Systems and methods for targeting test panels based on temporal, geographic, and demographic data

Abstract

A method is provided for targeting results provided by a test panel based on patient population data, comprising the steps of: identifying, by one or more processors, a set of relevant pathogen groups for each of one or more subject populations; obtaining, by the one or more processors, pathogen test results for the specific individual corresponding to the plurality of pathogen groups; and reporting, by the one or more processors to a device associated with the individual or the individual's healthcare provider, the pathogen test results for the specific individual corresponding to the set of relevant pathogen groups for the one or more subject populations with which the individual is associated.

Description

[Technical Field]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application claims priority to U.S. Provisional Application No. 63 / 446,766, filed February 17, 2023, entitled "System and Method for Targeting Test Panels Based on Temporal, Geographic, and Demographic Data," the entire disclosure of which is incorporated herein by reference.

[0002] [Field of the Invention] The present disclosure relates generally to panel technologies in which multiple tests (such as individual pathogen tests, a single output of a group of individual pathogen tests, antibiotic resistance gene tests, etc.) are performed on the same individual, and more specifically to targeting such panels based on patient population data. [Background technology]

[0003] The background description provided herein is for the purpose of outlining the context of the present disclosure. To the extent described in this Background section, the work of the named inventors, as well as aspects of the description that may not qualify as prior art at the time of filing, are not admitted, expressly or impliedly, as prior art to the present disclosure.

[0004] The availability of inexpensive reagents makes it possible to test a large number of pathogen targets on a single sample (e.g., using robotic pipetting systems, highly multiplexed syndromic panels, etc.), resulting in a large number of different pathogen test results for a given patient. While in some cases there is an advantage to obtaining a large number of different pathogen test results for a given patient, in other cases fewer, more focused pathogen test results are desired. Summary of the Invention

[0005] In one embodiment, a computer-implemented method for targeting results provided by a test panel based on population data is provided, comprising: identifying, by one or more processors, a set of associated pathogen groups for each of one or more subject populations; obtaining, by the one or more processors, pathogen test results for specific individuals corresponding to the plurality of pathogen groups; and reporting, by the one or more processors, to a device associated with the individual or the individual's healthcare provider, the pathogen test results for specific individuals in one or more subject populations with which the individual is associated, that correspond to the population's set of associated pathogen groups.

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

[0007] In yet another embodiment, a non-transitory computer-readable medium is provided that stores instructions for targeting results provided by a test panel based on population data, the instructions, when executed by one or more processors, causing the one or more processors to perform the steps of identifying, for each of one or more subject populations, a set of relevant pathogen groups; obtaining pathogen test results for a particular individual that correspond to the plurality of pathogen groups; and reporting to a device associated with the individual or the individual's healthcare provider, the pathogen test results for the particular individual that correspond to the set of relevant pathogen groups for a group of one or more subject populations with which the individual is associated.

[0008] In another embodiment, a computer-implemented method for targeting results provided by a test panel based on population data is provided, the computer-implemented method including the steps of: obtaining, by one or more processors, historical pathogen test results from a pathogen testing device; analyzing, by the one or more processors, the historical pathogen test results from the pathogen testing device to identify a set of related pathogen groups for the pathogen testing device; obtaining, by the one or more processors, pathogen test results for a particular individual from the pathogen testing device, the pathogen test results corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, the pathogen test results for the particular individual corresponding to the set of related 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 the individual's healthcare provider.

[0009] In yet another embodiment, a system for targeting results provided by a test panel based on population data is provided, comprising: one or more processors; and memory storing non-transitory computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of obtaining historical pathogen test results from a pathogen testing device; analyzing the historical pathogen test results from the pathogen testing device to identify a set of associated pathogen groups for the pathogen testing device; obtaining pathogen test results for a particular individual from the pathogen testing device, the pathogen test results corresponding to a plurality of pathogen groups; and reporting the pathogen test results for the particular individual that correspond to the set of associated 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 the individual's healthcare provider.

[0010] Additionally, in another embodiment, a non-transitory computer-readable medium is provided that stores instructions for targeting results provided by a test panel based on population data, the instructions, when executed by one or more processors, causing the one or more processors to perform the steps of obtaining historical pathogen test results from a pathogen testing device; analyzing the historical pathogen test results from the pathogen testing device to identify a set of related pathogen groups for the pathogen testing device; obtaining pathogen test results for a particular individual from the pathogen testing device, the pathogen test results corresponding to a plurality of pathogen groups; and reporting the pathogen test results for the particular individual that correspond to the set of related 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 the individual's healthcare provider. [Brief explanation of the drawings]

[0011] [Figure 1] Figure 1 shows the syndromic trend detection rates in the United States from 2017 to 2020.

[0012] [Figure 2] Figure 2 shows the top five most prevalent respiratory pathogen groups in the United States over several different time periods.

[0013] [Figure 3] Figure 3 shows the top five most prevalent respiratory pathogen groups in the United States over several different time periods.

[0014] [Figure 4] Figure 4 shows the prevalence of gastrointestinal (GI) pathogen groups across the United States from 2017 to 2020.

[0015] [Figure 5] Figures 5 and 6 show the top five most prevalent gastrointestinal pathogen groups in various regions of the United States from 2017 to 2022. [Figure 6] (the above)

[0016] [Figure 7] Figure 7 shows the top five most prevalent pathogen groups in the United States over various time periods.

[0017] [Figure 8A] Figure 8A shows the diagnostic yield over time for the respiratory panel.

[0018] [Figure 8B] Figure 8B shows the diagnostic yield of the GI panel over time.

[0019] [Figure 9] Figure 9 shows the performance of limited fixed menus and limited dynamic menus across the US as a percentage of the full panel (PPA) by week.

[0020] [Figure 10]Figure 10 shows the diagnostic yield by menu for limited fixed menu, limited dynamic menu, and full menu across the United States.

[0021] [Figure 11A] Figure 11A shows the performance of the limited fixed menu and limited dynamic menu as a percentage of the full panel (PPA) by week in the Midwest region of the United States.

[0022] [Figure 11B] Figure 11B shows the performance of the limited fixed menu and limited dynamic menu in the Northeast US region as a percentage of the full panel (PPA) by week.

[0023] [Figure 11C] Figure 11C shows the performance of the limited fixed menu and limited dynamic menu in the Western US region as a percentage of the full panel (PPA) by week.

[0024] [Figure 11D] Figure 11D shows the performance of the limited fixed menu and limited dynamic menu in the Southern region of the United States as a percentage of the full panel (PPA) by week.

[0025] [Figure 12A] Figure 12A shows the diagnostic yield by menu for limited fixed menu, limited dynamic menu, and full menu in the Midwest region of the United States.

[0026] [Figure 12B] Figure 12B shows the diagnostic yield by menu for the limited fixed menu, limited dynamic menu, and full menu in the Northeast region of the United States.

[0027] [Figure 12C] Figure 12C shows the diagnostic yield by menu for the limited fixed menu, limited dynamic menu, and full menu in the western United States region.

