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1.  Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data 
PLoS ONE  2014;9(7):e101116.
Background
After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions.
Methods
We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi.
Results
Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk.
Conclusions
The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities.
doi:10.1371/journal.pone.0101116
PMCID: PMC4084636  PMID: 24991915
2.  Mapping Malaria Transmission Intensity in Malawi, 2000–2010 
Substantial development assistance has been directed towards reducing the high malaria burden in Malawi over the past decade. We assessed changes in transmission over this period of malaria control scale-up by compiling community Plasmodium falciparum rate (PfPR) data during 2000–2011 and used model-based geostatistical methods to predict mean PfPR2–10 in 2000, 2005, and 2010. In addition, we calculated population-adjusted prevalences and populations at risk by district to inform malaria control program priority setting. The national population-adjusted PfPR2–10 was 37% in 2010, and we found no evidence of change over this period of scale-up. The entire population of Malawi is under meso-endemic transmission risk, with those in districts along the shore of Lake Malawi and Shire River Valley under highest risk. The lack of change in prevalence confirms modeling predictions that when compared with lower transmission, prevalence reductions in high transmission settings require greater investment and longer time scales.
doi:10.4269/ajtmh.13-0028
PMCID: PMC3820324  PMID: 24062477
3.  A Bayesian Two Part Model Applied to Analyze Risk Factors of Adult Mortality with Application to Data from Namibia 
PLoS ONE  2013;8(9):e73500.
Despite remarkable gains in life expectancy and declining mortality in the 21st century, in many places mostly in developing countries, adult mortality has increased in part due to HIV/AIDS or continued abject poverty levels. Moreover many factors including behavioural, socio-economic and demographic variables work simultaneously to impact on risk of mortality. Understanding risk factors of adult mortality is crucial towards designing appropriate public health interventions. In this paper we proposed a structured additive two-part random effects regression model for adult mortality data. Our proposal assumed two processes: (i) whether death occurred in the household (prevalence part), and (ii) number of reported deaths, if death did occur (severity part). The proposed model specification therefore consisted of two generalized linear mixed models (GLMM) with correlated random effects that permitted structured and unstructured spatial components at regional level. Specifically, the first part assumed a GLMM with a logistic link and the second part explored a count model following either a Poisson or negative binomial distribution. The model was used to analyse adult mortality data of 25,793 individuals from the 2006/2007 Namibian DHS data. Inference is based on the Bayesian framework with appropriate priors discussed.
doi:10.1371/journal.pone.0073500
PMCID: PMC3774685  PMID: 24066052
4.  Explaining Marital Patterns and Trends in Namibia: A Regression Analysis of 1992, 2000 and 2006 Demographic and Survey Data 
PLoS ONE  2013;8(8):e70394.
Background
Marriage is a significant event in life-course of individuals, and creates a system that characterizes societal and economic structures. Marital patterns and dynamics over the years have changed a lot, with decreasing proportions of marriage, increased levels of divorce and co-habitation in developing countries. Although, such changes have been reported in African societies including Namibia, they have largely remained unexplained.
Objectives and Methods
In this paper, we examined trends and patterns of marital status of women of marriageable age: 15 to 49 years, in Namibia using the 1992, 2000 and 2006 Demographic and Health Survey (DHS) data. Trends were established for selected demographic variables. Two binary logistic regression models for ever-married versus never married, and cohabitation versus married were fitted to establish factors associated with such nuptial systems. Further a multinomial logistic regression models, adjusted for bio-demographic and socio-economic variables, were fitted separately for each year, to establish determinants of type of union (never married, married and cohabitation).
