Numerical findings of a user trial on the android version of SmartWoundCare.
\r\n\tTo sum up, there are numerous engineering applications of diamond which are yet to be realized and this book will address some of the mentioned and hopefully open some new topics.
\r\n\t
Increasingly, mobile consumer electronic devices are able to make meaningful applications in mobile health or mHealth, defined as the delivery of healthcare and healthcare support through mobile devices. For example, there are apps that allow users to track diet and fitness, health condition monitoring (e.g. diabetes [1]; arthritis [2]), and using mobile devices to replace paper records and share information between multiple healthcare providers [3].
\nThis chapter overviews the development of a mHealth app called SmartWoundCare, designed to document and assess chronic wounds on Android and iOS smartphones and tablets. The chapter reviews the design of SmartWoundCare, the results of a user trial in a long‐term care facility in Winnipeg, Canada, and the subsequent development of algorithms to provide automated analysis of wound images for wound size and colour.
\nThe initial application area is pressure ulcers, which is also known as bedsores. However, the app is easily applicable to other wounds as well, such as venous leg ulcers, diabetic foot ulcers, and surgical wounds.
\nDecubitus ulcers are more commonly referred to as pressure ulcers or bedsores. They are injuries to the skin, or skin lesions which may extend to underlying tissues. Pressure ulcers typically occur over bony areas of the body as a result of skin pressure and friction when an individual sits or lies in one position for a long time. As such, pressure ulcers often occur in the elderly population and people who may be relatively immobile due to other illness or injury. Bedsores are preventable, but easily aggravated with heat and humidity at the wound site once they are present. Bedsores are also regrettably common, with the incidence of pressure ulcers reported to be as high has 30% in non‐acute care settings, with an average incidence rate of 25% over all types of healthcare facilities [4, 5].
\nPressure ulcers have numerous negative impacts on patients, both in immediate comfort and well‐being and in long‐term quality of life. When they develop after a patient is admitted to hospital for other conditions, they can lengthen the patient\'s overall stay and complicate their overall healing. There are also numerous quality of life impacts reported including the psycho‐emotional impacts of chronic pain and the negative impacts of social isolation when patients’ movements are significantly impaired. A pressure ulcer starts as a seemingly minor skin wound and obscures its significant risk. Pressure ulcers are noted to be the second leading iatrogenic cause of death. From an institutional perspective, pressure ulcers treatment is also costly to the healthcare system [6–11].
\nThere are many standard patient treatments used to prevent pressure ulcers in patients who are known to be at risk. These include regularly turning patients, optimizing diet and nutrition, caring for skin before pressure ulcers occur, and using pressure mattresses, pillows, and other supports to relieve pressure [12]. However, studies have also identified that due to the chronic and often long‐term duration of pressure ulcers, significant information about the wound over time can become obscured when documentation is not standardized, when risk assessments are not integral to the regular wound assessment protocol, or when assessments are incomplete or lack detail. In part, standardized forms – designed to capture all possible types of pressure ulcers – often become too unwieldy for healthcare workers with heavy patient loads to use effectively [13–15].
\nIn many other areas of healthcare delivery, electronic health (eHealth) is being examined for its promise to increase the overall efficiency of a healthcare system and to improve patient outcomes. As eHealth grows in scope and maturity, its potential includes improvements and enhancements to patient safety, health outcomes, financial efficiencies, and communication between multiple healthcare providers.
\nWhen considering the health burden of pressure ulcers, the area of electronic medical records (EMR) within eHealth is of particular interest. In the research literature, EMRs are reported to have positive impacts on the quality of care and to reduce the reliance or use of care [16].
\nSeveral studies examined the impact of EMRs relative to chronic wounds specifically. In one, an EMR system simplified wound evaluation and treatment. In this case, the impact is highly dependent on a standardized protocol for taking pictures of the wound [17]. In another study, the financial benefits of home telehealth in treating bedsores were examined. The findings indicated low‐cost technologies did lead to cost savings, whereas high‐cost technologies did not have that benefit. The study also determined that home telehealth could decrease the prevalence of advanced stage pressure ulcers [18]. However, not all EMR systems for wound care are effective. Other research identified that common problems with wound EMRs included redundancy or the opposite situation where the platform was not flexible or detailed enough to consider all potential types of wounds. Other issues included the lack of standard vocabulary, and custom‐built EMRs which were not transferable to include or integrate with other medical records or across facilities [19].
\nWhile EMRs and other forms of electronic documentation are not a panacea, there is emerging evidence that when properly designed, they can potentially lead to better communication, better patient information and wound charting, and ultimately improved patient care and health outcomes. The work outlined in this chapter follows this anticipation that better compliance in documenting wound care, higher consistency in how a wound is documented, and the added intelligence provided by the app relative to alerts and information presentation can influence health outcomes.
\nTo date, many eHealth technologies have been and are being developed; however, they are not well‐catalogued. Relative to wound care, MediSense, WoundRounds, and How2Trak offer web‐based and/or mobile interfaces for wound management. In 2013, WoundMAP Pump, Ulcercare, and Wound Mender entered the stage of wound care apps in various stages of development [20].
\nSmartWoundCare is similarly a mobile app for Android and iOS devices, developed in a computer engineering research lab at the University of Manitoba, Canada. SmartWoundCare was designed to replace the paper chart used in the Winnipeg Regional Health Authority (WRHA) for pressure ulcer management. The WRHA is a publicly funded system which includes both services and facilities. It serves over 700,000 people and supports referral services to another 500,000 people outside of its boundaries in hospitals, personal care homes, as well as a home care program. Over 28,000 people are employed by the WRHA in over 200 facilities.
\nAs its core functionality, SmartWoundCare allows nurses and other healthcare providers to replicate the information that would be entered on a paper chart. A user can create a new patient record, view an existing patient\'s record, enter new wounds, and assess existing wounds using the Pressure Ulcer Scale for Healing (PUSH tool) [21], Braden Scale [22], and the Bates‐Jensen tool [23]. Several configurations were considered, in that one device could be associated with a given patient, and each nurse or other healthcare provider who cares for that patient would enter information on that patient\'s unique device. However, the model chosen was to associate the device with an individual nurse or other healthcare provider, who would use the device with all of their patients on that shift, and then transfer the device to the healthcare provider on the next shift.
\nAs with all software, some general design objectives were established. These included keeping the user interface as simple as possible, using colours and other cues to focus the user\'s attention on important information, minimizing the steps needed to complete tasks, aligning the flow of information with emerging standard expectations from users (“look and feel”), and using the user\'s input to guide them to the applicable areas (and conversely, using the user\'s input to skip over areas not relevant for the particular patient or the particular wound). In light of the small screen size of a smartphone or tablet device, free‐form comments in data entry are discouraged by design. Entering data from pre‐set menu options is designed to reduce errors and to enable better comparisons between assessments, even when completed by different people. In a large‐scale rollout within a facility or a healthcare region, attention would also need to be given to battery life of the device, protocols for infection control, and the EMR as part of the legal medical record.
\nBeyond the duplication of paper‐based charting, SmartWoundCare was designed for several intended benefits:\n
Data sharing between multiple healthcare providers:the potential to seek consultation between multiple healthcare providers, including wound clinicians, physicians, allied health professionals (e.g. occupational therapy), and other specialists as needed. This potential reduces the need to transport the patient between facilities, saving the patient considerable discomfort and stress, and saving cost in the overall wound treatment. Just as significantly, the timeliness of interventions and changes in the direction of care can be improved. Information sharing (i.e. a telehealth framework) can occur within a given facility, within the same community, or between major centres and remote communities where remote communities do not have specialized health services. In Canada, with a small population living in a large geographical area, this is of particular relevance.