[0028] [Figure 12D] Figure 12D shows the diagnostic yield by menu for the limited fixed menu, limited dynamic menu, and full menu in the southern region of the United States.

[0029] [Figure 13] Figure 13 shows an example of a rapid increase in a pathogen of low prevalence but great medical importance (B. pertussis).

[0030] [Figure 14] Figure 14 shows the 36-week forecast for adenovirus pathogens.

[0031] [Figure 15] FIG. 15 illustrates an exemplary system for targeting results provided by a test panel based on patient population data, according to some examples provided herein.

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

[0033] [Figure 17] FIG. 17 is a flowchart of an exemplary method for targeting results provided by a test panel based on data from test devices, which may be implemented by the system 100 of FIG. 15, according to some examples provided herein. DETAILED DESCRIPTION OF THE INVENTION

[0034] [overview] As discussed above, the availability of inexpensive reagents has made it possible to test a large number of pathogen targets on a single sample (e.g., using robotic pipetting systems, highly multiplexed syndromic panels, etc.), resulting in a large number of different pathogen test results for a given patient. While obtaining a large number of different pathogen test results for a given patient can be beneficial in some cases, fewer, more focused pathogen test results may be more important to a patient population. For example, a positive test for a given rare pathogen group (e.g., Ebola, Middle East Respiratory Syndrome (MERS)) may result in reporting and quarantine requirements, as well as the need to use a biosafety level 3 (BSL-3) laboratory for a given specimen suspected to be positive for that pathogen group. Due to the rarity of these pathogen groups in some populations, the probability of a false positive may be higher than the probability of a true positive. Other consequences of false positives include the misprescription of medications with harmful side effects and the overprescription of antibiotics, which may promote antibiotic resistance. Therefore, in some cases, it may be preferable to obtain a patient's pathogen test results without including results for unlikely pathogen groups in order to avoid false positive results. This may be achieved by targeting the specific tests administered to the individual being tested, or by narrowing the targeting of the specific test results provided to the individual being tested, or a combination of both.

[0035] Furthermore, pathogen tests exempt under the Centers for Disease Control and Prevention (CDC) Clinical Laboratory Improvement Act (CLIA) may be performed by untrained or inadequately trained personnel, who may be overwhelmed by the large number of different pathogen test results. Furthermore, some insurance companies only provide reimbursement for a fixed number of pathogen test results (e.g., five or fewer). Some existing pathogen tests offer a limited menu of pathogen test results, which is typically created at the time of development and cannot be updated or changed thereafter. However, spatial and temporal factors may change the circulating pathogen population most relevant to a particular patient at a particular time. The testing environment and patient demographics may also change the pathogen population associated with a given patient.

[0036] It is understood that some pathogen diagnostics test for a single pathogen target, while others test for a group of related pathogens and provide a single result for the group. For example, human rhinoviruses and enteroviruses are often reported together in a single assay. As another example, various parainfluenza assays may report parainfluenza types 1 through 4 separately or provide a single report for parainfluenza in general. As yet another example, influenza A and influenza B may be reported together or separately, and influenza A may be reported as pan-influenza A or subtyped. Similarly, coronaviruses may be reported as individual coronaviruses or grouped together as a single group. As used herein, "group of pathogens" includes both individual pathogens reported individually and grouped pathogens reported together.

[0037] The technology includes providing a limited but dynamic menu of pathogen test results that are customized / modified based on 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 about the patient, and the timing of the pathogen testing. Surveillance pathogen test results for various target populations can be obtained and analyzed, and a set of relevant pathogen groups for each target population can be identified. When pathogen testing is performed on a new patient, the patient population to which the patient belongs can be identified, and pathogen test results for the set of relevant pathogen groups corresponding to the target population to which the patient belongs can be sent to the patient or the patient's healthcare provider. In this way, a limited number of pathogen test results can be provided to the patient without significantly sacrificing the relevant pathogen test results for each particular patient. While this disclosure refers to "patients," it should be understood that these technologies may be applied to any individual, including individuals who are not "patients," i.e., individuals not currently receiving treatment and / or individuals not known to have a disease or condition. For example, tests may be performed on samples that are not necessarily from a "patient," or may be performed on animal, environmental, or other samples that may or may not be related to a patient.

[0038] For example, Figure 1 shows the syndromic trend detection rates in the United States from 2017 to 2020. As shown in Figure 1, the top five most prevalent respiratory pathogen groups across the United States from 2017 to 2020 were human rhinovirus / enterovirus (HRV / EV), respiratory syncytial virus (RSV), parainfluenza virus (PIV), influenza A, and coronavirus.

[0039] However, changes in the prevalence of respiratory pathogen groups can occur not only seasonally but also annually. For example, as shown in Figure 2, the top five most prevalent respiratory pathogen groups from December 26, 2021, to January 8, 2022, were coronaviruses, HRV / EV, human metapneumovirus, influenza A, and respiratory syncytial virus; the top five most prevalent respiratory pathogen groups from May 29, 2022, to June 11, 2022, were HRV / EV, coronaviruses, parainfluenza, adenovirus, and respiratory syncytial virus; and the top five most prevalent respiratory pathogen groups from August 28, 2022, to September 10, 2022, were HRV / EV, coronaviruses, respiratory syncytial virus, adenovirus, and parainfluenza.

[0040] Furthermore, as shown in Figure 3, the top five most prevalent respiratory pathogens since March 2017 were HRV / EV, RSV, human metapneumovirus, influenza B, and coronavirus; the top five most prevalent respiratory pathogens since March 2018 were HRV / EV, RSV, human metapneumovirus, influenza B, and coronavirus; and the top five most prevalent respiratory pathogens since March 2019 were HRV / EV, influenza A, RSV, human metapneumovirus, and coronavirus.

[0041] Furthermore, as another example, variations in the prevalence of gastrointestinal (GI) pathogen groups may occur due to the geography and climate of different regions. Due to population density and mobility, these geospatial relationships may not be intuitive. Figure 4 shows the prevalence of GI pathogen groups across the United States from 2017 to 2020. As shown in Figure 4, the top five most prevalent GI pathogen groups across the United States from 2017 to 2020 were norovirus, group A rotavirus, Campylobacter, adenovirus F, and sapovirus. As shown in Figures 5 and 6, the top five most prevalent gastrointestinal pathogens in the Western United States from 2017 to 2020 were norovirus, group A rotavirus, Campylobacter, adenovirus F, and sapovirus. In the Midwest, the top five most prevalent gastrointestinal pathogens were norovirus, group A rotavirus, Campylobacter, sapovirus, and adenovirus E. In the Northeast, the top five most prevalent gastrointestinal pathogens were norovirus, Campylobacter, group A rotavirus, parasites, and adenovirus E. In the Southern United States from 2017 to 2020, the top five most prevalent gastrointestinal pathogens were norovirus, group A rotavirus, Salmonella, adenovirus F, and sapovirus.