Results and Conclusions
Findings indicate a general change away from marriage, with a shift in singulate mean age at marriage. Cohabitation was prevalent among those less than 30 years of age, the odds were higher in urban areas and increased since 1992. Be as it may marriage remained a persistent nuptiality pattern, and common among the less educated and employed, but lower odds in urban areas. Results from multinomial model suggest that marital status was associated with age at marriage, total children born, region, place of residence, education level and religion. We conclude that marital patterns have undergone significant transformation over the past two decades in Namibia, with a coexistence of traditional marriage framework with co-habitation, and sizeable proportion remaining unmarried to the late 30s. A shift in the singulate mean age is becoming distinctive in the Namibian society.
doi:10.1371/journal.pone.0070394
PMCID: PMC3744526  PMID: 23967073
5.  Analysis of Schistosomiasis haematobium Infection Prevalence and Intensity in Chikhwawa, Malawi: An Application of a Two Part Model 
Background
Urinary Schistosomiasis infection, a common cause of morbidity especially among children in less developed countries, is measured by the number of eggs per urine. Typically a large proportion of individuals are non-egg excretors, leading to a large number of zeros. Control strategies require better understanding of its epidemiology, hence appropriate methods to model infection prevalence and intensity are crucial, particularly if such methods add value to targeted implementation of interventions.
Methods
We consider data that were collected in a cluster randomized study in 2004 in Chikhwawa district, Malawi, where eighteen (18) villages were selected and randomised to intervention and control arms. We developed a two-part model, with one part for analysis of infection prevalence and the other to model infection intensity. In both parts of the model we adjusted for age, sex, education level, treatment arm, occupation, and poly-parasitism. We also assessed for spatial correlation in the model residual using variogram analysis and mapped the spatial variation in risk. The model was fitted using maximum likelihood estimation.
Results and discussion
The study had a total of 1642 participants with mean age of 32.4 (Standard deviation: 22.8), of which 55.4 % were female. Schistosomiasis prevalence was 14.2 %, with a large proportion of individuals (85.8 %) being non-egg excretors, hence zero-inflated data. Our findings showed that S. haematobium was highly localized even after adjusting for risk factors. Prevalence of infection was low in males as compared to females across all the age ranges. S. haematobium infection increased with presence of co-infection with other parasite infection. Infection intensity was highly associated with age; with highest intensity in school-aged children (6 to 15 years). Fishing and working in gardens along the Shire River were potential risk factors for S. haematobium infection intensity. Intervention reduced both infection intensity and prevalence in the intervention arm as compared to control arm. Farmers had high infection intensity as compared to non farmers, despite the fact that being a farmer did not show any significant association with probability of infection.
These results evidently indicate that infection prevalence and intensity are associated with risk factors differently, suggesting a non-singular epidemiological setting. The dominance of agricultural, socio-economic and demographic factors in determining S. haematobium infection and intensity suggest that disease transmission and control strategies should continue centring on improving socio-economic status, environmental modifications to control S. haematobium intermediate host snails and mass drug administration, which may be more promising approaches to disease control in high intensity and prevalence settings.
Author Summary
Schistosomiasis is one of the great causes of morbidity among school aged children in the tropical region and Sub Saharan Africa in particular. It's mainly transmitted through contact with water infested with intermediate host snail Cercariae. Currently, over 200 million people are estimated to be infected in SSA alone. Here, we used robust and contemporary statistical methods in a two part application to analyse risk factors for S. haematobium infection intensity and prevalence. We found that S. haematobium was more common in younger children as compared to older children, thus making the infection and prevalence age dependent. We also found that mass chemotherapy reduced both infection prevalence and intensity. We found that dominance of agricultural, socio-economic and demographic factors in determining S. haematobium infection risk in the villages carries important implications for disease surveillance and control strategies. Therefore disease transmission and control strategies centered on improving strategies involving socio-economic status, environmental modifications to control S. haematobium intermediate host snails and mass drug administration may be more promising approaches to disease control in high intensity and prevalence settings.
doi:10.1371/journal.pntd.0002131
PMCID: PMC3605235  PMID: 23556017
6.  Surveillance Programme of IN-patients and Epidemiology (SPINE): Implementation of an Electronic Data Collection Tool within a Large Hospital in Malawi 
PLoS Medicine  2013;10(3):e1001400.
Miguel Sanjoaquin and colleagues describe their experience of setting up an electronic patient records system in a large referral hospital in Blantyre, Malawi.
doi:10.1371/journal.pmed.1001400
PMCID: PMC3595207  PMID: 23554578
7.  Childhood mortality in sub-Saharan Africa: cross-sectional insight into small-scale geographical inequalities from Census data 
BMJ Open  2012;2(5):e001421.
