Research gaps and priorities for quantitative microbial risk assessment (QMRA).

The coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose-response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co-exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source-to-outcome continuum. Cross-cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.

A microbial risk assessor's guide to Valley Fever (Coccidioides spp.): Case study and review of risk factors.

Valley Fever is a respiratory disease caused by inhalation of arthroconidia, a type of spore produced by fungi within the genus Coccidioides spp. which are found in dry, hot ecosystems of the Western Hemisphere. A quantitative microbial risk assessment (QMRA) for the disease has not yet been performed due to a lack of dose-response models and a scarcity of quantitative occurrence data from environmental samples. A literature review was performed to gather data on experimental animal dosing studies, environmental occurrence, human disease outbreaks, and meteorological associations. As a result, a risk framework is presented with information for parameterizing QMRA models for Coccidioides spp., with eight new dose-response models proposed. A probabilistic QMRA was conducted for a Southwestern US agricultural case study, evaluating eight scenarios related to farming occupational exposures. Median daily workday risks for developing severe Valley Fever ranged from 2.53 × 10-7 (planting by hand while wearing an N95 facemask) to 1.33 × 10-3 (machine harvesting while not wearing a facemask). The literature review and QMRA synthesis confirmed that exposure to aerosolized arthroconidia has the potential to result in high attack rates but highlighted that the mechanistic relationships between environmental conditions and disease remain poorly understood. Recommendations for Valley Fever risk assessment research needs in order to reduce disease risks are discussed, including interventions for farmers.

Tenets of a holistic approach to drinking water-associated pathogen research, management, and communication.

In recent years, drinking water-associated pathogens that can cause infections in immunocompromised or otherwise susceptible individuals (henceforth referred to as DWPI), sometimes referred to as opportunistic pathogens or opportunistic premise plumbing pathogens, have received considerable attention. DWPI research has largely been conducted by experts focusing on specific microorganisms or within silos of expertise. The resulting mitigation approaches optimized for a single microorganism may have unintended consequences and trade-offs for other DWPI or other interests (e.g., energy costs and conservation). For example, the ecological and epidemiological issues characteristic of Legionella pneumophila diverge from those relevant for Mycobacterium avium and other nontuberculous mycobacteria. Recent advances in understanding DWPI as part of a complex microbial ecosystem inhabiting drinking water systems continues to reveal additional challenges: namely, how can all microorganisms of concern be managed simultaneously? In order to protect public health, we must take a more holistic approach in all aspects of the field, including basic research, monitoring methods, risk-based mitigation techniques, and policy. A holistic approach will (i) target multiple microorganisms simultaneously, (ii) involve experts across several disciplines, and (iii) communicate results across disciplines and more broadly, proactively addressing source water-to-customer system management.

A Quantitative Risk Estimation Platform for Indoor Aerosol Transmission of COVID-19.

Aerosol transmission has played a significant role in the transmission of COVID-19 disease worldwide. We developed a COVID-19 aerosol transmission risk estimation model to better understand how key parameters associated with indoor spaces and infector emissions affect inhaled deposited dose of aerosol particles that convey the SARS-CoV-2 virus. The model calculates the concentration of size-resolved, virus-laden aerosol particles in well-mixed indoor air challenged by emissions from an index case(s). The model uses a mechanistic approach, accounting for particle emission dynamics, particle deposition to indoor surfaces, ventilation rate, and single-zone filtration. The novelty of this model relates to the concept of "inhaled & deposited dose" in the respiratory system of receptors linked to a dose-response curve for human coronavirus HCoV-229E. We estimated the volume of inhaled & deposited dose of particles in the 0.5-4 µm range expressed in picoliters (pL) in a well-documented COVID-19 outbreak in restaurant X in Guangzhou China. We anchored the attack rate with the dose-response curve of HCoV-229E which provides a preliminary estimate of the average SARS-CoV-2 dose per person, expressed in plaque forming units (PFUs). For a reasonable emission scenario, we estimate approximately three PFU per pL deposited, yielding roughly 10 PFUs deposited in the respiratory system of those infected in restaurant X. To explore the model's utility, we tested it with four COVID-19 outbreaks. The risk estimates from the model fit reasonably well with the reported number of confirmed cases given available metadata from the outbreaks and uncertainties associated with model assumptions.

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance.

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Legionnaires' disease in dental offices: Quantifying aerosol risks to dental workers and patients.

