Optimising food plants for worker safety

The COVID-19 pandemic has threatened the food supply in the United States, in part due to food industry workers falling ill, which reduces the workforce and can lead to temporary facility shutdowns.

A project by Cornell University will use computer modelling and outreach to find optimal strategies to minimise cases and transmission among workers in food processing facilities while maintaining the best possible production.

Researchers will collaborate with a dozen meat, dairy and produce industry partners to explore potential solutions in real-world settings.

Lead researcher Renata Ivanek said the project will address current issues while also providing valuable insights for future disease outbreaks.

“This is a problem that requires rapid solutions. We need to solve this right now,” Ivanek said.

Keeping workers safe in the food production industry has been a challenge since they often need to work close to each other, increasing the risk of transmission.

Many companies have tried to address the risk by shutting down a portion of their production lines and adding plexiglass dividers.

However, this has reduced production capacity and has added to the complexity of maintaining production flows, as each facility is unique.

“Part of the project is to investigate how segments of the food production industry differ and how to develop control strategies that will fit a specific industry segment,” Ivanek said.

The project aims to develop mathematical models relating to how a facility produces food to how COVID-19 spreads in plants, and how one affects the other.

“The goal is to optimise by looking into different interventions that have already been proposed, and in some cases also implemented, and try to find the optimal combination of measures,” Ivanek said.

Once a model has been developed and validated, it will be scaled up and applied in several specific facilities to validate it in real-world settings.

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