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

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

Seasonal and geographic differences in treatment-seeking and household cost of febrile illness among children in Malawi

BACKGROUND: Households in malaria endemic countries experience considerable costs in accessing formal health facilities because of childhood malaria. The Ministry of Health in Malawi has defined certain villages as hard-to-reach on the basis of either their distance from health facilities or inaccessibility. Some of these villages have been assigned a community health worker, responsible for referring febrile children to a health facility. Health facility utilization and household costs of attending a health facility were compared between individuals living near the district hospital and those in hard-to-reach villages. METHODS: Two cross-sectional household surveys were conducted in the Chikhwawa district of Malawi; one during each of the wet and dry seasons. Half the participating villages were located near the hospital, the others were in areas defined as hard-to-reach. Data were collected on attendance to formal health facilities and economic costs incurred due to recent childhood febrile illness. RESULTS: Those living in hard-to-reach villages were less likely to attend a formal health facility compared to those living near the hospital (Dry season: OR 0.35, 95%CI0.18-0.67; Wet season: OR 0.46, 95%CI0.27-0.80). Analyses including community health workers (CHW) as a source of formal health-care decreased the strength of this relationship, and suggested that consulting a CHW may reduce attendance at health facilities, even if indicated. Although those in hard-to-reach villages were still less likely to attend in both the dry (OR 0.53, 95%CI 0.25-1.11) and wet (OR 0.60, 95%CI 0.37-0.98) seasons. Household costs for those who attended a health facility were greater for those in HTR villages (Dry: USD5.24; Wet: USD5.60) than for those living near the district hospital (Dry: USD3.45; Wet: USD4.46). CONCLUSION: Those living in hard-to-reach areas were less likely to attend a health facility for a childhood febrile event and experienced greater associated household costs. Consulting CHWs was infrequent, but appeared to reduce attendance at a health facility, even when indicated. Health service planners must consider geographic and financial barriers to accessing public health facilities in designing appropriate interventions

Spatial prediction of malaria prevalence in an endemic area of Bangladesh

<p>Abstract</p> <p>Background</p> <p>Malaria is a major public health burden in Southeastern Bangladesh, particularly in the Chittagong Hill Tracts region. Malaria is endemic in 13 districts of Bangladesh and the highest prevalence occurs in Khagrachari (15.47%).</p> <p>Methods</p> <p>A risk map was developed and geographic risk factors identified using a Bayesian approach. The Bayesian geostatistical model was developed from previously identified individual and environmental covariates (p < 0.2; age, different forest types, elevation and economic status) for malaria prevalence using WinBUGS 1.4. Spatial correlation was estimated within a Bayesian framework based on a geostatistical model. The infection status (positives and negatives) was modeled using a Bernoulli distribution. Maps of the posterior distributions of predicted prevalence were developed in geographic information system (GIS).</p> <p>Results</p> <p>Predicted high prevalence areas were located along the north-eastern areas, and central part of the study area. Low to moderate prevalence areas were predicted in the southwestern, southeastern and central regions. Individual age and nearness to fragmented forest were associated with malaria prevalence after adjusting the spatial auto-correlation.</p> <p>Conclusion</p> <p>A Bayesian analytical approach using multiple enabling technologies (geographic information systems, global positioning systems, and remote sensing) provide a strategy to characterize spatial heterogeneity in malaria risk at a fine scale. Even in the most hyper endemic region of Bangladesh there is substantial spatial heterogeneity in risk. Areas that are predicted to be at high risk, based on the environment but that have not been reached by surveys are identified.</p

Patterns of malaria-related hospital admissions and mortality among Malawian children: an example of spatial modelling of hospital register data

