High burden and spatial clustering of canine hemoparasitic infections in southern Thailand: A molecular survey of free-roaming dogs

Rittidet kongtawee; Witchuta Junsiri; Duriyang Narapakdeesakul; Anyarat Thiptara; Frederic Beugnet; Piyanan Taweethavonsawat

doi:10.1016/j.onehlt.2026.101365

. 2026 Feb 16;22:101365. doi: 10.1016/j.onehlt.2026.101365

High burden and spatial clustering of canine hemoparasitic infections in southern Thailand: A molecular survey of free-roaming dogs

Rittidet kongtawee ^a, Witchuta Junsiri ^b, Duriyang Narapakdeesakul ^b, Anyarat Thiptara ^c, Frederic Beugnet ^b,^e, Piyanan Taweethavonsawat ^b,^d,^⁎

PMCID: PMC12926593 PMID: 41737196

Abstract

Canine vector-borne pathogens (CVBPs) are increasingly prevalent in tropical and subtropical regions, particularly among free-roaming dog populations, which serve as key reservoirs for transmission. This study investigated the prevalence and the spatial distribution of CVB pathogens in 318 free-roaming dogs from five sub-districts of Songkhla Province, southern Thailand. Conventional PCR was utilized to detect eight pathogens: Anaplasma platys, Ehrlichia canis, hemotropic Mycoplasma spp., Babesia spp., Hepatozoon spp., Trypanosoma evansi, Dirofilaria immitis, and Brugia malayi. An overall infection rate of 77.04% was observed, with A. platys (51.89%) and hemotropic Mycoplasma spp. (27.04%) being the most prevalent. Co-infections were common, occurring in over 42% of infected dogs. Spatial analysis using kernel density estimation (KDE) revealed pathogen-specific clustering patterns, particularly in the central and southwestern areas of the province. Infection prevalence was significantly associated with host factors such as age and weight. These findings highlight the critical role of free-roaming dogs in the epidemiology of CVBPs and the need for targeted surveillance and vector control strategies to mitigate zoonotic transmission. This One Health integrative approach provides a comprehensive assessment of pathogen diversity and prevalence while identifying environmental and host-related factors that may influence their geographic distribution.

Keywords: Canine vector-borne pathogens (CVBPs), Free-roaming dogs, Hemoparasites, Molecular diagnosis, Spatial epidemiology

Graphical abstract

Highlights

•
High prevalence (77%) of blood-borne parasites was detected in free-roaming dogs in southern Thailand.
•
Co-infections were common (42%), including cases with two, three, or four pathogens simultaneously.
•
Results highlight the role of free-roaming dogs as reservoirs and emphasize the importance of integrated One Health approaches for disease control.

1. Introduction

Canine vector-borne pathogens (CVBPs) comprise a group of infectious diseases transmitted by arthropod vectors, such as ticks, fleas, mosquitoes, and sand flies. These pathogens pose substantial health risks to dogs and, in some cases, humans. The most commonly implicated agents include Ehrlichia canis, Anaplasma platys, Mycoplasma haemocanis, Babesia vogeli, Hepatozoon canis and Dirofilaria spp. [1], [2], [3]. A previous molecular survey conducted in Thailand revealed infection rates among stray dogs as follows: Mycoplasma haemocanis (19.9%), H. canis (18.8%), B. vogeli (9.4%), A. platys (4.4%), and E. canis (3.9%) [4], [5]. These findings suggest that multiple CVB pathogens co-circulate within canine populations, potentially resulting in co-infections and exacerbated disease severity. Clinical signs are often overlapping rather than being pathogen-specific: E. canis causes canine monocytic ehrlichiosis, characterized by fever, lethargy, and lymphadenopathy, and thrombocytopenia [6], [7]; A. platys is responsible for canine cyclic thrombocytopenia, marked by intermittent thrombocytopenia and mild systemic illness [8]; Mycoplasma spp. causes hemotropic mycoplasmosis, resulting in anemia and lethargy [9]; Babesia spp. causes babesiosis, presenting with hemolytic anemia, jaundice, and fever [10]; and H. canis leads to canine hepatozoonosis, with clinical signs such as fever, weight loss, and muscle pain [11]. Microscopic examination often lacks sensitivity and fails to distinguish between morphologically similar species [12], [13]. While serological methods such as enzyme-linked immunosorbent assays (ELISA) and indirect immunofluorescence assays (IFA) can detect pathogen-specific antibodies or antigens, they may be less effective in identifying early infections [14]. In contrast, polymerase chain reaction (PCR), especially conventional PCR, offers superior sensitivity and specificity by directly detecting pathogen DNA in blood [15].

