Tick-borne pathogens, including Crimean-Congo haemorrhagic fever virus, at livestock markets and slaughterhouses in western Kenya

Abstract

Vectors of emerging infectious diseases have expanded their distributional ranges in recent decades due to increased global travel, trade connectivity and climate change. Transboundary range shifts, arising from the continuous movement of humans and livestock across borders, are of particular disease control concern. Several tick-borne diseases are known to circulate between eastern Uganda and the western counties of Kenya, with one fatal case of Crimean-Congo haemorrhagic fever (CCHF) reported in 2000 in western Kenya. Recent reports of CCHF in Uganda have highlighted the risk of cross-border disease translocation and the importance of establishing inter-epidemic, early warning systems to detect possible outbreaks. We therefore carried out surveillance of tick-borne zoonotic pathogens at livestock markets and slaughterhouses in three counties of western Kenya that neighbour Uganda. Ticks and other ectoparasites were collected from livestock and identified using morphological keys. The two most frequently sampled tick species were Rhipicephalus decoloratus (35%) and Amblyomma variegatum (30%); Ctenocephalides felis fleas and Haematopinus suis lice were also present. In total, 486 ticks, lice and fleas were screened for pathogen presence using established molecular workflows incorporating high-resolution melting analysis and identified through sequencing of PCR products. We detected CCHF virus in Rh. decoloratus and Rhipicephalus sp. cattle ticks, and 82 of 96 pools of Am. variegatum were positive for Rickettsia africae. Apicomplexan protozoa and bacteria of veterinary importance, such as Theileria parva, Babesia bigemina and Anaplasma marginale, were primarily detected in rhipicephaline ticks. Our findings show the presence of several pathogens of public health and veterinary importance in ticks from livestock at livestock markets and slaughterhouses in western Kenya. Confirmation of CCHF virus, a Nairovirus that causes haemorrhagic fever with a high case fatality rate in humans, highlights the risk of under-diagnosed zoonotic diseases and calls for continuous surveillance and the development of preventative measures.

Keywords: Nairovirus; Rhipicephalus; Rickettsia; East Africa; Zoonoses; emerging infectious disease.

FIGURE 1

Map of the three neighbouring counties of Busia, Bungoma and Kakamega showing the livestock markets and slaughterhouses from which arthropod samples were collected [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 2

Melt rate profiles. (a) CCHF virus RdRp amplicons, (b) Theileria/Babesia 18S rRNA amplicons, (c) Anaplasma 16SrRNA amplicons and (d) Rickettsia/Coxiella 16S rRNA amplicons. PC, positive control; Ra, Rh. appendiculatus; Rd, Rh. decoloratus [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 3

Maximum likelihood phylogeny of Crimean‐Congo haemorrhagic fever virus strains inferred from 34 aligned 434‐nt segments of the L‐segment (RdRp gene). GenBank accession numbers and country of origin are indicated for each sequence. Accession numbers for sequences from this from this study are in bold. Isolation sources in applicable sequences are also highlighted. Bootstrap values at the major nodes are of percentage agreement among 1,000 replicates. The branch length scale represents substitutions per site. The gaps indicated in the branches to the Nairobi sheep disease out‐group represent 0.8 substitutions per site. The sequences from this study fall into African genotype II as indicated by the vertical bars

FIGURE 4

Maximum likelihood phylogeny of apicomplexan protozoa inferred from 32 aligned 502‐nt segments of the 18S rRNA gene. GenBank accession numbers and isolation sources are indicated for each sequence. Accession numbers for sequences from this study are in bold. Bootstrap values at the major nodes are of percentage agreement among 1,000 replicates. The branch length scale represents substitutions per site

FIGURE 5

Maximum likelihood phylogeny of tick‐associated Coxiella endosymbionts inferred from 33 aligned 279‐nt segments of the 16S rRNA gene. GenBank accession numbers and tick species of origin are indicated for each sequence. Accession numbers for sequences from this study are in bold Bootstrap values at the major nodes are of percentage agreement among 1,000 replicates. The branch length scale represents substitutions per site. The gaps indicated in the branches to the L. pneumophila out‐group represent 0.12 substitutions per site. Sequences from this study and those from GenBank fall into three genotypes: A = Coxiella burnetii; B = Coxiella endosymbionts of Amblyomma spp. ticks; C = Coxiella endosymbionts of Rhipicephalus spp. ticks; D = Coxiella endosymbionts of Dermacentor and Amblyomma spp. ticks