Systems and methods for targeting testing panel based on temporal, geographic, and demographic data

Abstract

Methods for targeting the results provided by a testing panel based on patient population data are provided, comprising: identifying, by one or more processors, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtaining, by the one or more processors, pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

Description

SYSTEMS AND METHODS FOR TARGETING TESTING PANEL BASED ON TEMPORAL, GEOGRAPHIC, AND DEMOGRAPHIC DATACROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims priority to U.S. Provisional App. No. 63 / 446,766, entitled “SYSTEMS AND METHODS FOR TARGETING TESTING PANEL BASED ON TEMPORAL, GEOGRAPHIC, AND DEMOGRAPHIC DATA,” and filed February 17, 2023, the disclosure of which is incorporated by reference herein in its entirety.FIELD OF THE INVENTION

[0002] The present disclosure generally relates to techniques for panels in which multiple tests (which could be individual pathogen tests, single outputs for groups of individual pathogen tests, antibiotic resistance genetic tests, etc.) are performed on the same individual and, more particularly, to targeting such panels based on patient population data.BACKGROUND

[0003] The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.

[0004] With the availability of inexpensive reagents, it is possible to test for a large number of pathogen targets for a single sample (e.g., using robotic pipetting systems, highly multiplexed syndromic panels, etc.), resulting in a large quantity of different pathogen test results for a given patient. While there are advantages to having a large quantity of different pathogen test results for a given patient in some cases, there are instances in which a smaller number of more focused pathogen test results is desired.SUMMARY

[0005] In an embodiment, a computer-implemented method for targeting results provided by a testing panel based on population data is provided, comprising: identifying, by one or more processors, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtaining, by the one or more processors, pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevantpathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

[0006] In another embodiment, a system for targeting results provided by a testing panel based on population data is provided, comprising: one or more processors, and a memory storing non-transitory, computer readable instructions that, when executed by the one or more processors, cause the one or more processors to identify, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtain pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and report, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

[0007] In still another embodiment, a non-transitory, computer-readable medium is provided, storing instructions for targeting results provided by a testing panel based on population data , that when executed by one or more processors, cause the one or more processors to: identify, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtain pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and report, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

[0008] In another embodiment, a computer-implemented method for targeting results provided by a testing panel based on population data is provided, comprising: obtaining, by one or more processors, historical pathogen testing results from a pathogen testing device; analyzing, by the one or more processors, the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device; obtaining, by the one or more processors, pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the individual.

[0009] In still another embodiment, a system for targeting results provided by a testing panel based on population data is provided, comprising: one or more processors, and a memory storing non-transitory, computer readable instructions that, when executed by the one or more processors, cause the one or more processors to: obtain historical pathogen testing results from a pathogen testing device; analyze the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device; obtain pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and report, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the individual.

[0010] Additionally, in another embodiment, a non-transitory, computer-readable medium is provided, storing instructions for targeting results provided by a testing panel based on population data , that when executed by one or more processors, cause the one or more processors to: obtain historical pathogen testing results from a pathogen testing device; analyze the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device; obtain pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and report, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the individual.BRIEF DESCRIPTION OF THE DRAWINGS

[0011] FIG. 1 illustrates syndromic trend detection rates for the USA from 2017-2020.

[0012] FIG. 2 illustrates the top five most prevalent respiratory pathogen groups for the USA for several different time periods.

[0013] FIG. 3 illustrates the top five most prevalent respiratory pathogen groups for the USA for several different time periods.

[0014] FIG. 4 illustrates the prevalence of gastrointestinal (Gl) pathogen groups for the entire USA for 2017-2020.

[0015] FIGS. 5 and 6 illustrate the top five most prevalent Gl pathogen groups for various regions of the USA for 2017-2022.

[0016] FIG. 7 illustrates the top five most prevalent pathogen groups in the USA for various periods of time.

[0017] FIG. 8A illustrates diagnostic yield over a period of time for a respiratory panel.

[0018] FIG. 8B illustrates diagnostic yield over a period of time for a Gl panel.

[0019] FIG. 9 illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for the entire USA.

[0020] FIG. 10 illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for the entire USA.

[0021] FIG. 1 1 A illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for a Midwestern USA region.

[0022] FIG. 1 1 B illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for a Northeastern USA region.

[0023] FIG. 1 1 C illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for a Western USA region.

[0024] FIG. 1 1 D illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for a Southern USA region.

[0025] FIG. 12A illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for a Midwestern USA region.

[0026] FIG. 12B illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for a Northeastern USA region.

[0027] FIG. 12C illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for a Western USA region.

[0028] FIG. 12D illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for a Southern USA region.

[0029] FIG. 13 illustrates an example of a sharp increase in a less prevalent but very medically important pathogen (Bordetella pertussis).

[0030] FIG. 14 illustrates a 36-week forecast for an Adenovirus pathogen.

[0031] FIG. 15 illustrates an exemplary system for targeting results provided by a testing panel based on patient population data, in accordance with some examples provided herein.

[0032] FIG. 16 illustrates an exemplary method for targeting results provided by a testing panel based on population data, as may be implemented by the system of FIG. 15, in accordance with some examples provided herein.

[0033] FIG. 17 is a flow diagram of an example method for targeting the results provided by a testing panel based on data from the testing device, as may be implemented by the system 100 of FIG. 15, in accordance with some examples provided herein.DETAILED DESCRIPTIONOverview

[0034] As discussed above, with the availability of inexpensive reagents, it is possible to test for a large number of pathogen targets for a single sample (e.g., using robotic pipetting systems, highly multiplexed syndromic panels, etc.), resulting in a large quantity of different pathogen test results for a given patient. While there are advantages to having a large quantity of different pathogen test results for a given patient in some cases, there are instances in which a smaller number of more focused pathogen test results can be more relevant for the patent population. For instance, positive tests for certain rare pathogen groups (e.g., Ebola, Middle East Respiratory Syndrome (MERS)) include reporting and quarantine requirements, as well as the need to use a bio-safety level 3 (BSL-3) lab for certain specimens suspected of being positive for certain pathogen groups. Because of the rarity of these pathogen groups in some populations, the chances for a false positive can be larger than the potential for a true positive. Other consequences of false positives include the mis-prescription of drugs with adverse sideeffects and over-prescription of antibiotics that could fuel antibiotic resistance. Consequently, in some cases, it may be preferable to obtain patients’ pathogen test results without including results for unlikely pathogen groups, to avoid consequences for false positives. This may be achieved either by targeting specific tests performed for the individual being tested, or by targeting specific test results provided to the individual being tested, or some combination of the two.