[0042] In addition, epidemiological events, such as local outbreaks or pandemics, as well as environmental events, such as natural disasters and floods, can disrupt circulating pathogen populations and temporarily increase the importance of certain targets. That is, unexpected events can temporarily shift the pathogen landscape, and outbreaks may require rapid retargeting of testing capacity. For example, Figure 7 shows that from December 29, 2019, to February 1, 2020, the top five most prevalent pathogen groups in the United States were RSV, HRV / EV, coronaviruses, influenza A, and influenza B. However, from March 29, 2020, to April 30, 2022, the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, the virus that causes coronavirus disease 2019 or COVID-19) increased, and the top five most prevalent pathogen groups in the United States were HRV / EV, adenovirus, RSV, parainfluenza, and other coronaviruses. Flooding is another example of an epidemiological event. In floods, such as after major storms, wastewater surveillance can be used to monitor such events. Such epidemiological signals can help identify sets of relevant pathogens to test for.

[0043] Furthermore, medical importance is also a variable that can be used to identify sets of related pathogens: an outbreak of one pathogen may be of much greater medical importance than another, for example, due to its severity (e.g., Bordetella pertussis) or its transmissibility (e.g., SARS-CoV2).

[0044] Therefore, when provided by this technology, the menu needs to change dynamically to account for fluctuations in pathogen circulation. Many factors contribute to an "ideal" panel menu, as discussed above, including currently circulating pathogen groups, the medical significance of various pathogen groups, outbreaks, and unexpected events.

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

[0046] PPA yield is a measure of the proportion of positive tests captured using a limited menu (fixed or dynamic). TIFF2026506092000002.tif18170

[0047] Diagnostic yield is a measure of the number of tests that, with a limited menu (fixed or dynamic), will give at least one positive result over a period of time. TIFF2026506092000003.tif18170

[0048] Figure 8A shows the diagnostic yield over time for the respiratory panel.

[0049] Figure 8B shows the diagnostic yield of the GI panel over time.

[0050] A fixed diagnostic yield algorithm may identify the top "N" targets that maximize diagnostic yield over a large historical period. For a menu of N targets in S periods and T target sets, TIFF2026506092000004.tif12170

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

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

[0053] A fixed medical relevance yield algorithm may identify the top "N" targets that maximize medical benefit 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 a dynamically determined top "N" targets each week that maximize diagnostic yield by adjusting for both location and time. The menu of N targets for W weeks is selected from target set T (as above):

[0056] TIFF2026506092000005.tif12170

[0057] Figure 9 shows the performance of limited fixed menus and limited dynamic menus as a percentage of the weekly full panel (PPA) for the entire United States. Figure 10 shows the diagnostic yield per menu for limited fixed menus, limited dynamic menus, and full menus for the entire United States. Figure 11A shows the performance of limited fixed menus and limited dynamic menus as a percentage of the weekly full panel (PPA) for the Midwest region of the United States. Figure 11B shows the performance of limited fixed menus and limited dynamic menus as a percentage of the weekly full panel (PPA) for the Northeast region of the United States. Figure 11C shows the performance of limited fixed menus and limited dynamic menus as a percentage of the weekly full panel (PPA) for the Western region of the United States. Figure 11D shows the performance of limited fixed menus and limited dynamic menus as a percentage of the weekly full panel (PPA) for the Southern region of the United States.

[0058] Figure 12A shows the diagnostic yield by menu for limited fixed menus, limited dynamic menus, and full menus in the Midwest region of the United States. Figure 12B shows the diagnostic yield by menu for limited fixed menus, limited dynamic menus, and full menus in the Northeast region of the United States. Figure 12C shows the diagnostic yield by menu for limited fixed menus, limited dynamic menus, and full menus in the Western region of the United States. Figure 12D shows the diagnostic yield by menu for limited fixed menus, limited dynamic menus, and full menus in the Southern region of the United States.

[0059] As discussed above, this diagnostic yield and PPA data provide an example of how a dynamic menu can maximize detection while limiting irrelevant test results. However, in some situations, the goal may not be to maximize diagnostic yield, but rather to maximize medical relevance and treatment effectiveness. That is, high prevalence does not necessarily indicate medical importance. Furthermore, outbreaks and long-term events may increase the importance of some pathogen groups, thereby increasing their medical relevance. The type of testing site and the demographics of the site may also affect medical relevance. For example, a pediatric facility may be interested in a specific set of results relevant to pediatric patients, which may differ from the set of results relevant to the adult population, even within the same geographic region. Other factors may also be considered as part of medical relevance, including vaccine availability, availability of targeted therapeutics, presence of vulnerable populations affected, and availability of appropriate quarantine protocols. All of these factors, along with others related to medical relevance, may inform menu selection.

[0060] For example, HRV / EVs have a high prevalence but low medical relevance. Another example is Bordetella pertussis, which has a low prevalence but is highly medically important. Typically, low-prevalence pathogens, such as Bordetella pertussis, may be excluded from a fixed, limited panel. However, if prevalence suddenly increases (e.g., as shown in Figure 13), its importance, along with its medical relevance, increases, justifying its inclusion in the panel until prevalence returns to normal. That is, epidemiological events can cause temporary shifts in importance. As discussed above, these temporary shifts can illustratively include temporal or geographic shifts, or demographic groups.

[0061] Additionally, in some cases, trend data can be used to estimate which pathogen groups will be important in future days or weeks, for example, by using data from the previous week to inform relevant pathogen groups for the current week, or based on environmental surveillance data / systems. Advanced predictions and forecasts can be leveraged to estimate pathogen circulation as early as possible. For example, probabilistic time series forecasting can not only provide more accurate predictions but also help detect anomalous events. For example, recurrent neural networks (RNNs) can be used to capture complex patterns (long-term and short-term). For example, Figure 14 shows a 36-week forecast for adenovirus pathogens.

[0062] [System example] Figure 15 is a block diagram of a system 100 for targeting results provided by a test panel based on population data, according to some examples provided herein. The high-level architecture illustrated in Figure 15 can include both hardware and software applications, as well as various data communication channels for communicating data between the various hardware and software components, as described below.