Data organization and interpretation:\n
Alerts: When logging into SmartWoundCare, the user will see a list of alerts, including wounds that are due for re‐assessment and wounds that are deteriorating. The specific parameters for the alerts (days between assessments, criteria used to determine deterioration) can be set by the user.
Because users have individual preferences on how they best understand data, SmartWoundCare presents wound histories in three formats: text, graph, and photographs. Text histories allow a user to scroll through a summary of the main wound parameters from one assessment to the next. Graph histories plot an overall wound score (e.g. generated from the PUSH tool) against time. Using the smartphone or tablet devices’ built‐in cameras, users can also add wound photographs to the record, and scroll through the images in a chronological gallery for each individual wound.
By design, the benefit of SmartWoundCare is its potential as an EMR, either on a stand‐alone basis or integrated into a wider EMR system within a facility or region. As such, privacy of data is a non‐negotiable concern. In its current form, SmartWoundCare requires each user to set up a unique user ID and password to facilitate a secure login and the login is restricted to that device. When envisioning a fully networked application within a facility or wider region, SmartWoundCare access rights would be confirmed by a secure connection to a server storing all information. Connections would be via cellular or Wi‐Fi, relying on all standard Internet security protocols. In that case, all login IDs and passwords would be managed centrally by a server‐side application rather than a device‐based login. An additional benefit of a central server, which could be facility‐specific or shared between several facilities, is the potential for additional data analysis in a Big Data framework. For example, when large datasets are available centrally in standard formats, they can be examined for anomalies, trends, and correlations that ultimately feed into the body of knowledge for pressure ulcer treatment.
\nSelected screenshots of SmartWoundCare (iOS version) are shown in Figures 1–5.
\nPatient list upon login (iOS).
Wound locations and status (iOS).
Assessment data entry screen (iOS).
Single wound summary in list and graph format.
Chronological wound image gallery (iOS).
SmartWoundCare in a prototype Android version was subject to a small‐scale user trial. Voluntary participants were nurses in a personal care home in Winnipeg, Canada, and they used the mobile app with their patients. The objective was to obtain nurses’ impressions on the app\'s design, its functionality, and how it performed as a part of their daily clinical experiences in treating patients’ wounds. Investigating patients’ experiences and patients’ health outcomes with the app was beyond the scope of the user trial.
\nThe user trial took place in Riverview Health Centre (RHC) in Winnipeg, Canada. Riverview Health Centre provides rehabilitation, palliative, and long‐term care. The facilities consist of hospital and personal care home units with almost 400 beds overall, as well as community programs and outpatient services. Riverview specializes in geriatric rehabilitation, brain injury, and stroke rehabilitation, palliative care, and complex long‐term care.
\nAll nurses at RHC were invited to participate in the user trial. Approximately 12 nurses expressed interest, and after timelines and the scope of the nurses’ participation were established, eight nurses (three men and five women) remained willing to participate. Their participation was entirely voluntary and was not financially compensated. The nurses all had regular duties caring for patients with pressure ulcers or other wounds, and they were full‐time employees of RHC. The participants had a range of experience, ranging from less than 10 years nursing experience to over 20 years in a personal care home settings specifically, and ranged from 30 to 60 years in age.
\nParticipants were also asked to judge themselves on their comfort with technology. Four participants judged themselves to be “very tech‐savvy” while the other four judged themselves to be “comfortable with common features of phones and tablets”. Participants’ confidence with smartphone/tablet interfaces and with touch screens was self‐assessed at 4.57/5.00 (range=4.0–5.0; SD=0.53) and 4.71/5.00 (range=4.0–5.0; SD=0.49), respectively.
\nTo preserve anonymity, the characteristics of participants were intentionally not cross‐referenced with one another.
\nThe nurses received a new Nexus 4 smartphone (four nurses) or a new Nexus 7 tablet (four nurses) with SmartWoundCare loaded and a training manual for the wound care app. They were given a 90‐minute training and demonstration of the app. After this training session, the nurses took the mobile devices home and familiarized themselves with SmartWoundCare further before beginning the user trial.
\nThe nurses used SmartWoundCare (Android version) during their nursing shifts. SmartWoundCare was only used for patients who had pressure ulcers and who had consented to participate in the user trial. Given the patient population, patient consent was provided either directly or through a designate such as a family member. Participants used SmartWoundCare for at least seven shifts. At times, vacation schedules interrupted data collection over consecutive shifts. In most cases, participants were able to use SmartWoundCare for a longer period (more than seven shifts), enhancing the depth and scope of their feedback. All data collection was completed within two‐and‐a‐half months of the start of the user trial.
\nUsing SmartWoundCare in nursing practice was an additional workload over the participants’ regular nursing duties, because it did not replace but rather it duplicated the paper chart that forms the patient\'s official medical record.
\nOnce the nurses had been using SmartWoundCare for approximately 3 weeks, the nurses completed an anonymous on‐line survey. This data collection instrument was timed to gain participants’ immediate opinions and experiences of SmartWoundCare\'s functionality and design. The survey was administered via Surveymonkey and included open‐ and closed‐ended questions on SmartWoundCare features, content, look and feel, usability, navigation between screens, assessment of its intended advantages over paper‐based charting, as well as overall qualitative impressions of how well SmartWoundCare fits into nursing practice. An important part of the survey was for participants to assess the commensurability of the wound data entered into SmartWoundCare relative to data entered on paper‐based forms (scope and format), as this forms the basis of the integrity of the app.
\nSix weeks later and after an initial analysis of the survey results, a focus group session was held with the participants and the researchers. The focus group was used to probe into the survey results. In that way, the findings of the user trial include both the immediate and the long‐term impressions of the app\'s features and intended benefits, both of which are valuable to assess functionality. The research design complied with qualitative research norms, in which data and interpretations of data are validated by using triangulation and member checks.
\nThe findings were then used to identify the key design issues for ongoing development of both the Android and a subsequent iOS version of SmartWoundCare.
\nThe objectives of the survey and the focus group were to obtain feedback on the design and functionality of the app and to investigate the nurses’ experiences in using the app. The main numerical findings discussed in this section are summarized in Table 1.
\nSurvey parameter All parameters are ranked on a Likert‐type scale from 1.0 (low) to 5.0 (high) | \nMean score | \nRange | \nStandard deviation | \n
---|---|---|---|
How well‐matched is the scope and depth of the software application to the Braden Scale tool? | \n4.60 | \n4.0–5.0 | \n0.55 | \n
How well‐matched is the scope and depth of the software application to the PUSH tool? | \n4.57 | \n4.0–5.0 | \n0.53 | \n
Ease of entering a new patient record | \n4.57 | \n4.0–5.0 | \n0.53 | \n
Ease of finding my existing patient’s / resident’s wound record | \n4.71 | \n4.0–5.0 | \n0.49 | \n
Ease of adding a new wound to the patient’s record | \n4.50 | \n3.0–5.0 | \n0.84 | \n
Ease of assessing a new wound for the first time | \n4.57 | \n3.0–5.0 | \n0.79 | \n
Ease of assessing an existing wound that had been previously assessed | \n4.29 | \n2.0–5.0 | \n1.11 | \n
Screens were presented in an expected and logical order | \n4.17 | \n3.0–5.0 | \n0.75 | \n
Text history: this presentation is easy to understand | \n4.50 | \n4.0–5.0 | \n0.55 | \n
Text history: this presentation is helpful in understanding wound progression | \n4.50 | \n4.0–5.0 | \n0.55 | \n
Text history: this presentation adds to my understanding of the history of the patient\'s/resident\'s wounds and wound care, compared to not having this text‐based history available | \n4.50 | \n4.0–5.0 | \n0.55 | \n
Graph history: this presentation is easy to understand | \n3.67 | \n2.0–5.0 | \n1.03 | \n
Graph history: this presentation is helpful in understanding wound progression | \n3.83 | \n3.0–5.0 | \n0.75 | \n
Graph history: this presentation adds to my understanding of the history of the patient\'s/resident\'s wounds and wound care, compared to not having this graph‐based history available | \n3.67 | \n2.0–5.0 | \n1.03 | \n
Numerical findings of a user trial on the android version of SmartWoundCare.
