Non-pharmaceutical interventions (NPIs) are currently holding the fort against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent for the coronavirus disease 2019 (COVID-19) pandemic. A few NPIs that have been adopted globally are travel restrictions, social distancing, and personal protective measures.
Currently, successful treatments for COVID-19 disease, or effective vaccines against SARS-CoV-2, are absent. While the virus has infected over 58.5 million individuals and claimed over 1.38 million lives, such NPIs are primarily responsible for averting an even worse crisis everywhere. NPIs are implemented to delay and moderate the spread of the virus in a population.
Under the rapidly changing epidemiological situations in the face of COVID-19, governments across the world have implemented diverse NPIs. These interventions were employed with or without scientific evidence on the individual and combined effectiveness of these measures, the degree of compliance of the population and societal impressions.
A recent article, published in the journal Nature Human Behaviour, analyses quantitatively the NPIs implemented in different geographies and their impact on the effective reproduction number, Rt, of COVID-19. In this study, Dr. Peter Klemik and his team use a comprehensive, hierarchically coded dataset of 6,068 NPIs implemented in March–April 2020 in 79 territories. This is the period when most European countries and the United States experienced their first SARS-CoV-2 infection waves.
Also, they investigate country-specific control strategies as well as the impact of selected country-specific metrics. In this study, the authors dissect and elaborate on the direct impact and the collateral consequences when these interventions are implemented.
To analyze the impact of government interventions on Rt, the authors studied using harmonized results from a multi-method application. They propose a modeling approach that combines the four computational techniques merging statistical, inference, and artificial intelligence tools.
From the dataset of hierarchical taxonomy of 6,068 NPIs, the authors observe that the themes of social distancing and travel restrictions top all the methods. In contrast, environmental measures (for example, cleaning and disinfection of shared surfaces) rank least effective.
The authors find the most considerable impacts on Rt in the following: small gathering cancellations, the closure of educational institutions, border restrictions, increase in healthcare and public health capacities, individual movement restrictions, national lockdown (including stay-at-home order in US states).
They also find additional NPI categories that are consensual in their methods: mass gathering cancellations, risk-communication activities to inform and educate the public and government assistance to vulnerable populations.
As opposed to these, the least effective interventions they find: government actions to provide or receive international help, measures to enhance testing capacity or improve case detection strategy (which may lead to a short-term rise in cases), tracing and tracking measures, land border and airport health checks and environmental cleaning.
The most effective communication strategies include warnings against travel to and return from high-risk areas and several measures to actively communicate with the public. Such as, to encourage staying at home, social distancing, workplace safety measures, self-initiated isolation of people with mild respiratory symptoms, and information campaigns (through various channels including the press, flyers, social media, or phone messages).
In this study, the authors also validate their findings with external datasets and find the most full-consensus measures.
Analysis from this study also indicates substantial variations between world geographical regions in terms of NPI effectiveness. The authors present this as a measure of the heterogeneity of NPI rankings in different territories through an entropic approach. Whereas the social distancing measures and travel restrictions are the most effective, they show a high entropy, i.e., the effectiveness varies considerably across countries. But the case identification, contact tracing, and healthcare measures show substantially less country dependence.
None of the individual NPIs is independent. Hence, the impact of a specific NPI cannot be evaluated in isolation. Therefore, the authors quantify whether the effectiveness of a specific NPI depends on its epidemic age of implementation: for each country and each NPI, the authors obtain a curve of the most likely change in Rt versus the adoption time of the specific NPI.
The authors present a detailed discussion on the change in Rt as a function of the adoption time of selected NPIs, averaged over countries where those NPIs had been adopted.
The results from this study indicate that a suitable combination of NPIs is necessary to curb the spread of the virus - no single NPI can decrease Rt below one. There are less disruptive and costly NPIs that are as effective as more intrusive and drastic ones, such as the national lockdown. This study will enable policymakers to possess at hand decisive NPIs - each tailored to the specific country and its epidemic age - to intelligently combat a resurgence of COVID-19 or any other future respiratory outbreak.
“The ensemble of these results calls for a strong effort to simulate what-if scenarios at the country level for planning the most probable effectiveness of future NPIs, and, thanks to the possibility of going down to the level of individual countries and country-specific circumstances, our approach is the first contribution toward this end.” - Dr. Peter Klemik and his team
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