[0035] Furthermore, pathogen tests that are waived under the Centers for Disease Control (CDC)’s Clinical Laboratory Improvement Amendments (CLIA) may be performed by untrained or less trained individuals, who may be overwhelmed by a large quantity of different pathogen test results. Moreover, some insurance providers will only provide reimbursement for a fixednumber of pathogen test results (illustratively five or fewer). While some existing pathogen tests provide a limited menu of pathogen test results, this limited menu provided is typically made at the time of development and cannot be updated or changed after that point. However, spatial and temporal factors can alter the most relevant circulating pathogen groups for a particular patient at a particular point in time. The testing environment and patient demographics may also change which pathogen groups are relevant for a given patient.

[0036] It is understood that some pathogen diagnostics test for a single pathogen target, whereas other pathogen diagnostics test for a group of related pathogens and output a single result for that related group. For example, human rhinovirus and enterovirus are often reported together in a single assay. In another example, various parainfluenza assays may report individually for parainfluenza 1 through 4, or may provide a single report for parainfluenza generally. In yet another example, influenza A and B may be reported together or separately, and influenza A may be reported as pan-influenza A or may be subtyped. Similarly, coronaviruses may be reported as individual coronaviruses or may be grouped together as a single group. As used herein, “pathogen groups” includes both individual pathogens that are reported individually and pathogens that are grouped and reported together.

[0037] The present techniques involve providing a limited, but dynamic, menu of pathogen test results that is customized / modified based on the characteristics of the patient being tested, such as demographic information associated with the patient, the patient’s location, the patient’s occupation, the patient’s interactions with other people, communities, or animals, or other individual information regarding the patient, and the timing of the pathogen test. Surveillance pathogen testing results for various populations of interest may obtained and may be analyzed, and a set of relevant pathogen groups for each population of interest may be identified. When a pathogen test is performed for a new patient, a patient population to which the patient belongs may be identified, and the results of the pathogen test for the set of relevant pathogen groups corresponding to the population of interest to which the patient belongs may be sent to the patient, or the patient’s healthcare provider. In this way, a limited number of pathogen test results may be provided to patients without significantly sacrificing relevant pathogen test results for each particular patient. While this disclosure refers to “patients,” it is to be understood that these techniques may be applied for any individual, including an individual that is not a “patient,” i.e., is not currently seeking treatment, and / or is not known to have any diseases or conditions. For example, testing may be performed on samples that are not necessarily from “patients,” ormay be performed on animal, environmental, or other samples that may or may not be related to any patient.

[0038] For instance, FIG. 1 illustrates syndromic trend detection rates for the USA from 2017- 2020. As shown at FIG. 1 , the top five most prevalent respiratory pathogen groups for the entire USA for 2017-2020 are Humanrhinovirus / Enterovirus (HRV / EV), Respiratory Syncytial Virus (RSV), Parainfluenza Virus (PI V), Influenza A, and Coronavirus.

[0039] However, changes in prevalence of respiratory pathogen groups can occur seasonally as well as year to year. For example, as shown at FIG. 2, the top five most prevalent respiratory pathogen groups from December 26, 2021 to January 8, 2022 are Coronavirus, HRV / EV, Human Metapneumovirus, Influenza A, and Respiratory Syncytial Virus, while the top five most prevalent respiratory pathogen groups from May 29, 2022 to June 11 , 2022 are HRV / EV, Coronavirus, Parainfluenza, Adenovirus, and Respiratory Syncytial Virus, and the top five most prevalent respiratory pathogen groups from August 28, 2022 to September 10, 2022 are HRV / EV, Coronavirus, Respiratory Syncytial Virus, Adenovirus, and Parainfluenza.

[0040] Furthermore, as shown at FIG. 3, the top five most prevalent respiratory pathogen groups from March 2017 were HRV / EV, RSV, Human Metapneumovirus, Influenza B, and Coronavirus, while the top five most prevalent respiratory pathogen groups from March 2018 were HRV / EV, RSV, Human Metapneumovirus, Influenza B, and Coronavirus, and the top five most prevalent respiratory pathogen groups from March 2019 were HRV / EV, Influenza A, RSV, Human Metapneumovirus, and Coronavirus.

[0041] Moreover, as another example, changes in prevalence of Gastrointestinal (Gl) pathogen groups can occur due to geography and climate in various regions. These geospatial relationships may not be intuitive, due to population density and mobility. FIG. 4 illustrates the prevalence of Gl pathogen groups for the entire USA for 2017-2020. As shown at FIG. 4, the top five most prevalent Gl pathogen groups across the entire USA for 2017-2020 were Norovirus, Rotavirus A, Campylobacter, Adenovirus F, and Sapovirus. As shown at FIGS. 5 and 6, the top five most prevalent Gl pathogen groups for the Western region of the USA for 2017-2020 were Norovirus, Rotavirus A, Campylobacter, Adenovirus F, and Sapovirus, while the top five most prevalent Gl pathogen groups for the Midwestern region of the USA for 2017- 2020 were Norovirus, Rotavirus A, Campylobacter, Sapovirus, and Adenovirus E, the top five most prevalent Gl pathogen groups for the Northeast region of the USA for 2017-2020 were Norovirus, Campylobacter, Rotavirus A, Parasites, and Adenovirus E, and the top five mostprevalent Gl pathogen groups for the Southern region of the USA for 2017-2020 were Norovirus, Rotavirus A, Salmonella, Adenovirus F, and Sapovirus.

[0042] Additionally, epidemiological events, such as local outbreaks or pandemics, as well as environmental events, such as natural disasters, flooding, etc., can disrupt circulating pathogen groups, temporarily elevating the importance of a specific target. That is, unexpected events can temporarily change the pathogen landscape, and outbreaks might require a rapid retargeting of testing capability. For example, FIG. 7 illustrates that from December 29, 2019 to February 1 , 2020, the top five most prevalent pathogen groups in the USA were RSV, HRV / EV, Coronavirus, Influenza A, and Influenza B, while from March 29, 2020 to April 30, 2022, with the rising prevalence of severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2, the virus that causes coronavirus disease 2019 or COVID-19),, the top five most prevalent pathogen groups in the USA were HRV / EV, Adenovirus, RSV, Parainfluenza, and other Coronaviruses. Flooding is another example of an epidemiological event. With flooding, illustratively after a large storm, surveillance of waste water could be used to monitor such events. Such epidemiological signals can be used to aid in identifying the set of relevant pathogen groups to be tested.

