Estimating risk factors of urban malaria in Blantyre, Malawi: A spatial regression analysis

Objective: To estimate risk factors of urban malaria in Blantyre, Malawi, with the goal of understanding the epidemiology and ecology of the disease, and informing malaria elimination policies for African urban cities that have markedly low prevalence of malaria.Methods: We used a case-control study design, with cases being children under the age of five years diagnosed with malaria, and matched controls obtained at hospital and communities. The data were obtained from Ndirande health facility catchment area. We then fitted a multivariate spatial logistic model of malaria risk. Covariate and risk factors in the model included child-specific, household and environmental risk factor(nearness to garden, standing water, river and swamps). The spatial component was assumed to follow a Gaussian process and model fitted using Bayesian inference.Results: Our findings showed that children who visited rural areas were 6 times more likely to have malaria than those who did not [odds ratio(OR) = 6.66, 95% confidence interval(CI): 4.79–9.61]. The risk of malaria increased with age of the child(OR = 1.01,95% CI: 1.003–1.020), but reduced with high socio-economic status compared to lower status(OR = 0.39, 95% CI: 0.25–0.54 for the highest level and OR = 0.67, 95% CI: 0.47–0.94 for the medium level). Although nearness to a garden, river and standing water showed increased risk, these effects were not significant. Furthermore, significant spatial clusters of risk emerged, which does suggest other factors do explain malaria risk variability apart from those established above.Conclusions: As malaria in urban areas is highly fuelled by rural-urban migration,emphasis should be to optimize information, education and communication prevention strategies, particularly targeting children from lower socio-economic position.

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.