Background
■The rapid spread of infections by the Omicron variant is spreading nationwide.
■From January 27, application to 18 prefectures including Osaka started, for a total of 34 subject prefectures.
■Some test kits are missing or their processing is delayed.
■The need to recognize infections without positive confirmation using the existing testing method is also pressing.
■We need to know the discrepancy between appearances and the actual change in infected people in a situation where testing capacity is insufficient, and
■the impact that the increase in the number of uncaptured infected people has on infections overall.
Simulation
■We use a multi-agent model that moves in two-dimensional space. The number of agents is one million people.
■Out of the 128 simulations conducted to January 24, we selected eight trials from those close to the trend in the number of positive patients in Tokyo, followed by 16 trials each, for a total of 128 trials.
■It is assumed that a certain degree of changes in action will appear due to the quasi state of emergency from January 21 to February 13.
■It is assumed that 3rd vaccinations will be carried out seven months after the 2nd vaccination.
■The effects of pre-existing immunity and medicines are assumed to be 70%.
■We carried out simulations for the three cases where the toxicity of the Omicron variant was 8, 12 and 16% of that of the Delta variant.
■We also carried out five simulations for the cases where tests per day are for 0.2, 0.4, 0.6, and 0.8% of the population and unlimited.
■We ran tests 128 times for 3 x 5 = 15 scenarios and observed their means and standard deviations.
■The number of positive patients, the number of patients in isolation, the number of people actually infected, the number of patients with moderate or severe illness, and the number of patients with severe illness were examined.
■Requests for testing that cannot be processed will be deferred.However, if the delay is more than seven days from the test request, it is assumed it will be excluded from the test subjects without waiting.
■It is assumed that pseudo-infected people are not subject to testing.
Simulation Result #1-1 (Change in Number of Positive Cases)
■The figure below is in the case where toxicity is 12% of that of the Delta variant.
■Regardless of the upper limit on testing, a rapid spread of infections will happen.
Simulation Result #1-2 (Change in Number of Positive Cases)
■When approaching the upper limit on testing capacity, growth dulls and the number stays high in accordance with the sensitivity of testing.
■If testing capacity is sufficient, the peak in the number of positive patients is 1.05 0.03% around February 26. About 147,000 people
Simulation Result #2 (Change in Number of Patients in Isolation)
■Total number of patients grasped at each time point. (Number of patients who have not recovered after finding a positive result)
■If positive patients can be detected sufficiently, the peak in the number of patients in isolation is 6.52 ±0.18% around March 6. About 910,000 people
■There is a danger of interference with the maintenance of social functions.
Simulation Result #3 (Change in Number of Actually Infected People)
■The actual number of infected people regardless of whether or not they have symptoms or have had tests at each time point.
■The peak period is around February 24 regardless of testing capacity.
■If positive patients can be detected sufficiently, the peak is 23.8 ±0.5%, or about 3.32 million people, and in the case of 0.2%, 25.0 ±0.5%, or about 3.49 million people
Simulation Result #4 (Change in Number of Patients with Moderate Illness)
■The action restriction period was 24 days and toxicity was assumed to be 8, 12 or 16% of that of the Delta variant.
■In the case of 12% toxicity, the peak was around March 8 at 1.08 ±0.03%. About 140,000 people
■There is a danger medical resources for treatment, including hospitalization, will become tight.
Simulation Result #5 (Change in Number of Patients with Severe Illness)
■The action restriction period was 24 days and toxicity was assumed to be 4 to 20% of that of the Delta variant.
■In the case of 12% toxicity, the peak was around the end of March at 0.0064 ±0.0006%. About 893 people
Insights from the simulation
■We analyzed the case in which sufficient tests could not be carried out due to tightness of testing capacity.
■Deviations from the actual number of infected people -> Occurrence of patients with moderate or severe illness who require hospitalization and treatment even without a positive test result.
■It seems the number of asymptomatic infected people in the community will increase by more than 10% due to non-testing, but the impact on the actual spread of infections is not that big.→ Even if people cannot be tested, if they have symptoms, they should isolate and be treated at the judgment of a doctor.
Issues
■As the nature of the Omicron variant becomes clearer, the simulation should be updated from time to time taking into consideration such information.
■Further scrutiny of the impact of non-testing.
■We will refine the gatherings model to help advise on detailed measures.
■Simulation of the effects of therapeutic agents expected in the future.
Supplemental information
■Details of the simulations→ http://www.intlab.soka.ac.jp/~unemi/SimEpidemic1/info/simepidemic_sim_omicronB4.html
■Details of the simulation model→ http://www.intlab.soka.ac.jp/~unemi/SimEpidemic1/info/simepidemic-model191.html
■So that we could conform to the transition of the weekly mean number of positive cases in Tokyo up to January 24, we mainly adjusted the transition of the parameter with the frequency of gatherings and the rate of infectivity, and established a subsequent scenario for its continuation.
