By Joey Syer, Spatial Epidemiology and Outbreak Detection Instructor
We all know what geography is. It’s all that business about the names of countries, flags and making maps, right? A recent article in Wired surveyed the discipline among present circumstances with a refreshing resonance, whilst not overlooking its pragmatism. The point is that geography as a discipline has never really seemed so important. Like fighter-pilot enlistment rates following the release of Top Gun, geography seems to have recaptured the interest of the public and the scientific community.
Indeed, geography has come a long way since our early school days. The subject, like many disciplines before it, has adopted a more rigid, objective scientific foundation. By no accident, geography followed in the footsteps of epidemiology, adopting data, statistics and frameworks as its modus operandi. And so today we find ourselves faced with the most captivating epidemiological issue we’ve ever known, which just so happens to be inseparable from geography. COVID-19 has demonstrated the interconnectivity of our world. This may have been evident through our expansive network of telecommunication. But that’s a different type of connectivity than the type of connectivity due to the transmission of disease. A virus hitching a ride from its origins in China across the globe is a phenomenon that will be studied extensively (if not indefinitely), in both epidemiology and geography.
COVID-19 is a disease resulting from a virus, which we may remember was originally called a ‘novel coronavirus’. While the disease itself may be novel, the endless number of geographical and epidemiological opportunities are also novel. Never before has this much data been at the fingertips of epidemiology and geography. For any geographer or epidemiologist (or the hybrid, the spatial epidemiologist), the wealth of data to be studied is amazing.
So, this begs the question: what are people doing with all of this data? Here is a quick survey of three interesting ways COVID-19 is being dealt with in an epidemiological and geographic context.
Viruses evolve and change. To what extent does, or has, SARS-CoV-2 (the virus, not the disease) changed? A recent New York Times article identified that researchers haven’t found any concerning features regarding its mutations. This is excellent epidemiology work, but where does geography come in? Nextstrain—an open-source project to harness the scientific and public health potential of pathogen genome data—is following virus mutation across space. This means that they know, from what data they have, the genomic constitution of the virus in individuals from different parts of the world. This can be good for a number of reasons. First, we may be able to find out where this specific strain came from. Second, keeping tabs on who has which strain means we can account for this strain alongside any other variables of interest. It’s amazing to watch the data visualizations on their website. The visualizations demonstrate, perhaps better than anything, the sheer wealth of data available to us. It will be interesting to see what place geographic genome information plays in future decision-making, treatment, and the like.
In the beginning, there was the Johns Hopkins University GIS dashboard, then there was the WHO GIS dashboard, and now there are just too many to keep track of. But the goal of all of these dashboards is simply to keep track of COVID-19: where it is and how many cases there are. It was equally fascinating (and frightening) to watch the JHU case data grow and migrate out of China and across the world. In one sense, you could say these dashboards accomplished an early-stage goal: they demonstrated just how fast this virus was spreading, and the enormity of both cases and mortalities. As we know, the world responded with major shutdowns and changes. Months in, these GIS dashboards are continually updated and have been enhanced to incorporate more functionality such as epidemic curves, case-fatality ratios, and extremely valuable metadata panes.
When facing COVID-19, we are of course interested in predicting case counts and mortalities, but we are also interested in allocating resources where they are needed. If we can find holes and weak spots in our health infrastructure, we can allocate the necessary resources like masks, ventilators and ICU beds to the right places. GIS can tell us both of those things: where the cases are, and where the resources are needed. One of the most popular platforms for this is the Institute for Health Metrics’ projections for hospital resource use. Dozens of countries are included in their modelling, and one of their models predicts when ICU beds will be maxed-out. This data is also matched to a GIS web map.
This is but a taste of what is happening in the world of epidemiology and geography right now. What’s evident is that these two disciplines are front-and-centre in the world, and it only seems that their uses will become more necessary as time goes on.