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

[0064] The pathogen testing device 104 may be configured to analyze a sample associated with an individual to identify a positive or negative result for a variety of different possible pathogen groups. In some examples, the pathogen testing device 104 may be configured to identify a positive or negative result for a number of different possible pathogen groups (e.g., a group of 10 pathogens, a group of 20 pathogens, a group of 30 pathogens, etc.) and provide the positive or negative result to the computing device 102 over the network 110, for example, in an example where 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 a user and / or provide an interactive display to a user, one or more processors 114, and 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, for example, retrieve computer-readable instructions 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] Execution of the pathogen testing analysis application 118 may include obtaining pathogen test results for various target populations and / or obtaining pathogen test result history for the pathogen testing device 104. For example, the pathogen testing analysis application 118 may obtain the pathogen test results directly from the pathogen testing device 104 and / or other pathogen testing devices similar to the pathogen testing device 104, or may obtain the pathogen test results from a database that stores pathogen test results for various target populations, such as a population pathogen database 120 that may be communicatively coupled to or accessible by the computing device 102. Optionally, the pathogen database 120 may receive data from other sources associated with other pathogen testing devices and / or research institutions, such as a Centers for Disease Control and Prevention (CDC) database (e.g., external computing device 122). In some examples, the target population may include a population associated with a particular geographic location (e.g., a particular country, a particular state, a particular region, a particular county, a particular city, town, or village, etc.). Additionally, in some examples, the target population may include a population associated with a particular age group or other demographic. Further, in some examples, the target population may include a population associated with pathogen testing in a particular year, month, or season. The pathogen testing analysis application 118 may analyze the pathogen test results for the target populations to identify a set of pathogen groups associated with each target population. In some examples, the set of relevant pathogen groups may be a fixed number of sets for each target population (e.g., the five most relevant pathogen groups for each population).

[0067] Execution of the pathogen testing analysis application 118 may further include receiving positive or negative results for various pathogen groups (e.g., a group of 10 pathogens, a group of 20 pathogens, a group of 30 pathogens, 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 greater than a fixed set of relevant pathogen groups for various subject populations.

[0068] Further, execution of the pathogen testing analysis application 118 may include identifying a target population to which a particular individual belongs. For example, in some instances, the individual or a healthcare provider associated with the individual may provide geographic, demographic, age, or other data associated with the individual via the user interface 112. The pathogen testing analysis application 118 may identify a target population to which a particular individual belongs based on the data provided by the individual or healthcare provider via the user interface 112. Additionally, in some instances, the pathogen testing analysis application 118 may identify a target population to which a particular individual belongs based on the timing (e.g., year, month, season) of the individual's pathogen testing.

[0069] The pathogen test analysis application 118 may identify, based on the identified target population to which the particular individual belongs, pathogen test results for the individual that correspond to a fixed set of pathogen groups relevant to the population to which the particular individual belongs, provide those pathogen test results via the user interface 112, transmit those pathogen test results to one or more mobile computing devices 108 associated with the individual or the individual's healthcare provider, and / or print those pathogen test results via one or more printing devices 109 associated with the individual or the individual's healthcare provider. In particular, the pathogen test analysis 118 may avoid transmitting pathogen test results that fall outside the fixed set of pathogen groups relevant to the population to any of the individual or the individual's healthcare provider's mobile computing devices 108.

[0070] Additionally, in some examples, the computer-readable instructions stored in memory 116 may include instructions for performing any of the steps of methods 200 and 300, which are described in more detail below with respect to FIGS. 16 and 17.

[0071] [Example method based on population data] Figure 16 is a flowchart of an exemplary method 200 for targeting results provided by a test panel based on population data, which may be implemented by system 100 of Figure 15, according to some examples provided herein. One or more steps of method 200 may be implemented as a set of instructions stored in a computer-readable memory (e.g., memory 116) and executable on one or more processors (e.g., processor 114).

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

[0073] Based on the analysis of the pathogen test results for the one or more subject populations, a set of relevant pathogens may be identified for each of the subject populations (block 206). In some examples, processor 114 may perform the steps discussed with respect to blocks 202 and 204 and identify the set of relevant pathogens for each subject population based on those steps. In other examples, for example, another device (e.g., external source computing device 122) may perform the steps discussed with respect to blocks 202 and 204 and send an indication of the set of relevant pathogens for each subject population to processor 114 or a database accessible to processor 114 (e.g., database 120).

[0074] In some examples, each set may include a predetermined number of pathogen groups (e.g., five pathogen groups). The set of relevant pathogen groups for one population may be distinct (i.e., may include at least one different pathogen or pathogen group) from the set of relevant pathogen groups for another population. For example, each target population may correspond to, e.g., a different geographic region, a different age group or other demographic group, a different time period or time of year, different travel history characteristics, different health / medical history characteristics, etc. For example, the set of pathogen groups associated with one geographic region may be different from the set of pathogen groups associated with another geographic region. Similarly, the set of relevant pathogen groups for individuals belonging to a first age group or other demographic group may be different from the set of relevant pathogen groups for individuals belonging to a second age group or other demographic group. Additionally, the set of pathogen groups associated with a certain time of year (e.g., a given month or season) or time of year may be different from the set of pathogen groups associated with another time of year or time of year. Furthermore, the set of pathogen groups associated with one travel history characteristic (e.g., recent travel to South America) may differ from the set of pathogen groups associated with another travel history characteristic (e.g., recent travel to Africa). Furthermore, the set of pathogen groups associated with an individual with a particular health / health history characteristic (e.g., an individual diagnosed with an autoimmune disease or an individual who has already tested negative for one or more pathogen groups and does not need to be retested for those pathogen groups) may differ from the set of pathogen groups associated with an individual who does not have that disease / health history characteristic or who has an otherwise different disease / health history characteristic (e.g., an individual who has not been diagnosed with an autoimmune disease or an individual who has not yet been tested for one or more pathogen groups).

[0075] Further, in some examples, the set of relevant pathogen groups can be the set of pathogen groups that are most relevant to a given population. This can be based, for example, on the medical relevance of each pathogen group for each population, the positive interpretation rate (PPA) captured using a limited menu that includes each pathogen group for each population, the epidemiological signal associated with each pathogen group for each population, etc. For example, the set of relevant pathogen groups can be a set of pathogen groups that exceed a threshold (e.g., a medical relevance threshold, a PPA threshold, etc.) or a set of pathogen groups that have experienced a significant relative change in medical relevance over a particular period of time.

[0076] In some circumstances, the healthcare professional may choose to select additional pathogen groups for the list of pathogen test results. Illustratively, such a situation may occur when a patient is a member of more than one demographic group, and each demographic group has a different list of pathogen test results associated with that demographic group. Thus, in some circumstances, it may be desirable to have the healthcare professional identify a set of related pathogens so that the healthcare professional can tailor the list of pathogen test results before moving to block 208.

[0077] Pathogen test results for a particular individual (e.g., patient) may be obtained for each of a plurality of pathogen groups (block 208). The number of pathogen groups for which test results are obtained may be greater than the (possibly predetermined) number of relevant pathogen groups and / or may be greater than the predetermined number of pathogen groups. For example, in one example, test 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 exemplary predetermined number of pathogen test groups is 5. The test results may then be reported back to block 202 and used as test results for future target populations.

[0078] Pathogen test results for the particular individual that correspond to the set of relevant pathogen groups for the population to which the particular individual belongs may be reported via a device (e.g., a computing device, a printer) associated with the particular individual or associated with the particular individual's healthcare provider (block 210). Additionally, method 200 may include not transmitting pathogen test results for the particular individual that correspond to a pathogen group that is not included in the set of relevant pathogen groups for the population to which the individual is associated.