[0043] Furthermore, medical importance may also factor into variation and may be used in identifying the set of relevant pathogen groups. An outbreak of one pathogen might be much more medically relevant than another, e.g., due to its severity (e.g. Bordetella pertussis) or its contagiousness (e.g. SARS-CoV2).

[0044] Accordingly, as provided by the present techniques, to account for variation in pathogen circulation the menu should be changed dynamically. Many factors contribute to the ‘ideal’ panel menu, including currently circulating pathogen groups, the medical relevance of various pathogen groups, outbreaks and unexpected events, etc., as discussed above.

[0045] The performance of a fixed, compared to a dynamic, menu is demonstrated below. To quantify performance, two metrics may be defined: percent positive agreement (PPA) yield and diagnostic yield.

[0046] The PPA yield is a measure of the percentage of positive interpretations that would be captured using a limited menu (fixed or dynamic).# Detections (limited panel) PPA Yield limited panel) = — — - : -z / , „ - - —# Detections (full panel)

[0047] The diagnostic yield is a measure of the number of tests that would have at least one positive result over a time period given a limited menu (fixed or dynamic).Diagnostic Yield (limited panel}# Runs with any detection(limited panel}# Runs

[0048] FIG. 8A illustrates diagnostic yield over a period of time for a respiratory panel.

[0049] FIG. 8B illustrates diagnostic yield over a period of time for a Gl panel.

[0050] A fixed diagnostic yield algorithm may identify the top “N” targets that maximize diagnostic yield over a large previous time period. For an N target menu in timespan S and set of targets T Menu(N, S, T} = argmaxT{ u=1means(Trate}}

[0051] S = 2016-2020 RP menu = {HRV / EV, RSV, FluA / B, PIV, Adenovirus}

[0052] 2016-2020 Gl Menu = {C. difficile, E.Coli, Norovirus, Campylobacter, Sapovirus}

[0053] A fixed medical relevance yield algorithm may identify the top “N” targets that maximize medical impact, as determined by medical experts.

[0054] Example RP menu = {RSV, FluA / B, PIV, Coronavirus}

[0055] A dynamic yield algorithm based on the previous week may identify the top “N” targets determined dynamically each week that maximize diagnostic yield by tailoring to both location and time. For an N target menu in week W selected from a set of targets T (like above):

[0056] Menu(N,W, T} = argmaxT{^l =1meanw-1(Trate)}

[0057] FIG. 9 illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for the entire USA. FIG. 10 illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for the entire USA. FIG. 11 A illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for a Midwestern USA region. FIG. 1 1 B illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for a Northeastern USA region. FIG. 1 1 C illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for aWestern USA region. FIG. 1 1 D illustrates the performances of a limited fixed and a limited dynamic menu as a percentage of a full panel (PPA) per week, for a Southern USA region.

[0058] FIG. 12A illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for a Midwestern USA region. FIG. 12B illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for a Northeastern USA region. FIG. 12C illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for a Western USA region. FIG. 12D illustrates diagnostic yield by menu, for a limited fixed menu, a limited dynamic menu, and a full menu, for a Southern USA region.

[0059] As discussed above, this diagnostic yield and PPA data provides an example how of dynamic menu can maximize detections, even while limiting extraneous test results. However, in some settings the goal may not be to maximize diagnostic yield but rather maximize medical relevance and treatment impact. That is, high prevalence does not necessarily indicate medical importance. Moreover, outbreaks and long-term events may raise the importance of some pathogen groups, thereby increasing their medical relevance. Also, the testing site type and site demographics can influence medical relevance as well. For instance, pediatric institutions may be interested in a specific set of results that are relevant to child patients, that may be different from the set of interest to the adult population, even in the same geographic area. Other factors may be considered as part of medical relevance, including vaccine availability, whether targeted therapeutics are available, whether there are affected vulnerable populations, and the availability of suitable quarantine protocols. All of these factors and others relating to medical relevance may inform a metric for menu selection.

[0060] For example, while HRV / EV are highly prevalent, their medical relevance is low. As another example, Bordetella pertussis is less prevalent but very medically important. Typically, a low prevalence pathogen such as Bordetella pertussis may have been excluded from a fixed limited panel. But a sharp increase in rate (e.g., as shown at FIG. 13), in addition to its medical relevance elevates its importance and warrants inclusion into the menu until rate returns to normal. That is, epidemiological events can trigger temporary changes in importance. As discussed above, these temporary changes can include, illustratively, temporal or geographic changes or demographic groups.

[0061] Additionally, in some cases, it is possible to estimate which pathogen groups will become relevant in future days or weeks using trend data, e.g., by using a previous week to inform the relevant pathogen groups for the current week, or based on environmentalsurveillance data / systems. Advanced prediction and forecasting may be utilized to provide an estimate of pathogen circulation as early as possible. For instance, probabilistic time series forecasting may provide better predictions as well as detect anomalous events. For instance, a recurrent neural networks (RNN) may be used to capture complicated patterns (both long term and short term). For instance, FIG. 14 illustrates a 36 week forecast for an Adenovirus pathogen.Example system

[0062] FIG. 15 is a block diagram of a system 100 for targeting the results provided by testing panels based on population data, in accordance with some examples provided herein. The high- level architecture illustrated in FIG. 15 may include both hardware and software applications, as well as various data communications channels for communicating data between the various hardware and software components, as is described below.

[0063] The system 100 may include a computing device 102, a pathogen testing device 104, and optionally one or more computing devices 108 (such as, e.g., smart phones, laptop computers, smart watches, tablets, etc.), and / or one or more printing devices 109, each of which may communicate with one another via a wired or wireless network 110, which may be, for instance, a public internet network, a private network between the devices, etc. In some examples, the computing device 102 may be part of (e.g., on-board) the pathogen testing device 104, while in other examples, the computing devices 102 may be separate from the pathogen testing device 104.

