Computational models of infectious disease can make all the difference in our response to pandemics. As habitat loss and climate change make zoonotic… - Chris von Csefalvay

Today, the efforts waged to curb the COVID-19 pandemic may be the first example of a large-scale, global data-driven response to a worldwide crisis, and as such perhaps the first war of data science.

We may think of maps and mapping as an objective process, but that would be an illusion. What gets mapped, and more importantly, what does not, is a product of various social, economic, and political phenomena. Quite apart from border disputes and contentious sovereignty, mapping also reflects political priorities. Creating the survey data that can be used in maps is expensive, and large-scale mapping endeavors are typically the preserve of states, whose ability to deliver that data often depends on resources that compete with other governmental priorities. This is true especially in resource-constrained settings.

Despite the advances of modern medicine, the challenges of global epidemics have only become greater. Habitat loss of viral reservoir species increases the likelihood of zoonotic spillover events. Our global trade and transportation networks enable pathogens to make their way around the world in 24 hours. Climate change is disrupting fragile ecosystems and global poverty, especially urban poverty, exacerbates the problem.