Vehicular Livestock Mobility in West Africa: Seasonal Traffic Flows of Cattle, Sheep, and Goats across Bamako

Feed balances for ruminant livestock: gridded estimates for data-constrained regions

Demand for animal-source foods and livestock feed are forecast to increase across sub-Saharan Africa. In this context, there is a need to estimate the availability of livestock feed to support decision-making at local, sub-national and national levels. In this study, we assess feed balances for ruminant livestock in Ethiopia and Burkina Faso. Feed availability was estimated using remotely sensed products and detailed feed composition data. Feed requirements were estimated for maintenance, growth, lactation, gestation and locomotion using a data-intensive model. Biomass available as animal feed was estimated to be 8.6 tonnes of DM per hectare in the Ethiopian highlands and midlands, 3.2 tonnes DM per hectare in the Ethiopian lowlands, 2.9 tonnes DM per hectare in Burkina Faso's Sudanian agro-ecological zone and 1.0 tonne DM per hectare in the Sahel. The energy requirements of lactating cows were estimated to be 62.1 Megajoules (MJs) per animal per day in the Ethiopian highlands and midlands, 62.7 MJ in the Ethiopian lowlands, 88.5 MJ in Burkina Faso's Sudanian agro-ecological zone and 53.1 MJ per animal per day in the Sahel. Feed scarcity hotspots are most prominently located in the Ethiopian highlands and the Sahelian agro-ecological zone of Burkina Faso. Demand-side policy and investment initiatives can address hotspots by influencing herd sizes, nutritional requirements and herd mobility. Supply-side policy and investment initiatives can secure existing feed resources, develop new sources of feed and incentivise trade in feed resources. Improving feed balances will be of value to decision-makers with the aims of optimising livestock productivity, minimising exposure to climatic shocks and minimising greenhouse gas emission intensity.

A spatio-temporal dataset on food flows for four West African cities

Gaining insight into the food sourcing practices of cities is important to understand their resilience to climate change, economic crisis, as well as pandemics affecting food supply and security. To fill existing knowledge gaps in this area food flow data were collected in four West African cities - Bamako (Mali), Bamenda (Cameroon), Ouagadougou (Burkina Faso), and Tamale (Ghana). The data cover, depending on the city, road, rail, boat, and air traffic. Surveys were conducted for one week on average during the peak harvest, lean, and rainy seasons, resulting in a dataset of over 100,000 entries for 46 unprocessed food commodities. The data collected includes information on the key types of transportation used, quantity, source, and destination of the food flows. The data were used to delineate urban foodsheds and to identify city-specific factors constraining rural-urban linkages. The data can also be employed to inform academic and policy discussions on urban food system sustainability, to validate other datasets, and to plan humanitarian aid and food security interventions.

Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions

Infectious diseases in livestock are well-known to infect multiple hosts and persist through a combination of within- and between-host transmission pathways. Uncertainty remains about the epidemic dynamics of diseases being introduced on farms with more than one susceptible host species. Here, we describe multi-host contact networks and elucidate the potential of disease spread through farms with multiple hosts. Four years of between-farm animal movement among all farms of a Brazilian state were described through a static and monthly snapshot of network representations. We developed a stochastic multilevel model to simulate scenarios in which infection was seeded into single host and multi-host farms to quantify disease spread potential, and simulate network-based control actions used to evaluate the reduction of secondarily infected farms. We showed that the swine network was more connected than cattle and small ruminants in both the static and monthly snapshots. The small ruminant network was highly fragmented, however, contributed to interconnecting farms, with other hosts acting as intermediaries throughout the networks. When a single host was initially infected, secondary infections were observed across farms with all other species. Our stochastic multi-host model demonstrated that targeting the top 3.25% of the farms ranked by degree reduced the number of secondarily infected farms. The results of the simulation highlight the importance of considering multi-host dynamics and contact networks while designing surveillance and preparedness control strategies against pathogens known to infect multiple species.