A Risk Assessment Scheme of Infection Transmission Indoors Incorporating the Impact of Resuspension

A new risk assessment scheme was developed to quantify the impact of resuspension to infection transmission indoors. Airborne and surface pathogenic particle concentration models including the effect of two major resuspension scenarios (airflow‐induced particle resuspension [AIPR] and walking‐induced particle resuspension [WIPR]) were derived based on two‐compartment mass balance models and validated against experimental data found in the literature. The inhalation exposure to pathogenic particles was estimated using the derived airborne concentration model, and subsequently incorporated into a dose‐response model to assess the infection risk. Using the proposed risk assessment scheme, the influences of resuspension towards indoor infection transmission were examined by two hypothetical case studies. In the case of AIPR, the infection risk increased from 0 to 0.54 during 0–0.5 hours and from 0.54 to 0.57 during 0.5–4 hours. In the case of WIPR, the infection risk increased from 0 to 0.87 during 0–0.5 hours and from 0.87 to 1 during 0.5–4 hours. Sensitivity analysis was conducted based on the design‐of‐experiments method and showed that the factors that are related to the inspiratory rate of viable pathogens and pathogen virulence have the most significant effect on the infection probability under the occurrence of AIPR and WIPR. The risk assessment scheme could serve as an effective tool for the risk assessment of infection transmission indoors.     

Influenza Infection Risk and Predominate Exposure Route: Uncertainty Analysis

An effective nonpharmaceutical intervention for influenza interrupts an exposure route that contributes significantly to infection risk. Herein, we use uncertainty analysis (point‐interval method) and Monte Carlo simulation to explore the magnitude of infection risk and predominant route of exposure. We utilized a previously published mathematical model of a susceptible person attending a bed‐ridden infectious person. Infection risk is sensitive to the magnitude of virus emission and contact rates. The contribution of droplet spray exposure to infection risk increases with cough frequency, and decreases with virus concentration in cough particles. We consider two infectivity scenarios: greater infectivity of virus deposited in the upper respiratory tract than virus inhaled in respirable aerosols, based on human studies; and equal infectivity in the two locations, based on studies in guinea pigs. Given that virus have equal probability of infection throughout the respiratory tract, the mean overall infection risk is 9.8 × 10^?2 (95th percentile 0.78). However, when virus in the upper respiratory tract is less infectious than inhaled virus, the overall infection risk is several orders of magnitude lower. In this event, inhalation is a significant exposure route. Contact transmission is important in both infectivity scenarios. The presence of virus in only respirable particles increases the mean overall infection risk by 1–3 orders of magnitude, with inhalation contributing ≥ 99% of the infection risk. The analysis indicates that reduction of uncertainties in the concentration of virus in expiratory particles of different sizes, expiratory event frequency, and infectivity at different sites in the respiratory tract will clarify the predominate exposure routes for influenza.     

Relative Contributions of Four Exposure Pathways to Influenza Infection Risk

The relative contribution of four influenza virus exposure pathways—(1) virus-contaminated hand contact with facial membranes, (2) inhalation of respirable cough particles, (3) inhalation of inspirable cough particles, and (4) spray of cough droplets onto facial membranes—must be quantified to determine the potential efficacy of nonpharmaceutical interventions of transmission. We used a mathematical model to estimate the relative contributions of the four pathways to infection risk in the context of a person attending a bed-ridden family member ill with influenza. Considering the uncertainties in the sparse human subject influenza dose-response data, we assumed alternative ratios of 3,200:1 and 1:1 for the infectivity of inhaled respirable virus to intranasally instilled virus. For the 3,200:1 ratio, pathways (1), (2), and (4) contribute substantially to influenza risk: at a virus saliva concentration of 10⁶ mL⁻¹, pathways (1), (2), (3), and (4) contribute, respectively, 31%, 17%, 0.52%, and 52% of the infection risk. With increasing virus concentrations, pathway (2) increases in importance, while pathway (4) decreases in importance. In contrast, for the 1:1 infectivity ratio, pathway (1) is the most important overall: at a virus saliva concentration of 10⁶ mL⁻¹, pathways (1), (2), (3), and (4) contribute, respectively, 93%, 0.037%, 3.3%, and 3.7% of the infection risk. With increasing virus concentrations, pathway (3) increases in importance, while pathway (4) decreases in importance. Given the sparse knowledge concerning influenza dose and infectivity via different exposure pathways, nonpharmaceutical interventions for influenza should simultaneously address potential exposure via hand contact to the face, inhalation, and droplet spray.     

