Pooled prevalence, species diversity, and risk factors of ixodid ticks in Ethiopian domestic animals: A systematic review and meta-analysis

Abstract

Ixodid ticks are a significant global threat to animal health and production. They also play a crucial role in transmitting zoonotic and veterinary pathogens that affect both animals and humans. In Ethiopia, widespread grazing practices contribute to high levels of tick infestations among domestic animals. This systematic review and meta-analysis aimed to gather national evidence on the prevalence, species diversity, distribution, and risk factors of ixodid ticks in Ethiopian domestic animals. To achieve this, we conducted a thorough search of peer-reviewed and grey literature across multiple electronic databases and institutional repositories published during 2004–2025. We screened and assessed studies on ixodid tick infestations in Ethiopian domestic animals based on predefined quality criteria. Out of 5310 records retrieved, 173 studies involving 91,520 animals (50,668 infested) met the criteria for inclusion. The overall national tick infestation prevalence was 55.0% (95% CI: 50.0–59.9%), with significant variations across different regions, ranging from 3.2% to 100%. There was also considerable variability among different host species, regions, and sampling subgroups (I² > 83.0%, P ≤ 0.013). Thirty-five ixodid tick species were reported, mainly from the genera Rhipicephalus (16 species) and Hyalomma (10 species). Cattle showed the highest species richness, accounting for 88.6% of the tick diversity recorded. The most prevalent species included Amblyomma cohaerens, Amblyomma variegatum, Rhipicephalus decoloratus, and Rhipicephalus pulchellus. Geographical location and host species significantly contributed to the variability observed in various tick species (P < 0.05). Tick infestation was mostly linked to host factors, such as poor body condition, older age, and female sex. Lower elevations, the wet season, and extensive management systems all significantly affected tick infestation (pooled odds ratio, pOR ≥ 1.34). Many zoonotic bacterial and protozoan pathogens were found in the most frequently encountered ixodid tick species, raising potential risks for humans. In conclusion, cattle and camels serve as important hosts for various ixodid tick species. The greatest risk of infestation occurred in the humid lowlands and mid-highlands of southeastern, western, and southwestern Ethiopia. These findings highlight the need for integrated, risk-based, ecoregional tick management strategies that consider the complex interactions among ticks, hosts, and environmental factors.

Graphical abstract

Highlights

• •Review covering 173 studies on ixodid ticks on domestic animals in Ethiopia published from 2004 to 2025.
• •Thirty-five ixodid tick species of four genera were reported; the overall pooled prevalence was 55.0%.
• •The most prevalent species were Amblyomma cohaerens, A. variegatum, Rhipicephalus pulchellus, and R. decoloratus.
• •Tick infestation was mostly linked to host factors, such as poor body condition, older age, and female sex.
• •Higher infestation occurred in lowlands, during the wet season, and in extensive management systems.

1. Background

Parasitic infestations caused by ectoparasites, including ticks, mites, lice, fleas, and biting flies, pose significant threats to animal health, welfare, and livestock productivity, with additional implications for humans (Kaminsky and Mäser, 2025; Tilahun et al., 2025). Among these, ticks of the families Ixodidae and Argasidae are major vectors of pathogens of medical and veterinary importance (Guglielmone, 2010; Walker et al., 2014; Petney et al., 2019; Onyiche and MacLeod, 2023). In tropical and subtropical regions, infestations with ixodid ticks may result in anaemia, immunosuppression, reduced milk production, loss of body weight, tick paralysis, toxicosis, and hypersensitivity reactions in affected hosts (Walker et al., 2014; Kasaija et al., 2021). Consequently, ticks and tick-borne diseases (TBDs) impose substantial global economic burdens on the livestock sector, with global losses estimated at $20–30 billion annually due to decreased productivity, treatment costs, and damage to hides and skins (Silatsa et al., 2019; Makwarela et al., 2023). In addition to their direct and indirect effects on animals, ticks are important vectors of zoonotic and non-zoonotic pathogens, including Anaplasma spp., Babesia spp., Borrelia spp., Coxiella spp., Cytauxzoon spp., Ehrlichia spp., Francisella spp., Rickettsia spp., Theileria spp., Crimean-Congo haemorrhagic fever virus, Nairobi sheep disease virus, African swine fever virus, heartland virus, Bourboun virus, and tick-borne encephalitis virus (Chitanga et al., 2014; Walker et al., 2014; Moming et al., 2024; Nepveu-Traversy et al., 2024; Gong et al., 2025; Springer et al., 2025). In Ethiopia, where domestic animal-human-environment interactions are widespread, tick infestations present an important One Health concern.

The epidemiology of ticks and TBDs is influenced by host availability, parasite traits, and environmental conditions (Yessinou et al., 2022; Makwarela et al., 2023). Climate change is expected to alter tick population dynamics further and facilitate the expansion of their geographical distribution and vectorial capacity into new territories (Ledwaba et al., 2022; Makwarela et al., 2023). In Ethiopia, where animal production underpins rural livelihoods, reported tick infestation levels range from 3.1% to 100%, reflecting considerable ecological and management variability (Pegram et al., 1981; Zenebe, 2007; Abunna et al., 2009; Kumsa et al., 2019; Taddesse et al., 2024; Tarekegn et al., 2025). However, epidemiological data remain fragmented, limiting the development of integrated control strategies. Therefore, a comprehensive meta-analysis is needed to estimate national prevalence and identify key determinants of infestation. This study aimed to (i) estimate the pooled prevalence of ixodid tick infestations in domestic animals in Ethiopia, (ii) identify dominant tick species and their geographical distribution, and (iii) assess associated risk factors to support targeted control initiatives.