Objectives
To estimate and quantify childhood mortality, its spatial correlates and the impact of potential correlates using recent census data from three sub-Saharan African countries (Rwanda, Senegal and Uganda), where evidence is lacking.
Design
Cross-sectional.
Setting
Nation-wide census samples from three African countries participating in the 2010 African Census round. All three countries have conducted recent censuses and have information on mortality of children under 5 years.
Participants
111 288 children under the age of 5 years in three countries.
Primary and secondary outcome measures
Under-five mortality was assessed alongside potential correlates including geographical location (where children live), and environmental, bio-demographic and socioeconomic variables.
Results
Multivariate analysis indicates that in all three countries the overall risk of child death in the first 5 years of life has decreased in recent years (Rwanda: HR=0.04, 95% CI 0.02 to 0.09; Senegal: HR=0.02 (95% CI 0.02 to 0.05); Uganda: HR=0.011 (95% CI 0.006 to 0.018). In Rwanda, lower deaths were associated with living in urban areas (0.79, 0.73, 0.83), children with living mother (HR=0.16, 95% CI 0.15 to 0.17) or living father (HR=0.38, 95% CI 0.36 to 0.39). Higher death was associated with male children (HR=1.06, 95% CI 1.02 to 1.08) and Christian children (HR=1.14, 95% CI 1.05 to 1.27). Children less than 1 year were associated with higher risk of death compared to older children in the three countries. Also, there were significant spatial variations showing inequalities in children mortality by geographic location. In Uganda, for example, areas of high risk are in the south-west and north-west and Kampala district showed a significantly reduced risk.
Conclusions
We provide clear evidence of considerable geographical variation of under-five mortality which is unexplained by factors considered in the data. The resulting under-five mortality maps can be used as a practical tool for monitoring progress within countries for the Millennium Development Goal 4 to reduce under-five mortality in half by 2015.
doi:10.1136/bmjopen-2012-001421
PMCID: PMC3488715  PMID: 23089207
8.  Pattern of Maternal Knowledge and Its Implications for Diarrhoea Control in Southern Malawi: Multilevel Thresholds of Change Analysis 
A survey was conducted in Southern Malawi to examine the pattern of mothers’ knowledge on diarrhoea. Diarrhoea morbidity in the district is estimated at 24.4%, statistically higher than the national average at 17%. Using hierarchically built data from a survey, a multilevel threshold of change analysis was used to determine predictors of knowledge about diarrhoeal aetiology, clinical features, and prevention. The results show a strong hierarchical structured pattern in overall maternal knowledge revealing differences between communities. Responsible mothers with primary or secondary school education were more likely to give more correct answers on diarrhoea knowledge than those without any formal education. Responsible mothers from communities without a health surveillance assistant were less likely to give more correct answers. The results show that differences in diarrhoeal knowledge do exist between communities and demonstrate that basic formal education is important in responsible mother’s understanding of diseases. The results also reveal the positive impact health surveillance assistants have in rural communities.
doi:10.3390/ijerph9030955
PMCID: PMC3367290  PMID: 22690176
responsible mother’s knowledge; pattern of variation; diarrhoea control; multilevel threshold of change; southern-tip of Malawi
9.  Quantifying Spatial Disparities in Neonatal Mortality Using a Structured Additive Regression Model 
PLoS ONE  2010;5(6):e11180.
Background
Neonatal mortality contributes a large proportion towards early childhood mortality in developing countries, with considerable geographical variation at small areas within countries.
Methods
A geo-additive logistic regression model is proposed for quantifying small-scale geographical variation in neonatal mortality, and to estimate risk factors of neonatal mortality. Random effects are introduced to capture spatial correlation and heterogeneity. The spatial correlation can be modelled using the Markov random fields (MRF) when data is aggregated, while the two dimensional P-splines apply when exact locations are available, whereas the unstructured spatial effects are assigned an independent Gaussian prior. Socio-economic and bio-demographic factors which may affect the risk of neonatal mortality are simultaneously estimated as fixed effects and as nonlinear effects for continuous covariates. The smooth effects of continuous covariates are modelled by second-order random walk priors. Modelling and inference use the empirical Bayesian approach via penalized likelihood technique. The methodology is applied to analyse the likelihood of neonatal deaths, using data from the 2000 Malawi demographic and health survey. The spatial effects are quantified through MRF and two dimensional P-splines priors.
