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Category Archives: Behavior
On people’s reactions to the pandemic – more cars?
There is this article that argues that one result of the pandemic and the scare that it caused to a many is that people have resorted to car use during and after the lockdowns:
Vanderbilt, T. (2020) “People Are Buying Cars Because of the Pandemic. Cities May Change as a Result,“ Medium, https://gen.medium.com/people-are-buying-cars-because-of-the-pandemic-cities-may-change-as-a-result-e0657584f45e [Last accessed: 6/20/2020]
It was amusing for me to read the reference to cars as a sort of PPE but it comes as no surprise. It is psychologically like a suit of armor to some people and I guess this affects them the same way as some people’s personalities change when behind the wheel.
Whether this is true for the Philippines’ case we are now seeing somewhat but I say ‘somewhat’ because of the deficiencies in public transportation especially in Metro Manila. Government agencies in-charge of transportation seem to have found the perfect situation to roll out and push for both route rationalization and modernization. Major public transport routes have resumed operations but with buses instead of jeepneys. And slowly but somehow surely the “modern jeepneys” are being allowed but following the terms and conditions of the DOTr and the LTFRB.
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On pandemic travel patterns and the future
Here is a recent article on travel patterns as influenced by the COVID-19 pandemic.
Bliss, L., Lin, J.C.F., and Patino, M. (2020) “Pandemic Travel Patterns Hint at Our Urban Future,” Bloomberg CityLab, https://www.bloomberg.com/graphics/2020-coronavirus-transportation-data-cities-traffic-mobility/?sref=ViNyghXi [Last accessed 6/19/2020].
Are these travel patterns similar to those of our cities and municipalities in the Philippines? Or were there a different reactions or outcomes considering local factors including perhaps cultural aspects?
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On the importance of public transportation post-pandemic
I am sharing another article from Todd Litman that appear yesterday:
Litman, T. (2020) “Lessons from Pandemics: Valuing Public Transportation,” Planetizen, https://www.planetizen.com/blogs/109584-lessons-pandemics-valuing-public-transportation?fbclid=IwAR2jduFuYoyf_MoksI2Th4UoWtQYMQVOdwHuiih8JM9NxMN5pT_e1lwhgDQ [Last accessed: 6/13/2020]
The article contains material derived from previous work by the author and provides a list (and links to) resources or references related to this topic.
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Are face shields to be recommended for pedestrians and other commuters?
Here are some references regarding the use of face shields. Again, I post these here also for my easy reference whenever I need to search for such in the work I am doing or will be doing.
- Perencevich, E.N., Diekema, D.J. and Edmond, M.B. (2020) “Moving Personal Protective Equipment Into the Community – Face Shields and Containment of COVID-19,” JAMA Network, https://jamanetwork.com/journals/jama/fullarticle/2765525 [Last accessed: 5/25/2020]
- Lindsley, W.G., Noti, J.D., Blachere, F.M., Szalajda, J.V. and Beezhold, D.H. (2020) “Efficacy of Face Shields Against Cough Aerosol Droplets From a Cough Simulator,” Journal of Occupational and Environmental Hygiene, 2014;11(8):509-18.
- Mundell, E.J. (2020) “Face shields a more effective deterrent to COVID?”, WebMD, https://www.webmd.com/lung/news/20200430/face-shields-a-more-effective-deterrent-to-covid#1 [Last
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Infographics: Infection Risk Classification of Transport Modes Post-ECQ
The infection risk table I posted a few days ago was improved into the following infographics:
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COVID-19 Infection Risk Assessment of Transport Modes
I posted about the work we have been doing to assess the infection risk (i.e., spread of COVID-19) for various modes of transport considering the transition of many areas including the National Capital Region (NCR) to the General Community Quarantine (GCQ). The work was undertaken through the Transportation Science Society of the Philippines (TSSP), which is under the umbrella of the Eastern Asia Society for Transportation Studies (EASTS). Here is the outcome in the form of an “Infection Risk Classification of Transport Modes or Vehicle Types” developed by a core group of public transportation and road safety specialists among its members:
Note again that this is the product of a rapid assessment using the mentioned criteria and factors. It is a qualitative assessment and a quantitative one, given the data, would obviously been preferred. Moreover, this is an assessment for risk of infection rather than for road safety. In the “old normal”, for example, cycling and motorcycle use may have a higher risk in traffic given traffic mix, human behavior and lack of facilities to make these modes safe.
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Assessing the risk of infection from the transport safety perspective
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.
Next – Why we should not return to the old normal…
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On the DOTr GCQ Guidelines for Public Transport Operations – Rail Sector
I had previously posted for information and reference the Department of Transportation’s (DOTr) guidelines for road public transportation. Here are the guidelines for rail public transportation:
While I said that I will refrain from commenting or critiquing these guidelines starting from the previous post on road public transport, I could not help but say a few things about the case for rail. In particular, I am most concerned about the reduced capacity of trains based on the infographics above. The particular infographic states that passenger capacities for Line 1, Line 2, Line 3 and PNR would be 12, 10, 13 and 20 percent, respectively. These are very low numbers that are not even comparable to the 30 to 50% passenger capacities that road public transportation may be able to achieve. Would it be worth it (and I’m talking about financial terms here) to operate at these capacities? Or are there solutions that could increase train passenger capacities while ensuring physical separation. I use the term “physical separation” here instead of “physical distancing” because it may be possible to design not just a layout but barriers that would also be effective in minimizing if not eliminating the possibility of infection of the virus should any passenger turn out to be infected. People, after all, will be required to wear masks and even gloves. Others may opt to wear face shields. And there are also measures vs infection at the stations or terminals as well as the workplaces. What do you think?
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On the DOTr GCQ Guidelines for Public Transportation – Road Sector
I just wanted to post, share and document here the DOTr’s Guidelines for Public Transport Operations for areas under General Community Quarantine (GCQ). The images are self explanatory so I will not discuss these nor will I offer a critique at this point. The following are public and posted on DOTr’s social media pages (i.e., Facebook) and have been shared and circulating among the public. I also post it here for future reference as I do to many other references like articles and infographics.
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Reference on Bicycle Facility Preferences and Increasing Bicycle Trips
There are many references that are free for downloading. These include the latest publications from the National Academies Press that includes outputs from the National Academies of Sciences, Engineering and Medicine. I am sharing here and posting also as a reference for me to return to a new publication from the National Cooperative Highway Research Program:
NCHRP Research Report 941: Bicyclist Facility Preferences and Effects on Increasing Bicycle Trips by Watkins, Clark, Mokhtarian, Circella, Handy and Kendall.
The research was supported by the American Association of State Highway and Transportation Officials (AASHTO) in cooperation with the Federal Highway Administration (FHWA).
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Caught (up) in traffic 