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Lessons from mathematical modelling
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#94402
What have been the key public health lessons, principles and contributions from the field of mathematical modelling so far?
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Controlling Infectious Diseases »
Controlling Infectious Diseases
Controlling Infectious Diseases☜Mapping the issues around endemic diseases—such as malaria, measles, influenza, HIV, Dengue and West Nile Virus—with the aims of identifying improved control strategies and of providing insights into to the work of mathematical biologists, epidemiologists and public health officials in this field.☜F1CEB7
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Lessons from mathematical modelling
Lessons from mathematical modelling☜What have been the key public health lessons, principles and contributions from the field of mathematical modelling so far?☜59C6EF
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Distribution of age at infection »
Distribution of age at infection
Distribution of age at infection☜Age-specific susceptibility and Population age distribution manifest the distribution of age at infection. This distribution at the beginning of an epidemic may be different from that at endemic equilibrium. The latter is sometimes used to estimate the reproduction number.☜59C6EF
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Herd immunity »
Herd immunity
Herd immunity☜The Wikipedia page on Herd Immunity is embedded in the Details, and will be updated whenever the Wikipedia page updates.☜59C6EF
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Heterogeneity / core groups »
Heterogeneity / core groups
Heterogeneity / core groups☜A small core group of disease transmitters may account for a large percentage of cases.☜59C6EF
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Optimal strategies to manage resistance »
Optimal strategies to manage resistance
Optimal strategies to manage resistance☜Mathematical modelling has helped to identify optimal strategies for managing resistance.☜59C6EF
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Perverse effects of vaccination »
Perverse effects of vaccination
Perverse effects of vaccination☜The Wikipedia page on the Perverse Effects of Vaccination is embedded in the Details, and will update whenever the Wikipedia page updates.☜59C6EF
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Snapshots and linear models may be dangerously misleading »
Snapshots and linear models may be dangerously misleading
Snapshots and linear models may be dangerously misleading☜Snapshots, linear models tend to be accessible to the common sense understanding of non-mathematical policy stakeholders; however, natural systems are often best understood as dynamic, non-linear systems, which are harder concepts to communicate and sell to the policy makers.☜59C6EF
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Utility of modelling and simulation for planning »
Utility of modelling and simulation for planning
Utility of modelling and simulation for planning☜Planning and decision making can often be made more effective via mathematical modelling and simulation.☜59C6EF
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Entered by:-
David Price
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#94402
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Entry date (GMT):
3/4/2011 2:49:00 AM
Last edit date (GMT):
10/2/2014 9:13:00 AM
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