[0079] [Exemplary Method Based on Data from Inspection Equipment] Figure 17 is a flowchart of an exemplary method 300 for targeting results provided by a test panel based on data from a single pathogen testing device, which may be implemented by system 100 of Figure 15, according to some examples provided herein. One or more steps of method 300 may be implemented as a set of instructions stored in a computer-readable memory (e.g., memory 116) and executable on one or more processors (e.g., processor 114).

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

[0081] The pathogen test result history from the pathogen testing device may be analyzed (block 304) 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., five pathogen groups). In some examples, the set of relevant pathogen groups may be the set of pathogen groups most relevant to the pathogen testing device. The set of most relevant pathogen groups for the pathogen testing device may be based, at least in part, on the pathogen groups most prevalent to the pathogen testing device. Additionally, the set of pathogen groups that are most relevant to a pathogen testing device may be based, at least in part, on, for example, the medical relevance of each pathogen group to a population associated with the pathogen testing device (e.g., if the pathogen testing device is installed in a pediatric clinic, children may be the population associated with the pathogen testing device; if the pathogen testing device is installed in a gynecological clinic, women may be the population associated with the pathogen testing device, etc.), a set of pathogen groups that exceed a threshold (e.g., a medical relevance threshold, a PPA threshold, etc.), or a set of pathogen groups that have experienced a significant relative change in medical relevance for a particular pathogen testing device over a particular period of time.

[0082] Pathogen test results for a particular individual may be obtained from the pathogen testing device (block 308). The pathogen test results may correspond to multiple pathogen groups. The number of pathogen groups for which test results are obtained may be greater than the (possibly predetermined) number of relevant pathogen groups and / or may be greater than the predetermined number of pathogen groups. For example, in one example, test 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 exemplary predetermined number of pathogen test groups is 5. The test results may then be reported back to block 302 and used as the individual's future test result history. Pathogen test results for the particular individual that correspond to the set of associated pathogen groups for the pathogen testing device may be reported via a device (e.g., a computing device, a printer) associated with the particular individual or associated with the particular individual's healthcare provider (block 310). Additionally, method 300 may include not transmitting pathogen test results for the particular individual that correspond to pathogen groups not included in the set of associated pathogen groups for the pathogen testing device.

[0083] [Additional Considerations] The following additional considerations apply to the foregoing discussion: Throughout this specification, a component, operation, or structure described as a single instance may be implemented by multiple instances. 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 simultaneously, and there is no requirement that the operations be performed in the order illustrated. Structures and functions presented as separate components in exemplary configurations may be implemented as composite structures or components. Similarly, structures and functions presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements are within the scope of the subject matter of this disclosure.

[0084] Additionally, certain implementations are described herein as including logic or multiple components, modules, or mechanisms. A module may constitute either a software module (e.g., code stored on a machine-readable medium) or a hardware module. A hardware module is a tangible unit capable of performing certain operations, and may be configured or arranged in a certain manner. In exemplary implementations, one or more computer systems (e.g., standalone, client, or server computer systems) or one or more hardware modules (e.g., processor or processors) of a computer system 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 to perform certain operations (e.g., as a dedicated processor such as a field programmable gate array (FPGA) or application specific integrated circuit (ASIC)). A hardware module may also comprise programmable logic or circuitry that is temporarily configured by software to perform certain operations (e.g., as contained within a general-purpose processor or other programmable processor). It will be appreciated that the decision to implement a hardware module with dedicated, permanently configured circuitry or with temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.

[0086] Thus, the term hardware should be understood to encompass tangible entities that are physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a predetermined manner or to perform certain operations described herein. Given embodiments in which hardware modules are temporarily configured (e.g., programmed), each hardware module need not be configured or instantiated at one time. For example, if the hardware modules comprise a general-purpose processor that is configured using software, the general-purpose processor may be configured as different hardware modules at different times. Thus, the software may, for example, configure the processor to configure a particular hardware module at one time and a different hardware module at a different 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 can be considered communicatively coupled. When multiple such hardware or software modules are present simultaneously, communication can be achieved through signal transmission (e.g., via appropriate circuits and buses) connecting the hardware or software modules. In embodiments in which multiple hardware or software modules are configured or instantiated at different times, communication between such hardware or software modules can be achieved, for example, through the storage and retrieval of information in a memory structure accessible to the multiple hardware or software modules. For example, one hardware or software module can perform an operation and store the output of that operation in a communicatively coupled memory device. An additional hardware or software module can then access the memory device at a later time to retrieve and process the stored output. Hardware and software modules can also initiate communication with input or output devices and operate on resources (e.g., sets of information).

[0088] Various operations of the example methods described herein may be performed, at least in part, by one or more processors that are temporarily (e.g., by software) or permanently configured to perform the associated operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. Modules referred to herein may, in some example implementations, include processor-implemented modules.

[0089] Similarly, the methods or routines described herein may be implemented, at least in part, by a processor. For example, at least some operations of a method may be performed by one or more processors or hardware modules implemented by processors. Execution of certain operations may be distributed among one or more processors, and may reside within a single machine or may be spread across multiple machines. In some implementations, a processor or processors may be located in a single location (e.g., in a home environment, an office environment, or as a server farm), while in other implementations, processors may be distributed across multiple locations.

[0090] The one or more processors may also operate to support the execution of related operations as part of a "cloud computing" environment or SaaS. For example, as described above, at least some operations may be performed by a cluster of computers (as examples of machines that include processors), which are accessible via a network (e.g., the Internet) and one or more suitable interfaces (e.g., APIs).

[0091] Execution of a given operation may be distributed among one or more processors, and may reside within a single machine or may be spread across multiple machines. In some exemplary implementations, one or more processors or processor-implemented modules may be located in a single geographic location (e.g., in a home environment, an office environment, or a server farm). In other exemplary implementations, one or more processors or processor-implemented modules may be distributed across multiple geographic locations.

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

[0093] Unless otherwise indicated, discussions herein using words such as "processing," "computing," "calculating," "determining," "presenting," and "displaying" may refer to machine (e.g., computer) operations or processes that manipulate or transform 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, a reference to "one embodiment" or "an embodiment" means that a particular element, feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment. The appearances of the phrase "one embodiment" in various places in this specification are not necessarily all referring to the same embodiment.

[0095] Some embodiments may be described using the terms "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. However, the term "coupled" may also mean that two or more elements are not in direct contact with each other, but yet still cooperate or interact with each other. The embodiments are not limited in this context.

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

[0097] Additionally, the use of "a" or "an" is used to describe elements and components of embodiments herein. This is used only for convenience and to give a general sense of the description. This description should be read to include one or at least one, and the singular also includes the plural unless specifically intended otherwise.

[0098] Upon reading this disclosure, those skilled in the art will recognize still further alternative structural and functional designs through the principles disclosed herein. Thus, while specific embodiments and applications have been illustrated and described, it is to be understood that the disclosed embodiments are not limited to the precise structure 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 methods and apparatus disclosed herein without departing from the spirit and scope of the present invention as defined by the appended claims.