The Effect of Mask Use on the Spread of Influenza During a Pandemic

Face masks have traditionally been used in general infection control, but their efficacy at the population level in preventing transmission of influenza viruses has not been studied in detail. Data from published clinical studies indicate that the infectivity of influenza A virus is probably very high, so that transmission of infection may involve low doses of virus. At low doses, the relation between dose and the probability of infection is approximately linear, so that the reduction in infection risk is proportional to the reduction in exposure due to particle retention of the mask. A population transmission model was set up to explore the impact of population‐wide mask use, allowing estimation of the effects of mask efficacy and coverage (fraction of the population wearing masks) on the basic reproduction number and the infection attack rate. We conclude that population‐wide use of face masks could make an important contribution in delaying an influenza pandemic. Mask use also reduces the reproduction number, possibly even to levels sufficient for containing an influenza outbreak.     

A probabilistic transmission and population dynamic model to assess tuberculosis infection risk

The purpose of this study was to examine tuberculosis (TB) population dynamics and to assess potential infection risk in Taiwan. A well‐established mathematical model of TB transmission built on previous models was adopted to study the potential impact of TB transmission. A probabilistic risk model was also developed to estimate site‐specific risks of developing disease soon after recent primary infection, exogenous reinfection, or through endogenous reactivation (latently infected TB) among Taiwan regions. Here, we showed that the proportion of endogenous reactivation (53–67%) was larger than that of exogenous reinfection (32–47%). Our simulations showed that as epidemic reaches a steady state, age distribution of cases would finally shift toward older age groups dominated by latently infected TB cases as a result of endogenous reactivation. A comparison of age‐weighted TB incidence data with our model simulation output with 95% credible intervals revealed that the predictions were in an apparent agreement with observed data. The median value of overall basic reproduction number (R₀) in eastern Taiwan ranged from 1.65 to 1.72, whereas northern Taiwan had the lowest R₀ estimate of 1.50. We found that total TB incidences in eastern Taiwan had 25–27% probabilities of total proportion of infected population exceeding 90%, whereas there were 36–66% probabilities having exceeded 20% of total proportion of infected population attributed to latently infected TB. We suggested that our Taiwan‐based analysis can be extended to the context of developing countries, where TB remains a substantial cause of elderly morbidity and mortality.     

Societal Responses to Familiar Versus Unfamiliar Risk: Comparisons of Influenza and SARS in Korea

This study examines the connections between familiar (influenza) and unfamiliar (SARS) risks among the general public in a SARS affected society. Using a survey of 350 respondents in Chonju, we find that risk perceptions and a belief that influenza vaccination reduces the incidence of SARS explain behavioral intentions for influenza vaccination and purchase responses to a hypothetical SARS vaccine. Those respondents who believe that an influenza vaccination will very likely reduce SARS incidence have a high probability (79%) of intending to vaccinate, but a much lower WTP for a SARS vaccine than those without such a belief. This belief undoubtedly was influenced by a reframing of influenza vaccination as preventing SARS. Such reframing may lead to short-term improvements in vaccination rates to the detriment of long-term SARS vaccination development. When compared with a similar study in Taiwan, societal risk perceptions of SARS and WTP for a vaccine vary greatly according to the extent of a society's experience with SARS.     

Effects of Surface Material,Ventilation, and Human Behavior on Indirect Contact Transmission Risk of Respiratory Infection

Infectious particles can be deposited on surfaces. Susceptible persons who contacted these contaminated surfaces may transfer the pathogens to their mucous membranes via hands, leading to a risk of respiratory infection. The exposure and infection risk contributed by this transmission route depend on indoor surface material, ventilation, and human behavior. In this study, quantitative infection risk assessments were used to compare the significances of these factors. The risks of three pathogens, influenza A virus, respiratory syncytial virus (RSV), and rhinovirus, in an aircraft cabin and in a hospital ward were assessed. Results showed that reducing the contact rate is relatively more effective than increasing the ventilation rate to lower the infection risk. Nonfabric surface materials were found to be much more favorable in the indirect contact transmission for RSV and rhinovirus than fabric surface materials. In the cases considered in this study, halving the ventilation rate and doubling the hand contact rate to surfaces and the hand contact rate to mucous membranes would increase the risk by 3.7–16.2%, 34.4–94.2%, and 24.1–117.7%, respectively. Contacting contaminated nonfabric surfaces may pose an indirect contact risk up to three orders of magnitude higher than that of contacting contaminated fabric surfaces. These findings provide more consideration for infection control and building environmental design.     

