Strategic Understanding of Symptom Variation and Long-Term Risks: A Data-Driven Perspective
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.
Full Text:
PDFDOI: https://doi.org/10.5430/jms.v16n1p1
Journal of Management and Strategy
ISSN 1923-3965 (Print) ISSN 1923-3973 (Online)
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