ENRICHING GEOGRAPHIC-INFORMATION SYSTEMS WITH GEOLOCATION ATTRIBUTES TO ENHANCE ACCURACY OF PANDEMIC-BIO-SURVEILLANCE MULTI PATHOGEN SYSTEMS

1 . A tangible, non-transitory, machine-readable medium storing instructions that, when executed by one or more processors, effectuate operations comprising:

receiving, with a computer system, from a client computing device of a user associated with a given geolocation, an attribute of the geolocation that affects propensity of a pathogen to be transmitted at the geolocation;

updating, with the computer system, a geographic-pathogen-risk score of the given geolocation based on the attribute;

obtaining, with the computer system, movement transactions indicating other geolocations to which users moved from the given geolocation;

updating, with the computer system, a geographic-pathogen-risk scores of the other geolocations based on the attribute or the updated geographic-pathogen-risk score of the given geolocation; and

storing, with the computer system, in memory, the updated geographic-pathogen-risk scores of the given geolocation and the other geolocations.

2 . The medium of claim 1 , wherein the given geolocation is a building, and the attribute is one of the following:

an attribute indicative of an air filtration system of the building;

an attribute indicative of a cleaning protocol of the building;

an attribute indicative of an ultraviolet light of the building;

an attribute indicative circulation of outside air into the building;

an attribute indicative of touchless automatic doors of the building;

an attribute indicative of humidity of air in the building;

an attribute indicative of temperature of air in the building;

an attribute indicative of sunlight in the building;

an attribute indicative of persistence of a pathogen on surfaces in the building; or

an attribute indicative of sneeze guards in the building.

3 . The medium of claim 1 , wherein the given geolocation is a building, and receiving the attribute comprises receiving at least four of the following different types of attributes:

an attribute indicative of an air filtration system of the building;

an attribute indicative of a cleaning protocol of the building;

an attribute indicative of an ultraviolet light of the building;

an attribute indicative circulation of outside air into the building;

an attribute indicative of touchless automatic doors of the building;

an attribute indicative of humidity of air in the building;

an attribute indicative of temperature of air in the building;

an attribute indicative of sunlight in the building;

an attribute indicative of persistence of a pathogen on surfaces in the building; or

an attribute indicative of sneeze guards in the building.

4 . The medium of claim 1 , wherein the given geolocation is a building, and receiving the attribute comprises receiving each of the following different types of attributes:

an attribute indicative of an air filtration system of the building;

an attribute indicative of a cleaning protocol of the building;

an attribute indicative of an ultraviolet light of the building;

an attribute indicative circulation of outside air into the building;

an attribute indicative of touchless automatic doors of the building;

an attribute indicative of humidity of air in the building;

an attribute indicative of temperature of air in the building;

an attribute indicative of sunlight in the building;

an attribute indicative of persistence of a pathogen on surfaces in the building; and

an attribute indicative of sneeze guards in the building.

5 . The medium of claim 1 , wherein the operations further comprise:

authenticating the user associated with the building and determining the user associated with the building is authorized to provide attributes of the geolocation.

6 . The medium of claim 1 , wherein the operations comprise:

receiving characterizations of the attribute from each of a plurality of users associated with the building;

determining at least some of characterizations of the attribute disagree; and

selecting a characterization of the attribute from among the received characterizations as the attribute.

7 . The medium of claim 6 , wherein selecting the characterization of the attribute comprises determining a majority characterization.

8 . The medium of claim 6 , wherein selecting the characterization of the attribute comprises selecting based on user-reliability scores indicative of accuracy of past characterizations of other attributes of other buildings by the plurality of users.

9 . The medium of claim 1 , wherein the operations comprise:

receiving a plurality of attributes, including the attribute, of the geolocation that affect propensity of the pathogen to be transmitted at the geolocation; and

determining a cumulative score from the plurality of attributes, wherein updating the geographic-pathogen-risk score of the given geolocation is based on the cumulative score.

