Urban structure and dengue incidence in Puntarenas, Costa Rica

Abstract

Dengue is currently the most important arboviral disease globally and is usually associated with built environments in tropical areas. Remotely sensed information can facilitate the study of urban mosquito-borne diseases by providing multiple temporal and spatial resolutions appropriate to investigate urban structure and ecological characteristics associated with infectious disease. In this study, coarse, medium and fine resolution satellite imagery (Moderate Resolution Imaging Spectrometer, Advanced Spaceborne Thermal Emission and Reflection Radiometer and QuickBird respectively) and ground-based data were analyzed for the Greater Puntarenas area, Costa Rica for the years 2002-04. The results showed that the mean normalized difference vegetation index (NDVI) was generally higher in the localities with lower incidence of dengue fever during 2002, although the correlation was statistically significant only in the dry season (r=−0.40; p=0.03). Dengue incidence was inversely correlated to built area and directly correlated with tree cover (r=0.75, p=0.01). Overall, the significant correlations between dengue incidence and urban structural variables (tree cover and building density) suggest that properties of urban structure may be associated with dengue incidence in tropical urban settings. KeywordsCosta Rica; dengue; normalized difference vegetation index (NDVI); QuickBird; remote sensing; urban environment Dengue is the most important arboviral disease in terms of worldwide morbidity and mortality with an estimated 50 to 100 million cases and 12 000 to 24 000 deaths per year (WHO, 2002;Gibbons & Vaughn, 2002). The principal mosquito vector, Aedes aegypti, lives in close association with humans mostly in urban and suburban environments where larvae commonly develop in water-filled artificial containers such as drums, buckets, tyres and flower pots (Focks & Chadee, 1997;Gubler, 1998; Calderon-Arguedas et al., 2004). The recent dissemination of dengue viruses and Ae. aegypti throughout the tropics has been influenced by such factors as increasing global trade, migration and travel, population growth and uncontrolled or unplanned urbanization (Kuno, 1995 Remotely sensed data, together with geographical information systems (GIS), have been used to study vector-borne diseases, mostly in ex-urban settings (Hay et al., 1997;Bergquist, 2001;Correia et al., 2004). The study of vector-borne diseases in urban environments poses particular challenges owing to urban spatial heterogeneity and structural complexity, complex movement of hosts and vectors, and anthropogenic creation of vector habitats. (Tran & Raffy, 2005). Using Landsat ETM+, spatial determinants of dengue infection were studied in specific rural and peri-urban areas (van Benthem et al., 2005). For other mosquito-borne diseases such as malaria, data obtained from very high resolution multispectral bands have been used to study disease risk (Sithiprasasna et al., 2005) and anopheline larval habitats (Mushinzimana et al., 2006;Jacob et al. 2006). However, ...

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

“…In Clorinda City, and in accordance with Ostfeld et al (2005), WHO (2014) and Troyo et al (2009), RS information has been used to determine the type of land cover that favours the presence of breeding sites and survival of Ae. aegypti.…”

Terrestrial Remotely Sensed Imagery in Support of Public Health: New Avenues of Research Using Object-Based Image Analysis

“…As is clear from the previous paragraphs, much of the work examining the utility of remote sensing for vector-borne diseases have occurred in ex-urban settings, and the study of vector-borne diseases in urban environments is more difficult due to urban spatial heterogeneity and complexity, the complex movement of hosts and vectors, and anthropogenic creation of often fine-scale vector habitats [61]. Dengue fever is an example of a disease that affects urban dwellers.…”

“…As evidenced in the following paragraphs, many researchers are choosing OBIA approaches to map discrete landscape features because the method typically results in higher accuracies than classification with pixel-based approaches (e.g., [54,55,61,109]). We could find no examples of object-based approaches in public health that made use of the topological and hierarchical benefits conveyed by the OBIA approach.…”

“…NDVI is a measurement of vegetation abundance and vigor and is directly related to relative humidity and rainfall as well as to vegetation growth; it is often used as a proxy for, or to augment, measures of surface climatic conditions. And since bio-climatic conditions are key determinants of arthropod vector distribution and abundance and consequently affect transmission rates of any diseases they may carry [60], NDVI is commonly used in models of vector suitability [61,62], abundance [20], and disease transmission and early warning [63,64]. The following research is summarized in Table 1.…”

“…Its mosquito vector, Aedes aegypti, lives in close association with humans mostly in urban and suburban environments in fine-scale micro-habitats that are impossible to capture via remote sensing because they are too small or are hidden. Troyo et al [61] used a combination of imagery and methods to study the spatial and seasonal determinants of dengue incidence in Costa Rica. In addition to examining dengue incidence and temporal NDVI dynamics, they also mapped urban land use/land cover classes and performed a landscape metric analysis to ascertain if urban land cover patterning could indicate dengue incidence.…”