Polymerase chain reaction (PCR) is a widely used molecular technique for the detection of pathogen DNA. Conventional PCR, also referred to as endpoint PCR, is a cost-effective and relatively simple method that amplifies specific DNA sequences of infectious agents [16]. Its application is particularly valuable for molecular surveys of blood parasites. By employing advanced molecular tools such as PCR and DNA sequencing, it is possible to accurately identify and characterize the range of blood-borne parasites circulating within dog populations [17]. This molecular approach provides a comprehensive assessment of parasite diversity and prevalence and facilitates investigation into environmental and host-related factors that influence their distribution. PCR is especially advantageous for detecting chronic and subclinical infections, offering greater diagnostic reliability for vector-borne pathogens in domestic animals compared to traditional techniques [5]. Conventional PCR can detect pathogens even in cases of low parasitemia, making it effective during early-stage infections when serological tests may yield false negatives [18]. Moreover, PCR enables precise differentiation between closely related species [19]. Despite these advantages, conventional PCR is not without limitations. It requires post-amplification procedures such as gel electrophoresis, which may increase the risk of contamination and false positives [9]. Additionally, it is not a quantitative technique and therefore cannot measure pathogen load, which may be important for assessing disease severity. In Thailand, PCR has been extensively used in epidemiological studies of CVBPs, aiding in the detection of Ehrlichia, Anaplasma, and Babesia species in canine populations [9], [20]. These efforts have significantly contributed to disease surveillance and support of public health and vector control strategies.

The prevalence and spread of canine vector-borne pathogens (CVBPs) in Thailand are influenced by multiple interconnected risk factors. The country's tropical and subtropical climate, characterized by high humidity and rainfall, creates favorable conditions for the survival and proliferation of arthropod vectors such as ticks and sandflies [21]. Urban areas pose a heightened risk due to denser dog populations, increased interaction with infected animals, and the abundance of vector habitats such as parks and moist environments, while rural areas present risks through greater vector contact with wildlife reservoirs [4], [13]. Free-roaming and stray dogs, especially those lacking supervision or preventive care, are particularly vulnerable to vector exposure [20]. High vector density in regions with standing water, such as rivers and ponds, and areas with poor veterinary infrastructure contributes significantly to disease transmission [22]. Inadequate tick control and infrequent veterinary visits further elevate the risk, especially in areas with limited access to animal healthcare or where preventive practices are lacking [21], [23]. Environmental changes, including deforestation and climate change, have expanded vector habitats and altered transmission patterns, allowing CVBPs to emerge in new geographic areas. Additionally, the movement of dogs through trade and travel can introduce infected animals into non-endemic regions, facilitating the spread of diseases [5]. Immunocompromised animals, such as puppies, older dogs, or those with underlying health conditions, are particularly susceptible to severe infections [17], [20]. Despite these insights, significant research gaps remain. Longitudinal studies are required to evaluate seasonal fluctuations in CVBPs prevalence and their association with environmental variables.

This survey aimed to improve the understanding of the prevalence of canine vector-borne pathogens (CVBPs) in southern Thailand by employing conventional PCR to detect pathogen DNA in free-roaming dog populations. Moreover, such study can enhance the knowledge of the transmission dynamics of blood-borne parasites in free-roaming dogs, highlighting the scope of the issue and its broader implications for both animal and public health. In addition, Brugia malayi, which is a known human lymphatic filariasis causative agent, bears dogs as putative reservoir hosts in this region. In this respect, monitoring of CVBPs in free-roaming dogs is important to guide One Health-focused prevention and control activities.

