DETAILED ACTION
Status
This Final Office Action is in response to the communication filed on 30 October 2025. Claims 2-4, 8, 10-12, 14-16, and 20-23 have been canceled currently or previously, claims 1, 9, and 13 have been amended, and no claims have been amended or added; therefore, claims 1, 5-7, 9, 13, and 17-19 are pending and presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
A summary of the Examiner’s Response to Applicant’s amendment:
Applicant’s amendment overcomes the claim objection(s); therefore, the Examiner withdraws the objection(s).
Applicant’s amendment does not overcome the rejection(s) under 35 USC § 101; therefore, the Examiner maintains the rejection(s) while updating phrasing in keeping with current examination guidelines.
Applicant’s amendment overcomes the rejection(s) under 35 USC §§ 102 and/or 103; therefore, the Examiner places new grounds of rejection.
Applicant’s arguments are found to be not persuasive; please see the Response to Arguments below.
Examiner’s Note
The Examiner notes that claim 1 recites “outputting information related to the subject determined to be tested for a disease, the information including identification information of a person who is estimated to have the disease among the plurality of persons, by at least one of a visual or acoustic output for use by healthcare staff in a medical facility”. The Examiner notes that the phrase “by at least one of a visual or acoustic output” is apparently in reference to the form of output rather than the information or identity of the person as grammar may suggest. Further, the phrase “for use by healthcare staff in a medical facility” is not a positive recitation requiring use by healthcare staff, it is actually intended or expected use that may be granted little if any patentable weight per MPEP §§ 2103(I)(C), 2111.04, and examples at 2106.04(d)(2).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 5-7, 9, 13, and 17-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Please see the following Subject Matter Eligibility (“SME”) analysis:
For analysis under SME Step 1, the claims herein are directed to methods, which would be classified under one of the listed statutory classifications (SME Step 1=Yes).
For analysis under revised SME Step 2A, Prong 1, independent claim 1 recites a method carried out on a computing device with one or more processors and a memory storing one or more programs executed by the one or more processors, the method comprising: collecting location information of each of a plurality of persons including at least one infected person and at least one non-infected person, each of the plurality of persons possessing a location information transmitting device configured to transmit identification information and location information to a plurality of receivers installed at fixed positions throughout a defined space, each of the plurality of receivers communicating with the computing device in real time or at a predetermined time interval to update the location information of the plurality of persons; and calculating a probability of being infected with a disease for each of the plurality of persons, based on infected person information including identification information and disease information of an infected person of the plurality of persons and the location information of each of the plurality of persons, wherein the disease information of the infected person indicates a contagious disease having a disease spreading route differentiated according to contact, droplets, and airborne, wherein the probability of being infected is calculated by calculating a disease spreading probability between the plurality of persons, the disease spreading probability calculated based on the infected person information and the location information of each of the plurality of persons, the calculating the disease spreading probability including determining a disease spreading power corresponding to the disease information of the infected person, determining a risk function corresponding to the disease information of the infected person, the risk function determined according to the disease spreading route indicated by the disease information of the infected person, calculating a contact degree between the plurality of persons based on the risk function and the location information of each of the plurality persons, and determining the disease spreading probability as a product of the disease spreading power and the contact degree, wherein the plurality of receivers are configured to receive the location information of each of the plurality of persons relative to at least one of the plurality of receivers, the location information indicating a specific time corresponding to the respectively received location information and a location within the defined space of each of the plurality of persons at the specific time, and wherein the computing device is configured to determine a disease latent period corresponding to the disease information of the infected person based on a latent period table for a plurality of diseases, the latent period table stored in the memory, and set a searching period for calculating the disease spreading probability based on the disease latent period for each of the plurality of diseases, the searching period having a starting time that is set according to an inflow time of the infected person or according to a disease onset time and an ending time that is set according to a current time, the method further comprising: determining a subject to be tested for the disease among the plurality of persons, based on the disease information of the infected person and the location information of each of the plurality of persons corresponding to the searching period: and outputting information related to the subject determined to be tested for a disease, the information including identification information of a person who is estimated to have the disease among the plurality of persons, by at least one of a visual or acoustic output for use by healthcare staff in a medical facility.
