DETAILED ACTION
Applicant’s response filed 02/02/2026 has been fully considered. The following rejections and/or objections are either reiterated or newly applied.
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 .
Claim Status
Claim 21 is newly added by Applicant.
Claim 10 is cancelled by Applicant.
Claims 1-9 and 11-21 are currently pending and are herein under examination.
Claims 1-9 and 11-21 are rejected.
Priority
The instant application claims domestic benefit to US Provisional Application No. 63/171,559 filed 04/06/2021. The claim to domestic benefit is acknowledged for claims 1-9 and 11-21. As such, the effective filing date for claims 1-9 and 11-21is 06/06/2021.
Drawings
The objection to the drawings is withdrawn in view of amended drawings filed 02/02/2026. As such, the drawings filed 04/04/2022 are accepted.
Withdrawn Rejections
35 USC 112(b)
The rejection of claims 4-6, 16 and 19 under 35 USC 112(b) is withdrawn in view of claim amendment.
Claim Rejections - 35 USC § 112
35 USC 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 19 and 21 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
This rejection is newly recited as necessitated by claim amendment.
Claim 19, lines 1-2, recites the phrase “the net value for a set of control measures” which renders the claim indefinite. It is unclear if this phrase refers to the net value for the set of control measures recited in claim 18, or if the phrase refers to a different net value for a different set of control measures. To overcome this rejection, clarify how the phrase should be interpreted.
Claim 19, lines 3-4, recites the phrase “the set of control measures that has a greater net value” which lacks antecedent basis. To overcome this rejection, it is suggested to amend the phrase to “a set of control measures that has a greater net value”.
Claim 21 is indefinite because it recites a method step in a system claim, as indicated by “is updated”. MPEP 2173.05(p) recites “A single claim which claims both an apparatus and the method steps of using the apparatus is indefinite under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.” For examination purposes, claim 21 is being interpreted to mean that the one or more processors are configured to update the user interface in real-time based on the control signal. To overcome this rejection, remove the method step or clarify that the processor is configured to update the interface in real-time.
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 1-9 and 11-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Step 1 asks whether the claims recite statutory subject matter. In the instant application, claims 1-9, 11-13 and 21 recite a system, claims 14-19 recite a method, and claim 20 recite a system. As such, these claims recite statutory subject matter (Step 1: YES).
Step 2A, Prong 1:
Claims that recite statutory subject matter are analyzed under Step 2A, Prong 1 to determine if they recite any concepts that equate to an abstract idea, law of nature or natural phenomena. The instant claims recite the following limitations that equate to one or more categories of judicial exception:
Claim 1 recites “… determine a risk index associated with a risk of exposure to a health threat for each node within a chain of nodes during a stage of a journey, wherein the risk index for each node is based on occupancy characteristics of the node, a set of one or more control measures in effect to reduce the risk of exposure in the node, and a health threat prevalence in a jurisdiction associated with the node; … aggregate the risk indices for the nodes to determine a risk value associated with the stage of the journey; and wherein each node in the chain of nodes is within a common building or vehicle.”
Claim 3 recites “wherein the stage of the journey is within an airport.”
Claim 4 recites “… determine a risk index associated with the risk of exposure to the health threat for each node in the chain of nodes during a second stage of the journey, the second stage representing one of transport to the airport, at least one flight segment departing from the airport, at least one flight segment arriving to the airport, or transport from the airport.”
Claim 5 recites “wherein the risk value is a first risk value … aggregate the risk indices for the nodes during the second stage of the journey …”
Claim 6 recites “wherein the health threat prevalence in the jurisdiction associated with a node of the chain of nodes is a weighted sum of a prevalence value of local jurisdiction that encompasses the airport and respective prevalence values of jurisdictions from which flight passengers arrive at the airport.”
Claim 7 recites “wherein the risk index for each node is also based on a behavior parameter indicative of a measure of behavioral compliance of people in the respective node to the set of one or more control measures in effect.”
Claim 8 recites “wherein the risk index for each node is also based on air flow characteristics of the node.”
Claim 9 recites “… determine an adverse impact associated with implementing the set of control measures, and to calculate a net value for the set of one or more control measures based on the risk value and the adverse impact.”
Claim 11 recites “… determine the chain of nodes by predicting movement and activity of a traveler during the stage of the journey.”
Claim 12 recites “wherein the risk index that is determined for each node is a relative risk index that represents a risk of exposure at the respective node compared to a risk of exposure at one or more benchmark locations outside of the stage of the journey.”
Claim 13 recites “wherein the set of one or more control measures in effect includes multiple different types of control measures in effect, such that the risk index for each node is based on the multiple different types of the control measures in effect.”
Claim 14 recites “determining, via … a model, a risk index associated with a risk of exposure to a health threat for each node within a chain of nodes within a common building or vehicle during a stage of a journey, wherein the risk index for each node is determined based on occupancy characteristics of the node, a set of one or more control measures in effect to reduce the risk of exposure in the node, and a health threat prevalence in a jurisdiction associated with the node; aggregating the risk indices for the nodes to determine a risk value associated with the stage of the journey”
Claim 16 recites “wherein the stage of the journey is within an airport, and the method further comprises determining a risk index associated with the risk of exposure to the health threat for each of node in the chain of nodes during second stage of the journey, the second stage representing one of transport to the airport, at least one flight segment departing from the airport, at least one flight segment arriving to the airport, or transport from the airport.”
Claim 17 recites “wherein the risk index for each node is also determined based on a behavior parameter indicative of a measure of behavioral compliance of people in the respective node to the set of one or more control measures.”