In general, findings over the user trial indicated that SmartWoundCare was easily learned and used in the participants’ nursing duties, and that it was well‐matched to the PUSH and Braden Scale tools. The benefit of the smartphone was that it was easily carried in the pocket of a uniform; however, a drawback was that the text size was difficult to read. On the other hand, tablet devices were more difficult to carry and store but had the advantage of readability.
\nThe user trial used an Android version of the SmartWoundCare prototype, and as a custom‐built software application, it did not always conform to users’ expectations of the look and feel of software and how one navigates through software. Areas that caused some initial confusion included cross‐navigation between different parts of the app, and confirming saves and deletions of data. Subsequent development on the Android version and later the iOS version of SmartWoundCare was a marked shift to the expected “look and feel” of mobile apps, as opposed to a custom interface.
\nAs an important part of validating the robustness of SmartWoundCare for its intended application, nurses confirmed a strong commensurability in content and data entry between SmartWoundCare and paper versions of the PUSH and Braden Scale tools. Participants reported that the intuitive guidance accurately reflected the fields necessary for a given patient and their wound condition.
\nHowever, SmartWoundCare was developed to do more than duplicate a paper chart, and the user trial also investigated the nurses’ perceptions of the added intelligence in the app. Although the user trial took place over a relatively short period of time, the nurses indicated that they appreciated and recognized the potential of the wound histories. The text histories were met with slightly better perception than the graph histories (Table 1), although not to an extent of statistical significance (p = 0.05).
\nA suggestion for additional features in SmartWoundCare is centred on developing a glossary of specialized terms. This was identified as a useful feature even for experienced wound care nurses.
\nAnother feature of SmartWoundCare over and above paper charts are the alerts that display to the user upon login. These alerts received mixed reviews by the users, with the primary complaint being that the alerts needed a more prominent place within the app rather than their location within a menu with five other menu options. In the subsequent iOS version, alerts follow a more standard format for iOS mobile apps.
\nThe strongest finding of the user trial was the value and benefit of wound images (photographs) in SmartWoundCare. Through both the survey and the focus group, nurses identified numerous benefits for the nurse at the bedside, for the patient and their family, and for the physician and allied health professionals. Nurses appreciated the ability to photograph the wound and the associated ability to show the wounds to the patient on the device.
\nThere are several benefits of wound images. At times, wounds are located on body parts that a patient cannot directly observe, such as buttocks, heels, or the soles of feet. The wound photo allowed them to see the wound and get a sense of its size and severity. Often, this led to a better understanding for patients and their families regarding the importance of wound hygiene and treatments.
\nAnother reported benefit is the time saved with each wound assessment, which could add up to significant time during a shift. It can take up to 20 minutes to undress, treat, and re‐dress a wound. If another healthcare provider (e.g. physician, physical therapist, wound clinician) asks to see the wound, the dressings need to be removed and the wound redressed after consultation. As a first option, the nurses could show the wound photograph to others in the healthcare team, and then a judgement was made as to whether the wound needed to be undressed or whether the photograph met the needed information within the healthcare team. A further advantage is when the healthcare team is consulting on a wound, the additional information that the wound photograph provided in comparison to solely having a verbal or written description of the wound.
\nOverall, the ability to add a wound history from photographs to the patient record was recognized for its potential to reduce the number of dressing changes and thus promote healing. The finding also supported SmartWoundCare\'s potential impact in telehealth.
\nThe findings of the user trial also corresponded to other research findings related to the value of wound photograph, which is contingent on the quality of camera equipment, photomicrography (the art of photographing small objects in large scale), the orientation of the camera lens relative to the wound, flash settings relative to consistent lighting, and duplicate photographs [17]. Two separate studies examined measurements of wounds taken in traditional ways compared to measurements taken from photographs. In those studies, the wounds were venous leg ulcers and diabetic foot ulcers, respectively [24, 25]. The conventional technique to measure wounds is to lay a transparent film over the wound, to trace the wound margin on the film, and then to lay the film over graph paper and count the number of squares. When comparing this technique to measurements derived from digital images, the latter method resulted in improved accuracy, lower inter‐observer variations, and improved ease of use. Because the film physically touches the patient\'s wound and can cause irritation, the digital photograph also had the advantage of being a non‐contact method. Another study explored the potential of telehealth, specifically videoconferencing, compared to in‐person assessment for pressure ulcer assessment. Both procedures led to very similar assessment of the stage of the wound. However, the telehealth approach led to an overestimate of wound size and volume when compared to in‐person assessment [26].
\nGiven the key finding of the user trial of the significant value of wound photographs, further work focussed on developing algorithms that would add intelligence to SmartWoundCare relative to image analysis.
\nThe objective of the image analysis work was to develop algorithms to determine the size of the wound in both relative and absolute terms, and to analyse the colour breakdown of a wound, all from an image of the wound taken by a smartphone or tablet camera. Further, this objective was to be carried out without any peripheral or ancillary devices. Such devices, as seen in related literature, might include templates or positioning boxes by which the user would help the patient to position themselves and the wound, or it may include ultrasonic transducers and additional lenses for the mobile device. Carrying out the image analysis independent of any ancillary devices contrasts work by other researchers which, for example, control the lighting and wound position with an image capture box when performing image analysis of diabetic foot ulcers [27].
\nThe application represented a general objective applicable to other fields, in that the work was intended to produce non‐contact measurements of irregularly‐shaped images taken with a smartphone or tablet camera, where the target range for error is <10% for images taken from distances of up to 30 cm. Relying only on the internal smartphone sensors to generate high‐accuracy measurements brings novelty to the work and specifically to the field of wound management.
\nEach new smartphone and tablet that comes to market generally has a higher‐resolution camera than the previous version of the device, and these progressions are often evident in short to medium timeframes of 6–18 months. Nonetheless, consumers are still hesitant to rely on on‐board cameras for any application that requires high precision and accuracy. In prior work, the state of image analysis from photographs was reviewed [28]. At first instance, several mobile apps were identified which claim to measure objects and distances in the 0.5–20 m range [29, 30], as well as ultrasonic‐transducer that ranges for measurements in the 1–6 cm range [31], and infrared distance measurements in the 4–30 cm range [32]. Depth‐of‐field cameras were also considered [33–35]. That early research also explored one method for determining distance from the camera to the wound and two algorithms to determine the size of the wound. Although both methods are promising, the specifications for error were not met [28].
\nIt is foreseeable that smartphones with dual‐lens camera will enter the market within a timeframe of 6–24 months [36]. This development would create new and significant potential for high‐resolution images and subsequent analysis for accurate and precise characterization. The analysis techniques would build on the existing work in other fields, such as stereoscopic cameras in manufacturing. Google\'s Project ARA, a collaborative effort to develop modular smartphone hardware may also provide a future framework by which to include dual‐lens cameras in mobile devices.
