Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making.

The United States Department of Agriculture (USDA) Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents (Select Agents List) that threaten crops of economic importance to the United States and regulates the procedures governing containment, incident response, and the security of entities working with them. Every 2 years the USDA DASAT reviews their select agent list, utilizing assessments by subject matter experts (SMEs) to rank the agents. We explored the applicability of multi-criteria decision analysis (MCDA) techniques and a decision support framework (DSF) to support the USDA DASAT biennial review process. The evaluation includes both current and non-select agents to provide a robust assessment. We initially conducted a literature review of 16 pathogens against 9 criteria for assessing plant health and bioterrorism risk and documented the findings to support this analysis. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for ensuring accuracy. Scoring criteria were adopted to ensure consistency. The MCDA supported the expectation that select agents would rank high on the relative risk scale when considering the agricultural consequences of a bioterrorism attack; however, application of analytical thresholds as a basis for designating select agents led to some exceptions to current designations. A second analytical approach used agent-specific data to designate key criteria in a DSF logic tree format to identify pathogens of low concern that can be ruled out for further consideration as select agents. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.

Application of multi-criteria decision analysis techniques and decision support framework for informing select agent designation for agricultural animal pathogens.

The United States Department of Agriculture (USDA), Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents and toxins (Select Agent List) that potentially threaten agricultural health and safety, the procedures governing the transfer of those agents, and training requirements for entities working with them. Every 2 years the USDA DASAT reviews the Select Agent List, using subject matter experts (SMEs) to perform an assessment and rank the agents. To assist the USDA DASAT biennial review process, we explored the applicability of multi-criteria decision analysis (MCDA) techniques and a Decision Support Framework (DSF) in a logic tree format to identify pathogens for consideration as select agents, applying the approach broadly to include non-select agents to evaluate its robustness and generality. We conducted a literature review of 41 pathogens against 21 criteria for assessing agricultural threat, economic impact, and bioterrorism risk and documented the findings to support this assessment. The most prominent data gaps were those for aerosol stability and animal infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. The MCDA analysis supported the intuitive sense that select agents should rank high on the relative risk scale when considering agricultural health consequences of a bioterrorism attack. However, comparing select agents with non-select agents indicated that there was not a clean break in scores to suggest thresholds for designating select agents, requiring subject matter expertise collectively to establish which analytical results were in good agreement to support the intended purpose in designating select agents. The DSF utilized a logic tree approach to identify pathogens that are of sufficiently low concern that they can be ruled out from consideration as a select agent. In contrast to the MCDA approach, the DSF rules out a pathogen if it fails to meet even one criteria threshold. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.

The development and use of decision support framework for informing selection of select agent toxins with modelling studies to inform permissible toxin amounts.

Many countries have worked diligently to establish and implement policies and processes to regulate high consequence pathogens and toxins that could have a significant public health impact if misused. In the United States, the Antiterrorism and Effective Death Penalty Act of 1996 (Public Law 104-132, 1996), as amended by the Bioterrorism Preparedness and Response Act of 2002 (Public Law 107-188, 2002) requires that the Department of Health and Human Services (HHS) [through the Centers for Disease Control and Prevention (CDC)] establish a list of bacteria, viruses, and toxins that have the potential to pose a severe threat to public health and safety. Currently, this list is reviewed and updated on a biennial basis using input from subject matter experts (SMEs). We have developed decision support framework (DSF) approaches to facilitate selection of select toxins and, where toxicity data are known, conducted modelling studies to inform selection of toxin amounts that should be excluded from select agent regulations. Exclusion limits allow laboratories to possess toxins under an established limit to support their research or teaching activities without the requirement to register with the Federal Select Agent Program. Fact sheets capturing data from a previously vetted SME workshop convened by CDC, literature review and SME input were developed to assist in evaluating toxins using the DSF approach. The output of the DSF analysis agrees with the current select toxin designations, and no other toxins evaluated in this study were recommended for inclusion on the select agent and toxin list. To inform the selection of exclusion limits, attack scenarios were developed to estimate the amount of toxin needed to impact public health. Scenarios consisted of simulated aerosol releases of a toxin in high-population-density public facilities and the introduction of a toxin into a daily consumable product supply chain. Using published inhalation and ingestion median toxic dose (TD50) and median lethal dose (LD50) values, where available, a range of toxin amounts was examined to estimate the number of people exposed to these amounts in these scenarios. Based on data generated by these models, we proposed toxin exclusion values corresponding to levels below those that would trigger a significant public health response (i.e., amounts estimated to expose up to ten people by inhalation or one hundred people by ingestion to LD50 or TD50 levels of toxin in the modeled scenarios).

