**3. Theoretical and conceptual issues**

The radical theoretical framework adopted here is complex systems theory as explicated by Wilson [1], Wilson [2], and Capra and Luisi [3]. Examining any system from this perspective includes identifying a delimited set of agents acting within operating rules and consistent with well-studied ecological principles, which constitute a scientific cosmology and resultant worldview. The importance of viewing any system as nested and situated within a larger context is essential and forces identification of boundary conditions, such as "cloud" versus "edge" as well as operative rules followed by system agents. This aids in the clarification of interface requirements such as rules of engagement for any edge computation process. It seems likely that EC will follow the common finding of fractal self-similarity, which can aid in stable and efficient system design. Systems should be designed and maintained with sensitivity to emergent and self-organizing phenomena, as well as the frequent finding of sensitivity to initial conditions (the "butterfly flapping its wings in Rio may cause a deluge in Boston" issue) which may greatly affect output variables.

The significant role of evolutionary processes known as the completed Darwinian revolution includes not only genetic technologies such as CRISPR-CAS 9 but the role of epigenetics, attachment theory, and self-domestication, known popularly as "survival of the friendliest." The importance and real necessity of acquiring large-scale longitudinal psychobiosocial data sets make EC ideally situated to better understand and manage these important processes since the pace of sociocultural and psychological evolution is orders of magnitude faster than classical genetic natural selection. This broadened understanding of the evolutionary process to include group selection and epigenetic modulation of methylation processes has massive implications for a variety of uses including computation-based interventions. Aside from Wilson's revered biophilia, appreciation of both ecological and evolutionary processes needs to include ecocognosy, the term meaning the acute observation of and learning from nature. Many invaluable lessons and facts have been drawn from acute observation of nature outside the built environment. Similarly, many important scientific discoveries have occurred after "accidental" events observed by perspicacious scientists that have been integrated into canonical science. A related principle is a biomimicry, which is the imitation of natural processes. This approach operationalizes the important Hippocratic Oath, second only to "Primum Non Nocere," which is to "follow the healing path of nature." A timely example of this may be the functional abilities of the octopus, which has not one "central nervous system," but a distributed distal system with each arm possessing an autonomous nervous system capable of many adaptive tasks that are only occasionally surveilled and supervised by the nervous plexus located in the octopus' head. It is perhaps only a slight exaggeration to say the octopus has nine brains, with each tentacle included "at the edge."

Another discipline that plays a central role in the systematic approach advocated here is epidemiology and its related health profession, global public health. The primary concern of epidemiology is the study of morbidity and mortality in specific populations, and the knowledge developed is invaluable in both disease prevention and management of disease manifestation progressing from outbreaks to epidemics

to pandemics and transdemics (multiple interacting pandemics). A critical point is that epidemiology does not focus on physiological disease pathology alone but includes the psychosocial realm of dysfunctions as well, so biomedical problems such as obesity are appropriate for study, as is the occurrence of gun violence and traffic fatalities. The study of life expectancy and excessive mortality are also highly relevant areas of inquiry. As the Lancet Commission on lessons learned from the COVID-19 pandemic has noted, the development and widespread adoption of sensitive sentinel surveillance systems make effective use of epidemiological data on outbreaks usable to the global public health community. The chronic underfunding and low prioritization of both epidemiological research and public health planning and preparation may well turn out to represent existential threats, as it is common knowledge within the scientifically literate that future pandemics are certain to arise, and experience with COVID-19 demonstrates that as mutation leads to variants of concern, the next pandemic may have both greater virulence and transmissibility, requiring novel approaches to containment of outbreaks and disease management. It is of some comfort that historically, public health has shown major benefits from use of nonmedical interventions (NMI) such as improved sanitation, nutrition, air quality management, and self-management behaviors such as masking, distancing, and avoidance of crowds. Almost equally distressing is the ease with which reasonable conservative scientific pronouncements have been distorted into misinformation by politically conservative and reactionary interests, as exemplified by a recent Cochrane review of mask-wearing. The conclusions were that the studies reviewed had high risk of bias, which hampers drawing firm conclusions regarding the efficacy of mask-wearing. This was miscast by the less scientifically literate but politically astute to conclude that mask-wearing was ineffective at controlling aerosolized infectious agents. Further, a politically expedient tendency to declare "the pandemic is over" overrides scientific public health practices at great risk to society and tends to delegitimize and discredit scientific knowledge. This has led to attacks on prominent scientists and health professionals. As the technology of data acquisition, analysis, and data-based intervention continues to mature, digital epidemiology will become increasingly valuable, especially regarding wireless sensors, deep learning algorithmic analysis, and last-mile EC, which provided that the distortions caused by misinformation and disinformation are identified and discredited.

Related to these developments, science itself has recently suffered damage by failure to replicate key findings and the withdrawal of peer-reviewed studies. The epidemic of drug-related morbidity and mortality, especially related to opioids like fentanyl, has been poorly understood and framed by the scientifically illiterate as needing a renewed "war on drugs" aimed either at limiting supply, either illicit or professionally prescribed and commercially marketed, or criminalization and punishment of users. This approach has repeatedly failed since it does not address the demand side of the issue, and efforts at mandated "treatment" have shown equivocal results at best. Health literacy is often neglected and research has shown that the more negative attitudes toward science and medicine are not justified. Recent attention to terms and concepts such as polycrisis, traveler surveillance, food wastage, aridification, gender food gap, climate-inspired resilience, poverty, and zero-dose children by the World Economic Forum has been poorly understood or misunderstood. For example, zero-dose children, those that have received none of the generally recommended childhood vaccinations are commended by some ill-informed parents. Another troubling development facilitated by the prominence of social media, powered by internet availability is stochastic violence and terrorism, whereby provocative

*Perspective Chapter: Edge Computing in Digital Epidemiology and Global Health DOI: http://dx.doi.org/10.5772/intechopen.110906*

public pronouncements increase the level of perceived fear, threat, and danger and lead to incidents of aggression, while the instigators claim innocence, in that they "never directly" advocated the aggressive act. Such pronouncements have been issued even at the highest level of government responsibility—the President of the US.

The polyvagal theory proposed by Porges [4] and the neurovisceral integration model described by Thayer [5] highlight the role of the autonomic nervous system in mediating and modulating a wide variety of health-related systems including the central nervous system, cardiovascular system, the respiratory system, the digestive system, and the immune system as well as the sensory and motor components that embody these systems. They both focus particularly on heart rate variability as a key biomarker of health and various disease states. The great number of pathological states and functional indicators have been reviewed by Laborde et al. [6] and Drury et al. [7] and various metrics of HRV are described as well, including time-domain, frequency-domain, and nonlinear analyses [8]. A key conceptual component of these theories is the social engagement system, which is the basis for all attachment phenomena and sociality. The neurological CNS substrates for this system have been identified to include the orbitofrontal cortex, the fusiform gyrus, and the cingulate cortex. This system appears to be very similar to the default mode network, which is active when a person is not focused on external events. Together with the central executive network, they are perhaps the brain's dominant control networks, crucially involved in social competence and interactional skill. Since HRV is based on easily obtainable heart rate interbeat intervals, it is an ideal candidate for wireless sensor longitudinal data acquisition and local algorithmic data processing, given the considerable power of current smart devices. This will be discussed in detail in Section 5.
