Spread of Covid-19 in the United States is controlled

Hu, Zixin; Ge, Qiyang; Li, Shudi; Xu, Tao; Boerwinkle, Eric; Jin, Li; Xiong, Momiao

doi:10.1101/2020.05.04.20091272

Cited by 4 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Official governmental regulations are possible resources for extracting features regarding the lockdown. Such features were examined for their association with infection rates in previous studies (Flaxman et al , 2020; Gatto et al , 2020; preprint: Hu et al , 2020; Li et al , 2020). However, the time governmental regulations were declared was often significantly different from the date social distancing initiated de facto (preprint: Kohanovski et al , 2020).…”

Section: Discussionmentioning

confidence: 99%

“…One could measure governmental regulations such as the permitted walking distance from the residence, limitations on mass gatherings, school closures, and whether people were allowed to attend their workplaces. For example, Hu et al (preprint: 2020) suggested a score that takes into account various governmental interventions in the United States. This score was used to predict future infections depending on the intervention level.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

COVID ‐19 pandemic‐related lockdown: response time is more important than its strictness

et al. 2020

View full text Add to dashboard Cite

The rapid spread of SARS‐CoV‐2 and its threat to health systems worldwide have led governments to take acute actions to enforce social distancing. Previous studies used complex epidemiological models to quantify the effect of lockdown policies on infection rates. However, these rely on prior assumptions or on official regulations. Here, we use country‐specific reports of daily mobility from people cellular usage to model social distancing. Our data‐driven model enabled the extraction of lockdown characteristics which were crossed with observed mortality rates to show that: (i) the time at which social distancing was initiated is highly correlated with the number of deaths, r2 = 0.64, while the lockdown strictness or its duration is not as informative; (ii) a delay of 7.49 days in initiating social distancing would double the number of deaths; and (iii) the immediate response has a prolonged effect on COVID‐19 death toll.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

COVID ‐19 pandemic‐related lockdown: response time is more important than its strictness

et al. 2020

View full text Add to dashboard Cite

show abstract

“…suggested a score that takes into account various governmental interventions in the United States 3 . This score was used to predict future infections depending on the intervention level.…”

Section: Introductionmentioning

confidence: 99%

“…One could measure governmental regulations such as the permitted walking distance from the residence, limitations on mass gatherings, school closures, and whether people were allowed to attend their workplaces. For example, Hu et al suggested a score that takes into account various governmental interventions in the United States 3 . This score was used to predict future infections depending on the intervention level.…”

Section: Introductionmentioning

confidence: 99%

COVID-19 pandemic-related lockdown: response time is more important than its strictness

Loewenthal

Abadi

Avram

et al. 2020

Preprint

View full text Add to dashboard Cite

The rapid spread of SARS-CoV-2 and its threat to health systems worldwide have led governments to take acute actions to enforce social distancing. Previous studies used complex epidemiological models to quantify the effect of lockdown policies on infection rates. However, these rely on prior assumptions or on official regulations. Here, we use country-specific reports of daily mobility from people cellular usage to model social distancing. Our data-driven model enabled the extraction of mobility characteristics which were crossed with observed mortality rates to show that: (1) the time at which social distancing was initiated is of utmost importance and explains 62% of the number of deaths, while the lockdown strictness or its duration are not as informative; (2) a delay of 7.49 days in initiating social distancing would double the number of deaths; and (3) the expected time from infection to fatality is 25.75 days and significantly varies among countries.

show abstract

“…Recently, AI has been applied to predict outbreak like coronavirus. For example, an prediction model using AI to estimate the size, lengths and ending time of COVID-19 across China [130] . An auto-encoder is designed for modelling the transmission dynamics of the epidemic based on dataset collected from WHO sources.…”

Section: Ai-based Solutions For Coronavirus Fightingmentioning

confidence: 99%

Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey

et al. 2021

View full text Add to dashboard Cite

The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. Blockchain can combat pandemics by enabling early detection of outbreaks, ensuring the ordering of medical data, and ensuring reliable medical supply chain during the outbreak tracing. Moreover, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating COVID-19 epidemics. First, we introduce a new conceptual architecture which integrates blockchain and AI for fighting COVID-19 . Then, we survey the latest research efforts on the use of blockchain and AI for fighting COVID-19 in various applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. A case study is also provided using federated AI for COVID-19 detection. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronaviruslike epidemics.

show abstract

Spread of Covid-19 in the United States is controlled

Cited by 4 publications

References 10 publications

COVID ‐19 pandemic‐related lockdown: response time is more important than its strictness

COVID ‐19 pandemic‐related lockdown: response time is more important than its strictness

COVID-19 pandemic-related lockdown: response time is more important than its strictness

Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey

Contact Info

Product

Resources

About