Legionella pneumophila is an opportunistic bacterial respiratory pathogen that is one of the leading causes of drinking water outbreaks in the United States. Dental offices pose a potential risk for inhalation or aspiration of L. pneumophila due to the high surface area to volume ratio of dental unit water lines-a feature that is conducive to biofilm growth. This is coupled with the use of high-pressure water devices (e.g., ultrasonic scalers) that produce fine aerosols within the breathing zone. Prior research confirms that L. pneumophila occurs in dental unit water lines, but the associated human health risks have not been assessed. We aimed to: (1) synthesize the evidence for transmission and management of Legionnaires' disease in dental offices; (2) create a quantitative modeling framework for predicting associated L. pneumophila infection risk; and (3) highlight influential parameters and research gaps requiring further study. We reviewed outbreaks, management guidance, and exposure studies and used these data to parameterize a quantitative microbial risk assessment (QMRA) model for L. pneumophila in dental applications. Probabilities of infection for dental hygienists and patients were assessed on a per-exposure and annual basis. We also assessed the impact of varying ventilation rates and the use of personal protective equipment (PPE). Following an instrument purge (i.e., flush) and with a ventilation rate of 1.2 air changes per hour, the median per-exposure probability of infection for dental hygienists and patients exceeded a 1-in-10,000 infection risk benchmark. Per-exposure risks for workers during a purge and annual risks for workers wearing N95 masks did not exceed the benchmark. Increasing air change rates in the treatment room from 1.2 to 10 would achieve an ∼85% risk reduction, while utilization of N95 respirators would reduce risks by ∼95%. The concentration of L. pneumophila in dental unit water lines was a dominant parameter in the model and driver of risk. Future risk assessment efforts and refinement of microbiological control protocols would benefit from expanded occurrence datasets for L. pneumophila in dental applications.

Reproducibility and sensitivity of 36 methods to quantify the SARS-CoV-2 genetic signal in raw wastewater: findings from an interlaboratory methods evaluation in the U.S.

In response to COVID-19, the international water community rapidly developed methods to quantify the SARS-CoV-2 genetic signal in untreated wastewater. Wastewater surveillance using such methods has the potential to complement clinical testing in assessing community health. This interlaboratory assessment evaluated the reproducibility and sensitivity of 36 standard operating procedures (SOPs), divided into eight method groups based on sample concentration approach and whether solids were removed. Two raw wastewater samples were collected in August 2020, amended with a matrix spike (betacoronavirus OC43), and distributed to 32 laboratories across the U.S. Replicate samples analyzed in accordance with the project's quality assurance plan showed high reproducibility across the 36 SOPs: 80% of the recovery-corrected results fell within a band of ±1.15 log10 genome copies per L with higher reproducibility observed within a single SOP (standard deviation of 0.13 log10). The inclusion of a solids removal step and the selection of a concentration method did not show a clear, systematic impact on the recovery-corrected results. Other methodological variations (e.g., pasteurization, primer set selection, and use of RT-qPCR or RT-dPCR platforms) generally resulted in small differences compared to other sources of variability. These findings suggest that a variety of methods are capable of producing reproducible results, though the same SOP or laboratory should be selected to track SARS-CoV-2 trends at a given facility. The methods showed a 7 log10 range of recovery efficiency and limit of detection highlighting the importance of recovery correction and the need to consider method sensitivity when selecting methods for wastewater surveillance.

Action Levels for SARS-CoV-2 in Air: Preliminary Approach.

Quantitative microbial risk assessment has been used to develop criteria for exposure to many microorganisms. In this article, the dose-response curve for Coronavirus 229E is used to develop preliminary risk-based exposure criteria for SARS-CoV-2 via the respiratory portals of entry.

Application of QMRA to MAR operations for safe agricultural water reuses in coastal areas.

A pathogenic Escherichia coli (E.coli) O157:H7 and O26:H11 dose-response model was set up for a quantitative microbial risk assessment (QMRA) of the waterborne diseases associated with managed aquifer recharge (MAR) practices in semiarid regions. The MAR facility at Forcatella (Southern Italy) was selected for the QMRA application. The target counts of pathogens incidentally exposed to hosts by eating contaminated raw crops or while bathing at beaches of the coastal area were determined by applying the Monte Carlo Markov Chain (MCMC) Bayesian method to the water sampling results. The MCMC provided the most probable pathogen count reaching the target and allowed for the minimization of the number of water samplings, and hence, reducing the associated costs. The sampling stations along the coast were positioned based on the results of a groundwater flow and pathogen transport model, which highlighted the preferential flow pathways of the transported E. coli in the fractured coastal aquifer. QMRA indicated tolerable (<10-6 DALY) health risks for bathing at beaches and irrigation with wastewater, with 0.4 infectious diseases per year (11.4% probability of occurrence) associated with the reuse of reclaimed water via soil irrigation even though exceeding the E. coli regulation limit of 10 CFU/100 mL by five times. The results show negligible health risk and insignificant impacts on the coastal water quality due to pathogenic E. coli in the wastewater used for MAR. However, droughts and reclaimed water quality can be considered the main issues of MAR practices in semiarid regions suggesting additional reclaimed water treatments and further stress-tests via QMRAs by considering more persistent pathogens than E. coli.

