Variations in seroprevalences of canine leishmaniasis: Could it be a consequence of the population structure?

• Published in: Veterinary parasitology Vol. 226; pp. 5 - 9
• Main Authors: Muniesa, Ana, Peris, Ana, Castillo, Juan Antonio, de Blas, Ignacio
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.08.2016
• Subjects: Age Factors; Animals; Antibodies, Protozoan - blood; Chi-Square Distribution; Computer Simulation; Confounding Factors (Epidemiology); Cross-Sectional Studies; dog diseases; Dog Diseases - epidemiology; Dog Diseases - parasitology; Dogs; Epidemiology; Female; gender; habitats; health status; Leishmania - immunology; Leishmania infantum; leishmaniasis; Leishmaniasis - epidemiology; Leishmaniasis - veterinary; Logistic Models; longevity; Male; Modelling; Models, Biological; Phlebotominae; Population dynamics; population structure; Rural Population; Seroepidemiologic Studies; Seroprevalence; Sex Distribution; Spain - epidemiology; Stochastic Processes; Urban Population; Leishmania infantum; Modelling; Population dynamics; Epidemiology; Seroprevalence
• ISSN: 0304-4017; 1873-2550; 1873-2550
• DOI: 10.1016/j.vetpar.2016.06.018

•Simulations reveal biases in the calculation of global seroprevalence.•It is important to consider effect of age, gender, habitat and dog abilities.•There is a clear causal factor between outdoor and longer exposure to the vector. Canine leishmaniasis is a parasitic disease caused by Leishmania infantum and is transmitted by Phlebotominae vectors. Despite numerous publications on the subject, some essential aspects of the epidemiology are not yet sufficiently clear. We proposed a stochastic model with the aim of identifying some important gaps in the current knowledge of leishmaniasis, such as the frequency of vector infection or a dog’s life expectancy depending on their purpose and their health status. We only found that the purpose was a significant factor. Furthermore, we detected relationships among age, gender and habitat with the dogs’ purposes that can affect the calculation of the overall seroprevalence of the analysed sample. The development of this model will allow us to discard potential confounding factors as gender, age, purpose or habitat.