Claim 18 recites “determining an adverse impact associated with implementing the set of control measures; and calculating a net value for the set of control measures based on the risk value and the adverse impact.”
Claim 19 recites “comparing the net value for a set of control measures to other net values associated with the stage of the journey that are calculated based on different sets of control measures, and selecting the set of control measures that has a greater net value as a recommended set of control measures.”
Claim 20 recites “… determine a risk index associated with a risk of exposure to a health threat for each node within a chain of nodes during a journey within a common building or vehicle, wherein the risk index for each node is based on occupancy characteristics of the node, a set of one or more control measures in effect to reduce the risk of exposure in the node, and a health threat prevalence in a jurisdiction associated with the node; … aggregate the risk indices for the nodes to determine a risk value associated with the journey and the set of one or more control measures, and to determine an adverse impact associated with implementing the set of one or more control measures; … calculate a net value for the set of control measures based on the risk value and the adverse impact.”
Limitations reciting a mental process.
The above cited limitations in claims 1, 4-9, 11-14 and 16-20 are recited at such a high level of generality that they equate to a mental process because they are similar to the concepts of collecting information, analyzing it, and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), which the courts have identified as concepts that can be practically performed in the human mind. The paragraph below discusses the limitations in these claims that recite a mental process under their broadest reasonable interpretation (BRI).
The BRI of claims 1, 4-5, 7-8, 13-14, 16-17 and 20 of calculating a risk index based on occupancy characteristics, control measures, a health threat prevalence, a behavioral parameter, and airflow characteristics includes performing calculations using the equations provided in para. [55-69], wherein the risk indexes can be aggregated through weighted means as taught in para. [21].
The BRI of claim 6 includes performing calculations to derive a weighted sum.
The BRI of claims 9 and 18 includes determining a quantitative measure of economic and operation impact associated with a set of control measures such as by a cost associated with implementing and regulating a control measure [25]. The BRI also includes subtracting the adverse impact 614 from the risk reduction 610 to derive a net value, as recited in para. [53].
The BRI of claim 11 includes predicting that a person who bought a plane ticket will go through security, wait at a terminal, and board a plane.
The BRI of claim 12 includes comparing risk indices between two locations and determining whether one node has a higher or lower associated risk, as stated in para. [20]. The specification also states “The value of the relative risk index may be a percentage or multiple of a value representing the risk of exposure at the benchmark location” [45].
The BRI of claim 19 includes comparing numbers and making a selection, which a human can practically perform.
Limitations reciting a mathematical concept.
The above cited limitations in claims 1, 4-9, 13-14, 16-18 and 20 equate to a mathematical concept because these limitations are similar to the concepts of organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)), which the courts have identified as mathematical concepts. Specifically, the BRI of calculating a risk index based on occupancy characteristics, control measures, a health threat prevalence, a behavioral parameter, and airflow characteristics includes performing calculations using the equations provided in para. [55-69], wherein the risk indexes can be aggregated through weighted means as taught in para. [21]. It also includes performing calculations to derive a weighted sum and calculating a net value by subtracting numbers.
Limitations included in the recited judicial exception.
The above cited limitations in claim 1, 14 and 20 of the nodes being within a building or vehicle and the limitation of claim 3 are included in the judicial exception of determining risk indices because they further limit the stage of the journey and each node within the chain of nodes, which are part of the judicial exception.
As such, claims 1-9 and 11-21 recite an abstract idea (Step 2A, Prong 1: YES).
Additional Elements:
Once limitations have been identified that recite a judicial exception, the claims are evaluated for additional elements. The additional elements are then analyzed under Step 2A, Prong 2 then Step 2B. The instant claims recite the following additional elements:
Claim 1 recites “A system comprising: one or more processors configured to … wherein the one or more processors are further configured to … generate a control signal to notify a user of the risk value associated with the stage of the journey.”
Claim 2 recites “a user interface on a display device, wherein the one or more processors are configured to generate the control signal to display the risk value associated with the stage on the user interface.”
Claim 4 recites “wherein the one or more processors are further configured to …”
Claim 5 recites “wherein the one or more processors are further configured to … generate a control signal to notify the user of the risk value associated with the second stage of the journey.”
Claim 9 recites “wherein the one or more processors are further configured to …”
Claim 11 recites “wherein the one or more processors are configured to …”
Claims 2-13 recite “the system”.
Claim 14 recites “… computer-implemented … generating a control signal to notify a user of the risk value associated with the stage of the journey.”
Claim 15 recites “displaying the risk value associated with the stage within a user interface on a display device.”
Claim 20 recites “A system comprising: a display device; and one or more processors communicatively connected to the display device, the one or more processors configured to … wherein the one or more processors are further configured to … wherein the one or more processors are configured to … display the net value on the display device.”
Claim 21 recites “wherein the user interface is updated in real-time based on the control signal.”
These above recited additional elements are analyzed below under both Step 2A, Prong 2 and Step 2B:
Step 2A, Prong 2:
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). The judicial exception is not integrated into a practical application because the claims do not recite additional elements that reflect an improvement to a computer, technology, or technical field (MPEP § 2106.04(d)(1) and 2106.5(a)), require a particular treatment or prophylaxis for a disease or medical condition (MPEP § 2106.04(d)(2)), implement the recited judicial exception with a particular machine that is integral to the claim (MPEP § 2106.05(b)), effect a transformation or reduction of a particular article to a different state or thing (MPEP § 2106.05(c)), nor provide some other meaningful limitation (MPEP § 2106.05(e)). Rather, the claims include limitations that equate to an equivalent of the words “apply it” and/or to instructions to implement an abstract idea on a computer (MPEP § 2106.05(f)), insignificant extra-solution activity (MPEP § 2106.05(g)), and field of use limitations (MPEP § 2106.05(h)). The paragraphs below discuss the additional elements recited above in the instant claims.
