics identified presence of positive spatial autocorrelation within the considered diseases, with Moran's I from 0.09 for typhoid to 0.21 for diarrhea (p < 0.001). This indicates a clustering of affected wards for each disease, suggesting that cases were not randomly distributed across the city. LISA mapping demonstrated the clustering of hotspots in central regions of the city, especially towards the east of the river Sabarmati, highlighting key geographical areas with elevated disease risk. The spatial clusters of infectious diseases were consistently associated with slum population density and illiteracy. Furthermore, temporal analysis suggested illiteracy rates could increase risk of viral hepatitis by 13 % (95 % Confidence Interval (CI): 1.01–1.26) and of diarrhea by 18 % (95 % CI: 1.07–1.31). Significant inverse association was also seen between viral hepatitis incidence and the distance of wards from rivers. Conclusively, the study highlight the impact of socio-economic gradients, such as slum population density (indicative of poverty) and illiteracy, on the localized transmission of water and foodborne infections. The evident social stratification between impoverished and affluent households emerges as a notable contributing factor and a potential source of differences in the dynamics of infectious diseases in Ahmedabad.

Seroprevalence of contagious bovine pleuropneumonia (CBPP) in cattle from Karamoja region, North-eastern Uganda

BackgroundContagious bovine pleuropneumonia [CBPP] is a transboundary animal disease of cattle caused by Mycoplasma mycoides subsp. mycoides [Mmm]. CBPP causes severe economic losses to livestock producers in sub-Saharan Africa mainly due to high mortality, morbidity, reduction in productivity as well as livestock trade restrictions. This study aimed at determining seroprevalence of Mmm in cattle from Karamoja region, north-eastern Uganda; data that are required to design and implement risk based CBPP control program.MethodsWe randomly collected blood samples from 2,300 cattle spread across Karamoja region. Serum was extracted and screened for antibodies against Mycoplasma mycoides subsp. mycoides [Mmm] using the competitive enzyme linked immunosorbent assay [cELISA].ResultsA quarter [25.4%; 95% CI: 23.7–27.3] of the screened cattle [n = 2,300] were sero-positive for Mmm. Amudat and Kaabong districts recorded the lowest [12.3%] and highest [30.7%] Mmm seroprevalence respectively. Increasing age, overnight stay in cattle kraals and location [certain districts, villages, herds and sub counties] of the cattle herds, the factors that promote animal commingling, were the most significant risk factors of seroconversion with Mmm.ConclusionResults from this study indicated a higher seroprevalence of Mmm in Karamoja region cattle herds. This could be due to the increased frequency of CBPP outbreaks in recent years. To be effective, CBPP vaccination programs should target high risk herds along the international borders and other hotspot areas [e.g., parishes or sub counties] where cattle commingling is high.

Sources apportionments of heavy metal(loid)s in the farmland soils close to industrial parks: Integrated application of positive matrix factorization (PMF) and cadmium isotopic fractionation

Understanding the source identification and distribution of heavy metal(loid)s in soil is essential for risk management. The sources of heavy metal(loid)s in farmland soil, especially in areas with rapid economic development, were complicated and need to be explored urgently. This study combined geographic information system (GIS) mapping, positive matrix factorization (PMF) model and cadmium (Cd) isotope fingerprinting methods to identify heavy metal(loid) sources in a typical town in the economically developed Yangtze River Delta region of China. Cd, As, Cu, Zn, Pb, Ni and Co in different samples were detected. The results showed that Cd was the most severely contaminated element, with an exceedance rate of 78.0 %. GIS mapping results indicated that the hotspot area was located in the northeastern area with prolonged operational histories of electroplating and non-ferrous metal smelting industries. The PMF model analysis also identified emissions from smelting and electroplating enterprises as the main sources of Cd in the soil, counted for 49.28 %, followed by traffic (25.66 %) and agricultural (25.06 %) sources. Through further isotopic analysis, it was found that in soil samples near the industrial park, the contribution of electroplating and non-ferrous metal smelting enterprises to cadmium pollution was significantly higher than other regions. The integrated use of various methodologies allows for precise analysis of sources and input pathways, offering valuable insights for future pollution control and soil remediation endeavors.

Remote Sensing &amp; GIS Integration Bases Evaluation of Ground Water Quality in Telangana State, India

About 85% of drinking water needs in rural and 40% drinking water needs in urban areas are met from groundwater resources in Telangana state. There is a huge demand of ground water for different uses like agriculture, drinking and industrial purposes as the command area is very low in the state and it is evidenced by the fact that around 70% irrigation is dependent on ground water sources as compared to other surface sources like Tanks/Canals/Reservoirs etc. Climate change has affected the hydrological cycle with uncertain and increased variability in rainfall followed by with high rainfall in a short span of time resulting more surface runoff which ultimately decreases there charge to groundwater. Decreased recharge to the groundwater and excess withdrawal of groundwater has accelerated the depletion of groundwater resources there by resulting in stress on groundwater regime in terms of quality as well as quantity. The groundwater quality evaluation of Telangana state is carried out by using legacy quality data (2012-14) collected from Rural Water Supply &amp; Sanitation Department, Government of Telangana. Contamination spread of groundwater is one of the most important concerns that have received attention at regional, local and global levels because of their importance on public health and its further impact in ecosystems. The spatial distribution of chemical parameters like pH, Total Dissolved Solids (TDS), Total Hardness (TH), Total Alkalinity (TA), Fluoride (F), Chloride (Cl), Iron (Fe), Nitrate (NO3) and Sulfate (SO4) are examined with respect to its contamination level. The spatial distribution and concentration of chemical elements is carried out by using spatial interpolation technique namely Inverse Distance Weightage (IDW) method from the point source data. The distribution maps reveal important information to understand the hot spot areas of the groundwater systems and for identification of potential areas for providing safe drinking water supply. Site specific water conservation and artificial recharge measures are needed to be taken up with scientific lines by using Remote Sensing &amp; GIS techniques, for enhancing the groundwater storage and also improving its quality.