A streamlined tool for rural household surveys – Q&A with Jim Hammond on RHoMIS – the Rural Household Multi-Indicator Survey

Interviewed by Vanessa Meadu

There are great opportunities to improve the process of gathering information from farming households, particularly in Low and Middle-Income countries where development projects depend on solid data for their success, and existing data resources are scarce.

Enter RHoMIS – the Rural Household Multi-Indicator Survey, which aims to reduce the costs, time requirements and reporting burdens for those who carry out household surveys. The development team have built and used a bank of survey questions based on internationally recognised indicators, covering all aspects of farming systems, including livestock. The database contains a wealth of information that may unlock important solutions to livestock challenges.

We spoke with Jim Hammond, a scientist based at the International Livestock Research Institute (ILRI), who co-leads the RHoMIS team, about how RHoMIS could help close livestock data gaps and uncover new insights.

Vanessa Meadu: How can RHoMIS help improve the reliability of data on livestock and rural livelihoods in Low and Middle-Income Countries?

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Monitor, learn, evaluate: Tracking the impact of livestock development projects

Projects will generate data and insights on progress and impacts

by Vanessa Meadu, Gareth Salmon, Louise Donnison and Karen Smyth

Across Low and Middle-Income Countries, organisations are working to improve livestock health and productivity so livestock keepers can find a pathway out of poverty. Ongoing monitoring, learning and evaluation (MLE) is critical to help project implementers and their funders understand how they are progressing towards desired impacts. But selecting the right indicators and collecting relevant data is an enormous challenge, requiring expertise, and staff time. Done poorly, MLE can lead to incomplete or incorrect conclusions, and be a waste of time. If done well, it can help project managers gain valuable insights for their business, and give funders a better sense of portfolio impact.

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Consultancy opportunity: Modelling Intervention Impacts

The Supporting Evidence-based Interventions (SEBI) initiative, based at the University of Edinburgh, aims to boost the livelihoods of smallholder farmers by delivering evidence-based technologies and interventions that offer sustainable solutions to the livestock production challenges they face.

SEBI is seeking a consultant who can model what actions would be necessary to reduce national ruminant livestock mortality rates by 10-15% (compared to a 2010 baseline reference point), in Ethiopia, Nigeria and Tanzania by 2020.

Deadline for proposals: 12 July 2019

Prospective applicants are invited to contact Professor Andy Peters for an informal discussion about the project.

Header image credit: Z Sewunet ILRI (source)

LiveGAPS team release nutrient production app

by Jeda Palmer, CSIRO

The LiveGAPS team have released a new app to compare nutrient production of livestock by farm size for Tanzania, Nigeria and Ethiopia.

With this app, you can visualise the quantity of different nutrients, for example protein, that is produced by livestock from farms of different sizes.

The data shows that small farms (<20 ha) produce the majority of protein for Tanzania, Nigeria and Ethiopia, with very small farms (<2 ha) contributing a considerable amount of protein.

Check out the nutrient production app on the LiveGAPS website.  

LiveGAPS is led by the Global Food and Nutrition Security team at Australia’s Commonwealth Scientific and Industrial Research Organisation (CSIRO). The project aims to identify ways to maximise yields in livestock systems for poverty alleviation, global food security and sustainability, by estimating the gap between actual and potential productivity of livestock. This will be achieved by using new information from surveys and livestock monitoring systems to develop livestock and household simulation models


Jeda Palmer is a research technician in the CSIRO Global Food and Nutrition group, based in Brisbane, Australia.

Photo credit: Jeda Palmer (CSIRO)

New study uncovers source of mystery neurological disease devastating Tanzanian sheep and goats

by Vanessa Meadu, SEBI

Pastoralist livestock keepers in Tanzania knew for some time that their sheep and goats were succumbing in large numbers to a neurological disease known locally as ormilo, but until recently this threat had gone largely unnoticed by the scientific community and the veterinary services. Now, researchers, from the University of Glasgow’s Institute of Biodiversity, Animal Health and Comparative Medicine (IBAHCM) and the Nelson Mandela African Institution of Science and Technology (NM-AIST), have identified the culprit as the dog tapeworm Taenia multiceps, opening the door for potential solutions.

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Livestock data community zeroes in on big challenges

Report back from LD4D meeting, 28-30 November

In November 2018 the Livestock Data for Decisions (LD4D) Community of Practice met in Hanoi, Vietnam, to discuss big questions in the livestock data sphere, assess progress to date on collaborative working groups, and map out next steps.

Meeting documentation

Access all presentation and session recordings

Download hi-res group photo

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Big Data approaches offer hope for improved livestock analysis

By Louise Donnison, Karen Smyth and Vanessa Meadu

LD4D members report back from the CGIAR Platform for Big Data in Agriculture Convention, which took place 3-5 October in Nairobi, Kenya.

How can data-driven approaches improve the sustainability and resilience of food systems? And can these approaches be successfully applied in the livestock sector? In October, members of the LD4D community met in Nairobi to participate in the CGIAR Platform for Big Data in Agriculture Convention, which brought together agriculture and data scientists from around the world to share their innovative tools and approaches. Due to its unique role in bringing together livestock data producers and users, LD4D also acts as the CGIAR’s Big Data in Agriculture livestock data community of practice. The convention presented plenty of ideas which could offer inspiration to the LD4D community. Read more