Regarding the above cited limitations in claims 1-13 and 21 of the system comprising one or more processors, in claim 14 of computer-implemented, in claims 2 and 15 of a user interface on a display device, in claim 20 of the system comprising a display device and one or more processors, these limitations require nothing more than a generic computer and/ or generic computing system. Therefore, these limitations equate to mere instructions to implement an abstract idea on a generic computer, which the courts have established does not render an abstract idea eligible in Alice Corp. 573 U.S. at 223, 110 USPQ2d at 1983.
Regarding the above cited limitations in claims 1-2, 5, 14-15 and 20 of generating a control signal to notify a user of the risk value associated with the first/second stage of the journey and generating a control signal to display the risk value associated with the first/second stage of the journey on the user interface. These limitations equate to insignificant, extra-solution activity of necessary data outputting. These limitations merely output the judicial exception (i.e., the risk value and the net value).
The limitation in claim 21 is being interpreted as intended use and is not required to be performed. As such, claim 21 is not being analyzed under Step 2A, Prong 2.
As such, claims 1-9 and 11-21 are directed to an abstract idea (Step 2A, Prong 2: NO).
Step 2B:
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). These claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because these claims recite additional elements that equate to instructions to apply the recited exception in a generic way and/or in a generic computing environment (MPEP § 2106.05(f)) and to well-understood, routine and conventional (WURC) limitations (MPEP § 2106.05(d)). The paragraphs below discuss the additional elements recited above in the instant claims.
Regarding the above cited limitations in claims 1-13 and 21 of the system comprising one or more processors configured to, in claim 14 of computer-implemented, in claims 2 and 15 of a user interface on a display device, in claim 20 of the system comprising a display device and one or more processors configured to, these limitations require nothing more than a generic computer and/ or generic computing system. Therefore these limitations equate to instructions to implement an abstract idea in a generic computing environment, which the courts have established does not provide an inventive concept in Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).
Regarding the above cited limitations in claims 1-2, 5, 14-15 and 20 of generating a control signal and displaying the risk and net value on a user interface or display device, these limitations equate to receiving/transmitting data over a network, which the courts have established as WURC limitation of a generic computer in buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014).
The limitation in claim 21 is being interpreted as intended use and is not required to be performed. As such, claim 21 is not being analyzed under Step 2B.
When these additional elements are considered individually and in combination, they do not provide an inventive concept because they all equate to WURC functions/components of a generic computer and/or generic computing system. Therefore, these additional elements do not transform the claimed judicial exception into a patent-eligible application of the judicial exception and do not amount to significantly more than the judicial exception itself (Step 2B: No).
As such, claims 1-9 and 11-21 are not patent eligible.
Response to Arguments under 35 USC 101
Applicant's arguments filed 02/02/2026 have been fully considered but they are persuasive only in part.
Applicant argues that the claims solve a problem associated with health threats within public transportation systems. Applicant appears to state that aggregating the risk indices then generating a control signal to notify a user of risk within a stage of a journey confers the practical application (pg. 9, last para. – pg 10, para. 2 of Applicant’s remarks). Applicant’s argument is not persuasive for the following reasons:
The improvement appears to be a result of calculating indices in various nodes along a journey, as recited in specification para. [4]. However, in claim 1, determining and aggregating risk indices recite an abstract idea. MPEP 210.06 recites “the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” The additional elements in claim 1 equate to implementing an abstract idea on a generic computer and to data outputting, wherein the control signal merely outputs the result of the abstract idea of aggregating the risk indices. Data outputting (MPEP 2106.05(g)) and instructions to implement an abstract idea on a generic computer do not provide a practical application (MPEP 2106.05(f)).
Applicant argues that the claims require collecting/analyzing data/information from a new source, referencing Electric Power Group (pg. 10, last para. of Applicant’s remarks). Applicant’s argument is not persuasive for the following reasons:
Applicant appears to reference limitations in claim 1 for determining and aggregating risk indices. These limitations recite a judicial exception. In Step 2B, only additional elements are evaluated for whether they recite an inventive concept.
It is noted that the independent claims do not recite acquiring data from check-in lines or queues, security screenings, waiting areas, lavatories, or restaurants. It is also noted that Electric Power Group recites “Information as such is an intangible … Accordingly, we have treated collecting information, including when limited to particular content (which does not change its character as information), as within the realm of abstract ideas.”
Applicants remarks regarding the August 2025 Memo about patent eligibility are noted (pg. 11, para. 1 of Applicant’s remarks).
Applicant argues that claim 21 is patent eligible because it depends on claim 1, and claim 21 does not recite a mental process (pg. 11, para. 3 of Applicant’s remarks). Applicant’s argument is persuasive in part. Claim 21 does not recite a mental process. However, claim 21 is not patent eligible because claim 1 is not patent eligible and because claim 21 does not render claim 1 patent eligible. It is noted that claim 21 is not required because it recites an intended use, as discussed above in section 35 USC 112(b).
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-8, 11-17 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (“Huang”; NPL ref. 2 on IDS filed 04/06/2023; previously cited) in view of Alshammari et al. (“Alshammari”; NPL ref. 3 on IDS filed 04/06/2023; previously cited) and MacKenzie (Risk analysis 34, no. 12 (2014): 2143-2162; previously cited on PTO892 mailed 11/04/2025).
The bold and italicized text below are the limitations of the instant claims, and the italicized text serves to map the prior art onto the instant claims.
Any newly recited portions herein are necessitated by claim amendment.
