MDR 0.4 Released

The Dartmouth Computational Genetics Laboratory is pleased to announce the release of version 0.4 of our open-source multifactor dimensionality reduction (MDR) software package.

MDR 0.4 has been posted to sourceforge.net which can be accessed from here.

New features in MDR 0.4 include:

1) Threading to take advantage of multi-processor computers. MDR will now automatically detect if your computer has multiple processors and will parallelize the algorithm accordingly. Thus, if you have two processors with threading turned on, MDR will run 4x faster.

2) Batch/command line mode to allow MDR to be run from scripts. This new feature allows MDR to be run from the command line with a Perl script, for example. This makes it possible to run MDR on a grid or parallel computer for simulation studies.

3) Visualization of the fitness landscape. This new feature plots the training accuracy for every model evaluated by MDR. Line plots or histograms can be selected. A zoom feature permits 'drilling down' on a particular region of the landscape. At a fine resolution, mousing over points reveals the model and the training accuracy of that model.

4) Odds ratios. This statistic and its 95% confidence interval have been added to the MDR output to facilitate an epidemiological interpretation of MDR models.

The next major additions to the MDR software will include computation search or wrapper algorithms for variable or attribute selection when the number of combinations to be evaluated is not computationally feasible. Random, greedy, and stochastic search algorithms will be added. These are necessary for genome-wide association studies. This feature will be available later in the summer.

Is there something you would like to see added to MDR? Request it here.

Note that MDR will be in beta testing for another 2-3 months. Please send us your feedback so we can roll out a polished MDR 1.0 later this summer.

The MDR project is funded by NIH grant AI59694.

Effects of behavioral changes in a smallpox attack model

A recent paper by Del Valle et al. explores the impact of individual and community behavioral changes in response to an outbreak of smallpox:

Del Valle S, Hethcote H, Hyman JM, Castillo-Chavez C. Effects of behavioral changes in a smallpox attack model. Math Biosci. 2005 Jun;195(2):228-251. [PubMed]

Abstract:

The impact of individual and community behavioral changes in response to an outbreak of a disease with high mortality is often not appreciated. Response strategies to a smallpox bioterrorist attack have focused on interventions such as isolation of infectives, contact tracing, quarantine of contacts, ring vaccination, and mass vaccination. We formulate and analyze a mathematical model in which some individuals lower their daily contact activity rates once an epidemic has been identified in a community. Transmission parameters are estimated from data and an expression is derived for the effective reproduction number. We use computer simulations to analyze the effects of behavior change alone and in combination with other control measures. We demonstrate that the spread of the disease is highly sensitive to how rapidly people reduce their contact activity rates and to the precautions that the population takes to reduce the transmission of the disease. Even gradual and mild behavioral changes can have a dramatic impact in slowing an epidemic. When behavioral changes are combined with other interventions, the epidemic is shortened and the number of smallpox cases is reduced. We conclude that for simulations of a smallpox outbreak to be useful, they must consider the impact of behavioral changes. This is especially true if the model predictions are being used to guide public health policy.

Models for the control of a smallpox outbreak

A new paper by Aldis et al. derives an integral equation model for the control of a smallpox outbreak:

Aldis GK, Roberts MG. An integral equation model for the control of a smallpox outbreak. Math Biosci. 2005 May;195(1):1-22. [PubMed]

Abstract:

An integral equation model of a smallpox epidemic is proposed. The model structures the incidence of infection among the household, the workplace, the wider community and a health-care facility; and incorporates a finite incubation period and plausible infectivity functions. Linearisation of the model is appropriate for small epidemics, and enables analytic expressions to be derived for the basic reproduction number and the size of the epidemic. The effects of control interventions (vaccination, isolation, quarantine and public education) are explored for a smallpox epidemic following an imported case. It is found that the rapid identification and isolation of cases, the quarantine of affected households and a public education campaign to reduce contact would be capable of bringing an epidemic under control. This could be used in conjunction with the vaccination of healthcare workers and contacts. Our results suggest that prior mass vaccination would be an inefficient method of containing an outbreak.