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Statistics in Defense and National Security: Bioterrorism and Biosurveillance
Abstract
In 1334 an epidemic struck the northeastern Chinese province of Hopei. This "Black Death" claimed up to 90% of the population, nearly five million people. The epidemic eventually reached and decimated Tartar forces that had been attacking Kaffa, a Genoese colony on the Crimean Peninsula. In 1347, the departing Tartars catapulted plague-infested bodies into Kaffa. The Genoese quickly dumped these bodies into the sea, however it was too late. Four ships escaped back to Italy carrying the plague that in just two years killed one-third of the European population. Today we have antibiotics to overcome the plague, however, this early example of bioterrorism stands as a reminder of our vulnerabilities. This point was reiterated after the attacks of September 11, 2001 revealed our vulnerability to terrorism in general. Shortly thereafter, anthrax in letters delivered by the U.S. Postal Service caused five deaths and thirteen confirmed additional infections, bringing the specific threat of bioterrorism into our consciousness. (See Jernigan JA et. al. (2001) for a detailed description of the first 10 cases.) These attacks have motivated an increase in bioterrorism-related research, and this evolving research area is creating new challenges, responsibilities, and opportunities for statisticians. Bioterrorism refers to the intentional release of organisms that can cause sickness or death. The Centers for Disease Control (CDC) classifies organisms into three categories based on the ease of dissemination or transmission, potential for major public health impact (high mortality), potential for public panic and social disruption, and requirements for public health preparedness. Category A agents (the most dangerous) include anthrax, smallpox, plague, botulism, tularemia, and viral hemorrhagic fever viruses such as Ebola. Research on many of these organisms require "biosafety level 4" (the highest level of containment) facilities. We focus on anthrax; the agent used in the well-publicized recent bioterrorism attacks.
... Vaccination can be preventing the individual health after the exposure 2-4 days later. Disease could be diagnosed easy when rashes are appear on the precise individual body [19]. ...
Bioterrorism comprises biological agents such as bacteria, viruses and toxins in population to cause illness even death. These
bio-wars are continuing panic threats in public health. Disrupting the economic, religious, social distraction, ideological and political influence.
These infectious agents may cause a larger impact on human life as compared to war. Millions of the population have died with such life-threating
agents including bubonic plague, smallpox, measles, influenza, typhus. Bioterrorism is an international practice of biological products or pathogens
to cause destruction in human-being, animals, plants and other living organisms. A particular organism can be detected Rapid molecular
detection, Sensitive assay also used to detect the bacterial DNA such as Bacillus anthracis DNA can be extracted by phenol-chloroform according
to standard, Burkholderia mallei, and Yersinia pestis. Using 16s rRNA genes that are specific-DNA sequence, these specific sequences are
conserved sequences and used in PCR as universal primers. For pathogen and sensitivity real-time PCR an amazing tool. Information systems
might identify the data of outbreaks and storage of disease information that helps in the control of life-threatening diseases via automatic
monitoring system, detection or occurrence of disease in many groups. Bio-war does not something new that is going away, it’s needed highly
advance technology to end the bioterrorist threats with due highly effect the population survives. The modification should be brought in field of
diagnosis, microbial identification, public health, antimicrobial therapies, surveillance and enhance immunizing systems that control relevant
infections. Appropriate reporting system or data-bases should be installed in cities, states and national even at the international level where data
must be rewarded and provide guidelines by the Centers for Disease Control and Prevention for the prevention of bioterrorism attack or outbreaks.
... While biosurveillance systems are most often used to detect and monitor natural diseases, they can also be used to detect bioterrorism events. Bioterrorism, as defined by Evans (2010), "refers to the intentional release of organisms that can cause sickness or death." Shmueli and Burkom (2010) caution that complications can arise from the intended dual use of biosurveillance systems for detecting natural outbreaks and bioterror-related illnesses. ...
The Monterey County Health Department (MCHD) in California uses the Early Aberration Reporting System (EARS) to monitor emergency room and clinic data for biosurveillance, particularly as an alert system for various types of disease outbreaks. The flexibility of the system has proven to be a very useful feature of EARS; however, little research has been conducted to assess its performance. In this thesis, a quantitative analysis based on modifications to EARS' internal logic and algorithms is assessed. Logic is used as a counting tool for potential cases of outbreak, and the Early Event Detection (EED) algorithms are used to determine whether or not an outbreak is about to occur. The EED methods are compared by assessing their ability to detect the presence of a known H1N1 outbreak in Monterey County. This research found the cumulative sum (CUSUM) detection method to be the most reliable in signaling the H1N1 outbreak, across all combinations of logic explored.
An automated early warning system has been developed and used for detecting clusters of human infection with enteric pathogens. The method used requires no specific disease modelling, and has the potential for extension to other epidemiological applications. A compound smoothing technique is used to determine baseline 'normal' incidence of disease from past data, and a warning threshold for current data is produced by combining a statistically determined increment from the baseline with a fixed minimum threshold. A retrospective study of salmonella infections over 3 years has been conducted. Over this period, the automated system achieved > 90% sensitivity, with a positive predictive value consistently > 50%, demonstrating the effectiveness of the combination of statistical and heuristic methods for cluster detection. We suggest that quantitative measurements are of considerable utility in evaluating the performance of such systems.