2. Materials and methods

2.1. Study area and sample collection

Blood samples were collected from 318 free-roaming dogs and preserved in EDTA tubes, then stored at −20 °C until molecular analysis. The minimum required sample size was estimated at ∼384 dogs (95% CI, z = 1.96, 5% error); however, due to field constraints, 318 dogs were ultimately sampled. Free-roaming dogs were purposively selected because they constitute a high-risk population with greater vector exposure, and sampling was based on accessibility without selection by age, health status, or tick presence. These dogs were recruited from various environments, including communities, garbage dumps, and temple grounds. Information on each dog's age (in months), sex, and breed was recorded. The age of dogs was estimated based on field records provided by local caretakers and community members when available. In cases where such information was unavailable, age was approximated through dentition examination conducted by a trained veterinarian based on dental eruption and wear characteristics. The sampled dogs, which had no documented health services or prior access to veterinary care such as vaccination, sterilization, deworming, or ectoparasite treatment, were purposively selected from five sub-districts with reported rabies cases across the three districts in Songkhla Province, Thailand, encompassing both urban and forested regions (Fig. 1). Sample collection was conducted between January and October 2024. The dogs were humanely restrained, and blood was drawn using Vacutainer tubes containing an anticoagulant. This study was approved and conducted in accordance with institutional guidelines for the use of animals in scientific research (IACUC No. 2431092) and the use of inocula and hazardous substances (IBC No. 2531002), as mandated by the Faculty of Veterinary Science, Chulalongkorn University.

Fig. 1 — (A) Map of Thailand indicating the location of the study area; (B) detailed identification of the sub-districts included in the study along with the number of samples collected; and (**C–G**) the approximate size of the foraging areas in each sub-district. (Source: Songkhla Province and administrative boundary data were obtained from the DIVA-GIS database. The map was generated using GEP (Google Earth Pro) version 7.3.6.1.

2.2. DNA extraction & DNA amplification

Genomic DNA was extracted from blood samples using the NucleoSpin® Blood extraction kit (MACHEREY-NAGEL, Germany) following the manufacturer's instructions. The extracted DNA was subsequently used as a template for PCR amplification with GoTaq® Green Master Mix (Promega Corporation, United States), targeting the 16S rRNA, 18S rRNA, ITS1, and COX1 gene regions. Instead, each gene corresponds to specific pathogen groups: 16S rRNA for E. canis, A. platys, and hemotropic Mycoplasma spp.; 18S rRNA for Hepatozoon and Babesia spp.; ITS1 for Trypanosoma spp.; and COX1 for filarial nematode. The extraction procedure followed established protocols as described in previous studies [16]. All genomic DNA samples were stored at −20 °C until use in the amplification steps (refer to Table 1). DNA concentration and purity were assessed using a spectrophotometer prior to PCR amplification to ensure adequate template quality. PCR products were separated by electrophoresis on 1% agarose gels, stained with ethidium bromide, and visualized under UV illumination to verify the expected fragment sizes using a DNA molecular weight marker. The amplified products were then purified and subjected to Sanger sequencing. Amplicons showing clear bands of the expected size were purified using a commercial PCR purification kit (MACHEREY-NAGEL, Germany) according to the manufacturer's protocol. Purified PCR products were subjected to bidirectional Sanger sequencing using an automated DNA sequencer. Raw chromatograms were manually inspected and edited to remove ambiguous base calls. Forward and reverse sequences were assembled to generate consensus sequences prior to downstream analysis. Sequence identity was confirmed using the BLASTn algorithm against reference sequences available in the NCBI GenBank database (http://www.ncbi.nlm.nih.gov/BLAST) to confirm identity. All verified DNA sequences were subsequently submitted to the GenBank database.

Table 1.

