Institute of Evolution, Centre for Ecological Research, Konkoly-Thege M. út 29-33, Budapest, 1121, Hungary.
MTA-ELTE Theoretical Biology and Evolutionary Ecology Research Group and Department of Plant Systematics, Ecology and Theoretical Biology, Eötvös Loránd University, Pázmány Péter sétány 1/c, 1117, Budapest, Hungary.
Sci Rep. 2022 Sep 20;12(1):15716. doi: 10.1038/s41598-022-19691-7.
The pandemic reminded us that the pathogen evolution still has a serious effect on human societies. States, however, can prepare themselves for the emergence of a novel pathogen with unknown characteristics by analysing potential scenarios. Game theory offers such an appropriate tool. In our game-theoretical framework, the state is playing against a pathogen by introducing non-pharmaceutical interventions to fulfil its socio-political goals, such as guaranteeing hospital care to all needed patients, keeping the country functioning, while the applied social restrictions should be as soft as possible. With the inclusion of activity and economic sector dependent transmission rate, optimal control of lockdowns and health care capacity management is calculated. We identify the presence and length of a pre-symptomatic infectious stage of the disease to have the greatest effect on the probability to cause a pandemic. Here we show that contrary to intuition, the state should not strive for the great expansion of its health care capacities even if its goal is to provide care for all requiring it and minimize the cost of lockdowns.
大流行提醒我们，病原体进化仍然对人类社会产生严重影响。然而，各国可以通过分析潜在情景，为新出现的具有未知特征的病原体做好准备。博弈论提供了这样一个合适的工具。在我们的博弈论框架中，国家通过引入非药物干预措施来对抗病原体，以实现其社会政治目标，例如保障所有需要的患者都能得到医院治疗，维持国家运转，同时施加的社会限制应尽可能宽松。通过纳入与活动和经济部门相关的传播率，计算出对封锁和医疗保健能力管理的最优控制。我们发现疾病的无症状感染阶段的存在和持续时间对引发大流行的可能性有最大的影响。在这里，我们表明，与直觉相反，即使国家的目标是为所有需要的人提供治疗并将封锁的成本降至最低，它也不应该追求扩大医疗保健能力。
