My colleagues and I have been developing a risk assessment table for land transport modes to be submitted to the UP COVID-19 Response Team. We did a rapid assessment using mainly concepts from road safety.

The concepts are fairly simple. Risk assessment can be based on the likelihood of contracting the virus gauged from certain exposure factors. Exposure estimation may be quantitative where metrics are applied and data collected for the analysis. Estimation may alternatively qualitative based on experiences, perceptions, expert opinions, etc. but subject to logic (e.g., careful deduction). In road safety, for example, these factors may be defined as three: time, distance and volume.

Time exposure can be determined using travel time as a metric. Longer the travel times mean higher exposures for a commuter. Higher exposure translate to a higher likelihood that a person may become involved in a road crash. Thus, a commuter traveling for 1 hour, one way, will have a higher likelihood of being involved in a crash compared to another traveling only 10 minutes even assuming that both use the same mode of transport. Applied to the risk of viral infection, longer commutes may mean people can have higher exposure to potential carriers of the virus.

Distance exposure can be determined using travel distance as a metric. Longer travel distances mean higher exposures for a commuter. Higher exposure again translate to a higher likelihood that a person may become involved in a road crash. Thus, a commuter with a travel distance of 10 kilometers will have a higher likelihood of being involved in a crash compared to someone traveling only 1 kilometer. Applying this to the risk of viral infection is similar to the previous case for time exposure even when assuming the same mode of transport.

Volume exposure can be determined using both the volume of vehicles as well as the number of passengers inside the vehicles. The more vehicles or people you have on the roads interacting, the higher the likelihood of one becoming involved in a crash. It can also be argued that riding public transport in high volume, mixed traffic makes a passenger have a higher likelihood of being involved in a crash. Again, applying this to the risk of viral infection, it should be easy to understand why physical distancing is necessary in vehicles as well as outdoors when walking or cycling. It should also extend to having less vehicles on the road to further reduce the likelihood of spreading the virus.

In the real world, we cannot isolate each factor from one another. Instead, we have to contend with all three combining to create various scenarios. Along expressways, for example, the volume of vehicles might be high and so are distances. Time exposure can be lower due to high speeds. Yet high speeds can contribute to increased likelihood of crashes. Meanwhile, traffic congestion has all the ingredients for maximizing the likelihood for crashes and, by extension, viral infection. Long commutes (by time and distance) plus high volumes of people and vehicles combine to create the worst case scenario from the perspectives of both road safety and infection, which are both public health issues.

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