Evidence map›Paper›PMID 28230525›Full record

ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2017

Inference and forecast of H7N9 influenza in China, 2013 to 2015.

Ruiyun Li, Yuqi Bai, Alex Heaney, Sasikiran Kandula, Jun Cai, Xuyi Zhao, Bing Xu, Jeffrey Shaman

Abstract read
In one paragraph

Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ruiyun LiState Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.
Yuqi BaiMinistry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China.
Alex HeaneyDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, United States.
Sasikiran KandulaDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, United States.
Jun CaiMinistry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China.
Xuyi ZhaoMinistry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China.
Bing XuState Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.
Jeffrey ShamanDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, United States.

Funding

True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MATTHEW S PERZANOWSKI · 1998 to 2026
$44.7M
Development and Dissemination of Operational Real-Time Respiratory Virus ForecastU01GM110748 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2014 to 2018
$2.6M
Interdisciplinary Training in Climate and HealthT32ES023770 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2014 to 2019
$1.5M
Influenza Outbreak Prediction: Applying Data Assimilation Methodology to Make...R01GM100467 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2011 to 2015
$1.4M
NIEHS NIH HHS P30 ES009089NIEHS NIH HHS T32 ES023770NIGMS NIH HHS R01 GM100467NIGMS NIH HHS U01 GM110748
6 · The paper itself

Abstract

The recent emergence of A(H7N9) avian influenza poses a significant challenge to public health in China and around the world; however, understanding of the transmission dynamics and progression of influenza A(H7N9) infection in domestic poultry, as well as spillover transmission to humans, remains limited. Here, we develop a mathematical model-Bayesian inference system which combines a simple epidemic model and data assimilation method, and use it in conjunction with data on observed human influenza A(H7N9) cases from 19 February 2013 to 19 September 2015 to estimate key epidemiological parameters and to forecast infection in both poultry and humans. Our findings indicate a high outbreak attack rate of 33% among poultry but a low rate of chicken-to-human spillover transmission. In addition, we generated accurate forecasts of the peak timing and magnitude of human influenza A(H7N9) cases. This work demonstrates that transmission dynamics within an avian reservoir can be estimated and that real-time forecast of spillover avian influenza in humans is possible.

Indexed as

Bayes TheoremDisease OutbreaksForecastingInfluenza A Virus, H7N9 SubtypeModels, TheoreticalAnimalsBirdsChinaHumansInfluenza, HumanInfluenza in BirdsPoultryavian influenzadata assimilationforecastingH7N9

Identifiers

PMID28230525
PMCPMC5322186

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.