New Measures for the Coronavirus Disease 2019 Response: A Lesson From the Wenzhou Experience

Ruan, Linhui; Wen, Miaowen; Zeng, Qingrun; Chen, Chengshui; Huang, Shuigen; Yang, Sheng; Yang, Jianjing; Wang, Jingqiang; Hu, Yuhuan; Ding, Saidan; Zhang, Ying; Zhang, Hongxia; Feng, Yuanjing; Jin, Kunlin; Zhuge, Qichuan

doi:10.1093/cid/ciaa386

Cited by 33 publications

(37 citation statements)

References 7 publications

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“…Retrospective analyses of NPI impact on disease spread, to date, have primarily consisted of cross-country analyses or focused on outcomes in China. 2,20,21,[23][24][25] In one comparison of 20 countries, Banholzer et al found public venue closures to be the most effective NPI in reducing new cases, followed by public gathering bans, non-essential business closures, and international travel restrictions, with school closures decreasing case count minimally. Interestingly, they found 'lockdowns' to be among the least effective policies in mitigating disease spread.…”

Section: Context and Contributionmentioning

confidence: 99%

“…2 Analysis at the city level in China has also associated comprehensive social distancing measures with preventing disease spread. 23,24 In Wuhan, a reduction in Rt was shown to chronologically follow implementation of traffic restrictions, home confinement, centralized quarantine, and other social distancing measures. 23 The United States presents unique challenges in epidemiological management due to its governmental emphasis on state and local autonomy.…”

Section: Context and Contributionmentioning

confidence: 99%

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Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States

Dreher

Spiera

McAuley

et al. 2020

Preprint

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Background: Policymakers have employed various non-pharmaceutical interventions (NPIs)such as stay-at-home orders and school closures to limit the spread of Coronavirus disease . However, these measures are not without cost, and careful analysis is critical to quantify their impact on disease spread and guide future initiatives. This study aims to measure the impact of NPIs on the effective reproductive number (Rt) and other COVID-19 outcomes in U.S. states. Methods:In order to standardize the stage of disease spread in each state, this study analyzes the weeks immediately after each state reached 500 cases. The primary outcomes were average Rt in the week following 500 cases and doubling time from 500 to 1000 cases. Linear and logistic regressions were performed in R to assess the impact of various NPIs while controlling for population density, GDP, and certain health metrics. This analysis was repeated for deaths with doubling time from 50 to 100 deaths and included several healthcare infrastructure control variables. Results:States that had a stay-at-home order in place at the time of their 500th case are associated with lower average Rt the following week compared to states without a stay-at-home order (p < 0.001) and are significantly less likely to have an Rt>1 (OR 0.07, 95% CI 0.01 to 0.37, p = 0.004). These states also experienced a significantly longer doubling time from 500 to 1000 cases (HR 0.35, 95% CI 0.17 to 0.72, p = 0.004). States in the highest quartile of average time spent at home were also slower to reach 1000 cases than those in the lowest quartile (HR 0.18, 95% CI 0.06 to 0.53, p = 0.002).Discussion: Few studies have analyzed the effect of statewide stay-at-home orders, school closures, and other social distancing measures in the U.S., which has faced the largest COVID-19 case burden. States with stay-at-home orders have a 93% decrease in the odds of having a positive Rt at a standardized point in disease burden. States that plan to scale back such measures should carefully monitor transmission metrics.

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Section: Context and Contributionmentioning

confidence: 99%

Section: Context and Contributionmentioning

confidence: 99%

Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States

Dreher

Spiera

McAuley

et al. 2020

Preprint

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“…Although these countries have successfully reduced case numbers, no causal relationship between use of app technology and epidemic control has yet been shown. 9 , 10 , 11 , 12 , 13 , 14 Many uncertainties remain on the optimal process of contact tracing with conventional methods or mobile apps, on the timing of testing for current or past infection, and on the required coverage of contact tracing needed.…”

Section: Introductionmentioning

confidence: 99%

Impact of delays on effectiveness of contact tracing strategies for COVID-19: a modelling study

