Considering that Infectious Diseases, especially those deriving from zoonotic sources, currently contribute approximately 20% of the global annual death causes and 10% of the total disease burden in the European continent [1]; and that the likely losses of a pandemic influenza outbreak could reach 3 trillion American dollars (~5% of the global Gross Domestic Product) [2], the different states within the European Union decided to prioritise health areas that include proactive monitoring and reactive responding, with special focus on antimicrobial resistance (AMR), vaccine preventable diseases, tuberculosis, influenza, and sexually transmitted infections.
In this respect, it is crucial to understand the pathway that takes data to realistically travel from clinical laboratories onto integrated-monitoring pieces of highly advanced software, as it is, the case with national governmental agencies (e.g., Public Health England). The disease surveillance program commissioned by Public Health England (PHE) covers 37 infectious diseases, including influenza.
Clinical microbiology laboratories (CMLs) demonstrate their ability to:
o inform and improve individual patient care,
o contribute to outbreak management and hospital infection control, and
o provide accurate surveillance data on infectious diseases and AMR. This information can be subsequently used in the reviewing of local treatment guidelines and the designing and evaluating of national health policies. [1]
In that sense, In vitro diagnostics play an important role in the scrutinising process - There are at least three major areas where in vitro diagnostics can provide essential contributions to diagnostic reasoning and managed care of patients with suspected or confirmed infection:
o aetiological diagnosis,
o patient monitoring,
o and epidemiologic surveillance. [3]
With special interest in the Reporting of bacterial and viral infections - In general, we can segregate the detection of viruses into three main categories:
o direct detection of the virus,
o viral RNA/DNA detection, and
o antibody detection. [4]
Data reporting feeds two very important surveillance systems, the UK Biobank (UKB) (an international health resource with 500K subjects allowing research into the genetic and lifestyle determinants of common diseases), as well as the Public Health England’s Second Generation Surveillance System (SGSS) (a centralised microbiology database covering English clinical diagnostics laboratories) participate in the national surveillance of highly relevant notifiable infections, bacterial isolations, and antimicrobial resistance. [5]
Analysis of shared data fed into these systems allows an improved management of relevant epidemiological scenarios based on:
o Rapid early detection validated by a large number of samples with high accuracy diagnosis supporting an enhanced surveillance.
And this process will synergistically assist the:
o Review of local treatment guidelines, and the
o Evaluation of National Health Policies
There are many challenges associated to laboratory reporting within the public health surveillance system:
o Data artifacts - missing, inconsistent and implausible data; gaps in data transmission;
o Constant change of guidelines and instructions – rapidly changing indicators;
o Heterogenous procedures - systematic differences between labs and in the utilisation of services; patient linkages over time, different data sources, numerous registries, and indicators,
o Time burden for busy providers
o Idiosyncratic +/- reporting - even though false positive/negative reporting is associated to (A) a low concentration of antibodies usually present in fluidic samples; (B) presence of homologous proteins; and (C) lack of sensitivity from the detection instrument, the fact that not all negatives are reported and that not all are reported via the same reporting systems and to the same surveillance agencies, enhances the monitoring difficulties associated to the process. [3] [4]
o Shortage of resources for high volume/frequency testing
o Incongruent shipment to reference labs
o Numerator-Denominator Incompatibility - a systematic distortion due to a denominator that does not match the numerator, or vice versa.
o Difficulties in exposure assessment
o Inadequate/Insufficient Environment/Equipment
o Culture of lax charting (e.g., ISO15189, ISO17025) - Regulatory standards demand clinical laboratories to establish and document their own performance guidelines for laboratory-developed tests in order to make sure the obtained results are done accurately and with precision results, even prior to implementation of the test. The relevant aspects that are to be considered are: accuracy, precision, reportable range, reference interval, analytical sensitivity, and analytical specificity.
• The first and possibly the most important lesson that policymakers and hospital administrators MUST learn from COVID-19 is that the continuing cut down on human and economic resources generates a huge impact in the healthy functioning of structures that can easily lead to collapse of the public/private health system, including the clinical laboratories with their enhanced testing demand. [3]
• Established labs are an important resource
• The linkage of COVID-19 test results to the UKB provides an invaluable resource to the international research community that has the potential to uncover new risk factors for severe infection. UKB is one of the largest and closest-studied cohorts in the world. [5]
• Biomolecular data exchange between databases - As is so well stated in Lenert and Sundwall (2012) "Clinical providers must exchange specified types of data with the public health system, such as immunisation and syndromic surveillance data and notifiable disease reporting. However, a crisis looms because public health’s information technology systems largely lack the capabilities to accept the types of data proposed for exchange. Cloud computing may be a solution for public health information systems. Through shared computing resources, public health departments could reap the benefits of electronic reporting". [6]
• IT infrastructural autonomy - It is understandable that each organisation wishes to maintain its autonomy, however and for the sake of a prompt positive intervention, such is completely impracticable in a diasporic multifaceted system. The idea is even considered to be OBSOLETE [6] and goes against the prominent technological inflection dictated by 'democratic' and very functional cloud services.