Independent claim 9 recites a method carried out on a computing device with one or more processors and a memory storing one or more programs executed by the one or more processors, the method comprising the same or similar activities as at claim 1 above as well as determining a subject to be tested based on the disease information of the infected person and the location information of each of the plurality of persons.
Independent claim 13 recites a method carried out on a computing device with one or more processors and a memory storing one or more programs executed by the one or more processors, the method comprising the same or similar activities as at claim 1 above and also calculating a disease spreading probability between the plurality of persons based on infected person information including identification information and disease information of an infected person of the plurality of persons, calculating a ratio of a disease spreading probability between the plurality of persons and at least one contact person who is in contact with the plurality of persons, with respect to each of the plurality of persons; and calculating a probability of having a disease of each of the plurality of persons, based on the ratio and the location information of each of the plurality of persons.
The dependent claims (claims 5-7 and 17-19) appear to be encompassed by the abstract idea of the independent claims since they merely indicate calculating a probability of being infected as based on primary and secondary contacts (claims 5 and 17), the probability of being infected is a maximum value of being infected determined according to contact routes (claims 6 and 18), and/or having a plurality of infected persons, calculating the probability of being infected in consideration of each infected person, and determining an arithmetic mean of the probability of being infected (claims 7 and 19).
The underlined portions of the claims are an indication of elements additional to the abstract idea (to be considered below).
The claim elements may be summarized as the idea of calculating probabilities related to having a disease or disease spreading and/or identifying persons to test for a disease – noting that the “determining a subject” of independent claim 9 appears to be (or encompass) the “determining a person” as at dependent claims 20-22; however, the Examiner notes that although this summary of the claims is provided, the analysis regarding subject matter eligibility considers the entirety of the claim elements, both individually and as a whole (or ordered combination). This idea is within the following grouping(s) of subject matter:
Mathematical concepts (e.g., relationships, formulas, equations, and/or calculations) – since the claims specifically and/or generally are performing calculations regarding infection probability, disease spreading probability, etc., and including one or more formulas in prose;
Certain methods of organizing human activity (e.g. fundamental economic principles or practices such as hedging, insurance, mitigating risk; commercial or legal interactions such as agreements, contracts, legal obligations, advertising, marketing or sales activities/behaviors, or business relations; and/or managing personal behavior or relationships between people such as social activities, teaching, and following rules or instructions) – since long managed their behavior and/or relationships by estimating or calculating the probability to either get or prevent disease transmission (i.e., pox parties vs. quarantine or isolation); and
Therefore, the claims are found to be directed to an abstract idea.
For analysis under revised SME Step 2A, Prong 2, the above judicial exception is not integrated into a practical application because the additional elements do not impose a meaningful limit on the judicial exception when evaluated individually and as a combination. The additional elements are that the methods are carried out on a computing device with transmitters and receivers configured to communicate with each other and the computing device one or more processors and a memory storing one or more programs executed by the one or more processors.
These additional elements do not reflect an improvement in the functioning of a computer or an improvement to other technology or technical field, effect a particular treatment or prophylaxis for a disease or medical condition (there is no medical disease or condition, much less a treatment or prophylaxis for one), implement the judicial exception with, or by using in conjunction with, a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing (there is no transformation/reduction of a physical article), and/or apply or use the judicial exception in some other meaningful way beyond generically linking use of the judicial exception to a particular technological environment.
The claims appear to merely apply the judicial exception, include instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform the abstract idea. The additional elements appear to merely add insignificant extra-solution activity to the judicial exception and/or generally link the use of the judicial exception to a particular technological environment or field of use.
For analysis under SME Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as indicated above, are merely “[a]dding the words ‘apply it’ (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp.” that MPEP § 2106.05(I)(A) indicates to be insignificant activity.
There is no indication the Examiner can find in the record regarding any specialized computer hardware or other “inventive” components, but rather, the claims merely indicate computer components which appear to be generic components and therefore do not satisfy an inventive concept that would constitute “significantly more” with respect to eligibility. The only apparent description in Applicant’s specification regarding the computers that may be used is Applicant pp. 68-69 as submitted (¶¶ 0224-0229 as published) describing a generic or general-purpose computer.
The individual elements therefore do not appear to offer any significance beyond the application of the abstract idea itself, and there does not appear to be any additional benefit or significance indicated by the ordered combination, i.e., there does not appear to be any synergy or special import to the claim as a whole other than the application of the idea itself.
