Behavioral manipulation—key to the successful global spread of the new coronavirus SARS‐CoV‐2?

Bouayed, Jaouad; Bohn, Torsten

doi:10.1002/jmv.26446

Cited by 11 publications

(10 citation statements)

References 13 publications

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“…The second, the topics and references. Category Topic and references Change to medical practice Mental health care [254] , [257] , [261] , [273] , [274] , [275] ; Emergency care [276] , [277] ; Substance abuse [253] , [263] , [278] , [279] , [280] ; Oncological care [264] , [281] Health care practices [255] , [259] , [262] , [282] , [283] , [284] ; Pediatric care [283] , [285] Other care [256] , [260] , [268] , [286] , [287] , [288] Modeling Modeling approaches [28] , [265] , [289] , [290] , [291] , [292] , [293] ; Transmission dynamics [294] , [295] , [296] , [297] , [298] Mobile phone data [29] ;

estimation [258] Effect of NPIs Effects on: children ...…”

Section: Comments And/or Perspectivesmentioning

confidence: 99%

“…Several comments and/or perspectives focus on different aspects of modeling COVID-19 dynamics and NPIs. In particular, we find articles discussing epidemic modeling efforts [28] , [265] , [289] , [290] , [291] , [292] , [293] , analyzing knowns and unknowns of transmission dynamics [294] , [295] , [296] , [297] , [298] , presenting opportunities to model and control the spreading of COVID-19 enabled by novel data streams such as mobile phone data [29] , and discussing the challenges in

estimation [258] .…”

Section: Comments And/or Perspectivesmentioning

confidence: 99%

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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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estimation [258] Effect of NPIs Effects on: children ...…”

Section: Comments And/or Perspectivesmentioning

confidence: 99%

estimation [258] .…”

Section: Comments And/or Perspectivesmentioning

confidence: 99%

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

2021

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“…In a matter of few days, the daily reported zero COVID-19 cases shoot up to two-digit figures and the number of active cases increased. Indeed, COVID-19 is currently being exacerbated worldwide by irresponsible behaviour at all ages, and adolescents with their propensity to party are major culprits [20][21][22].…”

Section: An Avoidable Debaclementioning

confidence: 99%

Mass Events Trigger Malta's Second Peak After Initial Successful Pandemic Suppression

Cuschieri

Balzan

Gauci³

et al. 2020

J Community Health

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The second COVID-19 wave is sweeping the globe as restrictions are lifted. Malta, the 'poster child of Europe's COVID-19 first wave success' also fell victim shortly after it welcomed the first tourists on 1st of July 2020. Only four positive cases were reported over the successive 15 days. Stability was disrupted when two major mass events were organized despite various health professional warnings. In a matter of few just days, daily cases rose to two-digit figures, with high community transmission, a drastic rise in active cases, and a rate per hundred thousand in Europe second only to Spain. Frontliners were swamped with swabbing requests while trying to sustain robust case management, contact tracing and follow-up. Indeed, the number of hospitalizations and the need for intensive ventilation increased. Despite the initial cases were among young adults, within weeks a small spill off on the more elderly population was observed. Restrictions were reintroduced including mandatory mask wearing in specific locations and capping of the total number of people in a single gathering. Malta is an island and the potential for containment would have been relatively simple and effective and permitting mass gatherings was unwise. Protecting the health of the population should take centre stage while carrying out extensive testing, contact tracing and surveillance. Containment and mitigation along with public cooperation is the key to curbing resurgences especially with the influenza season around the corner.

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“…Mental health care [253,256,260,[272][273][274]; Emergency care [275,276]; Substance abuse [252,262,[277][278][279]; Oncological care [263,280] Health care practices [254,258,261,[281][282][283]; Pediatric care [282,284] Other care [255,259,267,[285][286][287] Modeling modeling approaches [28,264,[288][289][290][291][292]; Transmission dynamics [293][294][295][296][297] Mobile phone data [29]; R t estimation [257] Effect of NPIs Effects on: children [30,298]; education [268,299]; gambling [300] other diseases…”

Section: Change To Medical Practicementioning

confidence: 99%

“…Several comments and/or perspectives focus on different aspects of modeling COVID-19 dynamics and NPIs. In particular, we find articles discussing epidemic modeling efforts [28,264,[288][289][290][291][292], analyzing known and unknowns of transmission dynamics [293][294][295][296][297], presenting opportunities to model and control the spreading of COVID-19 enabled by novel data streams such as mobile phone data [29], and discussing the challenges in R t estimation [257].…”

Section: Modelingmentioning

confidence: 99%

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

Perra

2020

Preprint

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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 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 *

show abstract

Behavioral manipulation—key to the successful global spread of the new coronavirus SARS‐CoV‐2?

Cited by 11 publications

References 13 publications

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

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

Mass Events Trigger Malta's Second Peak After Initial Successful Pandemic Suppression

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

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