GCRI · 生物技术与生物安全
面向生物技术与生物安全的概率与统计
How probability and statistics is applied in Biotechnology and Biosecurity. Probability and statistics provide the mathematical framework for describing uncertainty and learning from data. They underpin estimation, testing and prediction in every risk discipline.
What probability and statistics does here.
Probability and statistics provide the mathematical framework for describing uncertainty and learning from data. They underpin estimation, testing and prediction in every risk discipline. In health and biosecurity and food and agriculture, statistical methods quantify the likelihood and uncertainty of losses across interconnected 系统. They make the evidence behind risk decisions explicit and reproducible. The canonical description is on STEM Commons.
- 01
Methods used here
statistical inference; Bayesian analysis; regression modelling; sampling design; hypothesis testing; resampling methods.
- 02
验证
Results are checked through diagnostics, cross-validation and sensitivity to assumptions. Independent replication confirms findings.
Tail fit.
团队遵循该方法时会使用的界面：其指标、状态与决策。名称为示例，数值仅作示意。
Tail fit
Biotechnology and biosecurity · Probability and statistics · Run R-0830
Return level curve
方法卡
- 方法
- 概率与统计
- 方法
- peaks over threshold
- Threshold
- 93th percentile
- 标签
- 模型生成
参数
generalised Pareto fit
| Shape ξ | 0.20 | 0.00 | 0.41 | heavy tail if above zero |
| Scale σ | 2.0 | 1.0 | 7.5 | units of the variable |
| Exceedances | 98 | declustered |
该方法使用的输入。
Datasets and records used by probability and statistics on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Designed surveys and experiments | 输入 | 观测 |
| Observational datasets | 输入 | 观测 |
| Administrative records | 输入 | 观测 |
| Sensor time series | 输入 | 观测 |
| Simulation outputs | 输入 | 观测 |
地点网络上的 SEIR 模型。
An outbreak seeded in one place spreads through a small-world network by the share of contacts people make elsewhere; play it to see the order of arrival and how the timing of measures moves the peak. Teaching model with stated illustrative values, not a prediction.
控制措施
- 基本再生数 R0
- 2.5
- 潜伏期
- 3.0 days
- 传染期
- 5.0 days
- 在其他地点发生的接触所占比例
- 8%
- 网络中的地点
- 24
- 措施开始于第几天
- 40
- 措施带来的接触减少
- 40%
- 模拟天数
- 240 days
读数
- 新增感染峰值
- 5.28 per 1,000 a day
- 峰值日
- 148
- 累计感染比例
- 58%
- 已覆盖地点
- 100%
- 采取措施后的再生数
- 1.50
数字、方法与来源
| 日 | 每 1,000 人新增感染 | 累计感染（%） |
|---|---|---|
| 0 | 0.00 | 0.0 |
| 17 | 0.03 | 0.0 |
| 34 | 0.32 | 0.2 |
| 51 | 0.96 | 1.4 |
| 68 | 1.74 | 3.7 |
| 85 | 2.72 | 7.5 |
| 102 | 3.74 | 13.1 |
| 119 | 4.56 | 20.2 |
| 136 | 5.11 | 28.5 |
| 153 | 5.24 | 37.4 |
| 170 | 4.44 | 45.7 |
| 187 | 2.91 | 52.0 |
| 204 | 1.52 | 55.6 |
| 221 | 0.69 | 57.3 |
| 238 | 0.30 | 58.1 |
方法
- SEIR 仓室 Kermack 和 McKendrick（1927），Proc. R. Soc. A 115
- 通过人口流动实现的集合种群耦合 Balcan and others (2009), PNAS 106
- 小世界网络 Watts and Strogatz (1998), Nature 393
- 传染病建模 Keeling and Rohani (2008), Princeton University Press
- 不确定性扇形图（参数蒙特卡罗） Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- 单因素敏感性（龙卷风图） Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
数据
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- 城市 Natural Earth
- 机场 Natural Earth
- 主要道路 Natural Earth
贯穿六大支柱，由 Nexus Consortium 牵头
结果如何核查。
Results are checked through diagnostics, cross-validation and sensitivity to assumptions. Independent replication confirms findings.
Inference depends on assumptions about independence, distribution and sampling that may not hold. Small or biased samples limit reliability.
The model, the data and the uncertainty.
模型、其假设、数据和不确定性，以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意，不是研究发现。
不确定性区间
How far the outlook for probability and statistics for biotechnology and biosecurity could spread, shown as ranges rather than a single line.
- 中心估计值
- 集合的中位数
- 范围
- IPCC 校准用语中的“可能”和“很可能”
- 集合
- 明示成员、情景和初始条件
- 配合阅读
- 结果对每项输入的敏感性
由谁维护该方法。
系统科学与建模 stewards probability and statistics for the Consortium and reviews how it is applied across platforms.
本页在整个联合体中通向何处。
问题与解答。
What are the limits of probability and statistics in this field?
结果如何核查？
本页面上的数值是真实的吗？
该方法还应用于何处？
从本页贡献证据。
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