ArticleEpidemiology and infection2019
Spatial diffusion of the 2015-2016 Zika, dengue and chikungunya epidemics in Rio de Janeiro Municipality, Brazil.
Article in Epidemiology and infection, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Modeling Outbreak Prediction and the Impact of Emergency Vaccination on the 2024-2025 Chikungunya Outbreak in La Réunion.Vaccines · 2025Article
- Complex network analysis of arboviruses in the same geographic domain: Differences and similarities.Chaos, solitons, and fractals · 2023Article
- High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil.Revista de saude publica · 2023Article
- A Model for Highly Fluctuating Spatio-Temporal Infection Data, with Applications to the COVID Epidemic.International journal of environmental research and public health · 2022Article
- The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population.Globalization and health · 2021Article
- Spatiotemporal dynamics, risk areas and social determinants of dengue in Northeastern Brazil, 2014-2017: an ecological study.Infectious diseases of poverty · 2020Article
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Authors and funding
2 authors.
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Abstract
Different countries, especially Brazil, that have faced recurrent dengue epidemics for decades and chikungunya epidemics since 2014, have had to restructure their health services to combat a triple epidemic of arboviruses - Zika, dengue and Chikungunya - transmitted by the same vector, mainly Aedes aegypti, in 2015-2016. Several efforts have been made to better understand these three arboviruses. Spatial analysis plays an important role in the knowledge of disease dynamics. The knowledge of the patterns of spatial diffusion of these three arboviruses during an epidemic can contribute to the planning of surveillance actions and control of these diseases. This study aimed to identify the spatial diffusion processes of these viruses in the context of the triple epidemic in 2015-2016 in Rio de Janeiro, Brazil. Two study designs were used: cross-sectional and ecological. Sequential Kernel maps, nearest-neighbour ratios calculated cumulatively over time, Moran global autocorrelation correlograms, and local autocorrelation changes over time were used to identify spatial diffusion patterns. The results suggested an expansion diffusion pattern for the three arboviruses during 2015-2016 in Rio de Janeiro. These findings can be considered for more effective control measures and for new studies on the dynamics of these three arboviruses.
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