**Author details**

22 Toxoplasmosis – Recent Advances

[193].

management of meat-producing animals. For example, in intensively managed swine farms, modern biosecure management practices have resulted in reduced levels of infection in swine raised in confinement [96, 179, 180]. In organic livestock production systems, farmmanagement factors including feeding are thought to play an important role in the on-farm prevalence of *T. gondii* [181]. To limit *T. gondii* infection in such farms, recommended practices include exclusion of cats or other wildlife, strict rodent control and restriction of human entry in pig barns [182]. These measures could be effective in other species to reduce the level of contamination of meat. On the contrary, organic pork meat may pose a specific risk of transmitting T*. gondii* to humans [183]. However, due to the capacity of dissemination of *T. gondii*, the objective of a completely *T. gondii*-free meat seems difficult, but feasible

On the other hand, working to reduce the level of infection in meat does not act on the risk of toxoplasmosis due to direct contact with oocysts, which stays largely unknown and unmanaged. Limiting the level of contamination in meat may even result in the increase of the relative risk due to oocysts. The importance of oocysts in the overall contamination rate remains difficult to assess, due to the lack of information on the level of environmental contamination and to the difficulty to characterize the level of contact of people with contaminated areas. In this framework, a better knowledge of the life cycle of *T. gondii* in its natural environment should help to characterize the risk due to oocysts. For example, the estimates provided in Table 1 give an order of magnitude of the expected differences between environments. Moreover, two recent methodological advances should improve our knowledge of environmental contamination. First, new methods to detect oocysts in soil [185] and water [186, 187, 188] have been proposed, based on molecular detection or immunocapture. Being highly sensitive, these methods should allow researchers to better characterize areas and periods at risk of contamination. A few studies have already measured the level of soil and water contamination [50, 68, 189]. These studies confirmed that the risk in urban areas is spatially structured at the very local scale, and they should help to identify areas most contaminated in other environments. The second useful tool that should bring relevant information is the development of methods to detect antibodies specifically linked to infection by oocysts [190]. This test, based on western blot assay detecting for IgG positive serums antibodies to sporozoites, allowed the authors to determine the proportion of cases that had contacts with oocysts in Chile, both in humans [191] and in swine [192]. In North America, a survey using this method shows that a high proportion of mothers of congenitally infected infants had primary infection with oocysts

These new analytical tools should help to identify the origin of contamination, and thus solve several fundamental and practical questions regarding *T. gondii* life cycle. For example, estimating the frequency of infection from oocysts in cats of urban and rural area should help to estimate the part of the DH-environment life cycle in different environments. In people, these tools should help to assess if the relative role of oocyst and meat-born infection varies according to the area (urban versus rural populations for example). In such

using pre-harvest measures for prevention of T. gondii infection [184].

Emmanuelle Gilot-Fromont1,2,\*, Maud Lélu3, Marie-Laure Dardé4, Céline Richomme5, Dominique Aubert6, Eve Afonso7, Aurélien Mercier4, Cécile Gotteland1,6, Isabelle Villena6 *1UMR CNRS 5558 Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, Villeurbanne, France. 2VetAgro-Sup Campus Vétérinaire, Université de Lyon, Marcy l'Etoile, France, 3NIMBioS, University of Tennessee, Knoxville, Tennessee, USA, 4INSERM UMR1094, Tropical Neuroepidemiology, School of Medicine, Institute of Neuroepidemiology and Tropical Neurology, CNRS FR 3503 GEIST, University of Limoges, Limoges, France, 5ANSES, Nancy laboratory for rabies and wildlife, Technopole agricole et vétérinaire, Malzéville, France, 6Laboratoire de Parasitologie-Mycologie, EA 3800, UFR de Médecine, SFR Cap Santé, FED 4231, University of Reims Champagne-Ardenne, Reims, France, 7Department Chrono-environnement, UMR CNRS 6249 USC INRA, University of Franche-Comté, Besançon, France* 
