Unusual epidemic events: a new method of early orientation and differentiation between natural and deliberate epidemics

Mathematical models and analysis tools for risk assessment of unnatural epidemics: a scoping review

Predicting, issuing early warnings, and assessing risks associated with unnatural epidemics (UEs) present significant challenges. These tasks also represent key areas of focus within the field of prevention and control research for UEs. A scoping review was conducted using databases such as PubMed, Web of Science, Scopus, and Embase, from inception to 31 December 2023. Sixty-six studies met the inclusion criteria. Two types of models (data-driven and mechanistic-based models) and a class of analysis tools for risk assessment of UEs were identified. The validation part of models involved calibration, improvement, and comparison. Three surveillance systems (event-based, indicator-based, and hybrid) were reported for monitoring UEs. In the current study, mathematical models and analysis tools suggest a distinction between natural epidemics and UEs in selecting model parameters and warning thresholds. Future research should consider combining a mechanistic-based model with a data-driven model and learning to pursue time-varying, high-precision risk assessment capabilities.

Using a grey relational analysis in an improved Grunow-Finke assessment tool to detect unnatural epidemics

The Grunow-Finke epidemiological assessment tool (GFT) has several limitations in its ability to differentiate between natural and man-made epidemics. Our study aimed to improve the GFT and analyze historical epidemics to validate the model. Using a gray relational analysis (GRA), we improved the GFT by revising the existing standards and adding five new standards. We then removed the artificial weights and final decision threshold. Finally, by using typically unnatural epidemic events as references, we used the GRA to calculate the unnatural probability and obtain assessment results. Using the advanced tool, we conducted retrospective and case analyses to test its performance. In the validation set of 13 historical epidemics, unnatural and natural epidemics were divided into two categories near the unnatural probability of 45%, showing evident differences (p < 0.01) and an assessment accuracy close to 100%. The unnatural probabilities of the Ebola virus disease of 2013 and Middle East Respiratory Syndrome of 2012 were 30.6% and 36.1%, respectively. Our advanced epidemic assessment tool improved the accuracy of the original GFT from approximately 55% to approximately 100% and reduced the impact of human factors on these outcomes effectively.

Analysis of COVID-19 outbreak origin in China in 2019 using differentiation method for unusual epidemiological events

OBJECTIVES

Origin of outbreaks could be natural, accidental, deliberate, and caused by a new or re-emerging bioagent. The aim of this study was the retrospective analysis of whether the COVID-19 outbreak was natural, accidental, deliberate one, or caused by a new or re-emerging bioagent.

METHODS

Analysis was performed according to the Radosavljevic-Belojevic method for outbreak scoring and differentiation. Data for the application of this method were obtained by literature review in the Medline database for the period from 2000 to 2020.

RESULTS

The analysis of the unusual COVID-19 outbreak shows that the present official assumption of its natural origin is questionable and pointed out to a probability that the pathogen could have also been accidentally introduced in the human population.

CONCLUSION

There are no conclusive pieces of evidence about the reservoir of the pathogen or the source of infection. These parameters are essential for the final clarification of the outbreak origin. This study suggests that the COVID-19 outbreak is a consequence of an accidental release of a new COVID-19 virus, probably during the technical accident and/or negligent violation of hygienic norms in the laboratory facility. Further epidemiological, microbiological, and forensic analyses are needed to clarify the COVID-19 outbreak.

Biothreat & One Health: Current scenario & way forward

There is an increased connectedness among humans, animals, and the environment and the current pandemic has taught the interlinking of the health of humans, animals and the planet. This inter-connectedness and factors like population growth, migration, urbanization, and climate change contribute significantly to the enhanced probability of emergence of previously unknown wildlife source pathogens at any place, any time, and without warning. Lurking in the background is the massive potential for the deliberate use of biological agents as weapons by State or non-State entities. Biological weapons have been used in wars since antiquity, however, newer research and techniques have led to these being real threats with a vast potential of harm to humans, animals, and crops. Over a period, it has become increasingly difficult to differentiate between deliberate and natural biothreat incidents. The response to both types is alike to safeguard lives, livestock, crops and the environment and reduce the consequent socio-economic ramifications. Biothreat may be targeted towards humans, animals, or crops, or all these concurrently. Every country including India is at risk of biothreat. The concept of one health is thus essential for responding to emerging infectious diseases or biothreats. Comprehensive surveillance for early detection, reporting and early concerted action is needed for prevention and blunting the effect of biothreats, which require close coordination and collaboration among various stakeholders within each country as well as globally.

