Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications
Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications
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COVID-19 大流行期间人类需求的人口规模研究：分析和启示
DOI：
10.1145/3437963.3441788
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Althoff, Tim
中科院分区：
文献类型：
--
作者：
Suh, Jina;Horvitz, Eric;White, Ryen;Althoff, Tim
到目前为止，大多数缓解COVID-19大流行的工作都迫切关注生物医学和流行病学。然而，不能仅仅根据卫生信息作出与大流行病有关的政策决定。决策需要考虑对人民及其需求的更广泛影响。量化整个人口的人类需求具有挑战性，因为它需要高地理时间粒度，高人口覆盖率，并对季节和其他外部影响进行适当调整。在这里，我们提出了一个计算方法，马斯洛的需求层次的基础上，可以捕捉到一个整体的观点，在需求的相对变化，通过差异中的差异的方法，纠正季节性和数量变化。我们应用这种方法来描述美国生理，社会经济和心理领域人类需求的变化，基于14个月内超过36，000个邮政编码的350亿次搜索交互。分析表明，与大流行病爆发前相比，在大流行病期间，人类基本需求的表达呈指数增长，而较高层次的愿望则有所下降。在探索全州政策的时机和变化，我们发现，庇护的持续时间在地方的任务有显着影响社会和情感的需求。我们表明，潜在的障碍，以解决关键的需求，如支持失业和家庭暴力，可以通过网络搜索互动。我们的方法和结果表明，对人类需求变化的人口规模监测可以为当前和预期需求的政策和恢复工作提供信息。
Most work to date on mitigating the COVID-19 pandemic is focused urgently on biomedicine and epidemiology. Yet, pandemic-related policy decisions cannot be made on health information alone. Decisions need to consider the broader impacts on people and their needs. Quantifying human needs across the population is challenging as it requires high geo-temporal granularity, high coverage across the population, and appropriate adjustment for seasonal and other external effects. Here, we propose a computational methodology, building on Maslow's hierarchy of needs, that can capture a holistic view of relative changes in needs following the pandemic through a difference-in-differences approach that corrects for seasonality and volume variations. We apply this approach to characterize changes in human needs across physiological, socioeconomic, and psychological realms in the US, based on more than 35 billion search interactions spanning over 36,000 ZIP codes over a period of 14 months. The analyses reveal that the expression of basic human needs has increased exponentially while higher-level aspirations declined during the pandemic in comparison to the pre-pandemic period. In exploring the timing and variations in statewide policies, we find that the durations of shelter-in-place mandates have influenced social and emotional needs significantly. We demonstrate that potential barriers to addressing critical needs, such as support for unemployment and domestic violence, can be identified through web search interactions. Our approach and results suggest that population-scale monitoring of shifts in human needs can inform policies and recovery efforts for current and anticipated needs.
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