An operational nonhydrostatic mesoscale model has been developed by the Numerical Prediction Division (NPD) of the Japan Meteorological Agency (JMA) in partnership with the Meteorological Research Institute (MRI). The model is based on the MRI/NPD unified nonhydrostatic model (MRI/NPD-NHM), while several modifications have been made for operational numerical weather prediction with a horizontal resolution of 10 km. A fourth-order advection scheme considering staggered grid configuration is implemented. The buoyancy term is directly evaluated from density perturbation. A time-splitting scheme for advection has been developed, where the low-order (second order) part of advection is modified in the latter half of the leapfrog time integration. Physical processes have also been revised, especially in the convective parameterization and PBL schemes. A turbulent kinetic energy (TKE) diagnostic scheme has been developed to overcome problems that arise to predict TKE. The model performance for mesoscale NWP has been verified by comparison with a former operational hydrostatic mesoscale model of JMA. It is found that the new nonhydrostatic mesoscale model outperforms the hydrostatic model in the prediction of synoptic fields and quantitative precipitation forecasts.

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While mass gathering events have resumed in conjunction with vaccine-testing (VT) packages, their effects on reducing COVID-19 risk remain unclear. Here, we used an environmental exposure model to analyze the effects of vaccinations and proof of negative test results on reducing infection risk and serious illness among spectators at mass gathering events. We then analyzed the difference in risk with and without VT and regular seat zoning. Risk of infection and serious illness were quantified using a model incorporating parameters such as vaccination coverage, vaccine prevention effectiveness, and sensitivity of polymerase chain reaction (PCR) or qualitative antigen tests. When vaccine prevention effectiveness was 50% (corresponding to 4 months for the delta variant and 1-2 months for the omicron variant after the second vaccine dose), the risk of infection and serious illness among vaccinated spectators were 0.32-0.40 and 0.13-0.16 times of those who tested negative, respectively. In contrast, the risks of infection and serious illness among vaccinated spectators without measures such as mask wearing were 4.0 and 1.6 times higher than those among unvaccinated spectators with such measures, respectively. The risk of infection with an 80% vaccination coverage and a vaccine prevention effectiveness of 20% (corresponding to 5-6 months for the delta variant or 3-4 months for the omicron variant after the second vaccine dose) was comparable to that of a 20% vaccine coverage and a vaccine prevention effectiveness of 80% (corresponding to 1-3 months for delta variant after the second vaccine dose). Regarding zoning, there was little difference in risk with a vaccination coverage of ≥80%. Adherence to individual measures after vaccination and maintenance of high vaccine effectiveness among spectators at stadiums are important for reducing risk of infection and serious illness. Furthermore, seat zoning did not affect overall infection risk reduction.

There is a need to evaluate and minimise the risk of novel coronavirus infections at mass gathering events, such as sports. In particular, to consider how to hold mass gathering events, it is important to clarify how the local infection prevalence, the number of spectators, the capacity proportion, and the implementation of preventions affect the infection risk. In this study, we used an environmental exposure model to analyse the relationship between infection risk and infection prevalence, the number of spectators, and the capacity proportion at mass gathering events in football and baseball games. In addition to assessing risk reduction through the implementation of various preventive measures, we assessed how face-mask-wearing proportion affects infection risk. Furthermore, the model was applied to estimate the number of infectors who entered the stadium and the number of newly infected individuals, and to compare them with actual reported cases. The model analysis revealed an 86%-95% reduction in the infection risk due to the implementation of face-mask wearing and hand washing. Among the individual measures, face-mask wearing was particularly effective, and the infection risk increased as the face-mask-wearing proportion decreased. A linear relationship was observed between infection risk at mass gathering events and the infection prevalence. Furthermore, the number of newly infected individuals was also dependent on the number of spectators and the capacity proportion independent of the infection prevalence, confirming the importance of considering spectator capacity in infection risk management. These results highlight that it is beneficial for organisers to ensure prevention compliance and to mitigate or limit the number of spectators according to the prevalence of local infection. Both the estimated and reported numbers of newly infected individuals after the events were small, below 10 per 3-4 million spectators, despite a small gap between these numbers.

We developed an environmental exposure model to estimate the coronavirus disease 2019 (COVID-19) risk among participants at outdoor music festivals and validated the model using two real events—one in Japan (Event 1) and one in Spain (Event 2). Furthermore, we considered a hypothetical situation in which Event 1 was held but enhanced measures were implemented to evaluate the extent to which the risk could be reduced by additional infection control measures, such as negative antigen tests on the day of the event, wearing of masks, disinfection of environmental surfaces, and vaccination. Among 7,392 participants, the total number of already- and newly-infected individuals who participated in Event 1 according to the new model was 47.0 (95% uncertainty interval: 12.5–185.5), which is in good agreement with the reported value (45). The risk of infection at Event 2 (1.98 × 10−2; 95% uncertainty interval: 0.55 × 10−2–6.39 × 10−2), calculated by the model in this study, was also similar to the estimated value in the previous epidemiological study (1.25 × 10−2). These results for the two events in different countries highlighted the validity of the model. Among the additional control measures in the hypothetical Event 1, vaccination, mask-wearing, and disinfection of surfaces were determined to be effective. Based on the combination of all measures, a 94% risk reduction could be achieved. In addition to setting a benchmark for an acceptable number of newly-infected individuals at the time of an event, the application of this model will enable us to determine whether it is necessary to implement additional measures, limit the number of participants, or refrain from holding an event.