• "Establishment of an efficient network of regional clinical laboratories, involving those which are not directly challenged by the outbreak and where samples can be conveyed, is a feasible solution, provided that a straightforward regulation for specimen transportation and biosafety is set and monitored. This, in turn, highlights an unavoidable need to place major efforts for allowing better and wider harmonization of laboratory results and information, encompassing both analytical and extra-analytical issues." [3]
• Efficient communication to appropriate stakeholders - "It is essential that the laboratory personnel be instructed to communicate test results to the appropriate stakeholders (i.e. to the people who are officially in charge of dealing with the outbreak), thus avoiding to spread information that could generate unjustified panic, or inappropriate reassurance, among the general population." [3]
• Accurate diagnosis VS Patient stigmatisation - "Achieving, maintaining, and improving accuracy, timeliness and reliability of test results are key deliverables of diagnostic laboratories. Late or false-negative SARS-CoV-2 test results will lead to delays in or even preclude correct diagnosis, jeopardizing timely isolation and prevention of transmission. In turn, false-positive tests will waste public health resources, will lead to incorrect epidemiologic data, and might even lead to patient stigmatisation. Quality control is a cornerstone of safe, consistent, reliable diagnostics, and many studies and frameworks outline the structure of quality-management systems suitable for diagnostic laboratories."[7]
• Integration into biorepositories - "The significant role of the CML networks should not be underestimated in the sharing of routine clinical metadata or data collected. Their potential integration into a common data set (biorepositories—as proposed by the Clinical Data Interchange Standards Consortium) would maximize the opportunities for patient contributions to be translated into therapeutic and diagnostic solutions. The consolidation process for example provides a tangible opportunity to extend the scope of pooled analyses of individual patient biomarker data from heterogeneous laboratory platforms and cohorts into population-level studies using merging algorithms." [1]
• "The availability of commercial diagnostic kits in peripheral centres shall be part of the strategy for early and accurate identification of the largest possible number of infected patients." [3]
• Locally - "Near-patient testing would include so-called 1- to 2-h “plug-and-play” nucleic acid amplification tests for which a rapid result can directly impact patient care. Centrally - More-complex/high-volume tests would be dispatched to a core facility. In addition, the ability of networked CMLs to access multiple different partners, geographies, and clinical specialties can enhance their capabilities to provide advanced disease surveillance and early outbreak recognition." [1]
• Harmonised SOPs - "Laboratory professionals may also be made available on-site, where they could help define standard operating procedures (SOPs) for specimen collection and transportation. The choice between these possible solutions will obviously depend on many economic, legislative, juridical, logistical, environmental, and technical issues." [3]
• Same-day direct assays - "A major advantage of the consolidated CMLs is the expansion of the range of activities, able to accommodate high technology and sophisticated tests with increased sensitivity and specificity (30), while the usual day coverage is extended through a second (and third) shift. Same-day, direct assays, including molecular assays for selected organisms, are performed as a matter of routine thus reducing time to obtain results." [1]
• Inherent system flexibility - "The availability of increased amounts of high-resolution data at a lower cost creates an anticipation, requirement, and downstream cost(s) for the accommodation, analyses, and interpretation of these data. The inherent systemic flexibility that is necessary to receive different types of data at different speeds and from different locations—and link all that to routinely collected clinical data and report back—is not an insignificant task by itself." [1]
• Ethical implications of big data analysis - "A number of questions are raised regarding the new pathways that might be necessary, the different regulatory approaches within Europe to handling this data under the EU personal data protection directives, and data quality issues. If not correctly addressed by the inclusion of ethical design in the creation of big data, such ethical issues might become limiting factors preventing reaching of full potential." [1]
[1] Vanderberg, O., Kozlakidis, Z., Schrenzel, J. et al (2018). "Control of Infectious Diseases in the Era of European Clinical Microbiology Laboratory Consolidation: New Challenges and Opportunities for the Patient and for Public Health Surveillance". Frontiers in Medicine, 5(15), pp. 1-7.
[2] Gebreyes, W. A., Dupouy-Camet, J., Newport, M. J., et al (2014). "The Global One Health Paradigm: Challenges and Opportunities for Tackling Infectious Diseases at the Human, Animal, and Environment Interface in Low-Resource Settings". PLOS Negletected Tropical Diseases, 8(11), e3257, pp. 1-7.
[3] Lippi, G and Plebani, M. (2020). "The critical role of laboratory medicine during coronavirus disease 2019 (COVID-19) and other viral outbreaks". Clin Chem Lab Med, 58(7), pp. 1063-1069.
[4] Bhalla, N., Pan, Y., Farokh, A. (2020). "Opportunities and Challenges for Biosensors and Nanoscale Analytical Tools for Pandemics: COVID-19". ACS Nano, 14, pp. 7783-7807.
[5] Armstrong, J., Rudkin, J. K., Allen, N et al (2020). "Dynamic linkage of COVID-19 test results between Public Health England’s Second Generation Surveillance System and UK Biobank". Microbial Genomics, 6, pp. 1-9.
[6] Lenert, L., Sundwall, D. N., (2012). "Public Health Surveillance and Meaningful Use Regulations: A Crisis of Opportunity". American Journal of Public Health, 102(3), pp. e1-e7
[7] Homolka, S., Pawlowski, L., Andres, S. (2020). "Two Pandemics, One Challenge— Leveraging Molecular Test Capacity of Tuberculosis Laboratories for Rapid COVID-19 Case-Finding". Emerging Infectious Diseases, 26(11), pp. 2549-2554.
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