Difusão espaço-tempo do dengue no Município do Rio de Janeiro, Brasil, no período de 2000-2013

Xavier, Diego Ricardo; Magalhães, Mônica de Avelar Figueirêdo Mafra; Gracie, Renata; Reis, Izabel Cristina dos; Matos, Vanderlei Pascoal de; Barcellos, Christovam

doi:10.1590/0102-311x00186615

Cited by 30 publications

(37 citation statements)

References 34 publications

(48 reference statements)

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“…As dengue has been endemic in Rio de Janeiro for the last three decades and Janeiro has already been identified as a hot spot for dengue and as a key region for dengue diffusion. Previous studies also identified Catumbi, a neighbourhood in the Downtown area, as a high-risk location for dengue [38,39]. In our findings, Catumbi comprised the most likely chikungunya cluster, the second most likely cluster for dengue and the third most likely for Zika.…”

Section: Dengue Chikungunya and Zika Multivariate Clusterssupporting

confidence: 75%

Space-time clusters of dengue, chikungunya, and Zika cases in the city of Rio de Janeiro

Freitas

Cruz

Lowe

et al. 2019

Preprint

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Brazil is a dengue-endemic country where all four dengue virus serotypes circulate and cause seasonal epidemics. Recently, chikungunya and Zika viruses were also introduced. In Rio de Janeiro city, the three diseases co-circulated for the first time in 2015-2016, resulting in what is known as the 'triple epidemic'. In this study, we identify space-time clusters of dengue, chikungunya, and Zika, to understand the dynamics and interaction between these simultaneously circulating arboviruses in a densely populated and heterogeneous city.We conducted a spatio-temporal analysis of weekly notified cases of the three diseases in Rio de Janeiro city (July 2015 -January 2017), georeferenced by 160 neighbourhoods, using Kulldorff's scan statistic with discrete Poisson probability models.There were 26549, 13662, and 35905 notified cases of dengue, chikungunya, and Zika, respectively.The 17 dengue clusters and 15 Zika clusters were spread all over the city, while the 14 chikungunya clusters were more concentrated in the North and Downtown areas. Zika clusters persisted over a longer period of time. The multivariate scan statistic -used to analyse the three diseases simultaneously -detected 17 clusters, nine of which included all three diseases. This is the first study exploring space-time clustering of dengue, chikungunya, and Zika in an intraurban area. In general, the clusters did not coincide in time and space. This is probably the result of the competition between viruses for host resources, and of vector-control attitudes promoted by previous arbovirus outbreaks. The main affected area -the North region -is characterised by a combination of high population density and low human development index, highlighting the importance of targeting interventions in this area. Spatio-temporal scan statistics have the potential to direct interventions to high-risk locations in a timely manner and should be considered as part of the municipal surveillance routine as a tool to optimize prevention strategies. an arboviral disease transmitted by Aedes mosquitoes, has been endemic in Brazil for decades, but vector-control strategies have not led to a significant reduction in the disease burden and were not sufficient to prevent chikungunya and Zika entry and establishment in the country. In Rio de Janeiro city, the first Zika and chikungunya epidemics were detected between 2015-2016, coinciding with a dengue epidemic. Understanding the behaviour of these diseases in a triple epidemic scenario is a necessary step for devising better interventions for prevention and outbreak response. We applied scan statistics analysis to detect spatio-temporal clustering for each disease separately and for all three simultaneously. In general, clusters were not detected in the same locations and time periods, possibly due to competition between viruses for host resources, and change in behaviour of the human population (e.g. intensified vector-control activities in response to increasing cases of a particular arbovirus). Neighbourhoods with high populati...

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Section: Dengue Chikungunya and Zika Multivariate Clusterssupporting

confidence: 75%

Space-time clusters of dengue, chikungunya, and Zika cases in the city of Rio de Janeiro

