SYSTEM AND METHOD FOR MONITORING AND ANAYLZING ANIMAL RELATED DATA

A system and computerized method for monitoring and analyzing animal related data. In one embodiment, the system includes a processor and memory operable to identify a parameter related to animal management for species in a biological environment, aggregate animal related data from different sources about the parameter of the species, identify a baseline for the parameter, correlate the animal related data against the baseline to obtain correlated data, and analyze said correlated data to assess said animal management.

TECHNICAL FIELD OF THE INVENTION

The present invention relates in general to the field of data collection and processing, and more specifically to a system and method for monitoring and analyzing animal related data.

BACKGROUND OF THE INVENTION

Outbreaks of infectious animal diseases can easily overwhelm decision-makers with raw information, forcing them to cope with a torrent of news reports, official updates, spreadsheets, maps, photos and documents. The chaos can render a response both inefficient and ineffective. Coordinating the decision-making process would be advantageous for successful outbreak management and animal-related health monitoring in general.

SUMMARY OF THE INVENTION

These and other problems are generally solved or circumvented, and technical advantages are generally achieved, by advantageous embodiments of the present invention, including a system and computerized method for monitoring and analyzing animal related data. In one embodiment, the system includes a processor and memory operable to identify a parameter related to animal management for species in a biological environment, aggregate animal related data from different sources about the parameter of the species, identify a baseline for the parameter, correlate the animal related data against the baseline to obtain correlated data, and analyze said correlated data to assess said animal management.

DETAILED DESCRIPTION OF THE INVENTION

While the making and using of various embodiments of the present invention are discussed in detail below, it should be appreciated that the present invention provides many applicable inventive concepts that can be embodied in a wide variety of specific contexts. The specific embodiments discussed herein are merely illustrative of specific ways to make and use the invention and do not delimit the scope of the invention. Although the description of the invention and various embodiments relate to animal health data collection and assessment, the invention is may be applicable to the collection and assessment of non-animal health data. As a result, the present invention is not limited to animal health data or the examples described herein.

Various embodiments of the present invention provide a system and computerized methods that allow a diverse set of disparate data to be automatically collected and accessed in near real-time or real-time, brokered based on defined data sharing agreements, transformed (e.g., processed, aggregated, synthesized, integrated, fused, etc.) as needed, and presented to end-users in a customizable and interactive fashion. The system provides an extensible and modular framework that allows a variety of data and tools, and various underlying technologies to be integrated in a distributed yet seamless fashion. The system can be fully distributed integrating both fixed and mobile elements. The system allows producers, state animal health officials (“SAHOs”), federal regulatory agencies and others to better understand a situation (shared situational awareness) and to more effectively collaborate, coordinate, communicate and make decisions. The system supports both routine production scenarios and the full emergency cycle (i.e., planning, preparation, early detection, mitigation, response, management and recovery) for emerging disease indications and/or outbreak events.

Referring initially toFIG. 1, illustrated is a block diagram of an embodiment of a system100. The system100includes one or more computing devices102(e.g., a computer) communicably coupled directly or indirectly to one or more data sources104. The system100is communicably coupled to a network106that facilitates coupling the computing device(s)102to client device(s)108and third-party data source(s) and service(s)110. The network106can be the Internet, a wireless network, a public or private wide area or local area network, a cellular network, an optical network, a satellite network, a hardline connection, a wireless connection, a point-to-point connection, any other means of transmitting data, or any combination thereof. Note that the computing device(s)102can be a single computing device or a distributed network of locally or remotely located computing devices communicably coupled to one another. The data source(s)104can be any type of data storage or delivery medium (including memory) that allows data to be written, stored or retrieved by a computing device. Note that the data source(s)104can be a single storage device or a distributed network of locally or remotely located data storage devices communicably coupled to the computing device(s)102. The data source(s)104can be integrated into the computing device(s)102, or separate devices locally or remotely located with respect to the computing device(s)102, or a combination thereof. Moreover, the computing device(s)102and data source(s)104may include redundant devices or devices operating in parallel. Note that the client device(s)108can be a workstation, a client computer, a laptop, a handheld computer, a mobile computing tablet, a mobile phone, an input and/or output device, a user interface on equipment, a sensor, a client data source or any other desirable device. In addition, the data source(s)104and third-party data source(s) and service(s)110can be databases, data feeds, sensors, storage devices, other computers, other client devices, etc.

Some features and benefits of various embodiments of the system100will now be described. The system100allows secure and robust access to diverse sets of data, and enables dynamically brokered, controlled or compartmentalized sharing of data to end-users (i.e., based upon established data sharing/protection agreements) at varying levels of resolution/detail that can be dynamically adjusted based on changing needs and circumstances. In addition, the system100provides timely and usable information to a decision maker in a customizable form factor that: (a) integrates or fuses data together (e.g., service-oriented architecture, relational and not only Structured Query Language (NoSQL) databases), and allows for processing, transformation, synthesis, aggregation, filtering, or sorting to support better awareness and decision-making across different agriculture arenas, (b) transforms raw data into more actionable information through the use of interactive visualization and analytical tools, and (c) supports analysis across multiple dimensions including time, space, animal populations, and genetics. Moreover, the system100incorporates both interactive and automated tools for more effective data analysis. The system100supports the full spectrum of activities (from day-to-day monitoring to managing animal health events) and can rapidly adjust to support changing needs and circumstances. The system100also provides a portable and reconfigurable platform to support multiple usage contexts including real-world operations, training and preparedness, and planning and analysis. As a result, the system100improves collaboration, coordination, and communication between different users, groups, and organizations, and provides an extensible architecture that can be grown and adjusted as end-user needs/requirements change.

Various embodiments of the present invention integrate authoritative information into a single, easy-to-use format that empowers real-time collection, distribution, and analysis of biosurveillance, veterinary diagnostic, and animal movement data. These embodiments are capable of integrating data from multiple sources, such as clinical observations, laboratory diagnostic test results, animal production information (e.g., weight gain, feed intake, etc.), wildlife, geographical, and environmental/climate data. As a result, the system100can serve as a central point for multiple groups to collaborate and leverage their collective resources to monitor disease events and treatment efficacies, thus enabling efficient risk analysis and effective program design for disease intervention.

In summary, various embodiments of the system100can provide one or more of the following benefits: (a) enhance animal health management for producers, SAHOs, and federal regulatory agencies; (b) improve collaboration, coordination, and communication between these different end-users and groups thereby allowing them to leverage their collective resources to more effectively monitor and manage animal health, and assess different treatment efficacies; (c) eliminate latency of decisions by automatically providing access to current data (i.e., a decision maker no longer has to manually collect, process, integrate, and develop a presentation from the raw data); (d) provide a unified approach where data can be collected and accessed, processed, aggregated, transformed, synthesized, integrated, fused, and then presented in a meaningful way; (e) take existing parallel workflows/processes (i.e., production management, disease surveillance, disease response) and allows them to converge and interoperate, and allows automated integration of data in near real-time to support these activities; (f) allow interoperability between different systems and data that (to date) are not typically integrated in any automated way; (g) provide an infrastructure where data can be made available (i.e., based upon data sharing agreements in an actual, anonymized, or obfuscated fashion) to support modeling of disease spread, risk analysis and assessment, and determination of baselines/trends and anomalies for detecting new and/or emerging events; (h) support an array of decisions and allows decisions to be more aligned with current processes (i.e., as data is immediately available when needed); (i) support pre-event and post-event usage; and/or (j) help with day-to-day production animal health decisions and early detection, response, management, and recovery from disease events that occur.

Turning now toFIG. 2, illustrated is a block diagram of an embodiment of the computing device(s)102ofFIG. 1. The computing device(s)102includes a communications interface112, a memory114(capable of storing computer program code, which includes, without limitation, interpreted code, binaries, libraries, and/or executables), a display116and one or more processor(s)118. The processor(s)118are communicably coupled to the communications interface112, memory114and display116. Alternatively, the display116can be communicably coupled to the processor(s)118via the communications interface112. The communications interface112can be multiple interfaces and provides the appropriate connections and communication protocols to connect the processor(s)118to other devices, components and the network106. The computing device(s)102have a computer program embodied on a non-transitory computer readable medium that when executed causes the computing device(s)102to perform various computerized methods in accordance with the present invention, non-limiting examples of which will be described in more detail below.

The computing device(s)102is configured to monitor and analyze animal related data in a biological environment. In one embodiment, the processor(s)118and memory114(cooperating to execute computer program code) are configured to cause the computing device(s)102to identify a parameter related to animal management (e.g., a syndrome, animal health, animal production) for species (e.g., disparate species) in the biological environment. The parameter may include, without limitation, an animal diagnostic laboratory throughput parameter (e.g., a veterinary diagnostic laboratory throughput parameter), an animal resource allocation parameter (e.g., a veterinary diagnostic laboratory resource allocation parameter), an animal production parameter, an animal health monitoring parameter, an animal tracking parameter, an animal disease identification parameter, a phylogenetic analysis parameter, and an animal related emergency response parameter/dynamically changing situation.

The processor(s)118and memory114(executing computer program code) are configured to receive and encode animal related data from different sources into a common format. The animal related data may include, without limitation, animal health data, movement data, key location data, surveillance data, diagnostic testing data, geographic information system layer data, personnel data, resource data, phylogenetic data and laboratory data, and may be directed at the individual or group level. The conversion or translation associated with encoding the animal related data may be from a proprietary format to a common format. In a related embodiment, the common format allows the data to be employable across various types of software and/or devices. A unique identifier can also be assigned to the animal related data to associate the data to other data such as a species type. The unique identifier may also be relationally associated with an identifier assigned to the animal related data by the corresponding data source (e.g. producer, veterinarian or health authority). The animal related data may also be anonymized to sanitize sensitive information, but sufficient to enable some type of analysis thereof.

The processor(s)118and memory114(executing computer program code) are also configured to filter the animal related data from the different sources based on the parameter. The filtering of the animal related data from the different sources may be based on time, space and context associated with the parameter, and/or based on a guard band or pre-determined baseline associated with the parameter. Thus, certain animal related data may be flagged as anomalous and/or discarded if it falls outside of a particular expectation. Conversely, the animal related data that is filtered out may be retained within the memory114for other purposes. The processor(s)118and memory114(executing computer program code) are also configured to aggregate the animal related data from the different sources about the parameter of the species.

The processor(s)118and memory114(executing computer program code) are also configured to identify a baseline for the parameter. It should be noted that the baseline may be a time series model calculated over time and may fluctuate based on the animal related data. Thus, the baseline can then be tested to determine the validity thereof by, for instance, identifying patterns in the animal related data. If the baseline is invalid or should be updated, the processor(s)118and memory114(executing computer program code) are configured to modify the baseline. Once the baseline is set, the processor(s)118and memory114(executing computer program code) are configured to correlate the animal related data against the baseline to obtain correlated data and then analyze the correlated data to assess the animal management. The computing device(s)102may assess the animal management by predicting future outcomes associated with the animal management, by identifying a trend associated with the animal management, and/or by identifying an anomaly or confirming a normalcy associated with the animal management. The assessment may be performed in real-time, or delayed to account for incubation time.

The processor(s)118and memory114(executing computer program code) are also configured to present the animal related data in a first frame of the display116and present the correlated data in a second frame of the display116. The animal related data and correlated data may be presented as a geographical map, a graphical representation, a chart or a list, and dynamically formatted for presentation on the display116. The processor(s)118and memory114(executing computer program code) are also configured to track a movement of the species associated with the animal related data. As an example, the animals may be tagged with a sensor (such as a radio frequency identification tag) that communicates with a reader and server to provide location information to the computing device(s)102. Of course, the computing device(s)102may not only track, but in addition to or in lieu of incorporate data about the movement of the species. The processor(s)118and memory114(executing computer program code) are also configured to assign permissions (e.g., credential based on predefined rules) to the animal related data based on the source and restrict access to at least portions of the animal related data based on the permissions (e.g., county (or coarser)-level permissions), which may be dynamically adjusted (e.g., full or unlimited access) based on specific circumstances, teaming arrangement, investigation, or on a situational basis such as an emergency level or basis. The permissions may also be applied to access to the correlated data with the data granularity being commensurate with the permission levels. The permissions may be allocated by an external agency or service, and verified and assigned in accordance with the computing device(s)102.

