Environmental Epidemiology. 2020, 14, 2, 4 - 12 www.e-epidemiology.com Investigating COVID-19: Quantifying recurring methodological problems in the study of infectious disease, part 1 Beth Ann Fiedler, PhD Abstract In an era of emergency management, the lack of medical countermeasures in response to COVID-19 reveals methodological errors in the prevalence of the Pathogenic/Immunological Theories of Medicine in Part 1 of a series examining current events, understanding the ongoing infectious changes, and the reaction to them. We focus this investigation on erroneous reporting, distinguish the general framework between the actual and suggested clinical research approach for assessing chronic and infectious diseases, and discover how this path can help visualize countermeasure response depending on the population impact. Different response routes are suggested dependent upon population impact such as childhood disease, adult onset of chronic disease, or emerging infectious disease and/or pandemic. Data collection methods can be implemented to identify basic disease category (e.g., chronic, infectious), determine symptoms/outcomes in affected population using International Classification of Disease10 standards, and promote the concept of meeting certain criteria to determine what path a medical countermeasure may follow to best address the specific circumstances of the negative health event. Once establishing criteria for pathways, we suggest baseline health information collected at provider level should guide clinicians and research scientists in the identification of the proper pathway. Keywords: Experimental medicine, Clinical research; Infectious ecology; Pathogenic Theory of Medicine; Immunology; Medical countermeasures Health preparedness in the age of emergency management This document is the first in a series of preprints comprised from decades of research notes, publications, and external informative literature regarding the historical scientific response to infectious disease, current, and ongoing events relating to the reaction to COVID-19 built upon an initial introduction by Fiedler & Nikolaenko (2020) [1]. In part 1, we introduce the rules governing hospital preparedness, generally referenced in this paper as health preparedness, and suggest that a lack of clinical protocols/criteria for the medical countermeasures distinguishing chronic and infectious disease has hindered the medical community and clinical research. Providing healthcare workers and clinical research specialists with data collected to identify disease symptoms, population impact, and thus, proper routes to medical countermeasures with adherence to specific criteria would eliminate potential confusion, expedite results, and offer patients informed treatment solutions with several benefits including reduction in erroneous reporting, consistent analysis process, and the inclusion of scientific research at the cellular level to assess infectious disease. According to epidemiology, “infection is characterized by (1) a constant presence in nature, (2) identification as a contagion, and (3) is associated with numerous biological species-reservoirs,” [2]. Thus, the primary basis for opposition to the current methodological response to COVID-19 is the epidemiological dependence 4 Environmental Epidemiology. 2020, 14, 2, 4 - 12 www.e-epidemiology.com on the reservoir host. The concept of the reservoir host is co-dependent with other factors, 1) agent(s) which could be biological (bacteria, virus), physical (trauma, radiation, fire), chemical (poison, alcohol or other addiction), nutrient (deficit or excess), and/or mechanical, and 2) environment (weather, temperature, altitude) or environmental conditions (overcrowding, housing, community, food desert, pollution). In this scenario, the environment influences opportunity for exposure to the causal agent over time. Concurrently, the attributes of the host (human, plant, or animal) such as customs, previous disease, or immunity can be factors in the susceptibility to disease and elicit a wide array of health outcomes. The overreliance on pointing to a host instead of the discrete activation of a microorganism associated with infectious disease is the primary objection for several reasons. While learning about who is infected is important, the epidemiological approach stemming from Pathogenic/Immunology theories of medicine erroneously initiates investigation linking to a Ground Zero host instead of understanding the infectious organism. Also, the epidemiological path also has a basis in erroneous reporting due to the infected person or host attributes that are linked to the social determinants of health (SDOH). SDOH such as gender, marital status, or socioeconomic status can skew reports when underlying medical conditions or co-morbidities are overlooked. The introduction of a vector, defined as an intermediary or delivery system between the agent and the host, has added to the traditional epidemiological