Surveillance design and evaluation
Indicator-based reporting, sentinel sites and event-based signals are combined, and each stream is evaluated for sensitivity, timeliness, completeness and representativeness against agreed surveillance attributes.
GCRI · Health Nexus
Epidemiology is the core science of this platform: it describes who becomes ill, where and when, identifies the determinants of disease, and evaluates what prevents it. Surveillance, outbreak investigation and burden estimation turn scattered reports into evidence that public health authorities can act on, with delays and biases stated.
Epidemiology studies the distribution and determinants of health and disease in populations. It provides the evidence used to detect outbreaks, estimate burden and evaluate interventions. In health and biosecurity, epidemiological evidence informs preparedness, resource allocation and the economic consequences of disease. It shows how health shocks interact with travel, labour, supply chains and public finance. The canonical description is on STEM Commons.
Indicator-based reporting, sentinel sites and event-based signals are combined, and each stream is evaluated for sensitivity, timeliness, completeness and representativeness against agreed surveillance attributes.
Delay distributions estimated from past reports adjust recent counts for cases not yet reported, so the latest weeks are shown with their uncertainty rather than as an artificial decline.
Expected service use and outcomes are modelled from trends before a shock and compared with observed data, separating the indirect harm of interrupted care from the direct effects of the shock.
Population density, daytime surface heat and haze over Africa, from NASA GIBS. Each layer carries its own date.
交互式地图需要JavaScript;图层列表和来源见下文。
图层 3
本页的环境暴露
键盘操作,地图获得焦点时
按住 Ctrl 或 ⌘ 并滚动以缩放
最新可用
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth
正在加载最新的NASA影像。
拖动以移动。按住 Ctrl 或 ⌘ 并滚动、双指缩放或使用按钮缩放;悬停可查看指针下的数值;重置可返回该区域。
环境风险暴露,以非洲为范围。NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。
图层与日期
Datasets and records used by epidemiology and public health science 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 |
|---|---|---|
| Notifiable disease reporting 系统 | Case counts by place, time and person | 已报告 |
| Sentinel influenza and respiratory surveillance | Trends under stable case definitions | 观测 |
| Vital registration | Mortality baselines and excess deaths | 已发布统计 |
| Household and health surveys | Prevalence and coverage with sampling weights | 估算 |
| Routine health information systems | Service volumes and facility reporting | 已报告 |
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。
Health · Epidemiology for health security · Run R-8417
| Rt | 1.3 | 0.84 | 1.6 |
| Doubling time (days) | 18 | 4 | 29 |
| Reporting fraction | 0.4 | 0.2 | 0.9 |
Findings are checked through replication, sensitivity analyses and comparison of independent surveillance streams. Transmission models are assessed by out-of-sample forecasting of case counts.
| 核查 | 如何开展 |
|---|---|
| Surveillance attribute review | Sensitivity, timeliness, completeness and representativeness are assessed against established surveillance evaluation guidelines |
| Independent stream comparison | Trends in notifications are compared with laboratory, sentinel and mortality data before a change is described |
| Case definition stability | Changes in definitions, testing or reporting are logged and their effect on trends assessed |
| Out-of-sample scoring | Transmission models are scored on periods they were not fitted to |
Reporting delays, under-ascertainment and confounding bias estimates. Behaviour change during outbreaks alters the parameters models rely on.
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. The map on this page shows Africa; the model itself is not tied to a place.
控制措施
读数
| 日 | 每 1,000 人新增感染 | 累计感染(%) |
|---|---|---|
| 0 | 0.00 | 0.0 |
| 17 | 0.02 | 0.0 |
| 34 | 0.24 | 0.2 |
| 51 | 0.74 | 1.1 |
| 68 | 1.45 | 2.9 |
| 85 | 2.33 | 6.2 |
| 102 | 2.95 | 10.8 |
| 119 | 3.07 | 16.0 |
| 136 | 3.12 | 21.2 |
| 153 | 3.42 | 26.7 |
| 170 | 3.83 | 32.9 |
| 187 | 4.01 | 39.6 |
| 204 | 3.66 | 46.2 |
| 221 | 2.71 | 51.7 |
| 238 | 1.57 | 55.2 |
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:
贯穿六大支柱,由 Nexus Consortium 牵头
Assembled from the Nexus Standards area profile 卫生安全与同一健康: the hazards it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
灾害
系统与耦合
控制措施
NS-0 章程与原则NS-3 风险记录 UNI(语法、旧编码对照、分配机构)NS-9 情境 UNI(部署、实例、计划实例)NS-10 政策和条款(机器可读的义务:定义、约束、评估和执行)NS-11 验证与监测(证据、证明、零信任符合性观测)NRS-H83 危害族:卫生系统能力失效(NHS-1 health.system)NRS-H42 危害类别:罕见和持续性人类感染(NHS-1 health.other-human)NRS-H41 危害族:动物向人类的溢出(NHS-1 health.zoonotic)NRS-H43 危害族:畜牧业和水产养殖动物疫病(NHS-1 health.animal-health)NRS-D3 人道主义响应与韧性恢复NRS-H46 危害类别:环境与产品对人的伤害(NHS-1 health.harm)观测
示例地理范围
Health Nexus stewards epidemiology and public health science for the Consortium and reviews how it is applied across platforms.
The sectors pandemic touches and how strongly they depend on each other: what a study has to observe and model together.
选择背景
部门 · 大流行病压力
支柱 · 大流行病KPI
在此背景之中依赖或移交关系,越粗越强不在此背景之内
计划年度所有阶段
背景
大流行病
人员缺勤从诊所蔓延至电网运营、物流和农业劳动力。
W · E · I · F · H · B
风险
将鼠标悬停在某个角、某条线或某一行上,可在两侧追踪其走向。
路径
应用于大流行病
L · F · U · S · R · A
响应
期望值
将鼠标悬停在支柱、线条或行上,查看其应用方式。
A:基于典型城市区域教学用值的教学级联(冲击 0.6,增益 0.35,四轮),并非实测值。B:示意性应用及每个支柱所负责的关键绩效指标;数值为已发布并注明出处的基准,并非预测。开放事件:NASA EONET,实时。
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。
How far the outlook for epidemiology for health security could spread, shown as ranges rather than a single line.
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
切勿发送个人数据、敏感基础设施细节或您无权分享的任何内容。贡献在使用前会经过审查;发送贡献不赋予署名权或编辑权,赞助也绝不能换取研究结论。
本网站上的地图、数据和图表仅作为背景和一般信息展示。它们不是建议、预测或预警;信息的局限见免责声明和数据说明。
This site uses only strictly necessary cookies to work and to remember your privacy choices. Nothing loads from other companies, and we never sell or share your personal information.
This site uses only strictly necessary cookies to work and to remember your privacy choices. Nothing loads from other companies, and we never sell or share your personal information. We run no advertising. You can review your choices at any time through Privacy choices at the foot of every page.