The processor(s)118and memory114(executing computer program code) are also configured to provide a notification to a device such as a client device(s)108based on the correlated data. The notification may include an alert to a device such as a client device(s)108if the animal related data substantially deviates from the baseline by, for instance, a guard band. A notification may also be provided if the animal related data is outside a predetermined set or threshold, which may affect an accuracy of the correlated data. Of course, the processor(s)118and memory114(executing computer program code) may repeat at least a portion of the above-referenced operations as the application dictates.

Turning now toFIG. 3, illustrated is a block diagram of an embodiment of various applications and modules used to perform various computerized methods. Software programs are often subdivided into components that interact with one another or cause another component to perform some type of action or function to provide a desired functionality. This type of configuration and interaction between the components is also called “interconnected.” These components can take many forms depending on the programing language used and the operational environment(s) in which they are executed. In addition, the components can be interconnected in various ways to accommodate the programming language or operational environment(s). Primary functional components within software and hardware architectures are often referred to as layers or applications, which are typically interconnected in such a way to enable interaction between them. Secondary functional components are often referred to as modules, gadgets, widgets, tools, functions, etc. These secondary functional components can be interconnected with other secondary functional components and/or primary functional components. A frame is a type of box, window, container object or information dashboard displayed within a user interface that is used for input and/or output (e.g., an Internet browser, a word processing window, a file directory window, etc.). Many of these terms are interchangeable even though they may have different connotations within a specific software environment. As a result, the present invention is not limited by any use or definition of these terms.

In one embodiment of the present invention, a computer program300includes a data management application302, a data analysis application304and a user interface application306executable by one or more computing device(s)102communicably coupled to the one or more data source(s)104. In a related embodiment, the one or more computing device(s)102may be communicably coupled to the third party data source(s) and services110in addition to the one or more data source(s)104. The data management application302, data analysis application304and user interface application306are interconnected as indicated by the arrows340a,340b,340c. In one embodiment, the data management application302includes at least a data selection module308, but may include other data management modules310. The data management application302is the software interface to the data source(s)104. In another embodiment, the data management application302is the software interface to the data source(s)104and/or the third party data source(s) and services110. The data selection module308provides sufficient information to the data analysis application304and user interface application306such that those applications and modules therein are able to select, retrieve, save, process, manipulate and/or transform the desired data, and/or causes actions to be performed related to the desired data. The data management application302provides many other data management functions, which can be separate modules (e.g., other data management modules310), to users, database administrators, system administrators and authorized third parties. These functions may include, but are not limited to, data acquisition, collection, cleansing, filtering, formatting, integration, security, transformation, translation, conversion of formats, aggregation, queries, compression, encryption, decryption, repair, backup, delivery, etc.

The data analysis application304provides users with a set of manual and automated tools for analyzing data from the one or more data source(s)104via the data management application302. For example, data analysis application304can include an animal tracking module312, an animal disease detection module314, an animal event response module316, an animal health monitoring module318, an animal production management module320, a laboratory resource allocation module322, a laboratory throughput analysis module324, and other data analysis modules326. These modules will be described in more detail below in reference to various non-limiting examples. Moreover, some embodiments may include different sets of these modules or limit access to various modules.

The user interface application306provides a user friendly and user customizable interface to access, view, analyze, manipulate and otherwise use data from the one or more data source(s)104and/or the third party data source(s) and services110via the data management application302and data analysis application304. For example, the user interface application306can include an application control module328, a geospatial mapping module330, a data display module332, a macro or scripting module334and other user interface modules336. The application control module328provides a set of application control functions that allow a user to add, remove, change and manipulate frames displayed on the computing device(s)102, and to execute, control and terminate the modules within the program300, and the program300itself. The geospatial mapping module330displays a frame in the user interface that includes a map with one or more graphical objects representing various data from the data source(s)104or the modules from the data analysis application304. The geospatial mapping module330also provides various controls that allow a user to annotate, change and manipulate content displayed within the frame (e.g., map data overlaid with data from the data sources104or the modules from the data analysis application304). The data display module332displays a frame in the user interface that provides a listing, a chart or a graph of data from the data sources104or the modules from the data analysis application304in whatever visual format desired by the user. The macro or scripting module334allows the user to create, modify and save customized modules, which provide user-defined functions, analysis or displays.

Referring now toFIG. 4, illustrated is a block diagram of an embodiment of a user interface400created by the user interface application306ofFIG. 3. The application control module328creates and displays the user interface400(e.g., an initial, start-up or main window) on a display of the computing device(s)102. In this example, the user interface400includes six frames that can be removed, replaced, changed and manipulated by the user via a mouse, pen, keyboard, touch screen, other input device or a combination thereof. A first frame402typically includes a control menu, buttons, drop down menus, data entry fields, status information or other control functions of the application control module328that are used to control the user interface400and/or the program300. One of the other frames such as the second or fourth frames404,408, will typically provide input and output for the data display module332. Similarly, one of the frames such as the third frame406will provide input and output for the geospatial mapping module330. The other frames can provide input and output to any of the other modules within the program300or even additional instances of the data display module332or the geospatial mapping module330. Note that the frames within the user interface400can be moved, resized and manipulated by the user within the user interface400. Note that the user interface400can display more or less than six frames (e.g., one, two, ten, etc.). Moreover, the frames can be separated from the user interface400such that they are displayed outside the boarders of the user interface400or even on a second display.

Turning now toFIG. 5, illustrated is a block diagram of an embodiment of a modular and distributed architectural framework500for the system and computerized methods. The framework500includes a data sources layer502(i.e., the data management application302), a middleware layer504(i.e., the data analysis application304) having an integrated security layer506, and a presentation layer508(i.e., the user interface application306). The framework500: (a) relies upon a collection of loosely-coupled (and potentially distributed) services for contributing data and capabilities; (b) facilitates the fetching of raw data from services, brokering access to this data based on defined polices and user credentials, and feeding the data to supporting services linked to components (i.e., these can combine, fuse, visualize, and share or export the data); and (c) leverages a collection of reusable core services that are able to provide underlying system functionality (e.g., core dashboard, geocoding, administration services, data policy service, map server, data engine, and rendering services). The framework500can operate within a cloud environment or on one or more servers depending upon the system and application requirements.

The data sources layer502facilitates fusion of data and capabilities from different sources in an extensible, scalable, reliable, and secure way. The data sources layer502also allows for the development of custom components for integrating new sources of data from databases, data sources, sensors, etc. The set of data sources (i.e., for storing or warehousing and publishing data) and services (i.e., for accessing or interfacing and functioning on the data) provide a wide range of data and system capabilities, reside locally or remotely (i.e., in the cloud) to the system deployment, and support industry pervasive data exchange language such as Simple Object Access Protocol (“SOAP”), Representational State Transfer (“REST”), and/or Extensible Markup Language (“XML”) to facilitate data exchange. In one embodiment, the set of data sources and services include the data source(s)104and third party data source(s) and service(s)110.

In one embodiment, the framework500employs animal related data. The animal related data can include animal health data, movement data, key location data, surveillance data, diagnostic testing data, geographic information system (“GIS”) layer data, personnel data, resource data, other data, or a combination thereof. The animal related data can be collected automatically in near real-time or in real-time according to a predetermined schedule, on demand, randomly or when a change in the animal related data is detected within one or more of the third-party data source(s) or service(s)110. Note that, additional animal related data can be received from the client device(s)108.

As will be described in more detail below, the computerized method may include various ways of protecting confidential information obtained from the third-party data sources or disclosing such information only in an emergency. For example, one or more permissions can be assigned to the animal related data based on one or more data sharing agreements associated with the third-party data source. Thereafter, selected portions of the assessed animal related data are further transformed or restricted based on the one or more permissions assigned to the animal related data. The assessed animal related data can be transformed by aggregating the assessed animal related data to provide the selected portions of the assessed animal related data without disclosing any confidential information. In addition, access to the animal related data can be restricted based on a security level of a user, display or the client device. Access to the animal related data can be dynamically adjusted based on specific circumstances, teaming agreements, investigation, or on a situational basis such as an emergency level or basis. For instance, if emergency levels 1 to 5 represent emergency rankings from the lowest to the highest, then access may be dynamically adjusted based on the more severe rankings.

The middleware layer504bridges the data services layer502with the presentation layer508. The middleware layer504handles requests from data requestors to data providers, performs data processing as needed (e.g., processing, transforming, integrating, fusing or other data manipulation), and routes the data as required, which allows contributions from one component to another (i.e., sharing of data or capabilities across different components). For example, the middleware layer504can include various automated tools to support the analysis of integrated data such as: (a) baseline modeling and anomaly detection algorithms; (b) data mining algorithms for discovering patterns; and (c) intelligent agents for observing, learning, and determining, and responding to prescribed conditions, triggers, thresholds or events have been met or have occurred. In addition, the middleware layer504supports data caching to improve overall system and application performance.

The middleware layer504also integrates with the security layer506for enforcement of data access permissions. The security layer506allows the establishment and management of different policies and credentials that provide brokered access to data by the end users and groups. The security layer506can include a collection of administrative tools that: (a) allow for management of groups and end user account information; (b) allow for the management of data sharing and compartmentalization polices, and for granting permissioned access to data and system capabilities; (c) support the dynamic definition and configuration of custom profiles (i.e., both visual layouts and assignment of components); and (d) support the configuration of components and their underlying properties.

The middleware layer504may run various algorithms (modules) such as animal production management models, animal emergency models, baseline modeling, anomaly detection algorithms, data mining algorithms for discovering patterns, intelligent agents for observing, learning, and determining, and responding to when prescribed conditions, triggers, thresholds or events have been met or have occurred. If one or more conditions are detected, one or more notifications can be automatically created and sent to the display or one or more client devices. The one or more conditions may include an anomaly, a trigger condition, a pattern, a trend or a trigger event. In one example, one or more conditions indicate a possible animal disease event or a possible contamination event. The one or more notifications may include a request for additional animal health data, a request for one or more resources, an instruction to perform one or more tasks, an alert describing the one or more conditions, or a combination thereof. One example of such a notification is an indication that a case definition has been met through the input of prescribed animal health data, triggering the user to submit samples to a veterinary diagnostic laboratory. The notification is received as a pop-up window in the computing device(s)102and/or client device(s)108, and guides the user through the sample collection and submission process. Another example is an alert via pop-up window in the computing device(s)102and/or client device(s)108if animal related data indicates a disease for a particular animal herd and instructions not to move that particular animal herd.

The presentation layer508provides tools for interactive visualization and analysis of the contributed data. For example, the presentation layer508can include custom querying, filtering, grouping and sorting on the integrated data through form-based views, data viewing in a tabular fashion or transformed into interactive visualizations and custom computation that can be performed on the integrated data (i.e., basic calculations). The presentation layer508also supports development of custom visualizations that can be contributed to other components (i.e., allowing component data to be displayed on a map or timeline). Moreover, the presentation layer508allows the development of custom perspectives, profiles, and component configurations to address specific end user needs or activities (see, e.g., Information Dashboard Framework (“IDF”) described below).

Various non-limiting examples of the data sources layer502will now be described. The underlying data from the third-party databases contained in the data sources layer502includes animal related data (which may include animal health data and other information that is helpful in the assessment and presentation of the animal health data). Examples of various types of underlying data600(animal related data) are shown inFIG. 6. Note that the underlying data600can be obtained from a system owner or affiliated database(s). In one embodiment, the underlying data600can be classified into movement data602, key location data604, surveillance data606, diagnostic testing data608, animal data610, GIS layer data612, personnel data614, resource data616, etc. The movement data602can include production records, anticipated imports/exports, Certificates of Veterinary Inspections (“CVIs”), health papers, permits, exhibition registrations, product movement, region summaries, state summaries, etc. The key location data604can include animal premises, plants (packaging, processing, rendering, slaughter), market and buying stations, National Animal Health Laboratory Network (“NAHLN”) laboratories and other veterinary diagnostic laboratories, animal ports, checkpoints, landfills, disposal sites, burial locations, wash stations, etc. The surveillance data606can include field reports, facility biosecurity information and audit status, etc. The diagnostic testing data608can include test orders, test status, test results, etc. The animal data610can include tag and details, movements, testing, wildlife spotting, dead calls, etc. The GIS layer data612can include precipitation, cloud cover, temperature, vegetation, soil, land use/land cover, hydrology, flood zones or plains, roads, rail lines, parks, satellite imagery, etc. The personnel data614can include state veterinarians, animal health officials, certain governmental directors related to agriculture, accredited veterinarians, credentialed dealers, credentialed haulers, brand inspectors, other responders (sheriffs, emergency managers, sample collectors, vaccine distributors), etc. The resource data616can include vaccines, key equipment, warehouses, and staging locations, etc.

