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In order to determine the relationship between an exposure dose of Staphylococcus aureus (S. aureus) on the skin and the risk of infection, an understanding of the bacterial growth and decay kinetics is very important. Models are essential tools for understanding and predicting bacterial kinetics and are necessary to predict the dose of organisms post-exposure that results in a skin infection. One of the challenges in modeling bacterial kinetics is the estimation of model parameters, which can be addressed using an inverse problem approach. The objective of this study is to construct a microbial kinetic model of S. aureus on human skin and use the model to predict concentrations of S. aureus that result in human infection. In order to model the growth and decay of S. aureus on skin, a Gompertz inactivation model was coupled with a Gompertz growth model. A series of analyses, including ordinary least squares regression, scaled sensitivity coefficient analysis, residual analysis, and parameter correlation analysis were conducted to estimate the parameters and to describe the model uncertainty. Based on these analyses, the proposed model parameters were estimated with high accuracy. The model was then used to develop a new dose-response model for S. aureus using the exponential dose-response model. The new S. aureus model has an optimized k parameter equivalent to 8.05 × 10 −8 with 95 th percentile confidence intervals between 6.46 × 10 −8 and 1.00 × 10 −7 . their nose persistently, while another 20% to 30% carry intermittently [14]. The typical transmission route of S. aureus is from the nose to the hand of a person [15], then to a surface (e.g., a door knob), and/or via the hand to the nose of a second person [16,17]. Activities involving close physical contact and the risk of minor injuries are positively correlated with S. aureus spread and acquisition [18]. Even a brief contact of fingers with a S. aureus contaminated surface may cause the transfer of a large amount of organisms resulting in a potential infection hazard [19]. The transfer rate is higher from moist contaminated surfaces than dry surfaces [20,21].S. aureus can survive on dry surfaces between 2 and 4 days, and then can be easily transferred to hands and foods [22]. Other experiments showed more than a day of survival in hospital fabrics (cotton, terry, blend, and polyester) to over 90 days of survival in polyethylene [23]. These long survival times indicate a potential high risk of transmission of S. aureus through the surface-to-hand pathway. Once S. aureus is in the human body, it is believed to form biofilms, which makes the pathogen less vulnerable to host immune responses and allows them to cause colonization and local infections [14].S. aureus is an opportunistic pathogen and does not usually pose a fatal risk to humans even if it colonizes human mucosa or skin [14]. However, in some cases, S. aureus can cause severe or fatal infections. S. aureus infections progress in five stages: colonization, local infection, systematic dissemination, me...

Droughts affect many sectors, such as agriculture, economic, social, human health, and ecosystems. Many drought indices have been developed; yet, none of them quantifies the impacts of drought on stream health. The purpose of this study is to define a new drought index capable of assessing fish vulnerability. To accomplish this, a hydrological model, called the Soil and Water Assessment Tool (SWAT), and the Regional-scale Habitat Suitability model were integrated in order to understand the state of drought within 13,831 stream segments within the Saginaw Bay Watershed. The ReliefF algorithm was used as the variable selection method, and partial least squared regression was used to develop two sets of predictor models capable of determining current and future drought severities. Forty-seven different climate scenarios were used to investigate drought model predictability of future climate scenarios. The results indicated that the best drought model has a high capability for predicting future drought conditions with R 2 values ranging from 0.86 to 0.89. In general, the majority of reaches (94%) will experience higher drought probability under future climate scenarios compared to current conditions. The

Handwashing with soap is an effective and economical means to reduce the likelihood of Escherichia coli infection from indirect contact with contaminated surfaces during food preparation. The purpose of this study was to conduct a quantitative microbial risk assessment (QMRA) to evaluate the risk of infection from indirect contact with fomites contaminated with E. coli after hand washing with antimicrobial hand soaps. A Monte Carlo simulation was done with a total of 10,000 simulations to compare the effectiveness of two antimicrobial and one control (non-antimicrobial) bar soaps in reducing the exposure and infection risk compared to no hand washing. The numbers of E. coli on several fomites commonly found in household kitchens, as well as the transfer rates between fomites and onto fingertips, were collected from the literature and experimental data. The sponsor company provided the E. coli survival on hands after washing with antimicrobial and control soaps. A number of scenarios were evaluated at two different exposure doses (high and low). Exposure scenarios included transfer of E. coli between meat-to-cutting board surface-to-hands, meat-to-knife surface-to-hands, and from a countertop surface-to-hands, kitchen sponge-to-hands, hand towel-to-hands, and dishcloth-to-hands. Results showed that the risks of illness after washing with the control soap was reduced approximately 5-fold compared to no handwashing. Washing with antimicrobial soap reduced the risk of E. coli infection by an average of about 40-fold compared with no handwashing. The antimicrobial soaps ranged from 3 to 32 times more effective than the non-antimicrobial soap, depending on the specific exposure scenario. Importance: The Centers for Disease Control and Prevention indicate the yearly incidence rate of Shiga Toxin producing E. coli infections is about 1.7/100,000, with about 10% of cases leading to life-threatening hemolytic uremic syndrome and 3–5% leading to death. Our findings confirm handwashing with soap reduces the risks associated with indirect transmission of E. coli infection from contact with fomites during food preparation. Further, in these exposure scenarios, antimicrobial soaps were more effective overall than the non-antimicrobial soap in reducing exposure to E. coli and risk of infection.