ArticlePloS one2021
Impact of natural disasters on consumer behavior: Case of the 2017 El Niño phenomenon in Peru.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Assessing the usefulness of digital contact tracing using real-world contact data.Scientific reports · 2026Article
- Epidemiological dynamics of dengue in Peru: Temporal and spatial drivers between 2000 and 2022.PloS one · 2025Article
- Measuring accessibility to public services and infrastructure criticality for disasters risk management.Scientific reports · 2023Article
- Sugar-sweetened beverage purchases in urban Peru before the implementation of taxation and warning label policies: a baseline study.BMC public health · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
El Niño is an extreme weather event featuring unusual warming of surface waters in the eastern equatorial Pacific Ocean. This phenomenon is characterized by heavy rains and floods that negatively affect the economic activities of the impacted areas. Understanding how this phenomenon influences consumption behavior at different granularity levels is essential for recommending strategies to normalize the situation. With this aim, we performed a multi-scale analysis of data associated with bank transactions involving credit and debit cards. Our findings can be summarized into two main results: Coarse-grained analysis reveals the presence of the El Niño phenomenon and the recovery time in a given territory, while fine-grained analysis demonstrates a change in individuals' purchasing patterns and in merchant relevance as a consequence of the climatic event. The results also indicate that society successfully withstood the natural disaster owing to the economic structure built over time. In this study, we present a new method that may be useful for better characterizing future extreme events.
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