The Gini coefficient as a useful measure of malaria inequality among populations
Abstract Background Understanding 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...
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ftdoajarticles:oai:doaj.org/article:238069a07a52463faa0fb1f3b504e531 2023-05-15T15:14:19+02:00 The Gini coefficient as a useful measure of malaria inequality among populations Jonathan Abeles David J. Conway 2020-12-01T00:00:00Z https://doi.org/10.1186/s12936-020-03489-x https://doaj.org/article/238069a07a52463faa0fb1f3b504e531 EN eng BMC https://doi.org/10.1186/s12936-020-03489-x https://doaj.org/toc/1475-2875 doi:10.1186/s12936-020-03489-x 1475-2875 https://doaj.org/article/238069a07a52463faa0fb1f3b504e531 Malaria Journal, Vol 19, Iss 1, Pp 1-8 (2020) Inequality Epidemiology Heterogeneity Statistical index Infection Prevalence Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2020 ftdoajarticles https://doi.org/10.1186/s12936-020-03489-x 2022-12-31T15:43:47Z Abstract Background Understanding 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. Methods First, 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. Results Malaria 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 ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 19 1 |
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Inequality Epidemiology Heterogeneity Statistical index Infection Prevalence Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Inequality Epidemiology Heterogeneity Statistical index Infection Prevalence Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Jonathan Abeles David J. Conway The Gini coefficient as a useful measure of malaria inequality among populations |
topic_facet |
Inequality Epidemiology Heterogeneity Statistical index Infection Prevalence Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background Understanding 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. Methods First, 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. Results Malaria 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 ... |
format |
Article in Journal/Newspaper |
author |
Jonathan Abeles David J. Conway |
author_facet |
Jonathan Abeles David J. Conway |
author_sort |
Jonathan Abeles |
title |
The Gini coefficient as a useful measure of malaria inequality among populations |
title_short |
The Gini coefficient as a useful measure of malaria inequality among populations |
title_full |
The Gini coefficient as a useful measure of malaria inequality among populations |
title_fullStr |
The Gini coefficient as a useful measure of malaria inequality among populations |
title_full_unstemmed |
The Gini coefficient as a useful measure of malaria inequality among populations |
title_sort |
gini coefficient as a useful measure of malaria inequality among populations |
publisher |
BMC |
publishDate |
2020 |
url |
https://doi.org/10.1186/s12936-020-03489-x https://doaj.org/article/238069a07a52463faa0fb1f3b504e531 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 19, Iss 1, Pp 1-8 (2020) |
op_relation |
https://doi.org/10.1186/s12936-020-03489-x https://doaj.org/toc/1475-2875 doi:10.1186/s12936-020-03489-x 1475-2875 https://doaj.org/article/238069a07a52463faa0fb1f3b504e531 |
op_doi |
https://doi.org/10.1186/s12936-020-03489-x |
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Malaria Journal |
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19 |
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1 |
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1766344782418804736 |