scholarly journals Spatial Analysis and Geographic Factors Associated with Cutaneous Leishmaniasis in Southern Iran

2020 ◽  
Author(s):  
Mehdi Sharafi ◽  
Zahra Poormotaseri ◽  
Jalal Karimi ◽  
Shahab Rezaeian ◽  
Seyedeh Leila Dehghani ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Cutaneous Leishmaniasis ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Least Square ◽  
Environmental Data ◽  
Maximum Temperature ◽  
Fars Province ◽  
Disease Pattern ◽  
And Control

Introduction: This study aimed to determine the hotspot areas for Cutaneous Leishmaniasis (CL) in Fasa city and assess the relations between the geographical factors with CL incidence using spatial analysis. Materials and Methods: This ecological study was conducted in Fasa city, data of the CL disease such as the total number of CL cases and the population at risk from 2009 to 2014. Weather conditions' data including the means of temperature, humidity, rainfall, sunny days, rainy days, and evaporation were collected from the weather forecast centers in Fars province. The disease cases' information such as the number of disease cases was collected from all healthcare centers located in Fasa City. Ordinary Least Square (OLS) and Global Moran’s Index (GMI) were used to assess the associations of the various environmental variables with CL incidence and to map clustering of CL cases across the region. Results: The cumulative incidence of CL was 16 per 10,000 populations during a six-year period. The results showed the southern area of Fasa as a hotspot area which is considered as hyperendemic foci for CL. OLS revealed a high incidence of CL in areas with maximum temperature, mean of temperature, mean of evaporation, sunny days and wind velocity. Conclusion: A spatial disease pattern was found in the present study. Hence, substantial consideration to environmental data leads to not only suitable protection against CL but also designing a suitable measure for the prevention and control of the disease.

scholarly journals Spatial analysis of cutaneous leishmaniasis in an endemic area of Iran based on environmental factors

2017 ◽  
Author(s):  
Roghieh Ramezankhani ◽  
Nooshin Sajjadi ◽  
Roya Nezakati Esmaeilzadeh ◽  
Seyed Ali Jozi ◽  
Mohammad Reza Shirzadi
Keyword(s):  
Spatial Analysis ◽  
Cutaneous Leishmaniasis ◽  
Public Health Problem ◽  
Vegetation Coverage ◽  
Climatic Data ◽  
Overlay Analysis ◽  
Topographic Factors ◽  
Isfahan Province ◽  
High Incidence ◽  
Disease Pattern

Leishmaniasis is a parasitic disease caused by different species of protozoan parasites. Cutaneous leishmaniasis (CL) is still a great public health problem in Iran, especially in Isfahan Province. Distribution and abundance of vectors and reservoirs of this disease is affected by different factors such as climatic, socioeconomic and cultural. This study aimed to identify the hotspot areas for CL in Isfahan and assess the relations between the climatic and topographic factors with CL incidence using spatial analysis. We collected data on the total number of CL cases, population at risk, vegetation coverage, altitude and climatic data for each district of the province from 2011 to 2015. Global Moran’s Index was used to map clustering of CL cases across districts and the Getis-Ord (Gi*) statistics was used to determine hotspots areas of the disease in Isfahan. We applied overlay analysis to assess the correlation between the climatic and topographic factors with CL incidence. We found the CL distribution significantly clustered (Moran’s Index=0.17, P<0.001) with the Ardestan and Aran va Bidgol (P<0.01) districts along with the Naein and Natanz districts (P<0.05) to be strong hotspot areas. Overlay analysis revealed a high incidence of CL in areas with relative humidity of 27-30%, mean temperature of 15-19°C, mean precipitation of 5-20 mm, maximum wind speed about 12-16 m/s and an altitude of 600-1,800 m. Our study showed that spatial analysis is a feasible approach for identifying spatial disease pattern and detecting hotspots of this infectious disease.

Clinical, epidemiological and climatic factors related to the occurrence of cutaneous leishmaniasis in an endemic area in northeastern Brazil

2020 ◽  
Author(s):  
R. S. Oliveira ◽  
K. B. A. Pimentel ◽  
M. L. Moura ◽  
C. F. Aragão ◽  
A. S. Guimarães-e-Silva ◽  
...  
Keyword(s):  
Cutaneous Leishmaniasis ◽  
Climatic Factors ◽  
Wide Distribution ◽  
Northeastern Brazil ◽  
Public Health Issue ◽  
Air Humidity ◽  
Disease Occurrence ◽  
Relative Air Humidity ◽  
Age Range ◽  
And Control

