Spatial modeling of cutaneous leishmaniasis in Iranian army units during 2014–2017 using a hierarchical Bayesian method and the spatial scan statistic / 한국역학회지

OBJECTIVES@#This study aimed to map the incidence of cutaneous leishmaniasis (CL) in Iranian army units (IAUs) and to identify possible spatial clusters.@*METHODS@#This ecological study investigated incident cases of CL between 2014 and 2017. CL data were extracted from the CL registry maintained by the deputy of health of AJA University of Medical Sciences. The standardized incidence ratio (SIR) of CL was computed with a Besag, York, and Mollié model. The purely spatial scan statistic was employed to detect the most likely high- and low-rate clusters and to obtain the observed-to-expected (O/E) ratio for each detected cluster. The statistical significance of the clusters was assessed using the log likelihood ratio (LLR) test and Monte Carlo hypothesis testing.@*RESULTS@#A total of 1,144 new CL cases occurred in IAUs from 2014 to 2017, with an incidence rate of 260 per 100,000. Isfahan and Khuzestan Provinces were found to have more CL cases than expected in all studied years (SIR>1), while Kermanshah, Kerman, and Fars Provinces were observed to have been high-risk areas in only some years of the study period. The most significant CL cluster was in Kermanshah Province (O/E, 67.88; LLR, 1,200.62; p < 0.001), followed by clusters in Isfahan Province (O/E, 6.02; LLR, 513.24; p < 0.001) and Khuzestan Province (O/E, 2.35; LLR, 73.71; p < 0.001), while low-rate clusters were located in the northeast areas, including Razavi Khorasan, North Khorasan, Semnan, and Golestan Provinces (O/E, 0.03; LLR, 95.11; p < 0.001).@*CONCLUSIONS@#This study identified high-risk areas for CL. These findings have public health implications and should be considered when planning control interventions among IAUs.

Spatial modeling of cutaneous leishmaniasis in Iranian army units during 2014–2017 using a hierarchical Bayesian method and the spatial scan statistic / 한국역학회지

OBJECTIVES: This study aimed to map the incidence of cutaneous leishmaniasis (CL) in Iranian army units (IAUs) and to identify possible spatial clusters.METHODS: This ecological study investigated incident cases of CL between 2014 and 2017. CL data were extracted from the CL registry maintained by the deputy of health of AJA University of Medical Sciences. The standardized incidence ratio (SIR) of CL was computed with a Besag, York, and Mollié model. The purely spatial scan statistic was employed to detect the most likely high- and low-rate clusters and to obtain the observed-to-expected (O/E) ratio for each detected cluster. The statistical significance of the clusters was assessed using the log likelihood ratio (LLR) test and Monte Carlo hypothesis testing.RESULTS: A total of 1,144 new CL cases occurred in IAUs from 2014 to 2017, with an incidence rate of 260 per 100,000. Isfahan and Khuzestan Provinces were found to have more CL cases than expected in all studied years (SIR>1), while Kermanshah, Kerman, and Fars Provinces were observed to have been high-risk areas in only some years of the study period. The most significant CL cluster was in Kermanshah Province (O/E, 67.88; LLR, 1,200.62; p < 0.001), followed by clusters in Isfahan Province (O/E, 6.02; LLR, 513.24; p < 0.001) and Khuzestan Province (O/E, 2.35; LLR, 73.71; p < 0.001), while low-rate clusters were located in the northeast areas, including Razavi Khorasan, North Khorasan, Semnan, and Golestan Provinces (O/E, 0.03; LLR, 95.11; p < 0.001).CONCLUSIONS: This study identified high-risk areas for CL. These findings have public health implications and should be considered when planning control interventions among IAUs.

