Systems and methods for risk assessment for zoonotic disease in animal populations

Abstract

Systems and methods for assessing risk for zoonotic disease, including salmonella, amongst an animal population at a production facility. A user can provide data in response to a plurality of data entry fields that can, at least partially, pertain to a procedure, operation, and / or equipment at the production facility. For each data entry field, the data provided by the user can be assigned a value. The value can correspond to predetermined value of a predetermined response that is identified as corresponding to the user inputted data. The assigned value can be adjusted by a weighted factor, which may correspond to a predicted impact the actions or information reflected by the user inputted data may have on the prevention of zoonotic disease. The assigned and / or adjusted values can be compiled to generate a risk assessment score, which can be used to determine a food safety index score and / or food safety plan.

Description

SYSTEMS AND METHODS FOR RISK ASSESSMENT FOR ZOONOTIC DISEASE IN ANIMAL POPULATIONSFIELD OF THE DISCLOSURE

[0001] The present disclosure generally relates to systems and methods for assessing the risk for zoonotic disease, and, more specifically, to systems and methods for assessing the risk of salmonella positivity in poultry.BACKGROUND

[0002] Foodborne illnesses can be acquired in a variety of manners, including from the consumption of animal products, such as meat products. Zoonotic diseases have the potential to develop and spread at each stage of the meat product production, and moreover, from at least the cultivation of the associated animal to the final consumer. Worldwide, nearly half a million people die each year from foodborne illnesses. Currently, poultry is a primary source for salmonellosis in humans.

[0003] Various factors can contribute to the development and spread of zoonotic diseases, including pathogens, amongst collections or herds of animals, including poultry flocks that provide sources for meat products. For example, discrepancies in the enforcement of regulatory standards can adversely impact the prevention and containment of at least pathogens, including salmonella, among collections of animals. The intensity of animal husbandry can also contribute to the prevalence of diseases amongst those animals. Further, certain climates and environments at which animals are cultivated can be favorable to the development and spread of at least certain types of pathogens.

[0004] Additionally, various factors associated with the processing, handling, and storage of meat products can also contribute to the development and spread of such diseases. For example, foodborne diseases can develop or spread as a consequence of use of unclean water for food product cleaning and processing. Additionally, deficiencies with respect to refrigeration or freezing of meat products, including during handling and transport, can at least be a contributory factor to the development and spread of foodborne diseases, including foodborne pathogens, such as salmonella.

[0005] Various efforts have been taken to at least attempt to mitigate such diseases. Yet, because of the myriad of potential solutions, it is often difficult for producers and others within the production supply chain to develop a succinct and efficient strategy for the reduction in such diseases, including salmonella positivity.SUMMARY

[0006] The present disclosure may comprise one or more of the following features and combinations thereof.

[0007] In one embodiment of the present disclosure, a system is provided for assessing a risk for zoonotic disease amongst an animal population at a production facility. The system can include one or more databases having a plurality of data entry fields, the plurality of data entry fields including at least one data entry field pertaining to a procedure, an operation, or a piece of equipment at the production facility. The system can also include at least one processor and a memory device coupled to the at least one processor. The memory device can include instructions that, when executed by the at least one processor, can cause the system to communicate the plurality of data entry fields to a user of the system, and receive a signal corresponding to a data inputted by the user in responding to each data entry field of the plurality of data entry fields. Additionally, for each of the plurality of data entry fields, a value can be assigned for the data inputted by the user, and a determination can be made as to whether to modify the value for any of the data inputted by the user by a weighted factor to generate a weighted value. Additionally, the system can generate a risk assessment score using either the value or the weighted value associated with the data inputted for each of the plurality of data entry fields, the risk assessment score corresponding to an estimation of the risk for the zoonotic disease amongst the animal population at the production facility.

[0008] In another embodiment, a method is provided for assessing a risk for zoonotic disease amongst an animal population at a production facility. The method can include communicating a first plurality of data entry fields of a first data field query category to a user, the first plurality of data entry fields including at least one data entry field pertaining to a procedure, operation, or equipment at the production facility. Further, a first data set inputted by the user can be received, the first data set comprising data provided by the user in response to each data entry field of the first plurality of data entry fields. Additionally, for each data entry field of the first plurality of data entry fields, a first value can be assigned for the data inputted by the user, and a determination can be made as to whether to modify the first value for any of the data inputted by the user by a first weighted factor to generate a first weighted value. The method can also include generating a risk assessment score using at least either the first value or the first weighted value associated with the data inputted for each of the first plurality of data entry fields, the risk assessment score corresponding to an estimation of the risk for the zoonotic disease amongst the animal population at the production facility.

[0009] These and other features of the present disclosure will become more apparent from the following description of the illustrative embodiments.BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The invention described herein is illustrated by way of example and not by way of limitation in the accompanying figures. For simplicity and clarity of illustration, elements illustrated in the figures are not necessarily drawn to scale. For example, the dimensions of some elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference labels have been repeated among the figures to indicate corresponding or analogous elements.

[0011] Figure 1 illustrates a simplified block diagram of an exemplary risk assessment computing device for a food safety protection system.

[0012] Figure 2 illustrates a simplified block diagram of an exemplary food safety protection system.

[0013] Figure 3 illustrates a simplified flowchart of an exemplary method for assessing risk, and providing associated mitigation strategies, for reducing at least certain types of foodbome diseases.

[0014] Figure 4 illustrates a simplified block representation of a design for an exemplary food safety protection system.

[0015] Figure 5 illustrates an exemplary screen shot of a template table listing templates and associated categories or lists for use with the exemplary food safety protection system.

[0016] Figure 6 illustrates an exemplary screen shot of an Data Request or Add New Template page that can be utilized to add templates to the exemplary template table shown in Figure 5.

[0017] Figure 7 illustrates a simplified block representation of an overview diagram for a system that can be utilized with the embodiments discussed herein.

[0018] Figure 8 illustrates a simplified block diagram of an architecture for an exemplary system that can be utilized with various embodiments discussed herein.

[0019] Figure 9 illustrates a simplified flowchart of an exemplary method for use with embodiments of the exemplary food safety protection system disclosed herein.

[0020] Corresponding reference numerals are used to indicate corresponding parts throughout the several views.DETAILED DESCRIPTION

[0021] The following Detailed Description refers to accompanying drawings to illustrate exemplary embodiments consistent with the present disclosure. References in the Detailed Description to “one exemplary embodiment,” an “exemplary embodiment,” an “example exemplary embodiment,” etc., indicate the exemplary embodiment described may include a particular feature, structure, or characteristic, but every exemplary embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same exemplary embodiment. Further, when a particular feature, structure, or characteristic may be described in connection with an exemplary embodiment, it is within the knowledge of those skilled in the art(s) to effect such feature, structure, or characteristic in connection with other exemplary embodiments whether or not explicitly described.

[0022] The exemplary embodiments described herein are provided for illustrative purposes, and are not limiting. Other exemplary embodiments are possible, and modifications may be made to the exemplary embodiments within the spirit and scope of the present disclosure. Therefore, the Detailed Description is not meant to limit the present disclosure. Rather, the scope of the present disclosure is defined only in accordance with the following claims and their equivalents.

[0023] Embodiments of the present disclosure may be implemented in hardware, firmware, software, or any combination thereof. Embodiments of the present disclosure may also be implemented as instructions applied by a machine-readable medium, which may be read and executed by one or more processors. A machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computing device). For example, a machine-readable medium may include read only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices, electrical optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.), and others. Further firmware, software routines, and instructions may be described herein as performing certain actions. However, it should be appreciated that such descriptions are merely for convenience and that such actions in fact result from computing devices, processors, controllers, or other devices executing the firmware, software, routines, instructions, etc.

[0024] For purposes of this discussion, each of the various components discussed may be considered a module, and the term “module” shall be understood to include at least onesoftware, firmware, and hardware (such as one or more circuit, microchip, or device, or any combination thereof), and any combination thereof. In addition, it will be understood that each module may include one, or more than one, component within an actual device, and each component that forms a part of the described module may function either cooperatively or independently from any other component forming a part of the module. Conversely, multiple modules described herein may represent a single component within an actual device. Further, components within a module may be in a single device or distributed among multiple devices in a wired or wireless manner.

[0025] The following Detailed Description of the exemplary embodiments will so fully reveal the general nature of the present disclosure that others can, by applying knowledge of those skilled in the relevant art(s), readily modify and / or adapt for various applications such exemplary embodiments, without undue experimentation, without departing from the spirit and scope of the present disclosure. Therefore, such adaptations and modifications are intended to be within the meaning and plurality of equivalents of the exemplary embodiments based upon the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by those skilled in the relevant art(s) in light of the teachings herein.