[0064] The pathogen testing device 104 may be configured to analyze samples associated with individuals in order to identify positive or negative results for a variety of different possible pathogen groups. In some examples, the pathogen testing device 104 may be configured to identify positive or negative results for a large number of different possible pathogen groups (e.g., 10 pathogen groups, 20 pathogen groups, 30 pathogen groups, etc.), and provide the positive or negative results to the computing device 102, e.g., via the network 1 10 in examples in which the computing device 102 is separate from the pathogen testing device 104.

[0065] The computing device 102 may include a user interface 112 configured to receive information from users and / or provide interactive displays to users, one or more processors 114 and a memory 116 (e.g., volatile memory, non-volatile memory). The memory 116 may be accessible by the one or more processors 114 (e.g., via a memory controller). The one or more processors 114 may interact with the memory 116 to obtain, for example, computer-readableinstructions stored in the memory 116. The computer-readable instructions stored in the memory 116 may cause the one or more processors 114 to execute one or more applications, including a pathogen testing analysis application 118.

[0066] Executing the pathogen testing analysis application 1 18 may include obtaining pathogen testing results for various populations of interest, and / or obtaining historical pathogen testing results for the pathogen testing device 104. For instance, the pathogen testing analysis application 118 may obtain pathogen testing results directly from the pathogen testing device 104 and / or other pathogen testing devices similar to the pathogen testing device 104, or from a database storing pathogen testing results for the various populations of interest, such as a population pathogen database 120 that may be communicatively connected to, or otherwise accessible by, the computing device 102. Optionally, pathogen database 120 may receive data from other sources associated with other pathogen testing devices and / or research institutions, such as the Centers for Disease Control (CDC) databases (e.g., from an external computing device 122). In some examples, the populations of interest may include, e.g., populations associated with particular geographical locations (e.g., s from particular countries, particular states, particular regions, particular counties, particular cities or towns, etc.). Additionally, in some examples, the populations of interest may include populations associated with particular age ranges or other demographics. Furthermore, in some examples, the populations of interest may include populations associated with pathogen testing during particular years, or particular months or seasons. The pathogen testing analysis application 1 18 may analyze the pathogen testing results for the populations of interest in order to identify a set of relevant pathogen groups for each population of interest. In some examples, the set of relevant pathogen groups may be a fixed-number set for each population of interest (e.g., 5 most relevant pathogen groups for each population).

[0067] Executing the pathogen testing analysis application 1 18 may further include receiving positive or negative results for various pathogen groups (e.g., 10 pathogen groups, 20 pathogen groups, 30 pathogen groups, etc.) for a particular individual from the pathogen testing device 104. The number of pathogen results received from the pathogen testing device 104 may be larger than the fixed number set of relevant pathogen groups for the various populations of interest.

[0068] Furthermore, executing the pathogen testing analysis application 118 may include identifying a population of interest to which the particular individual belongs. For instance, in some examples, the individual or a healthcare provider associated with the individual mayprovide geographic, demographic, age, or other data associated with the individual via the user interface 1 12. The pathogen testing analysis application 118 may identify the population of interest to which the particular individual belongs based on the data provided by the individual or healthcare provider via the user interface 1 12. Additionally, in some examples, the pathogen testing analysis application 1 18 may identify the population of interest to which the particular individual belongs based on the timing (e.g., year, month, season) of the individual’s pathogen tests.

[0069] Based on the identified population of interest to which the particular individual belongs, the pathogen testing analysis application 1 18 may identify pathogen testing results for the individual corresponding to the fixed-number set of relevant pathogen groups for the population to which the particular individual belongs, and provide those pathogen results via the user interface 112, send those pathogen results to one or more mobile computing devices 108 associated with the individual or with a healthcare provider of the individual, and / or print those pathogen results via one or more printing devices 109 associated with the individual or with a healthcare provider of the individual. In particular, the pathogen testing analysis 118 may refrain from sending pathogen testing results outside of the fixed-number set of relevant pathogen groups for the population to which the individual belongs to any of the mobile computing devices 108 associated with the individual or the healthcare provider of the individual.

[0070] Furthermore, in some examples, the computer-readable instructions stored on the memory 116 may include instructions for carrying out any of the steps of the methods 200 and 300, described in greater detail below with respect to FIGS. 16 and 17.Example method based on population data

[0071] FIG. 16 is a flow diagram of an example method 200 for targeting the results provided by testing panels based on population data, as may be implemented by the system 100 of FIG. 15, in accordance with some examples provided herein. One or more steps of the method 200 may be implemented as a set of instructions stored on a computer-readable memory (e.g., memory 116) and executable on one or more processors (e.g., processors 114).

[0072] In some examples, the method 200 may begin when pathogen testing results for one or more populations of interest are obtained (block 202). The pathogen testing results for the one or more populations of interest may be analyzed (block 204).

[0073] Based on analyzing the pathogen testing results for the one or more populations of interest, a set of relevant pathogen groups for each of the respective populations of interest may be identified (block 206). In some examples, the processor(s) 114 may perform the steps discussed with respect to blocks 202 and 204, and may identify the set of relevant pathogen groups for each of the populations of interest based on those steps. In other examples, for instance, another device (e.g., an external source computing device 122) may perform the steps discussed with respect to blocks 202 and 204 and may send an indication of the set of relevant pathogen groups for each of the populations of interest to the processor(s) 114 or to a database (e.g., database 120) accessible by the processor(s) 1 14.

[0074] In some examples, each set may include a predetermined number of pathogen groups (e.g., 5 pathogen groups). The set of relevant pathogen groups for one of the populations may be distinct from (i.e., may include at least one different pathogen or pathogen group) than the set of relevant pathogen groups for another population. For example, the populations of interest may each correspond, e.g., to a different geographic area, a different age range or other demographic group, a different time period or time of year, different travel history characteristics, different health / medical history characteristics, etc. For instance, the set of relevant pathogen groups for one geographic area may be distinct from the set of relevant pathogen groups for another geographic area. Similarly, the set of relevant pathogen groups for individuals within a first age range or other demographic group may be distinct from the set of relevant pathogen groups for individuals within a second age range or other demographic group. Additionally, the set of relevant pathogen groups for one time of year (e.g., a certain month or season) or time period may be distinct from the set of relevant pathogen groups for another time of year or time period. Furthermore, the set of relevant pathogen groups for one travel history characteristic (e.g., recently traveled to South America) may be different than the set of relevant pathogen groups for another travel history characteristic (e.g., recently traveled to Africa). Moreover, the set of relevant pathogen groups for individuals that have a particular health / medical history characteristic (e.g., individuals diagnosed with an autoimmune disease or individuals who have already tested negative for one or more pathogen groups and do not need to be retested for those pathogen groups) may be different than the set of relevant pathogen groups for individuals who do not have that medical / health history characteristic, or who otherwise have different medical / health history characteristics (e.g., individuals not diagnosed with an autoimmune disease or have not been already tested for one or more pathogen groups).