10 . The medium of claim 9 , wherein the cumulative score indicates a non-linear combination of effects from the plurality of attributes on propensity of the pathogen to be transmitted at the geolocation.

11 . The medium of claim 9 , wherein the cumulative score is determined by accessing six-or-higher dimensional interaction matrix, the interaction matrix including an n-by-n matrix, where n is a number of attributes that is six or higher, having values indicating interactions between respective combinations of attributes.

12 . The medium of claim 9 , wherein the cumulative score is determined by a machine learning model trained to estimate cumulative effects of four or more attributes on propensity of the pathogen to be transmitted.

13 . The medium of claim 1 , wherein the operation further comprise:

steps for determining a cumulative effect of a plurality of attributes on propensity of the pathogen to be transmitted.

14 . The medium of claim 1 , wherein updating the geographic-pathogen-risk score of the given geolocation based on the attribute comprises updating a plurality of different geographic-pathogen-risk scores of the given geolocation based on the attribute, each of the different geographic-pathogen-risk scores corresponding to a different pathogen, wherein the different pathogens are affected differently by the attribute.

15 . The medium of claim 1 , wherein updating the geographic-pathogen-risk score of the given geolocation based on the attribute comprises updating a plurality of different geographic-pathogen-risk scores of the given geolocation based on the attribute, each of the different geographic-pathogen-risk scores corresponding to a different variant of a pathogen.

16 . The medium of claim 1 , wherein the operations comprise:

obtaining, with the computer system, first data about at least some of a plurality of geolocations including the given geolocation and the other geolocations, wherein:

the first data is updated less frequently than a first rate, and

the first data is not pathogen specific;

obtaining, with the computer system, second data about at least some of the plurality of geolocations, wherein:

the second data is updated more frequently than a second rate that is more frequent than the first rate, and

the second data is pathogen-specific;

determining, with the computer system, geolocation-pathogen-risk scores of the geographic regions based on both the first data and the second data;

determining, with the computer system, geolocation-pathogen-risk scores of the places of interest with a machine learning model trained to allocate risk of geographic regions to places of interest within those geographic regions based on at least some of the first data, such that at least some places of interest in the same geographic region have different geolocation-pathogen-risk scores; and

storing, with the computer system, the geolocation-pathogen-risk scores of the places of interest and the geolocation-pathogen-risk scores of the geographic regions in memory, wherein:

the first data is static data;

the second data is dynamic data;

at least some of the geographic regions are reporting districts;

at least some of the places of interest are smaller than 1 , 000 square meters;

the geolocation-pathogen-risk scores of the places of interest and the geolocation-pathogen-risk scores of the geographic regions are specific to the corresponding geolocations and are independent of potential visitors to those corresponding geolocations;

the static data includes census data updated once per decade; and

the dynamic data includes amounts of infections, vaccinations, or deaths attributable to a given pathogen in the geographic regions updated at least daily.

17 . The medium of claim 1 , wherein geographic-pathogen-risk scores of the other geolocations is performed with means for concurrently computing geographic-pathogen-risk scores.

18 . The medium of claim 1 , wherein the operations further comprise:

steps for reducing latency when querying a geographic information system;

steps for calculating geolocation-pathogen-risk scores; and

steps for personal-pathogen-risk-scoring for a plurality of variants of a plurality of pathogens.

19 . The medium of claim 1 , wherein:

the given geolocation is a building, and receiving the attribute comprises receiving each of the following different types of attributes:

an attribute indicative of an air filtration system of the building;

an attribute indicative of a cleaning protocol of the building;

an attribute indicative of an ultraviolet light of the building;

an attribute indicative circulation of outside air into the building;

an attribute indicative of touchless automatic doors of the building;

an attribute indicative of humidity of air in the building;

an attribute indicative of temperature of air in the building;

an attribute indicative of sunlight in the building;

an attribute indicative of persistence of a pathogen on surfaces in the building; and