The dependent claims, as indicated above, appear encompassed by the abstract idea since they merely limit the idea itself; therefore the dependent claims do not add significantly more than the idea.
Therefore, SME Step 2B=No, any additional elements, whether taken individually or as an ordered whole in combination, do not amount to significantly more than the abstract idea, including analysis of the dependent claims.
Please see the Subject Matter Eligibility (SME) guidance and instruction materials at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility, which includes the latest guidance, memoranda, and update(s) for further information.
NOTICE
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 5-7, 9, 13, and 17-19 are rejected under 35 U.S.C. 102 as being anticipated by Chatterjea et al. (U.S. Patent Application Publication No. 2020/0176125, hereinafter Chatterjea).
Claim 1: Chatterjea discloses a method carried out on a computing device with one or more processors and a memory storing one or more programs executed by the one or more processors, the method comprising:
collecting location information of each of a plurality of persons including at least one infected person and at least one non-infected person, each of the plurality of persons possessing a location information transmitting device configured to transmit identification information and location information to a plurality of receivers installed at fixed positions throughout a defined space, each of the plurality of receivers communicating with the computing device in real time or at a predetermined time interval to update the location information of the plurality of persons (see Chatterjea at least at, e.g., ¶¶ 0010, “an infectious disease transmission tracking system includes a real-time locating system (RTLS) including tags and tag readers in which the tag readers are distributed through a monitored area and are configured to track locations of the tags in the monitored area”, 0043, “RTLS systems are comprised of various tags (which may be referred to by other nomenclatures, e.g. as badges), platforms (Wi-Fi, Infrared, Ultrasound, and others), hardware infrastructure (tag readers and tag exciters, in the case of passive tags that must be externally energized) and other components (e.g. server computers and non-transitory storage medium storing software readable and executable by the server(s) to perform RTLS operations such as tracking tagged entities). Typically, an RTLS consists of either specialized fixed location sensors (i.e. tag readers) receiving wireless signals from small ID badges or other types of tags attached to equipment or persons, or fixed beacons (i.e. RF, infrared or ultrasound beacons) providing location information to ID badges or other types of tags attached to equipment or persons”; citation hereafter by number only); and
calculating a probability of being infected with a disease for each of the plurality of persons, based on infected person information including identification information and disease information of an infected person of the plurality of persons and the location information of each of the plurality of persons (0010, “an infectious disease transmission tracking system includes a real-time locating system (RTLS) including tags and tag readers in which the tag readers are distributed through a monitored area and are configured to track locations of the tags in the monitored area. A non-transitory storage medium stores a map of the monitored area. A nodes database stores information on nodes in which each node is a person, a mobile object, or a map zone and the nodes database stores information on the nodes including at least (i) an identification of each node as a person, a mobile object, or a map zone, (ii) an identification of a tag associated with each node that is identified as a person or a mobile object, (iii) locational information on the map for each node that is identified as a map zone, and (iv) an infection likelihood for each node with respect to a tracked pathogen”, “computing an infectious zone on the map along the pathway using the infectious transmission information stored in the pathogen database; for each node contacting the infectious zone, adjusting the infection likelihood of the contacting node in the nodes database based on at least the infectious transmission information for the tracked pathogen and designating the contacting node as an infected node if the updated infection likelihood of the contacting node satisfies the infected criterion, the adjusting of the infection likelihood of the contacting node in the nodes database being determined by the equation: p=f(d, a, t, s, T, H, o, i, h), where d is a distance between two nodes; a is air flow characteristics between the two nodes; t is a time passed since one of the nodes was last in contact with the pathogen of interest; s is a type of surface of the node, T is a temperature in the vicinity of the node; H is a humidity value in the vicinity of the node; o is an order of node from the node which is considered to be the original source of infection; I is a number of times that the nodes have encountered each other since first getting infected; and h is an execution of hygiene regime”),