Spatial modeling of cutaneous leishmaniasis in Iranian army units during 2014–2017 using a hierarchical Bayesian method and the spatial scan statistic / 한국역학회지

OBJECTIVES: This study aimed to map the incidence of cutaneous leishmaniasis (CL) in Iranian army units (IAUs) and to identify possible spatial clusters. METHODS: This ecological study investigated incident cases of CL between 2014 and 2017. CL data were extracted from the CL registry maintained by the deputy of health of AJA University of Medical Sciences. The standardized incidence ratio (SIR) of CL was computed with a Besag, York, and Mollié model. The purely spatial scan statistic was employed to detect the most likely high- and low-rate clusters and to obtain the observed-to-expected (O/E) ratio for each detected cluster. The statistical significance of the clusters was assessed using the log likelihood ratio (LLR) test and Monte Carlo hypothesis testing. RESULTS: A total of 1,144 new CL cases occurred in IAUs from 2014 to 2017, with an incidence rate of 260 per 100,000. Isfahan and Khuzestan Provinces were found to have more CL cases than expected in all studied years (SIR>1), while Kermanshah, Kerman, and Fars Provinces were observed to have been high-risk areas in only some years of the study period. The most significant CL cluster was in Kermanshah Province (O/E, 67.88; LLR, 1,200.62; p < 0.001), followed by clusters in Isfahan Province (O/E, 6.02; LLR, 513.24; p < 0.001) and Khuzestan Province (O/E, 2.35; LLR, 73.71; p < 0.001), while low-rate clusters were located in the northeast areas, including Razavi Khorasan, North Khorasan, Semnan, and Golestan Provinces (O/E, 0.03; LLR, 95.11; p < 0.001). CONCLUSIONS: This study identified high-risk areas for CL. These findings have public health implications and should be considered when planning control interventions among IAUs.

Spatial outline of malaria transmission in Iran

OBJECTIVE@#To conduct for modeling spatial distribution of malaria transmission in Iran.@*METHODS@#Records of all malaria cases from the period 2008-2010 in Iran were retrieved for malaria control department, MOH&ME. Metrological data including annual rainfall, maximum and minimum temperature, relative humidity, altitude, demographic, districts border shapefiles, and NDVI images received from Iranian Climatologic Research Center. Data arranged in ArcGIS.@*RESULTS@#99.65% of malaria transmission cases were focused in southeast part of Iran. These transmissions had statistically correlation with altitude (650 m), maximum (30 °C), minimum (20 °C) and average temperature (25.3 °C). Statistical correlation and overall relationship between NDVI (118.81), relative humidity (⩾45%) and rainfall in southeast area was defined and explained in this study.@*CONCLUSIONS@#According to ecological condition and mentioned cut-off points, predictive map was generated using cokriging method.

Effects of tyrode's solution osmolarities and milk on bull sperm storage above zero temperatures

Control of the medium osmolarity and temperature during long or short time sperm manipulation is essential. The objectives of the present study were to find the effects of different osmolarities of modified Tyrode's solution and milk on the bull sperm during incubation at above zero temperatures. Semen samples were collected twice from five Najdi bull. Centrifuged and most parts of seminal plasma were removed. First experiment: The concentrated semen were splited into nine aliquots to incubate in three different osmolarities [200, 300 and 400 mOsm] at three temperatures [5, 25 and 39°C] for 15 and 60 min of incubation. Second experiment: The semen samples were splited, mixed with the same volume of whole cow milk [5 and 25°C] and milk with 7% glycerol [5°C] and incubated for 15 and 60 min. Sperm motility severely affected [p<0.05] by incubation at low ionic tension [200 mOsm/l] especially at low temperature [5°C]. The impact of low osmolarity on sperm viability can reduce by increasing the incubation temperature to 39°C. The decreased sperm motility, which was induced by lowering osmolarity, was not improved [p>0.05] by increasing temperature during 1 h of incubation. Milk can protect the sperm viability and motility at cool conditions and there is no beneficial effect of glycerol in combination of milk on sperm incubation at above zero temperatures [p<0.05]. Iso- and hyper-osmotic solutions protect bull sperm motility and viability at 25 and 39°C, while milk can be used for protecting sperm at 5°C