Research Article: Community context and sub-neighborhood scale detail to explain dengue, chikungunya and Zika patterns in Cali, Colombia

Date Published: August 2, 2017

Publisher: Public Library of Science

Author(s): Amy R. Krystosik, Andrew Curtis, Paola Buritica, Jayakrishnan Ajayakumar, Robert Squires, Diana Dávalos, Robinson Pacheco, Madhav P. Bhatta, Mark A. James, Shannon L. LaDeau.


Cali, Colombia has experienced chikungunya and Zika outbreaks and hypoendemic dengue. Studies have explained Cali’s dengue patterns but lack the sub-neighborhood-scale detail investigated here.

Spatial-video geonarratives (SVG) with Ministry of Health officials and Community Health Workers were collected in hotspots, providing perspective on perceptions of why dengue, chikungunya and Zika hotspots exist, impediments to control, and social outcomes. Using spatial video and Google Street View, sub-neighborhood features possibly contributing to incidence were mapped to create risk surfaces, later compared with dengue, chikungunya and Zika case data.

SVG captured insights in 24 neighborhoods. Trash and water risks in Calipso were mapped using SVG results. Perceived risk factors included proximity to standing water, canals, poverty, invasions, localized violence and military migration. These risks overlapped case density maps and identified areas that are suitable for transmission but are possibly underreporting to the surveillance system.

Resulting risk maps with local context could be leveraged to increase vector-control efficiency- targeting key areas of environmental risk.

Partial Text

This study was approved by the appropriate local (Universidad ICESI #061) and University institutional review boards (Kent State University #15–529). Human case data are presented at the aggregate neighborhood level and individuals are not identifiable.

SVG rides were used to capture insights from “expert” passengers who had detailed information about dengue, chikungunya and Zika in 24 neighborhoods of Cali, Colombia. Note, GPS problems occurred in some neighborhoods, while in others the amount of commentary was too short for useful risk mapping. Only the “successful’ SVG are reported here. Interviewees included mosquito control experts, public health officials, and local leaders. For some rides, more than one expert was in the vehicle. Each ride began with the reading of an IRB consent script and obtaining informed consent. The path of the SVG was determined by the researcher selecting the neighborhood (using the hotspot and coldspot maps of Figs 2 and 3 as a guide), with the expert identifying which features were important to visit inside the area of study. In all cases the expert had a solid working knowledge of the neighborhood being studied. Fig 5 shows the overall spatial distribution of the rides. While most neighborhoods were covered only once, there were a few occasions where the neighborhood was repeatedly examined (Calipso) up to three times.

There is a rich tradition of spatial research on mosquito-vectored diseases, and especially dengue. Cali, Colombia is a large urban area with hypoendemic dengue transmission with recent outbreaks of Zika and chikungunya. Several studies have focused on the dengue, Zika and chikungunya situation in Colombia [11–21], ranging from disease patterns to the identification of fine scale environmental and social risks [29, 31–33]. Even in this well-studied urban environment, there is still a lack of sub-neighborhood scale investigations enriched with local context, which arguably is what is needed to design effective control interventions. We have addressed this deficiency using expert insight captured with SVG for various neighborhoods of the city. In addition, we have mapped, compared and contrasted risk features digitized from two similar data sources: SV and GSV.

This study has revealed the types of risks present at a geographic scale not commonly analyzed with regards to dengue or other mosquito-borne diseases. The combined SV and SVG approach not only can be used to identify potential risks, but also, when overlaid with actual disease cases, can be used as an ongoing data resource to determine what was happening inside each hotspot, what it looks like, and how it is described. This detail is invaluable when targeting limited intervention resources. Given the insights revealed from the SV and SVG, improvements in drainage and road surface quality might have an immediate impact on disease reduction. However, as only the main (commercial) roads were driven, a return visit might include all residential streets to assess the conditions closer to where people live. People in the general vicinity should also be educated as to the real disease risk and encouraged to use window screens, mosquito repellant or at least wear protective clothing while outside.




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