New York Times: Can an Algorithm Predict the Pandemic’s Next Moves?

New York Times: Can an Algorithm Predict the Pandemic’s Next Moves?. “Judging when to tighten, or loosen, the local economy has become the world’s most consequential guessing game, and each policymaker has his or her own instincts and benchmarks. The point when hospitals reach 70 percent capacity is a red flag, for instance; so are upticks in coronavirus case counts and deaths. But as the governors of states like Florida, California and Texas have learned in recent days, such benchmarks make for a poor alarm system.”

EurekAlert: Researchers use machine learning to build COVID-19 predictions

EurekAlert: Researchers use machine learning to build COVID-19 predictions. ” As parts of the U.S. tentatively reopen amid the COVID-19 pandemic, the nation’s long-term health continues to depend on tracking the virus and predicting where it might surge next. Finding the right computer models can be tricky, but two researchers at Binghamton University, State University of New York believe they have an innovative way to solve those problems, and they are sharing their work online. Using data collected from around the world by Johns Hopkins University, Arti Ramesh and Anand Seetharam — both assistant professors in the Department of Computer Science — have built several prediction models that take advantage of artificial intelligence. Assisting the research is PhD student Raushan Raj.”

Twitter Blog: Using data from the conversation on Twitter to help detect wildfires

Twitter Blog: Using data from the conversation on Twitter to help detect wildfires. “This wildfire season, Mayday.ai is set to combine data from the unfolding conversation on Twitter with its proprietary incident detection system, which is based on satellite sensors, an array of 35,000 traffic cameras, and IP911 to power a comprehensive detection and a highly targeted notification tracker. Mayday.ai has developed a comprehensive dispatch platform and a mobile app which will provide first responders and civilians unprecedented access to real-time incident information — and has so far had much success in detecting wildfires using its proprietary platform and is being used as a template for other disasters in Mayday’s roadmap.”

EurekAlert: New COVID-19 tool warns relaxing rules may increase deaths

EurekAlert: New COVID-19 tool warns relaxing rules may increase deaths. “A new tool designed to help state and local officials estimate the effects of social distancing and other public health interventions used to combat the COVID-19 pandemic has been released by the nonprofit, nonpartisan RAND Corporation. The free tool combines information from both epidemiological and economic models to estimate the effects of five different disease-fighting portfolios on public health metrics such as disease transmission and economic consequences such as gross state income.”

Cornell Chronicle: Weill Cornell doctor creates epidemic modeling tool

Cornell Chronicle: Weill Cornell doctor creates epidemic modeling tool. “Using a tool he created called the Cornell COVID Caseload Calculator C5V, Dr. Nathaniel Hupert, associate professor of population health sciences and of medicine at Weill Cornell Medicine, has been making forecasts of the potential impact of COVID-19 on local and regional health care systems. The data helps state and city leaders answer questions related to when cases of the disease will peak in hospitals and what resources will be needed to successfully care for those patients.”

Sydney Morning Herald: New database to predict which Sydney suburbs could have restrictions eased

Sydney Morning Herald: New database to predict which Sydney suburbs could have restrictions eased. “A new database could be the key to determining in which suburbs the NSW government could relax its social distancing measures and where to exercise greater control to curb the spread of the coronavirus. The interactive dashboard created by University of Sydney researchers combines NSW Health and ABS data to identify the neighbourhoods most vulnerable to outbreaks: postcodes with a high proportion of people

WAVY: ODU center launches COVID-19 prediction tool online

WAVY: ODU center launches COVID-19 prediction tool online. This is for Virginia only. “The Virginia Modeling, Analysis and Simulation Center produced the tool to give predictions about the virus’ spread and give a daily tally of COVID-19 symptom tweets. The online tool also includes age ranges and hospitalization outcomes forecasts, other COVID-19 modeling resources, and more.”

Washington Post: A leading model now estimates tens of thousands fewer covid-19 deaths by summer

Washington Post: A leading model now estimates tens of thousands fewer covid-19 deaths by summer. “The Post reported last week that Washington, D.C., is relying on a separate model offering a starkly different picture for how the virus will affect the district. At the time, IHME saw the peak number of deaths arriving in mid-April. The D.C. model, developed by Penn Medicine, estimates the peak will come in late June. That variance is a function of the difficulty of modeling the pandemic, something FiveThirtyEight explored last month. Models should get more accurate as the actual peak approaches — though identifying when the peak has arrived is itself tricky, predictive models aside.”

EurekAlert: Arkansas researchers developing prediction models for coronavirus

EurekAlert: Arkansas researchers developing prediction models for coronavirus. “Data science professor Justin Zhan is collaborating with University of Arkansas for Medical Sciences professors David Ussery and Xuming Zhang to develop accurate predictions of genomic variation trends of coronavirus.”

EurekAlert: New tool exploring different paths the corona pandemic may take

EurekAlert: New tool exploring different paths the corona pandemic may take. “Umeå University in Sweden is leading a team of researchers across Europe in the development of a coronavirus simulation framework that can support decision makers to experiment and evaluate possible interventions and their combined effects, in a simulated controlled world.”

Reuters: Google asks users about symptoms for Carnegie Mellon coronavirus forecasting effort

Reuters: Google asks users about symptoms for Carnegie Mellon coronavirus forecasting effort. “Alphabet Inc’s Google said on Monday that over the last three days it had surveyed some users about their health at the request of Carnegie Mellon University researchers aiming to forecast the spread of coronavirus infections.”

The Catholic Church’s new tool for ending hunger: machine learning (Aleteia)

Aleteia: The Catholic Church’s new tool for ending hunger: machine learning. “Drought, major storms, crop disease, other climate-related events, and illness are ‘shocks’ that threaten food security, says Catholic Relief Services, the American Catholic Church’s overseas aid agency. Now, CRS says it has a tool that it says can help aid agencies better respond to such shocks so that ordinary people don’t go hungry. That tool is called MIRA, or Measurement Indicators for Resilience Analysis.”

Engadget: New music label says it can use AI to find the next big artist

Engadget: New music label says it can use AI to find the next big artist. “At this point, artificial intelligence isn’t a new concept to musicians. We’ve seen artists like Björk and Arca use the technology to create new musical arrangements. But a new label called Snafu Records thinks it can also use AI to discover the next big artist long before even the most music-savvy talent scouts find them.”

Neowin: An AI epidemiologist was among the first to break news of the coronavirus outbreak in China

Neowin: An AI epidemiologist was among the first to break news of the coronavirus outbreak in China. “Near the end of the first week of January, news of a deadly flu outbreak in Wuhan, China started coming to mainstream media. The disease that started out from Wuhan has now spread to mainland China and to other parts of the world with confirmed cases in the United States and potential threats in the United Kingdom and other countries. Among the first reporters was BlueDot, which started notifying its customers of an impending outbreak as early as December 31.”