Ethiopia had the highest number of cattle in Africa as of 2023, nearly ** million heads. United Republic of Tanzania possessed the second-highest bovine animal stock on the continent, with about ** million heads. In 2022, Africa had over *** million heads of cattle, one of the major species raised for livestock farming on the continent.

Table shows maximum infected fractions of cows, peak infection time, and rate at which that maximum is attained for a heterogeneous network and a single infected cow in the Kabale municipality.

The raster dataset consists of a 500 m score grid for dairy processing industry facilities siting, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on sheep dairy production intensification potential, defined using crop production, livestock production systems, and cattle distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, dairy distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Dairy Intensification” * 0.4) + ("Crop Production" * 0.3) + (“Major Cities Accessibility” * 0.2) + (“Population Density” * 0.1)

Abstract

The Uganda Bureau of Statistics conducted the National Livestock Census (NLC) 2021 with an overall goal of providing information on the structure and organization of the livestock sector in Uganda. Specifically, the NLC 2021 provides inter alia a frame for livestock sample surveys; statistics on basic characteristics of livestock, farm infrastructure, farm equipment and machinery as well as aspects of the management of agricultural holdings disaggregated by sex. This information is used as benchmark data to validate and improve the reliability of livestock statistics generated from annual surveys and administrative sources.

The long-term objective of the NLC 2021 was to have information on the structure and organization of the livestock sector in Uganda and more specifically, the census was conducted to: 1. Generate statistics on basic characteristics of livestock, farm infrastructure, farm equipment and machinery; and aspects of the management of agricultural holdings disaggregated by sex. 2. Provide a frame for livestock sample surveys. 3. Provide benchmark data which will be used to validate and improve the reliability of livestock statistics generated from annual surveys and administrative sources. 4. Build national capacity for the development of the livestock sector

Geographic coverage

National coverage

Analysis unit

• Households

Universe

The NLC 2021 enumerated Household-based farms as well as Private Large Scale and Institutional Farms (PLS&IFs) in all the 135 districts of Uganda as of July 2019.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Sampling Frame The Sampling Frame that was used to select the EAs in the non-cattle corridor was the 2014 National Population and Housing Census (NPHC 2014). The NPHC 2014 contained an Agricultural Module where a sampling frame was formed for censuses/surveys. About Four (4.3) million out of the 7.5 million households enumerated during the NPHC 2014 reported that one or more of their members engaged in an agricultural activity as of September 2014.

Sample Size The statistical unit of enumeration both in the cattle and non-cattle corridor was the livestock-keeping households. The total number of Enumeration Areas covered during the livestock census was 32,163 of which, 23,443 EAs about 73% were in the 559 SubCounties of the cattle corridor where complete enumeration was undertaken. Only 8,720 EAs, representing 27 percent were sampled from the 961 Sub-counties of the non-cattle corridor districts.

Sample Design A two-stage stratified cluster sampling method was used for selection of Livestock-keeping households. In the non-cattle corridor, the first stage sampling units were the sub-counties that were selected with certainty. The second stage sampling units were the Enumeration Areas (EAs). Where an EA was selected, all livestock-keeping households were enumerated. In the cattle corridor, all EAs in all Sub-counties (in the case of districts), or Divisions (in the case of Municipalities), were covered through a complete enumeration.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the NLC 2021 were structured questionnaires based on the UNHS and UHIS Model Questionnaires with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household head/holding including sex, age, No. of persons in Housheold, legal status of holding, production systems, livestock populations, and farm infrastructure, equipment and implements, access to veterinary services, land ownership, land tenure systems, ownership of livestock, labour used and sources of water.

All questionnaires and modules are provided as external resources.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of Stata data files

Detailed documentation of the editing of data can be found in the "Data Processing Guidelines" document provided as an external resource.

Response rate

Overall, the NLC 2021 targeted 32,163 EAs and 31,195 EAs were covered constituting a coverage rate of 97 percent. The response rate based on the expected number of households reported in National Population and Housing Census 2014 was 69 percent.

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the NLC 2021 to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Table shows maximum infected fractions of cows, peak infection time, and rate at which that maximum is attained for a homogeneous network.

Cows in different locations in the Kabale District; this data set was derived from the UBOS Statistical Report 2012, Kabale District [24].