Recalibration of the Grunow-Finke Assessment Tool to Improve Performance in Detecting Unnatural Epidemics

Successful identification of unnatural epidemics relies on a sensitive risk assessment tool designed for the differentiation between unnatural and natural epidemics. The Grunow-Finke tool (GFT), which has been the most widely used, however, has low sensitivity in such differentiation. We aimed to recalibrate the GFT and improve the performance in detection of unnatural epidemics. The comparator was the original GFT and its application in 11 historical outbreaks, including eight confirmed unnatural outbreaks and three natural outbreaks. Three steps were involved: (i) removing criteria, (ii) changing weighting factors, and (iii) adding and refining criteria. We created a series of alternative models to examine the changes on the parameter likelihood of unnatural outbreaks until we found a model that correctly identified all the unnatural outbreaks and natural ones. Finally, the recalibrated GFT was tested and validated with data from an unnatural and natural outbreak, respectively. A total of 238 models were tested. Through the removal of criteria, increasing or decreasing weighting factors of other criteria, adding a new criterion titled "special insights," and setting a new threshold for likelihood, we increased the sensitivity of the GFT from 38% to 100%, and retained the specificity at 100% in detecting unnatural epidemics. Using test data from an unnatural and a natural outbreak, the recalibrated GFT correctly classified their etiology. The recalibrated GFT could be integrated into routine outbreak investigation by public health institutions and agencies responsible for biosecurity.

A Systematic Review of Risk Analysis Tools for Differentiating Unnatural From Natural Epidemics

Introduction: In the era of genetic engineering of pathogens, distinguishing unnatural epidemics from natural ones is a challenge. Successful identification of unnatural infectious disease events can assist in rapid response, which relies on a sensitive risk assessment tool used for the early detection of deliberate attacks (i.e., bioterrorism). Methods: A systematic review was conducted according to the outline of Preferred Reporting Items for Systematic Reviews. Published papers related to the detection of unnatural diseases were searched in MEDLINE (January 1927–April 2016), EMBASE (January 1937–March 2016), and Web of Science (January 1978–March 2016). Full texts were reviewed for the selection of studies on scoring systems specially designed to discern between unnatural and natural outbreaks. Results: A total of 1,753 papers were reviewed, of which we identified the following five scoring systems specifically designed for detecting unnatural outbreaks: (1) the Grunow–Finke epidemiological assessment tool, (2) potential epidemiological clues to a deliberate epidemic, (3) bioterrorism risk assessment scoring, (4) and (5) two modified scoring systems based on (3). Various criteria ranging from the information on perpetrators, type of agents, spatial distribution, and intelligence of deliberate release were involved. Of these systems, the Grunow–Finke assessment tool remains the most widely used, but has low sensitivity for correctly identifying unnatural epidemics when tested against actual historical outbreaks. Others were applied into a few scenarios but provided different perspectives for bioterrorism detection and bio-preparedness. Conclusion: There are few risk assessment tools for differentiating unnatural from natural epidemics. These tools are increasingly necessary and valuable, but improved scoring systems with higher sensitivity, specificity, timeliness, and wider application to biological attacks must be developed.

Primordial and Primary Levels of Biothreat and Bioterrorism Prevention

There is still an abundance of preventive and solving measures against biological attacks that makes confusion and dezorientation among experts and health policy-makers. Our pyramidal model of adversaries, and spherical system of prevention help us to solve this problem. They make clearly to us, which measures should be applied at any of four levels of prevention without robust spending.

Primordial level of prevention should be focused to stop entering perpetrator/source of infection/reservoir of pathogen and biological agent/pathogen on defended territory. This is the first line of biodefense, deeply and multiply linked with the strategies of intelligence and deterrence.

The primary prevention of biological attack is focused on monitoring and surveillance of potential internal sources of biological agents and bioterrorists. We elaborate three types of surveillance: clinical (syndromic), laboratory and environmental.

Both levels of prevention were detailed analyzed, according to the next issues: Perpetrator/source of infection/reservoir of pathogen (Sophistication, Motivation, Intention, Intelligence, Secrecy, Number of perpetrators, Number of sources of infection/reservoirs, Accessibility to sources of agent/pathogen, Accessibility to targets/population at risk), Biological agent/pathogen (A category, B category, C category, Emerging pathogens, Amount of the available agent/pathogen), Means/media of delivery/factors of transmission (Air, Water, Food, Fomites, Vectors, Biological ammunition, Delivery systems, Dispersion systems mechanism of release), Target/susceptible population at risk (Intelligence, Secrecy, Personal control, Control of means/media of delivery/factors of transmission, Physical protection, Protection by chemoprophylaxis, Protection by immunoprophilaxis, Number of people in a target/population at risk, Importance of target/population at risk, Location of target/population, Distribution of people in a target/population at risk), and for each issue a whole spectrum of cheap, simple and effective preventive measures were proposed.

