58 research outputs found

    Social and demographic factors associated with morbidities in young children in Egypt: A Bayesian geo-additive semi-parametric multinomial model.

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    Globally, the burden of mortality in children, especially in poor developing countries, is alarming and has precipitated concern and calls for concerted efforts in combating such health problems. Examples of diseases that contribute to this burden of mortality include diarrhoea, cough, fever, and the overlap between these illnesses, causing childhood morbidity and mortality. Methods: To gain insight into these health issues, we employed the 2008 Demographic and Health Survey Data of Egypt, which recorded details from 10,872 children under five. This data focused on the demographic and socio-economic characteristics of household members. We applied a Bayesian multinomial model to assess the area-specific spatial effects and risk factors of co-morbidity of fever, diarrhoea and cough for children under the age of five. Results: The results showed that children under 20 months of age were more likely to have the three diseases (OR: 6.8; 95% CI: 4.6-10.2) than children between 20 and 40 months (OR: 2.14; 95% CI: 1.38-3.3). In multivariate Bayesian geo-additive models, the children of mothers who were over 20 years of age were more likely to have only cough (OR: 1.2; 95% 2 CI: 0.9-1.5) and only fever (OR: 1.2; 95% CI: 0.91-1.51) compared with their counterparts. Spatial results showed that the North-eastern region of Egypt has a higher incidence than most of other regions. Conclusions: This study showed geographic patterns of Egyptian governorates in the combined prevalence of morbidity among Egyptian children. It is obvious that the Nile Delta, Upper Egypt, and south-eastern Egypt have high rates of diseases and are more affected. Therefore, more attention is needed in these areas. Funding: The authors have no support or funding to report. Competing Interests: The authors have declared that no competing interests exist

    Geo-additive modelling of malaria in Burundi

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    Abstract Background Malaria is a major public health issue in Burundi in terms of both morbidity and mortality, with around 2.5 million clinical cases and more than 15,000 deaths each year. It is still the single main cause of mortality in pregnant women and children below five years of age. Because of the severe health and economic burden of malaria, there is still a growing need for methods that will help to understand the influencing factors. Several studies/researches have been done on the subject yielding different results as which factors are most responsible for the increase in malaria transmission. This paper considers the modelling of the dependence of malaria cases on spatial determinants and climatic covariates including rainfall, temperature and humidity in Burundi. Methods The analysis carried out in this work exploits real monthly data collected in the area of Burundi over 12 years (1996-2007). Semi-parametric regression models are used. The spatial analysis is based on a geo-additive model using provinces as the geographic units of study. The spatial effect is split into structured (correlated) and unstructured (uncorrelated) components. Inference is fully Bayesian and uses Markov chain Monte Carlo techniques. The effects of the continuous covariates are modelled by cubic p-splines with 20 equidistant knots and second order random walk penalty. For the spatially correlated effect, Markov random field prior is chosen. The spatially uncorrelated effects are assumed to be i.i.d. Gaussian. The effects of climatic covariates and the effects of other spatial determinants are estimated simultaneously in a unified regression framework. Results The results obtained from the proposed model suggest that although malaria incidence in a given month is strongly positively associated with the minimum temperature of the previous months, regional patterns of malaria that are related to factors other than climatic variables have been identified, without being able to explain them. Conclusions In this paper, semiparametric models are used to model the effects of both climatic covariates and spatial effects on malaria distribution in Burundi. The results obtained from the proposed models suggest a strong positive association between malaria incidence in a given month and the minimum temperature of the previous month. From the spatial effects, important spatial patterns of malaria that are related to factors other than climatic variables are identified. Potential explanations (factors) could be related to socio-economic conditions, food shortage, limited access to health care service, precarious housing, promiscuity, poor hygienic conditions, limited access to drinking water, land use (rice paddies for example), displacement of the population (due to armed conflicts).</p

    Dynamic early identification of hip replacement implants with high revision rates. Study based on the NJR data from UK during 2004-2012

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    BACKGROUND: Hip replacement and hip resurfacing are common surgical procedures with an estimated risk of revision of 4% over 10 year period. Approximately 58% of hip replacements will last 25 years. Some implants have higher revision rates and early identification of poorly performing hip replacement implant brands and cup/head brand combinations is vital. AIMS: Development of a dynamic monitoring method for the revision rates of hip implants. METHODS: Data on the outcomes following the hip replacement surgery between 2004 and 2012 was obtained from the National Joint Register (NJR) in the UK. A novel dynamic algorithm based on the CUmulative SUM (CUSUM) methodology with adjustment for casemix and random frailty for an operating unit was developed and implemented to monitor the revision rates over time. The Benjamini-Hochberg FDR method was used to adjust for multiple testing of numerous hip replacement implant brands and cup/ head combinations at each time point. RESULTS: Three poorly performing cup brands and two cup/ head brand combinations have been detected. Wright Medical UK Ltd Conserve Plus Resurfacing Cup (cup o), DePuy ASR Resurfacing Cup (cup e), and Endo Plus (UK) Limited EP-Fit Plus Polyethylene cup (cup g) showed stable multiple alarms over the period of a year or longer. An addition of a random frailty term did not change the list of underperforming components. The model with added random effect was more conservative, showing less and more delayed alarms. CONCLUSIONS: Our new algorithm is an efficient method for early detection of poorly performing components in hip replacement surgery. It can also be used for similar tasks of dynamic quality monitoring in healthcare

