Use of outcomes to evaluate surveillance systems for bioterrorist attacks

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.

Biological warfare: the history of microbial pathogens, biotoxins and emerging threats

Bioterrorism is the deliberate misuse of a pathogen (virus, bacterium or other disease-causing microorganisms) or biotoxin (poisonous substance produced by an organism) to cause illness and death amongst the population. Bioterrorism and biological warfare (biowarfare) are terms often used interchangeably. However, bioterrorism is typically attributed to the politically motivated use of biological weapons by a rogue state, terrorist organisation or rogue individual whereas biological warfare refers to a country’s use of bioweapons. Although rare, bioterrorism is a rapidly evolving threat to global security due to significant advancements in biotechnology in recent years and the severity of agents that could be exploited. The pursuit of publicity plays a vital role in bioterrorism. The success of a biological attack is often calculated by the extent of terror resulting from the event, psychological disruption of society and political breakdown, rather than the lethal effects of the agent used.

The current state of bioterrorist attack surveillance and preparedness in the US

The use of biological agents as weapons to disrupt established structures, such as governments and especially larger urban populations, has been prevalent throughout history. Following the anthrax letters sent to various government officials in the fall of 2001, the US has been investing in prevention, surveillance, and preparation for a potential bioterrorism attack. Additional funding authorized since 2002 has assisted the Centers for Disease Control and Prevention, the Department of Health and Human Services, and the Environmental Protection Agency to invest in preventative research measures as well as preparedness programs, such as the Laboratory Response Network, Hospital Preparedness Program, and BioWatch. With both sentinel monitoring systems and epidemiological surveillance programs in place for metropolitan areas, the immediate threat of a large-scale bioterrorist attack may be limited. However, early detection is a crucial factor to initiate immediate response measures to prevent further spread following dissemination of a biological agent. Especially in rural areas, an interagency approach to train health care workers and raise awareness for the general public remain primary tasks, which is an ongoing challenge. Risk-management approaches in responding to dissemination of biological agents, as well as appropriate decontamination measures that reduce the probability of further contamination, have been provided, and suggest further investments in preparedness and surveillance. Ongoing efforts to improve preparedness and response to a bioterrorist attack are crucial to further reduce morbidity, mortality, and economic impact on public health.

Comparing the accuracy of syndrome surveillance systems in detecting influenza-like illness: GUARDIAN vs. RODS vs. electronic medical record reports

BACKGROUND

A highly sensitive real-time syndrome surveillance system is critical to detect, monitor, and control infectious disease outbreaks, such as influenza. Direct comparisons of diagnostic accuracy of various surveillance systems are scarce.

OBJECTIVE

To statistically compare sensitivity and specificity of multiple proprietary and open source syndrome surveillance systems to detect influenza-like illness (ILI).

METHODS

A retrospective, cross-sectional study was conducted utilizing data from 1122 patients seen during November 1–7, 2009 in the emergency department of a single urban academic medical center. The study compared the Geographic Utilization of Artificial Intelligence in Real-time for Disease Identification and Alert Notification (GUARDIAN) system to the Complaint Coder (CoCo) of the Real-time Outbreak Detection System (RODS), the Symptom Coder (SyCo) of RODS, and to a standardized report generated via a proprietary electronic medical record (EMR) system. Sensitivity, specificity, and accuracy of each classifier's ability to identify ILI cases were calculated and compared to a manual review by a board-certified emergency physician. Chi-square and McNemar's tests were used to evaluate the statistical difference between the various surveillance systems.ResultsThe performance of GUARDIAN in detecting ILI in terms of sensitivity, specificity, and accuracy, as compared to a physician chart review, was 95.5%, 97.6%, and 97.1%, respectively. The EMR-generated reports were the next best system at identifying disease activity with a sensitivity, specificity, and accuracy of 36.7%, 99.3%, and 83.2%, respectively. RODS (CoCo and SyCo) had similar sensitivity (35.3%) but slightly different specificity (CoCo = 98.9%; SyCo = 99.3%). The GUARDIAN surveillance system with its multiple data sources performed significantly better compared to CoCo (χ2 = 130.6, p < 0.05), SyCo (χ2 = 125.2, p < 0.05), and EMR-based reports (χ2 = 121.3, p < 0.05). In addition, similar significant improvements in the accuracy (>12%) and sensitivity (>47%) were observed for GUARDIAN with only chief complaint data as compared to RODS (CoCo and SyCo) and EMR-based reports.

CONCLUSION

In our study population, the GUARDIAN surveillance system, with its ability to utilize multiple data sources from patient encounters and real-time automaticity, demonstrated a more robust performance when compared to standard EMR-based reports and the RODS systems in detecting ILI. More large-scale studies are needed to validate the study findings, and to compare the performance of GUARDIAN in detecting other infectious diseases.

Integration of syndromic surveillance data into public health practice at state and local levels in North Carolina

OBJECTIVES

We sought to describe the integration of syndromic surveillance data into daily surveillance practice at local health departments (LHDs) and make recommendations for the effective integration of syndromic and reportable disease data for public health use.

METHODS

Structured interviews were conducted with local health directors and communicable disease nursing staff from a stratified random sample of LHDs from May through September 2009. Interviews captured information on direct access to the North Carolina syndromic surveillance system and on the use of syndromic surveillance information for outbreak management, program management, and the creation of reports. We analyzed syndromic surveillance system data to assess the number of signals resulting in a public health response.

RESULTS

Syndromic surveillance data were used for outbreak investigation (19% of respondents) and program management and report writing (43% of respondents); a minority reported use of both syndromic and reportable disease data for these purposes (15% and 23%, respectively). Receiving data from frequent system users was associated with using data for these purposes (p=0.016 and p=0.033, respectively, for syndromic and reportable disease data). A small proportion of signals (<25%) resulted in a public health response.

CONCLUSIONS

Use of syndromic surveillance data by North Carolina local public health authorities resulted in meaningful public health action, including both case investigation and program management. While useful, the syndromic surveillance data system was oriented toward sensitivity rather than efficiency. Successful incorporation of new surveillance data is likely to require systems that are oriented toward efficiency.

The potential economic value of a Staphylococcus aureus vaccine among hemodialysis patients

Staphylococcus aureus infections are a substantial problem for hemodialysis patients. Several vaccine candidates are currently under development, with hemodialysis patients being one possible target population. To determine the potential economic value of an S. aureus vaccine among hemodialysis patients, we developed a Markov decision analytic computer simulation model. When S. aureus colonization prevalence was 1%, the incremental cost-effectiveness ratio (ICER) of vaccination was ≤$25,217/quality-adjusted life year (QALY). Vaccination became more cost-effective as colonization prevalence, vaccine efficacy, or vaccine protection duration increased or vaccine cost decreased. Even at 10% colonization prevalence, a 25% efficacious vaccine costing $100 prevented 29 infections, 21 infection-related hospitalizations, and 9 inpatient deaths per 1000 vaccinated HD patients. Our results suggest that an S. aureus vaccine would be cost-effective (i.e., ICERs ≤ $50,000/QALY) among hemodialysis patients over a wide range of S. aureus prevalence, vaccine costs and efficacies, and vaccine protection durations and delineate potential target parameters for such a vaccine.