BackgroundFomite mediated transmission can be an important pathway causing significant disease transmission in number of settings such as schools, daycare centers, and long-term care facilities. The importance of these pathways relative to other transmission pathways such as direct person-person or airborne will depend on the characteristics of the particular pathogen and the venue in which transmission occurs. Here we analyze fomite mediated transmission through a comparative analysis across multiple pathogens and venues.MethodsWe developed and analyzed a compartmental model that explicitly accounts for fomite transmission by including pathogen transfer between hands and surfaces. We consider two sub-types of fomite-mediated transmission: direct fomite (e.g., shedding onto fomites) and hand-fomite (e.g., shedding onto hands and then contacting fomites). We use this model to examine three pathogens with distinct environmental characteristics (influenza, rhinovirus, and norovirus) in four venue types. To parameterize the model for each pathogen we conducted a thorough literature search.ResultsBased on parameter estimates from the literature the reproductive number () for the fomite route for rhinovirus and norovirus is greater than 1 in nearly all venues considered, suggesting that this route can sustain transmission. For influenza, on the other hand, for the fomite route is smaller suggesting many conditions in which the pathway may not sustain transmission. Additionally, the direct fomite route is more relevant than the hand-fomite route for influenza and rhinovirus, compared to norovirus. The relative importance of the hand-fomite vs. direct fomite route for norovirus is strongly dependent on the fraction of pathogens initially shed to hands. Sensitivity analysis stresses the need for accurate measurements of environmental inactivation rates, transfer efficiencies, and pathogen shedding.ConclusionsFomite-mediated transmission is an important pathway for the three pathogens examined. The effectiveness of environmental interventions differs significantly both by pathogen and venue. While fomite-based interventions may be able to lower for fomites below 1 and interrupt transmission, rhinovirus and norovirus are so infectious () that single environmental interventions are unlikely to interrupt fomite transmission for these pathogens.Electronic supplementary materialThe online version of this article (10.1186/s12879-018-3425-x) contains supplementary material, which is available to authorized users.
W. O. Kermack and A. G. McKendrick introduced in their fundamental paper, A Contribution to the Mathematical Theory of Epidemics, published in 1927, a simple deterministic model that captured the qualitative dynamic behavior of single infectious disease outbreaks. A Kermack-McKendrick discrete-time general framework, motivated by the emergence of a multitude of models used to forecast the dynamics of SARS and influenza outbreaks, is introduced in this manuscript. Results that allow us to measure quantitatively the role of classical and general distributions on disease dynamics are presented. The case of the geometric distribution is used to evaluate the impact of waiting-time distributions on epidemiological processes or public health interventions. In short, the geometric distribution is used to set up the baseline or null epidemiological model used to test the relevance of realistic stage-period distribution on the dynamics of single epidemic outbreaks. A final size relationship involving the control reproduction number, a function of transmission parameters and the means of distributions used to model disease or intervention control measures, is computed. Model results and simulations highlight the inconsistencies in forecasting that emerge from the use of specific parametric distributions. Examples, using the geometric, Poisson and binomial distributions, are used to highlight the impact of the choices made in quantifying the risk posed by single outbreaks and the relative importance of various control measures.
Using an approach similar to that for continuous-time models, derivations of R 0 and R C for discrete-time epidemic models with arbitrary stage distribution are presented, and the formulas are shown to be consistent with those obtained from biological considerations. Both models with specific distributions for the infectious stage and models with an arbitrarily distributed (bounded) infectious stage are considered. Results show that the formulas for R 0 and R C can be expressed in terms of disease transmission rates and the means of stage distributions. Examples of SusceptibleExposed-Infected-Recovered models as well as a model with disease control (e.g. isolation or hospitalization) are presented.
Background The inappropriate and/or high prescribing of benzodiazepine and ‘Z’ drugs (BDZ +) is a major health concern. The purpose of this study was to determine whether physician or pharmacist led interventions or a simple letter or a personalized prescribing report from a medical regulatory authority (MRA) was the most effective intervention for reducing BDZ + prescribing by physicians to patients 65 years of age or older. Methods This was a four-armed, one year, blinded, randomized, parallel-group, investigational trial in Alberta, Canada. Participants were fully licensed physicians (n = 272) who had prescribed 4 times the defined daily dose (4 + DDD) or more of any BDZ + to an older patient at least once in the 3rd quarter of 2016. All physician-participants were sent a personalized prescribing profile by the MRA. They were then randomized into four groups that received either nothing more, an additional personal warning letter from the MRA, a personal phone call from an MRA pharmacist or a personal phone call from an MRA physician. The main outcomes were prescribing behavior change of physicians at one year in terms of: change in mean number of older patients receiving 4 + DDD BDZ + and mean dose BDZ + prescribed per physician. To adjust for multiple statistical testing, we used MANCOVA to test both main outcome measures simultaneously by group whilst controlling for any baseline differences. Results All groups experienced a significant fall in the total number of older patients receiving 4 + DDD of BDZ + by about 50% (range 43–54%) per physician at one year, and a fall in the mean dose of BDZ + prescribed of about 13% (range 10–16%). However, there was no significant difference between each group. Conclusions A personalized prescribing report alone sent from the MRA appears to be an effective intervention for reducing very high levels of BDZ + prescribing in older patients. Additional interventions by a pharmacist or physician did not result in additional benefit. The intervention needs to be tested further on a more general population of physicians, prescribing less extreme doses of BDZ + and that looks at more clinical and healthcare utilization outcomes.
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