Time scaled infection risk and illness assessment method

A method of determining infection risks for individuals during an epidemic or pandemic, the method executed by a computer system and comprising:

• automatically determining and monitoring positional destinations of a first user using a first mobile electronic device of the user;
• automatically deducing as user information a location type and/or user activity of each of the positional destinations;
• automatically learning activity patterns for the user from the user information;
• assigning a user risk assessment to the first user according to locations and/or activities of the user during a predetermined timeframe;
• providing the user risk assessment to a community member via a community member electronic device;
• automatically determining a decrease deviation in the learned activity patterns during or after the predetermined timeframe from further monitoring of further user locations or further user activities;
• automatically analyzing the decrease deviation to identify a significance of the deviation, wherein analyzing the decrease deviation comprises:
• correlating the deviation to a current location of the first user to identify a temporary decrease in the learned activity patterns as a function of the current location not allowing for the learned activity patterns;
• automatically correlating the significance of the decrease deviation to a possible infection condition;
• and
• automatically alerting the first user via the first mobile electronic device or a second user via a second electronic device of the possible infection condition,
• wherein the user risk assessment is a compilation of a plurality of risk metrics determined for the locations and/or activities during the predetermined time period, and each of the risk metrics is determined from a predetermined assessment score for each of the location and any activity performed at the location, as a function of time at the location and/or performing the activity, and further comprising:
• determining a risk metric for each of the locations and/or activities for the user, to provide the plurality of risk metrics during the predetermined timeframe, wherein the determining the risk metric for the each of the locations and/or activities comprises comparing a location and/or an activity to a predetermined risk scale;
• determining a corresponding user participation time for the each of the locations and/or activities;
• scaling the risk metric for the each of the locations and/or activities according to the corresponding user participation time;
• increasing any risk metric of the user risk assessment upon an in-person contact at the each of the locations and/or activities with a person having a negative risk assessment;
• and
• computing the user risk assessment from the plurality of risk metrics.

A method of determining infection risks for individuals during an epidemic or pandemic, the method executed by a computer system and comprising:

• automatically monitoring destinations and user activities performed at the destinations of a first user via a first electronic device of the first user;
• receiving user information comprising a first user activity performed at each of the destinations upon a user arriving at the each of the destinations;
• automatically learning activity patterns for the first user activity by automatically associating the user information with the at least one of the destinations, automatically determining a user activity context for the first user activity, and automatically comparing a further context of each of a plurality of further user arrivals to the at least one of the destinations to the user activity context, wherein the activity patterns comprise an eating pattern or an exercise pattern, at a location or with one or more community members;
• automatically updating context information associated with the at least one destination from the further context of each of the further user arrivals;
• automatically identifying that the first user is participating in the first user activity upon future user arrivals at the at least one destination as a function of comparing the context information to a future context of each of the future user arrivals, without receiving any manually entered confirmation or manually entered additional user information;
• assigning a user risk assessment to the user according to locations and/or activities of the user during a predetermined timeframe, wherein the predetermined timeframe is at least a predetermined incubation or latency period of a contagion or pathogen;
• providing the user risk assessment to a community member via a community member electronic device before an in-person meeting with the user, wherein the assigning the user risk assessment comprises:
• determining a corresponding user participation time for the each of the locations and/or activities, and scaling the user risk assessment according to the corresponding user participation time for the each of the locations and/or activities;
• automatically determining a deviation in the learned activity patterns during or after the predetermined timeframe from further monitoring of further user locations or further user activities;
• automatically analyzing the deviation to identify a significance of the deviation, wherein analyzing the deviation comprises:
• correlating the deviation to a current location of the first user to identify a temporary change in the learned activity patterns as a function of the current location not allowing for the first user activity at the at least one of the destinations, and/or identifying words and/or ideas from sent or received messages via the first electronic device to identify an explanation for the deviation;
• automatically correlating the significance of the deviation to a possible infection condition;
• and
• automatically alerting the first user via the first electronic device or a second user via a second electronic device of the possible infection condition.