[0075] Moreover, in some examples, the set of relevant pathogen groups may be a set of most relevant pathogen groups for a given population. This may be based on, for instance, a medical relevance of each pathogen group for each population, a percentage of positive interpretations (PPA) that would be captured using a limited menu including each pathogen group for each population, epidemiological signals associated with each pathogen group for each population, etc. For instance, the set of relevant pathogen groups may be a set of pathogen groups that exceeds a threshold (e.g., a threshold medical relevance, a threshold PPA, etc.), or a set of pathogen groups that has experienced a significant relative change in medical relevance over a particular time frame.

[0076] In some situations, medical personnel may choose to select additional pathogen groups to the list of pathogen testing results. Illustratively, such a situation may occur when the patient is a member of more than one demographic group, wherein each of the demographic groups has a different list of pathogen testing results associated with that demographic group. Thus, in some situations, it may be desirable to identify the set of relevant pathogens to the medical personnel prior to moving to block 208, to permit the medical personnel to adjust the list of pathogen testing results.

[0077] Pathogen testing results for a particular individual (e.g., a patient) may be obtained (block 208) for each of a plurality of pathogen groups. The number of pathogen groups for which testing results are obtained may be greater than the (in some cases predetermined) number of relevant pathogen groups, and / or greater than the predetermined number of pathogen groups. For instance, as an example, testing results for 10 pathogen groups may be obtained, while the number of relevant pathogen groups may be 2, 3, 4, 5, 6, 7, 8 or more. An illustrative predetermined number of pathogen testing groups is 5. The testing results may then be reported back to block 202 to be used as testing results for future populations of interest.

[0078] The pathogen testing results for the particular individual that correspond to the set of relevant pathogen groups for a population with which the individual is associated may be reported (block 210) via a device (such as a computing device, a printer, etc.) associated with the particular individual, or associated with medical provider of the particular individual.Furthermore, the method 200 may include refraining to send the pathogen testing results for the particular individual that correspond to pathogen groups that are not within the set of relevant pathogen groups for the population with which the individual is associated.Example method based on data from testing device

[0079] FIG. 17 is a flow diagram of an example method 300 for targeting the results provided by testing panels based on data from a single pathogen testing device, as may be implemented by the system 100 of FIG. 15, in accordance with some examples provided herein. One or more steps of the method 300 may be implemented as a set of instructions stored on a computer- readable memory (e.g., memory 1 16) and executable on one or more processors (e.g., processors 114).

[0080] The method may begin when historical pathogen testing results from a pathogen testing device (e.g., device 104) are obtained (block 302). That is, all pathogen testing results may be obtained from a single pathogen testing device.

[0081] The historical pathogen testing results from the pathogen testing device may be analyzed (block 304) in order to identify (block 306) a set of relevant pathogen groups for the single pathogen testing device. In some examples, each set may include a predetermined number of pathogen groups (e.g., 5 pathogen groups). In some examples, the set of relevant pathogen groups may be a set of most relevant pathogen groups for the pathogen testing device. The set of most relevant pathogen groups for the pathogen testing device may be based at least partially on the most prevalent pathogen groups for the pathogen testing device. Moreover, the set of most relevant pathogen groups for the pathogen testing device may be based at least partially on, for instance, a medical relevance of each pathogen group for a population associated with the pathogen testing device (e.g., children may be the population associated with the pathogen testing device if it is located in a pediatric clinic, women may be the population associated with the pathogen testing device if it is located in a gynecological clinic, etc.), a set of pathogen groups that exceeds a threshold (e.g., a threshold medical relevance, a threshold PPA, etc.), or a set of pathogen groups that has experienced a significant relative change in medical relevance with respect to the particular pathogen testing device over a particular time frame.

[0082] Pathogen testing results for a particular individual may be obtained (block 308) from the pathogen testing device. The pathogen testing results may correspond to a plurality of pathogen groups. The number of pathogen groups for which testing results are obtained may be greater than the (in some cases predetermined) number of relevant pathogen groups, and / or greater than the predetermined number of pathogen groups. For instance, as an example, testing results for 10 pathogen groups may be obtained, while the number of relevant pathogen groups may be 2, 3, 4, 5, 6, 7, 8 or more. An illustrative predetermined number of pathogentesting groups is 5. The testing results may then be reported back to block 302 to be used as historical testing results for future individuals.The pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, may be reported (block 310) via a device (such as a computing device, a printer, etc.) associated with the particular individual, or associated with medical provider of the particular individual. Furthermore, the method 300 may include refraining to send the pathogen testing results for the particular individual that correspond to pathogen groups that are not within the set of relevant pathogen groups for the pathogen testing device.Additional considerations

[0083] The following additional considerations apply to the foregoing discussion. Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter of the present disclosure.

[0084] Additionally, certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code stored on a machine-readable medium) or hardware modules. A hardware module is tangible unit capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein.

[0085] A hardware module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC)) to perform certain operations. Ahardware module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware module in dedicated and permanently configured circuitry or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.

[0086] Accordingly, the term hardware should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where the hardware modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware modules at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.

[0087] Hardware and software modules can provide information to, and receive information from, other hardware and / or software modules. Accordingly, the described hardware modules may be regarded as being communicatively coupled. Where multiple of such hardware or software modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the hardware or software modules. In embodiments in which multiple hardware modules or software are configured or instantiated at different times, communications between such hardware or software modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware or software modules have access. For example, one hardware or software module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware or software module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware and software modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).

[0088] The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) orpermanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules.

[0089] Similarly, the methods or routines described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or processors or processor-implemented hardware modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations.