[0026] Embodiments of the present disclosure generally relate to a system for the reduction of salmonella positivity from a poultry production process, among other animals and zoonotic diseases. The system can comprise a risk mitigation software application that can be applicable to meat production facilities, including form example, poultry production facilities, such as, but not limited to, feed mills, hatcheries, production facilities (e.g. farms), and processing facilities (e.g. slaughterhouses), each of which can be collectively generally referred to herein as a production facility. The application can comprises a number of curated question sets, also referred to as data entry fields that can enable assessment of one or more poultry production facilities by a user of the software application. In certain embodiments, the software application can comprise one or more risk assessment models or algorithms (collectively referred to herein as model) that generates a score for a food safety index, the food safety index being an objective measure of the propensity for a pathogen, such as, for example, salmonella positivity, to arise within a particular production facility, including a poultry production facility.

[0027] In some embodiments, the software application can be hosted on a field assessment computing device, such as, for example, a mobile data entry device. In otherembodiments, a user can remotely interact with the software application, or otherwise provide information for use by the risk assessment model, via use of the field assessment computing device while within the production facility. Additionally, according to certain embodiments, the risk assessment model can generate a risk-prioritized food safety plan. In illustrative embodiments, the food safety plan can include an itemized listing of mitigation strategies. Implementing the listed mitigation strategies at the associated production facility can result in reduced presence of zoonotic diseases, including, for example, reduced salmonella positivity.

[0028] Also disclosed are methods for reducing zoonotic diseases, including salmonella positivity, at a production facility. The method can comprise launching a food safety program application on a field assessment computing device, such as, for example, a mobile device, and conducting an assessment of the poultry production facility according to a series of prompts provided by the application. The method can also include answering a series of questions provided by the application, and generating either, or both, a food safety plan and / or a food safety index, wherein implementation of the food safety plan or appreciation of the food safety index can result in reducing or preventing a presence of zoonotic diseases at the production facility, including, reduced salmonella positivity at a poultry production facility.

[0029] In illustrative embodiments, a risk assessment model is provided for assessing the propensity of zoonotic diseases, including salmonella positivity, at a production facility. The risk assessment model can comprise a first set of data entry fields, a series of weighting factors applicable to the first set of data entry fields, and a data field for reception of a food safety index score. The risk assessment model can also calculate the score within the a food safety index data field by comparing responses, including, data provided in first set of data entry fields with a set of predefined values, scoring the data according to the comparison, applying the series of weighting factors, and depositing the value in the data field for reception of the food safety index.

[0030] In some embodiments, the food safety index score is a number between 30 and 100. Additionally, the data entry fields can comprise, for example, between 10 and 500 data entry fields, among other numbers of data entry fields. Further, according to some embodiments, the model includes at least a second set of data entry fields. In another embodiment, the risk assessment model comprises a second series of weighting factors different from the series of weighting factors. In other embodiments, the risk assessment model comprises a food safety plan data series. In one embodiment, the risk assessment model provides data to the food safety plan data series in response to data within the first set of data entry fields in a manner reflecting the series of weighting factors.

[0031] Figure 1 illustrates a simplified block diagram of an exemplary risk assessment computing device 102 for a food safety protection system 100. A variety of different types of devices can be utilized as the risk assessment computing device 102, including, but not limited to mobile devices, smart phones, tablets, and computers, among other devices. According to the illustrated embodiment, the risk assessment computing device 102 has a controller 104 that includes one or more processors 106 and a memory device 108. The processor 106 can follow instructions, including control instructions, contained with, or are part of, the memory device 108, including, for example, a non-transitory machine-readable medium.

[0032] The risk assessment computing device 102 can also include a communication unit 110 that can communicate information to, as well as receive information from, other devices. The communication unit 110 can be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and / or a combination thereof. According to certain embodiments, the communication unit 110 can comprise a transceiver that is configured to wirelessly communicate information, as well as receive information, that may pertain to, or assist, in determining either or both a risk assessment for zoonotic diseases, including salmonella, and associated mitigation strategies.

[0033] The risk assessment computing device 102 can also include a risk assessment unit 112 that can include a processing unit that follows instructions contained on a non- transitory computer-readable or machine-readable medium. According to certain embodiments, the risk assessment unit 112 can be part of the controller 104, or can utilize the processor 106 or memory device 108 of the controller 104. Additionally, the risk assessment unit 112 can have, or utilize, one or more risk assessment models that can utilize a variety of different types of information to determine, including estimate, a risk estimation relating to zoonotic disease(s). Moreover, the risk estimation provided by the risk assessment model can relate to an assessment of a risk(s) of the development of one or more zoonotic diseases among one or more types of animals at one or more production facilities. According to certain embodiments, the risk estimation can correspond to the risk(s) for one or more zoonotic diseases at a particular meat production facility. Additionally, according to certain embodiments, the risk estimation can pertain to a specific type of zoonotic disease, such as, for example, salmonella. Further, according to certain embodiments, the risk estimation can pertain to a specific type of animal associated with the production facility, such as, for example, poultry. Thus, for example, according to certain embodiments, the risk estimation provided by the risk assessment model can pertain to a risk for salmonella positivity among a collection(s) of poultry at an associated production facility.

[0034] As discussed below, according to certain embodiments, the risk assessment model can generate a food safety index score 114 that can provide an objective measure of the propensity for a pathogen, such as, for example, salmonella positivity, to arise within a particular production facility(ies), including a poultry production facility. Additionally, the risk assessment model can generate a food safety plan 116 that can include one or more, including a listing of, mitigation strategies that can be customized to a particular production facility, and which can be based on a variety of inputted and / or historical information. As also discussed below, according to certain embodiments, the risk assessment model can be a selflearning model(s).

[0035] The risk assessment computing device 102 can include, or have access to via the communication unit 110, a data entry field database 118 that can include a plurality of data entry fields for one or more data field query categories. Each data field query category can correspond to a different topic, grouping, or category pertaining to processes, operations, handling, physical and / or organization infrastructure, and / or management, as well as combinations thereof, among other categories, relating to at least the cultivation, production, storage, and / or handling of meat products and the associated animals. The data entry fields can be particular questions within each data field query category for which a user is to provide a data, such as, for example, data in the form of an answer or information for the data entry field. Moreover, the data entry fields can comprise a number of curated question sets that can enable the risk assessment model to generate an assessment of one or more poultry production facilities. According to certain embodiments, the data entry fields can comprise, for example, between 10 and 500 data entry fields, among other numbers of data entry fields.

[0036] For example, according to certain embodiments, a data field query category can relate to an analysis of internal protection within a production facility, including associated operating procedures and safeguards, against one or more zoonotic diseases, including salmonella. Thus, for example, data entry fields within the internal protection data field query category can generally relate to management of protections, including, for example, the measures taken to prevent contamination from entering into the production facility via incoming air. With respect to production for meat products containing poultry, another data entry field for the internal protection data field query category can inquire as to whether the facility is a single stage or multi-stage hatchery. With respect to meat production relating to at least poultry, other data entry fields for an internal protection - management data field query category can, for example, include one or more of the following: how are the eggs transferred and handled internally during the hatchery process; what degree of attention is paid to thehygiene and maintenance of suction cups; measures to prevent contamination from incoming air; whether there is a decline in positive air pressure directed from the setter area to the hatcher area to the chick take off area and finally to the chick dispatch area; how are tools and equipment are used inside the hatchery; the kind of barriers are placed at entrances where people come back to the building from waste storage; how the salmonella status of the hatchery evaluated; the salmonella status of the hatchery (documentation); whether samples are taken from all areas in the hatchery; whether the plenum is sampled; whether salmonella was recently detected on box liners or dead / culled on arrival chicks; corrective measures in place if salmonella is detected either in the hatchery or in chicks; whether culled and exploded eggs are documented and microbiologically monitored; the tidiness and cleanliness of the service / utility rooms; whether the hatchery has SOPs for cleaning and disinfection of all rooms, setters, hatchers, equipment, trays, baskets, trolleys (daily, weekly, according to cycles); whether the hatchery has SOPs for the hygiene of hatchery employees (cleaning and disinfection of hands, boots, change of boots, clothes); whether there are regular trainings for employees to understand and act in accordance with the SOPs; how hatcher trays and chicken and boxes cleaned and disinfected; how chick boxes are (returning from farm) cleaned and disinfected; how egg trays and trolleys are cleaned and disinfected; whether there is a cleaning and disinfection register signed by the responsible person after every accomplished action; the surface quality of the hatchery house: porosity, joints; whether there is microbiological effectiveness control of disinfection on equipment and surfaces; the actions taken if exploders (bangers) exceed the normal value; whether there is a documentation of temperature flow within the hatchery; how climate parameters are documented, controlled and adjusted (temperature / humidity); whether the ventilation system is maintained regularly, including cleaned and serviced; and / or how often the functionality of the spray nozzles checked, recorded and maintained, among other data entry fields.

