التفاصيل البيبلوغرافية
| العنوان: |
How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19? |
| المؤلفون: |
Sharma, M, Mindermann, S, Brauner, J, Leech, G, Stephenson, A, Gavenciak, T, Kulveit, J, Teh, YW, Chindelevitch, L, Gal, Y |
| المصدر: |
Neural Information Processing Systems (NeurIPS 2020) |
| بيانات النشر: |
NeurIPS |
| سنة النشر: |
2020 |
| المجموعة: |
Imperial College London: Spiral |
| مصطلحات موضوعية: |
1701 Psychology, 1702 Cognitive Sciences |
| جغرافية الموضوع: |
Virtual |
| الوصف: |
To what extent are effectiveness estimates of nonpharmaceutical interventions (NPIs) against COVID-19 influenced by the assumptions our models make? To answer this question, we investigate 2 state-of-the-art NPI effectiveness models and propose 6 variants that make different structural assumptions. In particular, we investigate how well NPI effectiveness estimates generalise to unseen countries, and their sensitivity to unobserved factors. Models which account for noise in disease transmission compare favourably. We further evaluate how robust estimates are to different choices of epidemiological parameters and data. Focusing on models that assume transmission noise, we find that previously published results are robust across these choices and across different models. Finally, we mathematically ground the interpretation of NPI effectiveness estimates when certain common assumptions do not hold. |
| نوع الوثيقة: |
conference object |
| اللغة: |
unknown |
| تدمد: |
1049-5258 |
| العلاقة: |
Advances in neural information processing systems; http://hdl.handle.net/10044/1/86939Test |
| الإتاحة: |
http://hdl.handle.net/10044/1/86939Test |
| حقوق: |
© 2020 The Author(s). |
| رقم الانضمام: |
edsbas.51AB8283 |
| قاعدة البيانات: |
BASE |
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