Table 4 Descriptive summary of strengths and weakness of each data source
Data source | Strengths | Weaknesses |
|---|---|---|
Livestock farmers | Early warning for diseases with clear clinical signs Easy case detection due to high coverage | Not all farmers report the disease events due to factors such as the negative consequence of reporting or the value of the animal. Diseases with subclinical signs may not be reported. |
Slaughter facilities | A constant supply of surveillance data because of high slaughtering frequency It is easy to collect specimens for laboratory diagnosis. Data collection is less costly. | Poor infrastructures such as lack of lairage areas (holding pens) hence making it difficult for ante-mortem inspection. The collected data is not directly sent to the Ministry of Livestock and Fisheries; instead, they are sent to the Ministry of Agriculture and Food Security through ARDS. |
Animal dip sites | A large number of animals convened at one place during dipping It is easy for visual inspection and screening. It is less costly because data can be collected while waiting for dipping. High coverage because they are found all over the country | Not all farmers bring their livestock to the public dip tanks. Diseases with subclinical signs may not be reported. |
Livestock markets | It is easy for visual inspection and screening. They bring a large number of animals from different places weekly or monthly. It is less costly because animals can be screened before entering the auction bay. | Screening of animals wasn’t consistency. Conflict of interest between surveillance and revenue collection at the markets A limited number of human resources for screening and visual inspection |
Zoo-sanitary checkpoints | Data are readily available because every livestock consignment has to be pass-through identified checkpoints en route their destinations. | Incomplete data in some of the reports Most of the checkpoints are human resource-constrained No coordinated tracking system for the consignments in designated routes |
Veterinary shops | They serve a large number of livestock farmers per month. They enquire symptoms and animal health management. High coverage because there is at least one shop in every ward | They are not well regulated. They only keep sales records and not about symptoms. |
Commercial livestock farms | They have organized record keeping. | They only report notifiable diseases. |
SILAB | The system is automated from sample collection to test report. High coverage as it operates in entire national laboratory network in the country | Data are not linked to the Ministry of Livestock and Fisheries except for notifiable diseases. The server is not hosted in the country hence make it challenging to customize variables. Sample processing is not free; hence not many people take samples for testing. |
TANLITS | It keeps the register of all livestock in the country for identification and tracking. Dairy cattle have unique IDs. The system is flexible to accommodate more variables. GPS embedded features. | Groups identification stops at the village level hence makes it difficult to trace individual animals. Requires regular updates of the shapefiles due to constant changes in administrative boundaries. |
Agricultural Routine Data system (ARDS) | Data collection is coordinated from lower to ministry level. Data are submitted monthly. | Data collection and transmission is still manual hence take a lot of time and prone to human errors. The collected data are not linked to the Ministry of Livestock and Fisheries. Data submission rate is still low |
AfyaData database | Near real-time data transmission GPS embedded features Collects syndromic data Covers both animal and human health data Point of capture is at the community level. | Requires smart-phone technologies and must be connected to internet services |
EMA-I database | Near real-time data transmission GPS embedded features Collects case-based data Data verification at various levels | It only records presumptive diagnosis; hence there are chances of missing new symptoms. Requires smart-phone technologies and must be connected to internet services The server is not hosted in the country; therefore, it may not be flexible to make changes in the variables. |
TAWIRI | A well-coordinated sample collection system | Data collection is expensive and not regular. Only notifiable diseases are sent to DVS |