Required water temperature in hotel plumbing to control Legionella growth.

Legionella spp. occurring in hotel hot water systems, in particular Legionella pneumophila, are causing serious pneumonic infections, and water temperature is a key factor to control their occurrence in plumbing systems. We performed a systematic review and meta-analyses of the available evidence on the association between water temperature and Legionella colonization to identify the water temperature in hotel hot water systems required for control of Legionella. Qualitative synthesis and quantitative analysis were performed on 13 studies that met our inclusion criteria to identify the effect of temperature. The Receiver Operating Characteristic (ROC) curve identified 55 °C as a cutoff point for hotel hot water temperature with an Area Under the Curve (AUC) value of 0.914. The odds ratios (OR) for detecting Legionella at temperatures >55 °C compared to lower temperatures from a meta-analysis of three studies was 0.17 [95% CI: 0.11, 0.25], which indicates a strong negative association between temperature and Legionella colonization. A logistic regression on results from multiple studies using both molecular and culture methods found a temperature of 59 °C associated with an 8% probability of detectable Legionella. Only two studies reported sufficiently detailed data to allow a model of concentration vs. temperature to be fit, and this model was not statistically significant. Additional research or more detailed reporting of existing datasets is required to assess if Legionella growth can be limited below particular concentration targets at different temperatures.

Quantitative Microbial Risk Assessment and Molecular Biology: Paths to Integration.

Quantitative microbial risk assessment (QMRA) has now been in use for over 35 years and has formed the basis for developing criteria for ensuring public health related to water, food, and remediation, to name a few areas. The initial data for QMRA (both in exposure assessment and in dose response assessment) came from measurements using assays for viability, such as plate counts, plaque assays, or animal infectivity. With the increasing use of molecular methods for the measurement of microorganisms in the environment, it has become important to assess how to use such data to estimate infectious disease risks. The limitations to the use of such data and needs to resolve the limitations will be addressed.

Heavy precipitation, drinking water source, and acute gastrointestinal illness in Philadelphia, 2015-2017.

Runoff from heavy precipitation events can lead to microbiological contamination of source waters for public drinking water supplies. Philadelphia is a city of interest for a study of waterborne acute gastrointestinal illness (AGI) because of frequent heavy precipitation, extensive impervious landcover, and combined sewer systems that lead to overflows. We conducted a time-series analysis of the association between heavy precipitation and AGI incidence in Philadelphia, served by drinking water from Delaware River and Schuylkill River source waters. AGI cases on each day during the study period (2015-2017) were captured through syndromic surveillance of patients' chief complaint upon presentation at local emergency departments. Daily precipitation was represented by measurements at the Philadelphia International Airport and by modeled precipitation within the watershed boundaries, and we also evaluated stream flowrate as a proxy of precipitation. We estimated the association using distributed lag nonlinear models, assuming a quasi-Poisson distribution of the outcome variable and with adjustment for potential confounding by seasonal and long-term time trends, ambient temperature, day-of-week, and major holidays. We observed an association between heavy precipitation and AGI incidence in Philadelphia that was primarily limited to the spring season, with significant increases in AGI that peaked from 8 to 16 days following a heavy precipitation event. For example, the increase in AGI incidence related to airport precipitation above the 95th percentile (vs no precipitation) during spring reached statistical significance on lag day 7, peaked on day 16 (102% increase, 95% confidence interval: 16%, 252%), and declined while remaining significantly elevated through day 28. Similar associations were observed in analyses of watershed-specific precipitation in relation to AGI cases within the populations served by drinking water from each river. Our results suggest that heavy precipitation events in Philadelphia result in detectable local increases in waterborne AGI.

A Case Study Evaluating the Risk of Infection from Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV) in a Hospital Setting Through Bioaerosols.