The underlying data600in the data sources layer502can be integrated in such a way to satisfy one or more criteria. For example, the underlying data600may be digitally stored in an accessible means, ranges in type and scope (e.g., premises details, animal inventories, animal movements, diagnostic test orders and results, disease surveillance reports, animal production information), managed by a variety of different means (e.g., spreadsheets, databases, applications), stored in a variety of disparate formats and structures (e.g., JavaScript Object Notation (“JSON”), EXtensible Markup Language (“XML”), text, relational), managed and owned by different entities or organizations, and not currently integrated (in near real-time at least) as part of normal operational settings. In another embodiment, a portion or all of the underlying data600may be converted and stored in a common format or an extensible format. In addition, the underlying data600often varies in data resolution and/or completeness, and in some cases can be noisy in nature. Moreover, the underlying data600often contains business sensitive or confidential data requiring strict control and compartmentalization when sharing across different entities or organizations, and/or needs to be processed and presented in a variety of ways for effective use by different stakeholders across all aspects of the animal health.

Turning nowFIG. 7, illustrated is a diagram of an embodiment of an architectural framework700. The architectural framework700includes various network-based services705that are accessed by various middleware components750to provide an information dashboard framework (“IDF”)770that displays the accessed animal related data in various graphical and analytical representations. The network-based services705include various databases710, applications715(e.g., models, simulations, etc.), sensors720, and dashboards725. The middleware components750include agent-based monitors760that interface with the network-based services705to provide the selected animal related data to the IDF770, and provide cautions, alerts and warnings based on threshold conditions or values. In one embodiment, the IDF770is part of a computing device(s)102that causes the IDF770to be displayed on a display116. In another embodiment, the IDF770can be implemented as a thin client and used on mobile devices. The configuration of the middleware components750and the IDF770will vary based on the set of user-defined criteria used to populate the information displayed on the IDF770.

In one embodiment, the IDF770is part of the user interface application306and is a development environment for quickly generating information dashboards that receive data from multiple disparate sources. The IDF770supports command and control activities (and decision support) during emergency operations by providing a common integrated display that would serve as a common operational picture (“COP”) to enable better situational awareness for decision makers. This notion has been extended to the creation of user-defined operating pictures (“UDOP”) that allow for coordinated activity by allowing dashboards to be used by decision makers at different locations with different areas of responsibility. The system facilitates users making better decisions, faster. Thus, using a service-oriented architecture provides enhanced response capabilities by organizing relevant data from authoritative sources to facilitate rapid information sharing between industry and government at the national level for animal management including during an animal disease event.

In one embodiment, the domain that IDF770particularly excels in is related to command and control and the notion of establishing a common operating picture that facilitates situation awareness and aids in the decision making process at multiple levels or echelons. In this domain, common operating pictures are often GIS-centric with icons existing on maps that are linked to specific data components. Such an approach is not usually sufficient in fully gaining situational awareness. The IDF770overcomes this approach by providing a rich set of components that extends annotated maps with a number of functional components that can manipulate data (collection, filtering, and fusion), create visual analytical representations, link to external video and rich site summary (“RSS”) feeds, enforce data access rules, and a number of other functions that contribute to a common operating picture and can be tailored for a specific user. In fact, the notion of a common operation picture is extended to the concept of a user-defined operating picture.

The IDF770provides multiple capabilities and features, some of which include: (a) the ability to transform from one unique perspective to another very quickly, which relate to a specific task or mission that a user is performing and the collection of components chosen to support that task or mission; (b) the fusion of data from multiple data streams from different sources to create new perspectives oriented on a greater understanding of the problem space; (c) the inclusion of an agent layer capable of evaluating the incoming data based on a set of conditional rules; (d) the enforcement of privileged data access by controlling access to the set of components available to a particular user; (e) the ability for enabled dashboards to exchange data among themselves; (f) the redirection of a data stream from one service to another for additional processing; and (g) a powerful environment for dashboard administration and customizable layout. The particular technical approach for the IDF is centered on the implementation of a service-oriented architecture with access to a vast array of services existing within the “cloud.” The IDF770connects to candidate services such as data, applications (e.g., simulations), sensors, and other IDF-based dashboards. Data is represented directly in a prescribed manner, combined (fusion) with two or more data streams for unique representations, or acquired from one service and routed to another source for additional processing.

As illustrated, the IDF770is composed of one or more frames (one of which is designated775) providing input to and output from functional modules (i.e., each box or container object within the gridded display corresponds to an individual frame running a module). A module represents both function and access to a particular data source or service. In one embodiment, the modules represent a library of different capabilities that can include geospatial mapping, resource management, logs, communication, models and simulation, visual analytics, and integration of live sensor data. Different perspectives can then be configured within the dashboard to support different operational tasks or missions by organizing a unique set of frames running selected modules. Profiles represent user categories or positions within an organization and are usually represented by multiple pre-defined perspectives.

IDF-based dashboards are user-definable, and a user can easily customize the active modules from the available library. A user can swap these frames in and out of their display, and resize them, to customize the display to best meet their needs. This overall flexibility is what leads to a user-definable operating picture. In another embodiment, the IDF770allows the use of dashboard templates to allow configuration, control and/or customization of the frames of the IDF770. Finally, agent-based monitoring modules760can be setup and configured to monitor the component data feeds (running in the background) and when an event of interest is identified, an alert or warning can be provided to the end-user.

Non-limiting examples of various embodiments of the system include the Emergency Response Support System (“ERSS”), Enhanced Passive Surveillance System (“EPSS”), and Laboratory Capacity Estimation Model (“LCEM”), which will be described in more detail below in reference to exemplary IDFs. Another embodiment includes the Bio-surveillance Common Operating Picture (“BCOP”). The BCOP is a biological application of the IDF that allows analysts to track, organize, and share biological event information in real-time.

Turning nowFIG. 8, illustrated is a flow chart of an embodiment of a method of analyzing and displaying one or more sets of animal related data. With continuing reference to preceding FIGUREs, the method begins at a start step810. At a step820, the method invokes selected applications and modules ofFIG. 3. For instance, the method invokes: (a) the data selection module308within the data management application302; (b) the animal tracking module312, the animal disease detection module314and the animal event response module316within the data analysis application304; and (c) the application control module328, the geospatial mapping module330, the data display module332and the macro or scripting module334within the user interface application306.

The data management application302can be used to automatically collect the animal related data from the data source(s)104and/or third party data source(s) and service(s)110, or integrate additional animal related data from one or more sensors into the one or more sets of animal related data. The data management application302or data analysis application304can automatically create and send one or more notifications to client device(s)108communicably coupled to the computing device(s)102. The data management application302can also receive additional animal related data from client device(s)108communicably coupled to the computing device(s)102, assign one or more permissions to the animal related data based on one or more data sharing agreements associated with the data source(s)104and/or third party data source(s) and service(s)110, transform or restrict the selected portions of the assessed animal related data based on the one or more permissions assigned to the animal related data, aggregate the assessed animal related data to provide the selected portions of the assessed animal related data without disclosing any confidential information, limit access to the animal related data based on a security level of a user, display or a client device, or dynamically adjust access to the animal related data based on specific circumstances such as an emergency level or basis.

The data analysis application304provides users with a set of manual and automated tools for analyzing data from the data source(s)104and/or third party data source(s) and service(s)110via the data management application302. The user interface application306provides a user friendly and user customizable interface to access, view, analyze, manipulate and otherwise use data from the data source(s)104and/or third party data source(s) and service(s)110via the data management application302and data analysis application304.

A set of application control functions from the application control module328is displayed, by the computing device(s)102, in a user interface of a display in a step830. The application control module328provides a set of application control functions that allow a user to add, remove, change and manipulate frames displayed on the computing device(s)102, and to execute, control and terminate the modules and applications. The set of application control functions enable customization and control of the user interface, and execution of the data selection module308, the animal tracking module312, the animal disease detection module314, the animal event response module316, the geospatial mapping module330, the data display module332, and the macro or scripting module334. The user interface application306can also provide a data query tool, a map annotation tool, a calculator, one or more analytical tools, the macro or scripting module334to create user-defined modules, etc.

In a decisional step840, a user input is received, by the computing device(s)102, in the user interface of the display that indicates activation or selection of at least one of the modules. If the user input indicates activation of the data selection module308, the method obtains the one or more sets of animal related data and causes the one or more computing device(s)102to display the one or more sets of animal related data in a first frame of the user interface in step850. The animal related data can include animal health data, movement data, key location data, surveillance data, diagnostic testing data, GIS layer data, personnel data, resource data, other data, or a combination thereof. The third-party data source(s) and service(s)110can include governmental databases, laboratory databases, animal processing databases, animal producer databases, veterinarian databases, commercial databases, data feeds, sensor data, other sources, or a combination thereof.

If the user input indicates activation of the animal tracking module312, one or more sets of animal related data are correlated with geospatial data in a step855. The animal tracking module312can be used, among other things, to track movement of one or more animals over time, or track one or more permits associated with one or more animals over time and determine a status of the one or more permits.

If the user input indicates activation of the animal disease detection module314, one or more sets of animal related data are analyzed based on one or more disease identification parameters in a step860. As shown inFIG. 9, data from data stream(s) is monitored over time as shown in a graphical representation900. In one embodiment, the data is separated into three segments that slide forward in time. These segments include: (1) a baseline interval902to estimate expected data behavior; (2) the current event904, typically 1-7 days, of potentially anomalous data; and (3) a guard band906between the baseline interval902and the current event904to avoid contamination of the baseline interval902by an outbreak signal. Whether the quantities of interest are simple means and standard deviations, regression coefficients, spatial distributions, or distributions of covariate strata (e.g., age groups), these temporal subdivisions are used to determine whether the current event904violates the null hypothesis of expected behavior inferred from the baseline interval902. This analysis can be used to determine if a disease outbreak is more prevalent within or among different data groups. The baseline interval902is analyzed by examining different categorizations of data relationships. The significance of resulting signals as disease detection events: (a) requires examination of specific health information that is resulting in an algorithm-derived alert; (b) initiates communication between veterinarians and/or State/Federal Animal Health Officials; (c) identifies potential outbreak and geographic extent, changes in animal health status, or absence of a disease event; (d) quantifies how much we are looking for disease to report to trading partners; and (e) concepts of operation for disease response (SAHOs, Federal Government, and/or Veterinarians/Producers). Additional analysis may include cluster techniques and space-time statistics. The disease identification parameters can be adjusted to detect a specific disease, or detect a new strain of the specific disease, or to compensate for seasonality. One or more trigger conditions can be set to provide an alert or notification of the specific disease when such a disease is detected. The animal disease detection module314can provide an alert or warning not to move one or more animals to or from a specific geographic area. In another embodiment, the animal disease detection module314can also be used to analyze the data in order to detect one or more anomalies within the one or more sets of animal related data, predict spread of a disease based on a statistical analysis, detect one or more symptoms, or disease related patterns or trends, or identify a potential threat to human public health. The animal disease detection module314may also include one or more phylogenetic analysis tools.

If the user input indicates activation of the animal event response module316, one or more sets of animal related data are analyzed based on one or more animal related emergency response parameters in a step865. In a related embodiment, the one or more animal related emergency response parameters may dynamically change as the situation dynamically changes. The animal event response module316can be used to analyze the data and determine a quarantine zone or a buffer zone, determine an allocation of resources, plan a response to an actual or simulated animal disease outbreak, implement a response to an actual animal disease outbreak. The allocation of resources can be based on an animal vaccination scenario, an animal sampling scenario, an animal slaughter scenario or a combination thereof.

If the user input indicates activation of the geospatial mapping module330, the method causes a map with one or more graphical objects representing the one or more sets of animal related data, correlated data from the animal tracking module312, analyzed data from the animal disease detection module314or analyzed data from the animal event response module316to be displayed, by the one or more computing device(s)102in a second frame of the user interface in a step870. The geospatial mapping module330displays a frame in the user interface that include a map with one or more graphical objects representing various data (e.g., type of animal, stage of production, disease status, etc.). The geospatial mapping module330also provides various controls that allow a user to annotate, change and manipulate content displayed within the frame (e.g., map data overlaid with data from the other sources).