wherein the disease information of the infected person indicates a contagious disease having a disease spreading route differentiated according to contact, droplets, and airborne (0038, “The range of infectious transmission can also vary depending upon the transmission pathway (contact, airborne, or droplets), and the likelihood of transmission may depend on exposure time”),
wherein the probability of being infected is calculated by calculating a disease spreading probability between the plurality of persons, the disease spreading probability calculated based on the infected person information and the location information of each of the plurality of persons (0010, as cited above), the calculating the disease spreading probability including
determining a disease spreading power corresponding to the disease information of the infected person (0073, “as the RTLS 12 monitors the location of all nodes 18 in real-time, it continuously computes checks to see which pair of nodes should be connected by an edge and, if so, the at least one electronic processor 22 is programmed to assign a weight to the edge. The weight assigned to a node 18 corresponds to the probability that one node can infect the other. If both nodes 18 are in a position to infect each other, the edge is assigned the higher probability, i.e. weight. An edge is assigned between two nodes if the probability of one node infecting another is higher than a particular threshold p, where p (the weight assigned to the edge) is computed as follows: p=f(d, a, t, s, T, H, o, i, h), … where d: is a distance between the two nodes (i.e., a closest possible distance between the nodes); a is air flow characteristics (e.g. air velocity/pressure/etc.) between two nodes if they are connected through a common HVAC system; t is a time that has passed since the node was last in contact with the pathogen of interest; s is a type of surface (e.g. non-porous/textile/etc.) that predominantly defines the node; T is a temperature in the vicinity of the node; H is a humidity in the vicinity of the node; o is an order of node from the node which is considered to be the original source of infection; i is a number of times that the nodes have encountered each other since first getting infected; and h is an execution of hygiene regime (e.g. when a nurse uses a hand sanitizer, a room is disinfected, etc.). FIG. 5 shows a graph illustrating how p might vary over time (t) for different pathogens, given specific values for d, a, s, T, H, o, i and h. As shown in FIG. 5, the “top” curve is data for a first pathogen A, and the “bottom” curve is data for a second pathogen B”),
determining a risk function corresponding to the disease information of the infected person, the risk function determined according to the disease spreading route indicated by the disease information of the infected person (0010, as cited above, and 0066, “width of the infectious zone 36 around the pathway 35 may be adjusted based on various factors, such as the time the infected node 18 spends in each map zone (the infectious zone 36 may be widened if the infected node 18 spends more time in a given map zone), or based on the airborne residency of the particular pathogen whose transmission is being tracked (e.g., the infectious zone 36 may be widened if the pathogen has a longer airborne residency, or may be narrowed if the pathogen has a shorter airborne residency or cannot be transmitted by the airborne pathway)”),
calculating a contact degree between the plurality of persons based on the risk function and the location information of each of the plurality persons (0010, tracking location and residency time as applied to “the equation: p=f(d, a, t, s, T, H, o, i, h), where d is a distance between two nodes; a is air flow characteristics between the two nodes; t is a time passed since one of the nodes was last in contact with the pathogen of interest; s is a type of surface of the node, T is a temperature in the vicinity of the node; H is a humidity value in the vicinity of the node; o is an order of node from the node which is considered to be the original source of infection; I is a number of times that the nodes have encountered each other since first getting infected; and h is an execution of hygiene regime”), and
determining the disease spreading probability as a product of the disease spreading power and the contact degree (0010, as cited above)
wherein the plurality of receivers are configured to receive the location information of each of the plurality of persons relative to at least one of the plurality of receivers, the location information indicating a specific time corresponding to the respectively received location information and a location within the defined space of each of the plurality of persons at the specific time, the receiving performed in real time or at a predetermined time interval (0010, “a real-time locating system (RTLS) including tags and tag readers in which the tag readers are distributed through a monitored area and are configured to track locations of the tags in the monitored area. At least one electronic processor is in operative communication with the RTLS to receive locations of tags in the monitored area”, 0038, “the RTLS may identify the location of a patient with high spatial resolution in a patient hospital room, but with coarser resolution in hallways. The range of infectious transmission can also vary depending upon the transmission pathway (contact, airborne, or droplets), and the likelihood of transmission may depend on exposure time”), and
