About: Integrated biological–behavioural surveillance in pandemic-threat warning systems

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About: Integrated biological–behavioural surveillance in pandemic-threat warning systems Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Integrated biological–behavioural surveillance in pandemic-threat warning systems
Creator	Hagan, Emily Miller, Maureen
Source	Medline; PMC
abstract	Economically and politically disruptive disease outbreaks are a hallmark of the 21st century. Although pandemics are driven by human behaviours, current surveillance systems for identifying pandemic threats are largely reliant on the monitoring of disease outcomes in clinical settings. Standardized integrated biological–behavioural surveillance could, and should, be used in community settings to complement such clinical monitoring. The usefulness of such an approach has already been demonstrated in studies on human immunodeficiency virus, where integrated surveillance contributed to a biologically based and quantifiable understanding of the behavioural risk factors associated with the transmission dynamics of the virus. When designed according to Strengthening the Reporting of Observational Studies in Epidemiology criteria, integrated surveillance requires that both behavioural risk factors – i.e. exposure variables – and disease-indicator outcome variables be measured in behavioural surveys. In the field of pandemic threats, biological outcome data could address the weaknesses of self-reported data collected in behavioural surveys. Data from serosurveys of viruses with pandemic potential, collected under non-outbreak conditions, indicate that serosurveillance could be used to predict future outbreaks. When conducted together, behavioural surveys and serosurveys could warn of future pandemics, potentially before the disease appears in clinical settings. Traditional disease-outcome surveillance must be frequent and ongoing to remain useful but behavioural surveillance remains informative even if conducted much less often, since behaviour change occurs slowly over time. Only through knowledge of specific behavioural risk factors can interventions and policies that can prevent the next pandemic be developed.
has issue date	2017-01-01(xsd:dateTime)
bibo:doi	10.2471/blt.16.175984
bibo:pmid	28053365
has license	cc-by
sha1sum (hex)	37d6ce7eabf4b6177b9462771494c7c2fc36e5ee
schema:url	https://doi.org/10.2471/blt.16.175984
resource representing a document's title	Integrated biological–behavioural surveillance in pandemic-threat warning systems
has PubMed Central identifier	PMC5180348
has PubMed identifier	28053365
schema:publication	Bull World Health Organ
resource representing a document's body	covid:37d6ce7eabf4b6177b9462771494c7c2fc36e5ee#body_text
is schema:about of	named entity 'INTEGRATED' named entity 'PANDEMIC' named entity 'BIOLOGICAL' named entity 'SURVEILLANCE' named entity 'SYSTEMS' named entity 'THREAT' named entity 'BEHAVIOURAL' named entity 'WARNING' named entity 'outcome data' named entity 'zoonotic' named entity 'zoonotic' named entity 'viruses' named entity 'risk factors' named entity 'zoonotic' named entity 'live animals' named entity 'virus' named entity 'zoonotic' named entity 'pandemics' named entity 'zoonotic disease' named entity 'MERS' named entity 'Liberia' named entity 'seroprevalence' named entity 'zoonotic' named entity 'pandemics' named entity 'HIV transmission' named entity 'infection' named entity 'hantavirus' named entity 'T-lymphocyte' named entity 'zoonotic' named entity 'avian influenza' named entity 'zoonotic virus' named entity 'zoonoses' named entity 'Republic of Korea' named entity 'HIV' named entity 'SARS' named entity 'outcome data' named entity 'human infection' named entity 'rodent' named entity 'etiology' named entity 'risk factors' named entity 'risk factors' named entity 'Indirect contact' named entity 'zoonotic' named entity 'evidence-based' named entity 'Ebola outbreak' named entity 'zoonotic disease' named entity 'coronaviruses' named entity 'data collected' named entity 'simian foamy virus' named entity 'public health policy' named entity 'serological' named entity 'Nipah virus' named entity 'outcome data' named entity 'high-risk' named entity 'virus' named entity 'infectious disease' named entity 'risk factors' named entity 'pathogen' named entity 'zoonotic' named entity 'avian influenza' named entity 'civil registration' named entity 'paramyxoviruses' named entity 'HIV infection' named entity 'pandemic threats' named entity 'risk factors' named entity 'HIV' named entity 'global health' named entity 'risk factors' named entity 'cross-reactivity' named entity 'viral infections' named entity 'serological' named entity 'Observational Studies' named entity 'Africa' named entity 'cost-effective' named entity 'disease surveillance' named entity 'disease surveillance' named entity 'behaviour change' named entity 'viruses' named entity 'human-to-human' named entity 'zoonotic'

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