Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty.
Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty.
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DOI：
10.1038/s41467-023-42680-x
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发表时间：
2023-11-20
影响因子：
16.6
通讯作者：
Lessler J
中科院分区：
文献类型：
--
作者：
Howerton E;Contamin L;Mullany LC;Qin M;Reich NG;Bents S;Borchering RK;Jung SM;Loo SL;Smith CP;Levander J;Kerr J;Espino J;van Panhuis WG;Hochheiser H;Galanti M;Yamana T;Pei S;Shaman J;Rainwater-Lovett K;Kinsey M;Tallaksen K;Wilson S;Shin L;Lemaitre JC;Kaminsky J;Hulse JD;Lee EC;McKee CD;Hill A;Karlen D;Chinazzi M;Davis JT;Mu K;Xiong X;Pastore Y Piontti A;Vespignani A;Rosenstrom ET;Ivy JS;Mayorga ME;Swann JL;España G;Cavany S;Moore S;Perkins A;Hladish T;Pillai A;Ben Toh K;Longini I Jr;Chen S;Paul R;Janies D;Thill JC;Bouchnita A;Bi K;Lachmann M;Fox SJ;Meyers LA;Srivastava A;Porebski P;Venkatramanan S;Adiga A;Lewis B;Klahn B;Outten J;Hurt B;Chen J;Mortveit H;Wilson A;Marathe M;Hoops S;Bhattacharya P;Machi D;Cadwell BL;Healy JM;Slayton RB;Johansson MA;Biggerstaff M;Truelove S;Runge MC;Shea K;Viboud C;Lessler J
我们预测遥远未来的流行病的能力受到疾病系统的许多复杂性的限制。然而，在明确规定关键流行驱动因素未来状态的明确情景下，现实的长期预测可能是可能的。自2020年12月以来，美国新冠肺炎情景建模中心已经召集了多个建模团队，对SARS-CoV-2疫情进行提前数月的预测，总计近180万个国家和州层面的预测。在这里，我们发现SMH的性能作为情景有效性和模型校准的函数变化很大。我们显示，在出乎意料的SARS-CoV-2变种到来之前，情景平均保持了22周的接近现实，使关键假设无效。在有效情景假设期间，保留模型之间差异的参与模型集合(使用线性意见池方法)始终比任何单个模型更可靠，而预测区间覆盖率接近目标水平。卫生和卫生局的预测被用来指导大流行的应对，说明了协作中心对长期情景预测的价值。美国新冠肺炎情景建模中心根据不同的疫情情景做出了中长期预测。在这项研究中，作者通过将14轮预测与发生的疫情轨迹进行比较来评估它们，并讨论了为未来类似项目吸取的经验教训。
Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections. The US COVID-19 Scenario Modeling Hub produced medium to long term projections based on different epidemic scenarios. In this study, the authors evaluate 14 rounds of projections by comparing them to the epidemic trajectories that occurred, and discuss lessons learned for future similar projects.
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影响因子：
56.3
作者：
Bobrovitz, Niklas;Ware, Harriet;Ma, Xiaomeng;Li, Zihan;Hosseini, Reza;Cao, Christian;Selemon, Anabel;Whelan, Mairead;Premji, Zahra;Issa, Hanane;Cheng, Brianna;Abu Raddad, Laith J.;Buckeridge, David L.;Van Kerkhove, Maria D.;Piechotta, Vanessa;Higdon, Melissa M.;Wilder-Smith, Annelies;Bergeri, Isabel;Feikin, Daniel R.;Arora, Rahul K.;Patel, Minal K.;Subissi, Lorenzo
通讯作者：
Subissi, Lorenzo
DOI：
10.1098/rsif.2022.0659
发表时间：
2023-01
期刊：
Journal of the Royal Society, Interface
影响因子：
--
作者：
通讯作者：
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DOI：
10.1073/pnas.2113561119
发表时间：
2022-04-12
影响因子：
11.1
作者：
通讯作者：
--
DOI：
10.1371/journal.pgph.0001063
发表时间：
2023
期刊：
PLOS global public health
影响因子：
--
作者：
通讯作者：
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DOI：
10.15585/mmwr.mm7019e3
发表时间：
2021-05-14
期刊：
MMWR. Morbidity and mortality weekly report
影响因子：
--
作者：
Borchering RK;Viboud C;Howerton E;Smith CP;Truelove S;Runge MC;Reich NG;Contamin L;Levander J;Salerno J;van Panhuis W;Kinsey M;Tallaksen K;Obrecht RF;Asher L;Costello C;Kelbaugh M;Wilson S;Shin L;Gallagher ME;Mullany LC;Rainwater-Lovett K;Lemaitre JC;Dent J;Grantz KH;Kaminsky J;Lauer SA;Lee EC;Meredith HR;Perez-Saez J;Keegan LT;Karlen D;Chinazzi M;Davis JT;Mu K;Xiong X;Pastore Y Piontti A;Vespignani A;Srivastava A;Porebski P;Venkatramanan S;Adiga A;Lewis B;Klahn B;Outten J;Schlitt J;Corbett P;Telionis PA;Wang L;Peddireddy AS;Hurt B;Chen J;Vullikanti A;Marathe M;Healy JM;Slayton RB;Biggerstaff M;Johansson MA;Shea K;Lessler J
通讯作者：
Lessler J