RESUMEN
Probabilistic forecasts play an indispensable role in answering questions about the spread of newly emerged pathogens. However, uncertainties about the epidemiology of emerging pathogens can make it difficult to choose among alternative model structures and assumptions. To assess the potential for uncertainties about emerging pathogens to affect forecasts of their spread, we evaluated the performance 16 forecasting models in the context of the 2015-2016 Zika epidemic in Colombia. Each model featured a different combination of assumptions about human mobility, spatiotemporal variation in transmission potential, and the number of virus introductions. We found that which model assumptions had the most ensemble weight changed through time. We additionally identified a trade-off whereby some individual models outperformed ensemble models early in the epidemic, but on average the ensembles outperformed all individual models. Our results suggest that multiple models spanning uncertainty across alternative assumptions are necessary to obtain robust forecasts for emerging infectious diseases.
Asunto(s)
Enfermedades Transmisibles Emergentes/epidemiología , Epidemias/estadística & datos numéricos , Monitoreo Epidemiológico , Infección por el Virus Zika/epidemiología , Colombia/epidemiología , Interpretación Estadística de Datos , Conjuntos de Datos como Asunto , Predicción/métodos , Humanos , Modelos Estadísticos , Análisis Espacio-Temporal , IncertidumbreRESUMEN
This work examines both positive and negative impacts that economic growth may have on the ecological dynamics and stability of a single biological species. Local extinction of the species may force the social planner to implement defensive expenditures aimed at conservation of the species population by means of habitat protection. The latter may lead to an ecological equilibrium that will be different from the natural equilibrium that would have arisen in the absence of human intervention. Moreover, the existence of such equilibrium is formally demonstrated and its stability properties are revised. Additionally, optimal-choice decision policies are constructed on the basis of Pontryagin's maximum principle. Under such policies together with initial abundance of the species, the growth trajectories will move the system towards the fixed point of maximum species abundance.