\nThree components of the image analysis work are outlined in the following sections. In the first component referred to as Mask Image, the objective is to obtain the relative dimensions of an object in the image (in this case, a wound), in which the size determination is relative to the previous image of the same object. The second component, referred to as Camera Calibration, reconstructs an image taken on an angle and references it back to a two‐dimensional (2D) plane, in this way facilitating a measurement of the absolute or actual size of the object in the image. The third algorithm determines the range of colours present in an image. The algorithm separates the image into three component colours by extracting components from the red‐green‐blue (RGB) format of the image, and by doing so, makes possible an inference of the wound stage.
\nThe software framework (Figure 6) in a high level abstraction consists of modules including acquisition of the wound image, pre‐processing of the wound image, segmentation of the wound image, recognition of the wound type, and classification of the wound. In reference to the three major components of the analysis indicated previously, the Mask Image component lies within the image acquisition module. Grabcut (a segmentation method [37]) and the Camera Calibration component both lie within the segmentation module, and the colour analysis component lies within both the segmentation and the wound recognition modules.
\nBasic application model.
Although the wound photographs are taken with the cameras built into a mobile device (smartphone or tablet as per Table 2) or a webcam, all of the processing takes place on a computer. Computation times are generally in the order of seconds. Further work to have the processing take place on the mobile device itself is ongoing, and comes with the usual challenges of carrying out computation‐ and memory‐intensive processes on mobile devices.
\nProcessing the photograph on a computer allows for both static and dynamic environments. In this case, a static environment denotes an environment where both the camera setup relative to the wound position is fixed (e.g. known, constant distance and angle, often with the use of staging devices) and the light source is stable. A dynamic environment refers to a mobile camera (i.e. smartphone or tablet) and/or the wound in a natural position at varying distances and angles to the camera and in varying lighting conditions.
\nWith a series of photographs taken in a static environment, the Camera Calibration component, which corrects for angle by reconstructing an image in three‐dimensional (3D) space back to a 2D plane, only needs to be done once and the correction can be applied to the entire series of photographs. In a dynamic environment where distance and angle between the wound and the camera vary with each photograph, the Camera Calibration component needs to be done for each image.
\nTable 2 summarizes the hardware and software specification applied in this work.
\nNexus 4 (LG‐E960) | \nMacBook Pro | \n
---|---|
Krait Quad‐core 1.5 GHz | \nProcessor 2.6 GHz Intel Core i7 | \n
Display resolution 1280 × 768 | \nMemory 8 GB 1600 MHz DDR3 | \n
Camera resolution 8MP (3264 × 2448) | \nGraphics Intel Iris Pro 1024 MB | \n
High Performance Adreno 320 GPU | \nSoftware OS X 10.9.5 (13F34) | \n
Bluetooth 3.0 BLE | \n\n |
Wi‐Fi 802.11 a/b/g/n | \nSoftware | \n
\n | Android 4.2 (Jelly Bean) | \n
Samsung Galaxy S4 | \nAndroid NDK r9d | \n
ARM Cortex‐A15 Quad‐core 1.9 GHz processor | \nOpenCV 2.4.9 Android SDK | \n
Display resolution 1080 × 1920 | \nPython 2.7.10 | \n
13+ megapixel camera | \nNumpy | \n
Bluetooth 4.0 | \nMatplotlib | \n
802.11 a/b/g/n | \nOpenCV 3.0.0 Matlab | \n
Hardware and software specifications.
The first two components of the image analysis work, Mask Image and Camera Calibration, are used to determine the relative size and the absolute size of a wound, respectively, from the wound photograph. Figure 7 expands the first two modules of basic software framework in Figure 6, specifically the image acquisition module and the image pre‐processing module. The Mask Image component is situated within these modules.
\nImage acquisition and pre‐processing flowchart.
Wounds are generally three‐dimensional, with volume below the skin surface. Wounds can also exhibit undermining, which refers to a wound that is larger at its base (below the skin) than the opening at the surface of the skin suggests, creating a cavity below the surface of the skin. Tunnelling refers to wounds, similar to undermining, which have channels (rather than cavities) below the skin surface.
\nAs noted earlier, conventional methods to measure wound dimensions and/or area often use contact methods, in which adhesive strips or transparent films are laid around or on the wound, respectively, and wound edges are noted on the strips or films. The strips or films are then read directly for size or overlaid on to graph paper or rulers for measurement. The depth is generally measured with a cotton‐tipped applicator to the deepest part of the wound.
\nTwo approaches in the literature to automatically determine the size of a wound include grid capture and scanner capture. Grid capture is a hybrid of conventional contact methods and digital image analysis. In this case, a transparent film with a marked grid is placed on the wound and the wound perimeter is traced on to the film. The film with the tracing on a known grid is then the basis from which the dimensions and area of the wound can be calculated with a software application [38]. This approach has the advantage of basing the calculation on a real tracing of the wound perimeter and a known grid, thus capturing the near‐real orientation of the wound. However, the disadvantage remains the potential for discomfort to the patient when the film rests on the wound.
\nIn another approach denoted as scanner capture, a box with two internal mirrors is constructed as a template. The box has openings for a mobile device and an LED light source. In the scanner capture approach developed by others, a box with two mirrors inside is placed at 45 degrees relative to the horizontal, with openings for a smartphone and an LED light source [27]. The patient rests their foot in the box, and in this way, the setup maintains a constant distance between camera and wound and constant lighting conditions. While the computation remains intensive, the advantage of this method is that these two conditions serve to simplify the image processing requirements. The disadvantage of this method is the reliance on ancillary staging devices, and the setup will be impractical for certain areas of the body.
\nIn this work, the objective of the Mask Image component is to obtain the comparative dimensions of an object in the image relative to a previous image of the same wound. An initial photograph is taken, from which a transparent digital ‘mask’ of the wound is created. The user then overlays or aligns this digital mask to the wound for the subsequent assessment and photograph (Figures 8 and 9). While most of the perimeter is expected to align between the mask image and the wound in its current state, one can reasonably anticipate that if the wound is either healing or deteriorating, portions of the perimeter between the digital mask and the wound in its current state will differ. The algorithm compares the digital mask to the current wound image, recognizing and aligning wound perimeter, and estimating the relative size difference. From this size difference, either healing, deterioration, or no change is inferred. The result is given as a percentage change in the area of the most current image relative to the previous digital mask image.
\nThe mask image or mask overlay essentially serves to provide a point of reference when aligning the wound for the current assessment with its previous condition. As such, the point of reference does not necessarily need to be the transparent mask overlay. A medical tattoo could also act as a point of reference. In this case, it would be either a temporary or permanent skin marker or pattern (e.g. three dots) close to the wound. This marker or pattern would be used each to create a digital overlay which would provide the point of reference when aligning the camera for all subsequent photographs.
\nCreating a mask image from the wound.
Overlay of mask image to new wound.
The Mask Image component of the work provides the relative size of the wound from one assessment to the next. Users can choose to create one digital mask and compare all subsequent photographs to the initial digital mask; alternately, users can create a new digital mask at each wound assessment so that wound size comparison is always to the most recent assessment. A combination of the two methods is also possible. The advantage of the method is the absence of direct contact with the wound, thus preventing patient discomfort. Another advantage is that no additional devices to the camera or to the patient (e.g. props) are required. The error inherent in the approach is largely determined by the user\'s dexterity in aligning the digital mask over the current wound. A limitation of the method is that wound depth is not considered in the calculation. A further limitation of the method is that the outcome is a relative size of the wound rather than an absolute size. When an absolute size of the wound is desired, the Camera Calibration component is implemented.
\nFigure 10 shows the Camera Calibration component within the basic software framework outlined in Figure 6.
\nSize estimation with segmentation flowchart.