[0099] [Aspect] 1. A computer-implemented method for targeting results provided by a test panel based on population data, comprising the steps of: identifying, by one or more processors, a set of relevant pathogen groups for each of one or more subject populations; obtaining, by the one or more processors, pathogen test results for specific individuals corresponding to the plurality of pathogen groups; and reporting, by the one or more processors, to a device associated with the individual or the individual's healthcare provider, the pathogen test results for specific individuals in one or more subject populations with which the individual is associated that correspond to the population's set of relevant pathogen groups.

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

[0101] 3. The method of embodiment 2, wherein a set of most relevant pathogens for each of the one or more subject populations at a particular time point is selected.

[0102] 4. The method of any of aspects 1-3, wherein identifying the set of relevant pathogen groups for each of the one or more subject populations is based on one or more of the following: medical relevance of each pathogen group for each of the one or more subject populations; a positive interpretation rate (PPA) captured using a restricted menu including each pathogen group for each of the one or more subject populations; or an epidemiological signal associated with each pathogen group for each of the one or more subject populations.

[0103] 5. The method of any one of aspects 1 to 4, wherein the step of identifying a set of highly relevant pathogens for each of one or more subject populations is based on analyzing pathogen test results for the one or more subject populations.

[0104] 6. The method of any one of aspects 1 to 5, wherein the set of related pathogen groups comprises a predetermined number of pathogen groups.

[0105] 7. The method of embodiment 6, wherein the total number of the multiple pathogen groups in the test panel is greater than a predetermined number of pathogen groups.

[0106] 8. The method of any of aspects 1-7, further comprising the step of: not reporting, by the one or more processors, pathogen test results for the particular individual that correspond to a pathogen group among the plurality of pathogen groups that is not included in 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 the set of relevant pathogens for a first subject population, among each of the one or more subject populations, comprises one or more pathogens that are different from the set of relevant pathogens for a second subject population, among each of the one or more subject populations.

[0108] 10. The method of any of aspects 1-9, wherein the one or more subject populations each correspond to one or more of: a geographic area associated with each subject population; a demographic group associated with each subject population; a time period associated with each subject population; a recent travel history associated with each subject population; a health history associated with each subject population; an occupation of the subject population; an interaction of the subject population with other groups of people; or an interaction of the group with a predetermined animal.

[0109] 11. The method of any of aspects 1 to 10, wherein prior to the reporting step, a set of relevant pathogen groups is identified and output to a medical professional, who can input into one or more processors to add one or more additional pathogen groups to the set of relevant pathogen groups. 12. A system for targeting results provided by a test panel based on population data, comprising: one or more processors; and memory storing non-transitory computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of identifying, for each of one or more subject populations, a set of relevant pathogen groups; obtaining pathogen test results for specific individuals corresponding to the plurality of pathogen groups; and reporting to a device associated with the individual or the individual's healthcare provider, the pathogen test results for the specific individual corresponding to the set of relevant pathogen groups for a subset of the one or more subject populations with which the individual is associated.

[0110] 13. The system of aspect 12, wherein the set of relevant pathogens for each of the one or more subject populations is a set of relevant pathogens for each of the one or more subject populations.

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

[0112] 15. The system of any one of aspects 12-14, wherein the identification of the set of relevant pathogen groups for each of the one or more subject populations is based on one or more of the following: medical relevance of each pathogen group for each of the one or more subject populations; a positive interpretation rate (PPA) captured using a limited menu including each pathogen group for each of the one or more subject populations; or an epidemiological signal associated with each pathogen group for each of the one or more subject populations.

[0113] 16. The system of any one of aspects 12 to 15, wherein the identification of the set of relevant pathogens for each of the one or more subject populations is based on an analysis of pathogen test results for the one or more subject populations.

[0114] 17. The system of any one of aspects 12-16, wherein the set of related pathogen groups includes a predetermined number of pathogen groups.

[0115] 18. The system of aspect 17, wherein the total number of the multiple pathogen groups in the test panel is greater than a predetermined number of pathogen groups.

[0116] 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 pathogen test results for the particular individual that correspond to pathogen groups that are not included in the set of associated pathogen groups for a population with which the individual is associated, among the plurality of pathogen groups.

[0117] 20. The system of any one of aspects 12-19, wherein, for each of the one or more subject populations, the set of relevant pathogen groups for the first subject population includes one or more pathogen groups that are different from the set of relevant pathogen groups for the second subject population, respectively, for each of the one or more subject populations.

[0118] 21. The system of any one of aspects 12-20, wherein the one or more subject populations each correspond to one or more of: a geographic area associated with each subject population; a demographic group associated with each subject population; a time period associated with each subject population; a recent travel history associated with each subject population; a health history associated with each subject population; an occupation of the subject population; an interaction of the population with other groups of people; or an interaction of the population with a predetermined animal.

[0119] 22. The system of any one of aspects 12 to 21, wherein the set of related pathogen groups is identified and output to a medical professional prior to the reporting step, and the medical professional can add one or more additional pathogen groups to the set of related pathogen groups by inputting into one or more processors.

[0120] 23. A non-transitory computer-readable medium storing instructions for targeting results provided by a test panel based on population data, the instructions, when executed by one or more processors, causing the one or more processors to perform the steps of identifying, for each of one or more subject populations, a set of relevant pathogen groups; obtaining pathogen test results for a particular individual corresponding to the plurality of pathogen groups; and reporting to a device associated with the individual or the individual's healthcare provider, the pathogen test results for the particular individual corresponding to the set of relevant pathogen groups for a group of one or more subject populations with which the individual is associated.

[0121] 24. The non-transitory computer-readable medium of aspect 23, wherein the set of relevant pathogens for each of the one or more subject populations is a set of relevant pathogens for each of the one or more subject populations.

[0122] 25. The non-transitory computer-readable medium of embodiment 24, wherein the set of most relevant pathogens for each of the one or more subject populations at a particular time is selected.

[0123] 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 one or more subject populations is based on one or more of the following: medical relevance of each pathogen group for each of the one or more subject populations; a positive interpretation rate (PPA) captured using a limited menu including each pathogen group for each of the one or more subject populations; or an epidemiological signal associated with each pathogen group for each of the one or more subject populations.

[0124] 27. The non-transitory computer-readable medium of any one of aspects 23 to 26, wherein the step of identifying a set of relevant pathogens for each of the one or more subject populations is based on analyzing pathogen test results for the one or more subject populations.

[0125] 28. The non-transitory computer-readable medium of any one of aspects 23-25, wherein the set of related pathogen groups includes a predetermined number of pathogen groups.

[0126] 29. The non-transitory computer-readable medium of aspect 28, wherein the total number of the multiple pathogen groups in the test panel is greater than the predetermined number of pathogen groups.