Freitas

Cruz

Lowe

et al. 2019

Preprint

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“…Using mapping techniques to study vector-borne disease epidemiology has proven crucial, as seen with previous research on dengue virus [ 15 ] and chikungunya [ 16 ]. These health geography studies can identify disease propagation patterns and high-risk areas, then model forecasts allowing inferences for the determinants of these outcomes [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Zika virus infection and microcephaly: Evidence regarding geospatial associations

et al. 2018

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BackgroundAlthough the Zika virus (ZIKV) epidemic ceased to be a public health emergency by the end of 2016, studies to improve knowledge about this emerging disease are still needed, especially those investigating a causal relationship between ZIKV in pregnant women and microcephaly in neonates. However, there are still many challenges in describing the relationship between ZIKV and microcephaly. The few studies focusing on the epidemiological profile of ZIKV and its changes over time are largely limited to systematic reviews of case reports and dispersal mapping of ZIKV spread over time without quantitative methods to analyze patterns and their covariates. Since Brazil has been at the epicenter of the ZIKV epidemic, this study examines the geospatial association between ZIKV and microcephaly in Brazil.MethodsOur study is categorized as a retrospective, ecological study based on secondary databases. Data were obtained from January to December 2016, from the following data sources: Brazilian System for Epidemiological Surveillance, Disease Notification System, System for Specialized Management Support, and Brazilian Institute of Geography and Statistics. Data were aggregated by municipality. Incidence rates were estimated per 100,000 inhabitants. Analyses consisted of mapping the aggregated incidence rates of ZIKV and microcephaly, followed by a Getis-Ord-Gi spatial cluster analysis and a Bivariate Local Moran’s I analysis.ResultsThe incidence of ZIKV cases is changing the virus’s spatial pattern, shifting from Brazil’s Northeast region to the Midwest and North regions. The number of municipalities in clusters of microcephaly incidence is also shifting from the Northeast region to the Midwest and North, after a time lag is considered. Our findings suggest an increase in microcephaly incidence in the Midwest and North regions, associated with high levels of ZIKV infection months before.ConclusionThe greatest burden of microcephaly shifted from the Northeast to other Brazilian regions at the beginning of 2016. Brazil’s Midwest region experienced an increase in microcephaly incidence associated with ZIKV incidence. This finding highlights an association between an increase in ZIKV infection with a rise in microcephaly cases after approximately three months.

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“…Além dessa característica urbana, a sazonalidade do clima na região, marcado por uma estação seca e outra chuvosa, também influencia na dinâmica da dengue (SIQUEIRA et al,2017). Portanto, a análise do comportamento espaço-temporal da dengue é de grande importância, uma vez que, por se tratar de uma doença que tem uma forte dinâmica sazonal, é esperado que esses processos se manifestem no espaço por ondas de espalhamento, condicionadas pela mobilidade da população, sua imunização à doença, a presença do vetor e pelas condições do ambiente (XAVIER et al, 2017). Conhecer de maneira profunda a dinâmica da doença, particularmente em grandes centros urbanos, pode contribuir para as ações de controle e vigilância, otimizando recursos, apoiada pelo uso dos sistemas de informações geográficas (SIG), o que pode oferecer subsídios mais concretos, e com maior rapidez, sobre informações quantitativas e qualitativas (PETTA; NASCI-MENTO, 2000;CAIAFFA et al, 2008).…”

Section: Análise Espacial Das Ondas Epidêmicas De Dengue Por Sig No Dunclassified

“…Para a realização deste estudo, os trabalhos de Catão (2016), Caiaffa et.al (2008) e Xavier et al (2017) foram as principais referências e a partir destes foi feita a construção da metodologia. Os dados utilizados foram disponibilizados pela Secretaria de Saúde do Distrito Federal (SES-DF).…”

Section: Procedimentos Executadosunclassified

“…Analisando o comportamento das curvas, nas regiões citadas, pode-se verificar uma constatação que Xavier et al (2017) apresentaram em seu estudo. Os autores averiguaram que nas zonas em que se verificou que, os meses epidêmicos se iniciaram nos primeiros meses do ano, ocorreram epidemias mais intensas com maior capacidade de espalhamento.…”

Section: Figura 3 Mapeamento Do Início Das Alças Epidêmicas Nas Zbs Dunclassified

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Abordagens Geográfica da Vigilância, Prevenção e Promoção da Saúde

2019

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Difusão espaço-tempo do dengue no Município do Rio de Janeiro, Brasil, no período de 2000-2013

Cited by 30 publications

References 34 publications

Space-time clusters of dengue, chikungunya, and Zika cases in the city of Rio de Janeiro

Space-time clusters of dengue, chikungunya, and Zika cases in the city of Rio de Janeiro

Zika virus infection and microcephaly: Evidence regarding geospatial associations

Abordagens Geográfica da Vigilância, Prevenção e Promoção da Saúde

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