Development of a Dose‐Response Model for SARS Coronavirus

In order to develop a dose‐response model for SARS coronavirus (SARS‐CoV), the pooled data sets for infection of transgenic mice susceptible to SARS‐CoV and infection of mice with murine hepatitis virus strain 1, which may be a clinically relevant model of SARS, were fit to beta‐Poisson and exponential models with the maximum likelihood method. The exponential model (k= 4.1 × l0²) could describe the dose‐response relationship of the pooled data sets. The beta‐Poisson model did not provide a statistically significant improvement in fit. With the exponential model, the infectivity of SARS‐CoV was calculated and compared with those of other coronaviruses. The does of SARS‐CoV corresponding to 10% and 50% responses (illness) were estimated at 43 and 280 PFU, respectively. Its estimated infectivity was comparable to that of HCoV‐229E, known as an agent of human common cold, and also similar to those of some animal coronaviruses belonging to the same genetic group. Moreover, the exponential model was applied to the analysis of the epidemiological data of SARS outbreak that occurred at an apartment complex in Hong Kong in 2003. The estimated dose of SARS‐CoV for apartment residents during the outbreak, which was back‐calculated from the reported number of cases, ranged from 16 to 160 PFU/person, depending on the floor. The exponential model developed here is the sole dose‐response model for SARS‐CoV at the present and would enable us to understand the possibility for reemergence of SARS.     

Modeling the Effectiveness of Respiratory Protective Devices in Reducing Influenza Outbreak

Outbreaks of influenza represent an important health concern worldwide. In many cases, vaccines are only partially successful in reducing the infection rate, and respiratory protective devices (RPDs) are used as a complementary countermeasure. In devising a protection strategy against influenza for a given population, estimates of the level of protection afforded by different RPDs is valuable. In this article, a risk assessment model previously developed in general form was used to estimate the effectiveness of different types of protective equipment in reducing the rate of infection in an influenza outbreak. It was found that a 50% compliance in donning the device resulted in a significant (at least 50% prevalence and 20% cumulative incidence) reduction in risk for fitted and unfitted N95 respirators, high‐filtration surgical masks, and both low‐filtration and high‐filtration pediatric masks. An 80% compliance rate essentially eliminated the influenza outbreak. The results of the present study, as well as the application of the model to related influenza scenarios, are potentially useful to public health officials in decisions involving resource allocation or education strategies.     

Selecting Nonpharmaceutical Interventions for Influenza

Models of influenza transmission have focused on the ability of vaccination, antiviral therapy, and social distancing strategies to mitigate epidemics. Influenza transmission, however, may also be interrupted by hygiene interventions such as frequent hand washing and wearing masks or respirators. We apply a model of influenza disease transmission that incorporates hygiene and social distancing interventions. The model describes population mixing as a Poisson process, and the probability of infection upon contact between an infectious and susceptible person is parameterized by p. While social distancing interventions modify contact rates in the population, hygiene interventions modify p. Public health decision making involves tradeoffs, and we introduce an objective function that considers the direct costs of interventions and new infections to determine the optimum intervention type (social distancing versus hygiene intervention) and population compliance for epidemic mitigation. Significant simplifications have been made in these models. However, we demonstrate that the method is feasible, provides plausible results, and is sensitive to the selection of model parameters. Specifically, we show that the optimum combination of nonpharmaceutical interventions depends upon the probability of infection, intervention compliance, and duration of infectiousness. Means by which realism can be increased in the method are discussed.     