If the user input indicates activation of the data display module332, the method causes a listing, a chart or a graph of the one or more sets of animal related data, correlated data from the animal tracking module312, analyzed data from the animal disease detection module314or analyzed data from the animal event response module316to be displayed, by the one or more computing device(s)102in a third frame of the user interface in a step875. The data display module332displays a frame in the user interface that provides a listing, a chart or a graph of data.

If the user input indicates activation of the macro or scripting module334, the method allows the user to create, modify and save customized modules, which provide custom functions, analysis or displays in a step880. Thereafter, the method ends in a step890. The method may also start again or return to one of the earlier steps depending on the application. The method is not limited to the foregoing steps or the specific order of steps described.

As an example, the Emergency Response Support System (“ERSS”) is an integrated, fully distributed, multi-purpose system capable of supporting emergency response by featuring operational, training, and analytical functionality for animal disease outbreaks. The ERSS provides a web-based tool for large and small-scale incident management. The ERSS uses a service-oriented architecture to provide enhanced response capabilities by organizing relevant data from authoritative sources to facilitate rapid information sharing between industry and government at the national level during an animal disease event. The ERSS can be used as an operational tool during a response, as an analysis tool after an event is complete, and as a training tool to prepare for possible future incidents. The ERSS can be used as a pivotal tool for the day-to-day operations and incident response. The ERSS incorporates information from various governmental entities to allow calculation of the number of vaccine doses, personnel needs, and sampling required when one or more outbreak zones are “drawn” or selected on a user interface (i.e., scale and geographic distribution of an outbreak). Topics include resources related to vaccination, active surveillance, and depopulation. Accurate and timely information enables decision makers to mitigate the risk when managing animal movement in support of business continuity operations. Support for rapidly performing traceability of animal movement is also critical.

Turning now toFIG. 10, illustrated is a screen shot of an embodiment of an emergency response dashboard1000. The emergency response dashboard1000is divided into ten frames, namely, a system frame1001(minimized), an incident list frame1002, calculators frame1003, a NAHLN facilities frame1004, a current weather frame1005, an interactive mapping frame1006, a Meat, Poultry & Egg Product Inspection (“MPI”) directory frame1007, a Bio-Surveillance Field Entry System (“BFES”) reports frame1008, an ERSS news frame1009, and a map bookmarks frame1010. As shown, the incident list frame1002includes bovine data sets for June foot and mouth disease (“FMD”) Exercise1011, Antigo FMD Outbreak1012, Greenstown classical swine fever (“CSF”) Outbreak1013and Flat City Outbreak1014. The calculators frame1003includes a buffer zone calculator1015, a depopulation cost calculator1016, a generic filter computation calculator1017, an infected zone calculator1018, a number of test samples calculator1019and a surveillance zone calculator1020. The NAHLN facilities frame1004displays data regarding NAHLN facilities. The current weather frame1005provides current weather conditions with a link to a weather forecast. The interactive mapping frame1006graphically displays selected data on a map and includes a set of map navigational tools1021and a set of analytical tools1022. The interactive mapping frame1006overlays and color codes various infected, buffer and surveillance zones, as well as test sample locations and geographic information on the map. The MPI directory frame1007allows the user to search and display data from the Meat, Poultry & Egg Product Inspection (“MPI”) Directory. The BFES reports frame1008displays a bar chart of BFES report data for swine, ruminants, equine and bovine. The ERSS news frame1008displays various current new feeds. The map bookmarks frame1010allows the user to click on the tabs to display bovine inventory by county1023, swine inventory by county1024, sheep inventory by county1025, goat inventory by county1026, livestock inventory by state1027, sheep inventory by state1028, and swine inventory by state1029.

Turning now toFIG. 11, illustrated is a flow chart of an embodiment of a method of monitoring the health of one or more animal herds. With continuing reference to preceding FIGUREs, the method begins at a start step1110. At a step1120, the method invokes selected applications and modules ofFIG. 3. For instance, the method invokes: (a) the data selection module308within the data management application302; (b) the animal disease detection module314and the animal health monitoring module318within the data analysis application304; and (c) the application control module328, the geospatial mapping module330, the data display module332and the macro or scripting module334within the user interface application306.

The data management application302can be used to automatically collect the animal related data from the data source(s)104and/or or third party data source(s) and service(s)110, or integrate additional animal related data from one or more sensors into the one or more sets of animal related data. The data management application302or data analysis application304can automatically create and send one or more notifications to client device(s)108communicably coupled to the computing device(s)102. The data management application302can also receive additional animal related data from client device(s)108communicably coupled to the computing device(s)102, assign one or more permissions to the animal related data based on one or more data sharing agreements associated with the data source(s)104and/or third party data source(s) and service(s)110, transform or restrict the selected portions of the assessed animal related data based on the one or more permissions assigned to the animal related data, aggregate the assessed animal related data to provide the selected portions of the assessed animal related data without disclosing any confidential information, limit (or dynamically restrict) access to the animal related data based on a security level of a user, the display or a client device, or dynamically adjust access to the animal related data based on specific circumstances such as an emergency level or basis.

The data analysis application304provides users with a set of manual and automated tools for analyzing data from the data source(s)104and/or third party data source(s) and service(s)110via the data management application302. The user interface application306provides a user friendly and user customizable interface to access, view, analyze, manipulate and otherwise use data from the data source(s)104and/or third party data source(s) and service(s)110via the data management application302and the data analysis application304.

A set of application control functions from the application control module328is displayed, by the computing device(s)102, in a user interface of a display in a step1130. The application control module328provides a set of application control functions that allow a user to add, remove, change and manipulate frames displayed on the computing device(s)102, and to execute, control and terminate the modules and applications. The set of application control functions enable customization and control of the user interface, and execution of the data selection module308, the animal disease detection module314, the animal health monitoring module318, the geospatial mapping module330, the data display module332, and the macro or scripting module334. The user interface application306can also provide a data query tool, a map annotation tool, a calculator, one or more analytical tools, the macro or scripting module334to create user-defined modules, etc.

In a decisional step1140, a user input is received, by the computing device(s)102, in the user interface of the display that indicates activation of at least one of the modules. If the user input indicates activation of the data selection module308, the method obtains the one or more sets of animal related data and causes the one or more computing device(s)102to display the one or more sets of animal related data in a first frame of the user interface in a step1150. The animal related data can include animal health data, movement data, key location data, surveillance data, diagnostic testing data, GIS layer data, personnel data, resource data, other data, or a combination thereof. The third-party data source(s) and service(s)110can include governmental databases, laboratory databases, animal processing databases, animal producer databases, veterinarian databases, commercial databases, data feeds, sensor data, other sources, or a combination thereof.

If the user input indicates activation of the animal health monitoring module318, one or more sets of animal related data are analyzed for any changes in the health of the one or more animal herds in a step1155. The animal health monitoring module318can provide the same functionality as the animal tracking module312including, among other things, to track movement of one or more animals over time, or track one or more permits associated with one or more animals over time and determine a status of the one or more permits. In addition, animal health monitoring module318can request an additional testing of one or more animals, or an animal health data associated with one or more animals, etc. In another embodiment, the animal health monitoring module318can provide a notification such as an alert or warning not to move one or more animals to a specific geographic area.

If the user input indicates activation of the animal disease detection module314, one or more sets of animal related data are analyzed based on one or more disease identification parameters in a step1160. For a better understanding of monitoring data over time, see the description ofFIG. 9set forth above.

If the user input indicates activation of the geospatial mapping module330, the method causes a map with one or more graphical objects representing the one or more sets of animal related data, analyzed data from the animal health monitoring module318, or analyzed data from the animal disease detection module314to be displayed, by the one or more computing devices in a second frame of the user interface in a step or module1165. The geospatial mapping module330displays a frame in the user interface that include a map with one or more graphical objects representing various data (e.g., type of animal, stage of production, disease status, etc.). The geospatial mapping module330also provides various controls that allow a user to annotate, change and manipulate content displayed within the frame (e.g., map data overlaid with data from the other source(s)).

If the user input indicates activation of the data display module332, the method causes a listing, a chart or a graph of the one or more sets of animal related data, analyzed data from the animal health monitoring module318, or analyzed data from the animal disease detection module314to be displayed, by the one or more computing device(s)102in a third frame of the user interface in a step1170. The data display module332displays a frame in the user interface that provides a listing, a chart or a graph of data.

If the user input indicates activation of the macro or scripting module334, the method allows the user to create, modify and save customized modules, which provide custom functions, analysis or displays in a step1175. Thereafter, the method ends in a step1190. The method may also start again or return to one of the earlier steps depending on the application. The method is not limited to the foregoing steps or the specific order of steps described.

In an embodiment, the EPSS provides an integrated application for collecting and analyzing enhanced surveillance data, and includes a mobile device application (the Bio-surveillance Field Entry System (“BFES”)) to allow veterinarians to enter clinical animal health data from livestock premises, feedlots, and markets. The mobile application links to the Analyst Workstation (“AWS”) dashboard and allows epidemiologists to aggregate collected data through the use of visual, geospatial, and temporal analysis tools to aid in early disease detection or changes in animal health status. The EPSS has broad applications in the international community, especially for monitoring and understanding movement of and relationships between transboundary, emerging, and zoonotic diseases. The data on syndromic prevalence and risk factors associated with neglected diseases such as brucellosis are lacking in many under-developed and developing countries/regions of the world.

The EPSS supports the development of technology to enable the real-time (or near real-time) collection and analysis of pre-diagnostic data related to clinical symptoms or syndromes observed by an attending veterinarian at an AWS as shown inFIG. 12. An example of the AWS is shown inFIG. 12in which a biosurveillance dashboard1200is divided into seven frames, namely, a species reports frame1201(bar graph), a syndrome reports frame1202(bar graph), a system and filter frame1203, an interactive mapping frame1204, a data selection frame1205, a syndrome reports custom frame1206(line graph) and a Laboratory Information Management System (“LIMS”) frame1207(line graph). The system and filter frame1203includes a system tab1208and a global filter tab1209. The interactive mapping frame1204graphically displays selected data on a map and includes a set of map navigational tools1210and a set of analytical tools1211. The data selection frame1205includes an agencies tab1212, a links tab1213and a calculators tab1214. As shown, the calculators tab1214provides access to various filtered data sets, such as all data1215, generic filter reports1216and healthy reports1217.

EPSS uses mobile devices and web-enabled browsers to collect and send the data to an AWS where data is aggregated and combined with embedded tools to help determine baseline conditions in order to detect any anomalies that may signal the onset of an animal disease outbreak. Anomaly detection is the analysis and evaluation of surveillance data to identify unusual increases in animal health outcomes. Algorithms for anomaly detection can be used to quickly identify anomalies based on time series analyses of syndromic data (e.g., count data, number of cases with a given syndrome, or percent positive data, etc.). The anomalies may include abnormal deaths, unexpected clinical signs, weight loss, low birth count, low birth rate, etc. The methods vary in terms of sensitivity, specificity, and false positive rates (e.g., cumulative sum (“CUSUM”), multivariate regression, space-time analysis, etc.). Temporal aggregation can be used for determining syndrome baselines. The baseline period is selected from very recent week(s) relative to the current value. Possible fluctuations in the expected case count attributed to any particular syndrome are accounted for. Seasonal and regional variability is also considered.

The embodiments disclosed herein are capable of rapidly collecting data using computing devices such as mobile devices and integrating that information in real-time with other sources to quickly identify disease events and determine effective interventions and resource allocations. For example, EPSS captures field information from veterinarians, community animal health workers, livestock owners, and other animal and public health officials about livestock and poultry health status in real-time though a mobile device (e.g., tablet or smartphone). It then organizes the information in to an easy-to-use computer display for monitoring and analysis, combining it with other data coming from veterinary diagnostic laboratories, wildlife, livestock markets, slaughterhouses, and environmental data sources.

By improving data collection capabilities and integrating information from multiple disparate sources, the EPSS provides a more comprehensive view of animal health over space and time to aid in early disease detection or monitor changes in animal health status. It is estimated that 60 percent of all human pathogens are zoonotic; therefore analysis of real-time animal health information can have a direct impact on public health, especially in the developing world where animals and humans interact and live together on a daily basis.

