Animal movement in a pastoralist population in the Maasai Mara Ecosystem in Kenya and implications for pathogen spread and control

Analyzing the intrastate and interstate swine movement network in the United States

Identifying and restricting animal movements is a common approach used to mitigate the spread of diseases between premises in livestock systems. Therefore, it is essential to uncover between-premises movement dynamics, including shipment distances and network-based control strategies. Here, we analyzed three years of between-premises pig movements, which include 197,022 unique animal shipments, 3973 premises, and 391,625,374 pigs shipped across 20 U.S. states. We constructed unweighted, directed, temporal networks at 180-day intervals to calculate premises-to-premises movement distances, the size of connected components, network loyalty, and degree distributions, and, based on the out-going contact chains, identified network-based control actions. Our results show that the median distance between premises pig movements was 74.37 km, with median intrastate and interstate movements of 52.71 km and 328.76 km, respectively. On average, 2842 premises were connected via 6705 edges, resulting in a weak giant connected component that included 91 % of the premises. The premises-level network exhibited loyalty, with a median of 0.65 (IQR: 0.45 - 0.77). Results highlight the effectiveness of node targeting to reduce the risk of disease spread; we demonstrated that targeting 25 % of farms with the highest degree or betweenness limited spread to 1.23 % and 1.7 % of premises, respectively. While there is no complete shipment data for the entire U.S., our multi-state movement analysis demonstrated the value and the needs of such data for enhancing the design and implementation of proactive- disease control tactics.

Prioritization of livestock diseases by pastoralists in Oloitoktok Sub County, Kajiado County, Kenya

INTRODUCTION

Livestock diseases are a big challenge for the livelihood of pastoralists in sub-Saharan Africa because they reduce livestock productivity and increase mortality. Based on the literature available there is limited understanding on how pastoralists prioritize these diseases in the context of their culture, ecosystems and livelihoods. A study was conducted to provide insights on lay prioritization of animal diseases by pastoralists in Kenya.

METHODOLOGY

A qualitative study was undertaken between March and July 2021. Thirty in-depth interviews and six focus group discussions (FGDs) were conducted with community members to explore community attitudes on livestock diseases prioritization. Male and female livestock keepers were purposively selected and interviewed and they were all long-term residents of the area. Fourteen key informant interviews (KIIs) were conducted with professionals from different key sectors to provide detailed stakeholder perspectives on livestock diseases. The interviews were analyzed thematically using the QSR Nvivo software to identify the emerging themes related to the study objectives.

RESULTS

The pastoralists prioritized livestock diseases based on effect on their economic wellbeing, cultural values and utilization of ecosystem services. There were gender variabilities in how diseases were prioritized among the pastoralists. Men cited high priority diseases as foot and mouth disease and contagious bovine pleuropneumonia due to their regular occurrence and effect on livelihood. Notably, women regarded coenuruses as very important because it affected sheep and goats with a high mortality rate and lumpy skin disease because it rendered the meat from the carcasses inedible. Malignant catarrhal fever and trypanosomiasis were noted as some of the common diseases in the livestock-wildlife interface but not cited as priority diseases. Challenges related to disease control in pastoralist contexts exist including limited access to livestock treatment services, inadequate information on disease impact and complex environmental factors.

CONCLUSION

This study sheds light on the body of knowledge in Kenya regarding livestock diseases and their prioritization by livestock keepers. This could aid in the development of a common disease control framework and prioritization at the local level which would take into consideration the dynamic socio-cultural, ecological, livelihood and economic contexts of the communities.

Analysis of patterns of livestock movements in the Cattle Corridor of Uganda for risk-based surveillance of infectious diseases

Introduction

The knowledge of animal movements is key to formulating strategic animal disease control policies and carrying out targeted surveillance. This study describes the characteristics of district-level cattle, small ruminant, and pig trade networks in the Cattle Corridor of Uganda between 2019 and 2021.

Methodology

The data for the study was extracted from 7,043 animal movement permits (AMPs) obtained from the Ministry of Agriculture, Animal Industry and Fisheries (MAAIF) of Uganda. Most of the data was on cattle (87.2%), followed by small ruminants (11.2%) and pigs (1.6%). Two types of networks representing animal shipments between districts were created for each species based on monthly (n = 30) and seasonal (n = 10) temporal windows. Measures of centrality and cohesiveness were computed for all the temporal windows and our analysis identified the most central districts in the networks.

