It has been reported that the transmission of COVID-19 can be influenced by the variation of environmental factors due to the seasonal cycle. However, its underlying mechanism in the current and onward transmission pattern remains unclear owing to the limited data and difficulties in separating the impacts of social distancing. Understanding the role of seasonality in the spread of the COVID-19 pandemic is imperative in formulating public health interventions. Here, the seasonal signals of the COVID-19 time series are extracted using the EEMD method, and a modified Susceptible, Exposed, Infectious, Recovered (SEIR) model incorporated with seasonal factors is introduced to quantify its impact on the current COVID-19 pandemic. Seasonal signals decomposed via the EEMD method indicate that infectivity and mortality of SARS-CoV-2 are both higher in colder climates. The quantitative simulation shows that the cold season in the Southern Hemisphere countries caused a 59.71 ± 8.72% increase of the total infections, while the warm season in the Northern Hemisphere countries contributed to a 46.38 ± 29.10% reduction. COVID-19 seasonality is more pronounced at higher latitudes, where larger seasonal amplitudes of environmental indicators are observed. Seasonality alone is not sufficient to curb the virus transmission to an extent that intervention measures are no longer needed, but health care capacity should be scaled up in preparation for new surges in COVID-19 cases in the upcoming cold season. Our study highlights the necessity of considering seasonal factors when formulating intervention strategies.

据报道，由于季节周期，COVID-19的传播可能会受到环境因素变化的影响。然而，由于数据有限且难以区分社会距离的影响，其当前和未来传播模式的根本机制仍不清楚。了解季节性在 COVID-19 大流行传播中的作用对于制定公共卫生干预措施至关重要。这里，使用 EEMD 方法提取了 COVID-19 时间序列的季节性信号，并引入了结合季节性因素的修改后的易感、暴露、传染、恢复 (SEIR) 模型，以量化其对当前 COVID-19 大流行的影响。通过 EEMD 方法分解的季节性信号表明，SARS-CoV-2 的传染性和死亡率在寒冷气候下均较高。定量模拟显示，南半球国家的冷季导致感染总数增加59.71±8.72%，而北半球国家的暖季则导致感染总数减少46.38±29.10%。 COVID-19 的季节性在高纬度地区更为明显，在那里观察到环境指标的季节性幅度更大。仅凭季节性不足以遏制病毒传播，以至于不再需要干预措施，但应扩大医疗保健能力，为即将到来的寒冷季节新的 COVID-19 病例激增做好准备。我们的研究强调了制定干预策略时考虑季节性因素的必要性。