Molecular detection of canine vector-borne pathogens (CVBPs) using universal primers to test DNA samples for the presence of Anaplasma platys, Ehrlichia canis, hemotropic Mycoplasma spp., Hepatozoon spp., Babesia spp., Trypanosoma spp., and filarial nematodes.^a, ^b

Hemoparasites	gene	Primer name	Sequence from (5′ to 3′)	Product size	T(°C)	Reference
Anaplasma platys (Outer primer-Universal primer) (Inner primer - Nested PCR)	16 s rRNA	ECC F ECB R Platys F GA1UR	5’ AGAACGAACGCTGGCGGCAAGCC 3″ ^a 5’ CGTATTACCGCGGCTGCTGGCA 3′ ^a 5’ TTTGTCGTAGCTTGCTATG 3′ ^b 5’ GAGTTTGCCGGGACTTCTTCT 3′ ^b	402	63	[16]
Ehrlichia canis (Outer primer-Universal primer) (Inner primer - Nested PCR)	16 s rRNA	ECC F ECB R Canis F RHE3	5’ AGAACGAACGCTGGCGGCAAGCC 3″ ^a 5’ CGTATTACCGCGGCTGCTGGCA 3′ ^a 5’ CAATTATTTATAGCCTCTGGCTATAGGA 3′ ^b 5’ TATAGGTACCGTCATTATCTTCCCTAT 3′ ^b	478	53	[16]
Hemotropic Mycoplasma spp.	16 s rRNA	Myco93898 Myco3288	5’ ATACGGCCCATATTCCTACG 3′ 5’ TGCTCCACCACTTGTTCA 3’	595	60	[19]
Hepatozoon spp.	18 s rRNA	RLB F RLB R	5’ GAGGTAGTGACAAGAAATAACAATA 3′ 5’ TCTTCGATCCCCTAACTTC 3’	460–520	52	[40]
		Hemo1 Hemo2	5’ TATTGGTTTTAAGAACTAATTTTATGATTG 3′ 5’ CTTCTCCTTCCTTTAAGTGATAAGGTTCAC 3’	923	48	[30]
Babesia spp.	18 s rRNA	RLB F RLB R	5’ GAGGTAGTGACAAGAAATAACAATA 3′ 5’ TCTTCGATCCCCTAACTTC 3’	460–520	52	[40]
Trypanosoma spp.	ITS1	Tryp1S Tryp1R	5’ CGTCCCTGCCATTTGTACACA 3′ 5’ GGAAGCCAAGTAATCCATCG 3’	341–587	55	[41]
Filarial nematodes	COX1	COX1F COX1R	5’ ATRGTTTATCAGTCTTTTTTTATTGG 3′ 5’ GCAATYCAAATAGAAGCAAAAGT 3’	542	60	[42]

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Note: R = A, G; Y = C, T. Abbreviation: T (°C), annealing temperature.

First round PCR.

Nested PCR.

2.3. Molecular identification procedure

To detect Ehrlichia canis, Anaplasma platys, hemotropic Mycoplasma spp., Hepatozoon spp., Babesia spp., Trypanosoma spp., and. Filarial nematodes in blood samples, this study employed conventional polymerase chain reaction (cPCR) targeting partial sequences of the 16S rRNA, 18S rRNA, COX1, and ITS1 genes. The primers used are listed in Table 1. PCR conditions followed protocols described in previous studies [21]. Briefly, each 20 μL reaction mixture contained 2 μL of genomic DNA template, GoTaq® Green Master Mix (Promega, USA), 0.2 mM of each forward and reverse primer, and nuclease-free water. Amplification was carried out using a thermal cycler (BIOER Technology, China). Positive controls consisted of genomic DNA from previously confirmed cases by sequencing for each targeted pathogen, with GenBank accession numbers provided in the Results section. Nuclease-free water was used as a negative control. Species-level identification of PCR-positive samples was determined using sequence similarity analysis following BLASTN comparisons.

2.4. Quantum geographic information system analysis (QGIS)

Spatial analysis and mapping in this study were conducted using Quantum Geographic Information System (QGIS) version 3.34.7, which supports both raster and vector data formats and enables integration and processing of diverse spatial data sources. (https://qgis.org.).

The estimation of free-roaming dogs' potential spatial extent and movement patterns was based on the previously documented mean activity range of 178 ± 190 ha (approximately 1.78 ± 1.90 km²) [13]. Distances from each point to the nearest forest edge (approximately 0.75–3 km radius) and human settlement were calculated to explore spatial relationships that may influence movement behavior or disease transmission [24].