2. Materials and methods

2.1. Study area description

Ethiopia (3°–15°N, 33°–48°E), located in the Horn of Africa, covers approximately 1.04 million km² and is the second most populous country in Africa (Seyoum and Tora, 2023). The country supports a large and diverse livestock population, including approximately 70.3 million cattle, 59.5 million chickens, 52.5 million goats, 42.9 million sheep, 8.2 million camels, and 13.2 million equines (Legese et al., 2023; Mesafint et al., 2023; Begna and Masho, 2024). These populations are distributed across three agroecological zones defined by elevation: highlands (≥ 2300 m above sea level, m a.s.l.), mid-highlands (1500–2300 m a.s.l.), and lowlands (< 1500 m a.s.l.) (Legese et al., 2023; Tarekegn et al., 2025). This ecological variability and high livestock density support diverse ectoparasite populations. A map of Ethiopia and its elevation ranges is presented in Fig. 1.

Fig. 1.

Map of Ethiopia with elevation ranges.

2.2. Literature search

A systematic literature review was conducted between 1 October 2025 and 20 January 2026, to identify studies reporting ixodid tick infestations in domestic animals in Ethiopia. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page et al., 2021). Electronic searches were performed in African Journals Online (AJOL), CABI Digital Library, EBSCOhost (Medline), Google Scholar, Hinari/Research4Life, PubMed, PubMed Central, ResearchGate, ScienceDirect, and SpringerLink. Grey literature, including DVM, MSc, and PhD theses/dissertations, was retrieved from Ethiopian university repositories to minimize publication bias. Only English-language publications were included, with no restriction on publication year.

The search strategy followed the CoCoPop (Condition, Context and Population) framework: Condition (ixodid tick infestation), Context (Ethiopia), and Population (domestic animals, including camels, cats, cattle, dogs, donkeys, goats, horses, and sheep) (Hosseini et al., 2024). Boolean operators (AND, OR) were used to combine keywords and MeSH terms related to: tick infestations (“Hard ticks”, “Ixodid ticks”, “Prevalence”, “Infestation rate”, “Risk factors”); host species (“Domestic animals”, “Livestock”, “Ruminants”, “Cattle”, “Bovine”, “Camel”, “Goat”, “Caprine”, “Sheep”, “Ovine”, “Equines”, “Horses”, “Donkey”, “Dogs”, “Cat”, “Pet animals”), and geographical location (“Ethiopia”). Reference lists of retrieved studies were also screened to capture additional relevant publications.

2.3. Inclusion and exclusion criteria

Study selection followed predefined eligibility criteria. Included studies were original cross-sectional studies conducted in Ethiopia that reported ixodid tick or ectoparasite infestations in domestic animals (cattle, sheep, goats, camels, equines, dogs, and cats). Eligible studies were required to report the total sample size and number of infested animals to enable prevalence calculations. Peer-reviewed articles, dissertations/theses, and full conference papers published in English were considered. Review articles, case reports, experimental studies, studies focused on wildlife, and publications lacking sufficient quantitative data were excluded.

2.4. Study selection and data extraction

Study selection was conducted in two stages. First, titles and abstracts were screened to remove duplicates and irrelevant records. Secondly, full-text articles were assessed against the eligibility criteria. The selection process is summarised in the PRISMA flow diagram (Fig. 2). Data from eligible studies were extracted into a standardised Microsoft Excel spreadsheet. Extracted information included: (i) publication details (first author and year); (ii) study characteristics (sampling period, region, and design); (iii) methodological information (host species, sample size, and diagnostic methods); and (iv) outcome data (number of infested animals, prevalence estimates, and tick species distribution). Data on potential risk factors, such as host sex, age, breed, body condition score, physiological status, management system, agroecological zone, acaricide use, and season, were also recorded for further analysis.

Fig. 2.

PRISMA flow chart describing the selection process.

2.5. Assessment of studies reporting tick-borne pathogens and One Health relevance

In addition to studies detailing the prevalence of ticks, their species diversity, and associated risk factors in domestic animals, we identified relevant studies from Ethiopia for findings on tick-borne pathogens found in collected ticks. The information gathered included the type of pathogen (bacterial, viral, or protozoan), methods of detection, the source of host animals, the species of ticks involved, and the geographical area. These results were summarised narratively to emphasise the potential One Health implications of ticks acting as reservoirs and vectors for zoonotic and veterinary pathogens in Ethiopia.

2.6. Quality assessment

The methodological quality of included studies was assessed using the STROBE checklist (Von Elm et al., 2008). This 22-item guideline evaluates the reporting quality of observational studies across domains, including study objectives, design, sampling methods, statistical analysis, results, discussion, and limitations.

2.7. Statistical analysis and data synthesis

Statistical analyses were performed using STATA version 17. A random-effects meta-analysis model (DerSimonian and Laird, 2015) was used to estimate the pooled prevalence of ixodid tick infestations, accounting for expected inter-study variability. Prevalence estimates were logit-transformed to stabilise variances (Barendregt et al., 2013) and subsequently back-transformed to obtain pooled estimates with 95% confidence intervals (CI). Heterogeneity was assessed using Cochran’s Q test, the I² statistic, and tau-squared (τ²) to estimate between-study variance (Higgins and Thompson, 2002). Substantial heterogeneity was considered when I² exceeded 50%. Forest plots were generated to visualise prevalence estimates and confidence intervals across studies, while Galbraith plots were used to evaluate result consistency. Publication bias was assessed using funnel plots and further examined with Egger’s and Begg’s tests (Borenstein et al., 2021). Subgroup analyses and meta-regression were conducted to explore potential sources of heterogeneity, including host species, geographical region, publication year, sampling method, and sample size. For risk factor analysis (≥ 5 studies per factor), pooled odds ratios (ORs) with 95% CIs were calculated. Spatial distribution of study sites, prevalence estimates, and tick species was mapped using QGIS version 3.32.0.

