Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis

Malaria Journal

Research

Francisco G. S. Oliveira¹  Mônica da Silva-Nunes²  Gilberto G. Moresco³  Tiago F. M. Lima⁴  Nildimar A. Honório⁵  Oswaldo G. Cruz⁶  Thais I. S. Riback⁶  Cláudia T. Codeço⁶  Raquel M. Lana⁷ 

[1] Campus Cruzeiro do Sul, Universidade Federal do Acre, Estrada do Canela Fina, s/n, 69980-000, Cruzeiro do Sul, AC, Brazil;Centro de Ciências da Saúde, Universidade Federal do Acre, Campus Universitário-BR 364, km 4-Distrito Industrial, 69920-900, Rio Branco, AC, Brazil;Coordenação Geral dos Programas Nacionais de Controle e Prevenção da Malária e das Doenças transmitidas pelo Aedes, Departamento de Vigilância das Doenças Transmissíveis, Secretaria de Vigilância em Saúde-Ministério da Saúde, SRTV 702, Via W 5 Norte, Ed. PO700-6 andar, 70723-040, Brasília, DF, Brazil;Laboratório de Engenharia e Desenvolvimento de Sistemas, Departamento de Computação e Sistemas, Instituto de Ciências Exatas e Aplicadas, Universidade Federal de Ouro Preto., Rua 36, n. 115, Loanda, 35931-008, João Monlevade, MG, Brazil;Laboratório de Mosquitos Transmissores de Hematozoários-Lathema, Instituto Oswaldo Cruz, FIOCRUZ, Avenida Brasil, 4365, Manguinhos, 21040-360, Rio de Janeiro, RJ, Brazil;Núcleo Operacional Sentinela de Mosquitos Vetores-Nosmove/FIOCRUZ, Avenida Brasil, 4365, Manguinhos, 21040-360, Rio de Janeiro, RJ, Brazil;Programa de Computação Científica, Fundação Oswaldo Cruz, Residência Oficial, Avenida Brasil, 4365, Manguinhos, 21040-360, Rio de Janeiro, RJ, Brazil;Programa de Pós-Graduação em Epidemilogia em Saúde Pública, Escola Nacional de Saúde Pública Sérgio Arouca, Fundação Oswaldo Cruz, Rua Leopoldo Bulhões, 1480, Manguinhos, 21041-210, Rio de Janeiro, RJ, Brazil;Programa de Computação Científica, Fundação Oswaldo Cruz, Residência Oficial, Avenida Brasil, 4365, Manguinhos, 21040-360, Rio de Janeiro, RJ, Brazil;

关键词: Urban malaria;    Rurality;    Multiple correspondence analysis;    Amazon;    Micro-epidemiology;   

DOI  :  10.1186/s12936-017-2045-z

 received in 2017-07-04, accepted in 2017-09-23,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundIn the process of geographical retraction of malaria, some important endemicity pockets remain. Here, we report results from a study developed to obtain detailed community data from an important malaria hotspot in Latin America (Alto Juruá, Acre, Brazil), to investigate the association of malaria with socioeconomic, demographic and living conditions.MethodsA household survey was conducted in 40 localities (n = 520) of Mâncio Lima and Rodrigues Alves municipalities, Acre state. Information on previous malaria, schooling, age, gender, income, occupation, household structure, habits and behaviors related to malaria exposure was collected. Multiple correspondence analysis (MCA) was applied to characterize similarities between households and identify gradients. The association of these gradients with malaria was assessed using regression.ResultsThe first three dimensions of MCA accounted for almost 50% of the variability between households. The first dimension defined an urban/rurality gradient, where urbanization was associated with the presence of roads, basic services as garbage collection, water treatment, power grid energy, and less contact with the forest. There is a significant association between this axis and the probability of malaria at the household level, OR = 1.92 (1.23–3.02). The second dimension described a gradient from rural settlements in agricultural areas to those in forested areas. Access via dirt road or river, access to electricity power-grid services and aquaculture were important variables. Malaria was at lower risk at the forested area, OR = 0.55 (1.23–1.12). The third axis detected intraurban differences and did not correlate with malaria.ConclusionsLiving conditions in the study area are strongly geographically structured. Although malaria is found throughout all the landscapes, household traits can explain part of the variation found in the odds of having malaria. It is expected these results stimulate further discussions on modelling approaches targeting a more systemic and multi-level view of malaria dynamics.

【 授权许可】

CC BY   
© The Author(s) 2017

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