The numbers game
Maths can be a key weapon in the war against infectious disease
The spread of an infectious disease is a complex affair, affected by many factors. Mathematical equations modelling the spread of disease can help us limit the impact of future infections.
These mathematical models can be used to simulate or re-run outbreaks and to test the impact of different control strategies. In late 2014, for instance, Canadian scientists predicted using a mathematical model that 700,000 people will have been infected in the West African Ebola epidemic by 2016. Meanwhile, a US team calculated the number of new cases that could be prevented by isolating a certain proportion of infected people.
Data from drug trials have been fed into mathematical models to test the effects of combined therapies for malaria. In 2014 Dutch and UK researchers working with mathematical models predicted that adding the drug ivermectin to standard artemisinin-based treatments would kill more of the malaria-carrying parasites and reduce transmission.
Mathematical models of pandemic ﬂu have also produced some useful predictions: border and travel restrictions may delay but won’t prevent an outbreak; closing schools will cut the peak attack rate in half, but isolating the infected will have a bigger impact; and vaccines will help even if they are only partially effective.
However, the models make a number of assumptions about the nature of infection, so are inevitably simpliﬁcations. The main problem is that key information – how the disease spreads, how long it survives in the environment – may not be available.Lead image:
AJC1/Flickr CC BY NC
- Future scenarios show how easily Ebola could explode (2014)
- Mathematical models of malaria – a review (2011)
- The potential impact of adding ivermectin to mass treatment intervention to reduce malaria transmission: modelling study (2014)