Department of Mathematics, University of Florida, Gainesville, FL, 32611, USA.
Department of Biology, Hopkins Marine Station, Woods Institute for the Environment, Center for Innovation in Global Health, Stanford University, Pacific Grove, CA, 93950, USA.
Nat Ecol Evol. 2017 Aug;1(8):1153-1159. doi: 10.1038/s41559-017-0221-8. Epub 2017 Jul 3.
The world's rural poor rely heavily on their immediate natural environment for subsistence and suffer high rates of morbidity and mortality from infectious diseases. We present a general framework for modelling subsistence and health of the rural poor by coupling simple dynamic models of population ecology with those for economic growth. The models show that feedbacks between the biological and economic systems can lead to a state of persistent poverty. Analyses of a wide range of specific systems under alternative assumptions show the existence of three possible regimes corresponding to a globally stable development equilibrium, a globally stable poverty equilibrium and bistability. Bistability consistently emerges as a property of generalized disease-economic systems for about a fifth of the feasible parameter space. The overall proportion of parameters leading to poverty is larger than that resulting in healthy/wealthy development. All the systems are found to be most sensitive to human disease parameters. The framework highlights feedbacks, processes and parameters that are important to measure in studies of rural poverty to identify effective pathways towards sustainable development.
世界上的农村贫困人口主要依赖其直接的自然环境来维持生计,他们因传染病而导致发病率和死亡率居高不下。我们提出了一个通过将人口生态学的简单动态模型与经济增长模型相结合来模拟农村贫困人口的生存和健康状况的通用框架。这些模型表明,生物系统和经济系统之间的反馈可能导致持续贫困的状态。在不同假设下对广泛的具体系统进行分析表明,存在三种可能的状态,对应于全球稳定发展的均衡、全球稳定贫困的均衡和双稳态。双稳态作为广义疾病经济系统的一个特性,在大约五分之一的可行参数空间中始终存在。导致贫困的参数总体比例大于导致健康/富裕发展的参数比例。所有系统都被发现对人类疾病参数最为敏感。该框架突出了在农村贫困研究中需要测量的反馈、过程和参数,以确定实现可持续发展的有效途径。