Building Infestation Index for Aedes aegypti and occurrence of dengue fever in the municipality of Foz do Iguaçu, Paraná, Brazil, from 2001 to 2016

Rivas, Açucena Veleh; Defante, Renata; Delai, Robson Michael; Rios, Jean Avemir; Britto, André da Silva; Leandro, André de Souza; Gonçalves, Daniela Dib

doi:10.1590/0037-8682-0228-2017

Cited by 9 publications

(7 citation statements)

References 8 publications

(12 reference statements)

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“…LIRAa has become mandatory for all municipalities in the country since 2017 32 . Although some studies point that LIRAa produces more agile results, the indexes cannot be used to measure the risk dengue fever occurrence 33 – 35 .…”

Section: Discussionmentioning

confidence: 99%

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

Costa

Branco

Aquino

et al. 2018

Rev. Inst. Med. trop. S. Paulo

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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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Section: Discussionmentioning

confidence: 99%

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

Costa

Branco

Aquino

et al. 2018

Rev. Inst. Med. trop. S. Paulo

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“…Climatic factors, particularly the temperature, precipitation and humidity, could directly and indirectly affect the mosquito density and blood feeding behavior [8,[28][29]. In our study, the average temperature was the main influencing factor of the mosquito density, affecting all the study indices.…”

Section: Plos Onementioning

confidence: 52%

Relationships between traditional larval indices and meteorological factors with the adult density of Aedes albopictus captured by BG-mosquito trap

et al. 2020

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Objectives Larval indices have been used for Ae. albopictus surveillance for many years, while there is limited use in assessing dengue transmission risk and adult mosquito emergence. This study is aimed to explore the relationships between larval indices and the Ae. albopictus density captured by BG-mosquito trap (BG-trap) method, with considering the meteorological factors. Methods Data on larval density, adult mosquito density and meteorology factors were collected in an entomological survey carried out in Quzhou City, Zhejiang Province of China in 2018. The Spearman's rank correlation and Pearson correlation were used for the analysis on the correlation of density indices. Generalized additive models were established to analyze the influencing factors of mosquito density.

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“…The entry and transmission of DENV serotypes in different regions of the country can be explained by the number of municipalities infested with Ae. aegypti mosquitoes, the population mobility, and the rapid and unplanned urbanization that began in the 1990s [125][126][127][128][129] .…”

Section: Discussionmentioning

confidence: 99%

Entry of dengue virus serotypes and their geographic distribution in Brazilian federative units: a systematic review

Bezerra

Sousa

Tauil

et al. 2021

Rev. bras. epidemiol.

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Objective: To describe the entry of Dengue virus (DENV) serotypes in Brazil and its federative units. Methods: A systematic review of studies published between 1980 and 2018 in databases and in the gray literature was performed using descriptors related to the years of entry of the DENV serotypes. Additionally, experts and official sources of information (Brazilian Ministry of Health) were consulted. Results: From 100 publications selected for the systematic review, 26 addressed the entry of DENV serotypes in the North region of the country, 33 in the Northeast, 24 in the Southeast, 14 in the Central-West, and five in the South. DENV-1 and DENV-4 were introduced in the North region in 1981. DENV-2 was introduced in the Southeast in 1990. DENV-3 was introduced in the North in 1999. Conclusion: The rapid expansion of dengue throughout the Brazilian territory was verified from the second half of the 1980s, with the gradual entry of the four serotypes, which resulted in the emergence of epidemics of arbovirus, which are currently verified in the country. Considering the epidemiology of the disease, more information should be disseminated and published in the wide-ranging scientific literature for a better understanding of the spread and circulation of DENV serotypes.

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Building Infestation Index for Aedes aegypti and occurrence of dengue fever in the municipality of Foz do Iguaçu, Paraná, Brazil, from 2001 to 2016

Cited by 9 publications

References 8 publications

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

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

Relationships between traditional larval indices and meteorological factors with the adult density of Aedes albopictus captured by BG-mosquito trap

Entry of dengue virus serotypes and their geographic distribution in Brazilian federative units: a systematic review

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