In one embodiment, the client device108may include a mobile device application such as BFES, which allows for real time collection and reporting of enhanced surveillance data. Through the BFES mobile device application, veterinarians, technicians, production managers, and livestock market inspectors can enter healthy and syndromic animal health data from livestock and poultry premises and livestock markets. The BFES mobile device application links to the AWS shown inFIG. 12, which is part of the system, and allows epidemiologists to aggregate and analyze real-time data through the use of visual, geospatial, and temporal analysis tools to aid in early disease detection or changes in animal health status. The BFES mobile device application also provides valuable information back to veterinarians and livestock market inspectors regarding other syndromic reports in their state, providing access to a unique information source to aid in animal diagnosis and treatment, as well as increasing their situational awareness of the animal health status within their geographic region or state. The BFES mobile device application can link laboratory results with the pre-diagnostic syndromic reports.

As illustrated inFIGS. 13 to 15, BFES mobile device application users (veterinarians, technicians, wildlife service personnel, production managers, etc.) can use a mobile application interface for field data collection (i.e., populate animal related data via designated fields, (seeFIG. 13), the animal related data can be summarized, filtered, aggregated, anonymized and displayed by geographical region using analytics embedded in the mobile application and shared among veterinarians via a summary report feature within the BFES mobile device application (seeFIG. 14). In one embodiment, when a new user creates an account and logs into the BFES mobile device application, the user is informed of, and has to agree to, the requirements associated with protecting the data to which the user has access. In another embodiment, when the user logs into the BFES mobile device application, the user is verified as to the rights that user has and to what data the user has access to. In a related embodiment, the verified user has a predefined location and is prevented from changing his/her location to see another user's or state's data or information. The Summary Reports (seeFIG. 14) visualizes a user's own data and his/her state's data aggregated at the county level in graphical, geographical and tabular forms. Touching a county on the interactive map enables a popup window showing the number of submitted reports for that county. The user's forum is accessible via the application or Internet and allows communication between users of the same state (seeFIG. 15).

Turning now toFIGS. 16 to 20, illustrated are screen shots of an embodiment of a mobile device application.FIGS. 16 to 18relate to poultry andFIGS. 19 and 20relate to equine. As shown inFIGS. 16 and 20, pre-order and test result data from diagnostic laboratories can be incorporated. The BFES mobile device application generates an unique case identification number (“ID”) for tracking submission of lab samples and linking of messaged test results to submitted surveillance reports. Immediate notifications of test results can be linked to submitted surveillance reports. Also, global positioning system (“GPS”) data is provided at farm level, but typically is not shared beyond the producer. As shown inFIG. 17, historical data collection includes feed intake, water consumption, internal house temperature, and mortality history. Information can be reported for previous dates based on the report date entered. As shown inFIG. 18, the BFES mobile device application includes a report for a health survey for recording and tracking health data from routine necropsies. Feed program(s) are recorded; different programs can be specified for different poultry farms/houses. With respect to data entry, the user can scroll through necropsy codes at the top to select and add to the report, the scoring system for recording necropsy findings is based on industry criteria, and automatic analysis of data is provided.

As shown inFIG. 19, new reports can be created that describe the premises, animal, reason for examination, etc.FIG. 19shows a “healthy report,” but “syndromic reports” are also able to be generated by users. Pop-up windows throughout the application display additional information (e.g., definitions of the terms used, examples of the type of information to be entered into the data field, internal number validations, etc.). After completion, reports are submitted. If the user is out of connectivity, the reports are uploaded automatically when the user re-enters connectivity. As shown inFIG. 20, the BFES mobile device application includes a closed loop system supporting lab surveillance, lab test submission, and lab test results. The BFES mobile device application can notify the user that he/she can submit lab samples (i.e., this section becomes activated) if certain criteria are filled out in the report. These criteria compromise the “EPS Case Definition,” which is defined as a specific set of internal disease indicators pre-programmed into the BFES applications. When these criteria are met, a unique case identification number (“Case ID”) will be automatically generated, which is used to link the lab accession test results back to the specific BFES report. An additional feature allows users to generate Case IDs to include with laboratory order accession forms to pair messaged veterinary diagnostic laboratory tests reports on syndromic reports, even in the absence of a case definition, to allow for user flexibility in test ordering. In this instance, the unique Case ID that is automatically generated, also links test results back to the specific BFES report submission. The BFES mobile device application also includes standard operating procedures (“SOPs”) for sampling and shipping.

Traditionally, animal surveillance programs have focused on regulated disease- and agent-specific detection with confirmed laboratory diagnosis, and are not adapted to identify and react to nonregulated disease and health events. A properly developed comprehensive EPSS will provide early detection of endemic, zoonotic, transboundary, environmental, and newly emerging animal diseases, as well as provide the opportunity for targeted surveillance of regulated diseases. These systems leverage the use of state-of-the-art mobile technology for field data collection, giving increased power to traditional clinical veterinary observations by combining them with other existing animal health information streams. In addition, documenting the number of animals observed for signs of foreign animal diseases and found to be healthy will assist the government in demonstrating disease freedom to trading partners.

As illustrated inFIG. 21, the client device108may further include a mobile CVI application, which is an easy-to-use mobile device-based version of the electronic CVI (“eCVI”) form that automatically emails a portable document format (“PDF”) CVI form to the SAHOs to permit interstate animal movements. A paper certificate can be printed directly from the client device108(e.g., mobile device) to a mobile printer. Users will need to be verified before CVI submissions are allowed. Data can be transmitted automatically to the SAHO database and accessible for use in combination with other data streams within the system.

Turning now toFIG. 22, illustrated is a flow chart of an embodiment of a method of monitoring the health of one or more animal herds. With continuing reference to preceding FIGUREs, the method begins at a start step2210. At a step2220, the method invokes selected applications and modules ofFIG. 3. For instance, the method invokes: (a) the data selection module308within the data management application302; (b) the animal health monitoring module318and the animal production management module320within the data analysis application304; and (c) the application control module328, the geospatial mapping module330, the data display module332and the macro or scripting module334within the user interface application306.

The data management application302can be used to automatically collect the animal related data from the data source(s)104and/or or third party data source(s) and service(s)110, or integrate additional animal related data from one or more sensors into the one or more sets of animal related data. The data management application302can be used to protect confidential information obtained from the data source(s)104and/or third party data source(s) and service(s)110, and disclose such confidential information in an emergency. The data management application302or data analysis application304can automatically create and send one or more notifications to client device(s)108communicably coupled to the computing device(s)102. The data management application302can also receive additional animal related data from client device(s)108communicably coupled to the computing device(s)102, assign one or more permissions to the animal related data based on one or more data sharing agreements associated with the data source(s)104and/or third party data source(s) and service(s)110, transform or restrict the selected portions of the assessed animal related data based on the one or more permissions assigned to the animal related data, aggregate the assessed animal related data to provide the selected portions of the assessed animal related data without disclosing any confidential information, limit (or dynamically restrict) access to the animal related data based on a security level of a user, the display or a client device, or dynamically adjust access to the animal related data based on specific circumstances such as an emergency level or basis.

The data analysis application304provides users with a set of manual and automated tools for analyzing data from the data source(s)104and/or third party data source(s) and service(s)110via the data management application302. The user interface application306provides a user friendly and user customizable interface to access, view, analyze, manipulate and otherwise use data from the data source(s)104and/or third party data source(s) and service(s)110via the data management application302and the data analysis application304.

A set of application control functions from the application control module328is displayed, by the computing device(s)102, in a user interface of a display in a step2230. The application control module328provides a set of application control functions that allow a user to add, remove, change and manipulate frames displayed on the computing device(s)102, and to execute, control and terminate the modules and applications. The set of application control functions enable customization and control of the user interface, and execution of the data selection module308, the animal health monitoring module318, the animal production management module320, the geospatial mapping module330, the data display module332, and the macro or scripting module334. The user interface application306can also provide a data query tool, a map annotation tool, a calculator, one or more analytical tools, the macro or scripting module334to create user-defined modules, etc.

In a decisional step2240, a user input is received, by the computing device(s)102, in the user interface of the display that indicates activation of at least one of the modules. If the user input indicates activation of the data selection module308, the method obtains the one or more sets of animal related data and causes the one or more computing device(s)102to display the one or more sets of animal related data in a first frame of the user interface in a step2250. The animal related data can include animal health data, movement data, key location data, surveillance data, diagnostic testing data, GIS layer data, personnel data, resource data, other data, or a combination thereof. The third-party data source(s) and service(s)110can include governmental databases, laboratory databases, animal processing databases, animal producer databases, veterinarian databases, commercial databases, data feeds, sensor data, other sources, or a combination thereof.

If the user input indicates activation of the animal health monitoring module318, one or more sets of animal related data are analyzed for any changes in the health of the one or more animal herds in a step2255. The animal health monitoring module318can provide the same functionality as the animal tracking module312including, among other things, to track movement of one or more animals over time, or track one or more permits associated with one or more animals over time and determine a status of the one or more permits. In addition, animal health monitoring module318can request an additional testing of one or more animals, or an animal health data associated with one or more animals, etc. In another embodiment, the animal health monitoring module318can provide a notification such as an alert or warning not to move one or more animals to a specific geographic area.

If the user input indicates activation of the animal production management module320, one or more sets of animal related data are analyzed based on one or more animal production parameters in a step2260. The animal production management module320can also be used to adjust one or more preplanned animal movements, share an animal test data between two or more animal producers, and share premises disease status for a particular pathogen of interest between two or more animal producers, adjust an animal diet based on the analyzed data, and adjust an animal vaccination schedule based on the analyzed data.

If the user input indicates activation of the geospatial mapping module330, the method causes a map with one or more graphical objects representing the one or more sets of animal related data, analyzed data from the animal health monitoring module318, or analyzed data from the animal production management module320to be displayed, by the one or more computing devices in a second frame of the user interface in a step or module2265. The geospatial mapping module330displays a frame in the user interface that include a map with one or more graphical objects representing various data (e.g., type of animal, stage of production, disease status, etc.). The geospatial mapping module330also provides various controls that allow a user to annotate, change and manipulate content displayed within the frame (e.g., map data overlaid with data from the other source(s)).

If the user input indicates activation of the data display module332, the method causes a listing, a chart or a graph of the one or more sets of animal related data, analyzed data from the animal health monitoring module318, or analyzed data from the animal production management module320to be displayed, by the one or more computing device(s)102in a third frame of the user interface in a step2270. The data display module332displays a frame in the user interface that provides a listing, a chart or a graph of data.

If the user input indicates activation of the macro or scripting module334, the method allows the user to create, modify and save customized modules, which provide custom functions, analysis or displays in a step2275. Thereafter, the method ends in a step2290. The method may also start again or return to one of the earlier steps depending on the application. The method is not limited to the foregoing steps or the specific order of steps described.

As an example, the present invention can provide an approach to mitigate the disruption to the normal business cycle for livestock, poultry, and associated animal products that are likely to occur during an animal disease outbreak in the United States, or elsewhere. This embodiment provides a data/information sharing and management architecture that allows business sensitive data to be distributed in a controlled manner, and then integrates that information to support shared situational awareness and decision-making. This supports better risk assessment, mitigation, and management during response operations. Although the system can be provided in a regional or industry specific implementation, the system is scalable to provide a full-scale national or even international deployment of the system across all industries as hereinafter demonstrated.

Turning now toFIG. 23, illustrated is a screen shot of an embodiment of disparate data streams for an animal. In this case, the disparate data streams support the Secure Pork Supply (“SPS”) that feed into the ERSS system. Data is obtained from SAHOs2300, producers2302, processors2304, diagnostic labs2306and governmental agencies2308. The data is tagged with a premises identifier2310to indicate the source of the data, and then provided to the various applications, such as an ERSS2312. The data from the SAHOs2300includes state premises information2314and monthly movement and interstate movement reports2316. The data from the producers2302includes premises census numbers and movement data2318and health papers2320. The data from the processors2304include packer/packer movement data2322. The data from the diagnostic labs2306includes testing results2324. The data from the government agencies2308includes testing results2326, surveillance data2328, investigation data2330, permit data2332and federal health papers2334. In accordance therewith, data such as the state premises information2314, premises census numbers and movement data2318and testing results2324may be integrated and combined to provide real time graphical analysis of animal production data. The system shows the day-to-day usefulness for monitoring facility disease status, and premises disease status to support the decision on whether or not to move animals.

