Current Risk of Dirofilariosis Transmission in the Iberian Peninsula (Spain and Portugal) and the Balearic Islands (Spain) and Its Future Projection under Climate Change Scenarios

Abstract

Dirofilariosis is a vector-borne zoonotic disease whose distribution is linked to the presence of culicid mosquitoes. Spain and Portugal are considered endemic countries; however, the distribution of dirofilariosis is not uniform. Our aim was to develop a more accurate risk model of dirofilariosis transmission for the Iberian Peninsula (Spain and Portugal) and the Balearic Islands (Spain). To do this, we used a set of key variables related to parasite transmission: the potential distribution of suitable habitats for Culex pipiens calculated via an ecological niche model (ENM) and the potential number of Dirofilaria spp. generations. The resulting model was validated with the prevalence and geolocation of D. immitis-infected dogs from all provinces and districts. In addition, the impact of possible future climatic conditions was estimated. A quantitative estimate of the risk of infection by Dirofilaria spp. was obtained at a resolution of 1 km2. The entire analyzed territory was susceptible to contact with the parasite. The highest risk of infection was found throughout the eastern coastal strip and the south of the Iberian Peninsula and the Balearic Islands, as well as in the areas surrounding the basins of the main rivers, and the lowest risk was located in the higher-altitude areas. We found a robust and positive relationship between the risk of dirofilariosis and the observed prevalence of infested dogs in the study area (β ± SE = 3.32 ± 1.43 p < 0.05). In 2080, the percentage of territory gain for Cx. pipiens will increase to 49.98%, which will increase the risk of infection. This new model provides a high predictive value for the current and predicted presence and risk and can serve as a tool for the management and control of dirofilariosis.

Analysis of the current risk of Leishmania infantum transmission for domestic dogs in Spain and Portugal and its future projection in climate change scenarios

“…However, in some areas of the south of the territory, there would be a decrease in risk over time (9.6% in 2040, 14.4% in 2060 and 27.9% in 2080), which may be due to the foreseeable decrease in water resources, and the reduction of wetlands and vegetation in these areas ( 67 , 68 ). This work predicts that canine leishmaniosis, in line with other vector-borne diseases, will shift latitudinally and toward higher altitude areas, altering its dynamics both spatially and temporally, colonizing areas where it was previously absent ( 22 , 32 , 35 , 36 , 69 , 70 ). The effect of climate change on the seasonality and distribution of these types of vector-borne diseases will be more pronounced within the temperature ranges conducive to transmission occurs ( 71 , 72 ).…”

“…However, these studies did not integrate ecological niche models of the vectors with parasite development within them, extracting the full potential of these techniques and being much more realistic. The ability to model the development of the parasite inside the vectors together with the distribution of the latter through ENMs, has made infection risk mapping a supplementary tool in control plans for other vector-borne diseases, such as dirofilariosis on a larger scale ( 35 – 37 ).…”

Prediction and validation of potential transmission risk of Dirofilaria spp. infection in Serbia and its projection to 2080

“…Environmental and bioclimatic variables were obtained in the same way as Rodríguez-Escolar et al ( 42 ). In fact, 19 bioclimatic variables were downloaded from the World Clim website ( 51 , 52 ) at a spatial resolution of 1 km 2 for the years between 1970 and 2000 (current data), plus projected data for 2040, 2060, and 2080 ( 53 ).…”

“…The number of annual Dirofilaria spp. generations was calculated using the model described by Genchi et al ( 5 , 39 , 47 ), Rodríguez-Escolar et al ( 42 ), and Morchón et al ( 43 ) and in the R-software (v.4.3.0) with daily average temperature data between 1990 and 2016 in Serbia ( 59 , 60 ). With this model, it is possible to quantify the complete development of microfilariae of Dirofilaria spp.…”

“…These models are based on the processing of robust environmental and bioclimatic variables, as well as others directly related to vector, and thus assess the probability of transmission of vector diseases ( 5 , 39–43 ). One of the most important models for this situation and one of the most widely used is the maximum entropy algorithm (Max-Ent), which uses presence data and produces robust and very accurate statistical models ( 42 , 44–46 ).…”