Method to mitigate allergen symptoms in a personalized and hyperlocal manner
A system and method of determining an allergy impact profile of an individual are disclosed. The system and method may be employed to predict allergy impact environmental conditions may have on allergy symptoms of an individual and to recommend treatment of the individual in response to the predicted allergy impact.
1. A method of using a computerized processing device to determine an impact that an environmental condition may have on allergy symptom of an individual and to determine a therapeutic option for the individual, comprising:
tracking said individual's behavior data over time, wherein said individual's behavior data includes said individual's allergy symptom; behavior, environmental conditions; medications; and quality of life;
measuring an outcome for each of said individual's behavior data at multiple time points; wherein said individual's behavior data includes said individual's treatment regime (including mediation response (no response) data), adherence to use of one or more of said medications and symptom perception,
wherein measuring an outcome of said individual's behavior data includes:
calculating, for the individual, on the computerized processing device, the change in symptom and allergen outcome relationship over time (S n P n /dt) (or the modeling of nested/clustered data, wherein there are multiple individuals in each cluster) using a multivariate regression or probabilistic approach;
generating and including on the computerized processing device an analysis engine for analyzing potential treatment options based on the individual's behavior data and data regarding the individual's response (or no response) to medication in combination with the calculated change in symptom and allergen outcome relationship over time (S n P n /dt) data by applying at least a portion of the crowdsourced information acquired from the S n /P n /dt relationship between user symptoms (Sn) and allergens (P) over time (dt) and the individual's data tracked over time;
employing the analysis engine to train machine learning models for increasing the individual's pollen threshold, wherein such machine learning models are selected from support vector machines, k-nearest neighbors, random forests or mixtures thereof; and
comparing said individual's behavior data to said machine learning models, using the computerized processing device, to determine one or more of the individual's treatment recommendation(s) for increasing the individual's poller threshold.
2. The method of claim 1 , wherein said environmental conditions are selected from the group consisting of outdoor environmental conditions and indoor environmental conditions.
3. The method of claim 1 , wherein said outdoor environmental conditions are selected from the group consisting of geography, pollen, pollution, season and weather.
4. The method of claim 1 , wherein said indoor environmental conditions are selected from the group consisting of residential environmental conditions and work place environmental conditions.
5. The method of claim 1 , wherein at least one sensor is employed to determine at least one of said environmental conditions.
6. Use of the method of claim 1 on two or more individuals.