Spatial Analysis of Dengue Seroprevalence and Modeling of Transmission Risk Factors in a Dengue Hyperendemic City of Venezuela

Abstract

Background: Dengue virus (DENV) transmission is spatially heterogeneous. Hence, to stratify dengue prevalence in space may be an efficacious strategy to target surveillance and control efforts in a cost-effective manner particularly in Venezuela where dengue is hyperendemic and public health resources are scarce. Here, we determine hot spots of dengue seroprevalence and the risk factors associated with these clusters using local spatial statistics and a regression modeling approach.

Methodology/principal findings: From August 2010 to January 2011, a community-based cross-sectional study of 2012 individuals in 840 households was performed in high incidence neighborhoods of a dengue hyperendemic city in Venezuela. Local spatial statistics conducted at household- and block-level identified clusters of recent dengue seroprevalence (39 hot spot households and 9 hot spot blocks) in all neighborhoods. However, no clusters were found for past dengue seroprevalence. Clustering of infection was detected at a very small scale (20-110m) suggesting a high disease focal aggregation. Factors associated with living in a hot spot household were occupation (being a domestic worker/housewife (P = 0.002), lower socio-economic status (living in a shack (P<0.001), sharing a household with <7 people (P = 0.004), promoting potential vector breeding sites (storing water in containers (P = 0.024), having litter outdoors (P = 0.002) and mosquito preventive measures (such as using repellent, P = 0.011). Similarly, low socio-economic status (living in crowded conditions, P<0.001), having an occupation of domestic worker/housewife (P = 0.012) and not using certain preventive measures against mosquitoes (P<0.05) were directly associated with living in a hot spot block.

Conclusions/significance: Our findings contribute to a better comprehension of the spatial dynamics of dengue by assessing the relationship between disease clusters and their risk factors. These results can inform health authorities in the design of surveillance and control activities. Focalizing dengue control measures during epidemic and inter-epidemic periods to disease high risk zones at household and neighborhood-level may significantly reduce virus transmission in comparison to random interventions.

Fig 1. Study area.

Location of the three study sites: 1) Candelaria 2) Caña de Azucar and 3) La Cooperativa neighborhoods within the metropolitan area of Maracay city, Aragua State, Venezuela.

Fig 2. Dengue incidence in Mario Briceño Iragorry and Girardot municipalities, Aragua state, between 2005–2015.

Mario Briceño Iragorry municipality contains the neighborhoods of Caña de Azucar and Candelaria, while La Cooperativa neighborhood lies within Girardot municipality. Source: LARDIDEV (Laboratorio Regional para el Diagnóstico del Dengue y otras Enfermedades Virales), Corporación de Salud del Estado Aragua (CORPOSALUD Aragua), Ministerio del Poder Popular para la Salud, Venezuela, 2016.

Fig 3. Dengue seroprevalence within Candelaria & Caña de Azúcar neighborhoods, Maracay city, Venezuela.

a) Past dengue seroprevalence: Blocks show past dengue seroprevalence (%). No hot spots at any spatial scale were found (Gi*(d) < 2.79, P >0.05). Black dots indicate surveyed households. b) Recent dengue seroprevalence: Blocks show recent dengue seroprevalence (%). Blue encircled blocks show the results of the local Getis statistic (Gi*(d)) analyses at a distance of 90 meters, with significant (P <0.05) clusters of recent dengue infection at block level (hot spots). Red dots show the results of Gi*(d) analyses at a distance of 20 meters with significant clustering of recent dengue infection at household level (Gi*(d) >2.79, P <0.05). Black dots indicate surveyed households.

Fig 4. Dengue seroprevalence within La Cooperativa neighborhood, Maracay city, Venezuela.

a) Past dengue seroprevalence: Blocks show past dengue seroprevalence (%). No hot spots at any spatial scale were found (Gi*(d) < 2.79, P >0.05). Black dots indicate surveyed households. b) Recent dengue seroprevalence: Blocks show recent dengue seroprevalence (%). Blue encircled blocks show the results of the local Getis statistic (Gi*(d)) analyses at a distance of 110 meters, with significant (P <0.05) clusters of recent dengue infection at block level (hot spots). Red dots show the results of Gi*(d) analyses at a distance of 20 meters with significant clustering of recent dengue infection at household level (Gi*(d) >2.79, P <0.05). Black dots indicate surveyed households.