2.5. Statistical analysis

Statistical analyses were performed using RStudio version 2024.04.2 + 764. Basic statistics, including prevalence and its 95% confidence intervals (CIs), were calculated. Geographic variation in prevalence was assessed using Fisher's exact test [20], [25]. Associations between risk factors, including sex (male, female), age groups (0.1–2.0, 2.1–5.9, and 6+ years), and body weight categories (0.1–6.0 kg, 6.1–10.9 kg, and 11+ kg), with PCR detection results for A. platys, E. canis, hemotropic Mycoplasma spp., Babesia spp., Hepatozoon spp., Trypanosoma spp., and filarial nematodes were evaluated using a generalized linear model (GLM). Body weight categories were defined as 0.1–6.0 kg, 6.1–10.9 kg, and ≥ 11 kg. While breed information and body condition scores (BCS) were not available for all dogs, these categories were used as a proxy for size and general body condition. Potential variation in body weight with age was considered in the statistical models by including age groups as a covariate in multivariable analyses.

Univariable GLMs with a quasi-Poisson distribution and log link function were first conducted to examine crude associations between individual risk factors and pathogen detection, and to estimate prevalence ratios (PRs) with corresponding 95% CIs and p-values, which provide a direct and interpretable measure of relative risk in cross-sectional studies [26]. Variables with p < 0.20 in univariable analysis were considered for inclusion in the multivariable model. Statistical significance was defined at p < 0.05. The Wilson score interval was applied to calculate 95% confidence intervals for prevalence estimates. Prior to multivariable analysis, chi-square tests were used to assess independence among categorical predictors, and no significant associations were detected, indicating that the variables could be included in the same model. Confounding was also evaluated by examining changes in prevalence ratios (PRs) when variables were added or removed from the model; no substantial confounding effect was observed (change in PR < 10%). Because some pathogens could not be identified at the species level, analyses were performed at the genus level.

3. Results

3.1. Prevalence of canine vector-borne pathogens (CVBPs)

Molecular analysis revealed that 245 out of 318 samples (77.04%) tested positive for at least one hemoparasitic pathogen. Anaplasma platys was the most prevalent, detected in 164 dogs (51.57%), followed by hemotropic Mycoplasma spp. in 86 dogs (27.04%), Hepatozoon spp. in 71 dogs (22.32%), E. canis in 53 dogs (16.66%), Babesia vogeli in 10 dogs (3.14%), Dirofilaria immitis in 6 dogs (1.88%), Brugia malayi in 6 dogs (1.88%), and Trypanosoma evansi in a single dog (0.31%) (Table 2). Both single and mixed infections were observed, with 111 dogs (34.9%) harboring a single pathogen and 134 dogs (42.14%) presenting mixed infections involving two or more species. The most common dual infections included A. platys + E. canis (7.54%), followed by A. platys + Hepatozoon spp. (7.86%), and A. platys + hemotropic Mycoplasma spp. (9.43%). Triple and quadruple infections were also detected, with notable combinations such as A. platys + E. canis + hemotropic Mycoplasma spp. (2.83%), A. platys + Hepatozoon spp. + hemotropic Mycoplasma spp. (3.77%), and a quadruple infection involving A. platys, E. canis, hemotropic Mycoplasma spp. and Brugia malayi (0.31%). The geographic distribution of infections varied across the five sub-districts of Chang, Khuan Lang, Saton, Thung Lan, and Thung Tam Sao. As illustrated in the alluvial plot (Fig. 2), infections were widespread, with A. platys and hemotropic Mycoplasma spp. showing higher prevalence in Chang and Khuan Lang.

Table 2.

Distribution and Frequency of Single and Mixed Hemoparasitic Infections in Canine Blood Samples.

