Predicting the spread of epidemics: it's what's inside (the model) that counts

Predicting the spread of epidemics news
By James Gathany [Public domain], via Wikimedia Commons

Recent viral outbreaks such as Ebola or Zika remind us that every new virus has the potential to spread and cause a worldwide epidemic. Being able to map, quantify and make early predictions about the spread of an epidemic is therefore crucial.

Phylodynamic models allow researchers to do this, but their reliability is hindered by several issues, such as the paucity of sequence data available at the early stages of an outbreak.

Using data from the currently ongoing Zika epidemics in the Americas, a team of scientists from SIB's Tanja Stadler's Group at ETH Zurich have pinpointed the factors likely to influence the model's predictions.

The study, led by Veronika Bošková and published in Virus Evolution, provides recommendations to ensure datasets are informative enough to provide reliable estimates. The findings will help make real-time assessments of the spread of an epidemic more reliable in the future.



Geographical origin of the zika virus genome sequences sampled in the study

Veronika Bošková, Tanja Stadler and Carsten Magnus. The influence of phylodynamic model specifications on parameter estimates of the Zika virus epidemic. Virus Evolution, Volume 4, Issue 1, 1 January 2018, vex044,