Understanding West Nile virus transmission: Mathematical modelling to quantify the most critical parameters to predict infection dynamics.

West Nile disease is a vector-borne disease caused by West Nile virus (WNV), involving mosquitoes as vectors and birds as maintenance hosts. Humans and other mammals can be infected via mosquito bites, developing symptoms ranging from mild fever to severe neurological infection. Due to the worldwide spread of WNV, human infection risk is high in several countries. Nevertheless, there are still several knowledge gaps regarding WNV dynamics. Several aspects of transmission taking place between birds and mosquitoes, such as the length of the infectious period in birds or mosquito biting rates, are still not fully understood, and precise quantitative estimates are still lacking for the European species involved. This lack of knowledge affects the precision of parameter values when modelling the infection, consequently resulting in a potential impairment of the reliability of model simulations and predictions and in a lack of the overall understanding of WNV spread. Further investigations are thus needed to better understand these aspects, but field studies, especially those involving several wild species, such as in the case of WNV, can be challenging. Thus, it becomes crucial to identify which transmission processes most influence the dynamics of WNV. In the present work, we propose a sensitivity analysis to investigate which of the selected epidemiological parameters of WNV have the largest impact on the spread of the infection. Based on a mathematical model simulating WNV spread into the Lombardy region (northern Italy), the basic reproduction number of the infection was estimated and used to quantify infection spread into mosquitoes and birds. Then, we quantified how variations in four epidemiological parameters representing the duration of the infectious period in birds, the mosquito biting rate on birds, and the competence and susceptibility to infection of different bird species might affect WNV transmission. Our study highlights that knowledge gaps in WNV epidemiology affect the precision in several parameters. Although all investigated parameters affected the spread of WNV and the modelling precision, the duration of the infectious period in birds and mosquito biting rate are the most impactful, pointing out the need of focusing future studies on a better estimate of these parameters at first. In addition, our study suggests that a WNV outbreak is very likely to occur in all areas with suitable temperatures, highlighting the wide area where WNV represents a serious risk for public health.

Lost and found: Helminths infecting invasive raccoons introduced to Italy.

North American raccoons (Procyon lotor) have been introduced to several European countries, where they may represent a sanitary threat as hosts of several pathogens such as the zoonotic ascarid Baylisascaris procyonis. We carried out parasitological analysis on raccoons introduced to Italy to verify whether the species had carried along B. procyonis or any other gastro-intestinal helminths that may threaten humans, livestock or native wildlife. We examined 64 raccoons culled in Northern Italy during control activities and 3 roadkills opportunistically sampled from a separate population located in central Italy. Helminths were collected from the gastro-intestinal tract through standard parasitological techniques and identified based on a combination of morphology and molecular methods. Overall, examined raccoons showed a poor parasitic fauna, with almost 30% of individuals free of any helminth infection. The most prevalent species were the nematodes Strongyloides procyonis (26.9%), Aonchotheca putorii (25.4%) and Porrocaecum sp. (19.4%). Plagiorchis sp. trematodes were also common (13.4%), whereas cestodes were scarcely represented. With the exception of S. procyonis introduced from North America, all the other identified taxa have either a Eurasian or a wide Holarctic distribution. Despite not finding any B. procyonis in the examined raccoons, passive surveillance for this parasite should be implemented, especially in Tuscany, since the limited host sample examined in the present survey does not allow to exclude its presence.

How to choose the best control strategy? Mathematical models as a tool for pre-intervention evaluation on a macroparasitic disease.

During the last century, emerging diseases have increased in number, posing a severe threat for human health. Zoonoses, in particular, represent the 60% of emerging diseases, and are a big challenge for public health due to the complexity of their dynamics. Mathematical models, by allowing an a priori analysis of dynamic systems and the simulation of different scenarios at once, may represent an efficient tool for the determination of factors and phenomena involved in zoonotic infection cycles, but are often underexploited in public health. In this context, we developed a deterministic mathematical model to compare the efficacy of different intervention strategies aimed at reducing environmental contamination by macroparasites, using raccoons (Procyon lotor) and their zoonotic parasite Bayilsascaris procyonis as a model system. The three intervention strategies simulated are raccoon depopulation, anthelmintic treatment of raccoons and faeces removal. Our results show that all these strategies are able to eliminate the parasite egg population from the environment, but they are effective only above specific threshold coverages. Host removal and anthelmintic treatment showed the fastest results in eliminating the egg population, but anthelmintic treatment requires a higher effort to reach an effective result compared to host removal. Our simulations show that mathematical models can help to shed light on the dynamics of communicable infectious diseases, and give specific guidelines to contain B. procyonis environmental contamination in native, as well as in new, areas of parasite emergence. In particular, the present study highlights that identifying in advance the appropriate treatment coverage is fundamental to achieve the desired results, allowing for the implementation of cost- and time-effective intervention strategies.