[0090] The one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as an SaaS. For example, as indicated above, at least some of the operations may be performed by a group of computers (as examples of machines including processors), these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., APIs).

[0091] The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the one or more processors or processor- implemented modules may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the one or more processors or processor-implemented modules may be distributed across a number of geographic locations.

[0092] Some portions of this specification are presented in terms of algorithms or symbolic representations of operations on data stored as bits or binary digital signals within a machine memory (e.g., a computer memory). These algorithms or symbolic representations are examples of techniques used by those of ordinary skill in the data processing arts to convey the substance of their work to others skilled in the art. As used herein, an “algorithm” or a “routine” is a self-consistent sequence of operations or similar processing leading to a desired result. In this context, algorithms, routines and operations involve physical manipulation of physical quantities. Typically, but not necessarily, such quantities may take the form of electrical, magnetic, or optical signals capable of being stored, accessed, transferred, combined,compared, or otherwise manipulated by a machine. It is convenient at times, principally for reasons of common usage, to refer to such signals using words such as “data,” “content,” “bits,” “values,” “elements,” “symbols,” “characters,” “terms,” “numbers,” “numerals,” or the like. These words, however, are merely convenient labels and are to be associated with appropriate physical quantities.

[0093] Unless specifically stated otherwise, discussions herein using words such as “processing,” “computing,” “calculating,” “determining,” “presenting,” “displaying,” or the like may refer to actions or processes of a machine (e.g., a computer) that manipulates or transforms data represented as physical (e.g., electronic, magnetic, or optical) quantities within one or more memories (e.g., volatile memory, non-volatile memory, or a combination thereof), registers, or other machine components that receive, store, transmit, or display information.

[0094] As used herein any reference to “one embodiment” or “an embodiment” means that a particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.

[0095] Some embodiments may be described using the expression “coupled” and “connected” along with their derivatives. For example, some embodiments may be described using the term “coupled” to indicate that two or more elements are in direct physical or electrical contact. The term “coupled,” however, may also mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other. The embodiments are not limited in this context.

[0096] As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Further, unless expressly stated to the contrary, “or” refers to an inclusive or and not to an exclusive or. For example, a condition A or B is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present).

[0097] In addition, use of the “a” or “an” are employed to describe elements and components of the embodiments herein. This is done merely for convenience and to give a general sense ofthe description. This description should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise.

[0098] Upon reading this disclosure, those of skill in the art will appreciate still additional alternative structural and functional designs through the disclosed principles herein. Thus, while particular embodiments and applications have been illustrated and described, it is to be understood that the disclosed embodiments are not limited to the precise construction and components disclosed herein. Various modifications, changes and variations, which will be apparent to those skilled in the art, may be made in the arrangement, operation and details of the method and apparatus disclosed herein without departing from the spirit and scope defined in the appended claims.Aspects

[0099] 1 . A computer-implemented method for targeting results provided by a testing panel based on population data, comprising: identifying, by one or more processors, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtaining, by the one or more processors, pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

[0100] 2. The method of aspect 1 , wherein the set of relevant pathogen groups for each of the respective one or more populations of interest is a set of most relevant pathogen groups for each of the respective one or more populations of interest.

[0101] The method of aspect 2, wherein the set of most relevant pathogen groups for each of the respective one or more populations of interest is selected at a particular point in time.

[0102] 4. The method of any of aspects 1 -3, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on one or more of: a medical relevance of each pathogen group for each of the respective one or more populations of interest, a percentage of positive interpretations (PPA) that would be captured using a limited menu including each pathogen group for each of the respective one or more populations of interest, or epidemiological signals associated with each pathogen group for each of the respective one or more populations of interest.

[0103] 5. The method of any of aspects 1 -4, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on analyzing pathogen testing results for the one or more populations of interest.

[0104] 6. The method of any of aspects 1 -5, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

[0105] 7. The method of aspect 6, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

[0106] 8. The method of any of aspects 1 -7, further comprising: refraining from reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

[0107] 9. The method of any of aspects 1 -8, wherein a set of relevant pathogen groups for a first population of interest, of the respective one or more populations of interest, includes one or more different pathogen groups than a set of relevant pathogen groups for a second population of interest, of the respective one or more populations of interest.

[0108] 10. The method of any of aspects 1 -9, wherein the one or more populations of interest each correspond to one or more of: geographic areas associated with each population of interest, demographic groups associated with each population of interest, time periods associated with each population of interest, recent travel history associated with each population of interest, health history associated with each population of interest, occupations of the population of interest, interactions of the population with other groups of people, or interactions of the population with certain animals.

[0109] 1 1. The method of any of aspects 1 -10, wherein the set of relevant pathogen groups is identified and outputted to medical personnel prior to the reporting step, and medical personnel may input to the one or more processors to add one or more additional pathogen groups the set of relevant pathogen groups.12. A system for targeting results provided by a testing panel based on population data, comprising: one or more processors, and a memory storing non-transitory, computer readable instructions that, when executed by the one or more processors, cause the one or more processors to: identify, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtain pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and report, to a device associated with an individual or amedical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

[0110] 13. The system of aspect 1 , wherein the set of relevant pathogen groups for each of the respective one or more populations of interest is a set of relevant pathogen groups for each of the respective one or more populations of interest.

[0111] 14. The system of aspect 13, wherein the set of most relevant pathogen groups for each of the respective one or more populations of interest is selected at a particular point in time.

[0100] 15. The system of any one of aspects 12-14, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on one or more of: a medical relevance of each pathogen group for each of the respective one or more populations of interest, a percentage of positive interpretations (PPA) that would be captured using a limited menu including each pathogen group for each of the respective one or more populations of interest, or epidemiological signals associated with each pathogen group for each of the respective one or more populations of interest.

[0101] 16. The system of any one of aspects 12-15, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on analyzing pathogen testing results for the one or more populations of interest.

[0102] 17. The system of any one of aspects 12-16, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

[0103] 18. The system of aspect 17, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

[0104] 19. The system of any one of aspects 12-18, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: refrain from reporting the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

[0105] 20. The system of any one of aspects 12-19, wherein a set of relevant pathogen groups for a first population of interest, of the respective one or more populations of interest,includes one or more different pathogen groups than a set of relevant pathogen groups for a second population of interest, of the respective one or more populations of interest.

