![](bgc.png)
0 7 14 21 28
Number of days
0
20
40
60
80
100
% of infected people
% of infected people with 30% of vehicles per day
Unrestricted Movement
Restricted Movement
77%
63%
0 7 14 21 28
Number of days
0
20
40
60
80
100
% of infected people
% of infected people with 60% of vehicles
Unrestricted Movement
Restricted Movement
77%
85%
Figure 22: We show an equivalence point between unre-
stricted movement and restricted movement for the combi-
nation of transport modes. (a) The scenario of 30% of ve-
hicles with unrestricted movement shows a peak of 77% in
the number of infections. (b) The scenario of 60% of vehi-
cles with restricted movement shows a peak of 77% in the
number of infections.
0 7 14 21 28
Numberofdays
0
0.25
0.5
0.75
1
Normalisedvalueofnumberofinfectedpeople
Comparingthenumberofinfectionsinthreewaves
ofthepandemicwiththesimulationstudy
Unrestricted
Restricted
FirstWave
SecondWave
ThirdWave
Figure 23: A comparison of our combined transportation
simulation results to the three waves of COVID-19 in Goa.
The peak of the second wave resembles the case of unre-
stricted and the peak of the third wave resembles that of
restricted movement. This is a positive indicator for the ac-
curacy of the simulation as cases rose less rapidly for the
third wave, similar to the case of restricted movement.
used to identify exposure to the virus. This will re-
quire much more computation power as we need to
track each person’s and vehicle’s movement. We may
add vaccinated people to the simulation, who will
have immunity or fewer chances of getting the dis-
ease.
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Studying the Impact of Transportation During Lockdown on the Spread of COVID-19 Using Agent-Based Modeling
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