3. Results

3.1. Study characteristics and search results

The literature search yielded 5310 records, of which 173 cross-sectional studies published between 2004 and 2025 met the inclusion criteria (Fig. 2; Supplementary Table S1). All retrieved studies identified ticks using morphological methods. Only one study (Kumsa et al., 2016) used molecular and protein studies to characterise common ticks after morphological identification; this work is not included in this review. The dataset included 91,520 domestic animals: cattle (n = 50,519); sheep (n = 5687), goats (n = 15,184), camels (n = 7065), horses (n = 1240), dogs (n = 1081), donkeys (n = 497), and cats (n = 247). Ixodid tick infestations were reported in 50,668 animals. Apparent prevalence across individual studies ranged from 3.2% to 100%, with a weighted mean prevalence of 55.4% (95% CI: 55.0–55.7%). Prevalence varied by host species. Camels exhibited the highest mean prevalence (74.1%, 95% CI: 73.1–75.2%), followed by cattle (64.5%, 95% CI: 64.1–65.0%), whereas cats showed the lowest prevalence (8.1%, 95% CI: 4.7–11.5%) (Table 1).

Table 1.

Apparent and pooled prevalence of ixodid tick infestation in Ethiopian domestic animals reported during 2004–2025.

Host	No. of studies	Apparent prevalence (95% CI)	Pooled prevalence (95% CI)	I2 (%)	τ2
Camel	16	74.1 (73.1–75.2)	85.1 (72.4–92.6)	99.2	2.5
Cattle	113	64.5 (64.1–65.0)	68.1 (63.2–72.6)	99.1	1.3
Sheep	48	36.2 (35.5–37.0)	37.3 (28.6–53.0)	99.0	1.9
Goat	47	41.4 (40.6–42.2)	35.3 (26.3–45.4)	99.1	2.1
Horse	2	37.5 (34.8–40.2)	24.4 (7.2–57.2)	94.1	1.0
Donkey	2	29.8 (25.8–33.8)	19.3 (5.2–51.2)	88.9	1.0
Dog	4	20.9 (18.5–23.3)	16.8 (5.9–39.6)	98.1	1.4
Cat	2	8.1 (4.7–11.5)	6.9 (1.7–24.2)	83.9	0.9
Overall	173	55.4 (55.0–55.7)	55.0 (50.0–59.9)	99.4	2.4

3.2. Spatiotemporal distribution

The 173 studies represented 273 distinct sampling locations across Ethiopia (Fig. 3). Most studies (82.7%, 143/173) were published after 2010, although publication frequency declined slightly from 2020 onwards (trend line: y = 0.24x + 6.2) (Fig. 4). Geographically, studies covered nine Ethiopian regions, with research concentrated in central, southern, northwestern, and eastern areas (Fig. 5). The highest regional prevalence occurred in southeastern Ethiopia (74.8%, 95% CI: 73.1–76.5%), followed by western (69.9%, 95% CI: 68.6–71.2%) and southwestern regions (63.5%, 95% CI: 62.5–64.5%). The central region recorded the lowest prevalence (41.8%, 95% CI: 41.0–42.6%). Marked zonal variation was observed (Fig. 6). The highest infestation levels occurred in Gabi/Zone 3 (96.8%), Sheka (95.5%), and Bale (95.3%), whereas North Shewa (Amhara) recorded the lowest prevalence (4.4%).

Fig. 3.

Distribution of studies conducted on ixodid tick infestation in domestic animals in Ethiopia, 2004–2025.

Fig. 4.

Trend line and equation depicting the growing trend of published articles over the years.

Fig. 5.

Number of studies published during 2004–2025 and average apparent prevalence of hard tick infestation by region.

Fig. 6.

Map of Ethiopia displaying the zonal prevalence of hard tick infestation, 2004–2025.

3.3. Pooled prevalence and heterogeneity

Apparent prevalence across studies ranged from 3.2% to 100%. Continuity correction was applied to studies reporting extreme values (0% or 100%) to enable logit transformation. Using a random-effects model, the pooled prevalence of ixodid tick infestations was estimated at 50.0% (95% CI: 50.0–59.9%). Substantial heterogeneity was detected (I² = 99.4%; Cochran’s Q = 18,274.5, df = 233, P < 0.01, τ² = 2.4), supporting the use of a random-effects model. Heterogeneity is further illustrated in the Galbraith plot (Supplementary Fig. S1).

3.4. Subgroup meta-analysis

Subgroup analysis identified host species, geographical region, and sampling methodology as major contributors to heterogeneity (Supplementary Table S2). The highest pooled prevalence occurred in camels (85.1%) and cattle (68.1%), whereas small ruminants showed moderate prevalence (sheep: 37.3%; goats: 35.3%). Lower prevalence was observed in equids and companion animals, ranging from 24.4% in horses to 6.9% in cats. Geographically, prevalence was highest in southeastern Ethiopia (78.1%) and lowest in the central region (40.0%) (Supplementary Fig. S2). Sampling design also influenced estimates; multistage cluster sampling produced the highest pooled prevalence (76.5%). In contrast, publication year and sample size were not significant sources of variance (P > 0.05). Residual heterogeneity remained high within subgroups (I² > 83.0%, P ≤ 0.013), suggesting additional unmeasured determinants of tick infestation (Supplementary Table S2).

3.5. Meta-regression and publication bias

Multivariable meta-regression indicated that host species, geographical location, and sampling methodology (moderators with P < 0.25) explained 33.2% of the between-study variance (Supplementary Table S3). Publication bias was assessed using funnel plot symmetry and statistical tests. The funnel plot appeared largely symmetrical (Supplementary Fig. S3). Egger’s test (b = 1.7, 95% CI: −1.0–4.3, P = 0.21) and Begg’s test (P = 0.34) indicated no significant small-study effects or publication bias.

