Successful public health regimes for COVID-19 push below unity long-term regional R_t —the average number of secondary cases caused by an infectious individual. We use a susceptible-infectious-recovered (SIR) model for two coupled populations to make the conceptual point that asynchronous, variable local control, together with movement between populations, elevates long-term regional R_t, and cumulative cases, and may even prevent disease eradication that is otherwise possible. For effective pandemic mitigation strategies, it is critical that models encompass both spatiotemporal heterogeneity in transmission and movement.

中文翻译：

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运动和传播中时空变化的相互作用降低了大流行控制[人口生物学]

成功的COVID-19公共卫生制度将长期统一区域R _t降至统一水平以下，R _t是由传染性个体引起的平均继发病例数。我们使用两个耦合种群的易感感染恢复（SIR）模型来提出概念上的观点，即异步，可变的局部控制以及种群之间的移动会提高长期区域R _t和累积病例，甚至可能阻止否则有可能根除疾病。对于有效的大流行减缓策略，至关重要的是模型必须同时包含传播和运动的时空异质性。