Claims 1 and 14:
A system comprising: one or more processors configured to determine a risk index associated with a risk of exposure to a health threat for each node within a chain of nodes during a stage of a journey,
Huang discloses a web-based geographic information system called the vector-borne disease airline importation risk (VBD-AIR) tool aimed to help define the roles of airports and airlines in the transmission/spread of vector-born disease (abstract). Huang teaches “VBD-AIR is designed to be a flexible tool that combines multiple geospatial datasets to inform on the relative risks between differing airports, flight routes, times of year, diseases, and their vectors, in promoting the movement of passengers infected by vector-borne diseases and the vectors that spread these diseases” (pg. 6, col. 1, para. 3) (Figure 5).
wherein the risk index for each node is based on occupancy characteristics of the node, a set of one or more control measures in effect to reduce the risk of exposure in the node, and a health threat prevalence in a jurisdiction associated with the node;
Huang calculates three risk assessments (risk index) called imported vector-borne disease case risk assessment, onward transmission risk assessments, and imported vector risk assessments (pg. 7, sec. Risk assessments). These risks are calculated using schedule incoming flight routes in 2011 and the traffic capacity on these routes (occupancy characteristics) (pg. 7, sec. Risk assessments) as well as “disease/vector prevalence at origin locations” (a health threat prevalence in a jurisdiction associated with the node) (pg. 7, col. 1).
However, Huang does not teach that the risk assessments are based on a set of one or more control measures to reduce the risk of exposure in a node.
Alshammari discusses the effect that global mass gatherings have on importation/exportation of infectious disease to and from host countries by international participants (abstract). Alshammari teaches “a computational epidemic simulation framework to simulate disease transmission from the arrival, to the departure of international participants in the global event of Hajj” (abstract). The framework includes an agent-based epidemic framework that “includes parameters to assign vaccination status and preventative actions for each individual. The vaccination coverage, the proportion of participants following a preventative behavior, and the effectiveness of each measure are input parameters for the framework and can be modified depending on the data. In the framework, the effect of each preventative measure is simulated by reducing the transmission probability by the effectiveness or efficiency of the applied measure” (pg. 224, para. 1; sec. 3.2).
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Huang for calculating a risk based on cities with a population over 50,000 located near an airport and disease distribution maps depicting prevalence by using a third variable based on preventative measures as taught by Alshammari. The motivation for doing so is taught by Alshammari who teaches that agent-based simulations take into account preventative measured performed by an individual and “can be used to simulate disease transmission at an individual level providing a realistic representation of epidemic progress among individuals” (pg. 291, para. 2). This motivation aligns with the teachings of Huang which are directed to epidemiology, particularly transmission and spread of vector-borne disease in airlines and airports (abstract) (pg. 2, col. 1, para. 1).
One of ordinary skill in the art would have had a reasonable expectation of success for calculating a risk by combining the preventative measures of Alshammari to the datasets of Huang because Huang teaches “It is envisioned that future research … will build upon VBD-AIR to continue to improve quantification of these aspects, drawing on newly-developed … mathematical models of transmission, to provide an evidence base to enable airports, airlines, and public health officials to assess the appropriateness and efficacy of current control, surveillance and treatment practices, and tailor strategies to these differing risk profiles for each disease, route and airport (pg. 12, col. 2, para. 2). There is also a reasonable expectation because Huang also recites “additional risk-modifying factors such as actual passenger numbers, traveler activities and prophylaxis use, seasonal variations in disease transmission, chartered flights or multiple stopovers” (pg. 7, col. 1, para. 3). Therefore, it appears VBD-AIR can be modified to incorporate mathematical models of transmission such as the agent-based simulation framework of Alshammari that takes into account individual preventative measures.
wherein the one or more processors are further configured to aggregate the risk indices for the nodes to determine a risk value associated with the stage of the journey,
Huang discloses three risk assessments (pg. 7, col. 1, para. 1) and discloses different stages of a journey including flight origin and destination (stage of the journey) (Figures 4 and 5). However, Huang does not teach aggregating the three risk assessments to derived a risk value associated with a stage of a journey.
Mackenzie teaches summarizing risk using risk measures and risk indices (abstract) and teaches aggregating risk factors together (pg. 17, sec. 3.4).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant invention to have modified the method of Huang by aggregating risk values associated with nodes along a flight path into a single measure of risk as taught by MacKenzie. Motivation for the combination is taught by MacKenzie who recites “For the risk index to be additive, MLB must equal 0. The appealing feature of this property is that an organization can separately measure multiple risks and add the risks together to obtain a numerical measure of the organization’s risk” (pg. 23, para. 2). Although this quote is directed toward an organization’s risk, MacKenzie states that risk indices are often used for disease risk (pg. 4, para. 1). MacKenzie also states that combining risk measurements “limits the risk measures to expected values or expected exponential disutility” (pg. 25, para. 1).
One of ordinary skill in the art would have had a reasonable expectation of success for aggregating risks along a proposed flight into a single risk because MacKenzie states that this can be achieved through an additive risk measure/index by combining the two or more risks together (pg. 23, para. 2).
and to generate a control signal to notify a user of the risk value associated with the stage of the journey.
Huang teaches “The VBD-AIR tool takes the form of an interactive online interface and is
targeted at users with interests in specific airports or regions, and the risks to those locations of vector-borne disease importation and onward spread, or exotic vector importation and establishment” (pg. 2, col. 2, last para.). Figure 5 shows an example of displaying risks associated with airports and flight routes. However, Huang does not teach the aggregated risk. MacKenzie teaches the aggregated risk (pg. 23, para. 2). The above combination of MacKenzie and Huang teach displaying the aggregated risk value in the Figures of 4 and 5 in Huang.
wherein each node in the chain of nodes is within a common building or vehicle.
