The mathematical model has been developed by researchers from the University of Cambridge. As well as aiding public health professionals, the model also has the aim of keeping the general public informed about disease patterns.
The model relates to what are called zoonotic infections: diseases passed on from one animal to another — in this case from an animal to a human. Most of the major disease outbreaks that occur in Africa have a zoonotic origin. A prime example is with the Ebola virus, which killed at least 11,000 people in West Africa last year. Ebola probably transferred from fruit bats to people.
The new model aims to predict whether a newly recorded case of a disease will die out or spread, and, if it spreads, the direction the disease will take. The model begins with the transfer between an animal and a person (a factor called ‘spillover’).
Often a single case of a spillover goes no further (as with a person being bitten by a rabid dog; here human-to-human transfer cannot happen). However, with diseases like Ebola and Lassa fever (rat-to-person), or Crimean Congo haemorrhagic fever (ticks-to-people), the chances of spread through a human population is high.
Discussing this, lead researcher Dr Gianni Lo Iacono notes in a research statement: “Modelling spillovers is a real challenge. We don’t have particularly good data on wildlife numbers, such as fruit bats in Sierra Leone, and only a crude idea of their geographic distribution and how many are infected.”
For this reason the model requires inputs about human and animal behavior. Other factors include symptoms and modelling human communities. Because these are highly variable, the computer program uses sub-models based on so-termed “stuttering transmission.”
The model helps to identify risk factors, like failing to wash hands or contact with bodily fluids, thus helping to inform the general public about behaviors to avoid.
The model has been described in the journal PLOS Neglected Tropical Diseases. The research paper is: “A Unified Framework for the Infection Dynamics of Zoonotic Spillover and Spread.”
