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. 2018 Apr 24:5:180073.
doi: 10.1038/sdata.2018.73.

Spatiotemporal incidence of Zika and associated environmental drivers for the 2015-2016 epidemic in Colombia

Affiliations

Spatiotemporal incidence of Zika and associated environmental drivers for the 2015-2016 epidemic in Colombia

Amir S Siraj et al. Sci Data. .

Abstract

Despite a long history of mosquito-borne virus epidemics in the Americas, the impact of the Zika virus (ZIKV) epidemic of 2015-2016 was unexpected. The need for scientifically informed decision-making is driving research to understand the emergence and spread of ZIKV. To support that research, we assembled a data set of key covariates for modeling ZIKV transmission dynamics in Colombia, where ZIKV transmission was widespread and the government made incidence data publically available. On a weekly basis between January 1, 2014 and October 1, 2016 at three administrative levels, we collated spatiotemporal Zika incidence data, nine environmental variables, and demographic data into a single downloadable database. These new datasets and those we identified, processed, and assembled at comparable spatial and temporal resolutions will save future researchers considerable time and effort in performing these data processing steps, enabling them to focus instead on extracting epidemiological insights from this important data set. Similar approaches could prove useful for filling data gaps to enable epidemiological analyses of future disease emergence events.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1. Schematic overview of the workflow used to produce the output raster files, and their spatial aggregates at the municipal, departmental, and national scales.
The input stages are shown in yellow, and the processing stages are shown in orange, while the output stages are in green.
Figure 2
Figure 2. Illustrative maps of municipality level weighted output variables for a single sample week.
Variables include minimum temperature (a), mean temperature (b) maximum temperature (c), relative humidity (d), NDVI from Terra MODIS (e) NDVI from Aqua MODIS (f), total rainfall (g) average per capita gross cell product in 2005 US$ standard value (h) and average travel time to major cities in 2000 (i).
Figure 3
Figure 3. Illustration of weekly time-series outputs aggregated at the departmental scale for the departments of Antioquia (red) and Valle del Cauca (blue) for the period January 1, 2014 to October 1, 2016.
Time-series shown are for mean temperature (bold lines), minimum temperature (lower lines) and maximum temperature (upper lines) (a), relative humidity (b), NDVI from Terra (solid lines) and Aqua (dashed lines) MODIS (c), and precipitation (d).

Dataset use reported in

  • doi: 10.1038/nmicrobiol.2016.126
  • doi: 10.1136/bmjgh-2017-000309
  • doi: 10.1073/pnas.1620161114

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References

Data Citations

    1. Siraj A.S., et al. . 2017. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.83nj1 - DOI
    1. Didan K. 2015. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/modis/mod13a2.006 - DOI
    1. Didan K. 2015. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/modis/myd13a2.006 - DOI

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