triad of agent, host, and environment. A prominent example is the mosquito as a vector in Malaria. But this leads to one of many secondary objections to the epidemiological approach including an emphasis on the route of transmission instead of the variations in status of the hazardous microorganism. This secondary objection to epidemiology that allows for attribute variations in the 'host' or patient who has succumbed to an infectious disease, fails to allow for the same consideration in the analysis of the infectious agent in this method. Speculation on the vector already points to the animal kingdom as the culprit without scientific support [3]. Another prominent secondary objective to the epidemiological approach becomes apparent in the existing scientific research approach to two overarching disease classifications: 1) chronic disease, and 2) infectious disease. Existing global research, such as the Global Burden of Disease Collaborative Network, 2018 [4, database] utilizing behavioral and environmental factors that link to metabolic conditions is important to understanding chronic disease [5, 6]. Therefore, collecting poor behavior choices such as nicotine or alcohol addictions and sedentary behavior can predict the onset of various vascular diseases that could contribute to premature death. For example, metabolic measures such as high systolic blood pressure (SBP), high fasting blood glucose (FBG), or high low-density lipoprotein (LDL) cholesterol, and impaired kidney function coupled environmental conditions such as particulate matter pollution or iron deficiency lead to poor health outcomes including ischemic heart disease, diabetes, Chronic Obstructive Pulmonary Disease (COPD), and cancer. While these co-morbid conditions and other factors like age, race, and impaired immune systems increase the likelihood of succumbing to infectious disease, such as COVID-19, they do not cause the infection. Simply, infectious diseases are caused by microorganisms that further emphasize the need to study the microorganism with easily accessible patient information that are key factors in relation to the current study of COVID-19 and any emerging infection disease. Thus, while metabolic 5 Environmental Epidemiology. 2020, 14, 2, 4 - 12 www.e-epidemiology.com indicators influenced by behavior and environment lead to chronic disease, the same perspective is inconclusive regarding infectious disease. In this first preliminary investigation, we discuss the unfortunate nature of misinformation, review existing scientific criteria that dictates countermeasure response by reviewing US hospital regulatory guidelines and existing research scientist protocols, and direct attention to previously proposed methods of data collection to enhance patient level information to decision-making capacity. Then, we discuss some additional points in literature and move to scientific research recommendations that focus attention on the microorganism in the study of infectious disease. Erroneous reporting The SDOH element of race has been magnified in the reports of the number of COVID-19 deaths associated with COVID-19. A recent report by the BBC News Services [7] highlighted the seemingly disproportionate number of deaths in the Black community in Chicago in an alarmist fashion. The normally credible BBC suffered from a series of methodological reporting failures including ignoring relevant rates of co-morbid conditions such as HIV in the community, lifestyle and other realistic behavioral choices (riding public transportation and blue collar jobs that cannot be reproduced by working at home that increases susceptibility) contributing to final outcomes due to opportunity for disease transmission [8]. While recognizing differences in socio-cultural groups is important, there is an assumption of constant rates of infection and mortality without factual analysis of the agent acting on individuals that succumb to infection; lack of consideration for existing environmental and patient conditions such as high blood pressure and diabetes in the Black community; and the application of political agendas in the midst of a global pandemic. In the U.S., there have been a number of corrections in the reported deaths as states recognize that many deaths have been counted twice. Further, the way in which cause of death has been attributed to COVID-19 regardless of major underlying chronic conditions (e.g, heart disease, cancer) skews reporting as well. Most significantly, reporting scales can lead to the misconception that the number of deaths are declining when, in fact, the number of reported deaths are decreasing (Figure 1) [9]. In reporting the distribution of cases, an epidemiology curve depicts the number of confirmed cases over time [10]. Total confirmed cases can then be broken down into patients who recovered from the infectious disease or succumbed to the illness. However, the accuracy of the epi curve is dependent upon consistent testing. Without testing of new cases, epi curves that have flat lined can misrepresent the actual impact on public health. The current international status is provided of COVID19 can be located at [11]. We summarize this section indicating that there is an inherent global responsibility to continue testing and to report disease activity. But, we must do so by supplying contextual information and adherence to consistent testing in order to reflect a true picture of the situation in the context of the disease. 