Peste Des Petits Ruminants in the Middle East: Epidemiological Situation and Status of Control and Eradication Activities after the First Phase of the PPR Global Eradication Program (2017-2021).

Peste des petits ruminants (PPR) is a burdensome viral disease primarily affecting small ruminants, which is currently targeted for eradication by 2030 through the implementation of a Global Control and Eradication Strategy (PPR GCES). The PPR GCES, launched in 2015, has strongly encouraged countries to participate in Regional PPR Roadmaps, designated according to the Food and Agricultural Organization of the United Nations (FAO) and World Organisation for Animal Health (WOAH) regions and epidemiological considerations, with each targeted by dedicated meetings and activities. Following the conclusion of the first phase of the PPR Global Eradication Program (PPR GEP) (2017-2021), the present work focuses on the disease situation and status of the eradication campaign in the fourteen countries of the PPR GCES Middle Eastern Roadmap as well as Egypt. PPR is endemic to or suspected to be present in most of the region, except for Bahrain, which, as of 2021, is preparing to apply for official recognition as being free of PPR. Some substantial shortcomings are observed in surveillance and disease reporting, as well as in the implemented control strategies, most notably vaccination. Since many of these limitations are shared by many of the investigated countries, the international cooperation and harmonization of control efforts appears crucial to making PPR eradication attainable in the Middle East.

Peste des Petits Ruminants in Central and Eastern Asia/West Eurasia: Epidemiological Situation and Status of Control and Eradication Activities after the First Phase of the PPR Global Eradication Programme (2017-2021).

Peste des petits ruminants (PPR) is a highly contagious infectious disease of small ruminants caused by peste des petits ruminants virus (PPRV). PPR poses a significant threat to sheep and goat systems in over 65 endemic countries across Africa, the Middle East and Asia. It is also responsible for devastating outbreaks in susceptible wildlife, threatening biodiversity. For these reasons, PPR is the target of the Global Eradication Programme (PPR GEP), launched in 2016, which is aimed at eradicating the disease by 2030. The end of the first five-year phase of the PPR GEP (2017-2021) provides an ideal opportunity to assess the status of the stepwise control and eradication process. This review analyses 13 countries belonging to Eastern Europe, Transcaucasia, and Central and East Asia. Substantial heterogeneity is apparent in terms of PPR presence and control strategies implemented by different countries. Within this region, one country is officially recognised as PPR-free, seven countries have never reported PPR, and two have had no outbreaks in the last five years. Therefore, there is real potential for countries in this region to move forward in a coordinated manner to secure official PPR freedom status and thus reap the trade and socioeconomic benefits of PPR eradication.

A shift from cattle to camel and goat farming can sustain milk production with lower inputs and emissions in north sub-Saharan Africa's drylands.

Climate change is increasingly putting milk production from cattle-based dairy systems in north sub-Saharan Africa (NSSA) under stress, threatening livelihoods and food security. Here we combine livestock heat stress frequency, dry matter feed production and water accessibility data to understand where environmental changes in NSSA's drylands are jeopardizing cattle milk production. We show that environmental conditions worsened for ∼17% of the study area. Increasing goat and camel populations by ∼14% (∼7.7 million) and ∼10% (∼1.2 million), respectively, while reducing the dairy cattle population by ∼24% (∼5.9 million), could result in ∼0.14 Mt (+5.7%) higher milk production, lower water (-1,683.6 million m3, -15.3%) and feed resource (-404.3 Mt, -11.2%) demand-and lower dairy emissions by ∼1,224.6 MtCO2e (-7.9%). Shifting herd composition from cattle towards the inclusion of, or replacement with, goats and camels can secure milk production and support NSSA's dairy production resilience against climate change.

Using Random Forest to Improve the Downscaling of Global Livestock Census Data.

Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the livestock sector. This has been the major motivation behind the development of the Gridded Livestock of the World (GLW) database, which has been extensively used since its first publication in 2007. The database relies on a downscaling methodology whereby census counts of animals in sub-national administrative units are redistributed at the level of grid cells as a function of a series of spatial covariates. The recent upgrade of GLW1 to GLW2 involved automating the processing, improvement of input data, and downscaling at a spatial resolution of 1 km per cell (5 km per cell in the earlier version). The underlying statistical methodology, however, remained unchanged. In this paper, we evaluate new methods to downscale census data with a higher accuracy and increased processing efficiency. Two main factors were evaluated, based on sample census datasets of cattle in Africa and chickens in Asia. First, we implemented and evaluated Random Forest models (RF) instead of stratified regressions. Second, we investigated whether models that predicted the number of animals per rural person (per capita) could provide better downscaled estimates than the previous approach that predicted absolute densities (animals per km2). RF models consistently provided better predictions than the stratified regressions for both continents and species. The benefit of per capita over absolute density models varied according to the species and continent. In addition, different technical options were evaluated to reduce the processing time while maintaining their predictive power. Future GLW runs (GLW 3.0) will apply the new RF methodology with optimized modelling options. The potential benefit of per capita models will need to be further investigated with a better distinction between rural and agricultural populations.

Income Disparities and the Global Distribution of Intensively Farmed Chicken and Pigs.

The rapid transformation of the livestock sector in recent decades brought concerns on its impact on greenhouse gas emissions, disruptions to nitrogen and phosphorous cycles and on land use change, particularly deforestation for production of feed crops. Animal and human health are increasingly interlinked through emerging infectious diseases, zoonoses, and antimicrobial resistance. In many developing countries, the rapidity of change has also had social impacts with increased risk of marginalisation of smallholder farmers. However, both the impacts and benefits of livestock farming often differ between extensive (backyard farming mostly for home-consumption) and intensive, commercial production systems (larger herd or flock size, higher investments in inputs, a tendency towards market-orientation). A density of 10,000 chickens per km2 has different environmental, epidemiological and societal implications if these birds are raised by 1,000 individual households or in a single industrial unit. Here, we introduce a novel relationship that links the national proportion of extensively raised animals to the gross domestic product (GDP) per capita (in purchasing power parity). This relationship is modelled and used together with the global distribution of rural population to disaggregate existing 10 km resolution global maps of chicken and pig distributions into extensive and intensive systems. Our results highlight countries and regions where extensive and intensive chicken and pig production systems are most important. We discuss the sources of uncertainties, the modelling assumptions and ways in which this approach could be developed to forecast future trajectories of intensification.

Mapping the global distribution of livestock.

Livestock contributes directly to the livelihoods and food security of almost a billion people and affects the diet and health of many more. With estimated standing populations of 1.43 billion cattle, 1.87 billion sheep and goats, 0.98 billion pigs, and 19.60 billion chickens, reliable and accessible information on the distribution and abundance of livestock is needed for a many reasons. These include analyses of the social and economic aspects of the livestock sector; the environmental impacts of livestock such as the production and management of waste, greenhouse gas emissions and livestock-related land-use change; and large-scale public health and epidemiological investigations. The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 5×5 km at the equator). Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analytical procedure has been revised and extended to include a more systematic assessment of model accuracy and the representation of uncertainties associated with the predictions. This paper describes the current approach in detail and presents new global distribution maps at 1 km resolution for cattle, pigs and chickens, and a partial distribution map for ducks. These digital layers are made publically available via the Livestock Geo-Wiki (http://www.livestock.geo-wiki.org), as will be the maps of other livestock types as they are produced.