Towards an integrated animal health surveillance system in Tanzania: making better use of existing and potential data sources for early warning surveillance
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
BMC Veterinary Research
Abstract
Background: Effective animal health surveillance systems require reliable, high-quality, and timely data for
decision making. In Tanzania, the animal health surveillance system has been relying on a few data sources, which
suffer from delays in reporting, underreporting, and high cost of data collection and transmission. The integration
of data from multiple sources can enhance early detection and response to animal diseases and facilitate the early
control of outbreaks. This study aimed to identify and assess existing and potential data sources for the animal
health surveillance system in Tanzania and how they can be better used for early warning surveillance. The study
used a mixed-method design to identify and assess data sources. Data were collected through document reviews,
internet search, cross-sectional survey, key informant interviews, site visits, and non-participant observation. The
assessment was done using pre-defined criteria.
Results: A total of 13 data sources were identified and assessed. Most surveillance data came from livestock
farmers, slaughter facilities, and livestock markets; while animal dip sites were the least used sources. Commercial
farms and veterinary shops, electronic surveillance tools like AfyaData and Event Mobile Application (EMA-i) and
information systems such as the Tanzania National Livestock Identification and Traceability System (TANLITS) and
Agricultural Routine Data System (ARDS) show potential to generate relevant data for the national animal health
surveillance system. The common variables found across most sources were: the name of the place (12/13), animal
type/species (12/13), syndromes (10/13) and number of affected animals (8/13). The majority of the sources had
good surveillance data contents and were accessible with medium to maximum spatial coverage. However, there
was significant variation in terms of data frequency, accuracy and cost. There were limited integration and
coordination of data flow from the identified sources with minimum to non-existing automated data entry and
transmission. Conclusion: The study demonstrated how the available data sources have great potential for early warning
surveillance in Tanzania. Both existing and potential data sources had complementary strengths and weaknesses; a
multi-source surveillance system would be best placed to harness these different strengths.
Description
Research Article
Keywords
Surveillance, Animal health, Data source, Integration, Early warning, Tanzania