Infection Simulation based on Proposed Human Behavior Models derived from SNS and Press Data #8

Change in incubation period for Delta variant
We used to have the same time period for all variants, but now we have made the period for Delta variant shorter than the conventional and Alpha variant

Change in vaccine effect
The decline in the effect of the vaccine is incorporated to the extent that the effect of the vaccine in infection prevention is halved 6 months after the 2nd dose. In addition, infection prevention effect against Delta variant is 0.85 times that of the conventional variant

Projecting the number of positive cases by changing the effect of telework to be implemented from 9/1 to 10/31, assuming the declaration of a state of emergency from 8/25 to 9/12. In light of human flow data, a simulation result of between a state of emergency and priority measures seems realistic. If a state of emergency is declared, telework is expected to control the spread of infection, but if only priority measures are taken, the number of positive cases is expected to return to an upward trend due to the increased human flow and the decline of vaccine effectiveness.

In the simulation of positive cases by age, new positive cases under 14 years old were confirmed, and new positive cases in the age group of 15~64 years old were more frequent. On the other hand, the number of new positive cases among the elderly is assumed to be low.

Conditions
➡Telework for agents between 15 and 64 years old
➡Telework rate: 0%  50%  70%
➡The effect of the state of emergency is between that of priority measures and that of the 3rd state of emergency.

If telework is implemented, the number of new positive cases in Tokyo is likely to decline gradually.
On the other hand, when implementing measures comparable to priority measures, it is necessary to keep a high telework rate.

In the simulation of positive cases by age, there were more new positive cases in the age group of 15~64 years old regardless of the telework rate. If telework is not implemented, the number of positive cases may trend upward again from October.

Conditions
➡Telework for agents between 15 and 64 years old
➡Telework rate: 0%  50%  70%
➡The effect of the state of emergency is between that of priority measures and that of the 3rd state of emergency.

Twitter tweet analysis shows that although there are fluctuations around the start of the Tokyo Olympics, the feeling of scared has increased since 7/24 compared to the 2nd and 3rd state of emergency.

During the 4th state of emergency and priority measures to prevent the spread of infectious disease, we have confirmed a decrease in human flow in all regions.

・Mobile spatial statistics were used to identify changes in the population flow in downtown areas within the region where the state of emergency was declared.
・During past state of emergency, we have seen a significant reduction in human flow in each of the areas where the state of emergency was declared. The effect (reduction in the number of people in the region) was strongest at the time of the 1st declaration, with no significant difference in effect between the 2nd and 3rd.
・After the 4th state of emergency was declared, a decrease in human flow was observed in all areas where had the declaration. A decrease in human flow in downtown areas was observed, although not as drastic as during previous declarations.
・In areas where the priority measures has been newly declared (Hokkaido), the decrease in the human flow continues.

■Kabukicho, Tokyo (Number of people in the area by time axis)

■Shibuya Center Street, Tokyo (Number of people in the area by time axis)

■Ikebukuro, Tokyo (Number of people in the area by time axis)

■Harajuku, Tokyo (Number of people in the area by time axis)

■Ueno Ameyoko, Tokyo (Number of people in the area by time axis)

■South side of Shinagawa Station, Tokyo (Number of people in the area by time axis)

■Tokyo Station, Tokyo (Number of people in the area by time axis)

■Odaiba Tokyo Teleport, Tokyo (Number of people in the area by time axis)

■Yokohama Station, Kanagawa (Number of people in the area by time axis)

■Kawasaki Station, Kanagawa (Number of people in the area by time axis)

■Hiyoshi Station, Kanagawa (Number of people in the area by time axis)

■Kitashinchi, Osaka (Number of people in the are by time axis)

■Kawaramachi, Kyoto (Number of people in the area by time axis)

■Nakasu-Kawabata, Fukuoka (Number of people in the area by time axis)

■Susukino, Hokkaido (Number of people in the area by time axis)