Nature of infection	Number of positive samples (%)	Accession number
Single infection
Anaplasma platys (A)	164 (51.57)	PV875275-PV875291
Hemotropic Mycoplasma spp. (M)	86 (27.04)	PX072489-PX072497
Hepatozoon spp. (H)	71 (22.32)	PV876572-PV876579
Ehrlichia canis (E)	53 (16.66)	PV889315-PV889320
Babesia vogeli (B)	10 (3.14)	PV876597-PV876606
Dirofilaria immitis (Di)	6 (1.88)	PV876564-PV876569
Brugia malayi (Bs)	6 (1.88)	PX092363-PX092368
Trypanosoma evansi (T)	1 (0.31)	PV876607
Mixed infection
A+ M	30 (9.43)
A + H	25 (7.86)
A + E	24 (7.54)
A + H+ M	12 (3.77)
A + E+ M	9 (2.83)
E+ M	8 (2.51)
A + B	3 (0.94)
A + Bs	2 (0.62)
A + B + E	2 (0.62)
E + M + Di	2 (0.62)
A + Di	1 (0.31)
A + T	1 (0.31)
B + Di	1 (0.31)
E + H	1 (0.31)
H + M	1 (0.31)
M + Bs	1 (0.31)
A + E + Bs	1 (0.31)
A + H + Bs	1 (0.31)
E + H + Di	1 (0.31)
A + E+ M + Bs	1 (0.31)

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Fig. 2 — This figure illustrates the relationships between each identified hemoparasite species and the corresponding district of detection. Color-coded streams represent individual pathogens, with the width of each stream proportionate to the number of positive cases, thereby conveying both pathogen prevalence and spatial distribution patterns.

3.2. Spatial distribution of pathogens

Subdistrict-level analysis (Table 3) revealed that A. platys prevalence was highest in Thung Tam Sao (82.76%) and Saton (56.25%). Hepatozoon spp. showed the highest occurrence in Chang subdistrict (85.29%), while E. canis was most found in Khuan Lang (28.57%). Hemotropic Mycoplasma spp. was notably prevalent in Thung Tam Sao (72.41%), and filarial nematodes were most frequently detected in Khuan Lang (6.59%). The sole case of Trypanosoma evansi was identified in the Thung Ian Subdistrict. Significant geographic variation in the prevalence was observed for E. canis (p < 0.001), A. platys (p = 0.003), hemotropic Mycoplasma spp. (p < 0.001), and Hepatozoon spp. (p < 0.001). In contrast, no significant geographic variation was detected for B. vogeli, T. evansi, D. immitis, or B. malayi (p > 0.05).

Table 3.

Distribution of pathogen-positive cases and 95% confidence intervals across subdistricts in southern Thailand. (N 318).

Pathogens	Locations					Total	Fisher's exact
Pathogens	Hat Yai District (n = 211)		Na Thawi District (n = 66)		Khlong Hoi Khong District (n = 41)	Total	Fisher's exact
	Khuan Lang Subdistrict (n = 182)	Thung Tam Sao Subdistrict (n = 29)	Saton Subdistrict (n = 32)	Chang Subdistrict (n = 34)	Thung lan Subdistrict (n = 41)
	No. positive (%) CI	No. positive (%) CI	No. positive (%) CI	No. positive (%) CI	No. positive (%) CI	No. positive (%) CI
Ehrlichia canis	52 (28.57)	0(0.00)	0 (0.00)	1 (2.94)	0 (0.00)	53 (16.66)	< 0.0001***
	21.9, 35.2	0.0, 0.103	0.0, 0.094	0.0, 8.6	0.0, 0.073	12.74,21.23
Anaplasma platys	87 (47.80)	24 (82.76)	18 (56.25)	19 (55.88)	16 (39.02)	164 (51.57)	0.002851**
	40.6, 55.1	69.0, 96.5	39.1, 73.4	39.2, 72.6	24.1, 54.0	45.93,57.18
Hemotropic Mycoplasma spp.	46 (25.27)	21 (72.41)	10 (31.25)	3 (8.82)	6 (14.63)	86 (27.04)	< 0.0001***
	19.0, 31.6	56.1, 88.7	15.2, 47.3	0.0, 18.4	3.8, 25.5	22.38,32.47
Hepatozoon spp.	16 (8.79)	10 (34.0.48)	15 (46.88)	29 (85.29)	1 (2.44)	71 (22.32)	< 0.0001***
	4.7, 12.9	11.1, 51.2	30.2, 63.6	73.4, 97.2	0.0, 7.2	17.87,27.31
Babesia vogeli	5 (2.75)	0 (0.00)	0 (0.00)	3 (8.82)	2 (4.88)	10 (3.14)	0.05931
	0.4, 5.1	0.0, 0.103	0.0, 0.094	0.0, 18.4	0.0, 11.5	1.52,5.71
Trypanosoma evansi	0 (0.00)	0 (0.00)	0 (0.00)	0 (0.00)	1 (2.44)	1 (0.31)	0.4277
	0.0, 0.016	0.0, 0.103	0.0, 0.094	0.0, 0.088	0.0, 7.2	0.08,1.75
Dirofilaria immitis	6 (3.30)	0 (0.00)	0 (0.00)	0 (0.00)	0 (0.00)	6 (1.88)	0.7161
	1.0, 5.6	0.0, 0.103	0.0, 0.094	0.0, 0.088	0.0, 0.073	07.0,4.04
Brugia malayi	6 (3.30)	0 (0.00)	0 (0.00)	0 (0.00)	0 (0.00)	6 (1.88)	0.7161
	1.0, 5.6	0.0, 0.103	0.0, 0.094	0.0, 0.088	0.0, 0.073	07.0,4.04

