The top 1%: quantifying the unequal distribution of malaria in Brazil

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Abstract

Background: As malaria endemic countries strive towards elimination, intensified spatial heterogeneities of local transmission could undermine the effectiveness of traditional intervention policy. Methods: The dynamic nature of large-scale and long-term malaria heterogeneity across Brazilian Amazon basin were explored by (1) exploratory analysis of Brazil’s rich clinical malaria reporting database from 2004 to 2018, and (2) adapting Gini coefficient to study the distribution of malaria cases in the region. Results: As transmission declined, heterogeneity increased with cases clustering into smaller subpopulations across the territory. In 2004, the 1% of health units with the greatest number of cases accounted for 46% of all reported Plasmodium vivax cases, whereas in 2018 52% of P. vivax cases occurred in the top 1% of health units. Plasmodium falciparum had lower levels of transmission than P. vivax, and also had greater levels of heterogeneity with 75% of cases occurring in the top 1% of health units. Age and gender stratification of cases revealed peri-domestic and occupational exposure settings that remained relatively stable. Conclusion: The pathway to decreasing incidence is characterized by higher proportions of cases in males, in adults, due to importation, and caused by P. vivax. Characterization of spatio-temporal heterogeneity and risk groups can aid stratification for improved malaria control towards elimination with increased heterogeneity potentially allowing for more efficient and cost-effective targeting. Although distinct epidemiological phenomena were clearly observed as malaria transmission declines, the authors argue that there is no canonical path to malaria elimination and a more targeted and dynamic surveillance will be needed if Brazil decides to adopt the elimination target.

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Lana, R., Nekkab, N., Siqueira, A. M., Peterka, C., Marchesini, P., Lacerda, M., … Villela, D. (2021). The top 1%: quantifying the unequal distribution of malaria in Brazil. Malaria Journal, 20(1). https://doi.org/10.1186/s12936-021-03614-4

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