The NYC native air sampling pilot project: using HVAC filter data for urban biological incident characterization.

Native air sampling (NAS) is distinguished from dedicated air sampling (DAS) devices (eg, BioWatch) that are deployed to detect aerosol disseminations of biological threat agents. NAS uses filter samples from heating, ventilation, and air conditioning (HVAC) systems in commercial properties for environmental sampling after DAS detection of biological threat agent incidents. It represents an untapped, scientifically sound, efficient, widely distributed, and comparably inexpensive resource for postevent environmental sampling. Calculations predict that postevent NAS would be more efficient than environmental surface sampling by orders of magnitude. HVAC filter samples could be collected from pre-identified surrounding NAS facilities to corroborate the DAS alarm and delineate the path taken by the bioaerosol plume. The New York City (NYC) Native Air Sampling Pilot Project explored whether native air sampling would be acceptable to private sector stakeholders and could be implemented successfully in NYC. Building trade associations facilitated outreach to and discussions with property owners and managers, who expedited contact with building managers of candidate NAS properties that they managed or owned. Nominal NAS building requirements were determined; procedures to identify and evaluate candidate NAS facilities were developed; data collection tools and other resources were designed and used to expedite candidate NAS building selection and evaluation in Manhattan; and exemplar environmental sampling playbooks for emergency responders were completed. In this sample, modern buildings with single or few corporate tenants were the best NAS candidate facilities. The Pilot Project successfully demonstrated that in one urban setting a native air sampling strategy could be implemented with effective public-private collaboration.

Assessment of potential fumigants to control Chaetodactylus krombeini (Acari: Chaetodactylidae) associated with Osmia cornifrons (Hymenoptera: Megachilidae).

With the recent decline of honey bees, Apis mellifera (L.) (Hymenoptera: Apidae), there is a need for alternative or supplemental crop pollinators, such as Osmia cornifrons (Radoszkowski) (Hymenoptera: Megachilidae). However, O. cornifrons propagation could be impeded by a cleptoparasitic mite, Chaetodactylus krombeini Baker. We investigated the effects of formic acid and wintergreen oil on mortality of C. krombeini hypopi and O. cornifrons adults by determining the lethal concentration of each compound on each species. On average, >4.8 and >1.8 h were required to cause mortality in O. cornifrons adults when <2,473.5 ppm of formic acid and wintergreen oil was applied as a fumigant, respectively. When the two chemicals were directly applied to the exoskeleton of O. cornifrons adults, 353.4 ppm of wintergreen oil caused bee mortality within 10 min; however, no mortality was found with any formic acid application attempted. Mortality of C. krombeini hypopi occurred 5 and 10 min after application of >176.7 ppm of formic acid and wintergreen oil, respectively. Estimates of LC50 for C. krombeini hypopi treated with formic acid and wintergreen oil were 54.3 and 271.3 ppm, respectively. This study showed that C. krombeini could be controlled effectively without inducing O. cornifrons adult mortality based on concentration and duration of fumigation.

Overview of electrochemical DNA biosensors: new approaches to detect the expression of life.

DNA microarrays are an important tool with a variety of applications in gene expression studies, genotyping, pharmacogenomics, pathogen classification, drug discovery, sequencing and molecular diagnostics. They are having a strong impact in medical diagnostics for cancer, toxicology and infectious disease applications. A series of papers have been published describing DNA biochips as alternative to conventional microarray platforms to facilitate and ameliorate the signal readout. In this review, we will consider the different methods proposed for biochip construction, focusing on electrochemical detection of DNA. We also introduce a novel single-stranded DNA platform performing high-throughput SNP detection and gene expression profiling.