Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases
Abstract
:1. Introduction
2. NE and LB in Belgium
3. Methods
3.1. The Gravity Model
- The surface covered by vegetative systems is also an important determinant of the magnitude of disease risk and incidence [30]. Besides the ecological effects related to the size and degree of fragmentation of ecosystems, these attributes of vegetated areas affect the kind and intensity of interaction humans have with them. For instance, the size of vegetated areas is an important determinant of the attraction value of green areas [31].
- Accounting for human activities and their relation to disease risk is a complex matter [32] and no single model element is able to represent this complexity. Nonetheless, it is known that certain occupational groups are highly exposed to tick-bites and/or rodent-borne pathogens. Case-control studies report that foresters, hunters, farmers, amongst other professions, present specially high disease risk as consequence of intensive interaction with the habitat of vector organisms [33,34,35,36]. The connection between occupation and disease risk supports the consideration of the variable F in the model as proxy of the exposure to NE and LB pathogens linked to professional activities, as it represents the share of activities like forester, hunter or ranger in the economic structure of the municip
3.2. Disease Risk Estimator
3.3. Area and Location of Vegetative Systems
3.4. Human Population
4. Results
4.1. Disease Risk
4.2. Model Selection
5. Discussion
6. Conclusions
- Information on location, size and composition of vegetated areas is of great importance in modelling the spatial spread of NE, LB and other VBD. Our results show the suitability of both static (land cover maps) and dynamic (space-borne datasets) data sources to derive that information and incorporate it as input of the models.
- Accounting for habitat conditions is of paramount importance when attempting to model VBD. Nevertheless, the models should be enriched by including variables that may come from domains different than ecology or biophysics but that inform on human exposure to pathogens. In the particular case of NE and LB, previous studies highlighted the elevated risk associated to certain occupational groups. Our results showed that data on the number of active companies per branch of the economy at municipal level can provide a significant covariate of risk grade.
- Spatial interaction models have been applied in a large variety of domains where distance and attracting attributes of entities are relevant. The results obtained in this study support the idea of adopting GM or other forms of spatial interaction analysis to model the spread of NE and LB risk and encourage the investigation of the applicability of spatial interaction models in the study of other VBD.
Acknowledgments
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Barrios, J.M.; Verstraeten, W.W.; Maes, P.; Aerts, J.-M.; Farifteh, J.; Coppin, P. Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases. Int. J. Environ. Res. Public Health 2012, 9, 4346-4364. https://doi.org/10.3390/ijerph9124346
Barrios JM, Verstraeten WW, Maes P, Aerts J-M, Farifteh J, Coppin P. Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases. International Journal of Environmental Research and Public Health. 2012; 9(12):4346-4364. https://doi.org/10.3390/ijerph9124346
Chicago/Turabian StyleBarrios, José Miguel, Willem W. Verstraeten, Piet Maes, Jean-Marie Aerts, Jamshid Farifteh, and Pol Coppin. 2012. "Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases" International Journal of Environmental Research and Public Health 9, no. 12: 4346-4364. https://doi.org/10.3390/ijerph9124346