Results
Findings indicate that both fixed and spatial effects are associated with neonatal mortality.
Conclusions
Our study, therefore, suggests that the challenge to reduce neonatal mortality goes beyond addressing individual factors, but also require to understanding unmeasured covariates for potential effective interventions.
doi:10.1371/journal.pone.0011180
PMCID: PMC2887370  PMID: 20567519
10.  Applications of Bayesian approach in modelling risk of malaria-related hospital mortality 
Background
Malaria is a major public health problem in Malawi, however, quantifying its burden in a population is a challenge. Routine hospital data provide a proxy for measuring the incidence of severe malaria and for crudely estimating morbidity rates. Using such data, this paper proposes a method to describe trends, patterns and factors associated with in-hospital mortality attributed to the disease.
Methods
We develop semiparametric regression models which allow joint analysis of nonlinear effects of calendar time and continuous covariates, spatially structured variation, unstructured heterogeneity, and other fixed covariates. Modelling and inference use the fully Bayesian approach via Markov Chain Monte Carlo (MCMC) simulation techniques. The methodology is applied to analyse data arising from paediatric wards in Zomba district, Malawi, between 2002 and 2003.
Results and Conclusion
We observe that the risk of dying in hospital is lower in the dry season, and for children who travel a distance of less than 5 kms to the hospital, but increases for those who are referred to the hospital. The results also indicate significant differences in both structured and unstructured spatial effects, and the health facility effects reveal considerable differences by type of facility or practice. More importantly, our approach shows non-linearities in the effect of metrical covariates on the probability of dying in hospital. The study emphasizes that the methodological framework used provides a useful tool for analysing the data at hand and of similar structure.
doi:10.1186/1471-2288-8-6
PMCID: PMC2287185  PMID: 18284691
11.  Harmful lifestyles' clustering among sexually active in-school adolescents in Zambia 
BMC Pediatrics  2008;8:6.
Background
HIV is a leading cause of morbidity and mortality in Zambia. Like many other African nations with high HIV burden, heterosexual intercourse is the commonest mode of HIV spread. The estimation of prevalence and factors associated with sexual intercourse among in-school adolescents has potential to inform public health interventions aimed at reducing the burden of sex-related diseases in Zambia.
Methods
We carried out secondary analysis of the Zambia Global School-Based Health Survey (GSHS) 2004; a cross sectional survey that aims to study health-related behaviors among in-school adolescents. We estimated frequencies of relevant socio-demographic variables. The associations between selected explanatory variables and self-reported history of sexual intercourse within the last 12 months were assessed using logistic regression analysis.
Results
Data from 2136 in-school adolescents who participated in the Zambia Global School-Based Health Survey of 2004 were available for analysis. Out of these respondents, 13.4% reported that they had sexual intercourse in the past 12 months prior to the survey; 16.4% and 9.7% among males and females respectively. In multivariable logistic regression analysis, with age less than 15 years as the referent the adjusted odds ratio (AOR) of having engaged in sexual intercourse in adolescents of age 15 years, and those aged 16 years or more were 1.06 (95% CI 1.03–1.10) and 1.74 (95% 1.70–1.79) respectively. Compared to adolescents who had no close friends, adolescents who had one close friend were more likely to have had sexual intercourse, AOR = 1.28 (95% CI 1.24–1.32). Compared to adolescents who were not supervised by their parents, adolescents who were rarely or sometimes supervised by their parents were likely to have had sexual intercourse, and adolescents who were most of the time/always supervised by their parents were less likely to have had sexual intercourse; AORs 1.26 (95% CI 1.23–1.26) and 0.92 (95% CI 0.90–0.95) respectively. Compared to adolescents who did not smoke dagga, adolescents who smoked dagga 1 or 2 times, and those who smoked dagga 3 or more times in their lifetime were 70% and 25% more likely to have had sexual intercourse, respectively. Adolescents who drank alcohol in 1 or 2 days, and those who took alcohol in 3 or more days in a month preceding the survey were 12% and 9% more likely to have had sexual intercourse, respectively, compared to adolescents who did not drink alcohol in the 30 days prior to the survey. Furthermore, adolescents who had been drunk 1 or 2 times, and who had been drunk 3 or more times in a life time were 14% and 13% more likely to have had sexual intercourse compared to those who have never been drunk in their lifetime.