Huang recites “The VBD-AIR … is targeted at users with interests in specific airports or regions, and the risks to those locations of vector-borne disease importation and onward spread, or exotic vector importation and establishment.” Figure 5 shows disease risks between airports connected by flight paths, wherein each airport is a node. The BRI of an airport includes it being a common building.
Regarding claim 14, the only difference between claim 1 and 14 is that claim 14 discloses “via a computer-implemented model”. Huang teaches this limitation by reciting “VBD-AIR utilizes an entity-relationship model to integrate data sources from airport locations and air routes, disease and vector distributions, global climate data, and global land-based travel time data” (pg. 3, col. 1, para. 1), wherein VBD-AIR calculates the risk assessments (Figures 4 and 5). The same prima facie case for obviousness applied to claim 1 applies to claim 14.
Claims 2-8, 11-13 and 15-17:
Regarding claims 2-3 and 15, Huang shows in Figure 5 the display output of VBD-AIR to a user, wherein the display output shows the risk assessments for airports (node and building) and flight routes.
Regarding claims 4 and 16, the broadest reasonable interpretation includes performing the same procedure as described in claims 1 and 14 on another set of airports and flight routes. Huang discloses that the risk assessments are calculated for various airports and flight routes (Figures 4 and 5). Figure 4 shows a user selecting an airport with an output being the top 10 routes based on the risk assessments.
Regarding claim 5, the broadest reasonable interpretation of claim 5 includes performing the same procedures recited in claim 1 but for other airports and flight routes (the nodes during the second stage of the journey). Thus, the same prima facie case for obvious above regarding claim 1 applies to claim 5.
Regarding claim 6, this claim is being interpreted as a product-by-process. MPEP 2113.I recites “The patentability of a product does not depend on its method of production. If the product in the product-by-process claim is the same as or obvious from a product of the prior art, the claim is unpatentable even though the prior product was made by a different process.” In this case, the “health threat prevalence in the jurisdiction associated with the node” is the product and the process is “a weighted sum of a prevalence value of local jurisdiction that encompasses the airport and respective prevalence values of jurisdictions from which flight passengers arrive at the airport”. Huang uses a dataset set called land-based travel-time which depicts travel times from an airport to a major city that has more than 50,000 people and is within 2 hours and 50km from the airport (pg. 6, col. 1, para. 3). The land-based travel-time dataset was combined with disease distribution maps, which contain disease prevalence (pg. 2, col. 2, para. 2), to calculate a maximum predicted disease risk within the 2 hours and 50km of each airport, wherein the maximum level of disease risk within these travel times and distances were assigned to each airport in all tool calculations (pg. 6, col. 1, para. 3). Huang teaches the product of a health threat prevalence in a jurisdiction associated with a node, even though the process of making the product differs from the claimed invention.
Regarding claims 7-8 and 17, Huang teaches that the risk assessments are calculated based on scheduled incoming flight routes in 2011, the traffic capacity on these routes, among other variables (pg. 7, sec. Risk assessment). However, Huang does not teach that the risk assessments are calculated based on behavioral compliance to control measures or based on air flow characteristics. Alshammari teaches that the agent-based epidemic framework uses as an input parameter “the proportion of participants following a preventative behavior” (pg. 224, para. 1) as well as contact model that takes into account how far disease droplets travel in the air when an infected person sneezes, coughs, talks or breaths and is represented as equation 1 in sec. 2.5.
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Huang for calculating risk assessments by also accounting for the proportion of participants following a preventative behavior and disease droplet travel in air as taught by Alshammari. The motivation for doing so is taught by Alshammari who teaches that agent-based simulations take into account preventative measured performed by an individual and “can be used to simulate disease transmission at an individual level providing a realistic representation of epidemic progress among individuals” (pg. 291, para. 2). This motivation aligns with the teachings of Huang which are directed to epidemiology, particularly transmission and spread of vector-borne disease in airlines and airports (abstract) (pg. 2, col. 1, para. 1).
One of ordinary skill in the art would have had a reasonable expectation of success for calculating a risk by combining the preventative measures and disease droplet calculations of Alshammari to the datasets of Huang because Huang teaches mathematical models of transmission can be incorporated into VBD-AIR to tailor strategies to these differing risk profiles for each disease, route and airport (pg. 12, col. 2, para. 2). There is also a reasonable expectation of success because Huang also recites “additional risk-modifying factors such as actual passenger numbers, traveler activities and prophylaxis use, seasonal variations in disease transmission, chartered flights or multiple stopovers” (pg. 7, col. 1, para. 3). Therefore, it appears VBD-AIR can be modified to incorporate mathematical models of transmission such as the agent-based simulation framework to calculate risk as well as calculate the three risk assessments by including a parameter of preventative measures.
Regarding claim 11, Huang does not teach predicting movement and activity of a traveler during a state of a journey. Alshammari teaches a computational epidemic simulation framework that simulates disease outbreaks at global mass gatherings that includes a population model that simulates the movements and interactions of pilgrims throughout different stages (sec. 2.2 and sec. 3.1.1).
It would have been prima facie obvious to one of ordinary skill before the effective filing date of the instant invention to have modified the method of Huang for determining disease risk for travels by incorporating an agent-based epidemic framework that simulates travel interactions and movement, as taught by Alshammari, because Alshammari states that agent-based epidemic frameworks provide a realistic representation of epidemic progress among individuals (pg. 219, para. 2). One of ordinary skill in the art would have had a reasonable expectation of success to incorporate the agent-based simulation framework of Alshammari into Huang because Huang states that VBD-AIR can incorporate mathematical models of transmission (pg. 12, col. 2, para. 2).