3.6. Species diversity and host range

The systematic review identified 35 ixodid tick species across four genera infesting domestic animals in Ethiopia (Supplementary Table S4). The genus Rhipicephalus was the most diverse (16 species), followed by Hyalomma (10 species), Amblyomma (6 species), and Haemaphysalis (3 species). Cattle harboured the highest species diversity, hosting 88.6% (31/35) of all identified species. Goats, sheep, and camels also exhibited considerable diversity (14–20 species), whereas equids and companion animals hosted fewer species (3–9 species).

A meta-analysis of 14 ixodid tick species reported in at least 5 studies between 2004 and 2025 was conducted (Table 2). The most prevalent species were Amblyomma cohaerens (20.8%), Amblyomma variegatum (18.6%), Rhipicephalus pulchellus (17.8%), and Rhipicephalus decoloratus (17.7%). Other often reported species included Rhipicephalus evertsi (13.5%), Amblyomma lepidum (12.1%), Hyalomma rufipes (10.5%), Amblyomma gemma (9.8%), and Hyalomma truncatum (6.7%). Hyalomma anatolicum had the lowest prevalence (1.2%), followed by Rhipicephalus pravus (4.9%), Hyalomma dromedarii (4.1%), Rhipicephalus praetextatus (3.3%), and Rhipicephalus sanguineus (sensu lato) (2.4%).

Table 2.

Apparent prevalence of 14 tick species identified in five or more studies across Ethiopia.

Tick species	No. of studies	No. of sampled animals	No. of infested animals	Apparent prevalence range (%)	Average apparent prevalence (95% CI) (%)
Amblyomma cohaerens	24	10,011	2082	0.5–66.3	20.80 (20.0–21.6)
Amblyomma variegatum	72	42,812	7946	0.5–97.6	18.56 (18.2–8.9)
Rhipicephalus pulchellus	31	18,925	3376	0.3–92.7	17.84 (17.3–18.4)
Rhipicephalus decoloratus	70	41,493	7334	0.8–100	17.68 (17.3–18.0)
Rhipicephalus evertsi	66	39,186	5271	0.5–65.0	13.45 (13.1–13.8)
Amblyomma lepidum	20	10,087	1218	0.9–66.7	12.07 (11.4–12.7)
Hyalomma rufipes	30	16,555	1733	0.3–47.4	10.47 (10.0–10.9)
Amblyomma gemma	35	21,226	2085	0.4–65.8	9.82 (9.4–10.2)
Hyalomma truncatum	26	21,665	1458	0.4–42.6	6.73 (6.4–7.1)
Rhipicephalus pravus	12	12,217	592	0.1–29.4	4.85 (4.5–5.2)
Hyalomma dromedarii	9	8512	402	0.9–42.7	4.72 (4.3–5.2)
Rhipicephalus praetextatus	15	15,222	499	0.5–7.6	3.28 (3.0–3.6)
Rhipicephalus sanguineus (s.l.)	8	7501	181	0.1–14.1	2.41 (2.1–2.8)
Hyalomma anatolicum	5	9734	117	0.04–8.3	1.20 (1.0–1.4)

3.7. Species-specific meta-analysis

3.7.1. Amblyomma spp.

Meta-analysis of four major Amblyomma spp. revealed substantial heterogeneity (I²≥98.1%, P < 0.0001; Table 3). The highest pooled prevalence was observed for A. cohaerens (15.0%, 95% CI: 9.3–23.2%) and A. variegatum (13.3%, 95% CI: 10.3–17.1%), followed by A. lepidum (6.6%, 95% CI: 3.9–11.0%) and A. gemma (5.3%, 95% CI: 3.6–7.6%). Geographical region significantly influenced the prevalence of A. cohaerens, A. lepidum, and A. variegatum (Table 4, P < 0.001), while host species was a significant moderator for A. variegatum variance (Table 5). Publication bias was detected across all species (P ≤ 0.017). Trim-and-fill analysis adjusted the prevalence of A. gemma to 7.5% (Supplementary Figures S4.1–4.4).

Table 3.

Overall pooled prevalence of 14 tick species identified in five or more studies across Ethiopia.

Tick species	No. of studies	No. of sampled animals	No. of infested animals	Pooled prevalence (95% CI) (%)	Q-value	I2 (%)	τ2	P-value
A. cohaerens	24	10,011	2082	15.0 (9.3–23.2)	1488.5	98.9	2.1	<0.001
A. variegatum	72	42,812	7946	13.3 (10.3–17.0)	5581.5	99.0	2.0	<0.001
R. decoloratus	70	41,493	7334	12.0 (9.3–15.4)	5878.7	98.8	1.9	<0.001
R. pulchellus	31	18,925	3376	10.6 (6.1–17.8)	2935.7	99.4	3.6	<0.001
R. evertsi	66	39,186	5271	8.8 (6.8–11.3)	4712.1	98.6	1.6	<0.001
H. rufipes	30	16,555	1733	7.1 (5.0–10.3)	1307.2	98.1	1.4	<0.001
A. lepidum	20	10,087	1218	6.6 (3.9–11.0)	943.8	98.4	1.8	<0.001
A. gemma	35	21,226	2085	5.3 (3.6–7.6)	2990.0	98.1	1.8	<0.001
H. truncatum	26	21,665	1458	5.3 (3.4–7.9)	1863.6	98.1	1.6	<0.001
H. dromedarii	9	8512	402	4.2 (1.9–9.4)	859.6	97.9	2.0	<0.001
R. pravus	12	12,217	592	3.5 (1.7–7.3)	700.1	98.5	2.0	<0.001
R. praetextatus	15	15,222	499	3.0 (2.2–4.1)	110.0	89.5	0.4	<0.001
R. sanguineus (s.l.)	8	7501	181	2.5 (1.0–6.2)	186.5	97.1	2.1	<0.001
H. anatolicum	5	9734	117	1.0 (0.3–3.1)	183.8	96.0	2.1	<0.001

Table 4.

