The conundrum of human visceral leishmaniasis in Emilia-Romagna, Italy: are wild and peridomestic animals potential reservoirs?

Leishmaniasis is a complex parasitic disease caused by intracellular protozoans of the genus Leishmania mainly transmitted by the bite of sand flies. In Italy, leishmaniasis is caused by Leishmania infantum, responsible for the human visceral and canine leishmaniases (HVL and CanL, respectively). Within Emilia-Romagna region, Italy, recent molecular studies indicated that L. infantum strains circulating in dogs and humans are different. This suggests that an animal reservoir other than dog should be evaluated in the epidemiology of HVL in Emilia-Romagna. Therefore, the main aim of this PhD project was to investigate the role of wild and peridomestic mammals as potential animal reservoirs of L. infantum in the regional zones where HVL foci are still active, also evaluating the possible role of arthropod vectors other than phlebotomine sandflies as vectors of Leishmania spp. in the sylvatic cycle of the protozoa. Overall, 206 specimens of different animal species (roe deer, rats, mice, badgers, hares, polecats, foxes, beech martens, bank voles, hedgehogs, and shrews), collected in Emilia-Romagna were screened for Leishmania with a real-time PCR, revealing a prevalence of 33% for roe deer (first report in this species). Positivity was also found in brown rats (10.6%), black rats (13.1%), mice (10%), badgers (25%), hedgehogs (80%) and bank voles (11%). To distinguish the two strains of L. infantum circulating in Emilia-Romagna, a nested PCR protocol optimized for animal tissues was developed, demonstrating that over 90% of L. infantum infections in roe deer were due to the strain isolated from humans and suggesting their possible role as reservoirs in the study area. Furthermore, the presence of Leishmania kDNA was detected in unfed larvae, nymphs and males of questing Ixodes ricinus ticks collected in regional parks of Emilia-Romagna suggesting their possible role in the transmission of L. infantum in a sylvatic or rural cycle.

Characterization of geothermal reservoirs’ parameters by inverse problem resolution and geostatistical simulations

BTES (borehole thermal energy storage)systems exchange thermal energy by conduction with the surrounding ground through borehole materials. The spatial variability of the geological properties and the space-time variability of hydrogeological conditions affect the real power rate of heat exchangers and, consequently, the amount of energy extracted from / injected into the ground. For this reason, it is not an easy task to identify the underground thermal properties to use when designing. At the current state of technology, Thermal Response Test (TRT) is the in situ test for the characterization of ground thermal properties with the higher degree of accuracy, but it doesn’t fully solve the problem of characterizing the thermal properties of a shallow geothermal reservoir, simply because it characterizes only the neighborhood of the heat exchanger at hand and only for the test duration. Different analytical and numerical models exist for the characterization of shallow geothermal reservoir, but they are still inadequate and not exhaustive: more sophisticated models must be taken into account and a geostatistical approach is needed to tackle natural variability and estimates uncertainty. The approach adopted for reservoir characterization is the “inverse problem”, typical of oil&gas field analysis. Similarly, we create different realizations of thermal properties by direct sequential simulation and we find the best one fitting real production data (fluid temperature along time). The software used to develop heat production simulation is FEFLOW 5.4 (Finite Element subsurface FLOW system). A geostatistical reservoir model has been set up based on literature thermal properties data and spatial variability hypotheses, and a real TRT has been tested. Then we analyzed and used as well two other codes (SA-Geotherm and FV-Geotherm) which are two implementation of the same numerical model of FEFLOW (Al-Khoury model).