Non-pharmaceutical interventions during the COVID-19 pandemic: A 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 review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 348 articles written by more than 2518 of authors in the first 12 months of the emergency. 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.

Evaluation of home detection algorithms on mobile phone data using individual-level ground truth

“…The many applications of “big data” analytics to any kind of official statistics depend critically on our ability to identify, with more or less error, where someone lives , i.e., detecting an individual’s home location. This impacts all aspects of the work on statistics with non-traditional data sources such as the estimation of population density [ 10 , 18 , 38 ], commuting and migration flows [ 5 , 15 , 17 , 19 , 28 ], air pollution [ 21 , 37 ], and the estimation of privacy risk [ 8 , 9 , 12 , 32 , 33 ], and is of special importance now to inform epidemic models of COVID-19 transmission [ 34 ]. The knowledge of the home location of individuals forms the crucial link between digital data and census data, making it a key enabler for the integration of these two sources of information.…”

Socio-demographic and health factors drive the epidemic progression and should guide vaccination strategies for best COVID-19 containment

“…Solving this problem of unbiasing data is still an open issue and is particularly important for the development of epidemiological models as well. Second, the spreading of infectious diseases and human behavior are intertwined and is, particularly in the case with the SARS-CoV-2 virus, gradually affected by non-pharmaceutical interventions, which are calling for a coordinated international strategy [70] , [71] , as well as by endogenous reductions of social interactions [14] , [72] , [73] . Our study included this aspect in a very simplified form, i.e., by affecting contact rates by the number of symptomatic infected individuals and hospitalized individuals.…”

In-vivo Protection from SARS-CoV-2 infection by ATN-161 in k18-hACE2 transgenic mice

“…Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the agent causative of coronavirus disease 2019 (COVID- 19), is a highly transmissible respiratory pathogen in which an estimated 14% of all patients will develop serious conditions, with a subsequent mortality rate of 1.4 -3.4% [1][2][3]. Several non-pharmacological interventions have been implemented to slow down the spread of SARS-CoV-2 [4][5][6][7]. However, to date there is no universally agreed direct therapy available to treat COVID-19.…”