Host species-specific pooled prevalence of 14 tick species identified in five or more studies across Ethiopia.

Tick species	Geographical regions of Ethiopia									Tests of group difference
	CE	EE	NE	NEE	NWE	S	SEE	SWE	WE
	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	Q-value	df	P-value
A. cohaerens	3 (2.4)	2 (3.9)	1 (23.2)	1 (24.5)	–	4 (6.6)	–	8 (26.5)	5 (28.9)	52.7	6	<0.001
A. gemma	3 (3.6)	10 (6.3)	3 (3.0)	4 (3.9)	1 (3.4)	6 (16.2)	–	6 (3.9)	2 (1.7)	6.8	7	0.455
A. lepidum	1 (9.9)	1 (20.3)	1 (3.4)	2 (12.6)	4 (2.5)	4 (8.7)	–	6 (5.4)	1 (25.8)	95.4	7	<0.001
A. variegatum	20 (11.8)	9 (12.6)	2 (7.4)	4 (3.0)	6 (11.6)	11 (22.7)	1 (39.3)	12 (16.4)	7 (18.5)	80.1	8	<0.001
H. anatolicum	–	1 (1.9)	–	1 (0.6)	2 (0.2)	1 (8.3)	–	–	–	88.8	3	<0.001
H. dromedarii	2 (3.3)	3 (3.3)	1 (42.7)	2 (1.5)	–	1 (27.9)	–	–	–	404.5	4	<0.001
H. rufipes	7 (5.1)	3 (14.9)	2 (16.6)	2 (2.2)	5 (8.7)	5 (6.5)	1 (2.6)	1 (3.0)	4 (4.7)	80.3	8	<0.001
H. truncatum	8 (5.2)	4 (10.3)	2 (5.0)	2 (2.1)	2 (1.8)	5 (7.1)	–	3 (4.1)	–	25.9	6	<0.001
R. decoloratus	20 (9.6)	9 (11.4)	3 (6.7)	4 (6.0)	7 (12.1)	10 (16.6)	1 (19.6)	9 (13.8)	7 (26.6)	22.5	8	0.004
R. evertsi	19 (7.4)	10 (7.1)	3 (4.2)	4 (6.4)	6 (19.6)	9 (8.7)	1 (10.2)	8 (7.4)	6 (18.7)	15.7	8	0.047
R. praetextatus	5 (1.7)	2 (4.8)	–	2 (3.1)	2 (5.5)	2 (3.2)	–	1 (1.0)	1 (0.4)	44.7	6	<0.001
R. pravus	3 (1.2)	3 (3.6)	–	2 (1.4)	–	4 (9.6)	–	–	–	2.0	3	0.572
R. pulchellus	6 (4.8)	9 (9.8)	2 (79.0)	3 (20.2)	–	9 (12.0)	–	1 (6.2)	1 (0.4)	30.1	6	<0.001
R. sanguineus (s.l.)	3 (2.0)	2 (3.1)	–	–	1 (0.1)	1 (14.1)	–	1 (10.4)	–	73.7	4	<0.001

Abbreviations: CE, central Ethiopia; EE, eastern Ethiopia; NE, northern Ethiopia; NEE, northeastern Ethiopia; NWE, northwestern Ethiopia; SE, southern Ethiopia; SWE, southwestern Ethiopia; WE, western Ethiopia; n, number of studies per region; %, pooled prevalence in percent.

Note: Heterogeneity I² ≥ 98.31%; Test of group difference: Q-test = 29.86, P < 0.001.

Table 5.

Geographical region-specific pooled prevalence of 14 tick species identified in five or more studies across Ethiopia.

Tick species	Host infested							Tests of group difference
	Camels	Cats	Cattle	Dogs	Goats	Horses	Sheep
	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	Q-value	df	P-value
A. cohaerens	2 (8.1)	–	18 (17.8)	–	4 (8.9)	–	4 (14.9)	1.6	3	0.65
A. gemma	3 (8.8)	–	20 (6.8)	–	12 (4.1)	1 (2.3)	11 (4.0)	9.1	4	0.06
A. lepidum	2 (3.2)	–	14 (6.7)	–	4 (13.1)	–	4 (4.2)	5.6	3	0.13
A. variegatum	3 (9.6)	1 (1.5)	45 (22.7)	2 (14.5)	21 (7.9)	1 (2.6)	22 (7.8)	73.3	6	<0.001
H. anatolicum	–	–	2 (0.7)	–	2 (1.0)	–	3 (1.0)	0.03	2	0.99
H. dromedarii	3 (17.7)	–	3 (3.6)	–	3 (1.6)	–	2 (2.1)	6.7	3	0.08
H. rufipes	2 (31.2)	–	22 (5.7)	–	5 (10.1)	1 (2.6)	5 (8.5)	29.7	4	<0.001
H. truncatum	1 (8.9)	–	15 (6.5)	–	7 (3.8)	1 (2.1)	9 (4.9)	32.3	4	<0.001
R. decoloratus	3 (5.7)	–	43 (22.9)	1 (2.7)	22 (6.7)	1 (1.8)	25 (7.1)	101.9	5	<0.001
R. evertsi	2 (12.4)	–	43 (9.7)	–	17 (7.3)	1 (15.8)	21 (7.8)	18.6	4	0.001
R. praetextatus	–	–	8 (2.5)	1 (4.0)	5 (3.1)	–	4 (3.7)	1.7	3	0.64
R. pravus	2 (5.8)	–	4 (1.5)	–	5 (4.9)	–	3 (3.0)	2.4	3	0.504
R. pulchellus	3 (67.3)	–	17 (7.5)	2 (4.4)	7 (14.3)	1 (13.4)	9 (7.7)	26.0	5	<0.001
R. sanguineus (s.l.)	1 (1.4)	1 (0.7)	1 (0.1)	3 (11.0)	2 (3.0)	–	2 (1.9)	84.29	5	<0.001

Abbreviations: n, number of studies reporting infestation per host; %, pooled prevalence in percent.

