COVID-19 research

Map Coronavirus For China (MC4C) research group

MC4C, a research group at Zheijang University develops a downscaling approach to produce maps of COVID-19 in China at a fine spatial scale. Outputs can be visualised in an online ESRI dashboard.

Raster and shapefile maps can be downloaded here:

Download model monthly outputs (Jan-May 2020)

Raster maps

Expected (mean) COVID-19 counts (and log counts):

raster (Jan-May 2020)

Lower bound 95% CI COVID-19 counts (and log counts):

raster (Jan-May 2020)

Higher bound 95% CI COVID-19 counts (and log counts):

raster (Jan-May 2020)

Shape files

Expected (mean), lower and upper bounds 95% CI of COVID-19 counts (and log counts) at ADM-2 level:

shapefile (Jan-May 2020)

Expected (mean), lower and upper bounds 95% CI of COVID-19 counts (and log counts) at ADM-3 level:

shapefile (Jan-May 2020)

Data sources and software

Johns Hopkins University (JHU): dashboard | paper
Xu et al.: data | paper
The Paper: data
Disaggregation method: R package | paper

Downscaling Method

Illustrations

COVID-19 in China (Jan-Feb 2020)

Comparison of JHU data (top-left) and predictions (mean: bottom-left, lower bound 95% CI top-right; upper bound 95% CI bottom-right). Counts of COVID-19 in log scale.

Comparison of disaggregated data (Pengpai: left; Xu et al.: centre) and predictions aggregated at ADM-3. Counts of COVID-19 in log scale.

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