ArticleMalaria journal2020
The Gini coefficient as a useful measure of malaria inequality among populations.
Article in Malaria journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed.
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- Examining geographical inequalities for malaria outcomes and spending on malaria in 40 malaria-endemic countries, 2010-2020.Malaria journal · 2024Article
- Understanding the factors associated with nurse employment in clinics: Experiences in Taiwan.Journal of the Chinese Medical Association : JCMA · 2024Article
- Impacts of socioeconomic and environmental factors on neoplasms incidence rates using machine learning and GIS: a cross-sectional study in Iran.Scientific reports · 2024Article
- Identifying Malaria Hotspots Regions in Ghana Using Bayesian Spatial and Spatiotemporal Models.Infectious diseases & immunity · 2024Article
- Integrated biomarker profiling of the metabolome associated with type 2 diabetes mellitus among Tibetan in China.Diabetology & metabolic syndrome · 2023Article
- Malaria parasite density and detailed qualitative microscopy enhances large-scale profiling of infection endemicity in Nigeria.Scientific reports · 2023Article
- Unemployment and expenditure on health and education as mediators of the association between toothbrushing and global income inequalities.BMC oral health · 2022Article
- Global burden of atrial fibrillation/flutter due to high systolic blood pressure from 1990 to 2019: estimates from the global burden of disease study 2019.Journal of clinical hypertension (Greenwich, Conn.) · 2022Article
- Quantifying spatial heterogeneity of malaria in the endemic Papua region of Indonesia: Analysis of epidemiological surveillance data.The Lancet regional health. Southeast Asia · 2022Article
- Geographical and temporal variation in reduction of malaria infection among children under 5 years of age throughout Nigeria.BMJ global health · 2021Article
- Inequality indices to monitor geographic differences in incidence, mortality and fatality rates over time during the COVID-19 pandemic.PloS one · 2021Article
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Abstract
backgroundUnderstanding inequality in infectious disease burden requires clear and unbiased indicators. The Gini coefficient, conventionally used as a macroeconomic descriptor of inequality, is potentially useful to quantify epidemiological heterogeneity. With a potential range from 0 (all populations equal) to 1 (populations having maximal differences), this coefficient is used here to show the extent and persistence of inequality of malaria infection burden at a wide variety of population levels.
methodsFirst, the Gini coefficient was applied to quantify variation among World Health Organization world regions for malaria and other major global health problems. Malaria heterogeneity was then measured among countries within the geographical sub-region where burden is greatest, among the major administrative divisions in several of these countries, and among selected local communities. Data were analysed from previous research studies, national surveys, and global reports, and Gini coefficients were calculated together with confidence intervals using bootstrap resampling methods.
resultsMalaria showed a very high level of inequality among the world regions (Gini coefficient, G = 0.77, 95% CI 0.66-0.81), more extreme than for any of the other major global health problems compared at this level. Within the most highly endemic geographical sub-region, there was substantial inequality in estimated malaria incidence among countries of West Africa, which did not decrease between 2010 (G = 0.28, 95% CI 0.19-0.36) and 2018 (G = 0.31, 0.22-0.39). There was a high level of sub-national variation in prevalence among states within Nigeria (G = 0.30, 95% CI 0.26-0.35), contrasting with more moderate variation within Ghana (G = 0.18, 95% CI 0.12-0.25) and Sierra Leone (G = 0.17, 95% CI 0.12-0.22). There was also significant inequality in prevalence among local village communities, generally more marked during dry seasons when there was lower mean prevalence. The Gini coefficient correlated strongly with the standard coefficient of variation, which has no finite range.
conclusionsThe Gini coefficient is a useful descriptor of epidemiological inequality at all population levels, with confidence intervals and interpretable bounds. Wider use of the coefficient would give broader understanding of malaria heterogeneity revealed by multiple types of studies, surveys and reports, providing more accessible insight from available data.
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