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" "Some pathogens live exciting double lives, with entirely separate life cycles and be- haviors in different animals.
Chris von Csefalvay (born 15 July 1986) is a Hungarian-British computational epidemiologist and data scientist. He has written extensively about agentic AI, a concept he was among the first to describe, and on the computational modelling of infectious diseases. He is currently a Principal specializing in AI at HCLTech. He published his first monograph, Computational Modeling of Infectious Disease in 2023. He lives in Washington, DC with his wife, the art historian and illustrator Katie Hedrick, and their Golden Retriever.
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At the time of writing, the COVID-19 pandemic has been raging for almost three years. It has cost five million people their lives. The toll of destruction, the human cost, and the economic losses remain to be counted. Few outbreaks in history leave this kind of lasting mark on society: the Plague of Athens (430 BC), the Plague of Galen (165–180 AD), the Plague of Justinian (541–549), the Black Death (1346–1353), the Spanish Flu (1918–1920), and the HIV/AIDS pandemic (1981 onwards) are the most notable exceptions. COVID-19 has now joined the ranks of these sad episodes of human history. Yet humans are not helpless against pandemics. Amidst all the destruction and grief of the COVID-19 pandemic, science has been a bright, shining beacon showing how humanity can prevail against fearful odds.
It often takes years to create a viable antibody test as accurate as PCR-based testing. But in less than six weeks, biotech companies—approached by the U.S. government through the White House-created public-private partnership—have already seen their efforts bear fruit. This is a tribute to the incredible creative potential of the biotech sector, but it also shows the power of free enterprise, unshackled by government bureaucracy. It took more than America’s best scientists to rise to the occasion: it took a regulatory regime to let them do so.
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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.