dcyphr | Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period


It is important to understand the future of how COVID-19 will spread if we are to control it. The authors of this article examined known info on other viruses in the coronavirus family. They used this info to make models to predict how COVID-19 will spread after this initial pandemic. From these models, they predicted that after the pandemic, recurring outbreaks of COVID-19 will take place during subsequent winters. To avoid having more COVID-19 cases than hospitals can handle, social distancing measures may be maintained for longer periods of time. Increased hospital capacity and drugs against COVID-19 can further help this situation. Even after it seems COVID-19 has subsided, one should be wary of another potential outbreak. 


COVID-19 has afflicted thousands worldwide and can overwhelm even the most developed healthcare systems. Since we don’t currently have drugs to treat the infected, countries have been relying on social distancing, contact tracing, and other non-medicinal interventions to control virus spread. How long and how rigorously these measures need to be enforced will depend on how this initial pandemic pans out and how the virus will spread after the pandemic. The exact nature of how COVID-19 will spread after the pandemic will depend on seasonal changes in its infectivity and public immunity against it. 

COVID-19 is part of a group of viruses called the Betacoronaviruses. Past research shows that people infected with one betacoronavirus often develop immunity to other viruses in the group. This info may help predict what the extent of public immunity to COVID-19 will be after the pandemic. 

An important factor that measures how successful public health interventions are in reducing COVID-19 spread is whether healthcare facilities exceed capacity. To limit the possibility of surpassing capacity, many efforts have been made to expand or create makeshift facilities. 

In this article, the authors use viral and environmental data to predict how COVID-19 will spread after the pandemic. They draw up possible scenarios for its post-pandemic spread and discuss what they need to pick the most likely one. They then use this info to assess how long and intense social distancing needs to be in order to control the virus.

Transmission dynamics of HCoV-OC43 and HCoV-HKU1

The authors of this article examined how two other betacoronaviruses, HCoV-OC43 and HCoV-HKU1, have previously spread in the US. They found that the viruses were the most infectious in October and November and the least infectious between February and May. They also found that people infected with these viruses were immune for about 45 weeks. Each of the two viruses also provided immunity against the other, though this was more noticeable with HCoV-OC43.

Simulating the transmission of SARS-CoV-2

The models created from betacoronavirus data have produced the following insight:

- COVID-19 can spread at any time of the year, though its infection rate would likely be the highest during winter months

- If COVID-19 infections don’t provide permanent immunity, outbreaks will likely be recurring

- However, if COVID-19 infections provide permanent immunity, the virus could disappear in 5+ years after its first outbreak

- Seasonal differences in COVID-19 infectivity could vary from region to region

- Low levels of immunity provided by other betacoronaviruses would make COVID-19 seem to disappear, but it would likely reappear after a few years

Assessing intervention scenarios during the initial pandemic wave

Since it could take months to years to develop drugs and vaccines to combat COVID-19, non-medicinal interventions such as social distancing are vital. 

The authors evaluated the potential course of the pandemic if only one-time social distancing measures were put in place. Such measures would reduce peak infections, but would lead to a resurgence in cases after social distancing ends. When accounting for seasonal changes, the peak infections witnessed in these resurgences could be even greater than in situations where the virus isn’t controlled. 

Meanwhile, periodic social distancing could prevent healthcare systems from being overwhelmed. The length of time between each new session of social distancing would increase as more people develop an immunity against the virus. Regardless, with hospital capacities remaining the same, the pandemic in this scenario could last into 2022. If hospital capacities are increased in this scenario, we could see social distancing being fully gone sometime in 2021, with the pandemic ending in 2022. 


The authors iterate the key points that they’ve drawn from the predictive models they’ve made. They note some limitations of this study, including the fact that only five seasons of betacoronavirus data were used. It was assumed that seasonal differences in viral infectivity would be the same every year. Several other biological characteristics were assumed to be the same for different betacoronaviruses. Their predictions are also only applicable to regions with temperate environments.

The predictions made here have uncovered what info is needed to know how this pandemic will play out. More serological studies should be conducted, as they could provide insight into the extent of the immunity COVID-19 infections provide.

If we are to implement periodic social distancing, we should have more viral testing to see when social distancing periods should begin and end. Any COVID-19 treatments that are developed could reduce the amount of social distancing we need and reduce the burdens on hospital capacity. Regardless, such treatments are likely far off, so social distancing will absolutely be needed.