[0037] Additionally, or alternatively, a data field query category can relate to vaccination procedures, which may also be grouped in a data field query category relating to management and quality processes. Data entry fields relating to such a data field query category can pertain to the type, timing, storage, and usage of vaccinations, among other issues. For example, according to certain embodiments, a data entry field can relate to vaccination procedures, such as, for example, whether vaccines are stored in a refrigerator that is dedicated to vaccines. Other data entry fields relating to a vaccination data field query category can include, for example, one or more, if not all, of the following: whether there are different rooms for preparation of in ovo vaccine and spray or subcutaneous vaccine; whether the vaccinepreparation area clean; whether vial disposal follows guidelines; the kind of barriers between the vaccination zones regarding the flow of people; whether birds are placed in well illuminated and well ventilated areas; whether the sprayer is properly maintained and SOPs are in place and recorded ; if the in ovo vaccine machine is properly maintained and SOPs are in place and recorded; whether the sprayer is cleaned and disinfected with appropriate products and SOPs are in place and are recorded; and / or whether the in ovo vaccine machine is cleaned and disinfected with proper products, and SOPs are in place (for AM and PM cycles) and are recorded, among other data entry fields.

[0038] Additionally, the data field query categories can provide different categories, or, alternatively, be organized as subcategories for a data field query category. For example, a data field query category can generally relate to analysis of external protection, which can relate to processes, equipment, or procedures, among other subjects, relating to activities outside of the production facility. For example, a data field query category, or subset of an external protection data field query category, can relate to documentation. Such a data field query category, or subcategory, can be referred to herein as external protection - documentation, and can have data entry fields that, for example, pertain to: whether there are SOPs regarding hygiene, health, and safety issues to be signed by visitors; health monitoring for hatchery staff; and / or documentation of rodent control / protection measures, among other data entry fields.

[0039] Another data field query category, or subcategory relating to external protection can relate to dirty areas. Data entry fields for the external protection - dirty area category or subcategory can, with respect to at least meat products containing poultry, relate to, for example, one or more of the following: whether there are any standard operating procedures (SOP) or regime for hatching eggs from salmonella positive breeder flocks; whether there is a documentation of each delivery of eggs (quantity, quality, source); information regarding entrance control for visitors and vehicles; truck and company vehicle cleaning and disinfection (interior and exterior); disinfection of all trucks entering the hatchery premises; disinfection of cars and motorbikes belonging to staff and / or visitors; integrity of fencing and access control at the entrance to the hatchery; distance from hatchery to other hatcheries, feed mills, poultry farms, other livestock farms, rendering plants, biogas plants or swine farms (other possible sources for salmonella infection); whether other livestock species, including poultry, kept on the hatchery premises or at private homes of employees; whether there wild birds or signs of wild bird activity in the area surrounding the hatchery; roads and paths on the hatchery premises; tidiness and vegetation around the hatchery building; monitoring and control ofrodents; how hatchery waste collected and stored; location of waste storage containers; and / or hygiene and pest control at waste storage areas.

[0040] Additionally, another data field query category, or subcategory relating to external protection can relate to separation between dirty and clean areas. Data entry fields for the external protection - separation between dirty and clean area category or subcategory can, with respect to at least meat products containing poultry, relate to, for example, one or more of the following: whether there are separate entrances / exits for eggs, chicks and personnel; whether egg trays from the farm enter the hatchery; the effectiveness of cleaning and disinfection of egg trollies and trays; how movement of staff within the hatchery work flow is controlled; how movement of staff is regulated within the hatchery; and / or how biosecurity of visitors is handled in terms of (1) shower in and out, (2) hatchery-provided PPE, and (3) oneway movement through hatchery (from egg receiving, handling and storage to setting to chick vaccination and chick delivery area only), among data entry fields.

[0041] Another data field query category, or subcategory relating to external protection can relate to breeder farm management. Data entry fields for the external protection - breeder farm management category or subcategory can, with respect to at least meat products containing poultry, relate to, for example, one or more of the following: the handling of floor eggs and dirty eggs handled at the hatchery; the consequences of a salmonella-positive breeding flock; information flow between breeder flock and hatchery; salmonella status and others health problems of egg-supplying parent flocks; information flow regarding health problems between breeder flock and hatchery; sorting of eggs on farm level disinfection or fumigation of eggs; whether disinfection or fumigation of eggs is carried out according to the SOP; type of truck / lorry for egg transport; and / or use of egg transporting truck / lorry.

[0042] The data entry fields can be presented to the user of the risk assessment computing device 102, such as, for example, on an I / O device 120, including, but not limited to, a display, monitor, touch screen, and / or speaker. The user can enter data, such as, for example, information or responses, to the data entry fields via use of an I / O device 120, including, for example, via a keyboard, touch screen, joystick, or mouse, among other I / O devices 120. Further, according to certain embodiments, the user may verbally provide data for the data entry fields via an I / O device 120 in the form of a microphone.

[0043] The risk assessment computing device 102 can also include, or have access to via the communication unit 110, a weighting factor database 122. The weighting factor database 122 can provide weighting factors or values applicable to the data entry fields and / or the data provided by the user to a data entry field. Moreover, according to certainembodiments, certain data entry fields or collections of data entry fields can be weighted, such as, for example, a multiplier, so as to have a higher or lower value relative to other data entry fields. Additionally, the data provided by the user for the data entry fields of one data field query category can have a different weight than data provided by the user for data entry fields of at least one other data field query category. Additionally, to the extent data field query categories may have at least some, or overlapping, data entry fields, the value of the data provided for such data entry fields can be assigned different weights among the different data field query categories.

[0044] According to certain embodiments, the weighted factor for one or more data entry fields can be assigned one or more predetermined values. Moreover, according to certain embodiments, the weighted factor, if any, for a data entry field can be a predetermined value that is generally static in that the value assigned to the weighed factor remains constant. Alternatively, according to certain embodiments, the weighted factor is dynamic in that the value of the weighted factor, if any, can vary. According to such an embodiment, the risk assessment model can be adapted to assign a value of the weighted factor to the data entry based on the data provided by the user to the data entry field. Further, in such an embodiment, the assigned value of the weighted factor can be within a range of values. Thus, for example, for a particular data entry field, data provided by the user that is indicative of a process, procedure, policy, etc. that is more favorable to a prevention of an occurrence of a zoonotic disease may be assigned a higher valued weighted factor than data provided by the user that is less favorable to the prevention of the occurrence of a zoonotic disease. Additionally, according to certain embodiments in which the risk assessment model is self- learning, the value for weighted factors can change as the risk assessment model acquires more information and / or adjusts in view of information regarding actual outcomes with respect to actual occurrences of development, or non-development, of zoonotic diseases, including salmonella.

[0045] The risk assessment computing device 102 can also include, or have access to via the communication unit 110, a mitigation strategy database 124. The mitigation strategy database 124 can compile a collection of mitigation strategies, including, for example, mitigation strategies relating to therapeutics, vaccinations, filtration, sterilization, biosecurity, and cleaning, amongst other mitigation strategies. The risk assessment model can be adapted to determine, based at least in part, on the data provided by the user to the data entry fields, and / or based on a score generated from the data provided for the data entry fields, a food safety plan 116 to be utilized for the production facility. Thus, the food safety plan 116 can include selected mitigation strategies, as well as a plan for implementing of the selected mitigationstrategies. Thus, as the food safety plan 116 can be based at least in part to the data provided by the user to the data entry fields, the generated food safety plan 116 can be customized to a particular production facility.

[0046] Additionally, or alternatively, the risk assessment computing device 102 can also include, or have access to via the communication unit 110, a neural network 126 such that the risk assessment model can be a self-learning model. The neural network 126 can include a one or more databases that can receive neural network training data corresponding to a plurality of characteristics for a plurality of production facilities and recorded occurrences and / or nonoccurrences of zoonotic disease at each of the plurality of production facilities. For example, according to certain embodiments, the neural network 126 can include an outcome history log 128 that can maintain not only a record relating to a risk assessment determination made using at least the risk assessment model, but also information that may indicate the accuracy of that risk assessment determination. Thus, for example, the outcome history log 128 can include information relating to past predictions provided by the risk assessment model for production facilities, and whether those production facilities actually did, or did not, subsequently experience an occurrence of zoonotic disease, such as, for example, salmonella. Thus, the neural network 126 can, in connection with machine based learning of the neural network 126, analyze the historical information regarding actual outcomes with respect to the occurrence, or non-occurrence, of zoonotic disease, responses to data entry fields, and values of weighted factors for relationships that can be used to adjust, and improve, the accuracy of the risk assessment model. The neural network 126 can apply such data and information to one or more of the risk assessment models, such as but not limited to a multilayer perceptron (MLP), a restricted Boltzmann Machine (RBM), a convolution neural network (CNN), and / or any other neural network model that will be apparent to those skilled in the relevant art(s) without departing from the spirit and scope of the disclosure.

[0047] Figure 2 illustrates a simplified block diagram of an exemplary food safety protection system 100'. The food safety protection system 100' can be configured to accommodate remote access to a risk assessment server 130 by a risk assessment computing device 102'. Thus, for example, the risk assessment computing device 102' can utilize the features of the remote risk assessment server 130 when the risk assessment computing device 102' is located at a particular production facility. The risk assessment computing device 102' can include a controller 104' that includes at least one processor 106' and a memory device 108', a communication unit 110', and an I / O device 120' that can each be similar to thecorresponding controller 104, processor(s) 106, memory device(s) 108, communication unit 110, and an I / O device 120 discussed above with respect to Figure 1.