wherein the computing device is configured to
determine a disease latent period corresponding to the disease information of the infected person based on a latent period table for a plurality of diseases, the latent period table stored in the memory (0032, “identifying individuals who may be infectious but not yet symptomatic by utilizing RTLS data and data about incubation periods of specific pathogens of interest”, 0051, “Additional guidance can be provided by improved dynamic (temporal) updating of the infection probabilities. For example, if the pathogen has an incubation period of 12 hours before symptoms arise, then any person identified as infectious who is asymptomatic after 12 hours can be re-classified as not infected”), and
set a searching period for calculating the disease spreading probability based on the disease latent period for each of the plurality of diseases, the searching period having a starting time that is set according to an inflow time of the infected person or according to a disease onset time and an ending time that is set according to a current time (0051, “Additional guidance can be provided by improved dynamic (temporal) updating of the infection probabilities. For example, if the pathogen has an incubation period of 12 hours before symptoms arise, then any person identified as infectious who is asymptomatic after 12 hours can be re-classified as not infected”, 0077, “information about the incubation period of the pathogen of interest is determined. In one example, if the RTLS system 12 detects that a medical professional (i.e., a nurse) comes into contact with a known infected patient and does not follow the proper hygiene protocol (e.g. does not wash hands after interacting with patient), the system notes the time at which this violation occurred. It then starts a counter to keep track of the time that has passed since this violation occurred. The system generates an alarm (e.g., on the display device 26 or through a speaker system (not shown) installed in the monitoring area A) the moment the incubation period of the pathogen has passed. For example, if the incubation period of the pathogen is 30 hours, the system generates an alarm 30 hours after the first violation is detected. In this example, if the nurse has been infected, the nurse would be a silent carrier at this stage, i.e. no symptoms would be present”),
the method further comprising:
determining a subject to be tested for the disease among the plurality of persons, based on the disease information of the infected person and the location information of each of the plurality of persons corresponding to the searching period (0018, “a system with a selection strategy that indicates which high-risk individual (e.g., patients, and medical staff, and so forth) need to be tested for infection using NGS”, 0019, “a system with a selection strategy that indicates which high-risk rooms or areas (e.g., areas of the hospital, and so forth) need to be tested for infection using NGS”, 0032, “once test results confirm that the observed symptoms are due to the pathogen of interest the necessary hygiene protocols can immediately be put in place, e.g. relevant individuals can be sent for further tests or quarantined or infected rooms can be disinfected”): and
outputting information related to the subject determined to be tested for a disease, the information including identification information of a person who is estimated to have the disease among the plurality of persons, by at least one of a visual or acoustic output for use by healthcare staff in a medical facility (0077, “The system generates an alarm (e.g., on the display device 26 or through a speaker system (not shown) installed in the monitoring area A) the moment the incubation period of the pathogen has passed. For example, if the incubation period of the pathogen is 30 hours, the system generates an alarm 30 hours after the first violation is detected. In this example, if the nurse has been infected, the nurse would be a silent carrier at this stage, i.e. no symptoms would be present”).
Claim 5: Chatterjea discloses the method of claim 1, wherein the at least one non-infected person includes a primary contact person who is in contact with one of the at least one infected person and a secondary contact person who is in contact with the primary contact person, wherein the calculating the probability of being infected includes calculating a probability of being infected with a disease of the primary contact person, and wherein the probability of being infected is calculated based on the probability of being infected with a disease of the primary contact person and a disease spreading probability between the primary contact person and the secondary contact person (0010, “A nodes database stores information on nodes in which each node is a person, a mobile object, or a map zone and the nodes database stores information on the nodes including at least (i) an identification of each node as a person, a mobile object, or a map zone, (ii) an identification of a tag associated with each node that is identified as a person or a mobile object, (iii) locational information on the map for each node that is identified as a map zone, and (iv) an infection likelihood for each node with respect to a tracked pathogen” – a node as a person).