Abstract Cutaneous leishmaniasis (CL) is a neglected tropical disease with a wide distribution in the Americas. Brazil is an endemic country and present cases in all states. This study aimed to describe the occurrence, the underlying clinical and epidemiological factors, and the correlation of climatic variables with the frequency of reported CL cases in the municipality of Caxias, state of Maranhão, Brazil. This is a retrospective and descriptive epidemiological study based on data extracted from the Brazilian Information System of Diseases Notification, from 2007 to 2017. Maximum and minimum temperature, precipitation, and relative air humidity data were provided by the Brazilian National Institute of Meteorology. A total of 201 reported autochthonous CL cases were analyzed. The predominance of cases was observed in males (70.1%). The age range between 31 and 60 years old was the most affected, with 96 cases (47.9%). Of the total number of registered cases, 38.8% of the affected individuals were engaged in agriculture-related activities. The georeferenced distribution revealed the heterogeneity of disease occurrence, with cases concentrated in the Western and Southern regions of the municipality. An association was detected between relative air humidity (monthly mean) and the number of CL cases per month (p = 0.04). CL continues to be a concerning public health issue in Caxias. In this context, there is a pressing need to strengthen measures of prevention and control of the disease through the network of health services of the municipality, considering local and regional particularities.

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

scholarly journals An investigation of the effects of environmental and ecologic factors on cutaneous leishmaniasis in the old world: a systematic review study

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Abolfazl Mohammadbeigi ◽  
Salman Khazaei ◽  
Hamidreza Heidari ◽  
Azadeh Asgarian ◽  
Shahram Arsangjang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Environmental Factors ◽  
Land Cover ◽  
Cutaneous Leishmaniasis ◽  
Weather Condition ◽  
Weather Conditions ◽  
Eligibility Criteria ◽  
Screening Process ◽  
Old World ◽  
Review Study

AbstractObjectivesLeishmaniasis is a neglected and widespread parasitic disease that can lead to serious health problems. The current review study aimed to synthesize the relationship between ecologic and environmental factors (e.g., weather conditions, climatology, temperature and topology) and the incidence of cutaneous leishmaniasis (CL) in the Old World.ContentA systematic review was conducted based on English, and Persian articles published from 2015 to 2020 in PubMed/Medline, Science Direct, Web of Science and Google Scholar. Keywords used to search articles were leishmaniasis, environmental factors, weather condition, soil, temperature, land cover, ecologic* and topogr*. All articles were selected and assessed for eligibility according to the titles or abstracts. The quality screening process of articles was carried out by two independent authors. The selected articles were checked according to the inclusion and exclusion criteria.Summary and outlookA total of 827 relevant records in 2015–2020 were searched and after evaluating the articles, 23 articles met the eligibility criteria; finally, 14 full-text articles were included in the systematic review. Two different categories of ecologic/environmental factors (weather conditions, temperature, rainfall/precipitation and humidity) and land characteristics (land cover, slope, elevation and altitude, earthquake and cattle sheds) were the most important factors associated with CL incidence.ConclusionsTemperature and rainfall play an important role in the seasonal cycle of CL as many CL cases occurred in arid and semiarid areas in the Old World. Moreover, given the findings of this study regarding the effect of weather conditions on CL, it can be concluded that designing an early warning system is necessary to predict the incidence of CL based on different weather conditions.

scholarly journals Administration of GnRH at Onset of Estrus, Determined by Automatic Activity Monitoring, to Improve Dairy Cow Fertility during the Summer and Autumn

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2194
Author(s):  
Zvi Roth ◽  
Yaron Z. Kressel ◽  
Yaniv Lavon ◽  
Dorit Kalo ◽  
David Wolfenson
Keyword(s):  
Metabolic Diseases ◽  
Experimental Period ◽  
Visual Observation ◽  
Activity Monitoring ◽  
Least Square ◽  
Gnrh Analogue ◽  
Automatic Activity ◽  
Effect Of Treatment ◽  
Uterine Diseases ◽  
And Control

We examined gonadotropin-releasing hormone (GnRH) administration at onset of estrus (OE), determined by automatic activity monitoring (AAM), to improve fertility of dairy cows during the summer and autumn. The study was performed on two dairy farms in Israel. The OE was determined by AAM recorded every 2 h, and a single im dose of GnRH analogue was administered shortly after OE. Pregnancy was determined by transrectal palpation, 40 to 45 d after artificial insemination (AI). Conception risk was analyzed by the GLIMMIX procedure of SAS. Brief visual observation of behavioral estrus indicated that about three-quarters of the events (n = 40) of visually detected OE occurred within 6 h of AAM-detected OE. Accordingly, the GnRH analogue was administered within 5 h of AAM-detected OE, to overlap with the expected endogenous preovulatory LH surge. Overall, pregnancy per AI (P/AI) was monitored over the entire experimental period (summer and autumn) in 233 first, second or third AI (116 and 117 AI for treated and control groups, respectively). Least square means of P/AI for treated (45.8%) and control (39.4%) groups did not differ, but group-by-season interaction tended to differ (p = 0.07), indicating no effect of treatment in the summer and a marked effect of GnRH treatment (n = 58 AI) compared to controls (n = 59 AI) on P/AI in the autumn (56.6% vs. 28.5%, p < 0.03). During the autumn, GnRH-treated mature cows (second or more lactations), and postpartum cows exhibiting metabolic and uterine diseases, tended to have much larger P/AI than their control counterparts (p = 0.07–0.08). No effect of treatment was recorded in the autumn in first parity cows or in uninfected, healthy cows. In conclusion, administration of GnRH within 5 h of AAM-determined OE improved conception risk in cows during the autumn, particularly in those exhibiting uterine or metabolic diseases postpartum and in mature cows. Incorporation of the proposed GnRH treatment shortly after AAM-detected OE into a synchronization program is suggested, to improve fertility of positively responding subpopulations of cows.