an attribute indicative of sneeze guards in the building;

the operations further comprise:

authenticating the user associated with the building and determining the user associated with the building is authorized to provide attributes of the geolocation;

receiving characterizations of the attribute from each of a plurality of users associated with the building;

determining at least some of characterizations of the attribute disagree;

selecting a characterization of the attribute from among the received characterizations as the attribute, wherein selecting the characterization of the attribute comprises determining a majority characterization or selecting based on user-reliability scores indicative of accuracy of past characterizations of other attributes of other buildings by the plurality of users;

receiving a plurality of attributes, including the attribute, of the geolocation that affect propensity of the pathogen to be transmitted at the geolocation;

determining a cumulative score from the plurality of attributes, wherein updating the geographic-pathogen-risk score of the given geolocation is based on the cumulative score, wherein the cumulative score indicates a non-linear combination of effects from the plurality of attributes on propensity of the pathogen to be transmitted at the geolocation, and wherein the cumulative score is determined by:

accessing six-or-higher dimensional interaction matrix, the interaction matrix including an n-by-n matrix, where n is a number of attributes that is six or higher, having values indicating interactions between respective combinations of attributes, or

a machine learning model trained to estimate cumulative effects of four or more attributes on propensity of the pathogen to be transmitted;

updating the geographic-pathogen-risk score of the given geolocation based on the attribute comprises updating a plurality of different geographic-pathogen-risk scores of the given geolocation based on the attribute, each of the different geographic-pathogen-risk scores corresponding to a different pathogen, wherein the different pathogens are affected differently by the attribute;

updating the geographic-pathogen-risk score of the given geolocation based on the attribute comprises updating a plurality of different geographic-pathogen-risk scores of the given geolocation based on the attribute, each of the different geographic-pathogen-risk scores corresponding to a different variant of a pathogen; and

the operations further comprise:

obtaining, with the computer system, first data about at least some of a plurality of geolocations including the given geolocation and the other geolocations, wherein:

the first data is updated less frequently than a first rate, and

the first data is not pathogen specific;

obtaining, with the computer system, second data about at least some of the plurality of geolocations, wherein:

the second data is updated more frequently than a second rate that is more frequent than the first rate, and

the second data is pathogen-specific;

determining, with the computer system, geolocation-pathogen-risk scores of the geographic regions based on both the first data and the second data;

determining, with the computer system, geolocation-pathogen-risk scores of the places of interest with a machine learning model trained to allocate risk of geographic regions to places of interest within those geographic regions based on at least some of the first data, such that at least some places of interest in the same geographic region have different geolocation-pathogen-risk scores; and

storing, with the computer system, the geolocation-pathogen-risk scores of the places of interest and the geolocation-pathogen-risk scores of the geographic regions in memory, wherein:

the first data is static data;

the second data is dynamic data;

at least some of the geographic regions are reporting districts;

at least some of the places of interest are smaller than 1,000 square meters;

the geolocation-pathogen-risk scores of the places of interest and the geolocation-pathogen-risk scores of the geographic regions are specific to the corresponding geolocations and are independent of potential visitors to those corresponding geolocations;

the static data includes census data updated once per decade; and

the dynamic data includes amounts of infections, vaccinations, or deaths attributable to a given pathogen in the geographic regions updated at least daily.

20 . A method comprising:

receiving, with a computer system, from a client computing device of a user associated with a given geolocation, an attribute of the geolocation that affects propensity of a pathogen to be transmitted at the geolocation;

updating, with the computer system, a geographic-pathogen-risk score of the given geolocation based on the attribute;

obtaining, with the computer system, movement transactions indicating other geolocations to which users moved from the given geolocation;

updating, with the computer system, a geographic-pathogen-risk scores of the other geolocations based on the attribute or the updated geographic-pathogen-risk score of the given geolocation; and

storing, with the computer system, in memory, the updated geographic-pathogen-risk scores of the given geolocation and the other geolocations.