Quantifying Spatial Disparities in Neonatal Mortality Using a Structured Additive Regression Model

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 addressin

Prevalence and associated factors of physical fighting among school-going adolescents in Namibia

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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)).</p> <p>Conclusion</p> <p>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.</p

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

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

The threat of Covid-19 on food security: A modelling perspective of scenarios in the informal settlements in Windhoek

Due to the heterogeneity among households across locations, predicting the impacts of stay-at-home mitigation and lockdown strategies for COVID-19 control is crucial. In this study, we quantitatively assessed the effects of the Namibia government’s lockdown control measures on food insecurity in urban informal settlements with a focus on Windhoek, Namibia. We developed three types of conditional regression models to predict food insecurity prevalence (FIP) scenarios incorporating household frequency of food purchase (FFP) as the impacting factor, based on the Hungry Cities Food Matrix. Empirical data were derived from the 2017 African Food Security Urban Network (AFSUN) Windhoek study and applied univariate probit and bivariate partial observability models to postulate the relation between food insecurity and FFP within the context of stay-at-home disease mitigation strategy. The findings showed that FFP was positively correlated with the prevalence of food insecurity (r = 0.057, 95% CI: 0.0394, 0.085). Daily purchases portrayed a survivalist behaviour and were associated with increased food insecurity (coeff = 0.076, p = 0.05)

Wild and indigenous foods (wif) and urban food security in northern Namibia

Rapid urbanisation and food system transformation in Africa have been accompanied by growing food insecurity, reduced dietary diversity, and an epidemic of non-communicable disease. While the contribution of wild and indigenous foods (WIF) to the quality of rural household diets has been the subject of longstanding attention, research on their consumption and role among urban households is more recent. This paper provides a case study of the consumption of WIF in the urban corridor of northern Namibia with close ties to the surrounding rural agricultural areas. The research methodology involved a representative household food security sur vey of 851 urban households using tablets and ODK Collect. The key methods for data analysis included descriptive statistics and ordinal logistic regression. The main findings of the analysis included the fact that WIFs are consumed by most households, but with markedly different frequencies. Frequent consumers of WIF are most likely to be female-centred households, in the lowest income quintiles, and with the highest lived poverty. Frequent consumption is not related to food security, but is higher in households with low dietary diversity. Infrequent or occasional consumers tend to be higher-income households with low lived poverty and higher levels of food security. We conclude that frequent consumers use WIF to diversify their diets and that occasional consumers eat WIF more for reasons of cultural preference and taste than necessity. Recommendations for future research include the nature of the supply chains that bring WIF to urban consumers, intra-household consumption of WIF, and in-depth interviews about the reasons for household consumption of WIF and preferences for certain types of wild food

Competing risks modeling of length of hospital stay enhances risk-stratification of patient care: application to under-five children hospitalized in Malawi

Introduction Length of hospital stay (LOS), defined as the time from inpatient admission to discharge, death, referral, or abscondment, is one of the key indicators of quality in patient care. Reduced LOS lowers health care expenditure and minimizes the chance of in-hospital acquired infections. Conventional methods for estimating LOS such as the Kaplan-Meier survival curve and the Cox proportional hazards regression for time to discharge cannot account for competing risks such as death, referral, and abscondment. This study applied competing risk methods to investigate factors important for risk-stratifying patients based on LOS in order to enhance patient care. Methods This study analyzed data from ongoing safety surveillance of the malaria vaccine implementation program in Malawi's four district hospitals of Balaka, Machinga, Mchinji, and Ntchisi. Children aged 1–59 months who were hospitalized (spending at least one night in hospital) with a medical illness were consecutively enrolled between 1 November 2019 and 31 July 2021. Sub-distribution-hazard (SDH) ratios for the cumulative incidence of discharge were estimated using the Fine-Gray competing risk model. Results Among the 15,463 children hospitalized, 8,607 (55.7%) were male and 6,856 (44.3%) were female. The median age was 22 months [interquartile range (IQR): 12–33 months]. The cumulative incidence of discharge was 40% lower among HIV-positive children compared to HIV-negative (sub-distribution-hazard ratio [SDHR]: 0.60; [95% CI: 0.46–0.76]; P < 0.001); lower among children with severe and cerebral malaria [SDHR: 0.94; (95% CI: 0.86–0.97); P = 0.04], sepsis or septicemia [SDHR: 0.90; (95% CI: 0.82–0.98); P = 0.027], severe anemia related to malaria [SDHR: 0.54; (95% CI: 0.48–0.61); P < 0.001], and meningitis [SDHR: 0.18; (95% CI: 0.09–0.37); P < 0.001] when compared to non-severe malaria; and also 39% lower among malnourished children compared to those that were well-nourished [SDHR: 0.61; (95% CI: 0.55–0.68); P < 0.001]. Conclusions This study applied the Fine-Gray competing risk approach to more accurately model LOS as the time to discharge when there were significant rates of in-hospital mortality, referrals, and abscondment. Patient care can be enhanced by risk-stratifying by LOS based on children's age, HIV status, diagnosis, and nutritional status

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

Equity and Geography: The Case of Child Mortality in Papua New Guinea

Background: Recent assessments show continued decline in child mortality in Papua New Guinea (PNG), yet complete subnational analyses remain rare. This study aims to estimate under-five mortality in PNG at national and subnational levels to examine the importance of geographical inequities in health outcomes and track progress towards Millennium Development Goal (MDG) 4