Non Pharmaceutical Interventions for Optimal Control of COVID-19

Zamir, Muhammad; Shah, Zahir; Nadeem, Fawad; Memood, Arif; Alrabaiah, Hussam; Kumam, Poom

doi:10.1016/j.cmpb.2020.105642

Cited by 58 publications

(47 citation statements)

References 17 publications

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“…The COVID-19 studies based their models on limited data and made different assumptions about the virus 17 ; the stay-at-home variable was analyzed as a binary indicator 40 ; and the number of new cases could have been substantially undocumented 41 ; all which may have biased the results. A sophisticated mathematical model based on a high-dimensional system of partial differential equations to represent disease spread has been proposed 42 . According to this model, staying at home did not play a dominant role in disease transmission, but the combination of these, together with the use of face masks, hand washing, early-case detection (PCR test), and the use of hand sanitizers for at least 50 days could have reduced the number of new cases.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Stay-at-home policy is a case of exception fallacy: an internet-based ecological study

Savaris

Pumi

Dalzochio

et al. 2021

Sci Rep

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A recent mathematical model has suggested that staying at home did not play a dominant role in reducing COVID-19 transmission. The second wave of cases in Europe, in regions that were considered as COVID-19 controlled, may raise some concerns. Our objective was to assess the association between staying at home (%) and the reduction/increase in the number of deaths due to COVID-19 in several regions in the world. In this ecological study, data from www.google.com/covid19/mobility/, ourworldindata.org and covid.saude.gov.br were combined. Countries with > 100 deaths and with a Healthcare Access and Quality Index of ≥ 67 were included. Data were preprocessed and analyzed using the difference between number of deaths/million between 2 regions and the difference between the percentage of staying at home. The analysis was performed using linear regression with special attention to residual analysis. After preprocessing the data, 87 regions around the world were included, yielding 3741 pairwise comparisons for linear regression analysis. Only 63 (1.6%) comparisons were significant. With our results, we were not able to explain if COVID-19 mortality is reduced by staying at home in ~ 98% of the comparisons after epidemiological weeks 9 to 34.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Stay-at-home policy is a case of exception fallacy: an internet-based ecological study

Savaris

Pumi

Dalzochio

et al. 2021

Sci Rep

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“…The body of modeling work based on the SEIR scheme touches similar themes to those just mentioned, but due to the larger number of articles, there are also some new interesting angles. In particular, we find papers focusing, among other things, on the effects of face masks [82] , [85] , [86] , [87] , [89] , capturing different aspects of NPIs [64] , [67] , [69] , [70] , [71] , [73] , [74] , [75] , [77] , [79] , [80] , [81] , [83] , [84] , [90] , studying the problem of optimal control of the pandemic [72] , [76] , [78] , [88] , investigating approaches to lift measures put in place in the first wave [62] , [63] , [65] , model the possible exposure to the virus via droplets or fomites [91] , [92] , and consider the impact on the health care infrastructure of COVID-19 and seasonal flu in the winter [68] .…”

Section: Epidemic Modelsmentioning

confidence: 99%

“…Two theoretical approaches consider explicitly the presence of the virus in the compartmental structure [91] , [92] . In particular, authors of Ref.…”

Section: Epidemic Modelsmentioning

confidence: 99%

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

2021

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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.

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“…Particularly, a variety of approaches have been proposed to the problem of designing NPI policies subject to constraints by applying tools from control theory. An optimal control problem for NPI design is formulated in [7] with the aim of reducing infected population and contaminated objects. In [8], optimal intervention for reducing the peak of infections is proposed.…”

Section: Introductionmentioning

confidence: 99%

Potentials of constrained sliding mode control as an intervention guide to manage COVID19 spread

Nuñez

Inthamoussou

Valenciaga

et al. 2020

Preprint

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This work evaluates the potential of using sliding mode reference conditioning (SMRC) techniques as a guide for non-pharmaceutical interventions and population confinement to control the COVID-19 pandemic. SMRC technique allows robustly delimiting a given variable in dynamical systems. In particular, for the epidemiological problem addressed here, it can be used to compute day by day the contact rate reduction requirement in order to limit the intense care units occupancy to a given threshold. What is more, it could impose a given approaching rate to the health care system limits. Simulations are performed using the well-known SEIR model fitted to the Argentinian case to demonstrate what this control strategy suggests, while the effect of realistic period transitions between different confinement levels are also considered.

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Non Pharmaceutical Interventions for Optimal Control of COVID-19

Abstract: that if there is no control (variables/interventios), 900 out 1000 susceptible individuals may be infected (exposed) in very short period. As such a circumstances no agency fighting against COVID-19 could be successful due to its limited resources.

Cited by 58 publications

References 17 publications

RETRACTED ARTICLE: Stay-at-home policy is a case of exception fallacy: an internet-based ecological study

RETRACTED ARTICLE: Stay-at-home policy is a case of exception fallacy: an internet-based ecological study

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

Potentials of constrained sliding mode control as an intervention guide to manage COVID19 spread

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