Regarding claim 12, Huang states that VBD-AIR generates relative risks between differing airports and flight routes (pg. 6, col. 1, last para.).
Regarding claim 13, Huang teaches that the risk assessments are calculated based on scheduled
incoming flight routes in 2011, the traffic capacity on these routes, among other variables (pg. 7, sec. Risk assessment). However, Huang does not teach that the risk assessments are calculated based on multiple different types of control measures. Alshammari teaches that the agent-based epidemic framework uses as an input parameters vaccination status and preventative actions for each individual (multiple different types of control measures) (pg. 224, para. 1).
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Huang for calculating risk assessments by also accounting for vaccination status and preventative actions for each individual as taught by Alshammari. The motivation for doing so is taught by Alshammari who teaches that agent-based simulations “can be used to simulate disease transmission at an individual level providing a realistic representation of epidemic progress among individuals” (pg. 291, para. 2). This motivation aligns with the teachings of Huang which are directed to epidemiology, particularly transmission and spread of vector-borne disease in airlines and airports (abstract) (pg. 2, col. 1, para. 1).
One of ordinary skill in the art would have had a reasonable expectation of success for calculating a risk by combining the vaccination status and preventative actions of each individual of Alshammari to the datasets of Huang because Huang teaches mathematical models of transmission can be incorporated into VBD-AIR to tailor strategies to these differing risk profiles for each disease, route and airport (pg. 12, col. 2, para. 2). There is also a reasonable expectation of success because Huang also recites “additional risk-modifying factors such as actual passenger numbers, traveler activities and prophylaxis use, seasonal variations in disease transmission, chartered flights or multiple stopovers” (pg. 7, col. 1, para. 3). Therefore, it appears VBD-AIR can be modified to incorporate mathematical models of transmission such as the agent-based simulation framework to calculate risk as well as calculate the three risk assessments by including parameters of preventative actions and vaccination status.
Regarding claim 21, Huang teaches “The controller receives inputs from the users via html form and sends it to the model” (pg. 8, col. 1, para. 2). Huang also teaches that the WBD-AIR tool is automatically responsive to user input (Figure 5a) (pg. 9, col. 1, para. 3) (pg. pg. 10, col. 1, para. 2).
Claims 9 and 18-19 rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (“Huang”; NPL ref. 2 on IDS filed 04/06/2023; previously cited) in view of Alshammari et al. (“Alshammari”; NPL ref. 3 on IDS filed 04/06/2023; previously cited) and MacKenzie (Risk analysis 34, no. 12 (2014): 2143-2162; previously cited on PTO892 mailed 11/04/2025), as applied above to claims 1 and 14, and in further view of Perkins et al. (In What is the effect of reduced street lighting on crime and road traffic injuries at night? A mixed-methods study. NIHR Journals Library, 2015; previously cited on PTO892 mailed 11/04/2025).
Any newly recited portions herein are necessitated by claim amendment.
The limitations of claims 1 and 14 have been taught in the rejection above by Huang, Alshammari and MacKenzie.
Regarding claims 9 and 18, Alshammari teaches calculating “the effect of each preventative measure is simulated by reducing the transmission probability by the effectiveness or efficiency of the applied measure” (adverse impact associated with implementing the set of control measures) (pg. 224, para. 1). However, neither Huang, Alshammari, nor MacKenzie teach calculating a net value for a control measure based one risk value and adverse impact.
Perkins teaches a cost-benefit analysis (CBA) regarding evaluating large-scale public health interventions (title). The CBA includes calculating a net present value (NPV), which is the sum of costs (adverse impact) and benefits (risk value).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant invention to have modified the method of Huang, Alshammari, and MacKenzie for generating risk values associated with control measures by performing a CBA for the control measures resulting in an NPV, as taught by Perkins. The motivation for doing so is taught by Perkins who recites “CBAs synthesize all costs and benefits of an intervention by valuing all costs and benefits in monetary units. In principle, this approach is more attractive, as all outcomes and inputs are valued in the same units, making comparisons more straightforward. When the calculation of all of the values of costs and benefits are carefully justified and made explicit, CBAs can lead to more transparent decision-making. Academics have, therefore, argued that more attention should be placed on the CBA framework when evaluating large-scale public policy interventions” (pg. 2, para. 2), particularly in public health (pg. 2, para. 3)
One of ordinary skill in the art would have had a reasonable expectation of success for performing a CBA of the control measures resulting in a NPV based on the difference between a risk value and cost of implementing a control measure because Perkins states that revealed and stated preference techniques can be used to monetize the effect of an intervention (pg. 2, para. 3). In the case of the combination, the control measures such as vaccinations and mask wearing, as taught by Alshammari, can be monetized to calculate the NPV.
Regarding claim 19, as discussed above regarding claim 18 Huang, Alshammari, nor MacKenzie teach control measures and stages of journey. However, Huang, Alshammari, nor MacKenzie do not teach calculating net values for different sets of control measures to then compare the net values and select the control measure with the greatest net value.
Perkins teaches performing a CBA analysis and comparing the NPVs between a do-nothing scenario against the part-night lighting scenario (pg. 10, para. 3-4). Perkins determined based on the comparison that after 5 years the cost of street lighting provision in the part-night lighting scenario are greater than the do-nothing scenario (pg. 10, para. 4). determining which solution has a greater net value based on the CBA (pg. 10, para. 4).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant invention to have modified the method of Huang, Alshammari and MacKenzie for incorporating individual preventative measures such as vaccination status and mask wearing when calculating disease transmission risk by determining NPVs for each control measure to then compare the net values of each CBA such that the best control measure is selected based on its benefits and costs, as taught by Perkins. Perkins teaches the motivation for doing so by reciting “There are four main types of economic evaluation currently used in public health: … CBA … CBA can lead to more transparent decision-making” (pg. 1, para. 3 – pg. 2, para. 2).