Claim 6: Chatterjea discloses the method of claim 1, wherein calculating the probability of being infected includes calculating a probability of being infected with a disease of a specific person within the defined space according to each of a plurality of contact routes between the specific person and one of the at least one infected person, and wherein the probability of being infected with the disease of the specific person is determined by a maximum value of the probability of being infected with the disease of the specific person, the maximum value calculated according to each of the plurality of contact routes (0010, “A nodes database stores information on nodes in which each node is a person, a mobile object, or a map zone and the nodes database stores information on the nodes including at least (i) an identification of each node as a person, a mobile object, or a map zone, (ii) an identification of a tag associated with each node that is identified as a person or a mobile object, (iii) locational information on the map for each node that is identified as a map zone, and (iv) an infection likelihood for each node with respect to a tracked pathogen. A pathogen database stores infectious transmission information for at least the tracked pathogen including one or more transmission modes for the tracked pathogen and at least one node residency time for the tracked pathogen. The storage medium includes instructions readable and executable by the at least one electronic processor to perform an infectious disease transmission tracking method including: computing a pathway on the map of at least one infected node using locations of the tag associated with the infected node received from the RTLS wherein an infected node has a non-zero infection likelihood respective to the tracked pathogen which satisfies an infected criterion; computing an infectious zone on the map along the pathway using the infectious transmission information stored in the pathogen database; for each node contacting the infectious zone, adjusting the infection likelihood of the contacting node in the nodes database based on at least the infectious transmission information for the tracked pathogen and designating the contacting node as an infected node if the updated infection likelihood of the contacting node satisfies the infected criterion, the adjusting of the infection likelihood of the contacting node in the nodes database being determined by the equation: p=f(d, a, t, s, T, H, o, i, h), where d is a distance between two nodes; a is air flow characteristics between the two nodes; t is a time passed since one of the nodes was last in contact with the pathogen of interest; s is a type of surface of the node, T is a temperature in the vicinity of the node; H is a humidity value in the vicinity of the node; o is an order of node from the node which is considered to be the original source of infection; I is a number of times that the nodes have encountered each other since first getting infected; and h is an execution of hygiene regime”).
Claim 7: Chatterjea discloses the method of claim 1, wherein the at least one infected person includes a plurality of infected persons, wherein the calculating the probability of being infected includes: independently calculating the probability of being infected with a disease of each of the plurality of persons, in consideration of a disease spreading effect by each of the plurality of infected persons; and determining an arithmetic mean value of the probability of being infected with a disease of each of the plurality of persons, as a probability of being infected with a disease of each of the plurality of persons, wherein the arithmetic mean value is independently calculated in consideration of the disease spreading effect by each of the plurality of infected persons (0010, “A nodes database stores information on nodes in which each node is a person, a mobile object, or a map zone and the nodes database stores information on the nodes including at least (i) an identification of each node as a person, a mobile object, or a map zone, (ii) an identification of a tag associated with each node that is identified as a person or a mobile object, (iii) locational information on the map for each node that is identified as a map zone, and (iv) an infection likelihood for each node with respect to a tracked pathogen. A pathogen database stores infectious transmission information for at least the tracked pathogen including one or more transmission modes for the tracked pathogen and at least one node residency time for the tracked pathogen. The storage medium includes instructions readable and executable by the at least one electronic processor to perform an infectious disease transmission tracking method including: computing a pathway on the map of at least one infected node using locations of the tag associated with the infected node received from the RTLS wherein an infected node has a non-zero infection likelihood respective to the tracked pathogen which satisfies an infected criterion; computing an infectious zone on the map along the pathway using the infectious transmission information stored in the pathogen database; for each node contacting the infectious zone, adjusting the infection likelihood of the contacting node in the nodes database based on at least the infectious transmission information for the tracked pathogen and designating the contacting node as an infected node if the updated infection likelihood of the contacting node satisfies the infected criterion, the adjusting of the infection likelihood of the contacting node in the nodes database being determined by the equation: p=f(d, a, t, s, T, H, o, i, h), where d is a distance between two nodes; a is air flow characteristics between the two nodes; t is a time passed since one of the nodes was last in contact with the pathogen of interest; s is a type of surface of the node, T is a temperature in the vicinity of the node; H is a humidity value in the vicinity of the node; o is an order of node from the node which is considered to be the original source of infection; I is a number of times that the nodes have encountered each other since first getting infected; and h is an execution of hygiene regime”)).
