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Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021

INTRODUCTION: Disease surveillance provides vital data for disease prevention and control programs. Incomplete and untimely data are common challenges in planning, monitoring, and evaluation of health sector performance, and health service delivery. Weekly surveillance data are sent from health faci...

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Autores principales: Nansikombi, Hildah Tendo, Kwesiga, Benon, Aceng, Freda L., Ario, Alex R., Bulage, Lilian, Arinaitwe, Emma S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072024/
https://www.ncbi.nlm.nih.gov/pubmed/37016380
http://dx.doi.org/10.1186/s12889-023-15534-w
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author Nansikombi, Hildah Tendo
Kwesiga, Benon
Aceng, Freda L.
Ario, Alex R.
Bulage, Lilian
Arinaitwe, Emma S.
author_facet Nansikombi, Hildah Tendo
Kwesiga, Benon
Aceng, Freda L.
Ario, Alex R.
Bulage, Lilian
Arinaitwe, Emma S.
author_sort Nansikombi, Hildah Tendo
collection PubMed
description INTRODUCTION: Disease surveillance provides vital data for disease prevention and control programs. Incomplete and untimely data are common challenges in planning, monitoring, and evaluation of health sector performance, and health service delivery. Weekly surveillance data are sent from health facilities using mobile tracking (mTRAC) program, and synchronized into the District Health Information Software version 2 (DHIS2). The data are then merged into district, regional, and national level datasets. We described the completeness and timeliness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021. METHODS: We abstracted data on completeness and timeliness of weekly reporting of epidemic-prone diseases from 146 districts of Uganda from the DHIS2.Timeliness is the proportion of all expected weekly reports that were submitted to DHIS2 by 12:00pm Monday of the following week. Completeness is the proportion of all expected weekly reports that were completely filled and submitted to DHIS2 by 12:00pm Wednesday of the following week. We determined the proportions and trends of completeness and timeliness of reporting at national level by year, health region, district, health facility level, and facility ownership. RESULTS: National average reporting timeliness and completeness was 44% and 70% in 2020, and 49% and 75% in 2021. Eight of the 15 health regions achieved the target for completeness of ≥ 80%; Lango attained the highest (93%) in 2020, and Karamoja attained 96% in 2021. None of the regions achieved the timeliness target of ≥ 80% in either 2020 or 2021. Kampala District had the lowest completeness (38% and 32% in 2020 and 2021, respectively) and the lowest timeliness (19% in both 2020 and 2021). Referral hospitals and private owned health facilities did not attain any of the targets, and had the poorest reporting rates throughout 2020 and 2021. CONCLUSION: Weekly surveillance reporting on epidemic prone diseases improved modestly over time, but timeliness of reporting was poor. Further investigations to identify barriers to reporting timeliness for surveillance data are needed to address the variations in reporting.
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spelling pubmed-100720242023-04-04 Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021 Nansikombi, Hildah Tendo Kwesiga, Benon Aceng, Freda L. Ario, Alex R. Bulage, Lilian Arinaitwe, Emma S. BMC Public Health Research INTRODUCTION: Disease surveillance provides vital data for disease prevention and control programs. Incomplete and untimely data are common challenges in planning, monitoring, and evaluation of health sector performance, and health service delivery. Weekly surveillance data are sent from health facilities using mobile tracking (mTRAC) program, and synchronized into the District Health Information Software version 2 (DHIS2). The data are then merged into district, regional, and national level datasets. We described the completeness and timeliness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021. METHODS: We abstracted data on completeness and timeliness of weekly reporting of epidemic-prone diseases from 146 districts of Uganda from the DHIS2.Timeliness is the proportion of all expected weekly reports that were submitted to DHIS2 by 12:00pm Monday of the following week. Completeness is the proportion of all expected weekly reports that were completely filled and submitted to DHIS2 by 12:00pm Wednesday of the following week. We determined the proportions and trends of completeness and timeliness of reporting at national level by year, health region, district, health facility level, and facility ownership. RESULTS: National average reporting timeliness and completeness was 44% and 70% in 2020, and 49% and 75% in 2021. Eight of the 15 health regions achieved the target for completeness of ≥ 80%; Lango attained the highest (93%) in 2020, and Karamoja attained 96% in 2021. None of the regions achieved the timeliness target of ≥ 80% in either 2020 or 2021. Kampala District had the lowest completeness (38% and 32% in 2020 and 2021, respectively) and the lowest timeliness (19% in both 2020 and 2021). Referral hospitals and private owned health facilities did not attain any of the targets, and had the poorest reporting rates throughout 2020 and 2021. CONCLUSION: Weekly surveillance reporting on epidemic prone diseases improved modestly over time, but timeliness of reporting was poor. Further investigations to identify barriers to reporting timeliness for surveillance data are needed to address the variations in reporting. BioMed Central 2023-04-04 /pmc/articles/PMC10072024/ /pubmed/37016380 http://dx.doi.org/10.1186/s12889-023-15534-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Nansikombi, Hildah Tendo
Kwesiga, Benon
Aceng, Freda L.
Ario, Alex R.
Bulage, Lilian
Arinaitwe, Emma S.
Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021
title Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021
title_full Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021
title_fullStr Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021
title_full_unstemmed Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021
title_short Timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in Uganda, 2020–2021
title_sort timeliness and completeness of weekly surveillance data reporting on epidemic prone diseases in uganda, 2020–2021
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072024/
https://www.ncbi.nlm.nih.gov/pubmed/37016380
http://dx.doi.org/10.1186/s12889-023-15534-w
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