DIMACS/MBI US - African BioMathematics Initiative: Workshop
on Genetics and Disease Control
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Section I: Workshop on Genetics and Disease Control Section II: The Workshop
Using genetic engineering as a defense against the spread of
disease vectors has both great potential for successful control of
these diseases in humans, animals, and plants at great risk. In
general, understanding how genetic modifications will affect the
control of a disease involves the complex interplay of many factors in
our epidemiological models. These include the interplay of climate,
ecology, human population densities, infectivity, and life
cycle. Genetic modifications present particular hope for the control
of endemic diseases in
For instance, it has been a goal in malaria control to release large numbers of sterilized male mosquitoes, which would mate with females (who only mate once in their lifetime) and thereby prevent those females from producing offspring. A similar method was used to eradicate the screwworm fly in the US, Mexico and Central America. Adding a gene that makes the testicles of male mosquitoes fluorescent would enable us to distinguish males from females, sterilize the males, and release them (Adam, 2005). Mathematical modeling comes into play here in several ways. What is the size of the population of sterilized males that needs to be released to achieve a desired level of eradication? Where in a region should the sterilized population be released to maximize the effect? Are the modified male mosquitoes able to compete with wild males for selection by a female ready to mate, and how do different assumptions about the likelihood of a female choosing a modified male over a wild male affect the release strategy? Which parameters would be most effective in cost and accuracy in assessing the success of the program? What monitoring strategies can be planned to modify/improve the release program during its execution?
More general approaches to control of malaria also present interesting issues for mathematical scientists. One possibility is to model evolution and competition in mosquitoes to see whether the anopheles mosquito can be safely out-competed by a rival that shares the same ecological niche but does not transmit harmful disease. This would effectively eradicate malaria. We could also analyze how the mosquito and the malaria pathogen are evolving and adapting to their ecology. This is just one example of some of the strategies available for the genetic modification of vectors for effective disease control. It is easy to develop similar modeling ideas to generate potentially useful genetic strategies for the control treatment of HIV, FLU, Ebola, etc.
Genetic modifications in food crops to boost disease resistance are controversial, but could also have a profound impact on food supply stability, especially in Africa. It is fascinating to try to couple plant epidemiological models with genomic interventions. Changes in agriculture change the landscape through which disease spreads. Globally, this change is fueled by economic and biotechnological change and a growing world population, accentuated by regional asymmetries in supply and demand. In Africa, these changes are also highly influenced by socio-political stability of the region, the numbers of farm workers available during the farming season, and highly variable climatic and environmental conditions (including drought and flooding). Rapid advances in the transformation and genetic modification of crop plants are already underway in temperate agriculture and with it come the vast investments in molecular biology that underpin these changes (Stuiver and Custers, 2001). Many farms are becoming larger with heavy reliance on intensive production using high yielding varieties and heavy application of pesticides. It is important to inform epidemiological management with the mathematical theory of spatially-extended dynamics, ecological and metapopulation theory and population genetics. It is also important to use modeling to understand the risk of a phase transition in spatially-extended epidemiological systems.
The mathematical modeling issues and approaches arising in studying crop diseases encompass issues of stochasticity, nonlinearity, heterogeneity, and scale. Although “botanical epidemiology” shares many issues in common with medical and animal epidemiology, certain features will generate new mathematical approaches. Foremost among these is the occurrence of temporal disturbance associated with sowing and harvest, together with a preponderance of transient dynamics at far from equilibrium behavior and a highly hierarchical system with marked differences in scale. Modeling issues also arise from questions of scaling from individual to population behavior (Durrett and Levin, 1994, Kleczkowski, Gilligan and Bailey, 1997), the development and testing of stochastic models for the evolution of probability distributions within and between replicate epidemics with and without control, and model reduction, including perturbation and asymptotics (Gibson, Gilligan, and Kleczkowski, 1999).
Applications Requested from Interested Graduate Students who Request Funding (Including waiver of Registration Fee)
The Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) and the Mathematical Biosciences Institute (MBI) are holding a five day Workshop that will bring together US and African researchers and graduate students and introduce them to the present state of research in pathogen genetics, host genetics, and vector genetics. A partial list of topics to be covered include:
Evolution in response to specific selective pressures and/or alleviation of selective pressures, such as those caused by host range expansion, disease control measures, or climate change.
Genetic drift and Horizontal Gene Transfer
Evolutionary landscapes: within hosts versus among host selective pressures on pathogen fitness.
Diversity of host genetics as it influences pathogen
susceptability and how population dynamics are affected by that
Interactions between host genetics and disease control measures, such as the development of, and duration of, immunity from vaccination or the success/acceptability given side effects of drug therapies;
How can targeted selection of traits for robustness to disease function as effective agricultural protection methods? And are there some utilization schemes which provide more protection against undesired spread of resistant genes?
How genetic diversity in vector competence for multiple strains/pathogens affects the evolutionary constraints on pathogens;
Determining efficacy of release strategies for genetically modified vectors (such as "sterile male techniques" for mosquitoes), including ecological models of competition;
Can particular rotation/application strategies for insecticides reduce the emergence and spread of insecticide resistance (similar to models to reduce antibiotic resistance in bacteria)?
The inter-disciplinary workshop will also feature several
sessions devoted to the special biological/health/agricultural problems
of Ghana. Bringing together
mathematicians and biologists from Africa and the United States, the
workshop will also enable
participating graduate students to interact and establish collaborations with
During the workshop the graduate students' experience will be enhanced by tutorials and lectures preceding some of the presentations. These tutorials and lectures will be designed to augment the students' background in the workshop topics. Graduate students interested in being supported will be asked to apply and to indicate their relevant background.
A student who requires only partial funding should so indicate on their application.
The workshop is open to graduate students from all areas of science (genetics, bioinformatics, computational biology/chemistry, etc.) and mathematics. Students will be selected based on their applications and letter of recommendation. Students selected for the workshop will be from the United States and Africa, creating an opportunity for establishing early collaborations between junior researchers.
Additional Information: See the workshop website http://dimacs.rutgers.edu/Workshops/DisControl/index.html to:
Send additional questions to Gene Fiorini, or telephone at (732) 445-5930.
This is part of the DIMACS/MBI US - African BioMathematics Initiative Project.