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After this company had a Covid outbreak, they took a data-driven preventative approach

 

Client

Distribution & Logistics Company

…………………………

Our Solutions

  • Ambilytics: Data analytics & forecasting
  • AmbiAir: IoT connected indoor air quality monitor

Challenge

Simon*, the owner of a distribution and logistics business based in the heart of Dublin city centre was in a difficult situation. His staff couldn’t work from home, so he had introduced stringent work practises, in line with Government guidelines, to protect his staff from the risk of Covid-19 infection. These measures included social distancing, mask-wearing and a rigorous cleaning regime. Despite these measures, before the Christmas break one member of staff who worked in the office was diagnosed with Covid-19.

Alarmed, Simon requested that all employees be tested, all the staff members who worked in the office tested positive. However, the staff members who worked in the warehouse area, which consisted of 75% of the workforce, all tested negative.

Understandably Simon was keen to investigate the issue and to look at what measures could be put in place to reduce the risk of a recurrence. Given that the staff members in an office tested positive despite social distancing and mask-wearing, he decided to look for another Covid-19 spread factor. Knowing that the primary infection route for Covid-19 is through airborne droplets he focused his attention on the ventilation within the office area. While it would have been possible to make engineering changes to improve ventilation, these were expensive and not something that could be quickly implemented.

Instead, Simon decided to see if simple operational changes would reduce the Covid-risk in the office. A critical factor for him was being able to see whether the changes he was planning to introduce were actually working to keep his staff healthy and safe.

 

Approach

So, he installed four AmbiAir units across his business; two were installed in the warehouse and the other two units in the office area. The data showed that, as he expected, the warehouse area had excellent natural ventilation being open to the air during the workday. The data in the office area, on the other hand, showed consistently high levels of CO2, often exceeding 2000ppm and mostly averaging around 1500ppm.

CO2 concentration

This was where he needed to take quick action.

With the office ventilation so poor, he rapidly found himself depending on the predictive alerts within Ambilytics to manage the Covid-risk. He had set these up to alert him 5 minutes before CO2 levels were forecasted to rise above 800ppm and again above 1000ppm. This let him take preventative action which included simple things like opening a window or staff leaving the office for a short period.

The software even showed him, that if he continued with the methods he was currently using that the algorithm predicted the CO2 levels would continue to fall.

CO2 forecast in office

This approach provided a layer of reassurance to his employees, already wary and who did not have the option to work from home.

Results

Simon had taken many measures to protect his staff and it was not possible to conclusively prove that the outbreak before Christmas was tied to poor ventilation. However, given that the data generated in the office showed high CO2 levels and therefore poor ventilation (a key factor contributing to the spread of Covid-19) and the fact that 100% of the staff in the office contracted the disease while none of their colleagues in the warehouse where there was excellent ventilation did, Simon thought it likely ventilation was a high-risk factor and therefore something he needed to continue to monitor, predict and take mitigation actions.

Simon is considering possible structural changes, but what building works actually need to be done and their long-term efficiency is something he will determine using the data already generated, now and into the future.

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