The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has taken the world by surprise. No one was prepared for a widespread pandemic, prompting countries to adopt a range of measures aimed at curbing its spread while vaccine development was commenced.
A new study by researchers at the City University of Hong Kong examined the efficacy of non-pharmaceutical interventions (NPIs) on controlling the coronavirus disease 2019 (COVID-19) pandemic, the illness SARS-CoV-2 causes.
Since most COVID-19 infections appear to have mild or moderate symptoms, it is crucial to reduce the number of severely infected cases and deaths rather than only flattening the total epidemic curve.
The study looked into the common NPIs conducted in New York City to see which one is the most effective in preventing virus spread and reducing deaths.
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
The coronavirus pandemic
In December 2019, doctors and health care workers in Wuhan City, China, reported a cluster of pneumonia-like cases. The illness has spread in the city and was linked to a wet seafood market, where wild animal trade is rampant.
Since then, SARS-CoV-2 has spread to 191 countries and territories and infected over 67.11 million people. The illness has caused more than 1.53 million deaths, and it continues to spread as lockdown measures have been lifted in most countries.
The pandemic has taken a toll on the economy, with millions losing their jobs. Many businesses have been closed, and experts say it will take many years to bring back what was before the pandemic.
The control responses varied across countries, with different outcomes in terms of epidemic size and social disruption.
The study
In the study, which appeared on the preprint medRxiv* server, the researchers presented an age-specific susceptible-exposed-infected recovery-death model that considers the unique characteristics of COVID-19. The team wanted to examine the efficacy of various non-pharmaceutical interventions (NPIs) in New York City.
The team conducted a mathematical model to see the effect of NPIs, including social distancing measures on the number of infections. The NPIs considered in the study include school closure, social distancing for the entire population, social distancing for the elderly who are more than 65 years old, and adaptive policy, where a stringent control measure or full lockdown is implemented.
The team found that the control policies implemented in New York City reduced the number of infections by 72 percent and the number of deaths by 76 percent by the end of 2020.
The team also revealed that among all the NPIs, social distancing for the entire population and the protection of older adults in the public areas are the most effective control measures in decreasing severe infections and deaths tied to COVID-19.
Compared with the social distancing only for the elderly, social distancing for the entire population comes with more significant social disruption. However, though the social distancing for the elderly would not significantly reduce the total number of infections, it can effectively reduce the number of deaths.
The results reflect the clinical characteristics of COVID-19, which are high transmissibility but a high mortality or death rate only among the elderly and those with an underlying medical condition. It is for this reason social distancing for the elderly has been imposed in many countries.
Meanwhile, they also found that the school closure policy may not work effectively in reducing the number of COVID-19 deaths.
Our simulation results provide novel insights into the city-specific implementation of NPIs with minimal social disruption considering the locations and population characteristics,” the team concluded in the study.
The researchers added that it is not practical to implement the NPIs for extended periods because the social disruption could lead to a substantial economic loss. When there is an enormous economic loss, other public health problems could be triggered.
They further found that the immediate relaxation of NPIs after a peak of infections could lead to an instant rebound. Simultaneously, the team found that the later the relaxing of NPIs is implemented, the smaller the rebound size is.
The researchers recommend that the resumption of work and production should be gradually and carefully implemented. Although full lockdown is more effective in reducing the number of infections and deaths, it cannot last for a long time.
The adaptive policy, which seems to work in controlling the epidemic size, but leads to unrealistically frequent 325 switches between lockdown and relaxation, making it difficult to be realized,” the team wrote in the study.
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Source:
Journal references:
- Preliminary scientific report.
Yang, J., Zhang, Q., Cao, Z., Gao, J., et al. (2020). The impact of non-pharmaceutical interventions on the prevention and control of COVID-19 in New York City. medRxiv. doi: https://doi.org/10.1101/2020.12.01.20242347,https://www.medrxiv.org/content/10.1101/2020.12.01.20242347v1
- Peer reviewed and published scientific report.
Yang, Jiannan, Qingpeng Zhang, Zhidong Cao, Jianxi Gao, Dirk Pfeiffer, Lu Zhong, and Daniel Dajun Zeng. 2021. “The Impact of Non-Pharmaceutical Interventions on the Prevention and Control of COVID-19 in New York City.” Chaos: An Interdisciplinary Journal of Nonlinear Science 31 (2): 021101. https://doi.org/10.1063/5.0040560. https://aip.scitation.org/doi/10.1063/5.0040560.
Article Revisions
- Apr 3 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.