Non-pharmaceutical interventions during the COVID-19 pandemic: a rapid review

Abstract

Infectious diseases and human behavior are intertwined. On one side, our movements and interactions are the engines of transmission. On the other, the unfolding of viruses might induce changes to our daily activities. While intuitive, our understanding of such feedback loop is still limited. Before COVID-19 the literature on the subject was mainly theoretical and largely missed validation. The main issue was the lack of empirical data capturing behavioral change induced by diseases. Things have dramatically changed in 2020. Non-pharmaceutical interventions (NPIs) have been the key weapon against the SARS-CoV-2 virus and affected virtually any societal process. Travels bans, events cancellation, social distancing, curfews, and lockdowns have become unfortunately very familiar. The scale of the emergency, the ease of survey as well as crowdsourcing deployment guaranteed by the latest technology, several Data for Good programs developed by tech giants, major mobile phone providers, and other companies have allowed unprecedented access to data describing behavioral changes induced by the pandemic. Here, I aim to review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 347 articles written by more than 2518 of authors in the last 12 months. While the large majority of the sample was obtained by querying PubMed, it includes also a hand-curated list. Considering the focus, and methodology I have classified the sample into seven main categories: epidemic models, surveys, comments/perspectives, papers aiming to quantify the effects of NPIs, reviews, articles using data proxies to measure NPIs, and publicly available datasets describing NPIs. I summarize the methodology, data used, findings of the articles in each category and provide an outlook highlighting future challenges as well as opportunities *

Emergence of universality in the transmission dynamics of COVID-19

“…This is to be expected as these countries have very different population densities and different patterns of inhomogeneities in the density of population. Moreover, the policies of the government and the acceptance of these by the governed affect the implementation of precautionary measures [8][9][10]44]. The policies and exit strategies towards the end of a phase in any country also determines whether the spread of the disease lingers on, albeit at a much reduced rate, or is completely rooted.…”

“…While the spreading dynamics of the disease is not novel [1], the instabilities it has caused has made different parts of the society, and notably, different governance, respond to containing its spread in very different manners [2][3][4][5][6]. The determination of the optimal strategy, while not dragging what people have known as normality to the ground, has been quite a challenge and highly dependent on the socio-economic condition of the country or region [7][8][9][10]. On the other hand, researchers have been struggling to bring some predictability in the spread of the pandemic since even a few weeks of foresight can not only save an economy from being jettisoned but also save a considerable number of lives that needn't be lost.…”