dataset

The Effect of Passive Surveillance Training on Animal Health Parameters, Northern Ethiopia

Conducting a proof-of-concept research activity involving enhancement of awareness regarding recognition, reporting, and treatment of public and private good animal diseases 

The data asset for "The Effect of Passive Surveillance Training on Animal Health Parameters, Northern Ethiopia" project consists of two datasets: 1) training evaluation and 2) follow-up interview data.

The training evaluation dataset contains the pre-training and post-training test responses for livestock producers and veterinarians in the Tigray region of Ethiopia during the spring of 2017. It was used to evaluate the learning that occurred. The evaluation was given prior to and post training on transboundary and zoonotic disease presentation and reporting in an effort to evaluate educational interventions in reporting of nationally notifiable diseases.

The follow-up interview dataset was collected during the winter/spring of 2018 to learn more about the impacts of disease recognition training to livestock producers and veterinarians one year following the training. Four villages in one woreda (district) in the Tigray region were selected by convenience. Two villages had received the training and two had not. Sampling by convenience, producers and veterinarians were asked questions guided by the attached questionnaire about if they trained others, reported diseases, and what incentives they thought would encourage reporting. Producers were livestock producers. Veterinarians included veterinary technicians and veterinarians (private and public).

This work was funded and supported by the United States Agency for International Development through the Feed the Future Innovation Lab for Livestock Systems (University of Florida), and was done by colleagues at Mekelle University (Tigray Ethiopia), Cornell University (Ithaca, NY), and the University of Georgia (Athens, GA).

Datasets are available from USAID

Visit the project website for further details

 


Header photo: USAID Flickr, Photo by Antonio Fiorente (source)