Cargando…

Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania

An effective disease surveillance system is critical for early detection and response to disease epidemics. This study aimed to assess the capacity to manage and utilize disease surveillance data and implement an intervention to improve data analysis and use at the district level in Tanzania. Mappin...

Descripción completa

Detalles Bibliográficos
Autores principales: Mremi, Irene R., Sindato, Calvin, Kishamawe, Coleman, Rumisha, Susan F., Kimera, Sharadhuli I., Mboera, Leonard E.G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351552/
https://www.ncbi.nlm.nih.gov/pubmed/35916840
http://dx.doi.org/10.1080/16549716.2022.2090100
_version_ 1784762467509862400
author Mremi, Irene R.
Sindato, Calvin
Kishamawe, Coleman
Rumisha, Susan F.
Kimera, Sharadhuli I.
Mboera, Leonard E.G.
author_facet Mremi, Irene R.
Sindato, Calvin
Kishamawe, Coleman
Rumisha, Susan F.
Kimera, Sharadhuli I.
Mboera, Leonard E.G.
author_sort Mremi, Irene R.
collection PubMed
description An effective disease surveillance system is critical for early detection and response to disease epidemics. This study aimed to assess the capacity to manage and utilize disease surveillance data and implement an intervention to improve data analysis and use at the district level in Tanzania. Mapping, in-depth interview and desk review were employed for data collection in Ilala and Kinondoni districts in Tanzania. Interviews were conducted with members of the council health management teams (CHMT) to assess attitudes, motivation and practices related to surveillance data analysis and use. Based on identified gaps, an intervention package was developed on basic data analysis, interpretation and use. The effectiveness of the intervention package was assessed using pre-and post-intervention tests. Individual interviews involved 21 CHMT members (females = 10; males = 11) with an overall median age of 44.5 years (IQR = 37, 53). Over half of the participants regarded their data analytical capacities and skills as excellent. Analytical capacity was higher in Kinondoni (61%) than Ilala (52%). Agreement on the availability of the opportunities to enhance capacity and skills was reported by 68% and 91% of the participants from Ilala and Kinondoni, respectively. Reported challenges in disease surveillance included data incompleteness and difficulties in storage and accessibility. Training related to enhancement of data management was reported to be infrequently done. In terms of data interpretation and use, despite reporting of incidence of viral haemorrhagic fevers for five years, no actions were taken to either investigate or mitigate, indicating poor use of surveillance data in monitoring disease occurrence. The overall percentage increase on surveillance knowledge between pre-and post-training was 37.6% for Ilala and 20.4% for Kinondoni indicating a positive impact on of the training. Most of CHMT members had limited skills and practices on data analysis, interpretation and use. The training in data analysis and interpretation significantly improved skills of the participants.
format Online
Article
Text
id pubmed-9351552
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Taylor & Francis
record_format MEDLINE/PubMed
spelling pubmed-93515522022-08-05 Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania Mremi, Irene R. Sindato, Calvin Kishamawe, Coleman Rumisha, Susan F. Kimera, Sharadhuli I. Mboera, Leonard E.G. Glob Health Action Research Article An effective disease surveillance system is critical for early detection and response to disease epidemics. This study aimed to assess the capacity to manage and utilize disease surveillance data and implement an intervention to improve data analysis and use at the district level in Tanzania. Mapping, in-depth interview and desk review were employed for data collection in Ilala and Kinondoni districts in Tanzania. Interviews were conducted with members of the council health management teams (CHMT) to assess attitudes, motivation and practices related to surveillance data analysis and use. Based on identified gaps, an intervention package was developed on basic data analysis, interpretation and use. The effectiveness of the intervention package was assessed using pre-and post-intervention tests. Individual interviews involved 21 CHMT members (females = 10; males = 11) with an overall median age of 44.5 years (IQR = 37, 53). Over half of the participants regarded their data analytical capacities and skills as excellent. Analytical capacity was higher in Kinondoni (61%) than Ilala (52%). Agreement on the availability of the opportunities to enhance capacity and skills was reported by 68% and 91% of the participants from Ilala and Kinondoni, respectively. Reported challenges in disease surveillance included data incompleteness and difficulties in storage and accessibility. Training related to enhancement of data management was reported to be infrequently done. In terms of data interpretation and use, despite reporting of incidence of viral haemorrhagic fevers for five years, no actions were taken to either investigate or mitigate, indicating poor use of surveillance data in monitoring disease occurrence. The overall percentage increase on surveillance knowledge between pre-and post-training was 37.6% for Ilala and 20.4% for Kinondoni indicating a positive impact on of the training. Most of CHMT members had limited skills and practices on data analysis, interpretation and use. The training in data analysis and interpretation significantly improved skills of the participants. Taylor & Francis 2022-08-02 /pmc/articles/PMC9351552/ /pubmed/35916840 http://dx.doi.org/10.1080/16549716.2022.2090100 Text en © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Mremi, Irene R.
Sindato, Calvin
Kishamawe, Coleman
Rumisha, Susan F.
Kimera, Sharadhuli I.
Mboera, Leonard E.G.
Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania
title Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania
title_full Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania
title_fullStr Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania
title_full_unstemmed Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania
title_short Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania
title_sort improving disease surveillance data analysis, interpretation, and use at the district level in tanzania
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351552/
https://www.ncbi.nlm.nih.gov/pubmed/35916840
http://dx.doi.org/10.1080/16549716.2022.2090100
work_keys_str_mv AT mremiirener improvingdiseasesurveillancedataanalysisinterpretationanduseatthedistrictlevelintanzania
AT sindatocalvin improvingdiseasesurveillancedataanalysisinterpretationanduseatthedistrictlevelintanzania
AT kishamawecoleman improvingdiseasesurveillancedataanalysisinterpretationanduseatthedistrictlevelintanzania
AT rumishasusanf improvingdiseasesurveillancedataanalysisinterpretationanduseatthedistrictlevelintanzania
AT kimerasharadhulii improvingdiseasesurveillancedataanalysisinterpretationanduseatthedistrictlevelintanzania
AT mboeraleonardeg improvingdiseasesurveillancedataanalysisinterpretationanduseatthedistrictlevelintanzania