In 1800, the population of the region that makes up today's Republic of Uganda was just over two million people. Throughout the 19th century, the population of Uganda would see only modest growth, as increased exposure to the outside world would lead to a series of epidemics afflicting the population, including a devastating outbreak of rinderpest in 1891 killing off much of the region’s cattle, and several outbreaks of smallpox. Uganda’s population would begin to grow more rapidly in the years following the First World War, in part the result of economic growth from wartime agricultural production (unlike neighboring Tanzania, Uganda was spared much of the conflict in East Africa, and as a result saw a significant expansion of cash crop production).

The population of Uganda would continue to grow throughout the remainder of the 20th century, particularly so following the country’s independence from the British Empire in 1962. However, this growth would slow through the 1970s under Idi Amin’s Second Republic of Uganda, which saw real wage and salaries decrease by 90% in less than a decade, and mass expulsions and terror campaigns resulting in a significant number of deaths and refugees throughout the country. Following Idi Amin’s ousting from power in the 1979 Ugandan-Tanzanian War, Uganda’s population has continued to rise exponentially, and in 2020, Uganda is estimated to have a population of approximately 45.7 million.

East Coast fever (ECF) is a fatal sickness affecting cattle populations of eastern, central, and southern Africa. The disease is transmitted by the tick Rhipicephalus appendiculatus, and caused by the protozoan Theileria parva parva, which invades host lymphocytes and promotes their clonal expansion. Importantly, indigenous cattle show tolerance to infection in ECF-endemically stable areas. Here, the putative genetic bases underlying ECF-tolerance were investigated using molecular data and epidemiological information from 823 indigenous cattle from Uganda. Vector distribution and host infection risk were estimated over the study area and subsequently tested as triggers of local adaptation by means of landscape genomics analysis. We identified 41 and seven candidate adaptive loci for tick resistance and infection tolerance, respectively. Among the genes associated with the candidate adaptive loci are PRKG1 and SLA2. PRKG1 was already described as associated with tick resistance in indige...

The East African Shorthorn Zebu (EASZ) cattle are ancient hybrid between Asian zebu × African taurine cattle preferred by local farmers due to their adaptability to the African environment. The genetic controls of these adaptabilities are not clearly understood yet. Here, we genotyped 92 EASZ samples from Kenya (KEASZ) with more than 770,000 SNPs and sequenced the genome of a pool of 10 KEASZ. We observe an even admixed autosomal zebu × taurine genomic structure in the population. A total of 101 and 165 candidate regions of positive selection, based on genome-wide SNP analyses (meta-SS, Rsb, iHS, and ΔAF) and pooled heterozygosity (Hp) full genome sequence analysis, are identified, in which 35 regions are shared between them. A total of 142 functional variants, one novel, have been detected within these regions, in which 30 and 26 were classified as of zebu and African taurine origins, respectively. High density genome-wide SNP analysis of zebu × taurine admixed cattle populations from Uganda and Nigeria show that 25 of these regions are shared between KEASZ and Uganda cattle, and seven regions are shared across the KEASZ, Uganda, and Nigeria cattle. The identification of common candidate regions allows us to fine map 18 regions. These regions intersect with genes and QTL associated with reproduction and environmental stress (e.g., immunity and heat stress) suggesting that the genome of the zebu × taurine admixed cattle has been uniquely selected to maximize hybrid fitness both in terms of reproduction and survivability.

