DIMACS/MBI US - African Initiative: Clinic on Meaningful Modeling of Biological Data

May 11 - 19, 2009 African Institute for Mathematical Sciences (AIMS), Muizenberg, South Africa

Organizers:
Steve Bellan, UC Berkeley, sbellan at berkeley.edu
Wim Delva, Ghent University, Wim.Delva at UGent.be
Jonathan Dushoff, McMaster, dushoff at mcmaster.ca
Avner Friedman, Ohio State University, afriedman at math.ohio-state.edu
Marty Golubitsky, MBI, mg at mbi.osu.edu
John Hargrove, SACEMA, jhargrove at sun.ac.za
Travis Porco, University of California-San Francisco, Travis.Porco at ucsf.edu
Juliet Pulliam, NIH, pulliamjuliet at mail.nih.gov
Fred Roberts, DIMACS, froberts at dimacs.rutgers.edu
Brian Williams, WHO-retired, williamsbg at me.com

Presented under the auspices of the DIMACS/MBI US-African Initiative.

This Clinic is jointly organized with The Mathematical Biosciences Institute at Ohio State University (MBI), the African Institute for Mathematical Sciences (AIMS), and South African Centre for Epidemiological Modelling and Analysis (SACEMA) .

This Clinic is jointly sponsored by:

Preparatory exercise

Biomathematics & Epidemiological Dynamics
1. Getz & Lloyd-Smith (2005). Basic Methods for Modeling the Invasion and Spread of Contagious Diseases.
2. Grassly, N. C. and C. Fraser (2008). Mathematical models of infectious disease transmission. Nat Rev Micro 6(6): 477-487.

Statistics and Fitting Models
1. Draft introduction from Bolker's Ecological Models book (focus on sections 3 and 4). Don't worry about ?? symbols in Chapter references. There are links to the whole book below.
2. Huang (2005). Model Identifiability. Encyclopedia of Statistics in Behavioral Science Vol 3: 1249-1251.

Applications of Mathematical Modeling in Public Health
1. Brookhart et al. (2002). Statistical estimation of parameters in a disease transmission model: analysis of a Cryptosporidium outbreak. Statistics in Medicine 21(23): 3627-3638.
2. Porco et al. (2004). Decline in HIV infectivity following the introduction of highly active antiretroviral therapy. AIDS 18(1): 81-88.
3. Dye & Williams (2008) Eliminating human tuberculosis in the twenty-first century. J R Soc Interface 5: 653-662

Biomathematics & Epidemiological Dynamics
1. Grenfell & Keeling (2007) Dynamics in infectious disease.In: Theoretical Ecology, 3rd edition (RM May and A McLean, eds.) Oxford University Press: Oxford.

Statistical Modeling
1. The Ecological Detective (Google books excerpts).
2. Ecological modeling in R (Bolker)
+ Draft version as PDF
3. Bailey & Duppenthaler (1980). Sensitivity Analysis in the Modelling of Infectious Disease Dynamics. J. Math. Biology 10: 113-131.
4. Poole & Rafferty (2000). Inference for deterministic simulation models: The Bayesian melding approach. J. Am. Stat. Association 95(452): 1244-1255.

Applications of Mathematical Modeling in Public Health
1. Hampson et al. (2009) Transmission Dynamics and Prospects for the Elimination of Canine Rabies. PLoS Biol 7(3): e1000053
2. Read et al. (2009) How to Make Evolution-Proof Insecticides for Malaria Control. PLoS Biol 7(4): e1000058
3. Alkema et al. (2007). Probabilistic projections of HIV prevalence using Bayesian melding.
4. Williams et al. (2006). The Potential Impact of Male circumcision on HIV in Sub-Saharan Africa. PLoS Medicine 3(7): e262.
5. Granich et al. (2009) Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model. The Lancet 373(9657): 48-57.

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