His methods are similar to how weather forecasters combine factors such as air pressure, moisture levels and wind speed to predict whether the coming week will be sunny or rainy.
Graven has used multiple factors to predict COVID-19 cases and hospital capacity, initially weekly, and now every other week. “How many COVID-19 patients are in hospitals tells us how much stress the pandemic is putting on our health care system, and whether we might need to undertake more measures to ‘flatten the curve.’” Graven’s projections have proved to be remarkably close to the mark, so we value the preview they give us into where the pandemic is going,” said Paul Cieslak, medical director, communicable diseases and immunizations at OHA. It’s the kind of data Oregon Health Authority (OHA) looks at closely. “We are trying to estimate how many people are susceptible the virus and, given how fast we know the virus spreads, how many more people will get infected,” Graven said.īy also including data about how many people are likely to need hospitalization, Graven’s model can help predict how many hospital beds might be available during a COVID-19 surge. The pandemic has offered Graven an opportunity to do exactly that – to simplify COVID-19 data. A fancy model is only good if people can understand what it’s doing.” “But maybe just as importantly, we learn to make complex things simple. “As a Ph.D., you learn how to make simple things complex, and boy can we,” said Graven, age 44. Graven, director of Oregon Health & Science University’s (OHSU) Office of Advanced Analytics, has helped people in Oregon make sense of the pandemic with regular forecasts that began in March 2020.Īs complex as COVID-19 data collection and interpretation is, Graven works hard to simplify it. Peter Graven isn’t a fortune-teller, but he tries his best to predict the future. 1).Peter Graven, director of OHSU’s Office of Advanced Analytics Direct atmospheric observations began in the 1950s, capturing the rapid rise of Δ 14CO 2 and its subsequent quasi-exponential decay as the bomb 14C mixed into oceanic and biospheric reservoirs ( 6– 9) ( Fig. The apparent “aging” of the atmosphere-i.e., the decreasing trend in the ratio 14C/C of CO 2 (reported as Δ 14CO 2) ( 5)-was interrupted in the 1950s when nuclear weapons testing produced an immense amount of “bomb” 14C that approximately doubled the 14C content of the atmosphere. First observed by Hans Suess in 1955 using tree ring records of atmospheric composition ( 4), the dilution of 14CO 2 by fossil carbon provided one of the first indications that human activities were strongly affecting the global carbon cycle. Fossil fuels, which are millions of years old, are therefore devoid of 14C, and their combustion adds only the stable isotopes 12C and 13C to the atmosphere as CO 2.
Radiocarbon is produced naturally in the atmosphere and decays with a half-life of 5,700 ± 30 y ( 1– 3). This finding has strong and as yet unrecognized implications for many applications of radiocarbon in various fields, and it implies that radiocarbon dating may no longer provide definitive ages for samples up to 2,000 y old. Given current emissions trends, fossil fuel emission-driven artificial “aging” of the atmosphere is likely to occur much faster and with a larger magnitude than previously expected. Simulations of Δ 14CO 2 using the emission scenarios from the Intergovernmental Panel on Climate Change Fifth Assessment Report, the Representative Concentration Pathways, indicate that ambitious emission reductions could sustain Δ 14CO 2 near the preindustrial level of 0‰ through 2100, whereas “business-as-usual” emissions will reduce Δ 14CO 2 to −250‰, equivalent to the depletion expected from over 2,000 y of radioactive decay. Over this century, the ratio 14C/C in atmospheric CO 2 (Δ 14CO 2) will be determined by the amount of fossil fuel combustion, which decreases Δ 14CO 2 because fossil fuels have lost all 14C from radioactive decay. Many applications are sensitive to the radiocarbon ( 14C) content of atmospheric CO 2, which has varied since 1890 as a result of nuclear weapons testing, fossil fuel emissions, and CO 2 cycling between atmospheric, oceanic, and terrestrial carbon reservoirs. Radiocarbon analyses are commonly used in a broad range of fields, including earth science, archaeology, forgery detection, isotope forensics, and physiology.
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