Using the hierarchical ordinal regression model to analyse the intensity of urinary schistosomiasis infection in school children in Lusaka Province,Zambia

Background:Urinary schistosomiasis has been a major public health problem in Zambia for many years.However,the disease profile may vary in different locale due to the changing ecosystem that contributes to the risk of acquiring the disease.The objective of this study was to quantify risk factors associated with the intensity of urinary schistosomiasis infection in school children in Lusaka Province,Zambia,in order to better understand local transmission.Methods:Data were obtained from 1912 school children,in 20 communities,in the districts of Luangwa and Kafue in Lusaka Province.Both individual-and community-level covariates were incorporated into an ordinal logistic regression model to predict the probability of an infection being a certain intensity in a three-category outcome response:0=no infection,1=light infection,and 2=moderate/heavy infection.Random effects were introduced to capture unobserved heterogeneity.Results:Overall,the risk of urinary schistosomiasis was strongly associated with age,altitude at which the child lived,and sex.Weak associations were observed with the normalized difference vegetation index,maximum temperature,and snail abundance.Detailed analysis indicated that the association between infection intensities and age and altitude were category-specific.Particularly,infection intensity was lower in children aged between 5 and 9 years compared to those aged 10 to 15 years(OR=0.72,95%CI=0.51-0.99).However,the age-specific risk changed at different levels of infection,such that when comparing children with light infection to those who were not infected,age was associated with a lower odds(category 1 vs category 0:OR=0.71,95%CI:0.50-0.99),yet such a relation was not significant when considering children who were moderately or heavily infected compared to those with a light or no infection(category 2 vs category 0:OR=0.96,95%CI:0.45-1.64).Overall,we observed that children living in the valley were less likely to acquire urinary schistosomiasis compared to those living in plateau areas(OR=0.48,95%CI:0.16-0.71).However,category-specific effects showed no significant association in category 1(light infection),whereas in category 2(moderate/high infection),the risk was still significantly lower for those living in the valley compared to those living in plateau areas(OR=0.18,95%CI:0.04-0.75).Conclusions:This study demonstrates the importance of understanding the dynamics and heterogeneity of infection in control efforts,and further suggests that apart from the well-researched factors of Schistosoma intensity,various other factors influence transmission.Control programmes need to take into consideration the varying infection intensities of the disease so that effective interventions can be designed.

Does Hospital Ownership Influence Hand Hygiene Compliance?

The issue as to whether hospital ownership has an impact on the quality of care has long been a serious concern. Hand hygiene（HH） compliance is regarded as an important indicator of the quality of care in the control of hospital-acquired infections. However, little information is available on whether hospital ownership influences HH compliance. In this study, of 229 hospitals selected from Hubei province in China, 152 were public and 77 were private hospitals. A total of 23 652 healthcare workers（HCWs） were surveyed, using a convenience sampling. HH compliance, the WHO＇s ＂My Five Moments for hand hygiene＂（5 MHH）, among HCWs, together with the factors of hospital ownership, training frequency, bed occupancy rates, etc. were collected. Univariate analysis and ordinal logistic regression analysis were used to analyze factors affecting HH compliance. Overall, HH compliance rates were 67% and 79% for public and private hospitals, respectively. The HH compliance rates of HCWs and 5 MHH were between 55% and 95%, and influenced by hospital ownership（P〈0.05）, excluding compliance rate at the moment after body fluid exposure, and other influence factors included training frequency and bed occupancy rate（P〈0.05）. HH compliance is better in private than in public hospitals. Hospital ownership is a significant factor affecting HH compliance, in addition to training frequency and bed occupancy rate.

Stochastic Modeling for Coliform Count Assessment in Ground Water

Stochastic models are derived to estimate the level of coliform count in terms of MPN index, one of the most important water quality characteristic in ground water based on a set of water source location and soil characteristics. The study is based on about twenty location and soil characteristics, majority of them are observed through laboratory analysis of soil and water samples collected from nearly thee hundred locations of drinking water sources, wells and bore wells selected at random from the district of Kasaragod. The water contamination in wells are found to be relatively more as compared to bore wells. The study reveals that only 7 % of the wells and 40 o~ of the bore wells of the district are within the permissible limit of WHO standard of drinking water quality. The level of contamination is very high in the hospital premises and is very low in the forest area. Two separate multiple ordinal logistic regression models are developed to predict the level of coliform count, one for well and the other for bore well. The significant feature of this study is that in addition to scientifically proving the dependence of the water quality on the distances from waste disposal area and septic tanks etc., it highlights the dependence of two other very significant soil characteristics, the soil organic carbon and soil porosity. The models enable to predict the quality of water in a location based on the set of soil and location characteristics. One of the important uses of the model is in fixing safe locations for waste dump area, septic tank, digging well etc. in town planning, designing residential layouts, industrial layouts, hospital/hostel construction etc. This is the first ever study to describe the ground water quality in terms of the location and soil characteristics.