Claim 9 is rejected on the same basis as claim 1 above since Chatterjea discloses a method carried out on a computing device with one or more processors and a memory storing one or more programs executed by the one or more processors, the method comprising the same or similar activities as at claim 1 and also further
receiving infected person information including identification information of an infected person of the plurality of persons and disease information of the infected person from a user (0084, “NGS screening is optionally fed back to the infectious disease transmission tracking system 10 to appropriately update the list of infected nodes 18. For example, if a node 18 which is a person is screened by NGS or another test for the tracked pathogen, that person may test positive in which case the person is known to be infected with the tracked pathogen, or may test negative in which case the person is known to not be infected with the tracked pathogen. If the person has tested negative for the tracked pathogen, then the system 10 responds by re-designating the person as not infected”);
determining a subject to be tested for a disease among the plurality of persons by calculating a disease spreading probability between the plurality of persons, based on the disease information of the infected person and the location information of each of the plurality of persons corresponding to a searching period (0018, “a system with a selection strategy that indicates which high-risk individual (e.g., patients, and medical staff, and so forth) need to be tested for infection using NGS”, 0019, “a system with a selection strategy that indicates which high-risk rooms or areas (e.g., areas of the hospital, and so forth) need to be tested for infection using NGS”, 0032, “once test results confirm that the observed symptoms are due to the pathogen of interest the necessary hygiene protocols can immediately be put in place, e.g. relevant individuals can be sent for further tests or quarantined or infected rooms can be disinfected”); and
outputting information related to the subject to be tested for a disease, the information including identification information of a person who is estimated to have the disease among the plurality of persons, by at least one of a visual or acoustic output for use by healthcare staff in a medical facility (0077, “The system generates an alarm (e.g., on the display device 26 or through a speaker system (not shown) installed in the monitoring area A) the moment the incubation period of the pathogen has passed. For example, if the incubation period of the pathogen is 30 hours, the system generates an alarm 30 hours after the first violation is detected. In this example, if the nurse has been infected, the nurse would be a silent carrier at this stage, i.e. no symptoms would be present”, 0078, “The infectious disease transmission tracking system 10 allows the health care facility to only send those individuals considered to be at the greatest risk to be sent for further health check-ups/tests (e.g. NGS testing)”).
Claims 13 and 17-19 are rejected on the same basis as claims 1, 5-7, and 9 above since Chatterjea discloses a method carried out on a computing device with one or more processors and a memory storing one or more programs executed by the one or more processors, the method comprising the same or similar steps as at claims 1, 5-7, and 9 above, including
calculating a ratio of a disease spreading probability between the plurality of persons and at least one contact person who is in contact with the plurality of persons, with respect to each of the plurality of persons; and (0064, “labeling the infected node as having a percentage of infection likelihood (e.g., 25%, 50%, 100%, and so forth)”).
Response to Arguments
Applicant's arguments filed 30 October 2025 have been fully considered but they are not persuasive.
Applicant first argues the 101 rejections (Remarks at 16-19), alleging that “there is the presence of an infrastructure-specific implementation” (Id. at 16) since this indicates “a particular technological environment, requiring specialized transmitters and receivers operating with real-time or interval-based communication” (Id. at 17). However, the transmitters and receivers appear to be generic – e.g., the same as used in shopping malls and/or stores, casinos, etc. – and there is no indication of anything be “specialized” with regard to them.
Applicant then argues that “there is the inclusion of disease-specific clinical parameters” (Id.); however, that is just the data that is looked up and used for the mathematical calculations, as part of the abstract idea.
Applicant then argues that “Most critically, there is actionable prophylactic output” (Id. at 17-18); however, MPEP § 2106.04(d)(2) indicates that a treatment or prophylaxis must be particular, more than nominal or insignificant, and not “Merely Extra-Solution Activity Or A Field Of Use”. The claims only provide a notification output; there is not a positive recitation of treatment, and the prophylaxis effect of the notification (if there is one) is not required to be followed or acted upon. As examples, MPEP § 2106.04(d)(2) indicates
If the limitation does not actually provide a treatment or prophylaxis, e.g., it is merely an intended use of the claimed invention or a field of use limitation, then it cannot integrate a judicial exception under the "treatment or prophylaxis" consideration. For example, a step of "prescribing a topical steroid to a patient with eczema" is not a positive limitation because it does not require that the steroid actually be used by or on the patient, and a recitation that a claimed product is a "pharmaceutical composition" or that a "feed dispenser is operable to dispense a mineral supplement" are not affirmative limitations because they are merely indicating how the claimed invention might be used.
