Added value of routine emergency medical data for detecting clusters of acute gastrointestinal illness in Europe

Ziemann, Alexandra; Riesgo, Luis García-Castrillo; Kauhl, Boris; Schrell, S.; Rosenkötter, Nicole; Fischer, Matthias; Vergeiner, Gernot; Gillet, Jean Bernard; Meulemans, Agnes; Krafft, Thomas

doi:10.1016/j.resuscitation.2012.08.075

Cited by 3 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Prospective space-time cluster detection has been widely applied in syndromic surveillance [84,85] and an automated, space-time analysis could be implemented for pertussis as well [86]. …”

Section: Discussionmentioning

confidence: 99%

Is the current pertussis incidence only the results of testing? A spatial and space-time analysis of pertussis surveillance data using cluster detection methods and geographically weighted regression modelling

et al. 2017

Self Cite

View full text Add to dashboard Cite

BackgroundDespite high vaccination coverage, pertussis incidence in the Netherlands is amongst the highest in Europe with a shifting tendency towards adults and elderly. Early detection of outbreaks and preventive actions are necessary to prevent severe complications in infants. Efficient pertussis control requires additional background knowledge about the determinants of testing and possible determinants of the current pertussis incidence. Therefore, the aim of our study is to examine the possibility of locating possible pertussis outbreaks using space-time cluster detection and to examine the determinants of pertussis testing and incidence using geographically weighted regression models.MethodsWe analysed laboratory registry data including all geocoded pertussis tests in the southern area of the Netherlands between 2007 and 2013. Socio-demographic and infrastructure-related population data were matched to the geo-coded laboratory data. The spatial scan statistic was applied to detect spatial and space-time clusters of testing, incidence and test-positivity. Geographically weighted Poisson regression (GWPR) models were then constructed to model the associations between the age-specific rates of testing and incidence and possible population-based determinants.ResultsSpace-time clusters for pertussis incidence overlapped with space-time clusters for testing, reflecting a strong relationship between testing and incidence, irrespective of the examined age group. Testing for pertussis itself was overall associated with lower socio-economic status, multi-person-households, proximity to primary school and availability of healthcare. The current incidence in contradiction is mainly determined by testing and is not associated with a lower socioeconomic status.DiscussionTesting for pertussis follows to an extent the general healthcare seeking behaviour for common respiratory infections, whereas the current pertussis incidence is largely the result of testing. More testing would thus not necessarily improve pertussis control. Detecting outbreaks using space-time cluster detection is feasible but needs to adjust for the strong impact of testing on the detection of pertussis cases.

show abstract

“…Prospective space-time cluster detection has been widely applied in syndromic surveillance [84,85] and an automated, space-time analysis could be implemented for pertussis as well [86]. …”

Section: Discussionmentioning

confidence: 99%

Is the current pertussis incidence only the results of testing? A spatial and space-time analysis of pertussis surveillance data using cluster detection methods and geographically weighted regression modelling

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…(II) For conceptualization and subsequent design of the case study, the System for Early warning based on Emergency Data (SEED), an interdisciplinary expert workshop bringing together professionals from the EMS syndromic surveillance project SIDARTHa [16,17], Indian surveillance system and EMS experts was organized. A participatory approach was used to jointly develop a framework adapted to the Indian surveillance needs for using EMS routinely collected data for infectious disease surveillance and early warning of outbreaks.…”

Section: Interview Questionsmentioning

confidence: 99%

“…The pilot project SEED, co-funded by the Indian Council for Medical Research and the German Ministry of Research and Education, was conceptualized and based on earlier experiences from the EMS syndromic surveillance project SIDARTHa [16,17,38,39]. The original project structure is shown in Figure 1.…”

Section: System For Early Warning Based On Emergency Data (Seed)mentioning

confidence: 99%

“…The starting point for the project was the assumption that calls from emergency medical services are routinely collected in electronic formats and can thus be analyzed and used for symptom/syndromic surveillance. EMS syndromic surveillance project SIDARTHa [16,17,38,39]. The original project structure is shown in Figure 1.…”

