High-quality surveillance data provide valid and useful evidence for decision-making and rapid response. Data is pieces of information; it can be defined as the elements of measurements recorded during data collection. Data quality is a measure of data condition based on factors such as accuracy, completeness, reliability, and whether it’s up-to-date. There is no enough research in Ethiopia that describes the quality of animal health surveillance data reports. Therefore, the objective of the study is to analysis the animal health surveillance data of the woreda and to comment on identified problem. Retrospective case study was conducted in Guchi woreda of Borena zone, Oromia regional state. The district 2021 DOVAR report format was examined for timeliness, correctness, and completeness. To ascertain the reporting rates and quality issues, Microsoft Excel was employed. Using previously created structured interview questions, the woreda's overall data quality and associated problems were evaluated. Based on this study's evaluation of the DOVAR report, 77% of outbreaks were reported in the district last year; the remaining 22.2% of reports were zero reports. Nine reports were examined, and 66.6 % were inaccurate, while 44.4% had a timeliness issue. On the other hand, there is a problem with completeness in 77.7% of the reports. The surveillance data of the woreda have the problem of accuracy, completeness and timeliness. The woreda's goals for gathering surveillance data are well known. However, due to the high data quality issues in their DOVARs, the woreda should establish clear objectives for the data that is required, create a plan for the best way to collect the data, use standardized formats to capture the necessary data, train staff on how to collect accurate and reliable data, and store and retain data.
| Published in | Animal and Veterinary Sciences (Volume 10, Issue 5) |
| DOI | 10.11648/j.avs.20221005.16 |
| Page(s) | 161-169 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Data Quality, Surveillance Data, Accuracy, Completeness, Timeliness
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APA Style
Gerade Abduljami. (2022). Assessment on Animal Health Surveillance Data Quality: The Case Study in Guchi Woreda, Borena Zone, Ethiopia 2022. Animal and Veterinary Sciences, 10(5), 161-169. https://doi.org/10.11648/j.avs.20221005.16
ACS Style
Gerade Abduljami. Assessment on Animal Health Surveillance Data Quality: The Case Study in Guchi Woreda, Borena Zone, Ethiopia 2022. Anim. Vet. Sci. 2022, 10(5), 161-169. doi: 10.11648/j.avs.20221005.16
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Download@article{10.11648/j.avs.20221005.16,
author = {Gerade Abduljami},
title = {Assessment on Animal Health Surveillance Data Quality: The Case Study in Guchi Woreda, Borena Zone, Ethiopia 2022},
journal = {Animal and Veterinary Sciences},
volume = {10},
number = {5},
pages = {161-169},
doi = {10.11648/j.avs.20221005.16},
url = {https://doi.org/10.11648/j.avs.20221005.16},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.avs.20221005.16},
abstract = {High-quality surveillance data provide valid and useful evidence for decision-making and rapid response. Data is pieces of information; it can be defined as the elements of measurements recorded during data collection. Data quality is a measure of data condition based on factors such as accuracy, completeness, reliability, and whether it’s up-to-date. There is no enough research in Ethiopia that describes the quality of animal health surveillance data reports. Therefore, the objective of the study is to analysis the animal health surveillance data of the woreda and to comment on identified problem. Retrospective case study was conducted in Guchi woreda of Borena zone, Oromia regional state. The district 2021 DOVAR report format was examined for timeliness, correctness, and completeness. To ascertain the reporting rates and quality issues, Microsoft Excel was employed. Using previously created structured interview questions, the woreda's overall data quality and associated problems were evaluated. Based on this study's evaluation of the DOVAR report, 77% of outbreaks were reported in the district last year; the remaining 22.2% of reports were zero reports. Nine reports were examined, and 66.6 % were inaccurate, while 44.4% had a timeliness issue. On the other hand, there is a problem with completeness in 77.7% of the reports. The surveillance data of the woreda have the problem of accuracy, completeness and timeliness. The woreda's goals for gathering surveillance data are well known. However, due to the high data quality issues in their DOVARs, the woreda should establish clear objectives for the data that is required, create a plan for the best way to collect the data, use standardized formats to capture the necessary data, train staff on how to collect accurate and reliable data, and store and retain data.},
year = {2022}
}
TY - JOUR T1 - Assessment on Animal Health Surveillance Data Quality: The Case Study in Guchi Woreda, Borena Zone, Ethiopia 2022 AU - Gerade Abduljami Y1 - 2022/10/30 PY - 2022 N1 - https://doi.org/10.11648/j.avs.20221005.16 DO - 10.11648/j.avs.20221005.16 T2 - Animal and Veterinary Sciences JF - Animal and Veterinary Sciences JO - Animal and Veterinary Sciences SP - 161 EP - 169 PB - Science Publishing Group SN - 2328-5850 UR - https://doi.org/10.11648/j.avs.20221005.16 AB - High-quality surveillance data provide valid and useful evidence for decision-making and rapid response. Data is pieces of information; it can be defined as the elements of measurements recorded during data collection. Data quality is a measure of data condition based on factors such as accuracy, completeness, reliability, and whether it’s up-to-date. There is no enough research in Ethiopia that describes the quality of animal health surveillance data reports. Therefore, the objective of the study is to analysis the animal health surveillance data of the woreda and to comment on identified problem. Retrospective case study was conducted in Guchi woreda of Borena zone, Oromia regional state. The district 2021 DOVAR report format was examined for timeliness, correctness, and completeness. To ascertain the reporting rates and quality issues, Microsoft Excel was employed. Using previously created structured interview questions, the woreda's overall data quality and associated problems were evaluated. Based on this study's evaluation of the DOVAR report, 77% of outbreaks were reported in the district last year; the remaining 22.2% of reports were zero reports. Nine reports were examined, and 66.6 % were inaccurate, while 44.4% had a timeliness issue. On the other hand, there is a problem with completeness in 77.7% of the reports. The surveillance data of the woreda have the problem of accuracy, completeness and timeliness. The woreda's goals for gathering surveillance data are well known. However, due to the high data quality issues in their DOVARs, the woreda should establish clear objectives for the data that is required, create a plan for the best way to collect the data, use standardized formats to capture the necessary data, train staff on how to collect accurate and reliable data, and store and retain data. VL - 10 IS - 5 ER -
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