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Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen
BACKGROUND: Diseases Surveillance is a continuous process of data collection, analysis interpretation and dissemination of information for swift public health action. Recent advances in health informatics have led to the implementation of electronic tools to facilitate such critical disease surveill...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7501711/ https://www.ncbi.nlm.nih.gov/pubmed/32948155 http://dx.doi.org/10.1186/s12889-020-09460-4 |
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author | Dureab, Fekri Ahmed, Kamran Beiersmann, Claudia Standley, Claire J. Alwaleedi, Ali Jahn, Albrecht |
author_facet | Dureab, Fekri Ahmed, Kamran Beiersmann, Claudia Standley, Claire J. Alwaleedi, Ali Jahn, Albrecht |
author_sort | Dureab, Fekri |
collection | PubMed |
description | BACKGROUND: Diseases Surveillance is a continuous process of data collection, analysis interpretation and dissemination of information for swift public health action. Recent advances in health informatics have led to the implementation of electronic tools to facilitate such critical disease surveillance processes. This study aimed to assess the performance of the national electronic Disease Early Warning System in Yemen (eDEWS) using system attributes: data quality, timeliness, stability, simplicity, predictive value positive, sensitivity, acceptability, flexibility, and representativeness, based on the Centres for Disease Control & Prevention (US CDC) standard indicators. METHODS: We performed a mixed methods study that occurred in two stages: first, the quantitative data was collected from weekly epidemiological bulletins from 2013 to 2017, all alerts of 2016, and annual eDEWS reports, and then the qualitative method using in-depth interviews was carried out in a convergent strategy. The CDC guideline used to describe the following system attributes: data quality (reporting, and completeness), timeliness, stability, simplicity, predictive value positive, sensitivity, acceptability, flexibility and representativeness. RESULTS: The finding of this assessment showed that eDEWS is a resilient and reliable system, and despite the conflict in Yemen, the system is still functioning and expanding. The response timeliness remains a challenge, since only 21% of all eDEWS alerts were verified within the first 24 h of detection in 2016. However, identified gaps did not affect the system’s ability to identify outbreaks in the current fragile situation. Findings show that eDEWS data is representative, since it covers the entire country. Although, eDEWS covers only 37% of all health facilities, this represents 83% of all functional health facilities in all 23 governorates and all 333 districts. CONCLUSION: The quality and timeliness of responses are major challenges to eDEWS’ functionality, the eDEWS remains the only system that provides regular data on communicable diseases in Yemen. In particular, public health response timeliness needs improvement. |
format | Online Article Text |
id | pubmed-7501711 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-75017112020-09-22 Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen Dureab, Fekri Ahmed, Kamran Beiersmann, Claudia Standley, Claire J. Alwaleedi, Ali Jahn, Albrecht BMC Public Health Research Article BACKGROUND: Diseases Surveillance is a continuous process of data collection, analysis interpretation and dissemination of information for swift public health action. Recent advances in health informatics have led to the implementation of electronic tools to facilitate such critical disease surveillance processes. This study aimed to assess the performance of the national electronic Disease Early Warning System in Yemen (eDEWS) using system attributes: data quality, timeliness, stability, simplicity, predictive value positive, sensitivity, acceptability, flexibility, and representativeness, based on the Centres for Disease Control & Prevention (US CDC) standard indicators. METHODS: We performed a mixed methods study that occurred in two stages: first, the quantitative data was collected from weekly epidemiological bulletins from 2013 to 2017, all alerts of 2016, and annual eDEWS reports, and then the qualitative method using in-depth interviews was carried out in a convergent strategy. The CDC guideline used to describe the following system attributes: data quality (reporting, and completeness), timeliness, stability, simplicity, predictive value positive, sensitivity, acceptability, flexibility and representativeness. RESULTS: The finding of this assessment showed that eDEWS is a resilient and reliable system, and despite the conflict in Yemen, the system is still functioning and expanding. The response timeliness remains a challenge, since only 21% of all eDEWS alerts were verified within the first 24 h of detection in 2016. However, identified gaps did not affect the system’s ability to identify outbreaks in the current fragile situation. Findings show that eDEWS data is representative, since it covers the entire country. Although, eDEWS covers only 37% of all health facilities, this represents 83% of all functional health facilities in all 23 governorates and all 333 districts. CONCLUSION: The quality and timeliness of responses are major challenges to eDEWS’ functionality, the eDEWS remains the only system that provides regular data on communicable diseases in Yemen. In particular, public health response timeliness needs improvement. BioMed Central 2020-09-18 /pmc/articles/PMC7501711/ /pubmed/32948155 http://dx.doi.org/10.1186/s12889-020-09460-4 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Dureab, Fekri Ahmed, Kamran Beiersmann, Claudia Standley, Claire J. Alwaleedi, Ali Jahn, Albrecht Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen |
title | Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen |
title_full | Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen |
title_fullStr | Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen |
title_full_unstemmed | Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen |
title_short | Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen |
title_sort | assessment of electronic disease early warning system for improved disease surveillance and outbreak response in yemen |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7501711/ https://www.ncbi.nlm.nih.gov/pubmed/32948155 http://dx.doi.org/10.1186/s12889-020-09460-4 |
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