A Probabilistic Transmission Model to Assess Infection Risk from Mycobacterium Tuberculosis in Commercial Passenger Trains

The objective of this article is to characterize the risk of infection from airborne Mycobacterium tuberculosis bacilli exposure in commercial passenger trains based on a risk‐based probabilistic transmission modeling. We investigated the tuberculosis (TB) infection risks among commercial passengers by inhaled aerosol M. tuberculosis bacilli and quantify the patterns of TB transmission in Taiwan High Speed Rail (THSR). A deterministic Wells‐Riley mathematical model was used to account for the probability of infection risk from M. tuberculosis bacilli by linking the cough‐generated aerosol M. tuberculosis bacilli concentration and particle size distribution. We found that (i) the quantum generation rate of TB was estimated with a lognormal distribution of geometric mean (GM) of 54.29 and geometric standard deviation (GSD) of 3.05 quantum/h at particle size ≤ 5 μm and (ii) the basic reproduction numbers (R₀) were estimated to be 0.69 (0.06–6.79), 2.82 (0.32–20.97), and 2.31 (0.25–17.69) for business, standard, and nonreserved cabins, respectively. The results indicate that commercial passengers taking standard and nonreserved cabins had higher transmission risk than those in business cabins based on conservatism. Our results also reveal that even a brief exposure, as in the bronchoscopy cases, can also result in a transmission when the quantum generation rate is high. This study could contribute to a better understanding of the dynamics of TB transmission in commercial passenger trains by assessing the relationship between TB infectiousness, passenger mobility, and key model parameters such as seat occupancy, ventilation rate, and exposure duration.     

Influence of Routine Slaughtering on the Evolution of BSE: Example of British and French Slaughterings

The aim of this article is to build a methodology allowing the study and the comparison of the potential spread of BSE at the scale of countries under different routine slaughtering conditions in order to evaluate the risk of nonextinction due to this slaughtering. We first model the evolution in discrete time of the proportion of animals in the latent period and that of infectives, assuming a very large branching population not necessarily constant in size, two age classes, less than 1-year-old animals, and adult animals. We analytically derive a bifurcation parameter rho(0) allowing us to predict either endemicity or extinction of the disease, which has the meaning of an epidemiological reproductive rate. We show that the classical reproductive number R(0) cannot be used for prediction if the size of the population, when healthy, does not remain stable throughout time. We illustrate the qualitative results by means of simulations with either the British routine slaughtering probabilities or the French ones, the other conditions being assumed identical in both countries. We show that the French probabilities lead to a higher risk of spread of the disease than the British ones, this result being mainly due to a smaller value of the routine slaughtering probability of the adult animals in France than in Great Britain.     

Characterizing the Risk of Infection from Mycobacterium tuberculosis in Commercial Passenger Aircraft Using Quantitative Microbial Risk Assessment

Quantitative microbial risk assessment was used to predict the likelihood and spatial organization of Mycobacterium tuberculosis ( Mtb ) transmission in a commercial aircraft. Passenger exposure was predicted via a multizone Markov model in four scenarios: seated or moving infectious passengers and with or without filtration of recirculated cabin air. The traditional exponential ( k  = 1) and a new exponential ( k  = 0.0218) dose-response function were used to compute infection risk. Emission variability was included by Monte Carlo simulation. Infection risks were higher nearer and aft of the source; steady state airborne concentration levels were not attained. Expected incidence was low to moderate, with the central 95% ranging from 10⁻⁶ to 10⁻¹ per 169 passengers in the four scenarios. Emission rates used were low compared to measurements from active TB patients in wards, thus a "superspreader" emitting 44 quanta/h could produce 6.2 cases or more under these scenarios. Use of respiratory protection by the infectious source and/or susceptible passengers reduced infection incidence up to one order of magnitude.     

Annual Burden of Occupationally‐Acquired Influenza Infections in Hospitals and Emergency Departments in the United States

Infections among health‐care personnel (HCP) occur as a result of providing care to patients with infectious diseases, but surveillance is limited to a few diseases. The objective of this study is to determine the annual number of influenza infections acquired by HCP as a result of occupational exposures to influenza patients in hospitals and emergency departments (EDs) in the United States. A risk analysis approach was taken. A compartmental model was used to estimate the influenza dose received in a single exposure, and a dose–response function applied to calculate the probability of infection. A three‐step algorithm tabulated the total number of influenza infections based on: the total number of occupational exposures (tabulated in previous work), the total number of HCP with occupational exposures, and the probability of infection in an occupational exposure. Estimated influenza infections were highly dependent upon the dose–response function. Given current compliance with infection control precautions, we estimated 151,300 and 34,150 influenza infections annually with two dose–response functions (annual incidence proportions of 9.3% and 2.1%, respectively). Greater reductions in infectious were achieved by full compliance with vaccination and IC precautions than with patient isolation. The burden of occupationally‐acquired influenza among HCP in hospitals and EDs in the United States is not trivial, and can be reduced through improved compliance with vaccination and preventive measures, including engineering and administrative controls.     