3.7.2. Hyalomma spp.

Pooled prevalence of Hyalomma spp. ranged from 1.0% to 7.1% (Table 3), with H. rufipes showing the highest prevalence (7.1%) and H. anatolicum the lowest (1.0%). High heterogeneity was observed (I² ≥96.0%, P < 0.001). Geographical region significantly influenced prevalence variability across four Hyalomma spp., while host species impacted variation in H. rufipes and H. truncatum (P < 0.0001). Publication bias was substantial for H. rufipes and H. truncatum.

3.7.3. Rhipicephalus spp.

Analysis of six Rhipicephalus spp. revealed considerable heterogeneity (I²≥89.5%, P < 0.0001). Rhipicephalus decoloratus (12.0%) and R. pulchellus (10.6%) were the most prevalent species, whereas R. sanguineus (s.l.) showed the lowest prevalence (2.5%). Host species and geographical region significantly influenced the variation in prevalence estimates for most species (Table 4, Table 5). Evidence of publication bias was found for R. decoloratus, R. evertsi, and R. sanguineus (s.l.); trim-and-fill adjustments increased estimates for R. decoloratus (16.9%) and R. evertsi (12.7%).

3.8. Risk factors associated with tick infestations

Risk factor meta-analysis included studies on camels (n = 8), cattle (n = 71), and small ruminants (n = 29). The reported factors included host, environment, and management. Poor body condition score (BCS) was the strongest predictor of infestation, significantly increasing risk in camels (pooled OR, pOR = 7.2), cattle (pOR = 3.2), and small ruminants (pOR = 2.0). Older animals showed higher infestation risk in cattle (pOR = 1.9) and small ruminants (pOR = 3.5). Sex was a significant factor only in small ruminants, where females were more frequently infested (pOR = 1.3, P < 0.05). Breed in cattle and species differences among small ruminants were not significant. Environmental and management factors also influenced infestation risk. Low altitude increased risk in cattle (pOR = 3.8) and small ruminants (pOR = 3.7), while wet seasons (pOR = 2.8) and extensive management systems (pOR = 3.4) increased risk in cattle. Seasonal variation was not significant for small ruminants. Detailed outputs are presented in Table 6, Supplementary Tables S5–S6 and Supplementary Figures S5.1-5.3.

Table 6.

Potential risk factors for the prevalence of ixodid tick infestation in Ethiopian camels.

Potential risk factors	Effect model	OR (95% CI)	z	Overall effect	n	Q-value	I2 (%)	τ2	P-value
Adult vs Young	IV, Fixed	1.14 (0.9–1.4)	1.3	P < 0.21	8	13.4	47.8	NA	0.063
Female vs Male	REML, Random	1.23 (0.8–1.8)	1.0	P = 0.32	7	16.4	62.5	0.2	0.012
Poor vs Medium	REML, Random	3.58 (1.6–8.0)	3.1	P = 0.002	6	21.7	79.6	0.7	0.001
Medium vs Good	REML, Random	1.85 (1.1–3.1)	2.3	P = 0.021	7	16.3	70.6	0.3	0.012
Poor vs Good	IV, Fixed	7.24 (4.4–11.9)	7.7	P < 0.001	4	15.2	80.2	NA	0.002

Abbreviations: REML, restricted maximum likelihood; IV, inverse variance; n, number of studies; NA, not applicable.

Note: “Poor”, “Medium” and “Good” refer to the body condition score of the studied animals.

3.9. Tick-borne pathogens and One Health implications

Twelve studies in Ethiopia reported tick-borne pathogens in ixodid ticks collected from domestic animals, primarily in Oromia (Supplementary Table S8). Bacterial pathogens (species of Anaplasma, Borrelia, Rickettsia, Coxiella, Ehrlichia, Neoehrlichia, and Haemoplasma) as well as protozoan pathogens (species of Babesia and Theileria) were reported. These pathogens were found in several ixodid tick species, including A. cohaerens, A. lepidum, A. gemma, A. variegatum, H. rufipes, H. truncatum, H. marginatum, R. decoloratus, R. evertsi, R. praetextatus, and R. pulchellus. These pathogens might significantly increase animal morbidity and mortality, reduce milk production, and cause reproductive losses. Several species of Anaplasma, Borrelia, Rickettsia, Coxiella, Ehrlichia, Neoehrlichia, and Haemoplasma all represent zoonotic risks to humans. These findings highlight the importance of employing a One Health approach to better understand the public health and veterinary implications of ixodid ticks in Ethiopia. However, most studies have focused on cattle ticks, with limited data from small ruminants, camels, and companion animals.

4. Discussion

Our national meta-analysis of 173 studies spanning two decades revealed a high pooled prevalence (55.0%) of ixodid tick infestations in Ethiopian domestic animals. This finding indicates a substantial burden on the livestock sector and is consistent with reports from other African countries with comparable production systems (Zachée et al., 2020; Sado Yousseu et al., 2022; Magesa et al., 2023; Etiang et al., 2024; Offei Addo et al., 2024; Komtangi et al., 2025). Such widespread infestation highlights the significant economic and health impacts of ticks and associated tick-borne diseases (TBDs) across the region.

