Measuring infectious disease

If the idea of triaging patients at the emergency room seems complicated, consider how public health officials prioritize threats posed by organisms they can’t even see. Yet the microscopic microbes and viruses that sicken millions of people with infectious diseases still require a plan of attack. As in any medical scenario, resources are limited. And whether it’s due to low staff numbers, not enough research dollars, or too few hours in the day, someone ultimately has to make the call on where to funnel assets. In 1994, the World Health Organization started measuring the cumulative healthy years lost to disease with Disability Adjusted Life Years (DALY). And each infectious disease is currently ranked according to its DALY score, providing a numbered system to help guide the public health community in crafting a suitable approach to managing the myriad of diseases they face.

But a group of European researchers want to flip the system on its head. Their new method, instead of relying on observations and statistics calculated over the course of months to years, prioritizes infectious disease based on a quick search of scientific and medical publications. And according to a study they published in PLoS ONE, not only is their way faster, but it’s comparably accurate to WHO in identifying the latest trends.

The Hirsch index (or h-index) was created as a way to measure the impact a particular scientist has on his or her field. The value, h, represents the number of publications the researcher has with at least h other papers citing those works. So a scientist with an h-index of 10 has published that many journal articles which have been cited by 10 times a piece by others. It gives a reliable measure of a researcher’s overall value – and, let’s face it, feeds their ego better than standard measures of success, like publishing in top-tier journals.

By searching certain pathogen keyword terms, the team was able to adapt the h-index to score the impact of infectious disease. And as shown below, the two methods produced similar results. But the coolest part is that a single researcher complied h-indices for ~1,400 pathogens in 2 weeks’ time.

Granted, there are some limitations to the method described above, since no distinction is made between good and bad research articles, and emerging diseases may be ignored since they haven’t had enough time to generate a significant h-index score. But as I’ve discussed before, there is a clear trend of people working to bring public health data to light faster than before. It’ll be an interesting space to watch in the next few years.

Brian Mossop is currently the Community Editor at Wired, where he works across the brand, both magazine and website, to build and maintain strong social communities. Brian received a BS in Electrical Engineering from Lafayette College, and a PhD in Biomedical Engineering from Duke University in 2006. His postdoctoral work was in neuroscience at UCSF and Genentech.

Brian has written about science for Wired, Scientific American, Slate, Scientific American MIND, and elsewhere. He primarily cover topics on neuroscience, development, behavior change, and health.

Contact Brian at, on Twitter (@bmossop), or visit his personal website.