Turning now toFIG. 24, illustrated is a screen shot of an embodiment of a day-to-day animal health management dashboard2400. The day-to-day animal health management dashboard2400is divided into eight frames including a system and incident frame2405, a map shapes frame2410, a swine production frame2415, an interactive mapping frame2420, a data selection frame2425, a swine plants (e.g., packaging, processing, rendering, slaughter) frame2430, a swine movements frame2435and a lab results frame2440. The system and incident frame2405includes a system tab2406and an incident tab2408. The interactive mapping frame2420graphically displays selected data on a map and includes a set of map navigational tools2422and a set of analytical tools2424. The interactive mapping frame2420shows the locations of all premises and plants (e.g., packaging, processing, rendering, slaughter) within the given geographic area. Premises and plants without any outbreak incidents are shown as aqua colored circles, whereas premises and plants with outbreak incidents are shown as yellow colored circles. The data selection frame2425includes an agencies tab2450, a links tab2455and a calculators tab2460. As shown, the calculators tab2460provides access to various data sets, such as region of interest2462, labs with test results2464, labs with no test results2466, all premises testing positive2468, all premises testing negative2470, movement backward traceability2472, movement forward traceability2474, bovine premises2476, and porcine premises2478.

Turning now toFIG. 25, illustrated is a screen shot of an embodiment of a region of interest dashboard created from the day-to-day animal health management dashboard2400ofFIG. 24by selecting a first region of interest2480within the data selection frame2425. In response, the interactive mapping frame2420shows the locations of all premises and plants within the first region of interest2480. Referring now toFIG. 26, illustrated is a screen shot of an embodiment of a disease status and traceability dashboard with the first region of interest2480ofFIG. 25by selecting the all premises testing negative2470within the data selection frame2425to graphically display the data within interactive mapping frame2420. The system can also integrate veterinary diagnostic laboratory test reports to support traceability efforts through the integration of premises location, movement, and disease status data.

Supporting continuity of business operations during a disease outbreak requires traceability analysis for determining source/exposure, surveillance (testing/observation) for determining status, and permit issuing for animal/product movement. Examples of Information Dashboard Frameworks (“IDFs”) illustrating Business Continuity are set forth below.

Turning now toFIG. 27, illustrated is a screen shot of an embodiment of a day-to-day animal health management dashboard2700. The dashboard2700includes a system and incident frame2701, a map shapes frame2702, an interactive mapping frame2703, a data selection frame2704, a production frame2705, a permits frame2706, and a lab results frame2707. The system and incident frame2701includes a system tab2708and an incident tab2709. The interactive mapping frame2703graphically displays selected data on a map and includes a set of map navigational tools2710and a set of analytical tools2711. The interactive mapping frame2703shows the locations of all premises and plants (e.g., packaging, processing, rendering, slaughter) within the given geographic area. Premises and plants with bovine only are shown as green colored circles, porcine only as blue circles and combined bovine and porcine as purple circles. The data selection frame2704includes an agencies tab2712, a links tab2713and a calculators tab2714. As shown, the calculators tab2714provides access to various data sets such as a region of interest2715, labs with test results2716, labs with no test results2717, all premises testing positive2718, all premises testing negative2719, movement backward traceability (where did the animals come from)2720, movement forward traceability (where did the animals go)2721, bovine premises2722, porcine premises2723, and bovine porcine combined premises2724.

Turning now toFIG. 28, illustrated is a screen shot of an embodiment of a region of interest dashboard created from the day-to-day animal health management dashboard2700ofFIG. 27by zooming in on a selected area. In response, the interactive mapping frame2703shows the locations of all premises and plants within the selected area. Referring now toFIG. 29, illustrated is a screen shot of an embodiment of an animal movement permits dashboard showing permits and animal movement over a period of time by selecting the porcine premises2723within the data selection frame2704. In response, the interactive mapping frame2703shows all porcine permits going into a selected county over the last12months (yellow lines and highlighted states). The present invention is not limited to use of circles or lines in various colors to represent the relevant data or status. In other embodiments, different types of graphical objects and/or colors may be used to represent the relevant data or status.

Turning now toFIG. 30, illustrated is a screen shot of an embodiment of another animal movement permits dashboard created from the animal movement permits dashboard ofFIG. 29by zooming in on a selected area within the region of interest. In response, the interactive mapping frame2703shows the locations of all premises and plants within the selected county and details the permit destinations (yellow lines).

Turning now toFIG. 31, illustrated is a screen shot of an embodiment of a permits summary dashboard. The permits summary dashboard includes a system and incident frame3101, a total permits by state frame3130(line graph), a detailed data frame3131, a permit totals by animal type frame3132(line graph), a permit animal counts by animal type frame3133(line graph), a bovine permits total frame3134(bar graph), a bovine head counts frame3135(bar graph), a porcine permits total frame3136(bar graph), and a porcine head counts frame3137(bar graph). The system and incident frame3101includes a system tab3108and an incident tab3109.

Turning now toFIG. 32, illustrated is a flow chart of an embodiment of a method of managing diagnostic information from one or more veterinary diagnostic laboratories. In the illustrated embodiment, the animal related data is veterinary diagnostic laboratory related data. With continuing reference to preceding FIGUREs, the method begins at a start step3210. At a step3220, the method invokes selected applications and modules ofFIG. 3. For instance, the method invokes: (a) the data selection module308within the data management application302; (b) the laboratory resource allocation module322and the laboratory throughput analysis module324within the data analysis application304; and (c) the application control module328, the geospatial mapping module330, the data display module332and the macro or scripting module334within the user interface application306.

The data management application302can be used to automatically collect the animal related data from the data source(s)104and/or or third party data source(s) and service(s)110, or integrate additional animal related data from laboratories into the one or more sets of animal related data. The data management application302can be used to protect confidential information obtained from the data source(s)104and/or third party data source(s) and service(s)110, and disclose such confidential information in an emergency. The data management application302or data analysis application304can automatically create and send one or more notifications to client device(s)108communicably coupled to the computing device(s)102. The data management application302can also receive additional animal related data from client device(s)108associated with laboratories communicably coupled to the computing device(s)102, assign one or more permissions to the animal related data based on one or more data sharing agreements associated with the data source(s)104and/or third party data source(s) and service(s)110, transform or restrict the selected portions of the assessed animal related data based on the one or more permissions assigned to the animal related data, aggregate the assessed animal related data to provide the selected portions of the assessed animal related data without disclosing any confidential information, limit (or dynamically restrict) access to the animal related data based on a security level of a user, the display or a client device, or dynamically adjust access to the animal related data based on specific circumstances such as an emergency level or basis.

The data analysis application304provides users with a set of manual and automated tools for analyzing data from the data source(s)104and/or third party data source(s) and service(s)110via the data management application302. The user interface application306provides a user friendly and user customizable interface to access, view, analyze, manipulate and otherwise use data from the data source(s)104and/or third party data source(s) and service(s)110via the data management application302and the data analysis application304.

A set of application control functions from the application control module328is displayed, by the computing device(s)102, in a user interface of a display in a step3230. The application control module328provides a set of application control functions that allow a user to add, remove, change and manipulate frames displayed on the computing device(s)102, and to execute, control and terminate the modules and applications. The set of application control functions enable customization and control of the user interface, and execution of the data selection module308, the laboratory resource allocation module322, the laboratory throughput analysis module324, the geospatial mapping module330, the data display module332and the macro or scripting module334. The user interface application306can also provide a data query tool, a map annotation tool, a calculator, one or more analytical tools, the macro or scripting module334to create user-defined modules, etc.

In a decisional step3240, a user input is received, by the computing device(s)102, in the user interface of the display that indicates activation of at least one of the modules. If the user input indicates activation of the data selection module308, the method obtains the one or more sets of animal related data from laboratories and causes the one or more computing device(s)102to display the one or more sets of animal related data in a first frame of the user interface in a step3250. The animal related data can also include animal health data, movement data, key location data, surveillance data, diagnostic testing data, GIS layer data, personnel data, resource data, phylogenetic data, other data, or a combination thereof. The third-party data source(s) and service(s)110can include governmental databases, laboratory databases, animal processing databases, animal producer databases, veterinarian databases, commercial databases, data feeds, sensor data, other sources, or a combination thereof.

If the user input indicates activation of the laboratory resource allocation module322, one or more sets of animal related data from laboratories are analyzed based on one or more resource allocation parameters in a step3255. The laboratory resource allocation module322can determine an allocation of resources using one or more resource allocation parameters, and project an allocation of resources based on one or more actual or planned emergency scenarios.

If the user input indicates activation of the laboratory throughput analysis module324, one or more sets of animal related data from laboratories are analyzed based on one or more laboratory throughput parameters in a step3260. The laboratory throughput analysis module324can track one or more costs associated with the one or more laboratories, and perform a comparative analysis of the one or more laboratories.

If the user input indicates activation of the geospatial mapping module330, the method causes a map with one or more graphical objects representing the one or more sets of animal related data from laboratories, analyzed animal related data from the laboratory resource allocation module322, or analyzed animal related data from the laboratory throughput analysis module324to be displayed, by the one or more computing devices in a second frame of the user interface in a step or module3265. The geospatial mapping module330displays a frame in the user interface that include a map with one or more graphical objects representing various data (e.g., type of animal, stage of production, disease status, etc.). The geospatial mapping module330also provides various controls that allow a user to annotate, change and manipulate content displayed within the frame (e.g., map data overlaid with data from the other source(s)).

If the user input indicates activation of the data display module332, the method causes a listing, a chart or a graph of the one or more sets of animal related data from laboratories, analyzed animal related data from the laboratory resource allocation module322, or analyzed animal related data from the laboratory throughput analysis module324to be displayed, by the one or more computing device(s)102in a third frame of the user interface in a step3270. The data display module332displays a frame in the user interface that provides a listing, a chart or a graph of data.

If the user input indicates activation of the macro or scripting module334, the method allows the user to create, modify and save customized modules, which provide custom functions, analysis or displays in a step3275. Thereafter, the method ends in a step3290. The method may also start again or return to one of the earlier steps depending on the application. The method is not limited to the foregoing steps or the specific order of steps described.

An example based on the aforementioned method will now be described. The LCEM is a web-based tool to help increase the nation's capability to prepare and respond to a high consequence animal emerging and/or zoonotic disease. This system allows for the automated determination of diagnostic testing capacity estimates, supply and equipment usage, personnel requirements, and any process limitations for individual laboratories and laboratory networks using an underlying model for analysis. Generated data can be used to improve knowledge of individual laboratories and laboratory networks diagnostic testing capacity, support decisions as part of a laboratory network activation plan, assist in the prioritization of additional resources needed, and serve as a tool for managing a large number of diagnostic tests simultaneously. The system facilitates the distribution of samples to promote efficient diagnostic testing by allowing the laboratory network program office insight into laboratory capacity prior to and during an outbreak and promoting more efficient communications between the laboratories and laboratory network coordinator.

Turning now toFIG. 33, illustrated is a screen shot of an embodiment of a veterinary diagnostic laboratory capacity estimation dashboard3300. The veterinary diagnostic laboratory capacity estimation dashboard3300is divided into multiple frames including a system frame3301(minimized), a scenarios frame3302, a throughput frame3303(bar graph), a data summary frame3304, a supplies frame3305(bar graph), an equipment space3306(bar graph) and a skills frame3308. Aggregated analysis of different inputs will facilitate evaluation of the rate limiting process for laboratory capacity.

Turning now toFIG. 34, illustrated is a flow diagram of an embodiment of a method to operable in a biological environment. The method begins at a start step or module3405. At a step or module3410, the method identifies a parameter related to animal management (e.g., a syndrome, animal health, animal production) for species (e.g., disparate species) in the biological environment. The parameter may include, without limitation, an animal diagnostic laboratory throughput parameter (e.g., a veterinary diagnostic laboratory throughput parameter), an animal resource allocation parameter (e.g., a veterinary diagnostic laboratory resource allocation parameter), an animal production parameter, an animal health monitoring parameter, an animal tracking parameter, an animal disease identification parameter, a phylogenetic analysis parameter, and an animal related emergency response parameter/dynamically changing situation.

The method then receives and encodes animal related data from different sources into a common format at a step or module3415. The animal related data may include, without limitation, animal health data, movement data, key location data, surveillance data, diagnostic testing data, geographic information system layer data, personnel data, resource data, phylogenetic data and laboratory data, and may be directed at the individual or group level. The conversion or translation associated with encoding the animal related data may be from a proprietary format to a common format. In a related embodiment, the common format allows the data to be employable across various types of software and/or devices. A unique identifier can also be assigned to the animal related data to associate the data to other data such as a species type. The unique identifier may also be relationally associated with an identifier assigned to the animal related data by the corresponding data source (e.g. producer, veterinarian or health authority). The animal related data may also be anonymized to sanitize sensitive information, but sufficient to enable some type of analysis thereof.