Whole-genome sequencing in outbreak analysis

In addition to the ever-present concern of medical professionals about epidemics of infectious diseases, the relative ease of access and low cost of obtaining, producing, and disseminating pathogenic organisms or biological toxins mean that bioterrorism activity should also be considered when facing a disease outbreak. Utilization of whole-genome sequencing (WGS) in outbreak analysis facilitates the rapid and accurate identification of virulence factors of the pathogen and can be used to identify the path of disease transmission within a population and provide information on the probable source. Molecular tools such as WGS are being refined and advanced at a rapid pace to provide robust and higher-resolution methods for identifying, comparing, and classifying pathogenic organisms. If these methods of pathogen characterization are properly applied, they will enable an improved public health response whether a disease outbreak was initiated by natural events or by accidental or deliberate human activity. The current application of next-generation sequencing (NGS) technology to microbial WGS and microbial forensics is reviewed.

Escherichia coli O104:H4 outbreak in Germany--clarification of the origin of the epidemic

BACKGROUND

In 2011, Germany was hit by one of its largest outbreaks of acute gastroenteritis and haemolytic uraemic syndrome caused by a new emerging enterohaemorrhagic Escherichia coli O104:H4 strain. The German Haemolytic Uraemic Syndrome/Enterohaemorrhagic E. coli (GHUSEC) outbreak had unusual microbiological, infectiological and epidemiological features and its origin is still only partially solved. The aim of this article is to contribute to the clarification of the origin of the epidemic.

METHODS

To retrospectively assess whether the GHUSEC outbreak was natural, accidental or a deliberate one, we analysed it according to three published scoring and differentiation models. Data for application of these models were obtained by literature review in the database Medline for the period 2011-13.

RESULTS

The analysis of the unusual GHUSEC outbreak shows that the present official assumption of its natural origin is questionable and pointed out to a probability that the pathogen could have also been introduced accidentally or intentionally in the food chain.

CONCLUSION

The possibility of an accidental or deliberate epidemic should not be discarded. Further epidemiological, microbiological and forensic analyses are needed to clarify the GHUSEC outbreak.

Biowarfare and bioterrorism

Bioterrorism is not only a reality of the times in which we live but bioweapons have been used for centuries. Critical care physicians play a major role in the recognition of and response to a bioterrorism attack. Critical care clinicians must be familiar with the diagnosis and management of the most likely bioterrorism agents, and also be adequately prepared to manage a mass casualty situation. This article reviews the epidemiology, diagnosis, and treatment of the most likely agents of biowarfare and bioterrorism.

A New Method of Differentiation Between a Biological Attack and Other Epidemics

The main obstacle in identifying a biological attack (BA), while preventing false alarms, epidemics of panic and unnecessary expenditures is the insufficient data on which to rely. Тhis new method of outbreak analysis is based on our original model of bioterrorism risk assessment. The intention was to develop a model of quick and accurate evaluation of an unusual epidemiologic event (UEE) that would save time, money, human and material resources and reduce confusion and panic. This UEE analysis is a subtle and detailed differentiation through assessment of BA feasibility in comparison with three other types of outbreak scenarios. There are two types of differences between these four scenarios: qualitative and quantitative. Qualitative and quantitative differences are defined with 23 and 10 indicators, respectively. Both types of indicators can have three different values: N/A, 0 or 1. We have carried out a feasibility analysis for subtle and detailed differentiation among four outbreak scenarios. As a tool for feasibility analysis we have introduced a “system of elimination”. System elimination is applied if one component contains all indicators scored with 0 or as N/A – the related scenario is then eliminated from further consideration. The system was applied to four UEEs: (1) an intentional attack by a deliberate use of a biological agent (Amerithrax), (2) a spontaneous outbreak of a new or re-emerging disease (“swine flu”), (3) a spontaneous outbreak by an accidental release of a pathogen (Sverdlovsk anthrax), and (4) a spontaneous natural outbreak of a known endemic disease that may mimic bioterrorism or biowarfare (Kosovo tularemia). It was found that “agent” was the most important and the most informative UEE component of the new scoring system. This system might be helpful in the analysis of unusual epidemic events and a quick differentiation between biological attacks and other epidemics.