[0127] 30. The non-transitory computer-readable medium of any one of aspects 23-29, wherein the instructions, when executed by one or more processors, further cause the one or more processors to refrain from reporting pathogen test results for the particular individual that correspond to pathogen groups, among the plurality of pathogen groups, that are not included within a set of relevant pathogen groups for a population with which the individual is associated.

[0128] 31. The non-transitory computer-readable medium of any one of aspects 23-30, wherein the set of relevant pathogen groups for a first subject population of each of the one or more subject populations comprises one or more pathogen groups that are different from the set of relevant pathogen groups for a second subject population of each of the one or more subject populations.

[0129] 32. The non-transitory computer-readable medium of any one of aspects 23-31, wherein the one or more subject populations each correspond to one or more of: a geographic area associated with each subject population; a demographic group associated with each subject population; a time period associated with each subject population; a recent travel history associated with each subject population; a health history associated with each subject population; an occupation of the subject population; an interaction of the subject population with other groups of people; or an interaction of the subject population with a predetermined animal.

[0130] 33. The non-transitory computer-readable medium of any one of aspects 23 to 32, wherein the set of relevant pathogen groups is identified and output to a medical professional prior to the reporting step, and the medical professional can add one or more additional pathogen groups to the set of relevant pathogen groups by inputting into one or more processors.

[0131] 34. A computer-implemented method for targeting results provided by a population data-based test panel, comprising the steps of: obtaining, by one or more processors, historical pathogen test results from a pathogen testing device; analyzing, by the one or more processors, the historical pathogen test results from the pathogen testing device and identifying a set of related pathogen groups for the pathogen testing device; obtaining, by the one or more processors, pathogen test results for a particular individual from the pathogen testing device, the pathogen test results corresponding to a plurality of pathogen groups; and reporting, by the one or more processors, the pathogen test results for the particular individual corresponding to the set of related pathogen groups for the pathogen testing device to one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with the individual's healthcare provider.

[0132] 35. The method of embodiment 34, wherein the set of related pathogen groups comprises a predetermined number of pathogen groups.

[0133] 36. The method of embodiment 35, wherein the total number of the multiple pathogen groups in the test panel is greater than the predetermined number of pathogen groups.

[0134] 37. The method of any one of aspects 34-36, further comprising the step of: not reporting, by one or more processors, pathogen test results for the particular individual that correspond to pathogen groups of the plurality of pathogen groups that are not included in the set of relevant pathogen groups for the population with which the individual is associated.

[0135] 38. A system for targeting results provided by a test panel, comprising: one or more processors; and memory storing non-transitory computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of obtaining historical pathogen test results from a pathogen testing device; analyzing the historical pathogen test results from the pathogen testing device to identify a set of associated pathogen groups for the pathogen testing device; obtaining pathogen test results for a particular individual from the pathogen testing device, the pathogen test results corresponding to a plurality of pathogen groups; and reporting the pathogen test results for the particular individual that correspond to the set of associated 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 the individual's healthcare provider.

[0136] 39. The system of embodiment 38, wherein the set of related pathogen groups includes a predetermined number of pathogen groups.

[0137] 40. The system of aspect 39, wherein the total number of the multiple pathogen groups in the test panel is greater than a predetermined number of pathogen groups.

[0138] 41. The system of any one of aspects 38-40, further comprising the step of: not reporting, by one or more processors, pathogen test results for the particular individual that correspond to a pathogen group among the plurality of pathogen groups that is not included in the set of relevant pathogen groups for the population with which the individual is associated.

[0139] 42. A non-transitory computer-readable medium storing instructions for targeting results provided by a test panel, the instructions, when executed by one or more processors, causing the one or more processors to perform the steps of obtaining historical pathogen test results from a pathogen testing device; analyzing the historical pathogen test results from the pathogen testing device to identify a set of associated pathogen groups for the pathogen testing device; obtaining pathogen test results for a particular individual from the pathogen testing device, the pathogen test results corresponding to a plurality of pathogen groups; and reporting the pathogen test results for the particular individual, which correspond to the set of associated 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 the individual's healthcare provider.

[0140] 43. The non-transitory computer-readable medium of embodiment 42, wherein the set of related pathogen groups comprises a predetermined number of pathogen groups.

[0141] 44. The non-transitory computer-readable medium of aspect 43, wherein the total number of the multiple pathogen groups in the test panel is greater than a predetermined number of pathogen groups.

[0142] 45. The non-transitory computer-readable medium of any one of aspects 42-44, further comprising: preventing, by one or more processors, reporting of a pathogen test result for a particular individual that corresponds to a pathogen group among the plurality of pathogen groups that is not included in the set of relevant pathogen groups for the population with which the individual is associated.

Claims

1. 1. A computer-implemented method for targeting results provided by a test panel based on population data, comprising: identifying, by one or more processors, a set of relevant pathogens for each of the one or more subject populations; obtaining, by one or more processors, pathogen test 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 the individual or the individual's healthcare provider, pathogen test results for the particular individual that correspond to a set of relevant pathogen groups for the one or more target populations with which the individual is associated. A method comprising:

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

3. 3. The method of claim 2, wherein the most relevant set of pathogens for each of the one or more subject populations at a particular time point is selected.

4. 2. The method of claim 1, wherein the identification of the set of relevant pathogen groups for each of the one or more subject populations is based on one or more of the following: a medical relevance of each pathogen group for each of the one or more subject populations; a positive interpretation rate (PPA) captured using a limited menu including each pathogen group for each of the one or more subject populations; or an epidemiological signal associated with each pathogen group for each of the one or more subject populations.

5. 10. The method of claim 1, wherein the identification of the set of relevant pathogens for each of the one or more subject populations is based on an analysis of pathogen test results for the one or more subject populations.

6. 10. The method of claim 1, wherein the set of related pathogen groups comprises a predetermined number of pathogen groups.

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

8. and not reporting, by the one or more processors, pathogen test results for the particular individual that correspond to a pathogen group among the plurality of pathogen groups that is not included in a set of relevant pathogen groups for the population with which the individual is associated. The method of claim 1 further comprising:

9. 2. The method of claim 1, wherein the set of relevant pathogen groups for a first subject population of each of the one or more subject populations comprises one or more pathogen groups that are different from the set of relevant pathogen groups for a second subject population of each of the one or more subject populations.

10. 10. The method of claim 1, wherein the one or more subject populations each correspond to one or more of a geographic area associated with each subject population, a demographic group associated with each subject population, a time period associated with each subject population, a recent travel history associated with each subject population, a health history associated with each subject population, an occupation of the subject population, an interaction of the population with other groups of people, or an interaction of the population with a predetermined animal.

11. 10. The method of claim 1, wherein the set of related pathogen groups is identified and output to a medical professional prior to the reporting step, and the medical professional can input into one or more processors to add one or more additional pathogen groups to the set of related pathogen groups.