BACKGROUND: Malaria is a leading cause of hospitalization and in-hospital mortality among children in Africa, yet, few studies have described the spatial distribution of the two outcomes. Here spatial regression models were applied, aimed at quantifying spatial variation and risk factors associated with malaria hospitalization and in-hospital mortality. METHODS: Paediatric ward register data from Zomba district, Malawi, between 2002 and 2003 were used, as a case study. Two spatial models were developed. The first was a Poisson model applied to analyse hospitalization and minimum mortality rates, with age and sex as covariates. The second was a logistic model applied to individual level data to analyse case-fatality rate, adjusting for individual covariates. RESULTS AND CONCLUSION: Rates of malaria hospitalization and in-hospital mortality decreased with age. Case fatality rate was associated with distance, age, wet season and increased if the patient was referred to the hospital. Furthermore, death rate was high on first day, followed by relatively low rate as length of hospital stay increased. Both outcomes showed substantial spatial heterogeneity, which may be attributed to the varying determinants of malaria risk, health services availability and accessibility, and health seeking behaviour. The increased risk of mortality of children referred from primary health facilities may imply inadequate care being available at the referring facility, or the referring facility are referring the more severe cases which are expected to have a higher case fatality rate. Improved prognosis as the length of hospital stay increased suggest that appropriate care when available can save lives. Reducing malaria burden may require integrated strategies encompassing availability of adequate care at primary facilities, introducing home or community case management as well as encouraging early referral, and reinforcing interventions to interrupt malaria transmission

Mapping the Risk of Anaemia in Preschool-Age Children: The Contribution of Malnutrition, Malaria, and Helminth Infections in West Africa

Ricardo Soares Magalhães and colleagues used national cross-sectional household-based demographic health surveys to map the distribution of anemia risk in preschool children in Burkina Faso, Ghana, and Mali

Geographical disparities in core population coverage indicators for roll back malaria in Malawi

BACKGROUND: Implementation of known effective interventions would necessitate the reduction of malaria burden by half by the year 2010. Identifying geographical disparities of coverage of these interventions at small area level is useful to inform where greatest scaling-up efforts should be concentrated. They also provide baseline data against which future scaling-up of interventions can be compared. However, population data are not always available at local level. This study applied spatial smoothing methods to generate maps at subdistrict level in Malawi to serve such purposes. METHODS: Data for the following responses from the 2000 Malawi Demographic and Health Survey (DHS) were aggregated at subdistrict level: (1) households possessing at least one bednet; (2) children under 5 years who slept under a bednet the night before the survey; (3) bednets retreated with insecticide within past 6-12 months preceding the survey; (4) children under 5 who had fever two weeks before the survey and received treatment within 24 hours from the onset of fever; and (5) women who received intermittent preventive treatment of malaria during their last pregnancy. Each response was geographically smoothed at subdistrict level by applying conditional autoregressive models using Markov Chain Monte Carlo simulation techniques. RESULTS: The underlying geographical patterns of coverage of indicators were more clear in the smoothed maps than in the original unsmoothed maps, with relatively high coverage in urban areas than in rural areas for all indicators. The percentage of households possessing at least one bednet was 19% (95% credible interval (CI): 16-21%), with 9% (95% CI: 7-11%) of children sleeping under a net, while 18% (95% CI: 16-19%) of households had retreated their nets within past 12 months prior to the survey. The northern region and lakeshore areas had high bednet coverage, but low usage and re-treatment rates. Coverage rate of children who received antimalarial treatment within 24 hours after onset of fever was consistently low for most parts of the country, with mean coverage of 4.8% (95% CI: 4.5-5.0%). About 48% (95% CI: 47-50%) of women received antimalarial prophylaxis during their pregnancy, with highest rates in the southern and northern areas. CONCLUSION: The striking geographical patterns, for example between predominantly urban and rural areas, may reflect spatial differences in provider compliance or coverage, and can partly be explained by socio-economic and cultural differences. The wide gap between high bed net coverage and low retreatment rates may reflect variation in perceptions about malaria, which may be addressed by implementing information, education and communication campaigns or introducing long lasting insecticide nets. Our results demonstrate that DHS data, with appropriate methodology, can provide acceptable estimates at sub-national level for monitoring and evaluation of malaria control goals

Modelling the impact of women’s education on fertility in Malawi

Many studies have suggested that there is an inverse relationship between education and number of children among women from sub-Saharan Africa countries, including Malawi. However, a crucial limitation of these analyses is that they do not control for the potential endogeneity of education. The aim of our study is to estimate the role of women’s education on their number of children in Malawi, accounting for the possible presence of endogeneity and for nonlinear effects of continuous observed confounders. Our analysis is based on micro data from the 2010 Malawi Demographic Health Survey, and uses a flexible instrumental variable regression approach. The results suggest that the relationship of interest is affected by endogeneity and exhibits an inverted U-shape among women living in rural areas of Malawi, whereas it exhibits an inverse (nonlinear) relationship for women living in urban areas