One of ordinary skill in the art would have had a reasonable expectation of success for performing a CBA using the data acquired from Huang and Alshammari because Perkins states that CBAs are performed using public health data (pg. 1, para. 3).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (“Huang”; NPL ref. 2 on IDS filed 04/06/2023; previously cited) in view of Alshammari et al. (“Alshammari”; NPL ref. 3 on IDS filed 04/06/2023; previously cited) and MacKenzie (Risk analysis 34, no. 12 (2014): 2143-2162; previously cited on PTO892 mailed 11/04/2025), and Perkins et al. (In What is the effect of reduced street lighting on crime and road traffic injuries at night? A mixed-methods study. NIHR Journals Library, 2015; previously cited on PTO892 mailed 11/04/2025).
Any newly recited portions herein are necessitated by claim amendment.
The bold and italicized text below are the limitations of the instant claims, and the italicized text serves to map the prior art onto the instant claims.
Claim 20:
A system comprising: a display device; and one or more processors communicatively connected to the display device, the one or more processors configured to determine a risk index associated with a risk of exposure to a health threat for each node within a chain of nodes during a journey within a common building or vehicle,
Huang discloses a web-based geographic information system called the vector-borne disease airline importation risk (VBD-AIR) tool aimed to help define the roles of airports and airlines in the transmission/spread of vector-born disease (abstract). VBD-AIR is an interactive online interface that users can access to display information (a display device; and one or more processors communicatively connected to the display device, the one or more processors configured to) (Figure 5). Huang teaches “VBD-AIR is designed to be a flexible tool that combines multiple geospatial datasets to inform on the relative risks between differing airports, flight routes, times of year, diseases, and their vectors, in promoting the movement of passengers infected by vector-borne diseases and the vectors that spread these diseases” (pg. 6, col. 1, para. 3) (Figure 5).
Huang recites “The VBD-AIR … is targeted at users with interests in specific airports or regions, and the risks to those locations of vector-borne disease importation and onward spread, or exotic vector importation and establishment.” Figure 5 shows disease risks between airports connected by flight paths, wherein each airport is a node. The BRI of an airport includes it being a common building.
wherein the risk index for each node is based on occupancy characteristics of the node, a set of one or more control measures in effect to reduce the risk of exposure in the node, and a health threat prevalence in a jurisdiction associated with the node;
Huang calculates three risk assessments (risk index) called imported vector-borne disease case risk assessment, onward transmission risk assessments, and imported vector risk assessments (pg. 7, sec. Risk assessments). These risks are calculated using schedule incoming flight routes in 2011 and the traffic capacity on these routes (occupancy characteristics) (pg. 7, sec. Risk assessments) as well as “disease/vector prevalence at origin locations” (pg. 7, col. 1).
However, Huang does not teach that the risk assessments are based on a set of one or more control measures to reduce the risk of exposure in a node.
Alshammari discusses the effect that global mass gatherings have on importation/exportation of infectious disease to and from host countries by international participants (abstract). Alshammari teaches “a computational epidemic simulation framework to simulate disease transmission from the arrival, to the departure of international participants in the global event of Hajj” (abstract). The framework includes an agent-based epidemic framework that “includes parameters to assign vaccination status and preventative actions for each individual. The vaccination coverage, the proportion of participants following a preventative behavior, and the effectiveness of each measure are input parameters for the framework and can be modified depending on the data. In the framework, the effect of each preventative measure is simulated by reducing the transmission probability by the effectiveness or efficiency of the applied measure” (pg. 224, para. 1; sec. 3.2).
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Huang for calculating a risk based on cities with a population over 50,000 located near an airport and disease distribution maps depicting prevalence by using a third variable based on preventative measures as taught by Alshammari. The motivation for doing so is taught by Alshammari who teaches that agent-based simulations take into account preventative measured performed by an individual and “can be used to simulate disease transmission at an individual level providing a realistic representation of epidemic progress among individuals” (pg. 291, para. 2). This motivation aligns with the teachings of Huang which are directed to epidemiology, particularly transmission and spread of vector-borne disease in airlines and airports (abstract) (pg. 2, col. 1, para. 1).
One of ordinary skill in the art would have had a reasonable expectation of success for calculating a risk by combining the preventative measures of Alshammari to the datasets of Huang because Huang teaches “It is envisioned that future research … will build upon VBD-AIR to continue to improve quantification of these aspects, drawing on newly-developed … mathematical models of transmission, to provide an evidence base to enable airports, airlines, and public health officials to assess the appropriateness and efficacy of current control, surveillance and treatment practices, and tailor strategies to these differing risk profiles for each disease, route and airport (pg. 12, col. 2, para. 2). There is also a reasonable expectation because Huang also recites “additional risk-modifying factors such as actual passenger numbers, traveler activities and prophylaxis use, seasonal variations in disease transmission, chartered flights or multiple stopovers” (pg. 7, col. 1, para. 3). Therefore, it appears VBD-AIR can be modified to incorporate mathematical models of transmission such as the agent-based simulation framework of Alshammari that takes into account individual preventative measures.
wherein the one or more processors are further configured to aggregate the risk indices for the nodes to determine a risk value associated with the journey and the set of one or more control measures, and
Huang discloses three risk assessments (pg. 7, col. 1, para. 1) and discloses different stages of a journey including flight origin and destination (stage of the journey) (Figures 4 and 5). However, Huang does not teach aggregating the three risk assessments to derived a risk value associated with a stage of a journey.
