Spatial and socio-economic effects on malaria morbidity in children under 5 years in Malawi in 2012

Multilevel modelling of the risk of malaria among children aged under five years in Nigeria

BACKGROUND

Malaria is still a major cause of morbidity and mortality among children aged <5 y (U5s). This study assessed individual, household and community risk factors for malaria in Nigerian U5s.

METHODS

Data from the Nigerian Malaria Health Indicator Survey 2015 were pooled for analyses. This comprised a national survey of 329 clusters. Children aged 6-59 mo who were tested for malaria using microscopy were retained. Multilevel logit model accounting for sampling design was used to assess individual, household and community factors associated with malaria parasitaemia.

RESULTS

A total of 5742 children were assessed for malaria parasitaemia with an overall prevalence of 27% (95% CI 26 to 28%). Plasmodium falciparum constituted 98% of the Plasmodium species. There was no significant difference in parasitaemia between older children and those aged ≤12 mo. In adjusted analyses, rural living, northwest region, a household size of >7, dependence on river and rainwater as primary water source were associated with higher odds of parasitaemia, while higher wealth index, all U5s who slept under a bed net and dependence on packaged water were associated with lower odds of parasitaemia.

CONCLUSION

Despite sustained investment in malaria control and prevention, a quarter of the overall study population of U5s have malaria. Across the six geopolitical zones, the highest burden was in children living in the poorest rural households.

Prevalence of and factors associated with malaria in children under five years of age in Malawi, using malaria indicator survey data

BACKGROUND

Malaria remains a public health problem in developing countries and Malawi is no different. Although there has been an improvement in reducing malaria in Malawi, it remains a problem, especially in children less than five years old. The primary objective of the study was to assess whether socio-economic, geographic and demographic factors are associated with malaria, using the generalized additive mixed model (GAMM).

DATA AND METHODOLOGY

The study used a 2017 dataset from the Malawi Malaria Indicator Survey (MMI) with a total number of 2724 children under five years old. The study also utilized the GAMM to analyze data. The outcome was that either the child had malaria or did not, as detected using the malaria Rapid Diagnostic Test (RDT) (Ayele et al., 2014a).

RESULTS

In this study, more than 37 % of the total number of children who were tested showed a positive malaria result. In addition, the results from this study using GAMM indicated that anaemia, mother's education level, wealth index, child's age, the altitude of the place of residence, region, place of residence, toilet facility and electricity were significantly associated with a positive malaria RDT.

CONCLUSION

The study revealed that socio-economic, geographical and demographic variables are the key factors in improving malaria vectors in children. Improving income levels and supporting the poorer rural community mostly from the Central Region would be a great achievement in reducing malaria vectors in Malawi. In addition, improving health care in rural areas, especially at higher altitudes, would contribute to controlling malaria and reducing anaemia.

A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa

Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies using spatial statistics approaches for national health survey data in the SSA region. An organized literature search for studies related to spatial statistics and national health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting for survey design). We recommend that for future spatial analysis using health survey data in the SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve application of spatial statistical methods. We also recommend a wide range of applications using big health data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels.

Spatiality in Health: The Distribution of Health Conditions Associated with Electronic Waste Processing Activities at Agbogbloshie, Accra

Background

A walk through the Agbogbloshie e-waste recycling site shows a marked heterogeneity in the spatial distribution of the different e-waste processing activities, which are likely to drive clustering of health conditions associated with the different activity type in each space.

Objective of study

To conduct a spatial assessment and analysis of health conditions associated with different e-waste activities at different activity spaces at Agbogbloshie.

Methods

A choropleth showing the various activity spaces at the Agbogbloshie e-waste site was produced by mapping boundaries of these spaces using Etrex GPS device and individuals working in each activity spaces were recruited and studied. Upon obtaining consent and agreeing to participate in the study, each subject was physically examined and assessed various health outcomes of interest via direct physical examination while characterizing and enumerating the scars, lacerations, abrasions, skin condition and cuts after which both systolic and diastolic blood pressure values were recorded alongside the administration of open and close ended questionnaires. All individuals working within each activity space and consented to participate were recruited; giving a total of one hundred and twelve (112) subjects in all.

