Understanding transmissibility patterns of Chagas disease through complex vector-host networks

作者：Rengifo Correa Laura; Stephens Christopher R^*; Morrone Juan J; Luis Tellez Rendon Juan; Gonzalez Salazar Constantino

来源：Parasitology, 2017, 144(6): 760-772.

DOI：10.1017/S0031182016002468

• Trypanosoma cruzi
• potential hosts
• spatial data mining
• ecological epidemiology

Chagas disease is one of the most important vector-borne zoonotic diseases in Latin America. Control strategies could be improved if transmissibility patterns of its aetiologic agent, Trypanosoma cruzi, were better understood. To understand transmissibility patterns of Chagas disease in Mexico, we inferred potential vectors and hosts of T. cruzi from geographic distributions of nine species of Triatominae and 396 wild mammal species, respectively. The most probable vectors and hosts of T. cruzi were represented in a Complex Inference Network, from which we formulated a predictive model and several associated hypotheses about the ecological epidemiology of Chagas disease. We compiled a list of confirmed mammal hosts to test our hypotheses. Our tests allowed us to predict the most important potential hosts of T. cruzi and to validate the model showing that the confirmed hosts were those predicted to be the most important hosts. We were also able to predict differences in the transmissibility of T. cruzi among triatomine species from spatial data. We hope our findings help drive efforts for future experimental studies.

• 出版日期2017-5