Validating Behavioral Proxies for Disease Risk Monitoring via Large-Scale E-commerce Data
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866908783157968896 |
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| author | Sasaya, Naomi Kishida, Shigefumi Kikuchi, Ryo Tajima, Akira |
| author_facet | Sasaya, Naomi Kishida, Shigefumi Kikuchi, Ryo Tajima, Akira |
| contents | Digital traces of daily activities, such as e-commerce (EC) purchase histories, provide scalable signals for public health surveillance, yet their epidemiological validity remains unclear. This study validates a behavioral proxy for disease onset, defined as transitions from regular to therapeutic diets, by comparing large-scale EC data (N=55,645) against independent insurance-derived clinical records. Using feline lower urinary tract disease (FLUTD) as a case study, the proxy showed strong agreement with clinical data for ingredient-level risk patterns (r=0.74) and seasonal dynamics (r=0.82). Furthermore, analysis using EC data alone reproduced the established protective association of wet food consumption. These results demonstrate that validated behavioral signals from EC data can serve as cost-effective complements to traditional surveillance, with potential applicability to monitoring lifestyle-related diseases in human populations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_14795 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Validating Behavioral Proxies for Disease Risk Monitoring via Large-Scale E-commerce Data Sasaya, Naomi Kishida, Shigefumi Kikuchi, Ryo Tajima, Akira Social and Information Networks Populations and Evolution Digital traces of daily activities, such as e-commerce (EC) purchase histories, provide scalable signals for public health surveillance, yet their epidemiological validity remains unclear. This study validates a behavioral proxy for disease onset, defined as transitions from regular to therapeutic diets, by comparing large-scale EC data (N=55,645) against independent insurance-derived clinical records. Using feline lower urinary tract disease (FLUTD) as a case study, the proxy showed strong agreement with clinical data for ingredient-level risk patterns (r=0.74) and seasonal dynamics (r=0.82). Furthermore, analysis using EC data alone reproduced the established protective association of wet food consumption. These results demonstrate that validated behavioral signals from EC data can serve as cost-effective complements to traditional surveillance, with potential applicability to monitoring lifestyle-related diseases in human populations. |
| title | Validating Behavioral Proxies for Disease Risk Monitoring via Large-Scale E-commerce Data |
| topic | Social and Information Networks Populations and Evolution |
| url | https://arxiv.org/abs/2601.14795 |