RESUMO
BACKGROUND: Mepraia gajardoi and Mepraia spinolai are endemic triatomine vector species of Trypanosoma cruzi, a parasite that causes Chagas disease. These vectors inhabit arid, semiarid and Mediterranean areas of Chile. Mepraia gajardoi occurs from 18° to 25°S, and M. spinolai from 26° to 34°S. Even though both species are involved in T. cruzi transmission in the Pacific side of the Southern Cone of South America, no study has modelled their distributions at a regional scale. Therefore, the aim of this study is to estimate the potential geographical distribution of M. spinolai and M. gajardoi under current and future climate scenarios. METHODS: We used the Maxent algorithm to model the ecological niche of M. spinolai and M. gajardoi, estimating their potential distributions from current climate information and projecting their distributions to future climatic conditions under representative concentration pathways (RCP) 2.6, 4.5, 6.0 and 8.5 scenarios. Future predictions of suitability were constructed considering both higher and lower public health risk situations. RESULTS: The current potential distributions of both species were broader than their known ranges. For both species, climate change projections for 2070 in RCP 2.6, 4.5, 6.0 and 8.5 scenarios showed different results depending on the methodology used. The higher risk situation showed new suitable areas, but the lower risk situation modelled a net reduction in the future potential distribution areas of M. spinolai and M. gajardoi. CONCLUSIONS: The suitable areas for both species may be greater than currently known, generating new challenges in terms of vector control and prevention. Under future climate conditions, these species could modify their potential geographical range. Preventive measures to avoid accidental human vectorial transmission by wild vectors of T. cruzi become critical considering the uncertainty of future suitable areas projected in this study.
Assuntos
Doença de Chagas/transmissão , Mudança Climática , Insetos Vetores/fisiologia , Triatominae/fisiologia , Trypanosoma cruzi/fisiologia , Animais , Área Sob a Curva , Doença de Chagas/epidemiologia , Chile/epidemiologia , Humanos , Umidade , Insetos Vetores/parasitologia , Modelos Biológicos , Filogeografia , Curva ROC , Chuva , Medição de Risco , Temperatura , Triatominae/parasitologiaRESUMO
This paper presents a Closed Loop Input Error (CLIE) approach for on-line parametric estimation of a continuous-time model of a DC servomechanism functioning in closed loop. A standard Proportional Derivative (PD) position controller stabilizes the loop without requiring knowledge on the servomechanism parameters. The analysis of the identification algorithm takes into account the control law employed for closing the loop. The model contains four parameters that depend on the servo inertia, viscous, and Coulomb friction as well as on a constant disturbance. Lyapunov stability theory permits assessing boundedness of the signals associated to the identification algorithm. Experiments on a laboratory prototype allows evaluating the performance of the approach.