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Abstract：
COVID-19 scenarios were run using an epidemiological mathematical model (system dynamics model) and counterfactual analysis to simulate the impacts of different control and containment measures on cumulative infections and deaths in Bangladesh and Pakistan. The simulations were based on national-level data concerning vaccination level, hospital capacity, and other factors, from the World Health Organization, the World Bank, and the Our World in Data web portal. These data were added to cumulative infections and death data from government agencies covering the period from 18 March 2020 to 28 February 2022. Baseline curves for Pakistan and Bangladesh were obtained using piecewise fitting with a consideration of different events against the reported data and allowing for less than 5% random errors in cumulative infections and deaths. The results indicate that Bangladesh could have achieved more reductions in each key outcome measure by shifting its initial lockdown at least five days backward, while Pakistan would have needed to extend its lockdown to achieve comparable improvements. Bangladesh\'s second lockdown appears to have been better timed than Pakistan\'s. There were potential benefits from starting the third lockdown two weeks earlier for Bangladesh and from combining this with the fourth lockdown or canceling the fourth lockdown altogether. Adding a two-week lockdown at the beginning of the upward slope of the second wave could have led to a more than 40 percent reduction in cumulative infections and a 35 percent reduction in cumulative deaths for both countries. However, Bangladesh\'s reductions were more sensitive to the duration of the lockdown. Pakistan\'s response was more constrained by medical resources, while Bangladesh\'s outcomes were more sensitive to both vaccination timing and capacities. More benefits were lost when combining multiple scenarios for Bangladesh compared to the same combinations in Pakistan. Clearly, cumulative infections and deaths could have been highly impacted by adjusting the control and containment measures in both national settings. However, COVID-19 outcomes were more sensitive to adjustment interventions for the Bangladesh context. Disaggregated analyses, using a wider range of factors, may reveal several sub-national dynamics. Nonetheless, the current research demonstrates the relevance of lockdown timing adjustments and discrete adjustments to several other control and containment measures.
摘要：
使用流行病学数学模型（系统动力学模型）和反事实分析运行COVID-19情景，以模拟不同的控制和遏制措施对孟加拉国和巴基斯坦累积感染和死亡的影响。模拟基于关于疫苗接种水平的国家级数据，医院能力,和其他因素，来自世界卫生组织，世界银行,和我们的世界数据门户网站。这些数据被添加到2020年3月18日至2022年2月28日期间政府机构的累计感染和死亡数据中。巴基斯坦和孟加拉国的基线曲线是使用分段拟合获得的，考虑了与报告数据的不同事件，并允许累积感染和死亡的随机误差小于5％。结果表明，孟加拉国可以通过将其最初的封锁至少向后移动五天，在每个关键成果指标上实现更多的削减，而巴基斯坦需要延长封锁以实现可比的改进。孟加拉国的第二次封锁似乎比巴基斯坦的时机更好。两周前开始孟加拉国的第三次封锁，以及将其与第四次封锁结合起来或完全取消第四次封锁，都有潜在的好处。在第二波上升斜坡开始时增加两周的封锁可能会导致两个国家的累积感染减少40%以上，累积死亡人数减少35%。然而,孟加拉国的削减对封锁的持续时间更为敏感。巴基斯坦的反应受到医疗资源的限制更大，而孟加拉国的结果对疫苗接种时间和能力更敏感。与巴基斯坦的相同组合相比，孟加拉国的多种方案组合时损失了更多的好处。显然,通过调整这两个国家的控制和遏制措施，累积感染和死亡可能会受到高度影响。然而,COVID-19结果对孟加拉国背景下的调整干预更敏感。分类分析，使用更广泛的因素，可能会揭示几个地方的动态。尽管如此，当前的研究表明，锁定时间调整和离散调整与其他几种控制和遏制措施的相关性。
