Research Fellows Directory
Dr Julia Gog
University of Cambridge
As a modeller of infectious diseases, recent years have been very interesting. There was a flurry of activity from scientists to characterise the new H1N1 strain when it appeared and for modellers to predict the trajectory of the pandemic over 2009, and of course this attracted a lot of attention from the public – we all wanted to know what might happen and what steps could be taken to avoid it. Now the epidemic wave has passed for now, we were left with a few questions which might not be so much in the public eye, but are important in the long term: they might help us deal with future outbreaks.
I am working with scientists in the US on data from all different US cities on the number of influenza cases, broken down by age group and by week for the last ten years. The worldwide news of a “new” strain of influenza causing severe human disease in Mexico appeared in April 2009. However, most places in the US did not have a significant number of cases until after the summer. There were some exceptions, particularly some cities in the North East, including New York, where there was a significant wave of influenza in the spring. Some of these places had a small epidemic in the spring, and then the bulk of cases came in the Autumn, and some the other way around. We have found a relatively simple way of explaining this: if the transmission rate of influenza drops in the summer, then simply random fluctuations in the timing of introduction in the spring can explain the whole suite of different patterns that we observe. It could just be a matter of chance that the epidemic gets under way before transmission drops below threshold levels. The summer reduction of transmission acts effectively as a pause, not the end of the epidemic for those places.
Work in progress is on the spatial spread of the Autumn wave: when influenza appeared again after the summer, it appeared in different cities in the US at different times. We would like to explain what drove this pattern.