    Regional inequalities in under-5 mortality in Nigeria: a population-based analysis of individual- and community-level determinants

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    <p>Abstract</p> <p>Background</p> <p>Regions with geographically diverse ecology and socioeconomic circumstances may have different disease exposures and child health outcomes. This study assessed variations in the risks of death in children under age 5 across regions of Nigeria and determined characteristics at the individual and community levels that explain possible variations among regions.</p> <p>Methods</p> <p>Multilevel Cox proportional hazards analysis was performed using a nationally representative sample of 6,029 children from 2,735 mothers aged 15-49 years and nested within 365 communities from the 2003 Nigeria Demographic and Health Survey. Hazard ratios (HR) with 95% confidence intervals (CI) were used to express measures of association among the characteristics. Variance partition coefficients and Wald statistic were used to express measures of variation.</p> <p>Results</p> <p>Patterns of under-5 mortality cluster within families and communities. The risks of under-5 deaths were significantly higher for children of mothers residing in the South South (Niger Delta) region (HR: 1.30; 95% CI: 1.76-2.20) and children of mothers residing in communities with a low proportion of mothers attending prenatal care by a doctor (HR: 1.36; 95% CI: 1.15-1.86). In addition, the cross-level interaction between mothers' education and community prenatal care by a doctor was associated with a more than 40% higher risk of dying (HR: 1.41; 95% CI: 1.21-1.78).</p> <p>Conclusion</p> <p>The findings suggest the need to differentially focus on community-level interventions aimed at increasing maternal and child health care utilization and improving the socioeconomic position of mothers, especially in disadvantaged regions such as the South South (Niger Delta) region. Further studies on community-levels determinants of under-5 mortality are needed.</p

    Taenia solium Infections in a Rural Area of Eastern Zambia-A Community Based Study

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    Taenia solium taeniosis/cysticercosis is a zoonotic infection endemic in many developing countries, with humans as the definitive host (taeniosis) and pigs and humans as the intermediate hosts (cysticercosis). When humans act as the intermediate host, the result can be neurocysticercosis, which is associated with acquired epilepsy, considerable morbidity and even mortality. In Africa, most studies have been carried out in pigs with little or no data in humans available. In this human study, conducted in a rural community in Eastern Zambia, prevalences for taeniosis and cysticercosis were determined at 6.3% and 5.8% respectively, indicating the hyperendemicity of the area. Cysticercosis infection was strongly related with age, with a significant increase in prevalence occurring in individuals from the age of 30 onward. A collected tapeworm was confirmed to be T. solium. Risk factors associated with the transmission and maintenance of the parasite such as free roaming pigs, households without latrines, backyard slaughter of pigs without inspection and consumption of undercooked pork were also present. The findings of this work have identified the need for further research in the transmission dynamics and the burden that this infection has on the resources of poor local people

    Under-Five Mortality in High Focus States in India: A District Level Geospatial Analysis

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    <div><h3>Background</h3><p>This paper examines if, when controlling for biophysical and geographical variables (including rainfall, productivity of agricultural lands, topography/temperature, and market access through road networks), socioeconomic and health care indicators help to explain variations in the under-five mortality rate across districts from nine high focus states in India. The literature on this subject is inconclusive because the survey data, upon which most studies of child mortality rely, rarely include variables that measure these factors. This paper introduces these variables into an analysis of 284 districts from nine high focus states in India.</p> <h3>Methodology/Principal Findings</h3><p>Information on the mortality indicator was accessed from the recently conducted Annual Health Survey of 2011 and other socioeconomic and geographic variables from Census 2011, District Level Household and Facility Survey (2007–08), Department of Economics and Statistics Divisions of the concerned states. Displaying high spatial dependence (spatial autocorrelation) in the mortality indicator (outcome variable) and its possible predictors used in the analysis, the paper uses the Spatial-Error Model in an effort to negate or reduce the spatial dependence in model parameters. The results evince that the coverage gap index (a mixed indicator of district wise coverage of reproductive and child health services), female literacy, urbanization, economic status, the number of newborn care provided in Primary Health Centers in the district transpired as significant correlates of under-five mortality in the nine high focus states in India. The study identifies three clusters with high under-five mortality rate including 30 districts, and advocates urgent attention.</p> <h3>Conclusion</h3><p>Even after controlling the possible biophysical and geographical variables, the study reveals that the health program initiatives have a major role to play in reducing under-five mortality rate in the high focus states in India.</p> </div
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