Identifying urban hotspots of dengue, chikungunya, and Zika transmission in Mexico to support risk stratification efforts: a spatial analysis

Abstract

Abstract Background: Effective Aedes aegypti control is limited, in part, by the difficulty in achieving sufficient intervention coverage. To maximise the effect of vector control, areas with persistently high numbers of Aedes-borne disease cases could be identified and prioritised for preventive interventions. We aimed to identify persistent Aedes-borne disease hotspots in cities across southern Mexico.

Methods: In this spatial analysis, geocoded cases of dengue, chikungunya, and Zika from nine endemic Mexican cities were aggregated at the census-tract level. We included cities that were located in southern Mexico (the arbovirus endemic region of Mexico), with a high burden of dengue cases (ie, more than 5000 cases reported during a 10-year period), and listed as high priority for the Mexican dengue control and prevention programme. The Getis-Ord Gi(d) statistic was applied to yearly slices of the dataset to identify spatial hotspots of each disease in each city. We used Kendalls W coefficient to quantify the agreement in the distribution of each virus.

Findings: 128 507 dengue, 4752 chikungunya and 25 755 Zika clinical cases were reported between Jan 1, 2008, and Dec 31, 2016. All cities showed evidence of transmission heterogeneity, with a mean of 176 (SD 47) of their total area identified as persistent disease hotspots. Hotspots accounted for 256 (SD 97; range 128-430) of the population and 321 (105; 196-505) of all Aedes-borne disease cases reported. We found an overlap between hotspots of 617 for dengue and Zika and 533 for dengue and chikungunya. Dengue hotspots in 2008-16 were significantly associated with dengue hotspots detected during 2017-20 in five of the nine cities. Heads of vector control confirmed hotspot areas as problem zones for arbovirus transmission.

Interpretation: This study provides evidence of the overlap of Aedes-borne diseases within geographical hotspots and a methodological framework for the stratification of arbovirus transmission risk within urban areas, which can guide the implementation of surveillance and vector control.