Is SARS-CoV-2 a seasonal virus?

In a recent study posted on medRxiv* Preprint server Pfizer scientists have asked whether the case rates for coronavirus disease 2019 (COVID-19) in US (US) and European (EU) countries follow seasonal patterns using a time-series model. I decided.

study: Is COVID-19 seasonal?Time series modeling approach.. Image Credit: CKA / Shutterstock

Background

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) may follow a seasonal pattern like other respiratory viral infections. The interaction of viral pathogens, hosts, and environmental factors such as seasonal temperature, humidity, and increased indoor activity during the winter can affect the stability of viruses outside the host.

In addition, previous vaccine strategies have struggled to keep up with the emergence of new SARS-CoV-2 substances of concern (VOCs). Without data, public health agencies have no clue as to when to deploy booster doses that may help maintain peak levels of protection against serious illness throughout the pandemic.

Based on these observations, identifying seasonal patterns of SARS-CoV-2 infection is important for determining public health plans and optimal timing of booster immunization.

About research

In this study, researchers used COVID-19 data. Our World in Data (OWID) Database from March 2020 to April 2022 in the United States and five EU countries (EU5), including Spain, France, Germany, Italy and the United Kingdom. Twitter Decomposition method and generalized extreme student deviation (GESD) test.

Twitter Time Series Decomposition by Generalized Extreme Studentized Deviation (GESD) Anomaly Detection of COVID-19 Rate, March 7, 2020-April 9, 2022. Panel A: The world in US data. Panel B: EU5: Italy, Germany, France, Spain, UK, Our World in Data. The shaded area represents the normal range of data points.

Twitter Time Series Decomposition and Generalized Extreme Studentized Deviation (GESD) Anomaly Detection of Influenza Cases, March 1, 2014-April 10, 2020. The shaded area represents the normal range of data points. Data Source: US Centers for Disease Control and Prevention FluView

In addition, the team used Meta Prophet A time-series-breaking approach, US holidays, predominant circular mutations, and seasonality that adjust the age-specific proportions of fully vaccinated individuals over time.In addition, they used Markov Chain Monte Carlo Simulation Calculates the uncertainty interval of the decomposed components of the Prophet time series.

Researchers performed a sensitivity analysis to determine the impact of the data source.For example, we compared data from the US Centers for Disease Control and Prevention. [CDC] For OWID data. Finally, the Centers for Disease Control and Prevention (CDC) FluView data was used to examine trends in seasonal influenza to determine the accuracy of the time series model.

Survey results

Similar seasonal SARS-CoV-2 cases surged from November to February in the northern, Midwest, and western regions of the US Census Bureau. However, the authors also noted the second seasonal peak in the southern United States at the end of the summer of 2021. Anomaly detection analysis reliably predicted seasonal influenza spikes over the six seasons of influenza in the United States. Similarly, the anomalous plot detected a higher than expected COVID-19 rate in the United States between November and March each year and returned to normal by October 2021.

Sensitivity analysis confirmed that the threshold for the rate of anomalous observations had little effect on seasonal trends. In addition, the data source did not affect the seasonal COVID-19 trends in the United States. Therefore, they were similar in both US CDC and OWID data.

Meta’s Prophet model-based sensitivity analysis also showed the annual seasonal component of the US COVID-19 case rate from December to February, with holiday effects near Christmas and New Year, Independence Day, and Spring Holidays. .. The same analysis showed very similar trends for influenza, but with a little more variability remaining.

Conclusion

The study results supported the deployment of protective measures against SARS-CoV-2 each year in the same time frame as influenza prevention. In the United States and EU5, cases of seasonal respiratory virus infections surge from December to March each year. Therefore, according to the authors, administration of COVID-19 booster shots several months before winter significantly reduces the burden of COVID-19 illness.

The methodology used in the study was superior to the anomaly detection methods commonly used to identify seasonal patterns of common respiratory viruses. It was shown that the flu season was longer than the COVID-19 season. This is probably due to additional non-pharmaceutical measures taken against COVID-19, including masking and social distance. The authors emphasized the need for further confirmatory studies in the Southern Hemisphere and other US and EU regions to inform public health strategies and stay ahead of the upcoming seasonal wave of COVID-19.

Studies show that administering multiple booster doses of the COVID-19 vaccine each year is programmatically difficult and can also lead to a phenomenon called “boost immune fatigue.” Therefore, timing of administration of COVID-19 vaccine annually is the wisest approach to give vaccine protection when COVID-19 cases are proliferating. In addition, giving additional booster shots to some high-risk groups moving forward requires careful consideration of epidemiological, profit risk, and program. Therefore, vaccination alone is unlikely to lead to the elimination of SARS-CoV-2, but on-time deployment of the vaccine can mitigate the future wave of SARS-CoV-2 infection.

*Important Notices

medRxiv Publish preliminary scientific reports that should not be considered definitive as they have not been peer-reviewed, guide clinical practice / health-related behaviors, and should not be treated as established information.