Kretzschmar¹,

Rozhnova²,

Bootsma³

et al. 2020

The Lancet Public Health

680

741

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Summary Background In countries with declining numbers of confirmed cases of COVID-19, lockdown measures are gradually being lifted. However, even if most physical distancing measures are continued, other public health measures will be needed to control the epidemic. Contact tracing via conventional methods or mobile app technology is central to control strategies during de-escalation of physical distancing. We aimed to identify key factors for a contact tracing strategy to be successful. Methods We evaluated the impact of timeliness and completeness in various steps of a contact tracing strategy using a stochastic mathematical model with explicit time delays between time of infection and symptom onset, and between symptom onset, diagnosis by testing, and isolation (testing delay). The model also includes tracing of close contacts (eg, household members) and casual contacts, followed by testing regardless of symptoms and isolation if testing positive, with different tracing delays and coverages. We computed effective reproduction numbers of a contact tracing strategy ( R CTS ) for a population with physical distancing measures and various scenarios for isolation of index cases and tracing and quarantine of their contacts. Findings For the most optimistic scenario (testing and tracing delays of 0 days and tracing coverage of 100%), and assuming that around 40% of transmissions occur before symptom onset, the model predicts that the estimated effective reproduction number of 1·2 (with physical distancing only) will be reduced to 0·8 (95% CI 0·7–0·9) by adding contact tracing. The model also shows that a similar reduction can be achieved when testing and tracing coverage is reduced to 80% ( R CTS 0·8, 95% CI 0·7–1·0). A testing delay of more than 1 day requires the tracing delay to be at most 1 day or tracing coverage to be at least 80% to keep R CTS below 1. With a testing delay of 3 days or longer, even the most efficient strategy cannot reach R CTS values below 1. The effect of minimising tracing delay (eg, with app-based technology) declines with decreasing coverage of app use, but app-based tracing alone remains more effective than conventional tracing alone even with 20% coverage, reducing the reproduction number by 17·6% compared with 2·5%. The proportion of onward transmissions per index case that can be prevented depends on testing and tracing delays, and given a 0-day tracing delay, ranges from up to 79·9% with a 0-day testing delay to 41·8% with a 3-day testing delay and 4·9% with a 7-day testing delay. Interpretation In our model, minimising testing delay had the largest impact on reducing onward transmissions. Optimising testing and tracing coverage and minimising tracing delays, for instance with app-based technology, furth...

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“…(1) Duration of the SARS-CoV-2 viral loading: The virus load was fluctuated largely around the average level throughout the entire epidemic period [ 30 , 31 ] without a clear peak ( Figure 4A ). This indicated that the virus load was probably not a contributing factor to the dynamic of epidemic.…”

Section: Resultsmentioning

confidence: 99%

“…The patients were consecutively enrolled from 23 January to 3 March 2020 [ 30 , 31 ] in six medical centers and CDCs in Zhejiang province, China, including site 1 (Affiliated Taizhou Hospital of WMU), Site 2 (Wenzhou municipal CDC, WZ CDC), Site 3 (Zhejiang provincial CDC, ZJ CDC), Site 4 (1st affiliated hospital of WMU), Site 5 (2nd affiliated hospital of WMU) and Site 6 (Affiliated eye hospital of WMU). A total of 252 confirmed COVID-19, 54 COVID-19 convalescent and 300 COVID-19 negative, cases were included in the study cohort (see Table 2 ).…”

Section: Methodsmentioning

confidence: 99%

Identification of the RNase-binding site of SARS-CoV-2 RNA for anchor primer-PCR detection of viral loading in 306 COVID-19 patients

Wang²,

Hu³

et al. 2020

Briefings in Bioinformatics

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The pandemic of coronavirus disease 2019 (COVID-19) urgently calls for more sensitive molecular diagnosis to improve sensitivity of current viral nuclear acid detection. We have developed an anchor primer (AP)-based assay to improve viral RNA stability by bioinformatics identification of RNase-binding site of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA and implementing AP dually targeting the N gene of SARS-CoV-2 RNA and RNase 1, 3, 6. The arbitrarily primed polymerase chain reaction (AP-PCR) improvement of viral RNA integrity was supported by (a) the AP increased resistance of the targeted gene (N gene) of SARS-CoV-2 RNA to RNase treatment; (b) the detection of SARS-CoV-2 RNA by AP-PCR with lower cycle threshold values (−2.7 cycles) compared to two commercially available assays; (c) improvement of the viral RNA stability of the ORF gene upon targeting of the N gene and RNase. Furthermore, the improved sensitivity by AP-PCR was demonstrated by detection of SARS-CoV-2 RNA in 70–80% of sputum, nasal, pharyngeal swabs and feces and 36% (4/11) of urine of the confirmed cases (n = 252), 7% convalescent cases (n = 54) and none of 300 negative cases. Lastly, AP-PCR analysis of 306 confirmed and convalescent cases revealed prolonged presence of viral loading for >20 days after the first positive diagnosis. Thus, the AP dually targeting SARS-CoV-2 RNA and RNase improves molecular detection by preserving SARS-CoV-2 RNA integrity and reveals the prolonged viral loading associated with older age and male gender in COVID-19 patients.

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New Measures for the Coronavirus Disease 2019 Response: A Lesson From the Wenzhou Experience

Cited by 33 publications

References 7 publications

Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States

Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States

Impact of delays on effectiveness of contact tracing strategies for COVID-19: a modelling study

Identification of the RNase-binding site of SARS-CoV-2 RNA for anchor primer-PCR detection of viral loading in 306 COVID-19 patients

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