The social and spatial ecology of dengue presence and burden during an outbreak in Guayaquil, Ecuador, 2012

Abstract

Highlights• In 2012, Guayaquil, Ecuador had a large outbreak of dengue cases • Dengue case presence and burden exhibited spatial heterogeneity at the census block level • Social-ecological drivers of case presence and burden differed in this outbreak, highlighting the need to model both types of epidemiological data • Access to municipal resources such as garbage collection and piped water had counterintuitive relationships with dengue presence, but poor housing, garbage collection and remittances correlated to dengue burden. • Our findings inform risk mapping and vector control and surveillance allocation, relevant to this and other concurrent emergent epidemics such as chikungunya and zika AbstractDengue fever, a mosquito-borne viral disease, is an ongoing public health problem in Ecuador and throughout the tropics, yet we have a limited understanding of the disease transmission dynamics in these regions. The objective of this study was to characterize the spatial dynamics and social-ecological risk factors associated with a recent dengue outbreak in Guayaquil,Ecuador. We examined georeferenced dengue cases (n = 4,248) and block-level census data variables to identify potential social-ecological variables associated with the presence and burden of dengue fever in Guayaquil in 2012. We applied LISA and Moran's I tests to analyze hotspots of dengue cases and used multimodel selection in R computing language to identify covariates associated with dengue incidence at the census zone level. Significant hotspots of dengue transmission were found near the North Central and Southern portions of Guayaquil. Significant risk factors for presence of dengue included poor housing conditions (e.g., poor condition of ceiling, floors, and walls), access to paved roads, and receipt of remittances. Counterintuitive positive correlations with dengue presence were observed with several municipal services such as garbage collection and access to piped water. Risk factors for the increased burden of dengue included poor housing conditions, garbage collection, receipt of remittances, and sharing a property with more than one household. Social factors such as education and household demographics were negatively correlated with increased dengue burden. Our findings elucidate underlying differences with dengue presence and burden and indicate the potential to develop dengue vulnerability and risk maps to inform disease prevention and control -information that is also relevant for emerging epidemics of chikungunya and zika.

Hidden heterogeneity and its influence on dengue vaccination impact

“…At the same time, impact under even intervention coverage was considerably higher than under scenarios in which the intervention was allocated preferentially to the low-transmission community. Due to the possibility that socioeconomic factors could underlie a coupling between heterogeneities (48) in DENV transmission (19; 20; 21; 22) and access to dengue vaccines (24; 25; 49), it will be important for measures to be taken to ensure that coverage of CYD-TDV following pre-vaccination screening is no less than even, if not targeted preferentially to communities that contribute disproportionately to transmission.…”

“…DENV seroprevalence ranged 56-77% across neighborhoods of Rio de Janeiro, Brazil (15),74-91% across neighborhoods of Recife, Brazil (16), 67-90% across neighborhoods in Iquitos, Peru (17), and 21-100% between adjacent blocks in Maracay, Venezuela (18). Drivers of variability in DENV seroprevalence at this spatial scale can include a number of factors associated with socioeconomic differences, such as housing quality, free-standing water, open containers, and infrequent waste removal (19; 20; 21; 22).…”

Spatiotemporal Tools for Emerging and Endemic Disease Hotspots in Small Areas: An Analysis of Dengue and Chikungunya in Barbados, 2013–2016

“…16,17 Although large-scale climatological factors undoubtedly play a dominant role in driving outbreaks of mosquito-borne illness, this plays out at the local scale as a function of the human landscape. 18,19 Therefore, understanding the local distribution of human cases is also necessary for understanding patterns of exposure risk and guiding vector abatement strategies.…”

“…The role of household-level characteristics, such as housing condition and water storage habits, in promoting mosquito production has been repeatedly demonstrated. 18,19 In some instances, favorable microhabitats enable mosquitoes, and subsequently disease transmission, to persist despite general unfavorable environmental conditions. 22 Thus, identifying spatial clusters of high disease activity, or "hotspots," can prove invaluable when prioritizing the delivery of abatement and outreach services.…”

“…Global and local Moran's I tests have been applied in public health contexts to describe spatial distributions of mosquito-borne disease outbreaks, including dengue fever, and to detect the location of disease clusters. 19,28,29 Although LISA methods give us insight into the spatial structure of disease activity within a given time period, these analyses are temporally static. In instances where georeferenced disease surveillance data are available at regular time intervals, spatial scan statistics can be used to identify local areas of clustering in multiple dimensions (i.e., space, time, or space-time).…”