Conclusion
We identified a constellation of potentially harmful behaviours among adolescents in Zambia. Public health interventions aimed at reducing prevalence of sexual intercourse may be designed and implemented in a broader sense having recognized that sexually active adolescents may also be exposed to other problem behaviours.
doi:10.1186/1471-2431-8-6
PMCID: PMC2276492  PMID: 18267020
12.  Modelling the effect of malaria endemicity on spatial variations in childhood fever, diarrhoea and pneumonia in Malawi 
Background
Co-morbidity with conditions such as fever, diarrhoea and pneumonia is a common phenomenon in tropical Africa. However, little is known about geographical overlaps in these illnesses. Spatial modelling may improve our understanding of the epidemiology of the diseases for efficient and cost-effective control.
Methods
This study assessed subdistrict-specific spatial associations of the three conditions (fever, diarrhoea and pneumonia) in relation to malaria endemicity. We used data from the 2000 Malawi demographic and health survey which captured the history of childhood morbidities 2 weeks prior to the survey date. The disease status of each child in each area was the outcome of interest and was modelled using a trivariate logistic regression model, and incorporated random effects to measure spatial correlation.
Results
The risk of fever was positively associated with high and medium malaria endemicity levels relative to low endemicity level, while for diarrhoea and pneumonia we observed marginal positive association at high endemicity level relative to low endemicity level, controlling for confounding covariates and heterogeneity. A positive spatial correlation was found between fever and diarrhoea (r = 0.29); while weak associations were estimated between fever and pneumonia (r = 0.01); and between diarrhoea and pneumonia (r = 0.05). The proportion of structured spatial variation compared to unstructured variation was 0.67 (95% credible interval (CI): 0.31–0.91) for fever, 0.67 (95 % CI: 0.27–0.93) for diarrhoea, and 0.87 (95% CI: 0.62–0.96) for pneumonia.
Conclusion
The analysis suggests some similarities in subdistrict-specific spatial variation of childhood morbidities of fever, diarrhoea and pneumonia, and might be a result of shared and overlapping risk factors, one of which is malaria endemicity.
doi:10.1186/1476-072X-6-33
PMCID: PMC1963446  PMID: 17651488
13.  Prevalence and associated factors of physical fighting among school-going adolescents in Namibia 
Background
Interpersonal physical violence is an important global public health concern that has received limited attention in the developing world. There is in particular a paucity of data regarding physical violence and its socio-demographic correlates among in-school adolescents in Namibia.
Methods
We analysed cross-sectional data from the Namibia Global School-Based Health Survey (GSHS) conducted in 2004. We aimed to estimate the prevalence and socio-demographic correlates of physical fighting within the last 12 months. We obtained frequencies of socio-demographic attributes. We also assessed the association between self-reported history of having engaging in a physical fight and a selected list of independent variables using logistic regression analysis.
Results
Of the 6283 respondents, 50.6% (55.2% males and 46.2% females) reported having been in a physical fight in the past 12 months. Males were more likely to have been in a physical fight than females (OR = 1.71, 95% CI (1.44, 2.05)). Smoking, drinking alcohol, using drugs and bullying victimization were positively associated with fighting (OR = 1.91, 95% CI (1.49, 2.45); OR = 1.48, 95% CI (1.21, 1.81); OR = 1.55, 95% CI (1.22, 1.81); and OR = 3.12, 95% CI (2.62, 3.72), respectively). Parental supervision was negatively associated with physical fighting (OR = 0.82, 95% CI (0.69, 0.98)). Both male and female substance users (cigarette smoking, alcohol and drug use) were more likely to engage in physical fighting than non-substance users (OR = 3.53, 95% CI (2.60, 4.81) for males and OR = 11.01, 95% CI (7.25, 16.73) for females). Parental supervision was negatively associated with physical fighting (OR = 0.85, 95% CI (0.72, 0.99)).
