Dataset Information

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

ABSTRACT: BACKGROUND: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. METHODS: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. RESULTS: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. CONCLUSION:Resulting risk maps with local context could be leveraged to increase vector-control efficiency- targeting key areas of environmental risk.

SUBMITTER: Krystosik AR

PROVIDER: S-EPMC5540594 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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

Krystosik Amy R AR Curtis Andrew A Buritica Paola P Ajayakumar Jayakrishnan J Squires Robert R Dávalos Diana D Pacheco Robinson R Bhatta Madhav P MP James Mark A MA

PloS one 20170802 8

<h4>Background</h4>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.<h4>Methods</h4>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 ...[more]

PMID: 28767730

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Project description:Dengue, chikungunya, and Zika virus epidemics transmitted by Aedes aegypti mosquitoes have recently (re)emerged and spread throughout the Americas, Southeast Asia, the Pacific Islands, and elsewhere. Understanding how environmental conditions affect epidemic dynamics is critical for predicting and responding to the geographic and seasonal spread of disease. Specifically, we lack a mechanistic understanding of how seasonal variation in temperature affects epidemic magnitude and duration. Here, we develop a dynamic disease transmission model for dengue virus and Aedes aegypti mosquitoes that integrates mechanistic, empirically parameterized, and independently validated mosquito and virus trait thermal responses under seasonally varying temperatures. We examine the influence of seasonal temperature mean, variation, and temperature at the start of the epidemic on disease dynamics. We find that at both constant and seasonally varying temperatures, warmer temperatures at the start of epidemics promote more rapid epidemics due to faster burnout of the susceptible population. By contrast, intermediate temperatures (24-25°C) at epidemic onset produced the largest epidemics in both constant and seasonally varying temperature regimes. When seasonal temperature variation was low, 25-35°C annual average temperatures produced the largest epidemics, but this range shifted to cooler temperatures as seasonal temperature variation increased (analogous to previous results for diurnal temperature variation). Tropical and sub-tropical cities such as Rio de Janeiro, Fortaleza, and Salvador, Brazil; Cali, Cartagena, and Barranquilla, Colombia; Delhi, India; Guangzhou, China; and Manila, Philippines have mean annual temperatures and seasonal temperature ranges that produced the largest epidemics. However, more temperate cities like Shanghai, China had high epidemic suitability because large seasonal variation offset moderate annual average temperatures. By accounting for seasonal variation in temperature, the model provides a baseline for mechanistically understanding environmental suitability for virus transmission by Aedes aegypti. Overlaying the impact of human activities and socioeconomic factors onto this mechanistic temperature-dependent framework is critical for understanding likelihood and magnitude of outbreaks.

Dataset Information

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

Publications

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

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