ReviewBMC public health2011
A growing global network's role in outbreak response: AFHSC-GEIS 2008-2009.
Review in BMC public health, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Surveillance of emerging infectious diseases for biosecurity.Science China. Life sciences · 2022Review
- SARS-CoV-2 Transmission in the Military during the Early Phase of the Pandemic-A Systematic Analysis.International journal of environmental research and public health · 2022Article
- A Transdisciplinary Approach to Address Climate Change Adaptation for Human Health and Well-Being in Africa.International journal of environmental research and public health · 2021Article
- Respiratory Infections in the U.S. Military: Recent Experience and Control.Clinical microbiology reviews · 2015Review
- Emerging and re-emerging infectious diseases: challenges and opportunities for militaries.Military Medical Research · 2014Article
- Capacity-building efforts by the AFHSC-GEIS program.BMC public health · 2011Review
- International Health Regulations (2005) and the U.S. Department of Defense: building core capacities on a foundation of partnership and trust.BMC public health · 2010Article
- Initial identification and characterization of an emerging zoonotic influenza virus prior to pandemic spread.Journal of clinical microbiology · 2010Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
51 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A cornerstone of effective disease surveillance programs comprises the early identification of infectious threats and the subsequent rapid response to prevent further spread. Effectively identifying, tracking and responding to these threats is often difficult and requires international cooperation due to the rapidity with which diseases cross national borders and spread throughout the global community as a result of travel and migration by humans and animals. From Oct.1, 2008 to Sept. 30, 2009, the United States Department of Defense's (DoD) Armed Forces Health Surveillance Center Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) identified 76 outbreaks in 53 countries. Emerging infectious disease outbreaks were identified by the global network and included a wide spectrum of support activities in collaboration with host country partners, several of which were in direct support of the World Health Organization's (WHO) International Health Regulations (IHR) (2005). The network also supported military forces around the world affected by the novel influenza A/H1N1 pandemic of 2009. With IHR (2005) as the guiding framework for action, the AFHSC-GEIS network of international partners and overseas research laboratories continues to develop into a far-reaching system for identifying, analyzing and responding to emerging disease threats.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.