[0106] 21 . The system of any one of aspects 12-20, wherein the one or more populations of interest each correspond to one or more of: geographic areas associated with each population of interest, demographic groups associated with each population of interest, time periods associated with each population of interest, recent travel history associated with each population of interest, health history associated with each population of interest, occupations of the population of interest, interactions of the population with other groups of people, or interactions of the population with certain animals.

[0107] 22. The system of any one of aspects 12-21 , wherein the set of relevant pathogen groups is identified and outputted to medical personnel prior to the reporting step, and medical personnel may input to the one or more processors to add one or more additional pathogen groups the set of relevant pathogen groups.

[0108] 23. A non-transitory computer-readable medium storing instructions for targeting results provided by a testing panel based on population data, wherein the instructions, when executed by one or more processors, cause the one or more processors to: identify, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtain pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and report, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

[0109] 24. The non-transitory computer-readable medium of aspect 23, wherein the set of relevant pathogen groups for each of the respective one or more populations of interest is a set of relevant pathogen groups for each of the respective one or more populations of interest.

[0110] 25. The non-transitory computer-readable medium of aspect 24, wherein the set of most relevant pathogen groups for each of the respective one or more populations of interest is selected at a particular point in time.

[0111] 26. The non-transitory computer-readable medium of any one of aspects 23-25, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on one or more of: a medical relevance of each pathogen group for each of the respective one or more populations of interest, a percentage of positiveinterpretations (PPA) that would be captured using a limited menu including each pathogen group for each of the respective one or more populations of interest, or epidemiological signals associated with each pathogen group for each of the respective one or more populations of interest.

[0112] 27. The non-transitory computer-readable medium of any one of aspects 23-26, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on analyzing pathogen testing results for the one or more populations of interest.

[0113] 28. The non-transitory computer-readable medium of any one of aspects 23-27, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

[0114] 29. The non-transitory computer-readable medium of aspect 28, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

[0115] 30. The non-transitory computer-readable medium of any one of aspects 23-29, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: refrain from reporting the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

[0116] 31 . The non-transitory computer-readable medium of any one of aspects 23-30, wherein a set of relevant pathogen groups for a first population of interest, of the respective one or more populations of interest, includes one or more different pathogen groups than a set of relevant pathogen groups for a second population of interest, of the respective one or more populations of interest.

[0117] 32. The non-transitory computer-readable medium of any one of aspects 23-31 , wherein the one or more populations of interest each correspond to one or more of: geographic areas associated with each population of interest, demographic groups associated with each population of interest, time periods associated with each population of interest, recent travel history associated with each population of interest, health history associated with each population of interest, occupations of the population of interest, interactions of the population with other groups of people, or interactions of the population with certain animals.

[0118] 33. The non-transitory computer-readable medium of any one of aspects 23-32, wherein the set of relevant pathogen groups is identified and outputted to medical personnel prior to the reporting step, and medical personnel may input to the one or more processors to add one or more additional pathogen groups the set of relevant pathogen groups.

[0119] 34. A computer-implemented method for targeting results provided by a testing panel based on population data, comprising: obtaining, by one or more processors, historical pathogen testing results from a pathogen testing device; analyzing, by the one or more processors, the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device; obtaining, by the one or more processors, pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the individual.

[0120] 35. The method of aspect 34, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

[0121] 36. The method of aspect 35, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

[0122] 37. The method of any one of aspects 34-36, further comprising: refraining from reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

[0123] 38. A system for targeting results provided by a testing panel, comprising: one or more processors, and a memory storing non-transitory, computer readable instructions that, when executed by the one or more processors, cause the one or more processors to: obtain historical pathogen testing results from a pathogen testing device; analyze the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device; obtain pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and report, the pathogen testing results for the particular individual,corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the individual.

[0124] 39. The system of aspect 38, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

[0125] 40. The system of aspect 39, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

[0126] 41 . The system of any one of aspects 38-40, further comprising: refraining from reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

[0127] 42. A non-transitory computer-readable medium storing instructions for targeting results provided by a testing panel, wherein the instructions, when executed by one or more processors, cause the one or more processors to: obtain historical pathogen testing results from a pathogen testing device; analyze the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device; obtain pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and report, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the individual.

[0128] 43. The non-transitory computer-readable medium of aspect 42, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

[0129] 44. The non-transitory computer-readable medium of aspect 43, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

[0130] 45. The non-transitory computer-readable medium of any one of aspects 42-44, further comprising: refraining from reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality ofpathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

Claims

What is Claimed is:1 . A computer-implemented method for targeting results provided by a testing panel based on population data, comprising: identifying, by one or more processors, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtaining, by the one or more processors, pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

2. The method of claim 1 , wherein the set of relevant pathogen groups for each of the respective one or more populations of interest is a set of most relevant pathogen groups for each of the respective one or more populations of interest.

3. The method of claim 2, wherein the set of most relevant pathogen groups for each of the respective one or more populations of interest is selected at a particular point in time.

4. The method of claim 1 , wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on one or more of: a medical relevance of each pathogen group for each of the respective one or more populations of interest, a percentage of positive interpretations (PPA) that would be captured using a limited menu including each pathogen group for each of the respective one or more populations of interest, or epidemiological signals associated with each pathogen group for each of the respective one or more populations of interest.

5. The method of claim 1 , wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on analyzing pathogen testing results for the one or more populations of interest.

6. The method of claim 1 , wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

7. The method of claim 6, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

8. The method of claim 1 , further comprising: refraining from reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

9. The method of claim 1 , wherein a set of relevant pathogen groups for a first population of interest, of the respective one or more populations of interest, includes one or more different pathogen groups than a set of relevant pathogen groups for a second population of interest, of the respective one or more populations of interest.

10. The method of claim 1 , wherein the one or more populations of interest each correspond to one or more of: geographic areas associated with each population of interest, demographic groups associated with each population of interest, time periods associated with each population of interest, recent travel history associated with each population of interest, health history associated with each population of interest, occupations of the population of interest, interactions of the population with other groups of people, or interactions of the population with certain animals.11 . The method of claim 1 , wherein the set of relevant pathogen groups is identified and outputted to medical personnel prior to the reporting step, and medical personnel may input to the one or more processors to add one or more additional pathogen groups the set of relevant pathogen groups.