[0048] In an embodiment, multiple modules may be implemented on the risk assessment server 130. Such a risk assessment server 130 may include software, firmware, hardware or a combination thereof. Software may include one or more applications on an operating system. Hardware can include, but is not limited to, a processor, a memory, and / or graphical user interface display. The risk assessment server 130 can include the risk assessment unit 112 having one or more risk assessment models, the risk assessment unit 1 12 and risk assessment model having features that are at least similar to the corresponding features discussed above with respect to the embodiment shown in Figure 1. Thus, with respect to the embodiment shown in Figure 2, the risk assessment model can generate either or both a food safety index score 114 and / or a food safety plan 1 16, as discussed above.

[0049] The risk assessment server 130 can be operated using a controller 132 having at least one processor 134 and associated memory device(s) 136 that are dedicated to either the risk assessment server 130 or are part of another component of the food safety protection system 100'. Additionally, the risk assessment server 130 can include, or be communicatively coupled to, the data entry field database 118, weighting factor database 122, and mitigation safety database 124, each having features similar to those discussed above with respect to Figure 1.

[0050] Additionally, the risk assessment server 130 can include, or be communicatively coupled to a neural network 126. Thus, similar to the embodiment discussed above with respect to Figure 1 , according to certain embodiments, the risk assessment model for the embodiment shown in Figure 2 can, according to certain embodiments, be self-learning.

[0051] According to the illustrated embodiment, the risk assessment computing device 102' can communicate with the risk assessment server 130 via a network 138. The network 138 can include one or more networks, such as the Internet. In some embodiments of the present disclosure, the network 138 can include one or more wide area networks (WAN) or local area networks (LAN). Further, the network 138 can utilize one or more network technologies such as Ethernet, Fast Ethernet, Gigabit Ethernet, virtual private network (VPN), remote VPN access, a variant of IEEE 802.11 standard such as Wi-Fi, and the like. Communication over the network 138 can take place using one or more network communication protocols including reliable streaming protocols such as transmission control protocol (TCP). Further, according to certain embodiments, communications with the risk assessment server 130 can occur via a web interface and / or any other type of interface that willbe apparent from those skilled in the relevant art(s) without departing from the spirit and scope of the present disclosure. These examples are illustrative and not intended to limit the present disclosure. The risk assessment computing device 102' can interface with the risk assessment server 130 via network 138 through an application programming interface (API), web interface and / or any other type of interface that will be apparent from those skilled in the relevant art(s) without departing from the spirit and scope of the present disclosure. These examples are illustrative and not intended to limit the present disclosure.

[0052] Figure 3 illustrates a simplified flowchart of an exemplary method 300 for assessing risk, and providing associated mitigation strategies, for reducing at least certain types of foodbome diseases. The method 300 can be performed by either, or both, the food safety protection systems 100, 100' shown in Figures 1 and 2 in connection with determining a risk assessment for a production facility relating to one or more zoonotic diseases, including salmonella in poultry populations. The exemplary method 300 corresponds to, or is otherwise associated with, performance of the blocks described below in the illustrative sequence of Figure 3. It should be appreciated, however, that the method 300 can be performed in one or more sequences different from the illustrative sequence.

[0053] At block 302, the food safety protection system 100, 100' can receive one or more signals indicating a user engagement with, and / or activation of, the food safety protection system 100, 100', such as, for example via user engagement with the I / O device 120, 120'. Such engagement can include the food safety protection system 100, 100' receiving one or more parameters relating to a particular production facility, including, but not limited to, an identification of the type of production facility, such as, for example, feed mill, hatchery, production facility (e.g. farm), or processing facility (e.g. slaughterhouse). The parameters can also include identification of an animal classification, such as, for example, poultry, and / or an identification of a particular animal type within an animal classification, such as, for example, chickens, ducks, turkey, or geese, among others. Additionally, according to certain embodiments, parameters can include an identification of one or more zoonotic diseases that may be of interest, including a pathogen, such as, for example, salmonella. According to certain embodiments, such parameters can be provide via information from the user, information stored in the memory device 108, 108', 136, and / or be automatically set, such as, for example, set by a default.

[0054] At block 304, the food safety protection system 100, 100' can retrieve one or more data entry fields from a first data field query category for presentation to the user, such as, for example, for presentation via the I / O device 120, 120'. As discussed above, accordingto the illustrated embodiments, such data entry fields can comprise a number of curated question sets that can, based on data provided by a user in responding to the data entry fields, enable the risk assessment model to generate a risk assessment and / or mitigation plan for that production facility. Which particular data field query category is selected for the first data field query category can be based on a variety of different types of criteria. For example, according to certain embodiments, a data field query category, such as, for example, external protection - dirty area, among others, may be preset as the first data field query category. According to other embodiments, the processor 106, 106' or risk assessment unit 112 can determine which data field query category is to serve as the first data field query category based on information provided for the parameters at block 302.

[0055] At block 306, the food safety protection system 100, 100' can receive a signal or other data corresponding to a data provided by the user via the I / O device 120 in response to a data entry field. The food safety protection system 100, 100' can then determine at block 308 as to whether the user is to be prompted to provide data for to any other data entry field from the first data field query category. For example, as discussed above, according to certain embodiments, each data field query category can comprise a plurality or set of data entry fields for which the user is to be prompted to provide data. Thus, with respect to the illustrated example in which the user has provided data in response to a first data entry field, the user can be prompted to provide a data in response to at least a second data entry field, if not other additional data entry fields, from the same first data field query category. Thus, for example, the second data entry field may seek data from the user regarding whether hatchery waste is collected and stored. Thus, blocks 304, 306, and 308 can be repeated until the user has been provided an opportunity to provide data for a plurality, if not all, data entry fields from the first data field query category.

[0056] At block 310, the risk assessment unit 112 can compare, and / or attempt to match, the data provided by the user in the data entry fields of the first data field query category to a plurality of predetermined data information. For each data entry field, the corresponding plurality of predetermined data information can at least attempt to correspond to each potential response or information that can be provided by the data from user. Additionally, each predetermined data information of the plurality of predetermined data information can be assigned a value or score that can, at block 312, be assigned to the particular data provided by the user. Additionally, or alternatively, the data provided by the user can be evaluated and scored by an evaluation by the risk assessment model.

[0057] For each data entry field, the value or score given by the risk assessment model to the data provided by the user can correspond to the effectiveness or benefit the associated act or information being represented by data may provide in preventing the development and / or spread of a zoonotic disease, including, for example, salmonella. Thus, for example, data provided by the user in addressing a data entry field relating to entrance control to the production facility for visitors and vehicles that indicates a relatively high level of control may be assigned a higher score or value than if the provided data indicated little, or no, such control. Thus, the result from the comparison at block 310 of data from the user predetermined data information, can at block 312, result in the risk assessment model assigning or determination a value or score for that data. Further, a recording of the value or score, if any, for the provided data to each data entry field can be maintained by the risk assessment unit 112 or memory device 108, 136 among other components of the food safety protection system 100, 100'.

[0058] At block 314, the risk assessment unit 112 can utilize the weighting factor database 122 to determine what, if any, weighted factor is to be applied to the determined value or score from block 312. For example, some data entry fields may be correspond to actions or information that can be more impactful in terms of preventing the occurrence, and / or containing the spread, of zoonotic disease, including, for example, salmonella. In such instances, a weighting factor(s) can be utilized to account for the relative importance, or nonimportance, of information and / or actions / inactions being maintained or taken by the production facility, as indicated by the data provided by the user to, or in, the data entry fields. Additionally, according to other embodiments, certain data responses, or certain data for collections of selected data entry fields, can be determined to warrant a weighting factor that may increase, or decrease, the value or score for the associated data provided by the user for that data entry field and / or collection of data entry fields.

[0059] While the foregoing example is discussed with respect to use of data entry fields corresponding to a first data field query category, according to certain embodiments, the food safety protection system 100, 100' can utilize a plurality of data field query categories or subcategories. For example, in the illustrated example, the first data field query category was discussed with respect to the category of external protection - dirty area. However, alternatively, or additionally, one or more data field query categories can be utilized, including, but not limited to, the above discussed categories of: external protection - documentation, external protection - breeder farm management, external protection - separation between dirty and clean area, internal protection - management, and / or vaccination procedures -management and quality processes, as well as combinations thereof, among other data field query categories.

[0060] Thus, according to certain embodiments, at block 316, a determination can be made, such as, for example, by a controller 104, 104', 132 as to whether a second data field query category is to be used, among other additional data field query categories. In this example, if a second data field query category is to be used, the method 300 can return to block 304, and data entry fields for that second data field query category can retrieved, the data entry fields for the second data field query category being different than the data entry fields of the first data field query category. The method can then proceed with steps 306 through 312, with the data provided by the user in response to the data entry fields being evaluated and granted a score or weight that may be adjusted via a weighted factor, as discussed above. Further, the values or range of values associated with the predetermined data information for the second data field query category, and / or the associated weighted factors, may, or may not, be the same as that used for the predetermined data information and weighted factors of the first data field query category. Thus, for example, information associated with the data provided by the user in addressing the data entry fields of the first data field query category may be deemed to have a greater, or lesser, impact on the risk for zoonotic disease, including, for example, salmonella, then the data provided by the user in association with the data entry fields for the second data field query category. Thus, such differences in the potential impact data for different data field query categories can have on the risk assessment determination by the risk assessment model can be reflected by the differences in the values or scores, and / or weighted factors for the data field query categories.

