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.
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Lapisan 3
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Terbaru yang tersedia
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © kontributor OpenStreetMap (ODbL) · Natural Earth
Memuat citra NASA terbaru.
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Keterpaparan lingkungan, dengan bingkai Afrika.Produk satelit dan model sebagaimana diterbitkan NASA, masing-masing dengan tanggalnya sendiri. Produk ini adalah indikator, bukan penilaian atas tempat mana pun.
Lapisan dan tanggal
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 register sumber.
| Data | Peran | Label |
|---|---|---|
| Notifiable disease reporting sistem | Case counts by place, time and person | DILAPORKAN |
| Sentinel influenza and respiratory surveillance | Trends under stable case definitions | TERAMATI |
| Vital registration | Mortality baselines and excess deaths | Statistik terbitan |
| Household and health surveys | Prevalence and coverage with sampling weights | ESTIMASI |
| Routine health information systems | Service volumes and facility reporting | DILAPORKAN |
Layar yang akan digunakan sebuah tim untuk mengikuti metode ini: ukuran, status, dan keputusannya. Nama adalah contoh dan nilai bersifat ilustratif.
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.
| Pemeriksaan | Cara pelaksanaannya |
|---|---|
| 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.
Kendali
Pembacaan
| Hari | Infeksi baru per 1 000 | Kumulatif terinfeksi (%) |
|---|---|---|
| 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:
Di seluruh enam pilar, dipimpin oleh Nexus Consortium
Disusun dari profil bidang Nexus Standards profil area Ketahanan kesehatan dan One Health: bahaya yang disebutkannya, sistem dan sektor yang menanggung kerugian, kendali yang meredamnya, dan data yang mengamatinya. Pilih komponen, tentukan bahaya pemicu, dan telusuri kaskade langkah demi langkah. Tampilan Peta menempatkan proses pada contoh geografi dengan data terbuka. Setiap bobot keterkaitan adalah asumsi yang dinyatakan dan dapat Anda ubah. Model pengajaran, bukan prakiraan, penilaian, atau sertifikasi. Untuk memodelkan tempat pilihan Anda sendiri, buka System Builder.
Bahaya
Sistem dan keterkaitan
Kendali
NS-0 Anggaran dasar dan prinsipNS-3 UNI catatan risiko (tata bahasa, pemetaan ke sistem lama, kewenangan alokasi)NS-9 UNI kontekstual (penerapan, instans, instans program)NS-10 Kebijakan dan klausul (kewajiban yang dapat dibaca mesin: definisi, pengikatan, evaluasi, dan penegakan)NS-11 Verifikasi dan pemantauan (bukti, atestasi, pengamatan kesesuaian zero trust)NRS-H83 Keluarga bahaya: Kegagalan kapasitas sistem kesehatan (NHS-1 health.system)NRS-H42 Keluarga bahaya: Infeksi manusia yang langka dan menetap (NHS-1 health.other-human)NRS-H41 Keluarga bahaya: Limpahan dari hewan ke manusia (NHS-1 health.zoonotic)NRS-H43 Keluarga bahaya: Epizootik peternakan dan akuakultur (NHS-1 health.animal-health)NRS-D3 Respons kemanusiaan dan pemulihan yang tangguhNRS-H46 Keluarga bahaya: Bahaya lingkungan dan produk bagi manusia (NHS-1 health.harm)Pengamatan
Contoh geografi
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.
Pilih konteks
Sektor · PandemiTekanan
Pilar · PandemiKPI
Dalam konteks iniKetergantungan atau serah terima, semakin tebal semakin kuatDi luar konteks ini
Tahun programSemua fase
Konteks
Pandemi
Ketidakhadiran tenaga kerja merambat dari klinik ke operasi jaringan listrik, logistik, dan tenaga kerja pertanian.
W · E · I · F · H · B
Risiko
Arahkan kursor ke sudut, garis, atau baris untuk menelusurinya di kedua sisi.
Rute
Diterapkan pada pandemi
L · F · U · S · R · A
Respons
Nilai harapan
Arahkan kursor ke pilar, garis, atau baris untuk membaca cara penerapannya.
A: kaskade pengajaran (guncangan 0,6, penguatan 0,35, empat putaran) atas nilai pengajaran untuk wilayah kota yang tipikal, bukan pengukuran. B: penerapan ilustratif dan KPI yang menjadi tanggung jawab setiap pilar. Nilai adalah tolok ukur yang diterbitkan dan dikutip, bukan prakiraan. Peristiwa terbuka: NASA EONET, langsung.
Model, asumsi, data, dan ketidakpastiannya, dalam bentuk yang akan diperiksa ilmuwan atau insinyur. Strukturnya mengikuti metode yang dipublikasikan. Nilai yang digambar bersifat ilustratif, bukan temuan.
How far the outlook for epidemiology for health security could spread, shown as ranges rather than a single line.
Laporan 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.
Jangan pernah mengirim data pribadi, rincian infrastruktur sensitif, atau apa pun yang tidak berhak Anda bagikan. Kontribusi ditinjau sebelum digunakan. Mengirimkannya tidak memberikan hak kepenulisan atau editorial, dan sponsor tidak pernah membeli sebuah temuan.
Informasi dan pertanyaan sudah terbuka hari ini. Sebuah pertanyaan menerima nomor referensi dan menyebutkan langkah berikutnya; lamaran, pembayaran, alokasi komputasi, dan pendaftaran hanya dibuka ketika tim, ketentuan, dan kapasitas tinjauannya tersedia.
Peta, data, dan gambar di situs ini ditampilkan untuk konteks dan informasi umum. Semua itu bukan nasihat, prakiraan, atau peringatan; batasan informasinya dijelaskan dalam Penafian dan Pemberitahuan Data.
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