Prioritizing Risks and Uncertainties from Intentional Release of Selected Category A Pathogens

Abstract

This paper synthesizes available information on five Category A pathogens (Bacillus anthracis, Yersinia pestis, Francisella tularensis, Variola major and Lassa) to develop quantitative guidelines for how environmental pathogen concentrations may be related to human health risk in an indoor environment. An integrated model of environmental transport and human health exposure to biological pathogens is constructed which 1) includes the effects of environmental attenuation, 2) considers fomite contact exposure as well as inhalational exposure, and 3) includes an uncertainty analysis to identify key input uncertainties, which may inform future research directions. The findings provide a framework for developing the many different environmental standards that are needed for making risk-informed response decisions, such as when prophylactic antibiotics should be distributed, and whether or not a contaminated area should be cleaned up. The approach is based on the assumption of uniform mixing in environmental compartments and is thus applicable to areas sufficiently removed in time and space from the initial release that mixing has produced relatively uniform concentrations. Results indicate that when pathogens are released into the air, risk from inhalation is the main component of the overall risk, while risk from ingestion (dermal contact for B. anthracis) is the main component of the overall risk when pathogens are present on surfaces. Concentrations sampled from untracked floor, walls and the filter of heating ventilation and air conditioning (HVAC) system are proposed as indicators of previous exposure risk, while samples taken from touched surfaces are proposed as indicators of future risk if the building is reoccupied. A Monte Carlo uncertainty analysis is conducted and input-output correlations used to identify important parameter uncertainties. An approach is proposed for integrating these quantitative assessments of parameter uncertainty with broader, qualitative considerations to identify future research priorities.

Quantitative Models of the Dose-Response and Time Course of Inhalational Anthrax in Humans

“…Different model forms can lead to very different extrapolated estimates from the same set of data. This creates substantial uncertainty regarding the minimum dose required to cause infection in humans [20] and the dose-dependent time from exposure to appearance of illness (incubation period), key parameters required for sound risk assessment by public health and emergency preparedness authorities [12], [21].…”

Application of quantitative microbial risk assessment for selection of microbial reduction targets for hard surface disinfectants

“…2 QMRA also provides a mechanism for developing technically informed disinfection goals for surface hygiene and safety. 3,4 Fomites have been recognized as important in the spread of infectious disease, particularly through fomiteehand interactions and are common concerns in environments of high contacts (touches) with such pathogens as norovirus, influenza, and rotavirus, as well as and methicillin-resistant Staphylococcus aureus (MRSA). [5][6][7][8][9][10][11][12][13][14] Fomites have been associated with infectious disease outbreaks in such venues as cruise ships, restaurants and nursing homes, 15 schools, 16,17 daycare centers, 18 and gyms.…”

Development of Failure Scenarios for Biosolids Land Application Risk Assessment

“…Although the authors of this study are not aware of evidence that this is a practical concern for biosolids, existing literature studies do support the concept that non-detectable levels of pathogens might correspond to widely varying risk levels. Hong et al (2012) found that the detection limit for a pathogen can range from a risk on the order of 1 in 100 000 to a risk on the order of 1 in 10, depending on the pathogen. The expert who raised this concern explained that the issue could be addressed by establishing more rigorous and uniform sample size requirements for pathogen testing in Class A biosolids (see Hong et al, 2010 andHuang et al, 2010 for examples of how sampling requirements can be designed to meet risk targets), or by requiring specific treatment processes be used to achieve Class A status (i.e., eliminating the option of achieving Class A requirements based on testing alone).…”