VectorMap - Zika/Chikungunya/Dengue


INSTITUTIONS: Walter Reed Biosystematics Unit (WRBU)

GRANTING AGENCY: DoD, Global Emerging Infections Surveillance ystem (GEIS)

With the spread of the Zika virus we have responded by gathering information from VectorMap about the distribution of the primary vectors, Aedes aegypti and Ae. albopictus to assist in understanding the potential vector hazard. Zika along with Chikungunya and Dengue share vectors, so the information about Zika presented here will be useful for understanding the distribution of all of these mosquito-borne pathogens. Alternative models of vector distribution vary in their prediction of the occurrence of the vector so to simplify things we have chosen recent models by Kraemer et al. (2016) for Ae. aegypti and Ae. albopictus. Zika and Chikungunya distribution by country is available through the US CDC, which we also show in VectorMap. Aedes aegypti typically inhabits more urban environments than Ae. albopictus, and even when both inhabit urban environments, Ae. aegypti typically lives in closer proximity to humans (Ho et al. 1971, Tsuda et al. 2006). As these vectors are primarily urban or peri-urban we have tried to refine the vector models by considering human population density using the LandScan (2011) raster resource.


Click on the image above to go to the map

All analyses were conducted in ESRI ArcMap 10.3. Collection records for Ae. aegypti and Ae. albopictus were extracted from the VectorMap database (as at 7 Feb 2016) and those with uncertain identification and absence rather than presence records were discarded. Also discarded were records whose spatial uncertainty was greater than 2000 m. This left 225 unique localities for Ae. aegypti from 19 countries and 5723 unique localities for Ae. albopictus from 16 countries; the majority of Ae. albopictus (5228) were from the USA. These points were converted to shapefiles and a buffer of 1 km around each to represent the neighborhood of the mosquitoes was calculated and converted to a shapefile. Zonal statistics/histogram analyses of buffered collection locations against the LandScan (2011) population density raster (Ispop2011) showed that despite the high frequency of pixels of 51-100 people/sq km, the majority of Ae. albopictus and Ae. aegypti positive locations occurred in the categories 101-500 and 501-2500 people/sq km (see figure). Aedes aegypti appears more often than Ae. albopictus in denser human habitats but as these are of such low frequency considering the whole they were discounted for the purposed of this study. Therefore we created a polygon of the population raster for density 101-2500 then converted this to points (Data Management Tools>Features>Feature to point). This was necessary because some polygons are not counted when trying to extract elements of the population raster. Then we used Spatial analyst tools>Extraction>Extract by Mask to reveal instances where both conditions (>50% chance of the vector species and 101-2500 people) occurred.

To understand when conditions are right for the growth of Ae. aegypti and Ae. albopictus a major consideration is temperature. Brady et al. (2014) limited their predictions of temperature suitability to areas with a maximum monthly temperature exceeding 13°C for Ae. albopictus and 14°C for Ae. aegypti. These thresholds represent the observed temperatures below which biting and movement behaviours are impaired (Carrington et al. 2013a,b, Christophers, 1960, Estrada-Franco & Craig, 1995). Brady et al. (2014) provide as additional files several animations that show temporal change in environmental suitability for Ae. aegypti and Ae. albopictus. We also wanted to provide a monthly map of climate suitability based on the 13°C isotherm derived from the WorldClim data (1950-2000) of average monthly maximum temperature.

To create 12 monthly shapefiles of above and below 13°C from WorldClim (Hijmans et al. 2005) tmax rasters we converted the symbology to 2 categories, then we reclassified rasters to 2 categories ( below and above 13°C, 0 and 1, respectively), using the Conversion Tools>From Raster>Raster to Polygon tool. The resulting polygons had >4000 elements so we simplified these before uploading to ArcGIS Online (Data Management Tools>Generalization>Dissolve according to the Gridcode field).

The Ae. aegypti and Ae. albopictus layers, suitable (>13°C) and not suitable (<13°C) layers and other related layers from CDC and elsewhere can be explored in the associated ArcGIS Online map by clicking on the image above.

For those interested in Zika/Chikungunya/Dengue risk factors for U.S. CONUS military facilities, check out the downloadable Excel spreadsheets that map and rank facilities according to various risk factors, via VectorMap's ESWG project page.


Brady et al. Global temperature constraints on Aedes aegypti and Ae. albopictus persistence and competence for dengue virus transmission. Parasites & Vectors 2014, 7:338

Carrington LB, Armijos MV, Lambrechts L, Barker CM, Scott TW: Effects of fluctuating daily temperatures at critical thermal extremes on Aedes aegypti life-history traits. PLoS One 2013, 8(3):e58824.

Carrington LB, Seifert SN, Willits NH, Lambrechts L, Scott TW: Large diurnal temperature fluctuations negatively influence Aedes aegypti (Diptera: Culicidae) life-history traits. J Med Entomol 2013, 50(1):43–51.

Christophers R: Aedes aegypti (L.) the yellow fever mosquito: its life history, bionomics and structure. In 1st edition. Cambridge: Cambridge University Press; 1960.

Kraemer, Moritz et al. 2015. The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus. ELife: 4:e08347. DOI: 10.7554/eLife.08347.

Estrada-Franco JG, Craig GB: Biology, Disease Relationships, and Control of Aedes albopictus. Washington DC: Pan American Health Organization; 1995

Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.

Ho B, Chan K, Chan Y: Aedes aegypti (L.) and Aedes albopictus (Skuse) in Singapore City: 3. Population fluctuations. Bull World Health Organ 1971, 44(5):635.

LandScan 2011. This product was made utilizing the LandScan (2011)™ High Resolution global Population Data Set copyrighted by UT-Battelle, LLC, operator of Oak Ridge National Laboratory under Contract No. DE-AC05-00OR22725 with the United States Department of Energy. The United States Government has certain rights in this Data Set. Neither UT-BATTELLE, LLC NOR THE UNITED STATES DEPARTMENT OF ENERGY, NOR ANY OF THEIR EMPLOYEES, MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LEGAL LIABILITY OR RESPONSIBILITY FOR THE ACCURACY, COMPLETENESS, OR USEFULNESS OF THE DATA SET.

Tsuda Y, Suwonkerd W, Chawprom S, Prajakwong S, Takagi M: Different spatial distribution of Aedes aegypti and Aedes albopictus along an urbanrural gradient and the relating environmental factors examined in three villages in northern Thailand. J Am Mosq Control Assoc 2006, 22(2):222–228.


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