Determinants of the geographic distribution of Puumala virus and Lyme borreliosis infections in Belgium

@article{Linard2007_hanta_lyme, abstract = {Background Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Results Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. Conclusions A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting.}, author = {Linard, Catherine and Lamarque, Penelope and Heyman, Paul and Ducoffre, Genevieve and Luyasu, Victor and Tersago, Katrien and Vanwambeke, Sophie O. and Lambin, Eric F. }, citeulike-article-id = {1271868}, doi = {10.1186/1476-072X-6-15}, issn = {1476-072X}, journal = {International Journal of Health Geographics}, keywords = {disease, hanta, ixodes, risk, ticks}, month = {May}, pages = {15+}, posted-at = {2007-05-03 08:17:33}, priority = {2}, title = {Determinants of the geographic distribution of Puumala virus and Lyme borreliosis infections in Belgium}, url = {http://dx.doi.org/10.1186/1476-072X-6-15}, volume = {6}, year = {2007} }

TY - JOUR ID - Linard2007_hanta_lyme L3 - citeulike-article-id:1271868 TI - Determinants of the geographic distribution of Puumala virus and Lyme borreliosis infections in Belgium JF - International Journal of Health Geographics VL - 6 SP - 15 SN - 1476-072X N2 - Background Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Results Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. Conclusions A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting. KW - disease KW - hanta KW - ixodes KW - risk KW - ticks AU - Linard, Catherine AU - Lamarque, Penelope AU - Heyman, Paul AU - Ducoffre, Genevieve AU - Luyasu, Victor AU - Tersago, Katrien AU - Vanwambeke, Sophie AU - Lambin, Eric PY - 2007/05/02/ UR - http://dx.doi.org/10.1186/1476-072X-6-15 ER -