Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy at Tufts University, Boston, Massachusetts, United States of America.
Feed the Future Innovation Lab for Nutrition, Boston, Massachusetts, United States of America.
PLoS One. 2020 Nov 5;15(11):e0241791. doi: 10.1371/journal.pone.0241791. eCollection 2020.
Household food insecurity remains a major policy challenge in low-income countries. Identifying accurate measures that are relatively easy to collect has long been an important priority for governments seeking to better understand and fund solutions for communities in remote settings. Conventional approaches based on surveys can be time-consuming and costly, while data derived from satellite imagery represent proxies focused on biological processes (such as rainfall and crop growth) lack granularity in terms of human behaviors. As a result, there has recently been interest in tapping into the large digital footprint offered by mobile phone usage. This paper explores empirical relationships between data relating to mobile phones (ownership and spending on service use), and food insecurity in rural Nepal. The work explores models for estimating community-level food insecurity through aggregated mobile phone variables in a proof-of-concept approach. In addition, sensitivity analyses were performed by considering the performance of the models under different settings. The results suggest that mobile phone variables on ownership and expenditure can be used to estimate food insecurity with reasonable accuracy. This suggests that such an approach can be used in and beyond Nepal as an option for collecting timely food insecurity information, either alone or in combination with conventional approaches.
家庭粮食不安全仍然是低收入国家面临的一个主要政策挑战。长期以来，各国政府一直高度重视寻找准确且易于收集的衡量指标，以便更好地了解和为偏远地区社区的解决办法提供资金。基于调查的传统方法既费时又费钱，而源自卫星图像的数据代表了侧重于生物过程（如降雨和作物生长）的代理指标，在人类行为方面缺乏粒度。因此，最近人们对利用手机使用所提供的大量数字足迹产生了兴趣。本文探讨了与尼泊尔农村地区手机（拥有和服务使用支出）相关的数据与粮食不安全之间的实证关系。这项工作通过聚合手机变量来探索在概念验证方法中估算社区粮食不安全程度的模型。此外，还通过考虑不同设置下模型的性能进行了敏感性分析。结果表明，手机拥有量和支出变量可用于估算粮食不安全状况，准确度尚可。这表明，这种方法可以在尼泊尔内外作为一种收集及时粮食不安全信息的选择，无论是单独使用还是与传统方法结合使用。