At a step or module3420, the method filters the animal related data from the different sources based on the parameter. The filtering of the animal related data from the different sources may be based on time, space and context associated with the parameter, and/or based on a guard band or pre-determined baseline associated with the parameter. Thus, certain animal related data may be flagged as anomalous and/or discarded if it falls outside of a particular expectation. Conversely, the animal related data that is filtered out may be retained within the memory114for other purposes. The method then aggregates the animal related data from the different sources about the parameter of the species at a step or module3425.

At a step or module3430, the method identifies a baseline for the parameter. It should be noted that the baseline may be a time series model calculated over time and may fluctuate based on the animal related data. At a decisional step or module3435, the method tests the baseline to determine the validity thereof. The method may identify patterns in the animal related data to test the baseline. If the baseline is invalid or should be updated, the method modifies the baseline in a step or module3440, and then proceeds to a step or module3445. If the baseline is valid, then the method proceeds to the step or module3445and correlates the animal related data against the baseline to obtain correlated data.

Thereafter, the method analyzes the correlated data to assess the animal management at a step or module3450. The method may assess the animal management by predicting future outcomes associated with the animal management, by identifying a trend associated with the animal management, and/or by identifying an anomaly or confirming a normalcy associated with the animal management. The assessment may be performed in real-time, or delayed to account for incubation time. At a step or module3455, the method presents the animal related data in a first frame of a display and presents the correlated data in a second frame of the display. The animal related data and correlated data may be presented as a geographical map, a graphical representation, a chart or a list, and dynamically formatted for presentation on the display.

The method then tracks movement of the species associated with the animal related data at a step or module3460. As an example, the animals may be tagged with a sensor (such as a radio frequency identification tag) that communicates with a reader and server to provide location information to a system performing the method. Of course, the method may not only track, but in addition to or in lieu of incorporate data about the movement of the species. At a step or module3465, the method assigns permissions (e.g., credential based on predefined rules) to the animal related data based on the source and restricts access to at least portions of the animal related data based on the permissions (e.g., county (or coarser)-level permissions), which may be dynamically adjusted (e.g., full or unlimited access) based on specific circumstances, teaming arrangement, investigation, or on a situational basis such as an emergency level or basis, at a step or module3470. The permissions may also be applied to access to the correlated data with the data granularity being commensurate with the permission levels. The permissions may be allocated by an external agency or service, and verified and assigned in accordance with the computing device(s)102.

The method also provides a notification to a device such as a client device(s)108based on the correlated data at a step or module3475. The notification may include an alert to a device such as a client device(s)108if the animal related data substantially deviates from the baseline by, for instance, a guard band. A notification may also be provided if the animal related data is outside a predetermined set or threshold, which may affect an accuracy of the correlated data. At a decisional step or module3480, it is determined if the method should be repeated. If the method should be repeated, then the method returns to the start step or module3405, other the methods concludes at an end step or module3485.

Turning now toFIG. 35, illustrated is a screen shot of an embodiment of a phylogenetic analysis dashboard3500divided into multiple frames. The frames include a system and lab results frame3505, a user entered genetic sequence frame3510, a NCBI frame3515, an alignment frame3520, a UniProt frame3525, a dendrogram frame3530, and a time navigator frame3535. The system and lab results3505include a system tab3506and lab results tab3508. An interactive mapping frame3550graphically displays selected data on a map and includes a set of map navigational tools3553and a set of analytical tools3556. The interactive mapping frame3550shows the specific geospatial locations of identified sequences color-coded based on their linkage and position within the dendrogram3530. As shown, the lab results tab3508provides the ability to query and display test procedures and results of interest from diagnostic laboratories. The user entered genetic sequences tab3510provides the ability to import and display a set of user-defined sequences. The NCBI tab3515provides the ability to query and display sequences from the NCBI reference library. The alignment tab3520provides a display of the aligned set of sequences. The UniProt tab3525provides the ability to query and display sequences from the UniProt reference library. The dendrogram tab3530provides a graphical tree-based visualization of the set of sequences based upon their relationship to one another. The time navigator tab3535provides a tool to temporally filter and navigate the selected and displayed data across the system. The phylogenetic analysis tool integrates genetic sequence data from various sources (e.g., laboratories, end-user, reference libraries) and allows for time/space/visual analysis of the sequences of interest. It allows a user to visualize, analyze, and understand how similar or divergent the disease or condition is over time and space at a genetic level. It builds off of many foundational methodologies from the bio-informatics area.

Various embodiments of the present invention provide a system and computerized methods and applications that allow a diverse set of disparate data to be automatically collected and accessed in near real-time or real-time, brokered based on defined data sharing agreements, transformed (e.g., processed, aggregated, synthesized, integrated, correlated, fused, etc.) as needed, and presented to end-users in a customizable and interactive fashion. The system provides an extensible and modular framework that allows a variety of data and tools, and various underlying technologies to be integrated in a distributed yet seamless fashion. The system can be fully distributed integrating both fixed and mobile elements. The system allows producers, state animal health officials, federal regulatory agencies and others to better understand a situation (shared situational awareness) and to more effectively collaborate, coordinate, communicate and make decisions. The system supports both routine production scenarios and the full emergency cycle (i.e., planning, preparation, early detection, mitigation, response, management and recovery) for emerging disease indications and/or outbreak events. The method and applications, when executed, analyze and display one or more sets of animal related data, monitor the health of one or more animal herds, manage a health of one or more animal herds, or manage one or more animal laboratories.

One embodiment of the present invention is a computer-implemented method of analyzing and displaying one or more sets of animal related data operable on one or more computing devices. A data management application, data analysis application and user interface application executable by the one or more computing devices communicably coupled to one or more data sources are provided. The data management application, data analysis application and user interface application are interconnected. A data selection module is provided within the data management application. An animal tracking module, animal disease detection module and animal event response module are provided within the data analysis application. An application control module, geospatial mapping module and data display module are provided within the user interface application. The one or more computing devices display a set of application control functions from the application control module in a user interface of a display that enable customization and control of the user interface, and execution of the data selection module, animal tracking module, animal disease detection module, animal event response module, geospatial mapping module, phylogenetics analysis module, and data display module. The display is communicatively coupled to at least one of the one or more computing devices. The one or more computing devices receive a user input in the user interface of the display that indicates activation of the data selection module, animal tracking module, animal disease detection module, animal event response module, geospatial mapping module or data display module.

Whenever the user input indicates activation of the data selection module, the data selection module obtains the one or more sets of animal related data and causes the one or more computing devices to display the one or more sets of animal related data in a first frame of the user interface. The animal related data may be automatically collected from the one or more data sources, and additional animal related data from one or more sensors or one or more client devices can be integrated with the one or more sets of animal related data. The one or more sets of animal related data includes an animal health data, a movement data, a key location data, a surveillance data, a diagnostic testing data, a GIS layer data, a personnel data, a resource data, a laboratory data or a combination thereof, phylogenetics data, and a third party source thereof includes governmental databases, laboratory databases, animal processing databases, animal producer databases, veterinarian databases, commercial databases, data feeds, sensor data or a combination thereof.

Whenever the user input indicates activation of the animal tracking module, the one or more sets of animal related data are correlated with a geospatial data using the animal tracking module. The animal tracking module may also track a movement of one or more animals over time, and/or track one or more permits associated with one or more animals over time and determine a status of the one or more permits.

Whenever the user input indicates activation of the animal disease detection module, the one or more sets of animal related data are analyzed based on one or more disease identification parameters using the animal disease detection module. The disease identification parameters may include a baseline interval to estimate expected data behavior, a current event of potentially anomalous data and a guard band between the baseline interval and the current event to avoid contamination of the baseline interval by an outbreak signal. The animal disease detection module may adjust the disease identification parameters to detect a specific disease or a new strain of the specific disease, and set one or more trigger conditions that provide an alert or notification of the specific disease. The disease identification parameters may also be adjusted to compensate for seasonality. The animal disease detection module may detect one or more anomalies within the one or more sets of animal related data, predict a spread of a disease based on a statistical analysis, detect one or more symptom or disease related patterns or trends, and/or identify a potential threat to human public health. The animal disease detection module may include one or more phylogenetic analysis tools.

Whenever the user input indicates activation of the animal event response module, the one or more sets of animal related data are analyzed based on one or more animal related emergency response parameters. The animal event response module may determine a quarantine zone or a buffer zone, determine an allocation of resources (e.g., based on an animal vaccination scenario, an animal sampling scenario and an animal slaughter scenario), plan a response to an actual or simulated animal disease outbreak and/or implement a response to an actual animal disease outbreak.

Whenever the user input indicates activation of the geospatial mapping module, the geospatial mapping module causes the one or more computing devices display a map with one or more graphical objects representing the one or more sets of animal related data, correlated data from the animal tracking module, analyzed data from the animal disease detection module or analyzed data from the animal event response module in a second frame of the user interface. Whenever the user input indicates activation of the data display module, the data display modules causes the one or more computing devices display a listing, a chart or a graph of the one or more sets of animal related data, correlated data from the animal tracking module, analyzed data from the animal disease detection module or analyzed data from the animal event response module in a third frame of the user interface.

The method may also automatically create and send one or more notifications to one or more client devices communicably coupled to the one or more computing devices. The method may assign one or more permissions to the one or more sets of animal related data based on one or more data sharing agreements associated with the one or more data sources, and transform or restrict selected portions of the assessed one or more sets of animal related data based on one or more permissions assigned to the one or more sets of animal related data. The method may also assess the one or more sets of animal related data, and transform the assessed one or more sets of animal related data by aggregating the assessed one or more sets of animal related data to provide selected portions of the assessed one or more sets of animal related data without disclosing any confidential information. The method may limit access to the one or more sets of animal related data based on a security level of a user, the display or a client device. The method may also dynamically adjust access to the one or more sets of animal related data based on specific circumstances such as an emergency level or basis. The method may also provide a data query tool, a map annotation tool, a calculator, one or more analytical tools and a macro or scripting module to create a user-defined module.

Another embodiment of the present invention is a computer-implemented method of monitoring the health of one or more animal herds operable on one or more computing devices. A data management application, data analysis application and user interface application executable by the one or more computing devices communicably coupled to one or more data sources are provided. The data management application, data analysis application and user interface application are interconnected. A data selection module is provided within the data management application. An animal health monitoring module and an animal disease detection module are provided within the data analysis application. An application control module, a geospatial mapping module and a data display module are provided within the user interface application. The one or more computing devices display a set of application control functions from the application control module in a user interface of a display that enable customization and control of the user interface, and execution of the data selection module, animal health monitoring module, animal disease detection module, geospatial mapping module and data display module. The display is communicatively coupled to at least one of the one or more computing devices. The one or more computing devices receive a user input in the user interface of the display that indicates activation of the data selection module, animal health monitoring module, animal disease detection module, geospatial mapping module or data display module.

Whenever the user input indicates activation of the data selection module, the data selection module obtains the one or more sets of animal related data and causes the one or more computing devices to display the one or more sets of animal related data in a first frame of the user interface. The animal related data may be automatically collected from the one or more data sources, and additional animal related data from one or more sensors or one or more client devices can be integrated with the one or more sets of animal related data. The one or more sets of animal related data includes an animal health data, a movement data, a key location data, a surveillance data, a diagnostic testing data, a GIS layer data, a personnel data, a resource allocation data, a veterinary diagnostic laboratory data or a combination thereof, phylogenetics data, and a third party source thereof includes governmental databases, laboratory databases, animal processing databases, animal producer databases, veterinarian databases, commercial databases, data feeds, sensor data or a combination thereof.

Whenever the user input indicates activation of the animal health monitoring module, the one or more sets of animal related data are analyzed for any changes in the health of the one or more animal herds using the animal health monitoring module. The animal health monitoring module may also track a movement of one or more animals over time, and/or track one or more permits associated with one or more animals over time and determine a status of the one or more permits. The animal health monitoring module may also request an additional testing of one or more animals, and/or request an animal health data associated with one or more animals.

