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. 2022 Aug 23;16(8):e0010334.
doi: 10.1371/journal.pntd.0010334. eCollection 2022 Aug.

Spatio-temporal clusters and patterns of spread of dengue, chikungunya, and Zika in Colombia

Affiliations

Spatio-temporal clusters and patterns of spread of dengue, chikungunya, and Zika in Colombia

Laís Picinini Freitas et al. PLoS Negl Trop Dis. .

Abstract

Background: Colombia has one of the highest burdens of arboviruses in South America. The country was in a state of hyperendemicity between 2014 and 2016, with co-circulation of several Aedes-borne viruses, including a syndemic of dengue, chikungunya, and Zika in 2015.

Methodology/principal findings: We analyzed the cases of dengue, chikungunya, and Zika notified in Colombia from January 2014 to December 2018 by municipality and week. The trajectory and velocity of spread was studied using trend surface analysis, and spatio-temporal high-risk clusters for each disease in separate and for the three diseases simultaneously (multivariate) were identified using Kulldorff's scan statistics. During the study period, there were 366,628, 77,345 and 74,793 cases of dengue, chikungunya, and Zika, respectively, in Colombia. The spread patterns for chikungunya and Zika were similar, although Zika's spread was accelerated. Both chikungunya and Zika mainly spread from the regions on the Atlantic coast and the south-west to the rest of the country. We identified 21, 16, and 13 spatio-temporal clusters of dengue, chikungunya and Zika, respectively, and, from the multivariate analysis, 20 spatio-temporal clusters, among which 7 were simultaneous for the three diseases. For all disease-specific analyses and the multivariate analysis, the most-likely cluster was identified in the south-western region of Colombia, including the Valle del Cauca department.

Conclusions/significance: The results further our understanding of emerging Aedes-borne diseases in Colombia by providing useful evidence on their potential site of entry and spread trajectory within the country, and identifying spatio-temporal disease-specific and multivariate high-risk clusters of dengue, chikungunya, and Zika, information that can be used to target interventions.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Number of notified dengue, chikungunya, and Zika cases by week of first symptoms, Colombia, 2014–2018.
Fig 2
Fig 2
Chikungunya (A) and Zika (B) spread across Colombia, 2014–2018. The angle of the arrowhead represents the direction of spread. Yellow arrowheads represent the first cases observed in the data. Base layer source: GADM (https://gadm.org/), available at https://www.diva-gis.org/gdata.
Fig 3
Fig 3
Space-time clusters ranked by likelihood ratio* (A-C), year of start date (D-F), duration in weeks (G-H) and relative risk (J-L) for dengue (1st column), chikungunya (2nd column) and Zika (3rd column), Colombia, 2014–2018. * The first cluster is the most likely cluster, i.e., with the maximum likelihood ratio. Base layer source: GADM (https://gadm.org/), available at https://www.diva-gis.org/gdata.
Fig 4
Fig 4
Temporal distribution of cases inside each cluster of dengue (A), chikungunya (B) and Zika (C), Colombia, 2014–2018. Orange bands represent the time period at which the cluster was detected. Clusters are ranked by likelihood ratio, being the first cluster the most likely cluster, i.e., with the maximum likelihood ratio.
Fig 5
Fig 5
Multivariate space-time clusters of dengue, chikungunya and Zika ranked by likelihood ratio* (A), diseases (B), year of start date (C), duration in weeks (D) and relative risk for each disease (E-G), Colombia, 2014–2018. * The first cluster is the most likely cluster, i.e., with the maximum likelihood ratio. Base layer source: GADM (https://gadm.org/), available at https://www.diva-gis.org/gdata.

References

    1. Lambrechts L, Scott TW, Gubler DJ. Consequences of the Expanding Global Distribution of Aedes albopictus for Dengue Virus Transmission. Halstead SB, editor. PLoS Negl Trop Dis. 2010;4: e646. doi: 10.1371/journal.pntd.0000646 - DOI - PMC - PubMed
    1. Mulligan K, Dixon J, Joanna Sinn C-L, Elliott SJ. Is dengue a disease of poverty? A systematic review. Pathog Glob Health. 2015;109: 10–18. doi: 10.1179/2047773214Y.0000000168 - DOI - PMC - PubMed
    1. Tapia-Conyer R, Méndez-Galván JF, Gallardo-Rincón H. The growing burden of dengue in Latin America. J Clin Virol. 2009;46: S3–S6. doi: 10.1016/S1386-6532(09)70286-0 - DOI - PubMed
    1. WHO. Dengue and severe dengue. In: World Health Organization; [Internet]. 2 Feb 2018. [cited 15 Jul 2018]. Available: http://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue
    1. Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al.. The global distribution and burden of dengue. Nature. 2013;496: 504–507. doi: 10.1038/nature12060 - DOI - PMC - PubMed

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