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 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 standard coefficient of variation, which has no finite range. Conclusions The 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.

Assessing Classic Maya multi-scalar household inequality in southern Belize

“…To calculate the Gini coefficient, we used the packages reldist [ 91 ] to calculate the Gini coefficient and boot [ 92 ] for bootstrapped error ranges [ 93 S1 Text ] to accommodate small sample sizes [ 41 ]. The confidence intervals are presented as the lower and upper boundaries of the Gini coefficient.…”

Geographical and temporal variation in reduction of malaria infection among children under five years of age throughout Nigeria

“…Conversely, many states in southern areas of the country had substantially reduced prevalence in 2015 compared to 2010, but no further reduction was seen by 2018, which raises concerns on how to consolidate and continue to reduce malaria after some initial progress. It was previously shown that variation in prevalence among states in the 2015 survey was greater than the sub-national variation seen in comparable DHS surveys of infection in young children other highly endemic West African countries 23 , emphasising the need to understand divergent trends occurring within Nigeria.…”

Geographical and temporal variation in reduction of malaria infection among children under 5 years of age throughout Nigeria

“…Conversely, many states in southern areas of the country had substantially reduced prevalence in 2015 compared with 2010, but no further reduction was seen by 2018, which raises concerns on how to consolidate and continue to reduce malaria after some initial progress. It was previously shown that variation in prevalence among states in the 2015 survey was greater than the subnational variation seen in comparable DHS surveys of infection in young children in other highly endemic West African countries, 23 emphasising the need to understand divergent trends occurring within Nigeria.…”

“…For each of the six major geographical zones of the country, the overall Mantel-Haenszel-adjusted prevalence ratio (PR adj ) is plotted with a purple diamond symbol (with 95% CIs), showing significant overall declines: North-West PR adj =0. 23 emphasising the need to understand divergent trends occurring within Nigeria.…”