The Message of “APEC Blue” for the Prevention and Control of Urban Air Pollution in China

2016 ◽  
Vol 04 (04) ◽  
pp. 1650027
Author(s):  
Rong ZHU
Keyword(s):  
Air Pollution ◽  
Emergency Response ◽  
Prevention And Control ◽  
Urban Air Pollution ◽  
Pollution Prevention ◽  
Warning System ◽  
Weather Conditions ◽  
Control Measures ◽  
Atmospheric Pollutant ◽  
And Control

Analysis of the meteorological conditions for atmospheric pollutant dispersion before and after the 2014 APEC meeting shows very significant effects of air pollution prevention and control measures on the meeting. It proves that the proper measures to control air pollution in the Beijing-Tianjin-Hebei Region are: establishing a regional emergency response mechanism to reduce emissions in the case of heavy air pollution, strengthening the local emergency response measures for emission reduction, and enhancing the early warning system for weather conditions conducive to heavy air pollution.

Weather effects on intrahabitat movements of the western green lizard, Lacerta bilineata (Daudin, 1802), at its northern distribution range border: a radio-tracking study

2000 ◽  
Vol 78 (10) ◽  
pp. 1831-1839 ◽  
Author(s):  
P Sound ◽  
M Veith
Keyword(s):  
Activity Patterns ◽  
Strong Dependence ◽  
Weather Conditions ◽  
Distribution Range ◽  
Maximum Temperature ◽  
Second Phase ◽  
Northern Distribution ◽  
Radio Transmitters ◽  
Movement Parameters ◽  
Bad Weather

Daily activity patterns of male western green lizards, Lacerta bilineata (Daudin, 1802), at the edge of their northern distribution range in western Germany after the breeding season from June to October were recorded using implanted radio transmitters. Different activity indices discriminating between stimulation, duration, and length of movement were correlated with actual weather conditions (d0) and with weather conditions on the 2 previous days (d-1 and d-2). The lizards' dependence on weather showed two different phases throughout the study period. During the first period and in the period preceding a drastic change of weather in midsummer, weather had no significant influence on movement parameters. After that event, temperatures dropped and a strong dependence on weather of all movement parameters except those indicating displacements became apparent. Thresholds for 50% activity during this second phase were a maximum temperature of 17°C and a minimum humidity of 35%. Two days after periods of bad weather, the influence of weather conditions increased again. This can be explained by physiological deficits that require compensation during the period of marginal weather conditions prior to hibernation. Displacement movements were significantly longer than home-range movements and were neither triggered nor modulated by the weather. They must therefore represent activities such as patrolling territory boundaries.

scholarly journals Spatial analysis of the regional variation of hypertensive disease mortality and its socio-economic correlates in South Korea

2016 ◽  
Vol 11 (2) ◽  
Author(s):  
Seong-Yong Park ◽  
Jin-Mi Kwak ◽  
Eun-Won Seo ◽  
Kwang-Soo Lee
Keyword(s):  
Higher Education ◽  
Spatial Analysis ◽  
South Korea ◽  
Local Governments ◽  
Regional Variation ◽  
Least Square ◽  
Hypertensive Disease ◽  
Significant Positive Association ◽  
Cross Sectional ◽  
Disease Mortality

This paper presents a cross-sectional study based on the cause of death statistics in 2011 extracted from all 229 local governments in South Korea. The standardised hypertensive disease mortality rate (SHDMR) was defined by age- and sex-adjusted mortality by hypertensive diseases distinguished by International Classification of Disease- 10 (ICD-10). Variables taken into account were the number of doctors per 100,000 persons, the proportion with higher education (including university students and high school graduates), the number of recipients of basic livelihood support per 100,000 persons, the annual national health insurance premium per capita and the proportion of persons classified as high-risk drinkers. Ordinary least square (OLS) regression and geographically weighted regression (GWR) were applied to identify the potential associations. The statistical analysis was conducted with SAS ver. 9.3, while ArcGIS ver. 10.0 was utilised for the spatial analysis. The OLS results showed that the number of basic livelihood recipients per 100,000 persons had a significant positive association with the SHDMR, and the proportion with higher education had a significant negative one. GWR coefficients varied depending on region investigated and some regional variables had various directions. GWR showed higher adjusted R2 than that of OLS. It was found that the SHDMR was affected by socio-economic status, but as the effects observed were not consistent in all regions of the country, the development of health policies will need to consider the potential for regional variation.

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

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