[0061] While the foregoing example is discussed with respect to two data field query categories, the method 300 can be utilized with any number of data field query categories. Thus, according to certain embodiments, a determination by a controller 104, 104', 132 at block 316 that another data field query category remains can trigger a repeat of steps 304-314 for that data field query category. However, upon a determination at block 316 that no other data field query categories remain, the method 300 can proceed to block 318, wherein an overall score can be accumulated, such as, for example, via the analytical unit 112 and / or a controller 104, 104', 132. The overall score can be a sum of the scores assigned at either blocks 312 or 314. Moreover the sum can include those scores from block 312 that were not subsequently adjusted at block 314, as well as the scores that were adjusted at block 314 by the weighted factor. Further, according to certain embodiments, the overall score can comprise such values,collectively, that were determined for the data that was provided for each data field query category for all data field categories.

[0062] The overall score determined at block 318 can provide, or, alternatively can be utilized at block 320 to generate, a food safety index score 114. For example, a food safety index can provide a scoring system that provides an indication of different levels of risk for zoonotic disease, or a particular zoonotic disease, such as, for example, salmonella. According to the certain embodiments, each risk level in the food safety index corresponds to a score or range of scores, which, in the illustrated embodiment, can be in the form of a percentage. Thus, according to certain embodiments, the food safety index can comprise two or more risk levels that, collectively, extend between a food safety index of 0% to 100%, each risk level corresponding to a different food index safety score. Thus, for example, according to certain embodiments, the food safety index can have a first level that corresponds to a “highest risk” for zoonotic disease that corresponds to a food index safety percentage range of 0% to up to 60%. Other levels of the food safety index can include: “higher risk (greater than 60% to 65%); “average risk” (66%-75%); “lower risk” (76% to 85%); and lowest risk (greater than 85%). According to the illustrated embodiments, based on the overall values or scores of the user inputted data to the data entry fields, and associated application, if any, of the weighted factors, the risk assessment unit 112, including the risk assessment model, can generate a food safety index score 114 that can be evaluated using the food safety index to determine a corresponding level of risk for the production facility for having a zoonotic disease amongst the associated animal population.

[0063] The food safety index score 114, or associated risk level determined at block 320, can also be used by the risk assessment unit 112, including the risk assessment model, at block 322 to generate a food safety plan 116. The food safety plan 116 can include an itemized listing of mitigation strategies, which can be attained from the mitigation strategy database 124. According to certain embodiments, the food safety plan 116 is customized in that the particular mitigation strategies selected for the food safety plan 116 can be based on either or both the determined food safety index score 114 or associated identified risk level from the food safety index and / or the data provided for one or more of the data entry fields. For example, the risk assessment model can, according to certain embodiments, evaluate the data provided by the user in responding to at least certain data entry fields to identify potential areas of strength and / or weakness in terms of preventing a development of zoonotic disease in deriving the mitigation strategy for the food safety plan 116 for the associated production facility. Additionally, or alternatively, the risk assessment model can, according to certainembodiments, determine a mitigation strategy using the determined food safety index score 114 or associated risk level alone or in combination with other information, including, for example, the parameters provided by the user at block 304. Implementing the mitigation strategies identified by the food safety plan 116 at the production facility can result in a reduced potential for, or presence of, zoonotic diseases, including, for example, reduced salmonella positivity.

[0064] Figure 4 illustrates a simplified block representation of a design for an exemplary food safety protection system 400. The system 400 can be utilized in connection with a food safety program (FSP) software application (referred to in Figure 4 as “FSP_App” 402), that can be used to model and conduct assessments, including in connection with food safety index scores and associated risk modeling discussed above with respect to Figures 1-3. The FSP App 402 can thus be a native iOS software application (app.) on a risk assessment computing device 102, 102', among other devices. Assessment data can be stored in database tables, and the system 400 can utilize a dedicated web service of the system 400 for users to login and download / upload data. Customers, sites, and contacts provided via use of the FSP App 402 will also be mapped and managed via a client information management system (“CIMS”) administrative counsel (Admin Counsel) 408, including via associated account management 410 features provided by, or otherwise accessible by at least use of, the Admin Console 408.

[0065] As illustrated by block 402, a customer or end user can have access to the FSP App. 402. The FSP App. 402 can be stored, for example, on a risk assessment computing device 102, 102'. The system 400 can further include an application programming interface (API) 404, such as, for example, a RESTful API, that can allow the FSP App. 402 to exchange information over the internet with a client information management (CMI) database 406 from a proprietary web service that can be utilized to support the FSP App. 402.

[0066] In the illustrated embodiment, an authentication (“Auth”) API 404a can be used in connection with confirming authorization and authentication of the FSP App. 402, or associated user, that is seeking to attain access to the data and information available in the system 400 via use of the web service. Thus, according to certain embodiments, identification information entered via the FSP App. 402 can be compared with information at, or available to, the food safety program database 406. If the food safety program database 406 is able to authenticate the submitted login information, the database 406 can provide a return token. According to certain embodiments, the return token can be utilized to allow the FSP App. 402to have access to the API 404. Additionally, as discussed below, according to certain embodiments, the token can be utilized in connection with offline use of the FSP App. 402.

[0067] The API 404 can also include a data API 404b that can provide the FSP App. 402 with access to data and data management functions. According to certain embodiments, the data API 404b can be utilized to check an AppID, as well as be involved in the uploading a syncing of data, including data associated with the customer or end user of the FSP App. 402, or associated site, including a facility or farm. The uploaded and synced data can also relate to one or more risk assessments performed via use of the system 400. Additionally, the FSP App. 402 can trigger a synchronization when a user of the FSP App. 402 performs any of the following: refreshes a particular screen seen while using the FSP App. 402, such as, for example, a “My Customers” screen or "My Sites" screen, logs into the FSP App. 402, uses the FSP App. 402 to generate a report, and / or refreshes a listing of previously performed assessments.

[0068] The synchronization status of a customer, sites of the customer, the assessments relating to a customer, and the number of assessments not synced can be displayed, such as, for example, on the risk assessment computing device 102, 102'. The risk assessment computing device 102, 102' can also be used to display a legend describing the meaning of each synchronization status for each applicable screen, including, for example, a status indicating customer, site, or assessment information has not been saved to either, or both, a server or a secure sever of the system 400.

[0069] A web monitoring tool 408, can be utilized to monitor the system 400, including the web service, API 404, and / or the FSP App. 402. Moreover, the web monitoring tool 408 can be used to imitate the operations of the FSP App. 402 so as to ensure the functionality of the web services. For example, the web monitoring tool 408 can be utilized to imitate login by the FSP App. 402 and / or functioning of the API 404, including functioning of the API 400 with respect to the uploading and downloading of data or information.

[0070] The system 400 can also include a client information management system (“CIMS”) Admin Console 408 (“QMS FSP Admin Console”) that can be utilized to support customer, farm, contact, and / or assessment management. According to certain embodiments, the Admin Console 408 can be utilized, managed, or viewed using a computing device having a display such that the below mentioned features, including hierarchal structures and formats can be viewed. Moreover, according to certain embodiments, the Admin Console 408 can allow administrative tasks for the system 400 to be performed by the entity providing the web service, including administrative tasks associated with manage customer accounts.

[0071] According to certain embodiments, upon logging in, the user has the option of using the I / O device 120, 120' of the risk assessment computing device 102, 102' to select a Customer on a “My customer” screen, which can be used to navigate the user to a “My Operation Sites” screen, which can correspond to particular facilities or operations associated with that end user or customer. When a user selects a site, or operation site, on a “My Operation Sites” screen, the user can be navigated to an assessment view or screen where all assessments associated with that site that are being, and / or were, performed via the systems and methods disclosed herein can be displayed. Thus, assessments in progress or have not been completed can be displayed, as well as completed assessments. The user can also be able to resume or delete an in-progress assessment, but may not be able to delete a completed assessment. In at least certain instances, a user may not have the ability to start a new assessment for a site if there is already an in-progress assessment for that same site. Thus, at the assessment view or screen, users can have the ability to: (1) open and view any in-progress or completed assessment; (2) perform a follow up assessment, with such follow up assessments not having limitations on systems or categories, and all assessment questions can be included in a followup assessment; and / or (3) generate a summary or detailed report relating to an assessment(s) or outcome of the assessment(s).

