Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe

Flaxman, Seth; Mishra, Swapnil; Gandy, Axel; Unwin, H. Juliette T.; Mellan, Thomas A.; Coupland, Helen; Whittaker, Charles; Zhu, Harrison; Berah, Tresnia; Eaton, Jeffrey W.; Monod, Mélodie; Perez‐Guzman, Pablo N; Schmit, Nora; Cilloni, Lucia; Ainslie, Kylie E. C.; Baguelin, Marc; Boonyasiri, Adhiratha; Boyd, Olivia; Cattarino, Lorenzo; Cooper, Laura V; Cucunubá, Zulma M.; Cuomo-Dannenburg, Gina; Dighe, Amy; Djaafara, Bimandra A; Dorigatti, Ilaria; Elsland, S Van; FitzJohn, Richard G.; Gaythorpe, Katy A. M.; Geidelberg, Lily; Grassly, Nicholas C.; Green, William D.; Hallett, Timothy B.; Hamlet, Arran; Hinsley, Wes; Jeffrey, B; Knock, Edward; Laydon, Daniel J.; Nedjati-Gilani, Gemma; Nouvellet, Pierre; Parag, Kris V; Siveroni, Igor; Thompson, Hayley; Verity, Robert; Volz, Erik; Walters, Caroline E.; Wang, Haowei; Wang, Yuanrong; Watson, Oliver; Winskill, Peter; Xi, Xiaoyue; Walker, Patrick; Ghani, Azra C; Donnelly, Christl A.; Riley, Steven; Vollmer, Michaela; Ferguson, Neil M.; Okell, Lucy; Bhatt, Samir

doi:10.1038/s41586-020-2405-7

Cited by 3,377 publications

(4,184 citation statements)

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“…It is crucial to assess whether the measures in place are likely to have brought R t below one. An analysis of containment measures introduced in different European countries attempts at dissecting the impact on R t by these measures [8], see Table I. The median effect on R t of measures such as school closure, increased social distancing and public events is rather moderate according to this analysis.…”

Section: Discussionmentioning

confidence: 84%

“…We adapted the model to the Okinawan scenario. To this aim, we used currently available estimates on COVID-19 parameters such as its incubation time and serial time [7][8][9], information about air travelers to Okinawa, data on age distribution of the Okinawan population, and daily number of confirmed and hospitalized cases in the Okinawan prefecture [1]. The model currently does not implement a regional age distribution, so that our simulations are performed using the Japanese age distribution.…”

Section: A Model -No Containmentmentioning

confidence: 99%

“…To understand this discrepancy, we compared with estimates from Europe. A recent study [8] performed a Bayesian analysis to estimate the percentage of infected populations in European countries on the 15th of March, 2020. We compared their results with the numbers of confirmed cases in Table III.…”

Section: A Model -No Containmentmentioning

confidence: 99%

“…• Incubation time, infectivity period, and serial interval. The incubation time of COVID-19 is estimated to be around 5 days [7,8]. During this period, pre-symptomatic transmission may occur, which is not included in the SEIR model.…”

Section: Parametersmentioning

confidence: 99%

“…We report in Table III an estiamte of the ratio between observed and estimated number of cases in different European countries from [8].…”

Section: Parametersmentioning

confidence: 99%

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Modeling the COVID-19 epidemic in Okinawa

Pigolotti

Chiuchiù

Martín

et al. 2020

Preprint

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We analyze current data on the COVID-19 spreading in Okinawa, Japan. We find that the initial spread is characterized by a doubling time of about 5 days. We implement a model to forecast the future spread under different scenarios. The model predicts that, if significant containment measures are not taken, a large fraction of the population will be infected with COVID-19, with the peak of the epidemic expected at the end of May and intensive care units having largely exceeded capacity. We analyzed scenarios implementing strong containment measures, similar to those imposed in Europe. The model predicts that an immediate implementation of strong containment measures (on the 19th of April) will significantly reduce the death count. We assess the negative consequences of these measure being implemented with a delay, or not being sufficiently stringent.

