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Assessing Red Fox ( Vulpes vulpes ) Demographics to Monitor Wildlife Diseases: A Spotlight on Echinococcus multilocularis .

Roberto CelvaBarbara CrestanelloFederica ObberDebora DellamariaKarin TrevisiolMarco BregoliLucia CenniAndreas AgreiterPatrizia DanesiHeidi Christine HauffeCarlo Vittorio Citterio
Published in: Pathogens (Basel, Switzerland) (2022)
The assessment of red fox population density is considered relevant to the surveillance of zoonotic agents vectored by this species. However, density is difficult to estimate reliably, since the ecological plasticity and elusive behavior of this carnivore hinder classic methods of inference. In this study, red fox population density was estimated using a non-invasive molecular spatial capture-recapture (SCR) approach in two study areas: one in a known hotspot of the zoonotic cestode Echinococcus multilocularis , and another naïve to the parasite. Parasitological investigations on collected samples confirmed the presence of the parasite exclusively in the former area; the SCR results indicated a higher fox population density in the control area than in the hotspot, suggesting either that the relationship between fox density and parasite prevalence is not linear and/or the existence of other latent factors supporting the parasitic cycle in the known focus. In addition, fox spotlight count data for the two study areas were used to estimate the index of kilometric abundance (IKA). Although this method is cheaper and less time-consuming than SCR, IKA values were the highest in the areas with the lower molecular SCR density estimates, confirming that IKA should be regarded as a relative index only.
Keyphrases
  • public health
  • risk factors
  • climate change
  • machine learning
  • toxoplasma gondii
  • risk assessment
  • plasmodium falciparum
  • deep learning
  • single molecule