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Questionnaire regarding Portulacaceae loved ones flora within Taif, Saudi Arabic.
Dengue is the worldwide most important mosquito-borne viral disease in humans. A large dengue outbreak occurred in Chiang Mai, Thailand in 2013. The aims of this study were to describe the epidemiology of this outbreak and determine the spatio-temporal pattern in the sub-district with the highest number of dengue cases. Data on patients, including date of illness, were obtained from the Chiang Mai Provincial Public Health Center and analyzed descriptively using R statistical software. The geographic location of patients' residences was determined from available geographical information databases supplemented with coordinated data collection in the field. A space-time permutation model from SaTScan™ was used to determine disease clusters corresponding to space and time. Results showed that Muang District, the centre of the province, had a higher number of cases than the other 25 districts. The Suthep subdistrict, part of Muang District, had most of the patients 625 subjects distributed between 213 residences. The space-time analysis identified a primary cluster and 7 secondary clusters in different time periods. The primary cluster had 128 patients in a period of approximately 3 months. The number of patients in the secondary clusters ranged between 7 and 65. Most of the clusters occurred in densely populated areas during June and July (the rainy season). The finding from this study may support health agencies to plan surveillance campaigns for people at specified local areas with a high incidence of the disease.Cysticercosis remains a public health problem in China, with disease prevalence attributed to poor socio-economic and public health conditions. This parasitic food-borne disease was prioritized for effective control following implementation of the national surveys on parasitic diseases carried out in China. We predicted the cysticercosis distribution in Dali, Yunnan Province by assessing spatio-temporal distribution characteristics between 2000 and 2014 to better understand the trend of the disease incidence. A database of cysticercosis cases was provided by the clinical department at the Dali Prefectural Institute of Research and Control of Schistosomiasis. Describing the epidemiological features of cysticercosis and analyzing its spatiotemporal distribution of cases using mapping, scanning and spatial autocorrelation analysis, our findings found a total of 3,347 patients with cysticercosis infection, neurocysticercosis in particular. Cysticercosis prevalence was the highest among young and middle-aged male farmers, and also predominant among the Bai nationality. Three aggregation areas were identified during the period 2000-2014. Hotspot analysis implicated Dali City, Eryuan County and Yangbi County between 2000 and 2007, with areas gradually shifting towards the western and northern parts of the province. The hotspot map indicated that Eryuan County was a constant problem with respect to cysticercosis. The results indicated three cysticercosis clusters in Dali that could be attributed to environmental factors and unhealthy lifestyles. Multi-sectoral control initiatives are, therefore, recommended in these areas to effectively control and prevent cysticercosis among the population.Malaria remains a leading cause of morbidity and mortality among children in Nigeria less than 5 years old (under-5). This study utilized nationally representative secondary data extracted from the 2015 Nigeria Malaria Indicator Survey (NMIS) to investigate the spatial variability in malaria distribution in those under- 5 and to explore the influence of socioeconomic and demographic factors on malaria prevalence in this population group. To account for spatial correlation, a Spatially Generalized Linear Mixed Model (SGMM) was employed and predictive risk maps was developed using Kriging. Highly significant spatial variability in under-5 malaria distribution was observed (P less then 0.0001) with a higher likelihood of malaria prevalence in this group in the Northwest and North-east of the country. The number of malaria infections increased with age, children aged between 49-59 months were found to be at a higher risk (Odds Ratio=4.680, 95% CI=3.674 to 5.961 at P less then 0.0001). After accounting for spatial correlation, we observed a strong significant association between the non-availability or non-use of mosquito bed-nets, low household socioeconomic status, low level of mother's educational attainment, family size, anaemia prevalence, rural type of residence and under-5 malaria prevalence. Faced with a high rate of under-5 mortality due to malaria in Nigeria, targeted interventions (which requires the identification of the child's location) may reduce malaria prevalence, and we conclude that socioeconomic impediments need to be confronted to reduce the burden of childhood malaria infection.Neglected tropical diseases characterized by skin lesions are highly endemic in the state of Mato Grosso, Brazil. We analyzed the spatial distribution of leprosy and Cutaneous Leishmaniasis (CL) and identified the degree of overlap in their distribution. All new cases of leprosy and CL reported between 2008 and 2017 through the national reporting system were included in the study. Bexotegrast solubility dmso Scan statistics together with univariate Global and Local Moran's I were employed to identify clusters and spatial autocorrelation for each disease, with the spatial correlation between leprosy and CL measured by bivariate Global and Local Moran's I. Finally, we evaluated the demographic characteristics of the patients. The number of leprosy (N = 28,204) and CL (N = 24,771) cases in Mato Grosso and the highly smoothed detection coefficients indicated hyperendemicity and spatial distribution heterogeneity. Scan statistics demonstrated overlap of high-risk clusters for leprosy (RR = 2.0; P less then 0.001) and CL (RR = 4.0; P less then 0.001) in the North and Northeast mesoregions. Global Moran's I revealed a spatial autocorrelation for leprosy (0.228; P = 0.001) and CL (0.311; P = 0.001) and a correlation between them (0.164; P = 0.001). Both diseases were found to be concentrated in urban areas among men aged 31-60 years, of brown-skinned ethnicity and with a low educational level. Our findings indicate a need for developing integrated and spatially as well as socio-demographically targeted public health policies.
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