Middle Eastern respiratory syndrome, an emerging viral infection with a global case fatality rate of 35.5%, caused major outbreaks first in 2012 and 2015, though new cases are continuously reported around the world. Transmission is believed to mainly occur in healthcare settings through aerosolized particles. This study uses Quantitative Microbial Risk Assessment to develop a generalizable model that can assist with interpreting reported outbreak data or predict risk of infection with or without the recommended strategies. The exposure scenario includes a single index patient emitting virus-containing aerosols into the air by coughing, leading to short- and long-range airborne exposures for other patients in the same room, nurses, healthcare workers, and family visitors. Aerosol transport modeling was coupled with Monte Carlo simulation to evaluate the risk of MERS illness for the exposed population. Results from a typical scenario show the daily mean risk of infection to be the highest for the nurses and healthcare workers (8.49 × 10-4 and 7.91 × 10-4 , respectively), and the lowest for family visitors and patients staying in the same room (3.12 × 10-4 and 1.29 × 10-4 , respectively). Sensitivity analysis indicates that more than 90% of the uncertainty in the risk characterization is due to the viral concentration in saliva. Assessment of risk interventions showed that respiratory masks were found to have a greater effect in reducing the risks for all the groups evaluated (>90% risk reduction), while increasing the air exchange was effective for the other patients in the same room only (up to 58% risk reduction).

A quantitative risk assessment method for synthetic biology products in the environment.

The need to prevent possible adverse environmental health impacts resulting from synthetic biology (SynBio) products is widely acknowledged in both the SynBio risk literature and the global regulatory community. To-date, however, discussions of potential risks of SynBio products have been largely speculative, and the limited attempts to characterize the risks of SynBio products have been non-uniform and entirely qualitative. As the SynBio discipline continues to accelerate and bring forth novel, highly-engineered life forms, a standardized risk assessment framework will become critical for ensuring that the environmental risks of these products are characterized in a consistent, reliable, and objective manner that incorporates all SynBio-unique risk factors. In their current forms, established risk assessment frameworks - including those that address traditional genetically modified organisms - fall short of the features required of this standard framework. To address this gap, we propose the Quantitative Risk Assessment Method for Synthetic Biology Products (QRA-SynBio) - an incremental build on established risk assessment methodologies that supplements traditional paradigms with the SynBio risk factors that are currently absent, and necessitates quantitative analysis for more transparent and objective risk characterizations. We demonstrate through a hypothetical case study that the proposed framework facilitates defensible quantification of the environmental risks of SynBio products in both foreseeable and hypothetical use scenarios. Additionally, we show how the quantitative nature of the proposed method can promote increased experimental investigation into the true likelihood of hazard and exposure parameters and highlight the most sensitive parameters where uncertainty should be reduced, ultimately leading to more targeted SynBio risk research and yielding more precise characterizations of risk.

Risk-Based Critical Concentrations of Legionella pneumophila for Indoor Residential Water Uses.

Legionella spp. is a key contributor to the United States waterborne disease burden. Despite potentially widespread exposure, human disease is relatively uncommon, except under circumstances where pathogen concentrations are high, host immunity is low, or exposure to small-diameter aerosols occurs. Water quality guidance values for Legionella are available for building managers but are generally not based on technical criteria. To address this gap, a quantitative microbial risk assessment (QMRA) was conducted using target risk values in order to calculate corresponding critical concentrations on a per-fixture and aggregate (multiple fixture exposure) basis. Showers were the driving indoor exposure risk compared to sinks and toilets. Critical concentrations depended on the dose response model (infection vs clinical severity infection, CSI), risk target used (infection risk vs disability adjusted life years [DALY] on a per-exposure or annual basis), and fixture type (conventional vs water efficient or "green"). Median critical concentrations based on exposure to a combination of toilet, faucet, and shower aerosols ranged from ∼10-2 to ∼100 CFU per L and ∼101 to ∼103 CFU per L for infection and CSI dose response models, respectively. As infection model results for critical L. pneumophila concentrations were often below a feasible detection limit for culture-based assays, the use of CSI model results for nonhealthcare water systems with a 10-6 DALY pppy target (the more conservative target) would result in an estimate of 12.3 CFU per L (arithmetic mean of samples across multiple fixtures and/or over time). Single sample critical concentrations with a per-exposure-corrected DALY target at each conventional fixture would be 1.06 × 103 CFU per L (faucets), 8.84 × 103 CFU per L (toilets), and 14.4 CFU per L (showers). Using a 10-4 annual infection risk target would give a 1.20 × 103 CFU per L mean for multiple fixtures and single sample critical concentrations of 1.02 × 105, 8.59 × 105, and 1.40 × 103 CFU per L for faucets, toilets, and showers, respectively. Annual infection risk-based target estimates are in line with most current guidance documents of less than 1000 CFU per L, while DALY-based guidance suggests lower critical concentrations might be warranted in some cases. Furthermore, approximately <10 CFU per mL L. pneumophila may be appropriate for healthcare or susceptible population settings. This analysis underscores the importance of the choice of risk target as well as sampling program considerations when choosing the most appropriate critical concentration for use in public health guidance.