Substantial heterogeneity was observed among studies (I² = 99.4%), reflecting Ethiopia’s diverse eco-geography, host composition, and methodological variation (Borenstein et al., 2021). Although a single national estimate simplifies a complex epidemiological landscape influenced by host, environmental, and parasite factors (Chepkwony et al., 2021; Makwarela et al., 2025), subgroup and meta-regression analyses identified host species, geographical location, and study design as key moderators. These findings provide important evidence for developing targeted tick-control strategies.

Host species strongly influenced infestation prevalence. Camels (85.1%) and cattle (68.1%) exhibited the highest rates, likely due to their large body surface area, limited grooming behaviour, and extensive grazing in vegetation-rich habitats that favour tick questing and transmission within communal pastures (Walker et al., 2014). Cattle also harbour the greatest tick species diversity in Ethiopia, highlighting their role as generalist hosts and their importance in maintaining tick populations nationally. High susceptibility in camels in arid and semi-arid regions may further reflect pastoral management practices and limited veterinary care, which favour specialized ticks such as H. dromedarii and R. pulchellus (Gharekhani et al., 2015; Perveen et al., 2020; Hussain et al., 2023). In contrast, lower prevalence in small ruminants, equids, and companion animals may result from physiological differences, grooming behaviour, host immunity, grazing patterns, tick host preferences, or faster population turnover in small-ruminant flocks (Pegram et al., 1981; Rehman et al., 2017).

Marked geographical variation was also observed. The southeastern, western, and southwestern regions exhibited the highest prevalence, whereas the central highlands showed the lowest. These patterns are largely driven by climatic and vegetation factors critical for tick survival (Cumming, 2002; Yawa et al., 2018). Low- to mid-altitude agroecological zones, characterised by warm temperatures and higher humidity, favour the metabolic activity and off-host survival of Amblyomma spp. and Rhipicephalus spp. within savannah-forest mosaics (Cumming, 2002; Ulloa-García et al., 2024; Tarekegn et al., 2025). Conversely, cooler and less humid highland environments, such as the North Shewa Zone (4.4%), may limit tick reproduction and survival (Ogden et al., 2021). However, ongoing climate warming may facilitate the expansion of ticks into previously low-risk highland areas, potentially exposing immunologically naïve livestock populations. These findings support geographically targeted surveillance and control strategies rather than uniform national interventions.

This study also provides an updated overview of tick diversity in Ethiopia, identifying reports of 35 ixodid species. The predominance of the genera Rhipicephalus (16 species), Hyalomma (10 species), and Amblyomma (6 species) reflects the country’s diverse agroecological zones and Afrotropical vegetation (Walker et al., 2014; Sado Yousseu et al., 2022). Species-specific analyses identified A. variegatum, A. cohaerens, R. decoloratus, and R. pulchellus as the most prevalent species, consistent with their widespread distribution and vector importance across Africa (Walker et al., 2014).

The high prevalence of Amblyomma species is particularly noteworthy. Amblyomma variegatum is the principal vector of Ehrlichia ruminantium, the causative agent of heartwater, and is strongly associated with bovine dermatophilosis (Mekonnen et al., 2001; Lorusso et al., 2013; Ndhlovu et al., 2017). Similarly, the abundance of A. cohaerens, particularly in western and southwestern Ethiopia, highlights its importance as a major regional tick pest (Mekonnen et al., 2001; Tufa et al., 2021).

The widespread occurrence of the one-host tick R. decoloratus is also significant because of its role in transmitting Babesia bigemina and Anaplasma marginale, the causative agents of bovine babesiosis and anaplasmosis, respectively (Jongejan and Uilenberg, 2004; Walker et al., 2014; Yessinou et al., 2022). This distribution suggests a substantial burden of TBDs affecting livestock productivity. Although H. anatolicum showed relatively low prevalence, its ability to transmit Theileria annulata and the zoonotic Crimean-Congo haemorrhagic fever virus remains an important concern (Walker et al., 2014; Rehman et al., 2017). Such species-specific information is essential for prioritising TBD surveillance and vaccine development in Ethiopia.

Body condition score (BCS) was strongly associated with tick infestation across camels, cattle, and small ruminants. Animals with poor BCS may exhibit reduced immune competence and grooming capacity, increasing susceptibility to infestation. Conversely, heavy tick burdens may exacerbate weight loss, suggesting a bidirectional relationship between host condition and infestation intensity (Heylen et al., 2023). Integrated control strategies that combine tick management with improved nutrition and animal health are therefore essential for sustainable control.

Risk factor analysis also revealed host-specific patterns. In cattle and small ruminants, age was a significant determinant of infestation, likely reflecting cumulative exposure, increased body surface area, and age-related immune changes (Rehman et al., 2017). These findings are consistent with previous studies reporting higher tick burdens in older animals (Lorusso et al., 2013; Asmaa et al., 2014; Rehman et al., 2017; Rocha et al., 2019). Management practices further influenced infestation risk; animals raised under extensive systems are more frequently exposed to infested pastures than those kept under confined conditions (Rehman et al., 2017; Sultan et al., 2022; Tarekegn et al., 2025). Seasonal dynamics also play a critical role, with infestation risk typically increasing during the wet season when warm and humid conditions favour tick development (Chepkwony et al., 2021; Etiang et al., 2024; Tarekegn et al., 2025).

Regarding the research landscape, the number of publications on tick infestations in Ethiopia has generally increased since 2010, although a potential decline after 2020 warrants further investigation. This meta-analysis also showed that sampling methodology significantly influences reported prevalence estimates. Multistage cluster random sampling yielded higher prevalence estimates, likely due to its ability to capture representative populations across heterogeneous settings. In contrast, convenience sampling may underestimate infestation levels by preferentially sampling easily accessible and potentially less affected populations (Stewart, 2002; Ajay and Masuku, 2014; Elfil and Negida, 2019).