Risk assessment methodologies for passive smoking-induced lung cancer

Risk assessment methodologies have been successfully applied to control societal risk from outdoor air pollutants. They are now being applied to indoor air pollutants such as environmental tobacco smoke (ETS) and radon. Nonsmokers' exposures to ETS have been assessed based on dosimetry of nicotine, its metabolite, continine, and on exposure to the particulate phase of ETS. Lung cancer responses have been based on both the epidemiology of active and of passive smoking. Nine risk assessments of nonsmokers' lung cancer risk from exposure to ETS have been performed. Some have estimated risks for lifelong nonsmokers only; others have included ex-smokers; still others have estimated total deaths from all causes. To facilitate interstudy comparison, in some cases lung cancers had to be interpolated from a total, or the authors' original estimate had to be adjusted to include ex-smokers. Further, all estimates were adjusted to 1988. Excluding one study whose estimate differs from the mean of the others by two orders of magnitude, the remaining risk assessments are in remarkable agreement. The mean estimate is approximately 5000 +/- 2400 nonsmokers' lung cancer deaths (LCDSs) per year. This is a 25% greater risk to nonsmokers than is indoor radon, and is about 57 times greater than the combined estimated cancer risk from all the hazardous outdoor air pollutants currently regulated by the Environmental Protection Agency: airborne radionuclides, asbestos, arsenic, benzene, coke oven emissions, and vinyl chloride.     

A Simulation Model for Occupational Tuberculosis Transmission

A simulation model of tuberculosis (TB) transmission among hospital employees is described. A hypothetical cohort of 1000 workers was divided into low-, medium-, and high-risk groups. The number of TB patients admitted daily was treated as a Poisson random variable. A patient imparted a daily infection risk that was identical for all workers within a risk group but that varied between risk groups. In some scenarios, infected employees were assigned a daily risk of developing TB disease. If disease developed, the individual remained on the job for 3 calendar weeks and imparted a substantial infection risk to 25 close contacts. Simulations were run over 5-year intervals. Cumulative infection incidence increased over time and with more TB patients admitted. Given a scenario in which there were 600, 300, and 100 susceptibles in the low-, medium-, and high risk groups, respectively, 50 TB patients admitted annually and accounting for disease among infected employees, at 5 years there were approximately 100 primary infections (due to infection by patients), 40 secondary infections (due to infection by diseased coworkers), five primary disease cases, and two secondary disease cases. The input parameter values and simulation outcomes were reasonably consistent with the sparse information reported in the literature.     

A Scenario‐Based Evaluation of the Middle East Respiratory Syndrome Coronavirus and the Hajj

Between April 2012 and June 2014, 820 laboratory‐confirmed cases of the Middle East respiratory syndrome coronavirus (MERS‐CoV) have been reported in the Arabian Peninsula, Europe, North Africa, Southeast Asia, the Middle East, and the United States. The observed epidemiology is different to SARS, which showed a classic epidemic curve and was over in eight months. The much longer persistence of MERS‐CoV in the population, with a lower reproductive number, some evidence of human‐to‐human transmission but an otherwise sporadic pattern, is difficult to explain. Using available epidemiological data, we implemented mathematical models to explore the transmission dynamics of MERS‐CoV in the context of mass gatherings such as the Hajj pilgrimage, and found a discrepancy between the observed and expected epidemiology. The fact that no epidemic occurred in returning Hajj pilgrims in either 2012 or 2013 contradicts the long persistence of the virus in human populations. The explanations for this discrepancy include an ongoing, repeated nonhuman/sporadic source, a large proportion of undetected or unreported human‐to‐human cases, or a combination of the two. Furthermore, MERS‐CoV is occurring in a region that is a major global transport hub and hosts significant mass gatherings, making it imperative to understand the source and means of the yet unexplained and puzzling ongoing persistence of the virus in the human population.     

Statistical Distributions of Daily Breathing Rates for Narrow Age Groups of Infants and Children

Children may be more susceptible to toxicity from some environmental chemicals than adults. This susceptibility may occur during narrow age periods (windows), which can last from days to years depending on the toxicant. Breathing rates specific to narrow age periods are useful to assess inhalation dose during suspected windows of susceptibility. Because existing breathing rates used in risk assessment are typically for broad age ranges or are based on data not representative of the population, we derived daily breathing rates for narrow age ranges of children designed to be more representative of the current U.S. children's population. These rates were derived using the metabolic conversion method of Layton (1993) and energy intake data adjusted to represent the U.S. population from a relatively recent dietary survey (CSFII 1994–1996, 1998). We calculated conversion factors more specific to children than those previously used. Both nonnormalized (L/day) and normalized (L/kg-day) breathing rates were derived and found comparable to rates derived using energy estimates that are accurate for the individuals sampled but not representative of the population. Estimates of breathing rate variability within a population can be used with stochastic techniques to characterize the range of risk in the population from inhalation exposures. For each age and age-gender group, we present the mean, standard error of the mean, percentiles (50th, 90th, and 95th), geometric mean, standard deviation, 95th percentile, and best-fit parametric models of the breathing rate distributions. The standard errors characterize uncertainty in the parameter estimate, while the percentiles describe the combined interindividual and intra-individual variability of the sampled population. These breathing rates can be used for risk assessment of subchronic and chronic inhalation exposures of narrow age groups of children.     

Use of Risk Assessment and Likelihood Estimation to Analyze Spatial Distribution Pattern of Respiratory Infection Cases

Obvious spatial infection patterns are often observed in cases associated with airborne transmissible diseases. Existing quantitative infection risk assessment models analyze the observed cases by assuming a homogeneous infectious particle concentration and ignore the spatial infection pattern, which may cause errors. This study aims at developing an approach to analyze spatial infection patterns associated with infectious respiratory diseases or other airborne transmissible diseases using infection risk assessment and likelihood estimation. Mathematical likelihood, based on binomial probability, was used to formulate the retrospective component with some additional mathematical treatments. Together with an infection risk assessment model that can address spatial heterogeneity, the method can be used to analyze the spatial infection pattern and retrospectively estimate the influencing parameters causing the cases, such as the infectious source strength of the pathogen. A Varicella outbreak was selected to demonstrate the use of the new approach. The infectious source strength estimated by the Wells‐Riley concept using the likelihood estimation was compared with the estimation using the existing method. It was found that the maximum likelihood estimation matches the epidemiological observation of the outbreak case much better than the estimation under the assumption of homogeneous infectious particle concentration. Influencing parameters retrospectively estimated using the new approach can be used as input parameters in quantitative infection risk assessment of the disease under other scenarios. The approach developed in this study can also serve as an epidemiological tool in outbreak investigation. Limitations and further developments are also discussed.     

Validation and Application of Models to Predict Facemask Influenza Contamination in Healthcare Settings

Facemasks are part of the hierarchy of interventions used to reduce the transmission of respiratory pathogens by providing a barrier. Two types of facemasks used by healthcare workers are N95 filtering facepiece respirators (FFRs) and surgical masks (SMs). These can become contaminated with respiratory pathogens during use, thus serving as potential sources for transmission. However, because of the lack of field studies, the hazard associated with pathogen‐exposed facemasks is unknown. A mathematical model was used to calculate the potential influenza contamination of facemasks from aerosol sources in various exposure scenarios. The aerosol model was validated with data from previous laboratory studies using facemasks mounted on headforms in a simulated healthcare room. The model was then used to estimate facemask contamination levels in three scenarios generated with input parameters from the literature. A second model estimated facemask contamination from a cough. It was determined that contamination levels from a single cough (≈19 viruses) were much less than likely levels from aerosols (4,473 viruses on FFRs and 3,476 viruses on SMs). For aerosol contamination, a range of input values from the literature resulted in wide variation in estimated facemask contamination levels (13–202,549 viruses), depending on the values selected. Overall, these models and estimates for facemask contamination levels can be used to inform infection control practice and research related to the development of better facemasks, to characterize airborne contamination levels, and to assist in assessment of risk from reaerosolization and fomite transfer because of handling and reuse of contaminated facemasks.