Mackenzie teaches summarizing risk using risk measures and risk indices (abstract) and teaches aggregating risk factors together (pg. 17, sec. 3.4).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant invention to have modified the method of Huang by aggregating risks along a planned flight path into a single measure of risk as taught by MacKenzie. Motivation for the combination is taught by MacKenzie who recites “For the risk index to be additive, MLB must equal 0. The appealing feature of this property is that an organization can separately measure multiple risks and add the risks together to obtain a numerical measure of the organization’s risk” (pg. 23, para. 2). Although this quote is directed toward an organizations risk, MacKenzie states that risk indices are often used for disease risk (pg. 4, para. 1). MacKenzie also states that combining risk measurements “limits the risk measures to expected values or expected exponential disutility” (pg. 25, para. 1).
One of ordinary skill in the art would have had a reasonable expectation of success for aggregating different risk assessments of Huang into a single risk because MacKenzie states that this can be achieved through an additive risk measure/index by combining the two or more risks together (pg. 23, para. 2).
to determine an adverse impact associated with implementing the set of one or more control measures;
Huang does not teach this limitation.
Alshammari teaches “the effect of each preventative measure is simulated by reducing the transmission probability by the effectiveness or efficiency of the applied measure” (pg. 224, para. 1).
It would have been prima facie obvious to one of ordinary skill before the effective filing date of the instant invention to have modified the method of Huang for determining disease risk for travels by incorporating an agent-based epidemic framework that incorporates the effects of individual control measures such as vaccination status and mask wearing to determine transmission probability, as taught by Alshammari because Alshammari states that agent-based epidemic framework provides a realistic representation of epidemic progress among individuals (pg. 219, para. 2). One of ordinary skill in the art would have had a reasonable expectation of success to incorporated the agent-based simulation framework of Alshammari into Huang because Huang states that VBD-AIR can incorporate mathematical models of transmission (pg. 12, col. 2, para. 2).
wherein the one or more processors are configured to calculate a net value for the set of control measures based on the risk value and the adverse impact, and display the net value on the display device.
Huang teaches a display device and risk values but does not teach calculating net values for control measures based on the risk value and calculated adverse impacts. As discussed above, Alshammari teaches calculating an adverse impact for a control measure. However, neither Huang, Alshammari, or MacKenzie discuss generating a net value for control measures based on risk value and adverse impact.
Perkins teaches a cost-benefit analysis (CBA) regarding evaluating large-scale public health interventions (title). The CBA includes calculating a net present value (NPV), which is the sum of costs (adverse impact) and benefits (risk value).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant invention to have modified the method of Huang, Alshammari, and MacKenzie for generating risk values associated with control measures by performing a CBA for the control measures resulting in an NPV, as taught by Perkins. The motivation for doing so is taught by Perkins who recites “CBAs synthesize all costs and benefits of an intervention by valuing all costs and benefits in monetary units. In principle, this approach is more attractive, as all outcomes and inputs are valued in the same units, making comparisons more straightforward. When the calculation of all of the values of costs and benefits are carefully justified and made explicit, CBAs can lead to more transparent decision-making. Academics have, therefore, argued that more attention should be placed on the CBA framework when evaluating large-scale public policy interventions” (pg. 2, para. 2), particularly in public health (pg. 2, para. 3).
One of ordinary skill in the art would have had a reasonable expectation of success for performing a CBA of the control measures resulting in a NPV based on the difference between a risk value and cost of implementing a control measure because Perkins states that revealed and stated preference techniques can be used to monetize the effect of an intervention (pg. 2, para. 3). In the case of the combination, the control measures such as vaccinations and mask wearing, as taught by Alshammari, can be monetized to calculate the NPV.
Response to Arguments under 35 USC 103
Applicant's arguments filed 02/02/2026 have been fully considered but they are not persuasive.
Applicant argues that Figure 5 of Huang does not teach each node within a chain of nodes is within a common building of vehicle (pg. 12-13 of Applicant’s remarks). Applicant’s argument is not persuasive for the following reasons:
Applicant appears to argue that “wherein each node in the chain of nodes is within a common building or vehicle” means that each node must be within the same common building or vehicle. However, the broadest reasonable interpretation (BRI) of this limitation includes each node being in separate common buildings or vehicles. The BRI of “a common building” includes an airport because it is a building that is shared by humans.
Huang shows in Figure 5 airports connected by flight routes. The airports are nodes in a journey. Huang recites “VBD-AIR is designed to be a flexible tool that combines multiple geospatial datasets to inform on the relative risks between differing airports” (pg. 6, col. 1, last para.). Thus each airport in a desired flight path would be a common building node in a chain of nodes.
Conclusion
No claims are allowed.
Notable, but not relied upon, prior art includes: Gaber et al. (Aviation, space, and environmental medicine 80, no. 7 (2009): 595-600; newly cited) teaches that disease transmission is more likely to occur in an airport than during a flight (pg. 598, col 1, last para.). Malaviya (US 2017/0024531 A1; newly cited) discloses real-time contact tracing which includes calculating risk scores for nodes in a pathway within a building [10][19][85][134]. Loomans et al. (REHVA Journal 2020, no. 5 (2020): 19-24; newly cited) teaches using Wells-Riley model to estimate risk of infection in buildings using building control measures and ventilation.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/N.A.A./Examiner, Art Unit 1687
/KAITLYN L MINCHELLA/Primary Examiner, Art Unit 1685