Predicting the emergence of drug-resistant HSV-2: new predictions

BACKGROUND: Mathematical models can be used to predict the emergence and transmission of antiviral resistance. Previously it has been predicted that high usage of antivirals (in immunocompetent populations) to treat Herpes Simplex Virus type 2 (HSV-2) would only lead to fairly low levels of antiviral resistance. The HSV-2 predictions were based upon the assumption that drug-resistant strains of HSV-2 would be less infectious than drug-sensitive strains but that the drug-resistant strains would not be impaired in their ability to reactivate. Recent data suggest that some drug-resistant strains of HSV-2 are likely to be impaired in their ability to reactivate. Objectives: (1) To predict the effect of a high usage of antivirals on the prevalence of drug-resistant HSV-2 under the assumption that drug-resistant strains will be less infectious than drug-sensitive strains of HSV-2 and also have an impaired ability to reactivate. (2) To compare predictions with previous published predictions. METHODS: We generated theoretical drug-resistant HSV-2 strains that were attenuated (in comparison with drug-sensitive strains) in both infectivity and ability to reactivate. We then used a transmission model to predict the emergence and transmission of drug-resistant HSV-2 in the immunocompetent population assuming a high usage of antivirals. RESULTS: Our predictions are an order of magnitude lower than previous predictions; we predict that even after 25 years of high antiviral usage only 5 out of 10,000 immunocompetent individuals will be shedding drug-resistant virus. Furthermore, after 25 years, 52 cases of HSV-2 would have been prevented for each prevalent case of drug-resistant HSV-2. CONCLUSIONS: The predicted levels of drug-resistant HSV-2 for the immunocompetent population are so low that it seems unlikely that cases of drug-resistant HSV-2 will be detected

Evaluation of the records management system for the Michigan Center for Truck Safety

This report documents the development of recommendations for a record-keeping system to help the Michigan Center for Truck Safety monitor and document their training activities easily, accurately, consistently, and securely, and to improve the reliability of the data for evaluations of the Center’s programs. The Center’s existing database and structure were reviewed, and the Center’s staff was interviewed about their use of the database system. It is recommended that the Center retain but enhance its existing Microsoft Access Database Management System. The services of a Microsoft Access programmer are recommended to add validity checks and input masks for data input, to develop templates for standard reports, and to develop a set of frequently-used queries. Barcode readers to read driver license numbers and use of DOT numbers are recommended to improve the accuracy of driver and company identification. These data are needed for linkages to driver records and to the Federal Motor Carrier Management Information System (MCMIS) carrier files for evaluations of the Center’s programs. It is recommended that data security is ensured through antivirus, malware protection, internet firewalls, and password protection for the computer and database; that trainees be informed that their privacy is protected; and course evaluations not be linked to individual trainees.Michigan Office of Highway Safety Planninghttp://deepblue.lib.umich.edu/bitstream/2027.42/116597/1/103234.pdfDescription of 103234.pdf : Final repor

The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability

Inductive Reasoning Games as Influenza Vaccination Models: Mean Field Analysis

We define and analyze an inductive reasoning game of voluntary yearly vaccination in order to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. We find that epidemics are rarely prevented. We also find that severe epidemics may occur without the introduction of pandemic strains. We further address the situation where market incentives are introduced to help ameliorating epidemics. Surprisingly, we find that vaccinating families exacerbates epidemics. However, a public health program requesting prepayment of vaccinations may significantly ameliorate influenza epidemics.Comment: 20 pages, 7 figure

Serving GODAE Data and Products to the Ocean Community

The Global Ocean Data Assimilation Experiment (GODAE [http:// www.godae.org]) has spanned a decade of rapid technological development. The ever-increasing volume and diversity of oceanographic data produced by in situ instruments, remote-sensing platforms, and computer simulations have driven the development of a number of innovative technologies that are essential for connecting scientists with the data that they need. This paper gives an overview of the technologies that have been developed and applied in the course of GODAE, which now provide users of oceanographic data with the capability to discover, evaluate, visualize, download, and analyze data from all over the world. The key to this capability is the ability to reduce the inherent complexity of oceanographic data by providing a consistent, harmonized view of the various data products. The challenges of data serving have been addressed over the last 10 years through the cooperative skills and energies of many individuals

Supplemental analysis for strategies to reduce CMV–involved crashes, fatalities and injuries in Michigan: Driver records and crash involvement

Final Report 10/1/7–9/30/08This research sought to identify differences in safety records of drivers who had undergone the training required to hold commercial drivers licenses, and to see if previous offenses and crashes in a CDL drivers record were reasonable indicators of future offenses and crashes. Crash and offense rates from the Michigan Driver Database from 2001-2005 of CDL drivers and non-CDL drivers were compared; crashes and offenses from 2006-2007 were compared across groups of CDL drivers based on their crash and offense records from 2001-2005; and driver records from the Michigan Driver Database were matched with CMV crash records from the Michigan Vehicle Crash data file from 2001-2005, to compare circumstances of CMV crashes of CDL drivers to those of drivers of CMVs that do not require a CDL. Previous offenses and crashes in CDL drivers’ records were reasonable indicators of future offenses and crashes. CDL drivers who had no crashes or no crashes or offenses in the prior period also had the lowest crash involvement for crashes of all severities in the after period. Among crash-involved CMV drivers, non-CDL holders had significantly higher rates of coded hazardous actions than CDL holders. They also had poor prior driving records in terms of prior offenses, serious offenses, and alcohol-related crashes. CDL holders had slightly higher average numbers of prior crash involvements. The findings of this research can be useful to the CDL program to identify critical safety factors, and to the trucking industry to improve driver hiring, training, and retention policies.Michigan Office of Highway Safety Planninghttp://deepblue.lib.umich.edu/bitstream/2027.42/61854/1/102177.pd

Evaluation of the Michigan TACT Program

This report documents the evaluation of the Michigan Ticketing Aggressive Cars and Trucks (TACT) program. The TACT program was conducted in three 2-week waves in the fall of 2013 near Grand Rapids, Michigan. Comparable sites in southeast Michigan served as a comparison area. The TACT program combined high visibility enforcement with a public information and education (PI&E) campaign focused on unsafe driving behaviors of cars and trucks near each other. An evaluation of the TACT implementation found that that the enforcement and PI&E plans were followed reasonably well. Outcomes in terms of driver behaviors, attitudes, and traffic safety were tested by means of surveys of motorists and truck drivers; an observational study of passing and merging behaviors of passenger cars near large trucks; and analysis of crash data. A before/after with comparison design was used to measure any effect in each outcome. Results indicated that the PI&E messages reached the drivers in the program area. Analysis of the survey data did not identify any statistically significant changes in self-reported behaviors among the drivers in the program area. The proportion of safe passing and merging maneuvers recorded in the observational study were quite high before the program and did not change significantly after the program. A Poisson crash rate model adjusted for over-dispersion and using six-years of monthly crash data from the program and comparison areas was developed. It accounted for traffic volumes, proportion of trucks in the traffic, snowfall and precipitation, and the economy. The crash data analysis did not identify significant effects of the program on crash rates.Michigan Office of Highway Safety Planning, Michigan State Policehttp://deepblue.lib.umich.edu/bitstream/2027.42/109414/1/103138.pd