12. A system for targeting results provided by a testing panel based on population data, comprising: one or more processors, and a memory storing non-transitory, computer readable instructions that, when executed by the one or more processors, cause the one or more processors to: identify, a set of relevant pathogen groups for each of a respective one or more populations of interest;obtain pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and report, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

13. The system of claim 12, wherein the set of relevant pathogen groups for each of the respective one or more populations of interest is a set of relevant pathogen groups for each of the respective one or more populations of interest.

14. The system of claim 13, wherein the set of most relevant pathogen groups for each of the respective one or more populations of interest is selected at a particular point in time.

15. The system of claim 12, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on one or more of: a medical relevance of each pathogen group for each of the respective one or more populations of interest, a percentage of positive interpretations (PPA) that would be captured using a limited menu including each pathogen group for each of the respective one or more populations of interest, or epidemiological signals associated with each pathogen group for each of the respective one or more populations of interest.

16. The system of claim 12, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on analyzing pathogen testing results for the one or more populations of interest.

17. The system of claim 12, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

18. The system of claim 17, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

19. The system of claim 12, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: refrain from reporting the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

20. The system of claim 12, wherein a set of relevant pathogen groups for a first population of interest, of the respective one or more populations of interest, includes one or more different pathogen groups than a set of relevant pathogen groups for a second population of interest, of the respective one or more populations of interest.21 . The system of claim 12, wherein the one or more populations of interest each correspond to one or more of: geographic areas associated with each population of interest, demographic groups associated with each population of interest, time periods associated with each population of interest, recent travel history associated with each population of interest, health history associated with each population of interest, occupations of the population of interest, interactions of the population with other groups of people, or interactions of the population with certain animals.

22. The system of claim 12, wherein the set of relevant pathogen groups is identified and outputted to medical personnel prior to the reporting step, and medical personnel may input to the one or more processors to add one or more additional pathogen groups the set of relevant pathogen groups.

23. A non-transitory computer-readable medium storing instructions for targeting results provided by a testing panel based on population data, wherein the instructions, when executed by one or more processors, cause the one or more processors to: identify, a set of relevant pathogen groups for each of a respective one or more populations of interest; obtain pathogen testing results for a particular individual, corresponding to a plurality of pathogen groups; and report, to a device associated with an individual or a medical provider of the individual, the pathogen testing results for the particular individual, corresponding to the set of relevantpathogen groups for a population, of the one or more populations of interest, with which the individual is associated.

24. The non-transitory computer-readable medium of claim 23, wherein the set of relevant pathogen groups for each of the respective one or more populations of interest is a set of relevant pathogen groups for each of the respective one or more populations of interest.

25. The non-transitory computer-readable medium of claim 24, wherein the set of most relevant pathogen groups for each of the respective one or more populations of interest is selected at a particular point in time.

26. The non-transitory computer-readable medium of claim 23, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on one or more of: a medical relevance of each pathogen group for each of the respective one or more populations of interest, a percentage of positive interpretations (PPA) that would be captured using a limited menu including each pathogen group for each of the respective one or more populations of interest, or epidemiological signals associated with each pathogen group for each of the respective one or more populations of interest.

27. The non-transitory computer-readable medium of claim 23, wherein identifying the set of relevant pathogen groups for each of the respective one or more populations of interest is based on analyzing pathogen testing results for the one or more populations of interest.

28. The non-transitory computer-readable medium of claim 23, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

29. The non-transitory computer-readable medium of claim 28, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

30. The non-transitory computer-readable medium of claim 23, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: refrain from reporting the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.31 . The non-transitory computer-readable medium of claim 23, wherein a set of relevant pathogen groups for a first population of interest, of the respective one or more populations of interest, includes one or more different pathogen groups than a set of relevant pathogen groups for a second population of interest, of the respective one or more populations of interest.

32. The non-transitory computer-readable medium of claim 23, wherein the one or more populations of interest each correspond to one or more of: geographic areas associated with each population of interest, demographic groups associated with each population of interest, time periods associated with each population of interest, recent travel history associated with each population of interest, health history associated with each population of interest, occupations of the population of interest, interactions of the population with other groups of people, or interactions of the population with certain animals.

33. The non-transitory computer-readable medium of claim 23, wherein the set of relevant pathogen groups is identified and outputted to medical personnel prior to the reporting step, and medical personnel may input to the one or more processors to add one or more additional pathogen groups the set of relevant pathogen groups.

34. A computer-implemented method for targeting results provided by a testing panel based on population data, comprising: obtaining, by one or more processors, historical pathogen testing results from a pathogen testing device; analyzing, by the one or more processors, the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device;obtaining, by the one or more processors, pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the particular individual.

35. The method of claim 34, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

36. The method of claim 35, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

37. The method of claim 34, further comprising: refraining from reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for a population with which the individual is associated.

38. A system for targeting results provided by a testing panel, comprising: one or more processors, and a memory storing non-transitory, computer readable instructions that, when executed by the one or more processors, cause the one or more processors to: obtain historical pathogen testing results from a pathogen testing device; analyze the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device; obtain pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and report, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the individual.

39. The system of claim 38, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

40. The system of claim 39, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.41 . The system of claim 38, further comprising: refraining from reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

42. A non-transitory computer-readable medium storing instructions for targeting results provided by a testing panel, wherein the instructions, when executed by one or more processors, cause the one or more processors to: obtain historical pathogen testing results from a pathogen testing device; analyze the historical pathogen testing results from the pathogen testing device in order to identify a set of relevant pathogen groups for the pathogen testing device; obtain pathogen testing results for a particular individual from the pathogen testing device, the pathogen testing results corresponding to a plurality of pathogen groups; and report, the pathogen testing results for the particular individual, corresponding to the set of relevant pathogen groups for the pathogen testing device, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with a medical provider of the individual.

43. The non-transitory computer-readable medium of claim 42, wherein the set of relevant pathogen groups includes a predetermined number of pathogen groups.

44. The non-transitory computer-readable medium of claim 43, wherein a total number of the plurality of pathogen groups in the testing panel is greater than the predetermined number of pathogen groups.

45. The non-transitory computer-readable medium of claim 42, further comprising:refraining from reporting, by the one or more processors, the pathogen testing results for the particular individual, corresponding to pathogen groups, of the plurality of pathogen groups, that are not within the set of relevant pathogen groups for the population with which the individual is associated.

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