Grabcut, a segmentation method used to differentiate an object (in this case, a wound) in the foreground from its background (in this case, the surrounding skin or body part), is applied in this module. Grabcut accomplishes this by using colour information to compare side by side pixels and also by using edge or contrast information to identify an object in an image. Further, Grabcut uses progressive iteration and runs the process multiple times to optimize the results. The result is a segmented image (the foreground object, in this case, a wound). This segmented image is then used in the Camera Calibration component as well as the third component of colour analysis. While other segmentation algorithms are available, Grabcut is considered an efficient algorithm and has the benefit of minimal user interaction [37], which was a requirement in this work. An example of Grabcut applied to wound photographs is found at https://youtu.be/Iyvochswrws.
\nThe purpose of the Camera Calibration component is to take an image photographed on an angle and reconstruct or reference it back to a two‐dimensional plane. Essentially, the Camera Calibration module computationally achieves one of the objectives of the scanner capture box [27] in terms of aligning the wound to known and fixed positions relative to the camera. The Camera Calibration component uses a known pattern with 13 or more fixed reference points, and applies the Tsai2D algorithm [39, 40] to obtain a reconstructed image of the wound. Since the distance between the points are known from the calibration model, the view angle can be calculated and the image can be reconstructed on a 2D plane. From here, the size of the wound can be calculated. Like the Mask Image component, the Camera Calibration component also does not identify depth or volume of wounds. This is a known limitation, given that surface size and area alone are an incomplete descriptor of wounds.
\nA chessboard pattern was chosen as the pattern. This was found to be effective for photographs taken in static and dynamic conditions. Similar to the conventional approach of placing an adhesive ruler near the wound to measure size, the chessboard pattern is placed close to the wound and then photographed. The inherent assumption is that the wound and the pattern are in the same two‐dimensional plane. Given that the chessboard pattern is known and fixed, the planar orientation of the pattern in the photograph can be calculated and then the image corrected accordingly. This approach has been shown to be effective in calculating the dimensions of a soccer field, in which a top (plan) view of the field was reconstructed from images taken on an angle, using Camera Calibration [41]. In this work, the chessboard pattern is used for calibration to obtain the extrinsic matrix of the wound. The extrinsic matrix provides information on the camera location and the view direction, allowing for translation and rotation to the two‐dimensional plane.
\nFigure 11 demonstrates the Camera Calibration sequence at a high level. The red lines denote the objects which were detected, i.e. the dark squares. The algorithm finds the centre of each square and applies the Tsai 2D algorithm to process the coordinates. The blue lines show the scanning sequence. The green lines are the re‐projected lines from the model points to the real world coordinates, as an indication of the success of the Camera Calibration algorithm. If the green lines were curved or otherwise irregular, this would indicate that the projection back to a two‐dimensional plane was not successful.
\nFigure 12 shows the Camera Calibration component applied to a wound. The wound was photographed at an angle and then re‐projected on a two‐dimensional plane at 90 degrees to the viewer.
\nOriginal and re‐projected planes.
Wound image before (left) and after (right) reconstruction.
While the Mask Image component results in a relative size of the wound and the Camera Calibration component results in a corrected orientation and an absolute size of the wound, taken together, they allow for more accurate calculations. When applied to a Canadian dollar coin (26.5 mm diameter with eleven edges), the actual size was determined with an error of <1%.
\nA demonstration of the Camera Calibration module is available at https://youtu.be/OiJk3nMymSE.
\nThe third algorithm focuses on colour analysis of the wound. It determines the range of colours present in an image, separating the image into three component colours by extracting components from the red‐green‐blue (RGB) format of the image and presenting them in a histogram. These data can then be fed into an expert system to infer the stage of the wound. Figure 13 shows the Colour Analysis component within the software framework outlined in Figure 6.
\nColour analysis flowchart.
Pressure ulcers will be assessed as one of six stages (stage I through IV, Suspected Deep Tissue Injury, and Unstageable) [42]. Because the current work is unable to calculate the depth of the wound, the last two categories (both of which are wounds with some depth below the skin surface) have been combined as Unstageable. In addition to wound depth, other factors that determine the stage of a wound include skin condition (intact or broken), tissue loss, the colour of the skin, tissue, and wound bed, and the presence and nature of discharge.
\nTo analyse the colour of a wound, the algorithm uses an RGB format of the image and determines the presence of the three component colours. Each component colour has a defined range, although the user can adjust that range or calibrate the range for variable lighting conditions.
\nWhile segmentation is not mandatory, the results of the colour analysis component are much more accurate if done on a segmented image, as this allows the algorithm to disregard the background (Figure 14 images taken from http://reference.medscape.com/features/slideshow/pressure‐ulcers).
\nUsers can also consider hue, saturation, value (HSV) and red‐yellow‐black (RYB) formats for colour analysis. Hue, saturation, value (HSV) format responds to lighting, and as such, it may be a good option when one wants to tune the colour more specifically. RYB (red‐yellow‐black) has a fitting relationship to wound stages, and RGB results can be converted to RYB. The approximate ratios of red, yellow, and black correlated to wound stages are shown in Figure 15. Wound stages I and II rely only on red, but are differentiated on the intensity of the red in the image. The subsequent wound stages are differentiated on the proportions of each of the three colours in the image. The error inherent in this method depends to some extent on the definitions of colours set by the user. A recommendation is to associate this component with a machine learning component, once a large enough data set is collected. In this way, colour parameters can be more precisely defined.
\nFinally, expert systems can be developed to determine wound stages from the RGB and/or RYB data. This again relies on collecting a sufficiently large data set. Alternatively, support vector machine (VSM) or another machine learning algorithm can be applied to determine the stages of a wound. In the current work, the framework for an expert system is in place. The next step is to collect and populate the expert system with training data.
\nAn example of the colour analysis on wound photographs can be viewed at https://youtu.be/Iyvochswrws.
\nHistogram results before and after segmentation.
RYB output correlated to wound stage.
SmartWoundCare as a mobile wound management prototype demonstrates the wide relevance of mHealth for applications within healthcare facilities and their integration with larger EMR and eHealth systems, as well as the application of telehealth to connect underserved communities. Community health and home‐based care is an equally important and in some way a more urgent implementation. For example, nurses of the Winnipeg Regional Health Authority alone carry out 450,000 wound visits per year in its Home Care program in clients’ homes. Particularly in home‐based care, the integration of SmartWoundCare with a suite of mHealth tools is a natural extension. A logical partner app for SmartWoundCare is diabetes monitoring, as well as novel pre‐emptive applications such as an early warning system for injury or damage to diabetic feet due to neuropathy [43].
\nSmartWoundCare and other mHealth applications also illuminate opportunities in Big Data, in which a community of users generate data – in this case, a wound database – from which relevant trends in wound diagnosis and healing can be extracted and form part of the body of knowledge in wound care.
\nIn dairy farms, biosecurity, surveillance, resilience/immunity, biocontainment, and control of disease spread within the herd are the pillars that need to be appropriately managed to ensure the healthy herd [1].
Biosecurity is focused to reduce and prevent the introduction of diseases or pests of animals on a farm, and to minimize the spread of diseases or pests within a farm. Biosecurity action plans need to be implemented mainly in large dairy farms where the disease agents can be introduced by various sources such as labor, advisers, replacement cattle, supplies, feedstuffs, and vehicles [2].
Surveillance programs are developed for early detection of emerging pathogens, to establish disease-free status or the prevalence of a specific disease in a herd [3].
Relation resilience immunity is based on the individuals’ resistance to diseases that can be modulated by the ability of animals to adapt to adverse conditions (stress factor) and recover from them [4].
Biocontainment and control programs are important backup systems for biosecurity plans that will prevent the emerging disease spreading within the herd or the endemic diseases spreading between animals into the farm [2, 5].