[0072] According to certain embodiments, the Admin Console 408 can be utilized to support data mapping on a server side of the system 400. Further, according to certain embodiments, the Admin Console 408 can be utilized in connection with account mapping 410, including manual account mapping and automatic account mapping. Further, account mapping 410 can be organize or arranged in a variety of manners, including for display on a display of a computing device being used for, or with, the Admin Console 408. For example, according to certain embodiments, such account mapping 410 can be organized or arranged in a multilevel hierarchy structure or format, such as, for example, a two level hierarchy having a customer level, and then, based on the identified customer, a site, location, and / or facility of the identified client level, among others. With respect to manual account mapping, according to certain embodiments, such mapping can account for mapping of unmatched client accounts and master accounts, among other accounts, including, but not limited to, accounts that may be associated with, or migrated (or have data extracted) from, one or other platforms, databases, or web services, among others.

[0073] The Admin Console 408 can be utilized in connection with auto account mapping, or auto mapping approve 412. The auto account mapping 412 can be organized or arranged in a multi-level hierarchy structure or format, such as, for example, a two levelhierarchy having a customer level as a parent level, and then, based on the identified customer, as a child level, a site, location, which can include a facility(ies) of the identified client level (also referred to as a site level), among others. According to such a two level hierarchy format for auto account mapping 412, site level accounts may only be viewed, approved, and / or rejected after the parent, customer level is approved. The auto account mapping 412 can cover mappings relating to unmatched client accounts or FSP clients versus master accounts, and accounts that may be associated with, or migrated or have data extracted from, one or other platforms, databases, or web services versus the master accounts.

[0074] Additionally, the Admin Console 408 can also be utilized in connection with contact farm management 414. Moreover, an entity, including one or more groups, departments, or employees, among others, or an external consultant(s) for that entity, can be associated / mapped to multiple external users, and vice versa. With such an arrangement, according to certain embodiments, the above-mentioned two level hierarchy having a customer level (parent) and site (child) format can be provided such as, for example, on a display. In such an embodiment, if the customer (parent) is selected, all of sites (child) under it can be selected automatically, such as, for example, via automatic checking of an associated checkbox(es). However, if needed, one or more of such checkboxes can be manually unchecked. Further, with such an arrangement, users, including individuals, groups, or departments, from the associated entity or external consultant can be able to view, or have panels displayed, that can be limited to particular customers or customer sites associated with that user plus the mapped customer / sites of an external user, including, for example, a user of the FSP App. 402.

[0075] The Admin Console 408 can also be utilized in connection with data migration 416. For example, a customer or one or more, if not all, of the sites associated with a customer, as well as the associated data, can be transferred from one individual, group, department, or external consultant associated with the entity providing the system 400 or associated services to another individual, group, department, or external consultant associated with that entity. Such data migration 416 can again be selectively utilized on the computing device having access to, or being utilized as / with, the Admin Console 408. Additionally, according to certain embodiments, the system 400, including the Admin Console 408, can further be adapted to provide instructions or tips on a display associated with the computing device utilizing such data migration 416 so as to guide the user in the data migration process, and, more specifically, how to do the data migration.

[0076] The Admin Console 408 can also be utilized in connection with deleting at least part, if not all, assessments associated with a customer, or one or more, if not all, sites associated with that customer (referred to in Figure 4 as “Deleted Assessment” 418). As previously mentioned, such assessment can include at least those discussed above with respect to Figures 1-3, including assessments relating to generation of a food safety index and associated risk determinations. According to certain embodiments, once an assessment is deleted, all users of the Admin Console 408 that previously had access to the deleted assessment(s) may no longer be able to access, retrieve, or otherwise see the deleted assessment(s). The system 400 can also include a TC Table 420, which can be utilized in connection with extracting data from at least the CMI database 406. Moreover, the CMI database 406 can be configured to store data for FSP App. 402. For example, the CMI database 406 can be configured as a backend database that can maintain a variety of information, including, but not limited to, tables, views, stored procedures, and / or functions, among other information.

[0077] As seen in Figure 4, according to certain embodiments, a request that is generated with identified parameters can be communicated from the TC Table 420 to the CMI database 406, with the CMI database 406 returning to the TC Table 420 data responsive to that request. Further, as seen in Figure 5, according to certain embodiments, the identified parameters can be predetermined, and can correspond to a template of the TC Table 420 having particular list or category columns, including, for example: Template Name; Operation Type; Bird Type; Region; Customer; Site Name; Query; Template Owner; Start Date; End Date; and / or, Last Update Date, as well as combinations thereof, among other list columns or associated categories of information. According to such an embodiment, each row in the TC Table 420 can correspond to the template, as identified by the Template Name, that has the particular characteristics identified in one or more, if not all, of the information identified in that row for the corresponding list or category identified in the column of the TC Table 420. The TC Table 420 can also include a column regarding Operation, which can correspond to a particular action that is to be taken with respect to each particular row, or corresponding template, in the TC Table 420. For example, the Operation can correspond to one of a plurality of actions, including, but not limited to edit, delete, or provide a history for the particular template identified in that row.

[0078] With respect to the history option, the history option can relate to the abovediscussed outcome history log 128. Moreover, according to certain embodiments, users of the FSP App. 402 can be able to view on a display a visualized history of food safety index scoresso as to monitor progress over time. For example, according to certain embodiments, a history of food safety index scores can be presented as a simple line graph as a function of time. For example, food safety index scores from one or more previous assessments and the food safety index score for the current assessment can be plotted to provide a food safety index (FSI) trend line graph in an assessment report. Additionally, according to certain embodiments, the FSP App. 402 can locally store a plurality of the most recent assessments based on completion date. For example, the FSP App. 402 can locally store the most recent 5 assessments. If a user needs to view an assessment which is not one of the most recent locally stored assessments, the user shall be able to download another assessment to replace the oldest of the locally stored assessments in online operation mode.

[0079] As seen in Figure 6, the TC Table 420 can be adapted to add new templates, as illustrated by the exemplary Data Request or Add New Template page or screen 420' captured in Figure 6. The information corresponding to each list or category identified in the column of the TC Table 420 can, via use of adding a new template, either be entered or retrieved using data from the CMI database 406. For example, according to certain embodiments, a user of the Admin Console 408 can be able to select the following parameters before generating a dataset: Template Owner; Assessment Date Range (Min - Max); Operation Type; Bird Type; Region (Hub); Customer; Site; and / or Query, among others. According to certain embodiments, the Operation Type can be selected from one or a plurality of options, such as for example, farm, hatchery, feed mill, or processing plant, among others. Additionally, with respect to certain embodiments, the identified Operation Type can impact available options for other lists or categories. For example, if the identified Operation Type is feed mill or processing plant, Bird Type may not be an option, and thus the new templates 420' may hide other otherwise make a selection for Bird Type unavailable. Further, a Query category can be available that can indicate locations or data to review, including, but not limited to, data obtained using the system or FSP App. 402 and / or other merged data. In the example shown in Figure 6, when the “Save” button is clicked on the Data Request or Add New Template page, the system 400 will save the new template and users can see the in the TC Table 420. When the illustrated “Generate” button is clicked on the Data Request or Add New Template page 420', the system 400 can pop-up a message, such as, for example, “The request dataset is being generating and you can download it from the Template List > Task History page after a few minutes”, among other messages.

[0080] Figure 7 illustrates a simplified block representation of an overview diagram for a system 700 that can be utilized with the embodiments discussed herein. Again, the system700 can enable the FSP App 402 to utilize a web service for an end user to login and further upload / download information and data to / from the system 400. Additionally, a backend database, such as that previously discussed with respect to the CMI database 406, can provide tables, views, stored procedures, and / or functions, among other information, that can be implemented to support FSP App. 402.

[0081] The FSP App. 402 can be function both when online or offline, including when not connected to the web service provided by the system 400. In the event of offline operation, a token, such as, for example, a 30-day token can be used for full offline mode use. The token can be renewed automatically once the device using the FSP App. 402, such as a risk assessment computing device 102, 102', among others, has connectivity to the internet. If the account credentials of the end user or customer using the FSP App. 402 are changed, the user shall be prompted to log in. Further, the token can be renewed upon successful log in to the FSP App. 402. Additionally, according to such an embodiment, the end user or customer using the FSP App. 402 can be logged out of the FSP App. 402 when 30-day token expires after no user activity. The system 400 can also be configured to not require the user to log in again in offline mode upon a first successful login and before the token expires. With respect to synching when the offline mode is used, or has been used, if an assessment or report is produced while offline, the assessment or report can be synced to the server as soon as connection is reestablished. Such synching can require that the FSP App. 402 be open and online. The FSP App. 402 can allow the user to download other assessments or reports from the server when connected. Upon such a connection, a newly downloaded assessment or report can replace the oldest of the locally saved assessments or reports.

[0082] Figure 8 illustrates a simplified block diagram of an architecture for a system 800 that can also be utilized with various embodiments discussed herein. A seen, the system 800 can comprise a plurality of layers. In the illustrated embodiment, the system 800 has a three-layer design that includes a presentation layer 802, which can contains the user-oriented functionality responsible for managing user interaction with the system 800. The presentation layer 802 can generally comprise components that provide a common bridge into the core business logic encapsulated in the business layer 804. The business layer 804 can implement the core functionality of the system 800, and can encapsulate relevant business logic. Further, the business layer 804 can generally consist of components, some of which may expose service interfaces that others can use. The system 800 can further include a data layer 806, which can provide access to data hosted within the boundaries of the system 800, and data exposed byother networked systems, such as, for example, accessed through services. The data layer 806 can also expose generic interfaces that the components in the business layer 804 can consume.