12. 1. A system for targeting results provided by a test panel based on population data, comprising: one or more processors; and when executed by the one or more processors, causing the one or more processors to: identifying a set of relevant pathogens for each of the one or more subject populations; obtaining pathogen test results for a particular individual corresponding to a plurality of pathogen groups; and reporting, to a device associated with the individual or the individual's healthcare provider, pathogen test results for the particular individual that correspond to a set of relevant pathogen groups for a population of one or more subject populations with which the individual is associated. and a memory storing non-transitory computer-readable instructions for executing the above.

13. 13. The system of claim 12, wherein the set of relevant pathogens for each of the one or more subject populations is a set of relevant pathogens for each of the one or more subject populations.

14. 14. The system of claim 13, wherein the most relevant set of pathogens for each of the one or more subject populations at a particular time point is selected.

15. 13. The system of claim 12, wherein the identification of the set of relevant pathogen groups for each of the one or more subject populations is based on one or more of the following: a medical relevance of each pathogen group for each of the one or more subject populations; a positive interpretation rate (PPA) captured using a limited menu including each pathogen group for each of the one or more subject populations; or an epidemiological signal associated with each pathogen group for each of the one or more subject populations.

16. 13. The system of claim 12, wherein the identification of the set of relevant pathogens for each of the one or more subject populations is based on an analysis of pathogen test results for the one or more subject populations.

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

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

19. The instructions, when executed by one or more processors, further cause the one or more processors to:

13. The system of claim 12, wherein the system prevents reporting of pathogen test results for a particular individual that correspond to a pathogen group among the plurality of pathogen groups that is not included within a set of relevant pathogen groups for a population with which the individual is associated.

20. 13. The system of claim 12, wherein the set of relevant pathogen groups for a first subject population of each of the one or more subject populations comprises one or more pathogen groups that are different from the set of relevant pathogen groups for a second subject population of each of the one or more subject populations.

21. 13. The system of claim 12, wherein each of the one or more subject populations corresponds to one or more of a geographic area associated with each subject population, a demographic group associated with each subject population, a time period associated with each subject population, a recent travel history associated with each subject population, a health history associated with each subject population, an occupation of the subject population, an interaction of the population with other groups of people, or an interaction of the population with a predetermined animal.

22. 13. The system of claim 12, wherein the set of related pathogen groups is identified and output to a medical professional prior to the reporting step, and the medical professional can add one or more additional pathogen groups to the set of related pathogen groups by inputting into the one or more processors.

23. 1. A non-transitory computer-readable medium storing instructions for targeting results provided by a test panel based on population data, the instructions, when executed by one or more processors, causing the one or more processors to: identifying a set of relevant pathogens for each of the one or more subject populations; obtaining pathogen test results for a particular individual corresponding to a plurality of pathogen groups; reporting, to a device associated with the individual or the individual's healthcare provider, pathogen test results for the particular individual that correspond to a set of relevant pathogen groups for the individual's associated population of one or more target populations. A non-transitory computer-readable medium for causing the

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

25. 25. The non-transitory computer-readable medium of claim 24, wherein the set of most relevant pathogens for each of the one or more subject populations at a particular time is selected.

26. 24. The non-transitory computer-readable medium of claim 23, wherein the identification of the set of relevant pathogen groups for each of the one or more subject populations is based on one or more of the following: a medical relevance of each pathogen group for each of the one or more subject populations; a positive interpretation rate (PPA) captured using a limited menu including each pathogen group for each of the one or more subject populations; or an epidemiological signal associated with each pathogen group for each of the one or more subject populations.

27. 24. The non-transitory computer-readable medium of claim 23, wherein the identification of the set of relevant pathogens for each of the one or more subject populations is based on an analysis of pathogen test results for the one or more subject populations.

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

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

30. The instructions, when executed by one or more processors, further cause the one or more processors to:

24. The non-transitory computer-readable medium of claim 23, which prevents reporting of pathogen test results for a particular individual that correspond to a pathogen group among a plurality of pathogen groups that is not included within a set of relevant pathogen groups for a population with which the individual is associated.

31. 24. The non-transitory computer-readable medium of claim 23, wherein the set of relevant pathogen groups for a first subject population of each of the one or more subject populations comprises one or more pathogen groups that are different from the set of relevant pathogen groups for a second subject population of each of the one or more subject populations.

32. 24. The non-transitory computer-readable medium of claim 23, wherein the one or more subject populations each correspond to one or more of a geographic area associated with each subject population, a demographic group associated with each subject population, a time period associated with each subject population, a recent travel history associated with each subject population, a health history associated with each subject population, an occupation of the subject population, an interaction of the population with other groups of people, or an interaction of the population with a predetermined animal.

33. 24. The non-transitory computer-readable medium of claim 23, wherein the set of related pathogen groups is identified and output to a medical professional prior to the reporting step, and the medical professional can add one or more additional pathogen groups to the set of related pathogen groups by inputting into the one or more processors.

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

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

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

37. and not reporting, by the one or more processors, pathogen test results for the particular individual that correspond to a pathogen group among the plurality of pathogen groups that is not included in a set of relevant pathogen groups for the population with which the individual is associated.

35. The method of claim 34, further comprising:

38. 1. A system for targeting results provided by a test panel, comprising: one or more processors; and when executed by the one or more processors, causing the one or more processors to: obtaining a pathogen test result history from the pathogen testing device; analyzing historical pathogen test results from the pathogen testing device to identify a set of relevant pathogen groups for the pathogen testing device; obtaining, from the pathogen testing device, pathogen test results for a particular individual, the pathogen test results corresponding to a plurality of pathogen groups; and reporting pathogen test 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 the individual's healthcare provider. and a memory storing non-transitory computer-readable instructions that cause the system to execute the above.

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

40. 40. The system of claim 39, wherein the total number of pathogen groups in the test panel is greater than a predetermined number of pathogen groups.

41. and not reporting, by the one or more processors, pathogen test results for the particular individual that correspond to a pathogen group among the plurality of pathogen groups that is not included within a set of relevant pathogen groups for the population with which the individual is associated.

39. The system of claim 38, further comprising:

42. 1. A non-transitory computer-readable medium storing instructions for targeting results provided by a test panel, the instructions, when executed by one or more processors, causing the one or more processors to: obtaining a pathogen test result history from the pathogen testing device; analyzing historical pathogen test results from the pathogen testing device to identify a set of relevant pathogen groups for the pathogen testing device; obtaining, from the pathogen testing device, pathogen test results for a particular individual, the pathogen test results corresponding to a plurality of pathogen groups; and reporting, via one or more of the pathogen testing device, a device associated with the particular individual, or a device associated with the individual's healthcare provider, pathogen testing results for the particular individual corresponding to the set of relevant pathogen groups for the pathogen testing device. A non-transitory computer-readable medium for causing the

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

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

45. and not reporting, by the one or more processors, pathogen test results for the particular individual that correspond to a pathogen group among the plurality of pathogen groups that is not included in the set of relevant pathogen groups for the population with which the individual is associated.

43. The non-transitory computer-readable medium of claim 42, further comprising:

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