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Section: Discussionmentioning

confidence: 84%

Section: A Model -No Containmentmentioning

confidence: 99%

Section: A Model -No Containmentmentioning

confidence: 99%

Section: Parametersmentioning

confidence: 99%

“…We report in Table III an estiamte of the ratio between observed and estimated number of cases in different European countries from [8].…”

Section: Parametersmentioning

confidence: 99%

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Modeling the COVID-19 epidemic in Okinawa

Pigolotti

Chiuchiù

Martín

et al. 2020

Preprint

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Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19)

Wiersinga

Rhodes

Cheng

et al. 2020

JAMA

4,454

4,322

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IMPORTANCEThe coronavirus disease 2019 (COVID-19) pandemic, due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19.OBSERVATIONS SARS-CoV-2 is spread primarily via respiratory droplets during close face-to-face contact. Infection can be spread by asymptomatic, presymptomatic, and symptomatic carriers. The average time from exposure to symptom onset is 5 days, and 97.5% of people who develop symptoms do so within 11.5 days. The most common symptoms are fever, dry cough, and shortness of breath. Radiographic and laboratory abnormalities, such as lymphopenia and elevated lactate dehydrogenase, are common, but nonspecific. Diagnosis is made by detection of SARS-CoV-2 via reverse transcription polymerase chain reaction testing, although false-negative test results may occur in up to 20% to 67% of patients; however, this is dependent on the quality and timing of testing. Manifestations of COVID-19 include asymptomatic carriers and fulminant disease characterized by sepsis and acute respiratory failure. Approximately 5% of patients with COVID-19, and 20% of those hospitalized, experience severe symptoms necessitating intensive care. More than 75% of patients hospitalized with COVID-19 require supplemental oxygen. Treatment for individuals with COVID-19 includes best practices for supportive management of acute hypoxic respiratory failure. Emerging data indicate that dexamethasone therapy reduces 28-day mortality in patients requiring supplemental oxygen compared with usual care (21.6% vs 24.6%; age-adjusted rate ratio, 0.83 [95% CI, 0.74-0.92]) and that remdesivir improves time to recovery (hospital discharge or no supplemental oxygen requirement) from 15 to 11 days. In a randomized trial of 103 patients with COVID-19, convalescent plasma did not shorten time to recovery. Ongoing trials are testing antiviral therapies, immune modulators, and anticoagulants. The case-fatality rate for COVID-19 varies markedly by age, ranging from 0.3 deaths per 1000 cases among patients aged 5 to 17 years to 304.9 deaths per 1000 cases among patients aged 85 years or older in the US. Among patients hospitalized in the intensive care unit, the case fatality is up to 40%. At least 120 SARS-CoV-2 vaccines are under development. Until an effective vaccine is available, the primary methods to reduce spread are face masks, social distancing, and contact tracing. Monoclonal antibodies and hyperimmune globulin may provide additional preventive strategies.CONCLUSIONS AND RELEVANCE As of July 1, 2020, more than 10 million people worldwide had been infected with SARS-CoV-2. Many aspects of transmission, infection, and treatment remain unclear. Advances in prevention and effective management of COVID-19 will require basic and clinical investigation and public health and clinical interventions.

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Reopening Society and the Need for Real-Time Assessment of COVID-19 at the Community Level

Angulo

Finelli

Swerdlow

2020

JAMA

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Through May 13, 2020, approximately 1.39 million cases of coronavirus disease 2019 (COVID-19) have been reported in the United States (by the Centers for Disease Control and Prevention) and more than 4.3 million cases of COVID-19 have been reported from 188 countries. 1 There is an urgent need for COVID-19 data, including community-level incidence, spectrum of disease, diagnostictestpenetration,andproportionofthecommunitywith protectiveimmunitytosevereacuterespiratorysyndrome coronavirus 2 (SARS-CoV-2) (herd immunity). These data are vital to understanding where communities are on the continuum of COVID-19 cumulative incidence and prevalence and how nonpharmaceutical interventions can be titratedtoreopenbusinessandsociety.Real-timeincidence and seroepidemiologic data are also essential to plan scenarios for the development of COVID-19 vaccines and therapeutics. Cross-sectional community surveys combined with seroepidemiology can help inform the present and help navigate the path forward.

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Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe

Cited by 3,377 publications

References 18 publications

Modeling the COVID-19 epidemic in Okinawa

Modeling the COVID-19 epidemic in Okinawa

Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19)

Reopening Society and the Need for Real-Time Assessment of COVID-19 at the Community Level

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