Laboratory for Epidemic Modeling and Analysis, Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University, 6997801, Tel Aviv, Israel.
Center for Combatting Pandemics, Tel Aviv University, 6997801, Tel Aviv, Israel.
BMC Public Health. 2021 Mar 25;21(1):596. doi: 10.1186/s12889-021-10561-x.
Applying heavy nationwide restrictions is a powerful method to curtail COVID-19 transmission but poses a significant humanitarian and economic crisis. Thus, it is essential to improve our understanding of COVID-19 transmission, and develop more focused and effective strategies. As human mobility drives transmission, data from cellphone devices can be utilized to achieve these goals.
We analyzed aggregated and anonymized mobility data from the cell phone devices of> 3 million users between February 1, 2020, to May 16, 2020 - in which several movement restrictions were applied and lifted in Israel. We integrated these mobility patterns into age-, risk- and region-structured transmission model. Calibrated to coronavirus incidence in 250 regions covering Israel, we evaluated the efficacy and effectiveness in decreasing morbidity and mortality of applying localized and temporal lockdowns (stay-at-home order).
Poorer regions exhibited lower and slower compliance with the restrictions. Our transmission model further indicated that individuals from impoverished areas were associated with high transmission rates. Considering a horizon of 1-3 years, we found that to reduce COVID-19 mortality, school closure has an adverse effect, while interventions focusing on the elderly are the most efficient. We also found that applying localized and temporal lockdowns during regional outbreaks reduces the overall mortality and morbidity compared to nationwide lockdowns. These trends were consistent across vast ranges of epidemiological parameters, and potential seasonal forcing.
More resources should be devoted to helping impoverished regions. Utilizing cellphone data despite being anonymized and aggregated can help policymakers worldwide identify hotspots and apply designated strategies against future COVID-19 outbreaks.
实施全国范围的严格限制是遏制 COVID-19 传播的有力手段，但会带来巨大的人道主义和经济危机。因此，提高我们对 COVID-19 传播的认识，并制定更有针对性和更有效的策略至关重要。由于人员流动驱动了传播，因此可以利用手机设备中的数据来实现这些目标。
我们分析了 2020 年 2 月 1 日至 5 月 16 日期间，来自 300 多万用户的手机设备的汇总和匿名移动数据，在此期间以色列实施并取消了多项流动限制。我们将这些移动模式整合到了按年龄、风险和地区结构的传播模型中。该模型根据 250 个涵盖以色列的地区的冠状病毒发病率进行了校准，评估了在地方和时间上实施封锁（居家令）以降低发病率和死亡率的效果和效率。
较贫困的地区表现出较低和较慢的限制遵守程度。我们的传播模型进一步表明，来自贫困地区的个体与高传播率有关。考虑到 1-3 年的时间范围，我们发现，要降低 COVID-19 的死亡率，关闭学校会产生不利影响，而针对老年人的干预措施则最为有效。我们还发现，在地区性爆发期间实施局部和临时封锁，与全国范围的封锁相比，可以降低整体死亡率和发病率。这些趋势在广泛的流行病学参数和潜在的季节性影响范围内均具有一致性。
应该投入更多资源来帮助贫困地区。尽管手机数据是匿名和汇总的，但可以帮助全球政策制定者识别热点，并针对未来的 COVID-19 爆发实施指定策略。
