Fig 1.
Average annual incidence rates of probable cases of DENV, CHIKV and ZIKV, RN, 2016.
The figure was created using the ggplot2 package in R version 4.2.2. The data for dengue, chikungunya, and Zika numbers were retrieved from the SINAN Database, while population numbers, used for the incidence calculations, were obtained from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística—IBGE).
Fig 2.
Incidence of probable cases of Dengue (Fig 2A), Chikungunya (Fig 2B), Zika (Fig 2C) per 100,000 inhabitants according to municipality of residence, RN, 2016. Maps were created using the ggplot2 package in R version 4.2.2. The shapefile for the RN map was downloaded from the Instituto Brasileiro de Geografia e Estatística–IBGE website (https://www.ibge.gov.br/geociencias/organizacao-do-territorio/malhas-territoriais/15774-malhas.html). The data for Dengue, Chikungunya, and Zika numbers were retrieved from the SINAN Database, while population numbers, used for the incidence calculations, were obtained from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística—IBGE).
Table 1.
Description of probable cases of DENV, CHIKV and ZIKV notified in SINAN, RN, 2016.
Table 2.
Description of probable cases of DENV, CHIKV and ZIKV in pregnant women reported in SINAN, RN, 2016.
Table 3.
Molecular analyses in samples from individuals with acute febrile illness reported as suspected arboviruses, RN, 2016.
Fig 3.
Results of molecular analyses on samples from individuals with acute febrile illness reported as suspected arboviruses, according to month of collection, during 2016 in Rio Grande do Norte.
The figure was created using the ggplot2 package in R version 4.2.2.