From October 4 to November 2, 2001, the first 10 confirmed cases of inhalational anthrax caused by intentional release of Bacillus anthracis were identified in the United States. Epidemiologic investigation indicated that the outbreak, in the District of Columbia, Florida, New Jersey, and New York, resulted from intentional delivery of B. anthracis spores through mailed letters or packages. We describe the clinical presentation and course of these cases of bioterrorism-related inhalational anthrax. The median age of patients was 56 years (range 43 to 73 years), 70% were male, and except for one, all were known or believed to have processed, handled, or received letters containing B. anthracis spores. The median incubation period from the time of exposure to onset of symptoms, when known (n=6), was 4 days (range 4 to 6 days). Symptoms at initial presentation included fever or chills (n=10), sweats (n=7), fatigue or malaise (n=10), minimal or nonproductive cough (n=9), dyspnea (n=8), and nausea or vomiting (n=9). The median white blood cell count was 9.8 X 10(3)/mm(3) (range 7.5 to 13.3), often with increased neutrophils and band forms. Nine patients had elevated serum transaminase levels, and six were hypoxic. All 10 patients had abnormal chest X-rays; abnormalities included infiltrates (n=7), pleural effusion (n=8), and mediastinal widening (seven patients). Computed tomography of the chest was performed on eight patients, and mediastinal lymphadenopathy was present in seven. With multidrug antibiotic regimens and supportive care, survival of patients (60%) was markedly higher (<15%) than previously reported.
An outbreak of anthrax occurred in the city of Sverdlovsk in Russia in the spring of 1979. The outbreak was due to the inhalation of spores that were accidentally released from a military microbiology facility. In response to the outbreak a public health intervention was mounted that included distribution of antibiotics and vaccine. The objective of this paper is to develop and apply statistical methodology to analyse the Sverdlovsk outbreak, and in particular to estimate the incubation period of inhalational anthrax and the number of deaths that may have been prevented by the public health intervention. The data available for analysis from this common source epidemic are the incubation periods of reported deaths. The statistical problem is that incubation periods are truncated because some individuals may have had their deaths prevented by the public health interventions and thus are not included in the data. However, it is not known how many persons received the intervention or how efficacious was the intervention. A likelihood function is formulated that accounts for the effects of truncation. The likelihood is decomposed into a binomial likelihood with unknown sample size and a conditional likelihood for the incubation periods. The methods are extended to allow for a phase-in of the intervention over time. Assuming a lognormal model for the incubation period distribution, the median and mean incubation periods were estimated to be 11.0 and 14.2 days respectively. These estimates are longer than have been previously reported in the literature. The death toll from the Sverdlovsk anthrax outbreak could have been about 14% larger had there not been a public health intervention; however, the confidence intervals are wide (95% CI 0-61%). The sensitivity of the results to model assumptions and the parametric model for the incubation period distribution are investigated. The results are useful for determining how long antibiotic therapy should be continued in suspected anthrax cases and also for estimating the ultimate number of deaths in a new outbreak in the absence of any public health interventions.
Outbreaks of infectious diseases must be detected early for effective control measures to be introduced. When dealing with large amounts of data, automated procedures can usefully supplement traditional surveillance methods, provided that the wide variety of patterns and frequencies of infections are taken into account. This paper describes a robust system developed to process weekly reports of infections received at the Communicable Disease Surveillance Centre. A simple regression algorithm is used to calculate suitable thresholds. Organisms exceeding their threshold are then flagged for further investigation.
Routine analysis of public health surveillance data to detect departures from historical patterns of disease frequency is required to enable timely public health responses to decrease unnecessary morbidity and mortality. We describe a monitoring system incorporating statistical 'flags' identifying unusually large increases (or decreases) in disease reports compared to the number of cases expected. The two-stage monitoring system consists of univariate Box-Jenkins models and subsequent tracking signals from several statistical process control charts. The analyses are illustrated on 1980-1995 national notifiable disease data reported weekly to the Centers for Disease Control and Prevention (CDC) by state health departments and published in CDC's Morbidity and Mortality Weekly Report. Published in 1999 by John Wiley & Sons, Ltd. This article is a U.S. Government work and is in the public domain in the United States.
The anthrax outbreak in the United States in fall 2001 resulted from the intentional dissemination of Bacillus anthracis spores ([1][1]). In response to the outbreak, public health authorities recommended that some groups of individuals undergo a 60-day regimen of antimicrobial prophylaxis (AP) ([2
The recent series of anthrax attacks has reinforced the importance of biosurveillance systems for the timely detection of epidemics. This paper describes a statistical framework for monitoring grocery data to detect a large-scale but localized bioterrorism attack. Our system illustrates the potential of data sources that may be more timely than traditional medical and public health data. The system includes several layers, each customized to grocery data and tuned to finding footprints of an epidemic. We also propose an evaluation methodology that is suitable in the absence of data on large-scale bioterrorist attacks and disease outbreaks.
Most disease registries are updated at least yearly. If a geographically localized health hazard suddenly occurs, we would like to have a surveillance system in place that can pick up a new geographical disease cluster as quickly as possible, irrespective of its location and size. At the same time, we want to minimize the number of false alarms. By using a space–time scan statistic, we propose and illustrate a system for regular time periodic disease surveillance to detect any currently ‘active’ geographical clusters of disease and which tests the statistical significance of such clusters adjusting for the multitude of possible geographical locations and sizes, time intervals and time periodic analyses. The method is illustrated on thyroid cancer among men in New Mexico 1973–1992.
Early Statistical Detection of Anthrax Outbreaks by Tracking Over-the-Counter Medication Sales
- A Goldenberg
- G Shmueli
- R A Caruana
- S E Fienberg
Goldenberg A. Shmueli G. Caruana RA. Fienberg SE. Early Statistical
Detection of Anthrax Outbreaks by Tracking Over-the-Counter Medication
Sales. Proceedings of the National Academy of Sciences of the United States
of America, 2002, 99(8):5237-40.