| Popis: |
Understanding the population dynamics of reservoirs of zoonotic diseases, such as bats, is a crucial first step to predict and prevent potential spillover of deadly viruses like Ebola. Due to the limited data on bats across Africa, their density and migrations can be studied with probabilistic numerical models based on samples of the ecological bare carrying capacity. To this purpose, the bare carrying capacity will be modeled as a random field and its statistics calibrated with the available data. The most popular methods for the calibration of the correlation of a random field are not applicable in the case of unevenly spaced data. We propose to use a least square regression model to estimate the autocorrelation function and remedy the problem of unevenly spaced data. The residuals (i.e., the differences between the predicted and actual values) of the regression model determining the bare carrying capacity were found to be weakly homogeneous across Africa. Correlation lengths of the residuals were found to be different along longitude and latitude. Along the longitude, the correlation length is 1.78 degrees (approximately 200 km) whereas along the latitude it is 1.40 degrees (approximately 150 km), which is expected as the climate and other parameters determining the carrying capacity change more rapidly along the latitude. The bare carrying capacity of bats was found to be more dense in central Africa. This is due to the fact that climatic and environmental conditions are more suitable for the survival of bats. |
