Strategic Understanding of Symptom Variation and Long-Term Risks: A Data-Driven Perspective

Yining Fan, Xu Han, Dongli Zhang, Jinhui Wu, Yucun Chen, Shihong Yang

Abstract


Understanding how individuals respond to infectious exposure and how symptom patterns evolve over time is critical for developing effective long-term management strategies. This study examines data from northern China to analyze symptom variation and the risk of chronic progression associated with delayed response. We apply data-driven models to explore how individual characteristics—such as occupation, age, and gender—are associated with different symptom profiles and long-term outcomes. Our findings suggest that individuals engaged in agriculture, animal handling, and related sectors are significantly less likely to experience high-fever symptoms. Additionally, younger individuals and females tend to exhibit higher peak body temperatures during acute phases. Importantly, delays in response management correlate strongly with an increased likelihood of long-term complications, while general supportive actions—even without specific identification of the underlying cause—can help mitigate chronic progression. These insights contribute to more effective planning, resource prioritization, and decision-making for better strategic management of complex symptom-based conditions.


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DOI: https://doi.org/10.5430/jms.v16n1p1

Journal of Management and Strategy
ISSN 1923-3965 (Print)   ISSN 1923-3973 (Online)

 

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