BackgroundVisceral Leishmaniasis (VL) is a life threatening neglected infectious disease in the Indian subcontinent, transmitted by the bite of female sand flies. Estimation of the infectivity in the vector population, collected in different seasons, may be useful to better understanding the transmission dynamics of VL as well as to plan vector control measures.MethodologyWe collected sand flies from highly endemic regions of Bihar state, India for one year over three seasons. The species of the sand flies were confirmed by species-specific PCR-RFLP. Leishmania donovani infection was investigated in 1397 female Phlebotomus argentipes using PCR, targeting the Leishmania specific minicircle of the kDNA region. Further, the parasitic load in the infected sand flies was measured using quantitative PCR.ConclusionThough sand flies were most abundant in the rainy season, the highest rate of infection was detected in the winter season with 2.84% sand flies infected followed by the summer and rainy seasons respectively. This study can help in vector elimination programmes and to reduce disease transmission.
BackgroundVisceral Leishmaniasis (VL) is a vector-borne infectious disease, caused by the protozoan Leishmania donovani, which is transmitted by phlebotomine sand flies. In an earlier study in Bihar, India, we found an association between incidence of VL and housing conditions. In the current study we investigated the influence of housing structure and conditions in and around the house on the indoor abundance of Phlebotomus argentipes, the vector of VL in this area.MethodsIn each of 50 study villages in Muzaffarpur district, we randomly selected 10 houses. Light traps were installed in each house for one night during three annual peaks of sand fly density over two successive years. Sand flies captured were morphologically identified and segregated by species, sex and feeding status. Data on housing conditions and socio-economic status were also collected. We fitted a linear mixed-effects regression model with log-transformed P. argentipes counts as outcome variable and village as random effect.Results P. argentipes was found in all but four of the 500 households. There was considerable variability between the years and the seasons. On bivariate analysis, housing structure, dampness of the floor, keeping animals inside, presence of animal dung around the house, and socio-economic status were all significantly associated with sand fly density. Highest sand fly densities were observed in thatched houses. In the multivariate model only the housing structure and socio-economic status remained significant.ConclusionsBetter housing conditions are associated with lower sand fly densities, independent of other socio-economic conditions. However, in this area in Bihar even in the better-built houses sand flies are present.
The main purpose of this study was to predict the long jump performance on the basis of speed, agility, height and weight of male athletes. 46 male athletes were participated in present study (mean ± SD; 22.28 ± 1.3770 years). The selected athletes were measured of their speed by 50m dash sprint test (sec.), agility measured by 4 x 10m shuttle run test (sec.) and long jump performance measured by long jump (meter). Pearson product-moment correlations revealed a significant negative correlation of Long Jump performance with speed (r = -0.813, p < 0.05), Agility (r = -0.702, p < 0.05) and weight (r = -0.343, p < 0.05). Multiple correlations revealed that joint contribution of all independent variables to estimating Long Jump performance (R = .847, R 2 =.717), which impales that 71.7% of Long Jump Performance is obtained by these variables (Weight, Height, Agility and Speed). The regression analysis (enter method) outcomes proved that long jump performance can be determined by selected independent variables (F=25.933, p<0.05). Based on the result of present study suitable formula was determined [Long Jump performance = 5.356 -.283 (Speed) -.102 (Agility) + .021 (Height) -.019 (Weight)]. It was concluded that the formula suggested in this study, can be used to determine the long jump performance of male athletes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.