A systematic review of the application and utility of geographical information systems for exploring disease-disease relationships in paediatric global health research: the case of anaemia and malaria

Abstract

Malaria and anaemia are important health problems among children globally. Iron deficiency anaemia may offer protection against malaria infection and iron supplementation may increase the risk of malaria-related hospitalization and mortality. The nature and mechanism of these relationships, however, remain largely unresolved, resulting in concern and uncertainty around policies for non-selective iron supplementation in malaria endemic areas. Use of geographical information systems (GIS) to investigate this disease-disease interaction could contribute important new information for developing safe and effective anaemia and malaria interventions. To assess the current state of knowledge we conducted a systematic review of peer-reviewed and grey literature. Our primary objective was to qualitatively assess the application and utility of geographical concepts or spatial analyses in paediatric global health research. The secondary objective was to identify geographical factors that may be associated with anaemia and malaria prevalence or incidence among children 0–5 years of age living in low- and middle-income countries. Evaluation tools for assessing the quality of geographical data could not be found in the peer-reviewed or grey literature, and thus adapted versions of the STROBE (Strengthening The Reporting of Observational Studies in Epidemiology) and GRADE (Grades of Recommendation, Assessment, Development and Evaluation) methods were used to create reporting, and overall evidence quality scoring systems. Among the 20 included studies, we found that both malaria and anaemia were more prevalent in rural communities compared to urban areas. Geographical factors associated with malaria prevalence included regional transmission stability, and proximity to a mosquito breeding area. The prevalence of anaemia tended to vary inversely with greater or poorer access to community services such as piped water. Techniques for investigating geographic relationships ranged from simple descriptive mapping of spatial distribution patterns, to more complex statistical models that incorporated environmental factors such as seasonal temperature and rain fall. Including GIS in paediatric global health research may be an effective approach to explore relationships between childhood diseases and contribute key evidence for safe implementation of anaemia control programs in malaria endemic areas. Further, GIS presentation of ecological health data could provide an efficient means of translating this knowledge to lay audiences.

Sleep characteristics, light at night and breast cancer risk in a prospective cohort

“…Although not statistically significant, the point estimates are consistent with other studies that have largely shown positive associations between artificial light at night exposure and breast cancer risk 21–25 and are in line with a meta-analysis reporting a 17% increase in overall breast cancer risk for artificial light exposure. 8 We were limited by not having additional information about artificial light in the evenings prior to bedtime or on duration of light exposure during sleep.…”

Moving to opportunity and mental health: Exploring the spatial context of neighborhood effects

“…It also improves our understanding of neighborhood effects on health by focusing on neighborhood concentrated disadvantage in addition to poverty – a broader indicator or neighborhood quality that is consistent with Wilson's insights on concentration effects (Wilson, 1987), the social disorganization literature (Sampson and Groves, 1989), a recent analysis of delinquency among MTO youth (Graif 2015a), and research on the neighborhood effects on other health outcomes in varying social groups and countries (Allender et al, 2012; Caughy et al, 2007; Sridharan et al, 2007; Zhang et al, 2011; Zhang et al, 2013). Our results show that exposure to residential neighborhood disadvantage is associated with worse mental health, as expected.…”

“…In contrast, deprived areas proximal to advantaged areas have been found to have higher rates of anxiety/mood disorder treatment (Pearson, 2013). Other studies have examined how spatial integration of deprived neighborhoods affects health outcomes other than mental health (Allender et al, 2012; Cuaghy et al, 2007; Chen et al, 2010; Lorant et al, 2001; Sridharan, 2007; Zhang et al, 2011; Zhang et al, 2013). …”

Visualization and analytics tools for infectious disease epidemiology: A systematic review

“…Many systems incorporated a temporal component, enabling either animation of data through time or restriction of the data displayed to a time window of interest [77, 79, 84, 110]. A step beyond mere display of information, some GIS or spatial statistical methods seek to perform kernel-based smoothing to estimate risk maps [87, 97, 107], visualize disease risk according to a statistical model [29, 46, 76, 81, 85, 86, 107, 111, 112], or compare one feature to another [71, 84, 97, 100, 101]. While the ability to zoom and pan to navigate maps [79, 96, 105] is a common interactive feature enjoyed by users, more advanced systems contain interactive controls to enable users to retrieve information about selected items or regions, visualize the results of arbitrary queries [79], control visualization options, control temporal ranges of data returned [77, 79], or link displays of data with alternate or comparative visualizations [78, 79].…”