Fig 1.
Modeled domestic dog population in Central African Republic.
A) Geographical distribution of the predicted dog subpopulations divided in rural (light blue) and urban (violet) patches. The red shaped area indicates the Ouham-Pendé prefecture. B) Probability distribution of the estimated dog population size per patch in rural (light blue) and urban (violet) patches. C) Probability distribution of the estimated dog population density per km2 per patch in rural (light blue) and urban (violet) patches. D) Probability distribution of the distance between any two patches in the metapopulation network, whether connecting two urban patches (orange), two rural patches (dark red), a urban with a rural patch (black). The two dashed vertical lines indicate the separation between short, medium, and long-range movements. The satellite map was generated using data sourced from OpenStreetMap (OpenStreetMap contributors) and created through QGIS software (QGIS Development Team (2019). QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.osgeo.org).
Fig 2.
Georeferenced multiscale network of estimated domestic dog mobility.
Dots represent patches and links represent the estimated human-mediated transports of dogs on long A), medium B), and short scales C). D) Bangui and its surrounding region. The red circle defines Bangui’s neighborhood. The Central African Republic borders were generated using data from "Global Administrative Areas (2019)". University of California, Berkely. Available online: http://www.gadm.org [21/07/2019].
Table 1.
Modeled dog movements in Central African Republic.
For each movement range we report the predicted number of links (and percentage of the total), and the predicted daily moving rate (dog/day).
Fig 3.
Dog rabies persistence probability in Central African Republic.
A) Predicted persistence probability of rabies in the domestic dog population of Central African Republic as a function of the basic reproductive number R0 and of the annual birth rate. Results are obtained using empirically distributed incubation and infectious periods. The symbol ‘x’ corresponds to the maximum likelihood estimate. B) Predicted persistence probability as a function of the annual birth rate for the maximum likelihood estimate R0 = 1.03. The two dotted lines indicate 80% and 95% persistence probability. C) As in A) assuming that incubation and infectious periods are exponentially distributed with the same average duration of incubation and infection of the empirical distributions.
Fig 4.
Numerical trajectories for Bangui.
A) Simulated number of monthly cases in Bangui. Colors correspond to five different numerical runs. B) Probability distribution of the periods of the simulated epidemic cycles in Bangui compared to the two empirical oscillation periods of 53.4 (blue) and 89.0 months (red) reported in [18]. The distribution is obtained through wavelet analysis. Its peak is at 92 months. The x axis is in log scale.
Fig 5.
Dog rabies endemic prevalence in Central African Republic.
A) Geographical representation of the predicted dog rabies endemic prevalence by administrative prefectures and by patch. Color codes range from low prevalence (<5%, green), to moderate prevalence (between 5% and 20%, yellow), to high prevalence (>20%, red). B) Predicted endemic prevalence by patch type. C) Scatter plot of the average density of infected dogs per km2 vs. the endemic patch prevalence. D) Epidemic concentration curve (ECC) for rabies prevalence in the domestic dog population in Central African Republic. ECC is used to address the relative contribution of high density and low density areas to endemic infection [68]. The Central African Republic borders and administrative areas were generated using data from "Global Administrative Areas (2019)". University of California, Berkeley. Available online: http://www.gadm.org [21/07/2019].
Fig 6.
Role of spatial fragmentation and mobility.
A) Likelihood to have persistence probability between 50% and 80%, or larger than 80% (light blue/dark blue stacked histogram) in the full parameter space (R0, birth rate) investigated and for different experimental scenarios (panels B-J). B), C), D), E), F), G), H), I), J) Predicted persistence probability of rabies in the domestic dog population as a function of the basic reproductive number R0 and of the annual dogs birth rate for the scenarios considering: only Bangui population B); only urban patches and their connections, discarding rural patches C); only rural patches and their connections, discarding urban patches D); all patches but connected only through short travels E), medium travels F), or long travels G); all patches but connected only through short and medium travels H), short and long travels I), or medium and long travels J).