Fig 1.
Estimated incidence of imported cholera cases for the first 6 weeks of the outbreak in Harare.
Map made with R package Leaflet v2.1.1 and map data from OpenStreetMap.
Fig 2.
Covariates included in the point process modelling.
Map made with R package Leaflet v2.1.1 and map data from OpenStreetMap.
Fig 3.
Distribution of cholera cases across Harare temporally by week (left) and spatially across all weeks (right).
Basemap attribution: CARTO (basemaps linked here), OpenMapTiles, OpenStreetMap contributors (license linked here).
Table 1.
Results from the point process modelling of cholera risk in Harare.
Coefficients represent the difference in the log of the expected rates for a unit increase in the covariate.
Fig 4.
Observed versus predicted numbers of cases per week (left) and per ~1km hex grid cell (right).
Fig 5.
The effect of proportion with piped water at different distances to the sewer network.
The y axis represents the risk (cases per person) when holding all other covariates at their mean value. Higher values indicate higher cholera risk.
Table 2.
Relative risk of moving into the next stratum of a covariate (excluding interaction between distance to sewer and proportion with piped water) where strata are formed by dividing the covariate values (in populated grid cells) into ten equal width strata.
For example, if the values in populated grid cells of a given covariate ranges from zero–two hundred, the relative risk is shown for every increase of twenty in the covariate.
Fig 6.
Predicted incidence of cholera across Harare for the first 6 weeks of the outbreak (September 1st–October 13th, 2018).
Note the log-scaled colour palette. Basemap attribution: CARTO (basemaps linked here), OpenMapTiles, OpenStreetMap contributors (license linked here).