| Author | Santana, Laís Santos | |
| Author | Braga, Jose Ueleres | |
| Access date | 2020-06-04T20:15:23Z | |
| Available date | 2020-06-04T20:15:23Z | |
| Document date | 2020 | |
| Citation | SANTANA, Laís Santos; BRAGA, Jose Ueleres. Spatial diffusion of Zika fever epidemics in the Municipality of Salvador-Bahia, Brazil, in 2015-2016: does Zika fever have the same spread pattern as Dengue and Chikungunya fever epidemics? Revista da Sociedade Brasileira de Medicina Tropical, v. 53, p. 1-11, 2020. | pt_BR |
| ISSN | 0037-8682 | pt_BR |
| URI | https://www.arca.fiocruz.br/handle/icict/41542 | |
| Language | eng | pt_BR |
| Publisher | Sociedade Brasileira de Medicina Tropical | pt_BR |
| Rights | open access | pt_BR |
| Subject in Portuguese | Zika Virus | pt_BR |
| Subject in Portuguese | Vírus Chikungunya | pt_BR |
| Subject in Portuguese | Dengue | pt_BR |
| Subject in Portuguese | Arbovirus | pt_BR |
| Title | Spatial diffusion of Zika fever epidemics in the Municipality of Salvador-Bahia, Brazil, in 2015-2016: does Zika fever have the same spread pattern as Dengue and Chikungunya fever epidemics? | pt_BR |
| Type | Article | pt_BR |
| DOI | 10.1590/0037-8682-0563-2019 | |
| Abstract | INTRODUCTION: The recent emergence and rapid spread of Zika and Chikungunya fevers in Brazil, occurring simultaneously to a Dengue fever epidemic, together represent major challenges to public health authorities. This study aimed to identify and compare the 2015-2016 spatial diffusion pattern of Zika, Chikungunya, and Dengue epidemics in Salvador-Bahia. METHODS: We used two study designs comprising a cross-sectional-to-point pattern and an ecological analysis of lattice data. Residential addresses involving notified cases were geocoded. We used four spatial diffusion analysis techniques: (i) visual inspection of the sequential kernel and choropleth map, (ii) spatial correlogram analysis, (iii) spatial local autocorrelation (LISA) changes analysis and, (iv) nearest neighbor index (NNI) modeling. RESULTS: Kernel and choropleth maps indicated that arboviruses spread to neighboring areas near the first reported cases and occupied these new areas, suggesting a diffusion expansion pattern. A greater case density occurred in central and western areas. In 2015 and 2016, the NNI best-fit model had an S-curve compatible with an expansion pattern for Zika (R2 = 0.94; 0.95), Chikungunya (R2 = 0.99; 0.98) and Dengue (R2 = 0.93; 0.99) epidemics, respectively. Spatial correlograms indicated a decline in spatial lag autocorrelations for the three diseases (expansion pattern). Significant LISA changes suggested different diffusion patterns, although a small number of changes were detected. CONCLUSIONS: These findings indicate diffusion expansion, a unique spatial diffusion pattern of Zika, Chikungunya, and Dengue epidemics in Salvador-Bahia, namely. Knowing how and where arboviruses spread in Salvador-Bahia can help improve subsequent specific epidemic control interventions. | pt_BR |
| Affilliation | Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Sergio Arouca. Programa de Pós-Graduação Stricto Sensu em Epidemiologia em Saúde Pública. Rio de Janeiro, RJ, Brasil. | pt_BR |
| Affilliation | Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Sergio Arouca. Departamento de Epidemiologia e Métodos Quantitativos. Rio de Janeiro, RJ, Brasil / Universidade do Estado do Rio de Janeiro. Instituto de Medicina Social. Rio de Janeiro, RJ, Brasil. | pt_BR |
| Subject | Zika | pt_BR |
| Subject | Chikungunya | pt_BR |
| Subject | Dengue | pt_BR |
| Subject | Arboviruses | pt_BR |
| Subject | Spatial Diffusion | pt_BR |
| DeCS | Zika Virus | pt_BR |
| DeCS | Chikungunya Virus | pt_BR |
| DeCS | Dengue | pt_BR |
| DeCS | Arboviruses | pt_BR |
| e-ISSN | 1678-9849 | |
