Despite how useful mathematical modelling can be to predict the spread of infectious diseases, we must be aware that there are many uncertainties and complexities that come with the assumptions made, that could have drastic impacts on our results.
For example, R 0
is very difficult to estimate as there are so many factors contributing towards it,
including water supply, sanitation and climate. Even if it were possible to estimate 0 in a particular area, it would be difficult expand the model to take into account a much larger area as the way people move around can be difficult to predict. Furthermore, as you start modelling larger populations across a larger area, the factors used to estimate R 0 may actually vary, making it difficult to develop accurate models. Another example of the complexity of the factors influencing the rate of spread of this communicable disease could be the age structures in the society at risk. Those in the population who are older will have been susceptible to these diseases to longer and are therefore more likely to be immune. However, despite the UK’s aging society, there is an effect known as assortativity, in which people of a particular age group will more often spend time with those of similar age. Hence, children often spend their time predominantly together and an infection’s spreading process can be streamlined through schools. Again, this only highlights the variety of effects across different cultures and areas. Overall though, mathematical modelling remains an incredible tool for epidemiologists, both at home and abroad, and will continue to develop and become more and more advanced. It has been vital in saving millions of lives, and will continue to be, so make sure to follow its development closely!
Bibliography:
‘Modelling Infectious Diseases’ IB Maths Resources : British International School, Phuket. Available at: https://ibmathsresources.com/2014/05/17/modelling-infectious-diseases/ [Accessed: 05/06/17]
Keeling, M. J., Danon, L. (24/10/09) ‘Mathematical Modelling of Infectious Diseases’ British Medical Bulletin. Available at: https://academic.oup.com/bmb/article/92/1/33/333536/Mathematical- modelling-of-infectiousdiseases#4614109 [Accessed: 05/06/17]
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