The overall biosecurity of dairy farm uses different levels or shells of actions (national or supranational, regional, and local), linked with the epidemiological profile of the pathogen. For highly contagious infectious agent (e.g., foot-and-mouth disease), the most efficient biosecurity plan is at national or European Union level, while for infectious agents transmitted by close contact between animals (e.g., bovine tuberculosis), the regional biosecurity measures such as movement controls will protect the status of the region [1].
Biosecurity practices on livestock farms have been described and prioritized in various ways [1, 2, 5, 6]. In this chapter, we grouped biosecurity measures in the following categories: dairy farm sanitation, facility biosecurity, animal biosecurity, feed biosecurity, and manure biosecurity.
Some infectious agents are specific for dairy cattle and others are zoonotic, affecting both bovine and human health. Employees and visitors can contribute to the spread of all these infectious agents on a dairy farm [7]. The transmission of pathogens by humans can be reduced or even stopped by providing on-farm laundry facilities for all protective clothing used on the farm, using only clean overalls during farm visits, providing disposable clean booties for visitors and cleaning of boots with disinfecting solution after scrubbing off any visible dirt at the end of the visit, and washing of hands before and after working with sick or young animals [7, 8, 9].
Milking parlor personnel should wear latex gloves while milking to reduce the spreading potential of the contagious mastitis pathogens [9]. Sometimes, these hired personnel can take care of other animals outside the dairy farm and carry pathogens on the farm. Employees should be regularly trained in good practices to prevent the spread of disease (the principles of hygiene and disease security). They need to know that calves are susceptible to diseases carried by adult animals, and daily activities should be organized so that employees work with younger animals before working with older animals. Prevention of the infectious agent’s introduction and spreading from outside and inside sources should also be considered in the education of hired personnel in basic hygiene and disinfection [10]. The main actions included in the biosecurity plan for dairy farms should reduce the risk of infectious diseases to be introduced by employees and visitors (Table 1).
Biosecurity measure | Action |
---|---|
Record in the logbook all farm visitors | Place the visitor logbook at the farm entrance |
Restrict the access of visitors to the stable | Locking the stable doors |
Inform unauthorized persons that they are not allowed to enter the stable | Post-warning signs asking visitors not to pass inside stable and several directing signs to the farm offices |
The visitors can access the stable only with clean clothes and boots, which they have not used in other farms | Provide clean boots and overalls for all visitors |
The visitors should use a footbath with disinfectant and clean their boots before entering the stable | Place a disinfectant footbath and brushes outside the stable |
The dealer or transporter of the newly arrived animals is not allowed to enter in stable or in contact with the farm animals | The access of the cars is made on a route that avoids contact with the farm animals, directly toward the quarantine area located at a distance from the herd |
The livestock renderer access in the stable or the contact with cattle is restricted | Store dead animals away from the stable and main roads |
Biosecurity measures designed to reduce the risk of the infectious disease’s introduction in dairy farms by employees and visitors.
The access of visitors must be limited and recorded in a logbook; the farm touring must start from younger to older animal groups; barn doors are recommended to be locked and a warning sign must be posted to keep out unauthorized personnel [9].
Also, along the access road of the farm must be displayed signs directing visitors to the administrative area and to the visitor parking, as well as warning signs to limit direct contact of visitors with farm feed and animals [11].
Equipment can be contaminated with infectious secretions, excretions, and blood and the movement of equipment between stalls and farms may also transport pathogens [12].
All equipment used on the farm must be regularly cleaned and disinfected [11]. To prevent contamination of equipment, storage containers need to be used for all tools and feeding equipment. Also, all storage containers are regularly cleaned and disinfected. The storage containers must protect equipment from diseases, pests, or weeds [13]. Before use in healthy animals, equipment that has been used on sick animals must be cleaned and disinfected. However, it is better not to use clothing, shoes, and tools dedicated to the compartment of sick animals [14]. Dehorners, ear taggers, hoof knives, clippers, and all shared and hired equipment will be cleaned and disinfected between uses [11, 14].
Nursing bottles and buckets must be sanitized before each feeding [14], calves kept indoors must have fresh clean dry bedding, and plastic calf hutches will be cleaned and disinfected after use [11].
The equipment used for manure disposal will not be used for transporting or delivering feed [13].
Disposable clothing and used veterinary equipment must be removed safely [11].
Vehicles are considered fomites mainly for pathogenic robust organisms that can survive a long time in the environment [1]. Mainly external vehicles that collect milk, calves, and carcasses or deliver feedstuffs, pharmaceuticals, and semen can be involved in the transmission of infectious disease because they travel daily from farm to farm [2, 10]. A high biosecurity risk is associated with carcasses (dead stock) collectors because they are usually in contact with diseased animals [15, 16].
To prevent the introduction of infectious agents, vehicles must be kept clean and should not have access to the zones where the animals are housed [10, 11, 17].
External vehicles should not be allowed on the farm [18]. If vehicles are necessary on the farm, then ensure that vehicles and trailers are clean when entering the farm and disinfected before and after use [6, 11, 18, 19]. Cleaning and disinfection will cover both the exterior and the interior of the vehicles, with greater attention to areas where dirt may be hidden (e.g., wheel arches and tires) [11]. Because the transport by dealers may pose additional risks of infectious disease transmission between farms, it is recommended that the animal moving will use only farm-owned vehicles [20], with clean and ample bedding to prevent both injuries and disease [14].
Guidance indicators and warning and restricting access signs to unauthorized vehicles must be placed at the entrance to the farm road and along the road. The farm must have a designated area for visitors’ vehicles that are at the entrance of the farm and away from the animal and animal stalls [6, 10, 14]. Also, service vehicles should not drive over the routes of feed delivery or manure handling [14].
In a dairy farm, the building’s design can help prevent the spread of pathogens to sick cows, periparturient cows, and newborns [2]. Buildings should have a well-established destination, in correlation with the categories of animals present on the farm. Dairy farms can secure their premises against domestic and wild animals by installing various types of fences (e.g., electric fence) around the buildings. Disinfectant footbaths should be at the entry of livestock housing. All farms should have isolation building (the quarantine facility) where the health status of the newly purchased cows will be observed before they join the rest of the herd [21]. To prevent direct and indirect contact between residents and new animals, the quarantine facility should be located in the farthest possible place on the dairy farm [10]. The farm must have a biosecurity plan that includes building maintenance activities (e.g., check and maintain fences, replace bird netting, and repair holes in buildings), which will reduce the contact of cattle with wild animals and the feed contamination with birds droppings or badger feces [14, 21].
The introduction of new cattle is one of the most important biosecurity risks for dairy farms [10]. In modern dairy farming, the sale and movement of cattle is an intrinsic part of the business as a consequence of the increased herd replacement rate of adult milking cows, the forced culling, and the need to increase the size of the herd [1]. Therefore, keeping a closed herd is the most effective biosecurity measure but is the least practical [6]. To reduce the risk of diseases spreading between farms, the new animals are purchased only from herds with known health status and known vaccination protocols [9, 10].
The best solution to prevent the introduction of diseases through the acquisition of new animals is the hosting of the newly purchased cows in a quarantine facility with trained personnel to handle isolated animals [10, 21]. Quarantine is one of the most important biosecurity tools and consists of the separation of specific groups of animals to prevent the transmission of infectious diseases. Prophylactic quarantine is designed to separate the resident herd from newly acquired animals for 1 month or more. During the 30 days of isolation, the personnel from the quarantine facility will monitor cattle health status and prevent direct and indirect contact between new and resident animals [9, 10]. If the infections have short incubation times, then the animals will develop acute diseases during the quarantine period. In other cases, to prevent the diseases spreading from animals that might be hiding an infectious agent without exhibiting clinical signs to resident animals, the quarantined animals will be tested for various diseases such as bovine tuberculosis, Johne’s disease, brucellosis, leptospirosis, salmonellosis, campylobacteriosis, leucosis, bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR), trichomoniasis, neosporosis, ringworm, liver fluke, lungworm, digital dermatitis, and contagious mastitis pathogens (Streptococcus agalactiae and Staphylococcus aureus) [10, 14]. The testing of animals in the prophylactic quarantine is a valuable biosecurity tool when properly applied.
