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. 2018 Oct 25:60:e62.
doi: 10.1590/S1678-9946201860062.

Spatial analysis of probable cases of dengue fever, chikungunya fever and zika virus infections in Maranhao State, Brazil

Silmery da Silva Brito Costa  1 , Maria Dos Remédios Freitas Carvalho Branco  1 , José Aquino Junior  2 , Zulimar Márita Ribeiro Rodrigues  2 , Rejane Christine de Sousa Queiroz  1 , Adriana Soraya Araujo  2 , Ana Patrícia Barros Câmara  1 , Polyana Sousa Dos Santos  3 , Emile Danielly Amorim Pereira  4 , Maria do Socorro da Silva  5 , Flávia Regina Vieira da Costa  2 , Amanda Valéria Damasceno Dos Santos  6 , Maria Nilza Lima Medeiros  7 , José Odval Alcântara Júnior  8 , Vitor Vieira Vasconcelos  9 , Alcione Miranda Dos Santos  1 , Antônio Augusto Moura da Silva  1
Affiliations

Spatial analysis of probable cases of dengue fever, chikungunya fever and zika virus infections in Maranhao State, Brazil

Silmery da Silva Brito Costa et al. Rev Inst Med Trop Sao Paulo. .

Erratum in

Abstract

Dengue fever, chikungunya fever, and zika virus infections are increasing public health problems in the world, the last two diseases having recently emerged in Brazil. This ecological study employed spatial analysis of probable cases of dengue fever, chikungunya fever, and zika virus infections reported to the National Mandatory Reporting System (SINAN) in Maranhao State from 2015 to 2016. The software GeoDa version 1.10 was used for calculating global and local Moran indices. The global Moran index identified a significant autocorrelation of incidence rates of dengue (I=0.10; p=0.009) and zika (I=0.07; p=0.03). The study found a positive spatial correlation between dengue and the population density (I=0.31; p<0.001) and a negative correlation with the Performance Index of Unified Health System (PIUHS) by basic care coverage (I=-0.08; p=0.01). Regarding chikungunya fever, there were positive spatial correlations with the population density (I=0.06; p=0.03) and the Municipal Human Development Index (MHDI) (I=0.10; p=0.002), and a negative correlation with the Gini index (I=-0.01; p<0.001) and the PIUHS by basic care coverage (I=-0.18; p<0.001). Lastly, we found positive spatial correlations between Zika virus infections and the population density (I=0.13; p=0.005) and the MHDI (I=0.12; p<0.001), as well as a negative correlation with the Gini index (I=-0.11; p<0.001) and the PIUHS by basic care coverage (I=-0.05; p=0.03). Our results suggest that several socio-demographic factors influenced the occurrence of dengue fever, chikungunya fever, and zika virus infections in Maranhao State.

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Conflict of interest statement

CONFLICT OF INTERESTS

The authors declare that there is no conflict of interest.

Figures

Figure 1
Figure 1. Lisa Cluster Map incidence rates of dengue fever, chikungunya fever and zika virus infections and incidence rates of dengue, chikungunya, and zika. Maranhao, 2015-2016.
Figure 2
Figure 2. Lisa Cluster Map of the spatial correlations between the dengue fever incidence rate and the population density, as well as Performance Index of Unified Health System by basic care coverage between the chikungunya fever incidence rate, the population density and Municipal Human Development Index. Maranhao, 2015-2016.
Figure 3
Figure 3. Lisa Cluster Map of the spatial correlations between the chikungunya fever incidence rate, Gini Index and Performance Index of Unified Health System by basic care coverage between the zika virus infections incidence rate, the population density and Municipal Human Development Index. Maranhao, 2015-2016.
Figure 4
Figure 4. Lisa Cluster Map of the spatial correlations between the zika virus infections incidence rate, Gini Index and Performance Index of Unified Health System by basic care coverage between incidence rates of dengue, chikungunya, and zika and the population density, as well as the Performance Index of Unified Health System by basic care coverage. Maranhao, 2015-2016.
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