Researchers find current disease maps 'astonishingly poor' | University of Oxford

Researchers find current disease maps 'astonishingly poor'

A systematic review examining the current methods used to map infectious diseases worldwide has found them to be severely lacking. The study, led by researchers at the University of Oxford, makes several recommendations to improve future mapping efforts.

The review, published as open-access in Philosophical Transactions of the Royal Society B, identified 355 infectious diseases of clinical significance to humans. There are strong arguments for mapping 174 of these, but only 7 have been mapped reliably. Unreliable mapping makes it difficult to fully understand the geographic scope and threat of diseases, which presents challenges to policy advisers looking to manage their spread.

'This systematic review has shown that we have an astonishingly poor knowledge of the global distribution of the vast majority of infectious diseases of clinical importance,' says Simon Hay, lead author of the study and Professor of Epidemiology at the University of Oxford.

Beyond detailing the shortcomings of current methods, the researchers also suggest ways in which maps could be improved.

'The data supplement is a substantial component of the paper,' explains Katherine Battle, one of the study's co-authors from the University of Oxford, 'We produced a "handbook" of epidemiological and mapping evidence for 355 diseases based on searches of literature and online databases. Future researchers will be able to see at a glance which diseases have the strongest rationale for mapping and where the greatest gaps in cartographic knowledge exist.'

The researchers have made the paper and supplementary information completely open access so that anyone can use their data. 'With public health issues like this, we think it is vital than anyone is able to access the data freely without restrictions,' says Battle.

Within the main paper, the group made more general recommendations for improving disease cartography. These include the use of new crowdsourcing techniques to gather data, such as analyzing the content and frequency of twitter messages about disease. twitter feeds during the 2009 H1N1 flu outbreak, for example, predicted outbreaks sooner than traditional disease surveillance methods.

'We have shown that novel solutions exist to enable us to use up-to-date data and technology to rapidly improve our geographic knowledge of a wide range of clinically important pathogens,' says Battle.

Unique to the review is the inclusion of how the basic reproduction rate, which is the primary epidemiological number used to determine the degree which a disease can spread through a population, might vary among pathogens.

'There is a clear need for better estimates of the potential growth of infectious diseases that allow spatial variations to be taken into consideration, and this paper is a wonderful contribution to help us meet this need,' said Louis Gross, the director of the National Institute for Mathematical and Biological Synthesis, which sponsored a workshop in 2011 that produced the paper.