Emerging arboviruses, old patterns? Observations on dengue, Chikungunya, and Zika in a dengue-endemic tropical state Open Access

Taylor, Marissa (Spring 2018)

Permanent URL: https://etd.library.emory.edu/concern/etds/6108vb321?locale=en
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Abstract

Globalization and urbanization have contributed to the emergence of arboviruses such as Chikungunya and Zika. In areas with endemic arboviruses, existing data may be able to predict novel arbovirus patterns because of the shared mosquito vector, Aedes aegypti. In Mexico, a study of the Yucatán state’s capital, Mérida, recently found dengue hot spots to recur as hot spots for Chikungunya and Zika. Analyses presented here are a follow-up to those findings. Statewide passive surveillance has been conducted for dengue since 2008, Chikungunya since 2015, and Zika since 2016. Epidemic curves were created from all confirmed and probable cases. Index cases of DENV-3, Chikungunya, and Zika were identified, and residence and travel history were described for early cases of Chikungunya and Zika. Data include the case’s reported residence, and these addresses have been geocoded for around 80% of observations. Where spatial data were available, points were mapped to determine which were within the state’s boundary and within urban centers. For all viruses and years, 52,257 of 56,152 (93%) points fell within the state’s boundary. Of those, 90% were urban and 10% rural. Age characteristics were described by year and virus for all cases in the state boundary. For dengue, serotype presence was mapped by number of cases identified per municipality. Municipalities were also used to describe annual incidence for each virus (dengue, Chikungunya, and Zika). To address incomplete years of data (due to invasion or incomplete geocoding), incidence was also described monthly by urban center. To define local and global clustering and identify hot spots, the local Getis-Ord G* and global weighted k-function tests were performed for urban center centroid points for case counts and cumulative incidence for each virus. Of the 127 urban centers, 40 (31%) were identified as hot spots. Cities around Mérida were common hot spots across viruses. Spatial analyses should be utilized for their ability to identify recurring problem areas. As arboviruses continue to emerge, robust surveillance and analysis tools are critical.

Table of Contents

Table of Contents

Introduction …………………………………………………..1

Methods ………………………………………………………6

Results ………………………………………………………12

Discussion…………………………………………………….17

References…………………………………………………..22

Tables………………………………………………………26

Figures………………………………………………………..29

 

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