[0083] Figure 9 illustrates a simplified flowchart of an exemplary method 900 for use with embodiments of the exemplary food safety protection system disclosed herein. The method 900 can be performed by, or using, any of the embodiments of the food safety protection systems disclosed herein, including in connection with determining a risk assessment for a production facility relating to one or more zoonotic diseases, including salmonella in poultry populations. The exemplary method 900 corresponds to, or is otherwise associated with, performance of the blocks described below in the illustrative sequence of Figure 9. It should be appreciated, however, that the method 900 can be performed in one or more sequences different from the illustrative sequence.

[0084] At block 902, for at least proposes of using the FSP App. 402 and the associated system 400, the customer, or customer account, can be created or added. For example, a username and password can be created, and information regarding associated policies can be provided and accepted by the customer. The type of information provided or used for the adding the new customer can vary, and, moreover, can vary depending on if the customer is being added by the customer or by an employee, representative, or consultant of the entity providing the web service or system 400. For example, when the customer is entering information, the information can pertain to identification, location and contact information, among other information. When an employee or consultant for the entity associated with providing the services associated with the system 400 is adding the customer, information in addition to identification, location and contact information can be created, including information used to identify and describe the customer in terms with formats and / or codes used by the system 400.

[0085] At block 904, information regarding the farm(s), hatchery(s), or operation(s) can be inputted into the system 400. According to certain embodiments, the information provided at block 904 may generally be identification information regarding one or more sites associated with the customer, including location information.

[0086] At block 906, additional information regarding the site information provided at block 904 can be provided or identified. The type of information provided at block 906 may be different than the type of information provided in response to various questions or queries that can be utilized in the above-discussed risk assessments. According to certain embodiments, a user can enter non-scored information for each operation site before starting an assessment on the "Add Operation Site" screen. Further, the particular non-scored questions displayed candepend on the type of operation and bird type (if applicable) selected, among other factors or criteria. Additionally, responding to non-scored questions may be optional, with the exception of for feed mill operations. Thus, according to such an embodiment, with respect to feed mill types of operations, all non-scored questions may require an answer before an assessment of the feed mill can proceed.

[0087] Further, at block 908, vaccination information can be provided that can relate to the animals at the identified site. Such vaccination information or data can, for example, be related to a particular type of vaccination, including, but not limited to, vaccinations relating to salmonella, among other diseases. Such vaccination information can also be treated by the system 400 as assessment level, rather than site level, information or data. According to certain embodiments, a user of the FSP App. 402 can have the ability to enter a variety of information for a plurality of vaccinations, including, for example, up to 6 different vaccines, which can be known as the vaccine program. Such information can include, for example, information that identifies the vaccine manufacturer, vaccination type, vaccine serotype, and / or animal age, among other information.

[0088] For feed mill operation types, there can also be a feed additives information module where a user of the FSP App. 402 can identify, including select from a list, specific feed additives. Such feed additives data can also be assessed by the system 400 as assessment, level rather than site level, information. According to certain embodiments, the FSP App. 402 can be configured to provide for selections from various additives, including, but not limited to, nutritional and anticoccidial additives, among others.

[0089] At block 910, a questionnaire can be completed that can provide information that can be used by the risk assessment model to generate the food safety index score 114. For example, the questionnaire can seek information for the identified site relating to one or more of the following, among other, categories:1) Operation Type a) Farm, b) Hatchery c) Feed Mill d) Processing Plant2) Bird Type (not applicable for Feed Mill or Processing Plant) a) Layer b) Breeder c) Broiler d) Turkey3) Bird Type Subcategories, if applicable, for based on identified Operation Type and Bird Type (e.g., in-lay / in-rear for Layer and Breeder Bird types and Breeder / Meat for turkey)4) Housing System (if applicable) a) Layers: Battery Cages, Enriched Colony, Floor, Voliere or other, Free- range / Organic / B ackyard b) Broiler: Caged, Houses with Litter, Houses with Slats, Free- range / Organic / B ackyard c) Breeders: Caged, Houses with Litter, Houses with Slats, Both Litter and Slats d) Turkeys: Houses with Litter, Houses with slats, Both litter and slats, Free- range / Organic / Backyard

[0090] Additionally, at block 910, photographs can be uploaded, and comments attached to assessment questions, which can be synced to the server and saved in a retrievable location. According to certain embodiments, users can be able to enter comments and attach up to two photos to each assessment question.

[0091] According to certain embodiments, on an assessment screen at which question sections of the questionnaire is displayed for the end user or customer, there can be a filter for users to filter the assessments questions. For example, according to certain embodiments, the filter options can include “Observation”, “All”, and / or “Question” flags. According to such an embodiment, if a user selects "All," then all questions shall be displayed in each section. However, if a user selects "Observation" or "Question", then only questions that have been assigned flag, which may be preset or pre-identified, may be displayed in the assessment. Such a filter however may not be applicable for feed mill operations, and thus, for feed mill assessments, the filter may be hidden.

[0092] The scoring for the assessment, and utilized in connection with generating a food safety index or other risk assessment, can involve a variety of different scoring approaches. For example, according to certain embodiments, each assessment question shall have 3 different answer choices, with each answer choice being associated with a different point value, such as, for example, either be worth 0 points, 3 points, or 5, points, among other point values. Additionally, each question can be assigned a weighting, such as, for example, a weighting of 1 , 2, or 3 that can be applied for calculating the question score for that question or a collection of questions. According to certain embodiments, where applicable, rather than answering a question, a user can have the option of selecting a “Not Applicable” answer option. In such situations, the scoring for that not applicable question can be removed from the total scoring, and not be included in the total number of questions for scoring. Further, for each section of questions, a food safety index score can be calculated by taking the total scored points in the section and dividing by the maximum possible scored points, and displaying a food safety index score as a percentage.

[0093] Any time an external user or customer completes an assessment and the assessment is synced to the server of the system 400, an automated email message can be sent to an employee, department, group, or consultant of the entity providing notification of the completed assessment. The notification can include contact information for the external user or customer, thereby facilitating the occurrence of a follow-up communication with the external user or customer. Further, a new assessment can be accessible by the creator (external user) and automatically mapped to an associated individual / group / department of the entity providing the service after synchronization.

[0094] At block 912, using the results from the assessment, including the associated food safety index, one or more opportunities for improvement of the food safety index can be identified, and a summary report can be generated for consultation with the customer or end user. According to the embodiment shown in Figure 9, three opportunities can be identified, which may, for example, be based on the sections of the assessment that received the lowest food safety index scores and / or areas, as identified by the scores, for largest potential improvement. However, the number of identified opportunities can vary, and can be based on different customers, sites, or situations.

[0095] The summary report can include a variety of information or components. For example, according to certain embodiments, the summary report can include an identification of an overall operation risk level, as well as section risk levels, and the corresponding FSI (food safety Index score) listed. In some instances, the varying risk levels or ranges can also be communicated using different colors or color gradients. The summary report can also include identification information regarding the customer and / or associated site. Additionally, the summary report can also include an executive summary that may be prepared by an employee, representative, to consultant of the entity providing the associated services, which may be manually entered. The summary can also include a description of the assessment methodology and scoring system.

[0096] Additionally, the summary report can include an identification of one or more positive to maintain areas that can indicate areas in which the customer or end user is performing positively. Such identified positive to maintain areas can be accompanied by information regarding the questions from the associated sections of the assessment, the selected answers, the best answers, any attached comments or photos, and background info. As previously mentioned, the summary report can further include an identification of one or more areas for improvement, which may be selected by user, and may include the questions from the identified sections of the assessment, the selected answers, the best answers, any attachedcomments or photos, and background info. According to certain embodiments, after completing an assessment, an employee, representative, or consultant of the entity providing the associated service can provide a prioritize option that can present a plurality of the lowest scoring areas or sections from the assessment. In such a situation, a selection can be manually made as to at least some, or a subset, of the lowest scoring areas from the assessment that are to be identified in the summary report as the areas for improvement.

[0097] Additionally, the summary can include a conclusion, which may be manually entered by the employee, representative, to consultant of the entity providing the associated service. For example, the system can provide a preview screen that can be shown on a display, and which a user, employee, representative, or consultant of the entity providing the service or can use in connection with adding an executive summary and a concluding summary.

[0098] At block 914, a detailed report can be generated for the customer. The detailed report can include, for example, at least some, if not all, the questions used from the assessment, the associated answers, the scores awarded to the answers, and / or an indication of weights, if any, applied to the scores. The detailed report, which, for example, can be viewed at the risk assessment computing device 102, among other devices, can provide an option to view all questions, specific questions, or questions from specific sections of the assessment. The detailed report can further include an identification of determined operation risk level, as well as section risk levels, and the corresponding overall food safety index score and / or from the sections of the assessment. Additionally, the detailed report can include, among other information or sections: a Table of Contents with embedded links to sections in the detailed report; an executive summary; one or more areas identified as positive areas to maintain, which can include the questions, the selected answers, the best answers, any attached comments or photos, and / or background information; one or more identified areas for improvement, which can include some or all of the associated questions, the selected answers, best answers, attached comments or photos, and / or background information; a table with questions and scores; additional assessment data; and / or, a conclusion. According to certain embodiments, an option can be provided to at least temporarily exclude the additional assessment data so as allow at least access to other aspects of the assessment or report.