To prevent the bovine tuberculosis introduction, the biosecurity plan should take into consideration all possibilities of Mycobacterium bovis transmission. Cattle are the main reservoir and spread microbes through aerosols (adults) or manure (calves) to many domestic and wild mammalian species. Sheep, goats, pigs, horses, and dogs are spillover hosts and spread M. bovis spread microbes in various ways (respiratory, digestive, by bites, or scratches). After infection, badgers, brush-tail opossums, wild boars, deer, and other wildlife species become wildlife reservoirs (maintenance host). Humans are susceptible and contract the infection mainly by drinking raw milk and raw milk products. People with pulmonary or urogenital tuberculosis can retransmit the infection to cattle [22].
Calves are more susceptible and should be kept in a separate area to minimize their exposure to infectious agents [14]. Calves can carry many infectious diseases without clinical signs and positive results on the laboratory tests (e.g., Johne’s disease). This risk can be reduced by purchasing calves only from herds officially certified as disease-free [1].
Because one of the most common ways of the BVD virus introduction in a free farm is via a pregnant heifer (“Trojan cow”) carrying a persistently infected fetus, all calves from purchased cattle should be tested at birth to detect persistently infected animals with BVD virus [1, 9, 10]. Persistently infected animals are the main route of the BVDV spreading between herds because they cannot be detected by serological tests (immunotolerant calves), but excrete massive amounts of virus [1, 23]. The risk of farm contamination can be reduced by purchasing animals only from herds officially certified as BVDV-free. If the BVDV status in the herd of origin is unknown, then pregnant females should be isolated on arrival (the contact with any animal of breeding age must be restricted), tested for BVD antibody and BVD antigen, and released from isolation only if they are negative results at both tests or antibody positive, antigen-negative, calved, and the calf was tested negative or removed from the herd [1]. To prevent BVDV introduction into a free farm, the following risk factors should be considered: trade with live animals, embryo transfer and semen recipients, return of animals from animal exhibitions, direct contacts between cattle on pasture or over fences, density and activity of arthropod vectors, vaccination, and employee and visitors contact with animals [9, 24].
Sick and suspicious animals should be isolated in a specific area and always handled at the end. In the control of contagious mastitis, the latter are milked cows suspected of the disease [9].
Implementing effective biosecurity programs will bring long-term economic benefits. Dutch studies have shown that the main benefits of a closed dairy herd with good biosecurity are better fertility and lower slaughter rates. The USA comparative studies in Johne’s disease-positive herds and Johne’s disease-negative herds revealed an economic loss of almost US$ 100 per cow in positive herds. Spread of an infectious disease onto a farm can lead to large economic losses. An outbreak of BVD in an Australian farm with 320 milking cows caused losses of $AUD 144,700 [25].
Vaccination is another important biosecurity tool designed to protect resident cattle from infectious agents that could have been brought in by the newly purchased cows [26]. In dairy cattle, immunization mainly targets common infectious agents such as BVD virus, IBR virus, parainfluenza-3 (PI3) virus, bovine respiratory syncytial virus (BRSV), leptospirosis, and clostridial infections [27]. Vaccination programs should be established in collaboration with the herd veterinarian and adapted to the risk of the disease spreading on the farm, including infectious agents that evolve in the area [25, 28]. Vaccination should not be considered the primary or single biosecurity tool because no vaccine provides 100% immunity [26, 28].
Dairy herd vaccination programs are affected by various factors such as age and category of production, disease history, housing, type of vaccine (killed or modified live), and costs [28]. Vaccination programs are designed by age categories and are applied continuously to maximize herd immunity and minimize the spread of the infectious agent [27, 28].
Vaccination schedule for dairy heifers from birth to 6 months of age can be started with an oral modified live vaccine (MLV) for bovine rotavirus and bovine coronavirus given 30 minutes before the ingestion of colostrum to prevent the inactivation [28]. In the first hour of life, calves must receive 2.8 L of colostrum, and in the next 23 hours, the rest of 2.8 L [27]. Depending on the epidemiological situation, an intranasal vaccination of neonatal calves with respiratory vaccines (IBR/PI-3/BRSV) can be started at 3 days of age or older [28]. At 6 weeks old, dairy heifers can receive an injectable modified-live IBR/PI3/BRSV/BVD vaccine and a seven-way clostridial bacterin-toxoid [27]. The immunity of injectable vaccines is longer than the immunity of intranasal vaccines [28]. Following national and international regulations on brucellosis prophylaxis, at 4–6 months age replacement heifers should receive brucellosis RB51 vaccine. Also, depending on the epidemiological situation, calves can receive the appropriate vaccination for leptospirosis clostridial diseases and/or Histophilus somnus. At 6 months of age, heifers should be revaccinated with modified live IBR/PI3/BRSV/BVD virus vaccine, seven-way clostridial vaccine, and five-way leptospirosis bacterin [27, 28].
Pre-breeding heifers (10–12 months of age) should be revaccinated with killed or modified live IBR/PI3/BRSV/BVD virus vaccine, five-way leptospirosis bacterin, and seven- or eight-way clostridial bacterin-toxoid [28]. Optionally, it can be done with vibriosis bacterin [27].
Pre-calving heifers should be revaccinated 40–60 days before calving with killed IBR/PI3/BRSV/BVD virus vaccine, five-way leptospirosis bacterin, killed rotavirus and coronavirus vaccine, and Escherichia coli + Clostridium perfringens types C and D bacterin/toxoid. Three weeks before to calving, heifers should be revaccinated with killed rotavirus and coronavirus vaccine, and Escherichia coli + Clostridium perfringens types C and D bacterin/toxoid [27, 28]. Also, pre-calving heifers should be vaccinated with coliform mastitis bacterin [27].
Adult cows should be annually vaccinated, 40–60 days before calving for IBR, PI3, BRSV, and BVDV [27]. Depending on the history of diseases in the region and the associated epidemiological risks, the farm veterinarian should choose vaccines that immunologically protect dairy cows during the lactation period and the dry period for leptospirosis, vibriosis, Rotavirus, Coronavirus, Clostridium perfringens types C and D, and Escherichia coli mastitis. Types of vaccines recommended are killed or bacterin/toxoid and modified-live vaccines (MLV) [27, 28]. Adult dairy cattle should receive a booster vaccination at 3 weeks before calving with killed rotavirus and coronavirus vaccine and Escherichia coli + Clostridium perfringens types C and D bacterin/toxoid vaccine [27]. MLV vaccines should be used with prudence in pregnant cows and only after consultation with the veterinarian [28]. The annual vaccination for vibriosis should be performed in dairy herds where the artificial insemination is not practiced [27].
The annual vaccination of adult dairy cattle for calf scours (rotavirus and coronavirus, Escherichia coli, and Clostridium perfringens types C and D) should be considered in all herds with recent history as a part of the preventative management practices [27].
Mastitis is one of the most important diseases in dairy cows that affects the welfare, production, and duration of the economic life of the animals [29]. Economic losses are due to direct milk production losses (reduction of quantity, unsalable, or poor quality), culling or removal from the herd of animals with unsatisfactory treatment results, cost of veterinary care, cost of excessive use of antimicrobials and other medicines, and the risk of antibiotic resistance [30].