Whenever the user input indicates activation of the animal disease detection module, the one or more sets of animal related data are analyzed based on one or more disease identification parameters using the animal disease detection module. The disease identification parameters may include a baseline interval to estimate expected data behavior, a current event of potentially anomalous data and a guard band between the baseline interval and the current event to avoid contamination of the baseline interval by an outbreak signal. The animal disease detection module may provide an alert or warning not to move one or more animals to a specific geographic area, adjust the disease identification parameters to detect a specific disease or a new strain of the specific disease, and set one or more trigger conditions that provide an alert or notification of the specific disease. The disease identification parameters may also be adjusted to compensate for seasonality. The animal disease detection module may detect one or more anomalies within the one or more sets of animal related data, predict a spread of a disease based on a statistical analysis, detect one or more symptom or disease related patterns or trends, and/or identify a potential threat to human public health. The animal disease detection module may include one or more phylogenetic analysis tools.

Whenever the user input indicates activation of the geospatial mapping module, the geospatial mapping modules causes a map to be displayed with one or more graphical objects representing the one or more sets of animal related data, analyzed data from the animal health monitoring module, or analyzed data from the animal disease detection module in a second frame of the user interface. Whenever the user input indicates activation of the data display module, the data display module causes a listing, a chart or a graph of the one or more sets of animal related data, analyzed data from the animal health monitoring module, or analyzed data from the animal disease detection module to be displayed by the one or more computing devices in a third frame of the user interface.

The method may also automatically create and send one or more notifications to one or more client devices communicably coupled to the one or more computing devices. The method may assign one or more permissions to the one or more sets of animal related data based on one or more data sharing agreements associated with the one or more data sources, and transform or restrict selected portions of the assessed one or more sets of animal related data based on one or more permissions assigned to the one or more sets of animal related data. The method may also assess the one or more sets of animal related data, and transform the assessed one or more sets of animal related data by aggregating the assessed one or more sets of animal related data to provide selected portions of the assessed one or more sets of animal related data without disclosing any confidential information. The method may limit access to the one or more sets of animal related data based on a security level of a user, the display or a client device. The method may also dynamically adjust access to the one or more sets of animal related data based on specific circumstances such as an emergency level or basis. The method may also provide a data query tool, a map annotation tool, a calculator, one or more analytical tools and a macro or scripting module to create a user-defined module.

Yet another embodiment of the present invention is a computer-implemented method of managing the health of one or more animal herds operable on one or more computing devices. A data management application, data analysis application and user interface application executable by the one or more computing devices communicably coupled to one or more data sources are provided. The data management application, data analysis application and user interface application are interconnected. A data selection module is provided within the data management application. An animal health monitoring module and an animal production management module are provided within the data analysis application. An application control module, a geospatial mapping module and a data display module are provided within the user interface application. The one or more computing devices display, in a user interface of a display that is communicatively coupled to at least one of the one or more computing devices, a set of application control functions from the application control module that enable customization and control of the user interface, and execution of the data selection module, animal health monitoring module, animal production management module, geospatial mapping module and data display module. The one or more computing devices receive a user input in the user interface of the display that indicates activation of the data selection module, animal health monitoring module, animal production management module, geospatial mapping module or data display module.

Whenever the user input indicates activation of the data selection module, the data selection module obtains the one or more sets of animal related data and causes the one or more computing devices to display the one or more sets of animal related data in a first frame of the user interface. The animal related data may be automatically collected from the one or more data sources, and additional animal related data from one or more sensors or one or more client devices can be integrated with the one or more sets of animal related data. The one or more sets of animal related data includes an animal health data, a movement data, a key location data, a surveillance data, a diagnostic testing data, a GIS layer data, a personnel data, a resource allocation data, a veterinary diagnostic laboratory data or a combination thereof, and a third party source thereof includes governmental databases, laboratory databases, animal processing databases, animal producer databases, veterinarian databases, commercial databases, data feeds, sensor data or a combination thereof.

Whenever the user input indicates activation of the animal health monitoring module, the one or more sets of animal related data are analyzed for any changes in the health of the one or more animal herds using the animal health monitoring module. The animal health monitoring module may also track a movement of one or more animals over time, and/or track one or more permits associated with one or more animals over time and determine a status of the one or more permits. The animal health monitoring module may also request an additional testing of one or more animals, and/or request an animal health data associated with one or more animals. The animal health monitoring module may provide an alert or warning not to move one or more animals to a specific geographic area.

Whenever the user input indicates activation of the animal production management module, the one or more sets of animal related data are analyzed based on one or more animal production parameters using the animal production management module. The animal production management module may adjust one or more preplanned animal movements, share an animal test data between two or more animal producers, and share premises disease status for a particular pathogen of interest between two or more animal producers, adjust an animal diet based on the analyzed data, and/or adjust an animal vaccination schedule based on the analyzed data. The animal production management module may include one or more phylogenetic analysis tools.

Whenever the user input indicates activation of the geospatial mapping module, the geospatial mapping module causes a map to be displayed by the one more computing devices with one or more graphical objects representing the one or more sets of animal related data, analyzed data from the animal health monitoring module, or analyzed data from the animal production management module. Whenever the user input indicates activation of the data display module, the data display module causes the one or more computing devices to display in a third frame of the user interface, a listing, a chart or a graph of the one or more sets of animal related data, analyzed data from the animal health monitoring module, or analyzed data from the animal production management module.

The method may also automatically create and send one or more notifications to one or more client devices communicably coupled to the one or more computing devices. The method may assign one or more permissions to the one or more sets of animal related data based on one or more data sharing agreements associated with the one or more data sources, and transform or restrict selected portions of the assessed one or more sets of animal related data based on one or more permissions assigned to the one or more sets of animal related data. The method may also assess the one or more sets of animal related data, and transform the assessed one or more sets of animal related data by aggregating the assessed one or more sets of animal related data to provide selected portions of the assessed one or more sets of animal related data without disclosing any confidential information. The method may limit access to the one or more sets of animal related data based on a security level of a user, the display or a client device. The method may also dynamically adjust access to the one or more sets of animal related data based on specific circumstances such as an emergency level or basis. The method may also provide a data query tool, a map annotation tool, a calculator, one or more analytical tools and a macro or scripting module to create a user-defined module.

Another embodiment of the present invention is a computer-implemented method of managing one or more animal laboratories operable on one or more computing devices. A data management application, data analysis application and user interface application executable by the one or more computing devices communicably coupled to one or more data sources are provided. The data management application, data analysis application and user interface application are interconnected. A data selection module is provided within the data management application. A laboratory resource allocation module and a laboratory throughput analysis module are provided within the data analysis application. An application control module, a geospatial mapping module and a data display module are provided within the user interface application. The one or more computing devices display a set of application control functions from the application control module in a user interface of a display that enable customization and control of the user interface, and execution of the data selection module, laboratory resource allocation module, laboratory throughput analysis module, geospatial mapping module and data display module. The display is communicatively coupled to at least one of the one or more computing devices. The one or more computing devices receive in the user interface of the display, a user input that indicates activation of the data selection module, laboratory resource allocation module, laboratory throughput analysis module, geospatial mapping module or data display module.

Whenever the user input indicates activation of the data selection module, the data selection module obtains the one or more sets of animal related data (e.g., laboratory data) and causes the one or more computing devices to display the one or more sets of laboratory data in a first frame of the user interface. The animal related data may be automatically collected from the one or more data sources, and additional animal related data from one or more sensors or one or more client devices can be integrated with the one or more sets of animal related data. The one or more sets of animal related data includes an animal health data, a movement data, a key location data, a surveillance data, a diagnostic testing data, a GIS layer data, a personnel data, a resource allocation data, a laboratory data or a combination thereof, and a third party source thereof includes governmental databases, laboratory databases, animal processing databases, animal producer databases, veterinarian databases, commercial databases, data feeds, sensor data or a combination thereof.

Whenever the user input indicates activation of the laboratory resource allocation module, the one or more sets of laboratory data are analyzed based on one or more resource allocation parameters using the laboratory resource allocation module. The laboratory resource allocation module also determines an allocation of resources, and/or project a required allocation of resources based on one or more actual or planned emergency scenarios.

Whenever the user input indicates activation of the laboratory throughput analysis module, the one or more sets of laboratory data are analyzed based on one or more laboratory throughput parameters using the laboratory throughput analysis module. The laboratory throughput analysis module may also track one or more costs associated with the one or more laboratories, and/or perform a comparative analysis of the one or more laboratories.

Whenever the user input indicates activation of the geospatial mapping module, the geospatial mapping module causes a map with one or more graphical objects representing the one or more sets of laboratory data, analyzed data from the laboratory resource allocation module, or analyzed data from the laboratory throughput analysis module to be displayed by the one or more computing devices in a second frame of the user interface. Whenever the user input indicates activation of the data display module, the data display module causes a listing, a chart or a graph of the one or more sets of laboratory data, analyzed data from the laboratory resource allocation module, or analyzed data from the laboratory throughput analysis module to be displayed by the one or more computing devices in a third frame of the user interface.

The method may also automatically create and send one or more notifications to one or more client devices communicably coupled to the one or more computing devices. The method may assign one or more permissions to the one or more sets of animal related data based on one or more data sharing agreements associated with the one or more data sources, and transform or restrict selected portions of the assessed one or more sets of animal related data based on one or more permissions assigned to the one or more sets of animal related data. The method may also assess the one or more sets of animal related data, and transform the assessed one or more sets of animal related data by aggregating the assessed one or more sets of animal related data to provide selected portions of the assessed one or more sets of animal related data without disclosing any confidential information. The method may limit access to the one or more sets of animal related data based on a security level of a user, the display or a client device. The method may also dynamically adjust access to the one or more sets of animal related data based on specific circumstances such as an emergency level or basis. The method may also provide a data query tool, a map annotation tool, a calculator, one or more analytical tools and a macro or scripting module to create a user-defined module.

The foregoing computerized methods can be implemented with a system that includes one or more data sources, and one or more computing devices communicably coupled to the one or more data sources. The one or more computing devices include a communications interface, a memory, a display and one or more processors communicably coupled to the communications interface, memory and display. The one or more processors are programmed to execute the computer program embodied on a non-transitory computer readable medium.

For a better understanding of correlation, see U.S. Pat. No. 8,948,279, entitled “Interrogator and Interrogation System Employing the same,” by Volpi, et al., issued Feb. 3, 2015. For a better understanding of scan statistics and models for surveillance and early outbreak detection, see “Biosurveillance Applying Scan Statistics with Multiple, Disparate Data Sources,” by Burkom, Journal of Urban Health: Bulletin of the New York Academy of Medicine, Volume 80, No. 2, Supplement 1, 2003; “A Statistical Algorithm for the Early Detection of Outbreaks of Infectious Disease,” by Farrington, et al., Journal of the Royal Statistical Society, 159, Part 3, pp. 547-563, 1996; “A Simulation Model for Assessing Aberration Detection Methods used in Public Health Surveillance for Systems with Limited Baselines,” by Hutwagner, et al., Statistics in Medicine, 24:543-550, 2005; “A Space-Time Permutation Scan Statistic for Disease Outbreak Detection,” by Kulldorff, et al., PLoS Medicine, Volume 2, Issue 3, e59, pp. 216-224, March 2005; “Evaluating Statistical Methods for Syndromic Surveillance,” by Stoto, et al., Statistical Methods in Counterterrorism, pp. 141-172,; and “Evaluation of Sliding Baseline Methods for Spatial Estimation for Cluster Detection in the Biosurveillance System,” by Xing, et al., International Journal of Health Geographics, 8:45, 2009.

As described above, the exemplary embodiment provides both a method and corresponding apparatus consisting of various modules providing functionality for performing the steps of the method. The modules may be implemented as hardware (embodied in one or more chips including an integrated circuit such as an application specific integrated circuit), or may be implemented as software or firmware for execution by a computer processor. In particular, in the case of firmware or software, the exemplary embodiment can be provided as a computer program product including a computer readable storage structure embodying computer program code (i.e., software or firmware) thereon for execution by the computer processor. Many of the features and functions discussed above can be implemented in software, hardware, or firmware, or a combination thereof. Also, many of the features, functions, and steps of operating the same may be reordered, omitted, added, etc., and still fall within the broad scope of the various embodiments.

The techniques shown in the FIGUREs illustrated herein can be implemented using code and data stored and executed on one or more electronic devices. Such electronic devices store and communicate (internally and/or with other electronic devices over a network) code and data using non-transitory tangible machine readable medium (e.g., magnetic disks; optical disks; read only memory; flash memory devices; phase-change memory) and transitory machine-readable communication medium (e.g., electrical, optical, acoustical or other forms of propagated signals such as carrier waves, infrared signals, digital signals, etc.).