6 Environmental Epidemiology. 2020, 14, 2, 4 - 12 www.e-epidemiology.com Figure 1. Discrete interval values on The reporting scale seemingly depict a decline in regionally reported deaths in Ukraine but the discrete interval scale on the right represents an actual number five times larger than the scale on the left. In reporting the distribution of cases, an epidemiology curve depicts the number of confirmed cases over time [10]. Total confirmed cases can then be broken down into patients who recovered from the infectious disease or succumbed to the illness. However, the accuracy of the epi curve is dependent upon consistent testing. Without testing of new cases, epi curves that have flat lined can misrepresent the actual impact on public health. The current international status is provided of COVID19 can be located at [11]. We summarize this section indicating that there is an inherent global responsibility to continue testing and to report disease activity. But, we must do so by supplying contextual information and adherence to consistent testing in order to reflect a true picture of the situation in the context of the disease. Existing hospital emergency response and scientific criteria dictates countermeasure response The California Hospital Association (CHA) recently updated their Hospital Seasonal Influenza/Pandemic Preparedness Checklist [12], a portion of their hospital preparedness program, which serves as a mechanism to establish baseline applicable 7 Environmental Epidemiology. 2020, 14, 2, 4 - 12 www.e-epidemiology.com resource/inventory, workforce priority vaccinations and monitoring, methods of triage, and factors in cross-training emphasizing communication regarding equipment, operational care, and business continuity in the overarching process of infection prevention. In addition to operations and policy, the San Francisco Department of Public Health, Population Health Division, provides an applicable Infectious Disease Emergency Response (IDER) Plan [13] that specifically directs an embedded organizational epidemiology response team to conduct internal investigations, gather case investigations on exposure and contact, and to liaison with laboratory team members to provide syndromic surveillance on known infectious diseases with available vaccinations. Although the laboratory team is tasked with “confirm(ing) the presence of an infectious disease agent and determine its identity and antimicrobial susceptibilities,” [13, p. 2], there is no mechanism for a swift and universal collection of data other than through ‘after the fact’ telephone survey investigation that is typical of chronic disease analysis. Coordination is a key internal factor but also a dedicated Infection Control/Occupational Health Team is utilized to acquire national and other regulatory guidance [14]. However, there is a notable gap in the translation of local patient data and microbial analysis in these scenarios. Organizations in the US, such as The Joint Commission [15], work diligently to provide national information to support local and regional hospitals maintain general regulatory guidance to improve care [16] and those items specific to COVID-19 [17]. An emergency management plan is required by the US Centers for Medicare & Medicaid Services [18] and these foundational guidelines are critical for hospital infection control and general disease containment. However, they also suggest that in the event of emerging diseases that hospitals may not be equipped to timely analyze, collect, and address patient data or effective microbial investigation. In light of the known problems associated with Germ Theory in association with the study of infectious disease, what is the right approach? A readily available solution appears in the antiquated phone survey methods used to collect data. Data collection leading to improved information As US and other organizations scramble to plan to change the way they collect data [19], existing literature propagated since 2009 in multiple national presentations [20-24] and publications [5, 25-29] provides the basis for applicable methods to expedite the data collection and analysis process to elicit improved medical countermeasure response to infectious disease building upon the existing platform of existing symptoms and medical diagnosis embedded in the International Classification of Diseases-10 [several numbers]. The collection and dissemination of information through better optimization of ICD-10 codes is the basis