Section: System For Early Warning Based On Emergency Data (Seed)mentioning

confidence: 99%

See 1 more Smart Citation

Towards Sustainable Public Health Surveillance in India: Using Routinely Collected Electronic Emergency Medical Service Data for Early Warning of Infectious Diseases

et al. 2017

Self Cite

View full text Add to dashboard Cite

Infectious disease surveillance, timely detection and early warning of outbreaks present a complex challenge to health authorities in India. Approaches based on the use of unexplored data sources, like emergency medical services (EMS) data, can contribute to the further advancement of public health surveillance capacities in India and support and strengthen the Integrated Disease Surveillance Programme (IDSP) strategy. This research followed a mixed method approach including a series of semi-structured interviews and fever data analysis of the EMS operating dispatch system in Andra Pradesh, India. In this paper, we explore whether routinely collected EMS health data can improve sustainable infectious disease surveillance and early warning capacity. The result highlights the need for improved surveillance systems for early warning of infectious diseases in India. The data availability at the EMS dispatch centre includes patient data and spatial information and can be used for near real-time analysis. Routine data relevant for health surveillance can be extracted to provide timely health information that supplements and enhances more traditional surveillance mechanisms and thus provides a cost-efficient, near real-time early warning system for the operating states. The designed intervention is sustainable and can improve infectious disease surveillance to potentially help the government officials to appropriately prioritize timely interventions to prevent infectious disease spread.

show abstract

“…Prospective space-time cluster detection has been widely applied in syndromic surveillance (84,85) and an automated, space-time analysis could be implemented for pertussis as well (86).…”

Section: Outbreak Detection Using Space-time Cluster Detectionmentioning

confidence: 99%

Geographic Information Systems (GIS) in public health

Kauhl¹

View full text Add to dashboard Cite

Citation for published version (APA): Kauhl, B. (2018). Geographic Information Systems (GIS) in public health: how can GIS facilitate demandbased planning of healthcare and targeted prevention strategies?. Maastricht: Maastricht University. https://doi.org/10.26481/dis.20180117bk Document status and date:Published: 01/01/2018 DOI:10.26481/dis.20180117bk Document Version:Publisher's PDF, also known as Version of record Please check the document version of this publication:• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:www.umlib.nl/taverne-license Take down policyIf you believe that this document breaches copyright please contact us at:repository@maastrichtuniversity.nl providing details and we will investigate your claim. The research for this dissertation was performed at the department of Health, Ethics and Society, School for Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands.All rights reserved. No part of this thesis may be reproduced, stored, or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording or any information storage or retrieval system, without prior permission of the copyright owner. GEOGRAPHIC INFORMATION SYSTEMS (GIS) INPUBLIC Contents CHAPTER 1General introduction 8 CHAPTER 2Estimating the spatial distribution of acute undifferentiated fever (AUF) and associated risk factors using emergency call data in India. A symptom-based approach for public health surveillance. Health & place, 31,[111][112][113][114][115][116][117][118][119]. 25 CHAPTER 3The spatial distribution of hepatitis C virus infections and associated determinants -An application of a geographi...

show abstract

Added value of routine emergency medical data for detecting clusters of acute gastrointestinal illness in Europe

Cited by 3 publications

References 0 publications

Is the current pertussis incidence only the results of testing? A spatial and space-time analysis of pertussis surveillance data using cluster detection methods and geographically weighted regression modelling

Is the current pertussis incidence only the results of testing? A spatial and space-time analysis of pertussis surveillance data using cluster detection methods and geographically weighted regression modelling

Towards Sustainable Public Health Surveillance in India: Using Routinely Collected Electronic Emergency Medical Service Data for Early Warning of Infectious Diseases

Geographic Information Systems (GIS) in public health

Contact Info

Product

Resources

About