Comparison of pathogen-derived 'total risk' with indicator-based correlations for recreational (swimming) exposure.

Typical recreational water risk to swimmers is assessed using epidemiologically derived correlations by means of fecal indicator bacteria (FIB). It has been documented that concentrations of FIB do not necessarily correlate well with protozoa and viral pathogens, which pose an actual threat of illness and thus sometimes may not adequately assess the overall microbial risks from water resources. Many of the known pathogens have dose-response relationships; however, measuring water quality for all possible pathogens is impossible. In consideration of a typical freshwater receiving secondarily treated effluent, we investigated the level of consistency between the indicator-derived correlations and the sum of risks from six reference pathogens using a quantitative microbial risk assessment (QMRA) approach. Enterococci and E. coli were selected as the benchmark FIBs, and norovirus, human adenovirus (HAdV), Campylobacter jejuni, Salmonella enterica, Cryptosporidium spp., and Giardia spp. were selected as the reference pathogens. Microbial decay rates in freshwater and uncertainties in exposure relationships were considered in developing our analysis. Based on our exploratory assessment, the total risk was found within the range of risk estimated by the indicator organisms, with viral pathogens as dominant risk agents, followed by protozoan and bacterial pathogens. The risk evaluated in this study captured the likelihood of gastrointestinal illnesses only, and did not address the overall health risk potential of recreational waters with respect to other disease endpoints. Since other highly infectious pathogens like hepatitis A and Legionella spp. were not included in our analysis, these estimates should be interpreted with caution.

Health risks from exposure to Legionella in reclaimed water aerosols: Toilet flushing, spray irrigation, and cooling towers.

The use of reclaimed water brings new challenges for the water industry in terms of maintaining water quality while increasing sustainability. Increased attention has been devoted to opportunistic pathogens, especially Legionella pneumophila, due to its growing importance as a portion of the waterborne disease burden in the United States. Infection occurs when a person inhales a mist containing Legionella bacteria. The top three uses for reclaimed water (cooling towers, spray irrigation, and toilet flushing) that generate aerosols were evaluated for Legionella health risks in reclaimed water using quantitative microbial risk assessment (QMRA). Risks are compared using data from nineteen United States reclaimed water utilities measured with culture-based methods, quantitative PCR (qPCR), and ethidium-monoazide-qPCR. Median toilet flushing annual infection risks exceeded 10-4 considering multiple toilet types, while median clinical severity infection risks did not exceed this value. Sprinkler and cooling tower risks varied depending on meteorological conditions and operational characteristics such as drift eliminator performance. However, the greatest differences between risk scenarios were due to 1) the dose response model used (infection or clinical severity infection) 2) population at risk considered (residential or occupational) and 3) differences in laboratory analytical method. Theoretical setback distances necessary to achieve a median annual infection risk level of 10-4 are proposed for spray irrigation and cooling towers. In both cooling tower and sprinkler cases, Legionella infection risks were non-trivial at potentially large setback distances, and indicate other simultaneous management practices could be needed to manage risks. The sensitivity analysis indicated that the most influential factors for variability in risks were the concentration of Legionella and aerosol partitioning and/or efficiency across all models, highlighting the importance of strategies to manage Legionella occurrence in reclaimed water.

Dose-Response Models for Eastern US, Western US and Venezuelan Equine Encephalitis Viruses in Mice - Part II: Quantification of the Effects of Host Age on the Dose Response.

Many infectious disease hazards demonstrate higher susceptibility with regards to younger host ages. This trend of increased susceptibility with decreasing host age can also lead to an increased likelihood of mortality, and prolonged/chronic health effects. For quantitative microbial risk assessment (QMRA) modeling, the ability to quantify the effect of host age in the dose response model can allow modelers to account for these effects mechanistically. Additionally, QMRA modelers using age-dependent dose response models can model entire populations within the dose-response itself rather than modeling age ranges using susceptibility factors. This research developed host-age dependent exponential and beta Poisson dose response models for Eastern, Western and Venezuelan encephalitis viruses (EEV, WEV and VEV respectively) for two routes - intracranial and intraperitoneal. Improvement in fit was statistically tested as a means of assessing the benefit of including age dependency into the dose response models. EEV demonstrated improvement in fit using host-age dependency only for the exponential model except for intracranial exposure. EEV demonstrated an improvement in fit when using age dependency in the beta Poisson dose response model for both exposure routes. VEV demonstrated an improvement in fit using age dependency for both exposure routes. WEV demonstrated an improvement in fit for intracranial exposure, but neither of the age dependent dose-response models provided a good fit for WEV intraperitoneal exposure.