for identifying the disease progression path or population segment (e.g., childhood disease, pandemic, etc.) while supplying valuable information to suppress expansion and inform decision-makers. The basic methodological approach eliminates ad hoc telephone survey data collection in favor of a universal collection of personal health behaviors (e.g., sedentary behavior, alcohol consumption, amount of exercise) in relation to known health conditions (Figure 2). Processing patient information including behavior and diagnosed conditions can be helpful in determining potential risk and trends in given communities. The capacity to determine this information at the local/regional level is a key to providing quick and timely information to providers, affiliated health 8 Environmental Epidemiology. 2020, 14, 2, 4 - 12 www.e-epidemiology.com personnel, and relevant agencies. This information can be collected prior to regular primary caregiver visits as part of the standard processing providing a wider view of the patient population and potential risks in association with emerging disease. Figure 2. This structural equation model demonstrates how individual exogenous predictors (left d1-d20) spanning sleep, sedentary behavior, physical activity and nutrition used by the United States Centers for Disease Control Prevention Behavioral Study Strategies, can be paired with existing patient/host conditions as identified by the International Classification of Diseases (shown here representing noncommunicable endogenous (e1 chronic) and communicable (e2 infectious) disease outcomes with some modification in the question format to elicit practical statistical models [5,20-24, 25-29]. Establishing significant causal predictors in relation to existing and potential health outcomes is important to effectively and efficiently optimizing limited resources. 9 Environmental Epidemiology. 2020, 14, 2, 4 - 12 www.e-epidemiology.com Conclusion During an emerging pandemic: solutions are preferable to panic; information to sensation; and microbial causation vs. vector assumption. Collecting factual patient data prior to an emerging infectious disease is an improvement upon existing processes with the added benefits of understanding local/regional population needs; projecting accurate risk factors and potential harm to patient population; and preparing for operational upticks in acute care. Determining an accurate patient impact vs. a rolling number based on growing cases can also properly indicate effectiveness of countermeasures put into place. This adds a dimension to the data beyond recovery/mortality as the scale of potential cases and their outcomes can be viewed in a mode that is less inflammatory to the general population. Part 1 of investigating the methodological inconsistencies of scientific research of infectious disease using COVID-19 clearly demonstrates that health preparedness in conjunction with emergency response must include 1) specific pathways differentiating chronic and infectious disease, 2) rigor in data collection and reporting, and 3) establishment of criteria to accurately identify and address the microorganism architecture and activity. References 1. Fiedler, Beth Ann and Nikolaenko, Dmitry. Investigating COVID-19: Recurring methodological problems in the study of infectious disease. Environmental Epidemiology. 2020, Preprint. DOI: 10.13140/RG.2.2.28731.77605/1. 2. Nikolaenko, D. & Fiedler, B.A. Infectious ecology: A new dimension in understanding the phenomenon of infection, in press. 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Fiedler Beth Ann & Bebber, Robert J. An international regulatory clinical trial comparative. International Journal of Pharmaceutical and Healthcare Marketing, 2013, 7(2), 199-215. 27. Fiedler, Beth Ann. Constructing legal authority to facilitate multi-level interagency health data sharing in the United States. International Journal of Pharmaceutical and Healthcare Marketing, 2015, 9(2), 175-194. 28. Cook, K. & Fiedler, B.A. (2018). Foundations of community health: Planning access to public facilities. In: Beth Ann Fiedler’ (Ed.), Translating National Policy to Improve Environmental Conditions Impacting Public Health Through Community Planning, pp. 107-130. Springer International Publishing 29. Fiedler, B.A. (2020). Environmental perspectives from the ground up: The cost of poor environmental health on human health, in press. In B.A. Fiedler’s (Ed.), Three Facets of Public Health and Paths to Improvements: Behavior, Culture, and Environment. Elsevier, Inc. For reference: Fiedler Beth Ann. Investigating COVID-19: Quantifying recurring methodological problems in the study of infectious disease, part 1. Environmental Epidemiology. 2020, 14, 3, 4 – 12. Preprint original: Fiedler, B.A. & Nikolaenko, D. (2020). Investigating COVID-19: Quantifying recurring methodological problems in the study of infectious disease, part 1. Environmental Epidemiology. Preprint. DOI: 10.13140/RG.2.2.15801.52329. 12