Results

The median in-degree for monthly networks ranged from 0-3 for cattle, 0-1 for small ruminants and 0-1 for pigs. The highest median out-degrees for cattle, small ruminant and pig monthly networks were observed in Lira, Oyam and Butambala districts, respectively. Unlike the pig networks, the cattle and small ruminant networks were found to be of small-world and free-scale topologies.

Discussion

The cattle and small ruminant trade movement networks were also found to be highly connected, which could facilitate quick spread of infectious animal diseases across these networks. The findings from this study highlighted the significance of characterizing animal movement networks to inform surveillance, early detection, and subsequent control of infectious animal disease outbreaks.

Factors influencing usage of antimicrobial drugs among pastoralists in Kenya

Agricultural use of antimicrobials in food animal production may contribute to the global emergence of antimicrobial resistance (AMR). However, considerable gaps exist in research on the use of antimicrobial drugs (AMDs) in food animals in small-scale production systems in low- and middle-income countries, despite the minimal regulation of antimicrobials in such regions. The aim of this study was to identify factors that may influence AMD use in livestock among pastoral communities in Kenya. We collected data related to household and herd demographics, herd health, and herd management from 55 households in the Maasai Mara ecosystem, Kenya, between 2018 and 2019. We used multi-model logistic regression inference (supervised machine learning) to ascertain trends in AMD use within these households. AMD use in cattle was significantly associated with AMD use in sheep and goats (p = 0.05), implying that decisions regarding AMD use in cattle or sheep and goats were interdependent. AMD use in sheep and goats was negatively associated with vaccination against the foot and mouth disease (FMD) virus in cattle (OR = 0.06, 95% CI 0.01-0.67, p = 0.02). Less AMD use was observed for vaccine-preventable diseases like contagious ecthyma when households had access to state veterinarians (OR = 0.06, p = 0.05, 95% CI 0.004-0.96). Overall, decisions to use AMDs were associated with vaccine usage, occurrence of respiratory diseases, and access to animal health advice. This hypothesis-generating study suggests that applying community-centric methods may be necessary to understand the use of AMDs in pastoral communities.

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.

Livestock Presence Influences the Seroprevalence of Crimean Congo Hemorrhagic Fever Virus on Sympatric Wildlife in Kenya

Crimean Congo Hemorrhagic Fever (CCHF) is an emerging tick-borne zoonotic viral disease with the potential of causing public health emergencies. However, less is known about the role of wildlife and livestock in spreading the virus. Therefore, we aimed to assess how the interactions between African buffalo (Syncerus caffer) and cattle may influence the seroprevalence of CCHF across livestock-wildlife management systems in Kenya. The study included archived sera samples from buffalo and cattle from wildlife only habitats (Lake Nakuru National Park and Solio conservancy), open wildlife-livestock integrated habitats (Maasai Mara ecosystem and Meru National Park), and closed wildlife-livestock habitats (Ol Pejeta Conservancy) in Kenya. We analyzed 191 buffalo and 139 cattle sera using IDvet multispecies, double-antigen IgG enzyme-linked immunosorbent assay (ELISA). The seroprevalence toward Crimean Congo hemorrhagic fever virus (CCHFV) was significantly higher for buffalo compared to cattle (75.3% and 28.1%, respectively, p < 0.001). We obtained the highest seroprevalence among buffalo of 92.1% in closed wildlife only systems compared to 28.8% and 46.1% prevalence in closed-integrated and open-integrated systems, respectively. The regression coefficients were all negative for cattle compared to buffalo in both closed-integrated and open-integrated compared to wildlife only system. Our results show that CCHFV circulates among the diverse animal community in Kenya in spatially disconnected foci. The habitat overlap between cattle and buffalo makes cattle a "bridge species" or superspreader host for CCHFV and increases transmission risks to humans. The effect of animal management system on prevalence is depended on tick control on the cattle and not the animal per se. We conclude that buffalo, a host with a longer life span than livestock, is a reservoir and may serve as a sentinel population for longitudinal surveillance of CCHFV.