This appears analogous the instant claims – just as merely prescribing treatment need not produce a result, so does merely providing a notification that a person should be tested not require an actual result. It would appear that even requiring the actual testing would still not necessarily be a particular prophylaxis in that MPEP § 2106.04(d)(2) appears to indicate that only the actual prevention of disease transfer would qualify as a treatment or prophylaxis that would constitute a practical application.
Applicant then argues Step 2B (Remarks at 18-19), alleging that the transmitter and receivers, the stored data table, and the output “effect concrete improvements in resource allocation, infection monitoring, and disease control” (Id. at 18). However, as noted above, the claims merely provide a notification output regarding a person that should be tested – the claims do not actually improve resource allocation, infection monitoring, nor disease control.
Applicant then argues the 103 rejections (Remarks at 19-25) based on the amended portions of the claims, alleging that Chatterjea does not disclose the time period for searching for persons (i.e., “nodes” as in Chatterjea) (Id. at 19-20); however, Chatterjea indicates considering the incubation period for a disease being used in finding those persons that are to be assessed or tested – see the rejections above. Using the term “latent” instead of “incubation” does not appear to convey patentability – the terms appear to mean the same thing in the current context.
Applicant then argues Brown (Id. at 21-22); however, based on the current phrasing and limitations, Brown does not appear required as a secondary reference. amendment necessitates new grounds of rejection – see the current rejections above. Therefore, the argument is considered moot and not persuasive.
Applicant then argues the ratio calculation of claim 13 (Id. at 23-24), arguing several indications from the specification (Id., especially at 23); however, MPEP § 2111.01(II) indicates that it is improper to import claim limitations from the specification. The claim 13 recites calculating a ratio of probability of spreading the disease and the percentages indicated in Chatterjea appear to be just that (i.e., 25% is a ratio of 25/100).
Therefore, the Examiner is not persuaded by Applicant’s argument(s).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Fuerst et al. (U.S. Patent Application Publication No. 2006/0036619, hereinafter Fuerst) also appears to be a 102(a)(1) reference, indicating “The method of the present invention derives the illness probability of any selected person from a database of people stored in a computer and/or on a computer network using collected relational data from every person in the database, including whether a person has a contact relationship with another person in said database and utilizes a database of illnesses infection probability functions given different illnesses and states of nature including data relating to social relationship; type of disease; probability function of infection given a time unit; length of contact of the particular contact relationship link; and calculates at least one relational path between said person and each person in the data base with whom there is a contact relationship, direct or via other persons in the said database for deriving the illness probability of the selected person. In addition. the method of the present invention permits selecting the optimum treatment for a patient with an infectious disease based upon recommending a drug or drugs deemed optimum for treating the patient and permits generating alerts for the detection of emergency events such as the outbreak of an infectious disease or a biological, chemical or nuclear attack and for diseases management. Moreover, in accordance with the method of the present invention a given patient may compare his or her medical record with summary information of patients with similar defined criteria.” (at Abstract).
Wallace et al. (U.S. Patent Application Publication No. 2014/0167917, hereinafter Wallace) also appears to be a 102(a)(1) reference, indicating “The present invention is a system and method for disease mapping and infection control. It may collect data from many sources, including through the tracking of Entities and external sources. Such data may be analysed by the system and represented visually. The system further facilitates data modelling. The present invention facilitates calculations of risk and exposure to an infection posed to a person, location or community. The system may be used to test and monitor infection spread and control measures. It can further be configured so as to produce reporting based upon its data to produce information relevant to the creation of infection control policies. The reports may also be utilized to develop standards and measures to improve the operation response to an outbreak of infection within an Institution or a Geographical Area, at the syndromic or pandemic levels.” (at Abstract).
Kwok et al., Epidemic Models of Contact Tracing: Systematic Review of Transmission Studies of Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome. Comput Struct Biotechnol J. 2019 Jan 26;17:186-194. doi: 10.1016/j.csbj.2019.01.003. PMID: 30809323; PMCID: PMC6376160. Downloaded 13 September 2024 from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376160/, indicating that “The emergence and reemergence of coronavirus epidemics sparked renewed concerns from global epidemiology researchers and public health administrators. Mathematical models that represented how contact tracing and follow-up may control Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) transmissions were developed for evaluating different infection control interventions, estimating likely number of infections as well as facilitating understanding of their likely epidemiology. We reviewed m