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CATI model

DOI

This repository contains the data used in the following article:

The potential impact of case-area targeted interventions in response to cholera outbreaks: A modeling study

Data

The folder data/casedata contains the epidemic curve as well as the (anonymized) coordinates of case households. A detailed description of this data can be found in Azman et al. (2018).

  • data/casedata/locationOffset.csv contains the xy-coordinates and dates of reported case households. The coordinates are in meters. A random offset has been added to the coordinates to make it impossible to identify absolute household locations. The relative location of households, necessary to compute the tau-statistics, is preserved.

  • data/casedata/epicurve.csv contains the number of reported cases per day.

In addition, the following data has been used:

  • data/population_distribution/populationDistrNdjamena.pickle contains the population distribution derived from the remotely sensed built-up density (Global Urban Footprint, Esch et al. (2017) and Esch et al. (2011)) and can be loaded in python using the following commands:
library(pickle)
f=open('populationDistrNdjamena.pickle','r')
popMatrix=pickle.load(f)
gridProp=pickle.load(f)
f.close()
  • data/districts_ndjamena/tcd_polbnd_adm9_a_osm_170206.shp contains the boundaries of the districts as used for the district-targeted mass campaigns. This data has been obtained from OpenStreetMap (© OpenStreetMap contributors).

  • The TRMM precipitation data used is by Huffman et al. (2010) and can been obtained from IRIDL.

References

Azman, A., Luquero, F.J., Salje, H., Naibei, N., Adalbert, N., Ali, M., Bertuzzo, E., Finger, F., Toure, B., Massing, L.A., Ramazani, R., Cardon, A., Saga, B., Allan, M., Olson, D., Leglise, J., Porten, K., Lessler, J., 2018. Micro-hotspots of Risk in Urban Cholera Epidemics. bioRxiv 248476. https://doi.org/10.1101/248476

Esch, T., Heldens, W., Hirner, A., Keil, M., Marconcini, M., Roth, A., Zeidler, J., Dech, S., Strano, E. (2017): Breaking new ground in mapping human settlements from space – The Global Urban Footprint. ISPRS Journal of Photogrammetry and Remote Sensing 134 (2017) 30-42. https://doi.org/10.1016/j.isprsjprs.2017.10.012

Esch, T., Schenk, A., Ullmann, T., Thiel, M., Roth, A., Dech, S. (2011): Characterization of Land Cover Types in TerraSAR-X Images by Combined Analysis of Speckle Statistics and Intensity Information. IEEE Transactions on Geoscience and Remote Sensing, Volume 49, Issue 6, pp. 1911-1925. https://doi.org/10.1109/TGRS.2010.2091644.

Huffman, G. J., Adler, R. F., Bolvin, D. T. & Nelkin, E. J. (2010), The TRMM multi-satellite precipitation analysis (TMPA), in M. Gebremichael & F. Hossain, eds, ‘Satellite Rainfall Applications for Surface Hydrology’, Springer Netherlands, pp. 3–22.

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