The main pathogens targeted by mastitis vaccines are Staphylococcus aureus, Streptococcus agalactiae, and Escherichia coli [29]. Reduction in the incidence and duration of intramammary infections can be obtained by applying the combination of vaccination with high milking hygiene procedures, treatment of clinical cases, segregation, and culling of known infected cows [29]. The following preventive measures were proved to have a positive result in the management of mastitis in dairy herds: the use of milkers’ gloves, blanket use of dry-cow therapy, washing unclean udders, maintaining cows upright after milking, back-flushing of the milking cluster after milking an animal with clinical mastitis, and application of a treatment protocol [30] Also, to maximize the success of immunization, within 5 days of mastitis vaccines, dairy cows must not receive any other Gram-negative bacterin vaccines (e.g., Escherichia coli, Salmonella spp., Pasteurella spp., Campylobacter sp., and Moraxella bovis) [27].
To evaluate the effects of mastitis vaccines in dairy cows, the following monitoring parameters are most commonly used:
Clinical and subclinical mastitis incidence and severity
Somatic cell count
Serum and/or milk immunoglobulin G concentrations
Milk bacterial culture or Staphylococcus aureus count in milk
Milk production
Cure or cull rate [29]
Newly acquired dairy herd bulls should be 30–60 days in prophylactic quarantine and tested with negative results for persistent BVDV infection, brucellosis, and tuberculosis. Recommended vaccination schedule for dairy herd bulls is an annual vaccination at the breeding soundness examination with IBR/PI3/BVD killed vaccine, five-way leptospirosis bacterin, and vibriosis bacterin [27].
If there are animal species other than cattle, then the vaccination actions must take into account for these species as well. Farm dogs and cats should be vaccinated at least against rabies to protect humans and other animals [14].
Antibiotic overuse can be reduced by using a proper mixture of natural antibacterial peptides, biological response modifiers, prebiotics, probiotics, and correct development of the gut microbiome [31].
The limited use of bacterial culture and sensitivity testing by veterinarians are other causes of the persistence of the multidrug resistance (MDR) isolates in dairy farms. The findings of the last decades highlight the necessity of using antimicrobial susceptibility testing each time before prescribing an antibiotic [32].
To reduce the risk of pathogens spreading in farm animals, dead animals should be disposed of in the shortest time. Depending on the national regulations and farm’s possibilities, the disposal of carcasses can be done by a licensed dead stock collector, burial, or composting [14].
Studies designed to investigate what motivates and withholds farmers to implement biosecurity measures placed the carcass storage away from the stables on the second rank for feasibility, but with a lower score for efficacy [33].
Rendering trucks have a particular risk for farm biosecurity because they are at high risk for carrying animals killed by infectious diseases [26]. To prevent farm contamination, mortality pick-up should be located away from the stable and feed storage bin and silo [34].
The biosecurity of feed and water must start from the source, respectively, from the fields where crops are grown and from the water capture source. Manure used as a natural fertilizer can contaminate the soil, crop, and water used for irrigation and groundwater sources [2]. The quality and potability of water should be tested regularly, and samples from each feedstuff batch or lot should be stored for possible laboratory analyses (e.g., bacteria, toxins, molds, and mycotoxins) until that batch is consumed without incidents [2, 10].
To reduce the risk of the diseases being introduced by contaminated feed, the dairy producer should record and monitor the manure application on its pastures and fields cultivated with feedstuffs [2]. The risk of a feed-related disease outbreak is increased when feedstuffs are purchased from multiple locations or the crops were fertilized with manure from other dairy farms [2, 10].
To prevent feedstuffs to be contaminated through fecal material and urine from rodents, birds, dogs, cats, and any wildlife, dairy farmers should design food storage areas in a way to be inaccessible (e.g., opened bags can be placed into containers with tight lids; barns can have welded wire fence) [2, 14].
The biosecurity plan of the dairy farm should include the frequency of storage areas cleaning, the way of feed bags storage off the floor on pallets, removing and disposing of the not consumed feed within 24 hours, rotation of feed inventory for the purpose to reduce the possible presence of detrimental organisms or toxins in stored feeds, and periodically checking of silos, bins, and bunks to detect and remove as soon as possible moldy or spoiled feedstuff [14].
Although not recommended, some cattle herds are still using surface water (e.g., lakes, ponds, and rivers) as a water source. Drinking water can be contaminated by animal carcasses (e.g., dead wild animals), manure from other livestock, bird droppings, urine and feces of wildlife, and human waste [2, 10, 14]. Water biosecurity programs should include several measures designed to prevent contamination with toxins and infectious agents such as restriction of the birds and wildlife access to farm water sources, filtration and chemical sterilization of water, and regular testing of water quality and potability [2]. Waterers should be cleaned once a week [14].
In dairy farms, manure is the most problematic waste and should be treated as a biological risk material because it has a huge bacterial load [2]. Manure should be stored in an area inaccessible to cattle [14]. Contact with manure from infected cattle is the main means of spread for rotavirus, coronavirus, Escherichia coli, Salmonellosis, and Johne’s disease to other receptive animals. Manure handling should prevent environmental contamination and should not violate the legislation in force [14].
Manure is rich in nutrients that could be recycled as fertilizer [35]. However, the use of this natural fertilizer should be done with caution to prevent contamination of crops, pastures, and groundwater sources [2]. Salmonella spp., Escherichia coli, Listeria spp., and Mycobacterium avium subsp. paratuberculosis can be killed by the process of manure composting but the process must be controlled before the use of compost in agriculture [2, 36, 37]. In the process of composting should not be used the manure from the hospital pen, where de infectious agents can be in a high concentration. Also, the temperature and microbial activity should be checked to confirm the complete sterilization [2, 14]. Also, manure can be recycled for bedding and to produce methane [2].
Manure biosecurity programs should include measures to prevent the manure equipment used to handle feed, the environment infestation with files and intestinal parasites (manure must be removed frequently to prevent the pest life cycles completion), manure run-off or transfer from adults to calves, and feed contamination by manure-covered wheels of farm vehicles [14].
Manure spreaders and slurry handling equipment are high-risk equipment and should be brought to the farm after proper cleaning or disinfection [1].
The manure cleaning of vehicles and equipment must be done in areas specially designed for this purpose, where water or disinfectants would not splash onto feed or into drinking water. Throughout the entire cleaning and disinfection process, the equipment will be inspected visually to dispel any suspicion of cross-contamination [2].
The development and implementation of biosecurity programs in dairy farms improve cattle health, welfare, and productivity. These programs must be monitored and evaluated continuously to identify new methods of control and new effective critical control points and to further improve the program to prevent the introduction and spread of infectious agents on the farm. The biosecurity program should be focused on the decision and adapted to the specific situations of each dairy farm. Many of the problems encountered can be prevented or minimized with the support of veterinary services. Staff and visitors should be trained on biosecurity measures applied on the farm.
The authors declare no conflict of interest.
"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges".
\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.
",metaTitle:"About Open Access",metaDescription:"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges.\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.",metaKeywords:null,canonicalURL:"about-open-access",contentRaw:'[{"type":"htmlEditorComponent","content":"The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\\n\\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\\n\\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nOAI-PMH
\\n\\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\\n\\nLicense
\\n\\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\\n\\nPeer Review Policies
\\n\\nAll scientific works are Peer Reviewed prior to publishing. Read more
\\n\\nOA Publishing Fees
\\n\\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\\n\\nDigital Archiving Policy
\\n\\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\\n"}]'},components:[{type:"htmlEditorComponent",content:'The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\n\nDigital Archiving Policy
\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
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