[0099] At block 916, if an outbreak of a disease has happened, such as, for example, a salmonella outcome, such an outcome can be reported to the system 400 by the customer or end user of the FSP App. 402.[000100] At block 918, follow-up with the customer can occur, which can include creation of an implementation plan based, at least in part, on the results of the implementation.Additionally, at block 918, the progress of the customer can continue to be monitored. Such monitoring can include the FSP App. 402 having the ability to display an internal benchmark for each site (farm / hatchery / feed mill / processing plant). The benchmark can also be updated in real time, as long as device is connected. Notifications can also be sent, such as, for example, via email, to end users or customers when benchmarks change. Such benchmarks can provide the benefit of urging end users and customers to look at the FSP App. 402 and perform regular follow up assessments and seeking consultation to improve their food safety index score. The site level benchmarking ranking logic can also use the latest food safety index score of a target site to compare with the latest food safety index scores of other sites under the same customer. Additionally, the server side can recalculate the benchmarking ranking in the event a new assessment has been completed for the customer, or account mapping / unmapping was recently completed in the system 400. Additionally, once ranking changes are identified, the server side of the system 400 can send email notification to external users. At block 920, assessment data can be extracted and used for custom analytics.[000101] While the disclosure has been illustrated and described in detail in the foregoing drawings and description, the same is to be considered as exemplary and not restrictive in character, it being understood that only illustrative embodiments thereof have been shown and described and that all changes and modifications that come within the spirit of the disclosure are desired to be protected.

Claims

CLAIMS1. A system for assessing a risk for zoonotic disease amongst an animal population at a production facility, the system comprising: one or more databases having a plurality of data entry fields, the plurality of data entry fields including at least one data entry field pertaining to a procedure, an operation, or a piece of equipment at the production facility; at least one processor; a memory device coupled to the at least one processor, the memory device including instructions that, when executed by the at least one processor, cause the system to: communicate the plurality of data entry fields to a user of the system; receive a signal corresponding to a data inputted by the user in responding to each data entry field of the plurality of data entry fields; assign, for each of the plurality of data entry fields, a value for the data inputted by the user; determine whether to modify the value for any of the data inputted by the user by a weighted factor to generate a weighted value; and generate a risk assessment score using either the value or the weighted value associated with the data inputted for each of the plurality of data entry fields, the risk assessment score corresponding to an estimation of the risk for the zoonotic disease amongst the animal population at the production facility.

2. The system of claim 1 , wherein the one or more databases further include, for each data entry field of the plurality of data entry fields, a plurality of predetermined responses, each of the predetermined responses being assigned a predetermined value.

3. The system of claim 2, wherein the memory device includes instructions that, when executed by the at least one processor, further cause the system to: compare, for each data entry field, the data inputted by the user to the plurality of predetermined responses; and identify, from the comparison, a predetermined response of the plurality of predetermined responses as corresponding to the data inputted by the user, wherein the value assigned to the data inputted by the user for the data entry field is the predetermined value of the predetermined response identified from the plurality of predetermined responses.

4. The system of any preceding claim, wherein the risk assessment score is a food safety index score, and wherein the memory device includes instructions that, when executed by the at least one processor, further cause the system to identify a risk level from a plurality of risk levels of a food safety index that corresponds to the food safety index score.

5. The system of any preceding claim, wherein the one or more databases further include a plurality of mitigation strategies, and wherein the memory device includes instructions that, when executed by the at least one processor, further cause the system to select one or more mitigation strategies from the plurality of mitigation strategies for a food safety plan for the production facility.

6. The system of claim 5, wherein the one or more mitigation strategies are selected using at least one of (a) the data inputted by the user for the plurality of data entry fields; and / or (b) the risk assessment score.

7. The system of any preceding claim, wherein the zoonotic disease is salmonella and the animal population is a collection of poultry.

8. The system of any preceding claim, wherein the one or more databases comprises a data entry field database that contains the plurality of data entry fields, a weighting factor database that contains a plurality of weighted factors, and a mitigation strategy database.

9. The system of any preceding claim, wherein the weighted factor is adjustable in response to the data inputted by the user for one or more of the plurality of data entry fields.

10. The system of any preceding claim, wherein the memory device includes instructions that, when executed by the at least one processor, further cause the system to select a value for the weighted factor from a predetermined range of values.

11. The system of any preceding claim, wherein the memory device includes instructions that, when executed by the at least one processor, further cause the system to receive a signal indicating one or more user inputted parameters, the one or more user input parameters providing an identification of one or more of the following: an animal type, a type or production facility, and a particular zoonotic disease.

12. The system of claim 1 1, wherein the memory device includes instructions that, when executed by the at least one processor, further cause the system to select, based on theidentification provided by the one or more user input parameters, the plurality of data entry fields from one or more data field query categories.

13. The system of any preceding claim, further comprising: one or more neural network databases that receive neural network training data corresponding to a plurality of characteristics for a plurality of production facilities and recorded occurrences and / or non-occurrences of zoonotic disease at each of the plurality of production facilities; and a neural network adapted to analyze, for continuous training of the neural network based on machine learning, the neural network training data to improve an accuracy of the risk assessment score generated by the system.

14. A method for assessing a risk for zoonotic disease amongst an animal population at a production facility, the method comprising: communicating a first plurality of data entry fields of a first data field query category to a user, the first plurality of data entry fields including at least one data entry field pertaining to a procedure, operation, or equipment at the production facility; receiving a first data set inputted by the user, the first data set comprising data provided by the user in response to each data entry field of the first plurality of data entry fields; assigning, for each data entry field of the first plurality of data entry fields, a first value for the data inputted by the user; determining whether to modify the first value for any of the data inputted by the user by a first weighted factor to generate a first weighted value; and generating a risk assessment score using at least either the first value or the first weighted value associated with the data inputted for each of the first plurality of data entry fields, the risk assessment score corresponding to an estimation of the risk for the zoonotic disease amongst the animal population at the production facility.

15. The method of claim 14, further comprising: comparing, for each data entry field of the first plurality of data entry fields, the data inputted by the user to a plurality of predetermined responses, each of the plurality of predetermined responses being assigned a first predetermined value; and identifying, from the comparison, a predetermined response of the plurality of predetermined responses as corresponding to the data inputted by the user,wherein assigning the first value comprises assigning the first predetermined value of the predetermined response identified from the plurality of predetermined responses.

16. The method of any one of claims 14 or 15, wherein the risk assessment score is a food safety index score, and wherein the method further includes identifying a risk level from a plurality of risk levels of a food safety index that corresponds to the food safety index score.

17. The method of any one of claims 14 to 16, further including generating, based at least in part on the risk assessment score and / or the first data set, a food safety plan for the production facility, the food safety plan including one or more mitigation strategies.

18. The method of claim 17, further including selecting the one or more mitigation strategies from a plurality of mitigation strategies.

19. The method of any one of claims 14 to 18, wherein the zoonotic disease is salmonella and the animal population is a collection of poultry.

20. The method of any one of claims 14 to 19, further including adjusting the first weighted factor in response to information contained in the first data set.

21. The method of any one of claims 14 to 20, further including selecting a value for the first weighted factor from a predetermined range of values.

22. The method of any one of claims 14 to 21, further comprising: receiving, by one or more neural network databases, neural network training data corresponding to a plurality of characteristics for a plurality of production facilities and recorded occurrences and / or non-occurrences of zoonotic disease at each of the plurality of production facilities; and analyzing, for continuous training of a neural network based on machine learning, the neural network training data to improve an accuracy of the generated risk assessment score.

23. The method any one of claims 14 to 22, further comprising: communicating a second plurality of data entry fields of a second data field query category to the user, the second plurality of data entry fields being different than the first plurality of data entry fields;receiving a second data set inputted by the user, the second data set comprising data provided by the user in response to each data entry field of the second plurality of data entry fields; assigning, for each data entry field of the second plurality of data entry fields, a second value for the data inputted by the user; and determining whether to modify the second value for any of the data of the second data set by a second weighted factor to generate a second weighted value, wherein the risk assessment score is based at least in part on the second value or the second weighted value associated with the data inputted for each of the second plurality of data entry fields.

24. The method of claim 23, wherein the second weighted factor is different than the first weighted factor.

25. The method any one of claims 14 to 24, further comprising: receiving one or more user inputted parameters that provide an identification of one or more of the following: an animal type, a type or production facility, and a particular zoonotic disease.

26. The method of claim 25, further including selecting, based on the identification provided by the one or more user input parameters, the first data field query category from a plurality of data field query categories.

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