Conclusion
Prevalence of physical fighting within the last 12 months was comparable to estimates obtained in European countries. We also found clustering of problem behaviours or experiences among adolescents who reported having engaged in physical violence in the past 12 months. There is a need to bring adolescent violent behaviour to the fore of the public health agenda in Namibia.
doi:10.1186/1744-859X-6-18
PMCID: PMC1947983  PMID: 17650328
14.  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.
doi:10.1186/1475-9276-6-5
PMCID: PMC1934906  PMID: 17610730
15.  Choice of treatment for fever at household level in Malawi: examining spatial patterns 
Malaria Journal  2007;6:40.
Background
Although malaria imposes an enormous burden on Malawi, it remains a controllable disease. The key strategies for control are based on early diagnosis and prompt treatment with effective antimalarials. Its success, however, depends on understanding the factors influencing health care decision making at household level, which has implications for implementing policies aimed at promoting health care practices and utilization.
Methods
An analysis of patterns of treatment-seeking behaviour among care-givers of children of malarial fever in Malawi, based on the 2000 Malawi demographic and health survey, is presented. The choice of treatment provider (home, shop, or formal hospital care, others) was considered as a multi-categorical response, and a multinomial logistic regression model was used to investigate determinants of choosing any particular provider. The model incorporated random effects, at subdistrict level, to measure the influence of geographical location on the choice of any treatment provider. Inference was Bayesian and based on Markov chain Monte Carlo techniques.
Results and Conclusion
Spatial variation was found in the choice of a provider and determinants of choice of any provider differed. Important risk factors included place of residence, access to media, care-giver's age and care factors including unavailability and inaccessibility of care. A greater effort is needed to improve the quality of malaria home treatment or expand health facility utilization, at all levels of administration if reducing malaria is to be realised in Malawi. Health promotion and education interventions should stress promptness of health facility visits, improved access to appropriate drugs, and accurate dosing for home-based treatments.
doi:10.1186/1475-2875-6-40
PMCID: PMC1855348  PMID: 17425775
16.  Patterns of malaria-related hospital admissions and mortality among Malawian children: an example of spatial modelling of hospital register data 
Malaria Journal  2006;5:93.
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.
doi:10.1186/1475-2875-5-93
PMCID: PMC1635723  PMID: 17067375
17.  Spatial analysis and mapping of malaria risk in Malawi using point-referenced prevalence of infection data 
Background
Current malaria control initiatives aim at reducing malaria burden by half by the year 2010. Effective control requires evidence-based utilisation of resources. Characterizing spatial patterns of risk, through maps, is an important tool to guide control programmes. To this end an analysis was carried out to predict and map malaria risk in Malawi using empirical data with the aim of identifying areas where greatest effort should be focussed.
Methods
Point-referenced prevalence of infection data for children aged 1–10 years were collected from published and grey literature and geo-referenced. The model-based geostatistical methods were applied to analyze and predict malaria risk in areas where data were not observed. Topographical and climatic covariates were added in the model for risk assessment and improved prediction. A Bayesian approach was used for model fitting and prediction.
Results
Bivariate models showed a significant association of malaria risk with elevation, annual maximum temperature, rainfall and potential evapotranspiration (PET). However in the prediction model, the spatial distribution of malaria risk was associated with elevation, and marginally with maximum temperature and PET. The resulting map broadly agreed with expert opinion about the variation of risk in the country, and further showed marked variation even at local level. High risk areas were in the low-lying lake shore regions, while low risk was along the highlands in the country.
Conclusion
The map provided an initial description of the geographic variation of malaria risk in Malawi, and might help in the choice and design of interventions, which is crucial for reducing the burden of malaria in Malawi.
doi:10.1186/1476-072X-5-41
PMCID: PMC1584224  PMID: 16987415

Results 1-17 (17)