Hello everyone.
Warmly welcome to my presentation about the paper: Who Will survive and revive undergoing
the epidemic: analyses about POI visit behavior in Wuhan via check-in records.
Here is Zhenyu Han, a Ph.D student at Department of Electronic Engineering of Tsinghua University,
under the direction of Prof. Yong Li.
The talk consists 5 parts, first is the background.
As we all know, huge impact on social economics have been identified after the outbreak of
COVID-19.
Which began exponentially spreading after the beginning of 2020.
As the first epicenter in China, Wuhan received great impact due to COVID-19.
We want to investigate how megacities with more than 10 million citizens react to the
epidemic.
We adopt a POI check-in dataset with more than 140 thousand POIs in Wuhan city.
More importantly, we have two parallel timelines for comparison study.
This is the overall structure of our method.
After the preprocessing, we align our data and perform trend extraction for further analyses.
First is the decline stage, where the visit continually decline due to the lockdown policies
We find that all the POI categories are less lively compared with the same period in 2019.
During the pre-lockdown phase, Business received the smallest affect, while Shopping and Tourist
Attractions received greatest influence.
People tend to maintain visits for “essential” POIs prior than “non-essentials”.
In conclusion, the POI visit behavior is greatly suppressed, and non-essential POIs are the
most vulnerable parts of urban life.
From previous analyses, we find that some specific POI categories already had a greater
decline than 2019 before the lockdown.
These POI categories are more sensitive to the epidemic, acting as the canary in the
coal mine.
We want to further identify these early birds before the official release of lockdown policies.
We calculate the average visit in the first week as the baseline, and compare it with
the last day of pre-lockdown phase.
Entertainment, Food, Hotel and Shopping demonstrate a greater reduction over 35% percent.
All these categories share a higher reduction than normal times, which means the consumer
categories are more sensitive to the epidemic.
According to the relative visit change of the above “early bird” categories, we
investigate their importance towards the early sensitivity.
Entertainment and Food POIs are most sensitive that are responsible for nearly 60% of visit
change of these “early bird” categories.
Medical and Shopping POIs have equal sensitivity for the upcoming epidemic, while Hotels are
relatively insensitive.
We further investigate the revival pattern of these POIs. we obtain four different revival
patterns.
For Food, Entertainment and Hotel, these POIs got the greatest shock during the lockdown,
and have the slowest recover in post-lockdown phase.
It fits our understanding since these POIs do not belong to life-essential ones.
Shopping, Medical and School categories received moderate impact,
Business POIs received the smallest affect during the epidemic, and got recovered before
the un-lockdown.
For the Tourist Attractions, it also suppressed greatly.
However, it got an early recovery before the un-lockdown, and reached a very high level
during the post-lockdown phase.
In the last part, we investigate the perseverance of the city.
POIs act as the basic infrastructure of a city.
Given lots of POIs got closedown during the epidemic, it will be very hard for the revival
stage.
Here, we use the number of POIs as an indicator.
We compare the number of POIs before the epidemic and after the epidemic as a comparison study
to understand the resilience of Wuhan city.
We that although all POI categories have less POIs after the lockdown, the degree of reduction
is limited.
The over all number of POIs maintains stable during the lockdown.
We do not observe large scale closures in Wuhan POIs, which is a good sign
of the city resilience.
Finally is the conclusion.
First, we introduce the POI visit timeline of 2019 and 2020.
Second, we reveal the most vulnerable part of urban life under the epidemic impact.
Third, we identify the early birds in pre-lockdown phase, which will be beneficial for understanding
the early reaction of the society toward upcoming epidemic and lockdown policies.
Fourth, we recognize different revival patterns of POIs as four types, which correlates with
POI functions.
Finally, we highlight the resilience of city during the epidemic by the statistics of POI
numbers.
Existence of POI infrastructures is important for the fast recovery of social economic after
public emergencies.
Here are some important references.
Thank you for your attention.
Any question is welcomed.