Assessment of publication bias produced mixed results. While the overall pooled prevalence (54.96%) showed no significant small-study effects, indicating reasonable robustness of the overall estimate, species-level analyses revealed potential publication bias that may overestimate the prevalence of certain ticks. Trim-and-fill procedures failed to stabilise estimates for A. cohaerens, A. variegatum, and H. rufipes because of extreme heterogeneity, suggesting that observed variation likely reflects genuine epidemiological differences rather than reporting bias. Although the multivariable meta-regression model explained 33.2% of the variance, the remaining heterogeneity may reflect unmeasured factors such as microclimatic variation, acaricide resistance, host genetics, and wildlife reservoirs.

The identification of zoonotic and veterinary important pathogens in ticks collected from domestic animals suggests that tick infestations in Ethiopia should not be seen just as an issue of animal production. The close interactions among livestock, humans, wildlife, and shared ecosystems, particularly in pastoral and mixed crop-livestock production systems, can promote pathogen spillover of pathogens, emphasising the larger One Health significance of tick infestations in Ethiopia, both in terms of livestock production losses and zoonotic risks to humans. Several zoonotic pathogens, such as Anaplasma spp., Borrelia spp., Rickettsia spp., Coxiella burnetii, Ehrlichia spp., Neoehrlichia spp., and Haemoplasma spp., pose potential occupational risks for farmers, veterinarians, abattoir workers, and pastoral communities. Considering the significant livestock population in Ethiopia and the frequent interactions between humans and animals, it is crucial to implement an integrated tick surveillance system that encompasses veterinary, medical, and environmental sectors. Nonetheless, pathogen surveillance in Ethiopia remains inadequate, with the majority of studies primarily focusing on tick identification rather than pathogen detection.

Despite providing a comprehensive national overview, several limitations should be acknowledged. These include possible inaccuracies in tick identification, substantial methodological heterogeneity among studies, and inconsistent reporting of key confounding variables such as acaricide resistance, wildlife host dynamics, land-use patterns, and host genetic resistance. These limitations highlight the need for standardised surveillance and reporting protocols in future tick epidemiology studies in Ethiopia.

Overall, according to this systematic review and meta-analysis, there are several policy and research priorities essential for enhancing tick control in Ethiopia. Control measures should focus on regions with the highest risk through improved surveillance, targeted distribution of acaricides, and better extension services for farmers. Special attention should be given to cattle and camels, as they carry the greatest tick loads and species diversity, thereby maintaining tick populations. National surveillance systems should also incorporate mapping of the distribution of key vectors, including A. cohaerens, A. variegatum, R. decoloratus, R. evertsi, R. praetextatus, R. pulchellus, H. dromedarii, H. rufipes, and H. truncatum, to help reduce the incidence of diseases such as heartwater, babesiosis, and anaplasmosis. Future research must employ molecular diagnostics, standardised methods, and long-term studies in less-studied areas to fill the gaps concerning acaricide resistance, interactions between wildlife and livestock, and host resistance. Additionally, analyses of economic burdens and One Health studies related to rickettsiosis and Q-fever are necessary.

Nonetheless, the present synthesis reveals clear ecological and host-related patterns shaping tick infestations across Ethiopian animal production systems. The strong influence of host species, agroecological variation, and livestock management practices underscores the complex interactions between ticks, hosts, and environmental conditions that drive infestation dynamics and disease risk. Collectively, these findings provide the first comprehensive national synthesis of tick infestation patterns in Ethiopian domestic animals and establish a robust evidence base for geographically targeted and host-specific tick control strategies.

5. Conclusions

Ixodid tick infestations remain a major constraint to animal health and productivity in Ethiopia, with a national pooled prevalence of 54.96%. Camels and cattle exhibited the highest infestation levels and hosted the greatest diversity of tick species. Spatially, the warm and humid lowland and mid-highland agroecologies of southeastern, western, and southwestern Ethiopia represent the principal high-risk zones. The dominant tick genera were Amblyomma and Rhipicephalus, with A. variegatum and R. decoloratus identified as key vectors of economically important tick-borne diseases. These findings highlight the need for strengthened veterinary surveillance targeting these key vector species. Poor body condition score emerged as a consistent risk factor across hosts, whereas the effects of altitude, seasonality, and production systems varied among animal species. Overall, the observed epidemiological patterns reflect complex tick-host-environment interactions, indicating that effective control requires risk-based strategies tailored to specific ecological and production contexts rather than generalised interventions.

Ethical approval

Not applicable.

CRediT authorship contribution statement

Zewdu S. Tarekegn: Conceptualization, Methodology, Investigation, Data curation, Validation, Formal analysis, Visualization, Writing - original draft, Writing - review & editing. Shimels D. Nigatu: Conceptualization, Supervision, Data curation, Visualization, Writing - review & editing. Kasim S. Abass: Conceptualization, Investigation, Data curation, Supervision, Visualization, Writing - review & editing. Sefinew A. Mekonnen: Conceptualization, Investigation, Data curation, Formal analysis, Supervision, Writing - review & editing. Wassie Molla: Conceptualization, Methodology, Investigation, Data curation, Validation, Formal analysis, Supervision, Writing - review & editing.

Data availability

The datasets supporting the conclusions of this article are included within the article and its supplementary files.

Statement on the use of AI-assisted technologies

During the preparation of this work, the authors used BioRender for Graphical Abstract preparation and Grammarly and Quillbot for writing assistance and grammar improvement. The authors reviewed and edited the output as needed and take full responsibility for the content of the published article.

Funding

This study received no funding.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following are the Supplementary data to this article: