Division of Epidemiology, School of Public Health, University of California, Berkeley, CA 94720, USA.
J R Soc Interface. 2011 Dec 7;8(65):1796-803. doi: 10.1098/rsif.2011.0153. Epub 2011 May 18.
The persistence of extreme poverty is increasingly attributed to dynamic interactions between biophysical processes and economics, though there remains a dearth of integrated theoretical frameworks that can inform policy. Here, we present a stochastic model of disease-driven poverty traps. Whereas deterministic models can result in poverty traps that can only be broken by substantial external changes to the initial conditions, in the stochastic model there is always some probability that a population will leave or enter a poverty trap. We show that a 'safety net', defined as an externally enforced minimum level of health or economic conditions, can guarantee ultimate escape from a poverty trap, even if the safety net is set within the basin of attraction of the poverty trap, and even if the safety net is only in the form of a public health measure. Whereas the deterministic model implies that small improvements in initial conditions near the poverty-trap equilibrium are futile, the stochastic model suggests that the impact of changes in the location of the safety net on the rate of development may be strongest near the poverty-trap equilibrium.
极端贫困的持续存在越来越多地归因于生物物理过程和经济之间的动态相互作用，尽管仍然缺乏能够为政策提供信息的综合理论框架。在这里，我们提出了一个由疾病驱动的贫困陷阱的随机模型。虽然确定性模型可能导致只有通过初始条件的实质性外部变化才能打破的贫困陷阱，但在随机模型中，总是存在一定的概率，即人口将离开或进入贫困陷阱。我们表明，“安全网”（定义为外部强制实施的最低健康或经济条件）可以保证最终摆脱贫困陷阱，即使安全网设置在贫困陷阱的吸引盆地内，即使安全网仅采取公共卫生措施的形式。虽然确定性模型意味着在贫困陷阱平衡附近的初始条件的微小改善是徒劳的，但随机模型表明，安全网位置的变化对发展速度的影响在贫困陷阱平衡附近可能最强。
