Characterising seasonal influenza epidemiology using primary care surveillance data

Citation

Robert C Cope, Joshua V Ross, Monique Chilver, Nigel P Stocks, Lewis Mitchell.

PLoS Comput Biol 2018; 14(8):e1006377. DOI: 10.1371/journal.pcbi.1006377

When patients present to their doctor with influenza-like symptoms, they may have influenza, or some other respiratory virus. The only way to discriminate between these viruses is with an expensive test, which is not performed in many cases. Additionally, results other than influenza may not be reported. This means that it can be difficult to determine how much influenza is circulating in the population each season.

We used a unique dataset of confirmed influenza with denominators to fit models for seasonal influenza in New South Wales, Australia. Knowing the denominators allowed us to estimate population level trends.

We found that the relationship between influenza transmission rates and immunity due to previous infections was critical, with relatively high transmission corresponding to substantial preexisting immunity likely. This existing immunity is critical to understanding and effectively modeling influenza dynamics.

Related Research Areas

  • Clinical research and infection prevention