Mycobacterium avium ssp. paratuberculosis (MAP) is the cause of Johne's disease (JD) in a wide range of domestic and wild ruminants. Single-nucleotide polymorphisms (SNPs) in several genes including solute-like carrier 11A1 (SLC11A1), interferon gamma (IFNγ), Toll-like receptor 4 (TLR4), nucleotide-binding oligomerization domain 2 gene (NOD2), and bovine peptidoglycan recognition protein 1 (PGLYRP1) have been implicated in influencing the infection outcome of MAP in cattle. We have carried out a survey in a population of Ankole cattle from three districts in the central region of Uganda including Isingiro, Lyantonde, and Rakai to determine the role played by several SNPs on the above genes in the infection outcome of local cattle in Uganda. Nine hundred fifty-five heads of cattle obtained from 93 herds were tested using ELISA. Thirty-five ELISA-positive cattle and 35 negative herd mates from a total of 955 cattle tested for MAP were genotyped using iPLEX MassARRAY genotyping systems to detect the presence of a total of 13 SNPS in five different genes (SLC11A1, IFNγ, TLR4, NOD2, and PGLYRP1). The cow-level prevalence of MAP infection in Ankole Longhorn cattle in the three districts was 3.98% (35/955), while the herd-level prevalence was 27.9% and within-herd prevalence was 12 ± 1.5% (95% CI = 9.1–14.8%). The genotypes and allele frequencies of the MAP-positive cattle were compared with those of their ELISA-negative herd mates to determine the significance of the polymorphisms. The results showed that SNPs rs109915208, rs110514940, and rs110905610 on SLC11A1, c.480G>A and c.625C>A on PGLYRP1, and c.2021C>T on TLR4 were monomorphic in both seropositive and seronegative cattle and therefore had no influence on the infection outcome. The remaining SNPs studied in the five genes [SLC11A1: rs109614179; TLR4: rs29017188 (c.226G>C), c.2021C>T; NOD2: rs110536091, rs111009394; PGLYRP1: c.102G>C, c.480G>A, c.625C>A; IFNγ: rs110853455] were polymorphic, but their allele and genotype frequencies did not show any significant difference between the seropositive and seronegative cattle. No significant difference was observed for any haplotype at the gene level.

BackgroundBrucellosis is a zoonotic disease with significant public health and economic effects on societies. In Uganda, brucellosis is endemic and a primary contributor in livestock productivity losses. This is more worrisome for populations in the cattle corridor with high reliance on cattle and milk for nutritional value and symbol in social relations and identity. The community’s social construction may affect comprehension of brucellosis hence leading to exposure and increased vulnerability to transmission. Despite brucellosis’ high prevalence in the cattle corridor, little attention has been paid to its social construction. Hence, this study explored the interplay between gender dynamics, vulnerability and social construction of brucellosis transmission, in consideration of the unique socio-cultural context that characterizes cattle corridor populations.MethodsUsing an exploratory qualitative approach, the study was conducted in Nakasongola cattle corridor within three sub counties; Nabiswera, Nakitoma and Wabinyonyi using key informant interviews (KIIs) and focus group discussions (FGDs). Purposive sampling was used to identify participants for the four FGD [8–12] each from a subcounty though one was combined and 15 KIIs. Data were collected using face -to -face interviews with an interview guide that was structured using the Socio Ecological Model of Human Behaviour framework (SEMHB) constructs. Thematic analysis was conducted in NVivo 12 Pro incorporating both deductive (guided by the SEMHB) and inductive approaches (guided by the data).FindingsThe study identified important themes under each SEMHB influence level (Individual, Interpersonal, Community and Societal level). The study indicates that social composition and role distribution are driven by social and cultural expectations and significantly contribute to exposure and vulnerability to infection in the cattle corridor. For instance, it is paramount that women undergoing marriage preparations to be fed on raw milk for a certain period prior to their ceremony to enhance beauty. Also, important to note that use of personal protection to assist births is viewed by the community as opposing cultural norms, creating a perception of detachment from the highly valued cattle. Another noteworthy finding is the level of knowledge on brucellosis in terms of symptoms, transmission route, prevention and treatment at the interpersonal level. Furthermore, findings show practices such as the consumption of raw milk and assisted births, as being rooted in the social cultural norms, hence critical for transmission of brucellosis. At the community and organizational levels, the findings indicate an inadequate level of knowledge sharing and reluctance towards preventive measures as structural factors for the transmission of brucellosis and are ingrained in family and power relations.ConclusionThe findings highlight that the social construction of brucellosis transmission is rooted in gender roles, social- cultural and power structures highlighting the influence of living process and spaces, at the different societal levels. Such complex dynamics play a critical role in determining individuals’ susceptibility to infection as well as transmission potential of the disease-causing agent in cattle keeping communities. The gendered induced vulnerabilities related to the socio-cultural norms and familial roles, also play an important role in the exposure and spill over at the individual, interpersonal and community levels. The insufficient knowledge-sharing and reluctance to adopt preventive measures emerge as structural contributors to the persistence of brucellosis and other emerging zoonoses. These factors, intertwined with family dynamics and power relations, call for targeted interventions that address both individual behaviors and broader socio-cultural and institutional barriers to effective disease management and prevention. Conversely, policies that align with the community’s social construction, gender and context are more likely to be feasible, adopted and sustained by the affected population.

Data were computed out of three minisatellite loci [37]. When host species is different, only subsamples not separated by more than three years were compared.