Results

A study of the choropleth showed that health conditions associated e-waste processing activities were clustered in a fashion similar to the corresponding distribution of each activity. While a total of 96.2% of all the study subjects had cuts, the dismantlers had higher mix of scars, lacerations and abrasions. Abrasions were observed in 16.3% of the dismantlers. Scars were the most common skin condition and were observed on the skins of 93.6% of the subjects. Prevalence of burns among the study subjects was 23.1%. Developing hypertension was not associated with activity type and while a total of 90.2% of subjects had normal blood pressure and 9.8% of them were hypertensives. Finally, 98.2% of respondents felt the need to have a first aid clinic at the site with 96.4% and 97.3% willing to visit the clinic and pay for services respectively.

Conclusion

We conclude that while the observed injuries were random and were due purely to accidents without any role of spatial determinants such as the configuration, slope, topography and other subterranean features of the activity spaces, a strong association between the injuries and activity type was observed.

Predicting Risk of Imported Disease with Demographics: Geospatial Analysis of Imported Malaria in Minnesota, 2010-2014

Although immigrants who visit friends and relatives (VFRs) account for most of the travel-acquired malaria cases in the United States, there is limited evidence on community-level risk factors and best practices for prevention appropriate for various VFR groups. Using 2010–2014 malaria case reports, sociodemographic census data, and health services data, we explored and mapped community-level characteristics to understand who is at risk and where imported malaria infections occur in Minnesota. We examined associations with malaria incidence using Poisson and negative binomial regression. Overall, mean incidence was 0.4 cases per 1,000 sub-Saharan African (SSA)–born in communities reporting malaria, with cases concentrated in two areas of Minneapolis–St. Paul. We found moderate and positive associations between imported malaria and counts of SSA- and Asian-born populations, respectively. Our findings may inform future studies to understand the knowledge, attitudes, and practices of VFR travelers and facilitate and focus intervention strategies to reduce imported malaria in the United States.

Development of a data collection and management system in West Africa: challenges and sustainability

BACKGROUND

Developing and sustaining a data collection and management system (DCMS) is difficult in malaria-endemic countries because of limitations in internet bandwidth, computer resources and numbers of trained personnel. The premise of this paper is that development of a DCMS in West Africa was a critically important outcome of the West African International Centers of Excellence for Malaria Research. The purposes of this paper are to make that information available to other investigators and to encourage the linkage of DCMSs to international research and Ministry of Health data systems and repositories.

METHODS

We designed and implemented a DCMS to link study sites in Mali, Senegal and The Gambia. This system was based on case report forms for epidemiologic, entomologic, clinical and laboratory aspects of plasmodial infection and malarial disease for a longitudinal cohort study and included on-site training for Principal Investigators and Data Managers. Based on this experience, we propose guidelines for the design and sustainability of DCMSs in environments with limited resources and personnel.

RESULTS

From 2012 to 2017, we performed biannual thick smear surveys for plasmodial infection, mosquito collections for anopheline biting rates and sporozoite rates and year-round passive case detection for malarial disease in four longitudinal cohorts with 7708 individuals and 918 households in Senegal, The Gambia and Mali. Major challenges included the development of uniform definitions and reporting, assessment of data entry error rates, unstable and limited internet access and software and technology maintenance. Strengths included entomologic collections linked to longitudinal cohort studies, on-site data centres and a cloud-based data repository.

CONCLUSIONS

At a time when research on diseases of poverty in low and middle-income countries is a global priority, the resources available to ensure accurate data collection and the electronic availability of those data remain severely limited. Based on our experience, we suggest the development of a regional DCMS. This approach is more economical than separate data centres and has the potential to improve data quality by encouraging shared case definitions, data validation strategies and analytic approaches including the molecular analysis of treatment successes and failures.