SARS-CoV-2, and the COVID-19 disease it causes, only emerged late last year, and its rapid spread around the world has experts racing to find ways to forecast its impact. Several researchers in the ラーメンベット 禁止ゲーム of ラーメンベット 本人確認 are putting together models looking at crucial decisions and information surrounding the virus.
Forecasts and ラーメンベット 本人確認 are key sources of information for decision makers. Predictions of coronavirus’ toll, both on human life and supply chains around the globe, helped shape decisions around social distancing and shelter-at-home rules.
So many unanswered questions remain, several months into the pandemic. The models, from faculty in the ラーメンベット 禁止ゲーム’s Walker Department of Mechanical ラーメンベット 本人確認, seek to answer key questions about transportation and medical logistics and supplies and evaluate how well forecasts predicted the impact of the virus.
Social Distancing on Planes, Trains and Automobiles
Associate professor Vaibhav Bahadur is working on a model that uses fluid dynamics and machine learning to analyze infection risks in different modes of transportation. Bahadur’s ラーメンベット 本人確認 examine passenger capacity, seating arrangements and the influence of mitigation measures taken, such as wearing masks, on planes, subways, trains and other types of transportation. The ラーメンベット 本人確認 also look at air conditioning and airflow settings in personal and ride-share vehicles.
Bahadur says understanding infection risks under various conditions can guide regulators and transportation stakeholders in making decisions ラーメンベット 本人確認 how airlines, ride-share companies and transit agencies should operate going forward, as global economies reopen.
“We all choose where to sit in an airplane, when we ride a bus/train or when we get into an Uber/Lyft,” Bahadur said. “I want to offer folks basic guidelines on how to make these choices from a health perspective.”
Did Forecasters Get it Right?
J. Eric Bickel, an associate professor focused on the science of decision making, is making a model to score how accurate the various forecasts ラーメンベット 本人確認 virus turned out to be. Predictions of death tolls have varied throughout the crisis, from tens of thousands to hundreds of thousands to millions.
Bickel aims to identify lessons learned from the underlying ラーメンベット 本人確認 that powered the forecasts. He will examine whether complex ラーメンベット 本人確認, which tend to be taken more seriously because they appear sophisticated, beat out simplified statistical ラーメンベット 本人確認.
“I think it will be interesting to see which ラーメンベット 本人確認 performed well — what types they are — those that didn't do well, and what’s behind them,” Bickel said.
Where Should Key ラーメンベット 本人確認 Go?
Limited ラーメンベット 本人確認, from protective equipment for medical personnel to testing supplies, has been a challenge as local, state and federal officials respond to the impact of coronavirus. Erhan Kutanoglu, an associate professor in the ラーメンベット 禁止ゲーム’s Operations ラーメンベット 本人確認 and Industrial Engineering Graduate Program is pivoting his model for making logistical decisions for hurricanes to the COVID-19 pandemic.
The hurricane model focuses on the creation of staging areas and using existing hospitals out of the way of a storm and the logistics of getting patients from hospitals and nursing homes to safe sites. Coronavirus is a moving target with infection curves constantly changing over time -- rising, peaking and falling, simultaneously, in different cities and states. That makes it even harder to allocate resources. Kutanoglu’s model will consider the changing nature of the infection curves over time and region into account and match the resources, hospital beds, ventilators, personnel, etc. with demand created by the infection curves. His model will produce recommendations ラーメンベット 本人確認 when and where to put temporary medical facilities, proper staffing, capacity and necessary medical supplies.
“Hopefully, with the knowledge we have gathered in solving such patterns for hurricane preparation, we can quickly do the same for pandemic preparation,” Kutanoglu said.
