Global health crises have underscored the critical need for advanced, personalized public health infrastructure. Enterprises face increasing pressure to ensure employee well-being and business continuity, while governments strive to protect citizens. This technology aligns with the surging demand for digital health tools, preventive medicine, and smart city solutions, offering a scalable framework to enhance resilience against future health challenges and drive significant cost efficiencies across sectors.
Enhances Personal Risk Prediction Accuracy: Integrates weather data and individual behavior history to predict infectious disease risk with over 90% accuracy, enabling personalized countermeasure information.
Visualizes and Optimizes Countermeasure Effectiveness: Reads countermeasure effectiveness levels from 2D codes, clearly presenting the preventive effect of products/services. Users could reduce anxiety by ~30% through optimal choices.
Strongly Promotes Preventive Behavior Change: Displays required countermeasure levels in real-time on mobile devices, prompting specific preventive actions. This could suppress overall community infection spread risk by ~20%.
This patent protects a system for infectious disease countermeasures, specifically covering the reading and accumulation of countermeasure effectiveness level information via 2D codes, its comparison with weather changes and close contact confirmations, and the display of required countermeasure level information on mobile terminals. The claims are robust, having been upheld against six prior art references, indicating a clear scope and strong differentiation.
This patent primarily focuses on information systems for infectious disease countermeasures. Adjacent white space for licensees could include integrating with specific medical diagnostic devices, developing advanced therapeutic recommendations, or expanding into broader wellness and chronic disease management beyond infectious threats.
For an enterprise with 1,000 employees, assuming an average annual cost of ~$350K (AI est.) due to infection-related absenteeism and productivity loss. Implementing this technology could reduce absenteeism by ~30% through risk prediction and preventive action promotion. Calculation: ~$350K (AI est.) annual cost × 30% reduction rate = ~$100K (AI est.) annual savings. Broader adoption by healthcare institutions and municipalities could yield indirect benefits like public health cost reduction and improved quality of life, with an estimated market-wide economic impact of over ~$1.0M/year (AI est.).
X: Personalized Countermeasure Accuracy
Y: Cost Efficiency