Modeling vaccination rollouts, SARS-CoV-2 variants and the requirement for non-pharmaceutical interventions in Italy.
Modeling vaccination rollouts, SARS-CoV-2 variants and the requirement for non-pharmaceutical interventions in Italy.
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DOI：
10.1038/s41591-021-01334-5
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发表时间：
2021-06
期刊：
影响因子：
82.9
通讯作者：
Bruno R
中科院分区：
文献类型：
--
作者：
Giordano G;Colaneri M;Di Filippo A;Blanchini F;Bolzern P;De Nicolao G;Sacchi P;Colaneri P;Bruno R
尽管在临床护理2019年冠状病毒病患者(新冠肺炎)方面取得了进展，但全人群干预措施对于控制这一大流行仍然至关重要，新的高度可传播性变种的出现加剧了这一大流行。在这项研究中，我们将预测SARS-CoV-2感染传播的SIDARTHE模型与一个新的基于数据的模型相结合，该模型将新病例预测到伤亡和医疗保健系统成本上。基于意大利的案例研究，我们概述了几种情景：不同步伐的大规模疫苗接种活动，由于新的变种而导致的不同传播率，以及不同的强制对策，包括开放和关闭阶段的交替。我们的结果表明，非药物干预(NPI)对疫情演变的影响比单独接种疫苗更大，这表明有必要在疫苗接种活动的第一阶段保持NPI到位。我们的模型预测，从2021年4月到2022年1月，在没有推出疫苗和弱NPI(=1.27)的情况下，可能会发生多达298,000例与新冠肺炎相关的死亡。然而，快速推出疫苗接种可能会将死亡率降低到5.1万人死亡。实施限制性NPI(=0.9)可以在不接种疫苗的情况下将新冠肺炎死亡人数减少到30,000人，如果快速推出疫苗，则可以减少到18,000人。我们还表明，如果采用间歇性的开放-关闭策略，首先实施关闭阶段可以减少死亡(在疫苗推出缓慢的情况下从47,000人减少到27,000人)和医疗系统成本，而不会实质性地加剧社会经济损失。在SIDARTHE-V模型中综合考虑疫苗接种推出的不同速度和新SARS-CoV-2毒株的传播动力学的变量表明，在意大利开展新冠肺炎疫苗接种活动期间保持非药物干预对于将意大利到2022年的死亡率降至最低至关重要。
Despite progress in clinical care for patients with coronavirus disease 2019 (COVID-19), population-wide interventions are still crucial to manage the pandemic, which has been aggravated by the emergence of new, highly transmissible variants. In this study, we combined the SIDARTHE model, which predicts the spread of SARS-CoV-2 infections, with a new data-based model that projects new cases onto casualties and healthcare system costs. Based on the Italian case study, we outline several scenarios: mass vaccination campaigns with different paces, different transmission rates due to new variants and different enforced countermeasures, including the alternation of opening and closure phases. Our results demonstrate that non-pharmaceutical interventions (NPIs) have a higher effect on the epidemic evolution than vaccination alone, advocating for the need to keep NPIs in place during the first phase of the vaccination campaign. Our model predicts that, from April 2021 to January 2022, in a scenario with no vaccine rollout and weak NPIs ( = 1.27), as many as 298,000 deaths associated with COVID-19 could occur. However, fast vaccination rollouts could reduce mortality to as few as 51,000 deaths. Implementation of restrictive NPIs ( = 0.9) could reduce COVID-19 deaths to 30,000 without vaccinating the population and to 18,000 with a fast rollout of vaccines. We also show that, if intermittent open–close strategies are adopted, implementing a closing phase first could reduce deaths (from 47,000 to 27,000 with slow vaccine rollout) and healthcare system costs, without substantive aggravation of socioeconomic losses. Integration of variables to account for different speeds of vaccination rollouts and transmission dynamics of new SARS-CoV-2 strains into the SIDARTHE-V model suggests that maintaining non-pharmaceutical interventions during the COVID-19 vaccination campaign in Italy is essential for minimizing mortality in Italy into 2022.
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DOI：
10.1126/science.abg3055
发表时间：
2021-04-09
期刊：
Science (New York, N.Y.)
影响因子：
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作者：
Davies NG;Abbott S;Barnard RC;Jarvis CI;Kucharski AJ;Munday JD;Pearson CAB;Russell TW;Tully DC;Washburne AD;Wenseleers T;Gimma A;Waites W;Wong KLM;van Zandvoort K;Silverman JD;CMMID COVID-19 Working Group;COVID-19 Genomics UK (COG-UK) Consortium;Diaz-Ordaz K;Keogh R;Eggo RM;Funk S;Jit M;Atkins KE;Edmunds WJ
通讯作者：
Edmunds WJ
通过快速周期性切换减少Covid-19。
影响因子：
4.3
作者：
Bin M;Cheung PYK;Crisostomi E;Ferraro P;Lhachemi H;Murray-Smith R;Myant C;Parisini T;Shorten R;Stein S;Stone L
通讯作者：
Stone L
影响因子：
56.9
作者：
Kissler, Stephen M.;Tedijanto, Christine;Lipsitch, Marc
通讯作者：
Lipsitch, Marc
DOI：
10.1056/nejmoa2035389
发表时间：
2021-02-04
期刊：
The New England journal of medicine
影响因子：
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作者：
Baden LR;El Sahly HM;Essink B;Kotloff K;Frey S;Novak R;Diemert D;Spector SA;Rouphael N;Creech CB;McGettigan J;Khetan S;Segall N;Solis J;Brosz A;Fierro C;Schwartz H;Neuzil K;Corey L;Gilbert P;Janes H;Follmann D;Marovich M;Mascola J;Polakowski L;Ledgerwood J;Graham BS;Bennett H;Pajon R;Knightly C;Leav B;Deng W;Zhou H;Han S;Ivarsson M;Miller J;Zaks T;COVE Study Group
通讯作者：
COVE Study Group
影响因子：
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作者：
D'Arienzo, Marco;Coniglio, Angela
通讯作者：
Coniglio, Angela