key: cord-0863792-c5diu4u7 authors: Liu, Xiaoyue; Huang, Jianping; Li, Changyu; Zhao, Yingjie; Wang, Danfeng; Huang, Zhongwei; Yang, Kehu title: The role of seasonality in the spread of COVID-19 pandemic date: 2021-02-19 journal: Environ Res DOI: 10.1016/j.envres.2021.110874 sha: 07a27384eb516ab5a8b278a513f5d7e7120bf928 doc_id: 863792 cord_uid: c5diu4u7 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. become available for general public since the end of 2020, while studies are still underway to 50 test whether the vaccines are still effective against these new variants (Mahase, 2021) . The 51 world is entering a new phase against in its fight against the COVID-19 pandemic, and how 52 long will it take to embrace full resumption of pre-COVID-19 normalcy remains highly 53 uncertain (Potvin, 2021) . 54 The seasonal cycle is a ubiquitous feature of influenza and other respiratory viral 55 infections, particularly in temperate climates (Martinez, 2018) . Since the beginning of the 56 outbreak, there was widespread speculation that COVID-19, like other respiratory viral 57 infections, might exhibit some form of seasonality. Research has reported that the Indonesia, and the highest COVID-19 cases in the area fit in with wind direction blows 76 (Rendana, 2020) . However, another case study in Turkey shows that COVID-19 spreads 77 more in windy weather (Coşkun et al., 2021) . Numerical simulation also indicates that the 78 microdroplets can transport in the air farther than 10 feet (3.05 m) due to wind convection, 79 causing a potential health risk to nearby people (Feng et al., 2020) . Wind and air circulation, 80 which both display seasonality, may also potentially influence the transmissibility of the virus. 81 In addition to the meteorological factors, environmental factors including air pollution 82 are also found to be related to COVID-19 incidence (Coccia, 2020a, 2020b) and other 83 respiratory infections (Tong, 2019) . Exposure to fine particulate matter, O 3 , and NO 2 can 84 influence the immune system of the susceptible population (Glencross et al., 2020) , which 85 may exert a direct impact on the severity of COVID-19 symptoms and mortality. In United 86 States, higher historical PM 2.5 exposures found to be positively associated with higher 87 county-level COVID-19 mortality rates after accounting for many area-level confounders 88 (Wu et al., 2020) . Bilal et al. (2020) found that PM 2.5 , O 3 , and NO 2 have a significant Hemisphere (SH) experience opposite seasons. Thus, in order to identify and extract the long-160 term impact of seasonality from the pandemic data and reflect its spatial discrepancy, we 161 select 5 countries in the NH and 5 countries in the SH. Figure S1 shows which performs an EMD on a copy of the input signal with added noise. When all workers 181 finish their work, a mean over all workers is considered as the true decomposition, and the 182 noise will cancel each other out. In this study, the white noise added to data has an amplitude 183 that was 0.05 times the standard deviation of the raw data, and the ensemble number is 100. 184 The result of EEMD could be expressed by the following equation: each country so that they range between 0 and 1 before conducting EEMD. (P), the quarantined (Q), and separates the recovered (R) and dead (D) cases. In this model, 208 the susceptible (S) can either be protected to become the protected (P) at the rate of 209 (protection rate) or get infected to become the exposed (E) at the rate of & (transmission rate). 210 After an individual is infected, it will take a certain period of time (pre-infectious period, 1/ 211 ) before he or she becomes infectious (I, capable of transmitting the virus to susceptible 212 individuals). The infectious will then spread the virus to others before admitted to the hospital 213 at the rate of (entering the quarantined stage, Q). The quarantined people cannot spread the 214 virus and will be reported either as the recovered cases (R) or, unfortunately, death cases (D). Table S1 ). Table 1 ). Eq. (8) to zero. Figures. 5a and 5b show the evolution of transmission rates in the NH and SH Climate factors and incidence of Middle East respiratory 580 syndrome coronavirus Seasonality of Respiratory Viral Infections: Will COVID-19 Follow Suit? 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Jianping Huang: Conceptualization, Supervision, Writing -Review & Editing. Changyu Li: Validation, Writing -review & editing. Yingjie Zhao: Writing-Reviewing and Editing. Danfeng Wang: Writing-Reviewing and Editing. Zhongwei Huang: Supervision, Conceptualization. Kehu Yang: Writing -review & editing