With the use of sophisticated mathematical modelling techniques, a
mathematician at The Hong Kong Polytechnic University (PolyU) and his
co-researchers have completed a study that explains the phenomenon of
multiple waves of influenza pandemic in the last century.
Taking part in this advanced study is Dr Daihai He, Assistant
Professor of PolyU's Department of Applied Mathematics. He has
collaborated with four researchers in Canada to offer an explanation to
the worst influenza pandemic in the history of mankind. The research
team found that behavioural response has the largest impact among three
primary factors causing the waves, thus paving the way for future
enhancement on control strategies to the spread of influenza virus.
The 1918 flu epidemic was one of the world's deadliest natural
disasters, causing the death of hundred thousands of people. Influenza
pandemic appears to be characterized by multiple waves of incidence in
one year, but the mechanism that explains this phenomenon has so far
been elusive.
In explaining the deadly pandemic, Dr Daihai He and his teammates
have incorporated in their mathematical model three contributing factors
for multiple waves of influenza pandemic in England and Wales:
- (i) schools opening and closing,
- (ii) temperature changes during the outbreak, and
- (iii) changes in human behaviour in response to the outbreak.
Dr He and the researchers further applied this model to the reported
influenza mortality during the 1918 pandemic in 334 British
administrative units and estimate the epidemiological parameters. They
have used information criteria to evaluate how well these three factors
explain the observed patterns of mortality. The results indicate that
all three factors are important, but behavioural responses had the
largest effect.
The findings have recently been published in the journal Proceedings
of the Royal Society Biological Sciences (July 2013 Issue). Dr He's
expertise in advanced mathematics and statistics has helped improve our
understanding of the spread of influenza virus at the population level
and lead to improved strategies to control and minimize the spread of
influenza virus.
