More Timely Response to Outbreaks of Zoonotic Compared to Non‐Zoonotic Diseases in Animals in Tanzania
ABSTRACT Timeliness metrics analysis is a useful approach for tracking speed in actions and identifying gaps during disease outbreaks. There is limited information on the time taken for preventing, controlling and containing disease outbreaks in human and animal populations in Tanzania. We conducted...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-07-01
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| Series: | Veterinary Medicine and Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/vms3.70483 |
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| Summary: | ABSTRACT Timeliness metrics analysis is a useful approach for tracking speed in actions and identifying gaps during disease outbreaks. There is limited information on the time taken for preventing, controlling and containing disease outbreaks in human and animal populations in Tanzania. We conducted timeliness metrics analysis on zoonotic and non‐zoonotic disease outbreaks which occurred between May 2019 and April 2023 in 10 selected districts within four regions located in the Northern (Arusha and Kilimanjaro regions) and Southern Highlands zones (Mbeya and Songwe regions) of Tanzania. Field‐based outbreak milestones for selected zoonotic diseases, namely rabies and anthrax and non‐zoonotic diseases, African swine fever (ASF), contagious caprine pleuropneumonia and Peste des petits ruminants, were recorded. Modified metrics for One Health Surveillance were employed to estimate the time used for disease outbreak detection, notification, verification, risk assessment, laboratory confirmation, inter‐sectoral sharing of information (for zoonotic diseases only), response and public communication. A total of 98 disease outbreaks, of which 63 were zoonotic (64.3%) and 35 were non‐zoonotic (35.7%), were recorded. These outbreaks were distributed across the Northern (68/98) and Southern Highlands (30/98) zones. The time taken to detect zoonotic disease outbreaks was significantly shorter (median = 2 days, range = 1–48 days) than the time taken to detect non‐zoonotic disease outbreaks (median = 3 days, range = 1–40 days) (p = 0.0485). Furthermore, the time taken to detect disease outbreaks in the Northern zone was significantly shorter (median = 2 days, range = 1–48 days) than the time taken in the Southern Highlands zone (median = 7 days, range = 1–40 days) (p = 0.0010). Variation between geographical locations was observed where in the Northern zone, a shorter time was taken to verify (median = 1 day, range = 1–14 days) and to respond (median = 1 day, range = 1–30 days) to disease outbreaks than in the Southern Highlands (verification time: median = 3 days, range = 1–30 days and response time: median = 30 days, range = 1–60 days). Such differences could be due to resource disparities in the two zones and shorter distance to access diagnostic facilities in the Northern zone. This is the first field‐based timeliness metrics analysis study carried out in Tanzania. Findings of this study may be utilised to guide animal and public health interventions for effective and efficient surveillance and control of emerging and re‐emerging infectious diseases. It is recommended that more investment is carried out in emergency preparedness for the timely management of zoonotic and non‐zoonotic diseases in Tanzania. |
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| ISSN: | 2053-1095 |