Global Disease Hotspots 2.0

Toph Allen is co-head of the Tech Team. One of his most recent projects has been refining the organization's global disease hotspots map. First released in 2008, the original hotspots map identified where on Earth infectious diseases were most likely to emerge. How did they do it? They looked at all of the major disease spillovers on record, and mapped where they were first identified in an attempt to glean where these major disease events may have first emerged. EcoHealth Alliance found that areas rich in biodiversity and with high population density were the most likely to see the emergence of new diseases. This is, in part, because so many viruses that could potentially go pandemic leap from animals into humans. The above-mentioned factors are good indicators of where those spillovers are most likely to happen. In that way, the map is not just a map of risk, but a map of human activity.

The original hotspots map(s).

Hotspots 2.0 is more refined and accomodates a host of other factors. Where before, EcoHealth scientists would only look at latitude as a factor for disease emergence, they now take into account land cover, like the presence of broad-leaf evergreen forests, or rainforests, and high mammal diversity. It is a more accurate and finely calibrated tool, indicating where field technicians are most likely to find the largest number of viruses with the potential to spillover into people. What will they do when they find them? Sample and test. That involves catching wild animals (predominantly rodents, bats, and non-human primates), taking swabs (blood, saliva, urine, and fecal matter), and releasing them back into the wild. Those samples are then combed through for new viruses in a lab. So EcoHealth Alliance scientists will sample animals in areas where land is being rapidly commercialized and developed, where animal production systems (think factory farms) are being constructed, and wherever along the supply chain mammals are being bred, bought, or sold—this includes the pet trade, traditional husbandry, and the illegal wildlife trade. That’s a wide net. But that’s why the geographic focus of the second hotspots map is so important. 

Hotspots 2.0 before being adjusted for research bias.

You might notice that in the above map, the areas of highest risk are in the United States, Europe, and Japan. Incidentally, these are also areas of the globe with some of the best medical infrastructures. That infrastructure is one reason many emergent diseases are first 'discovered' (officially entered into the scientific literature) in the developed world. But EcoHealth Alliance wants to know where spillovers happen, not just where they are discovered. The apparent prevalence of disease emergence in these places is caused by something called 'research bias' - you're more likely to see an outbreak if you're looking for it. Toph refers to the necessary adjustment that counteracts this bias as 'measuring the lens.' One of the critical additions to the map is making that adjustment regionally, and not just at the national level. 

Hotspots 2.0 after adjusting for research bias.

As you can see, the difference is extreme. Nearly all of Bangladesh and India are at the highest risk of disease spillover, as is most of coastal China. According to the three key indicators of population growth, biodiversity, rapid development and land-use change, places like South America should be far brighter, until we consider that the map is a map of risk. More than twice the number of people live in India than live in all of South America—even if an area is at a high theoretical risk of a spillover, that spillover is far less likely to happen where fewer people are present.

A Thai USAID PREDICT team prepares for sampling. Photo Credit: USAID Predict.

Disease spillovers from animals to people are rare events. To catch one where it happens, when it happens, is very difficult. Some people don’t show symptoms when infected, and when they do, they are ill for only a brief window of time. Some diseases have such general symptoms that they are usually mistaken for other diseases, or never get addressed in a clinical context. Being proactive is critical. As Toph says, “If we had been looking in the Congo—at the populations of apes and humans that lived there—it's possible we would have been in a better position to know about HIV before it went pandemic. It’s about moving where you’re looking earlier on in the process of emergence.” One of the reasons Ebola has gotten so much press is the nightmarish quality of its symptoms. A disease that only gave people mild fevers would hardly have garnered the same level of coverage or hysteria that Ebola did. Because of that, many of these zoonotic spillovers go unnoticed and unreported. These hotspot maps allow us to focus our energies on places where we're most likely to catch those elusive spillovers. They are but the first steps on a path that leads out of the pandemic era we inhabit.