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95% CI (lower, upper intervals) = 1.96 * p < 0.05,** p < 0.01, *** p < 0.001

The spatial distribution of pathogens in dogs from Songkhla Province is illustrated in Fig. 3. While all pathogens are ultimately blood-borne, we differentiate tick-borne (e.g., E. canis, A. platys, Babesia spp., Hepatozoon spp.) from non-tick-borne blood pathogens (e.g., hemotropic Mycoplasma spp. and filarial nematodes) to emphasize differences in transmission ecology. Kernel Density Estimation (KDE) was employed to produce heat maps, highlighting varying intensities of infection within the subdistricts. When data for all pathogens were aggregated (Fig. 3A), the highest concentration of positive samples was observed in the central and southwestern regions, indicating overlapping distributions of multiple pathogens. Spatial patterns of individual pathogens (Figs. 3B–I) demonstrated distinct trends: A. platys (B) and Hepatozoon spp. (D) exhibited focal clustering in the north-central area. Hemotropic Mycoplasma spp. (C) and B. vogeli (F) showed broader geographic distributions with multiple hotspots in both central and southern subdistricts. In contrast, E. canis (E) was confined to limited zones. D. immitis (G) and B.malayi (H) displayed two distinct clusters, indicating geographically separate transmission foci. These findings reveal pronounced spatial heterogeneity in pathogen distribution.

3.3. Impact of host demographics on pathogen detection rates

The univariable GLM analysis revealed that weight was associated with the occurrence of certain blood-borne pathogens in free-roaming dogs (Table 4). For E. canis, age and weight were significantly associated with infection. Dogs aged 0.1–2.0 years had a higher prevalence compared with those aged 2.1–5.9 years (PR = 1.92, 95% CI: 1.05–3.52, p = 0.033). In addition, dogs weighing more than 11.0 kg were more likely to be infected compared with those in the 6.1–10.9 kg group (PR = 2.19, 95% CI: 1.01–6.26, p = 0.049). In the case of Hepatozoon spp., a significant association was observed with weight. Dogs weighing 0.1–6.0 kg had a markedly lower prevalence compared with the reference group (PR = 0.21, 95% CI: 0.06–0.66, p = 0.007), whereas dogs weighing more than 11.0 kg also exhibited a significantly reduced prevalence (PR = 0.57, 95% CI: 0.36–0.91, p = 0.018). No significant associations were detected between demographic variables and the prevalence of A. platys, Hemotropic Mycoplasma spp., B. vogeli, T. evansi, D. immitis, or B. malayi. However, the multivariable GLM analysis adjusted for sex revealed that age and weight were associated only with E. canis in study dogs. Dogs aged 0.1 to 2.0 years had an 80% higher prevalence compared with those aged 2.1 to 5.9 years (PR = 1.80, 95% CI: 1.01 to 3.20, p = 0.047), and dogs weighing more than 11.0 kg had a higher prevalence compared with those in the 6.1 to 10.9 kg group (PR = 2.64, 95% CI: 1.06 to 6.61, p = 0.037).

Table 4.

Prevalence ratios (PR) with 95% confidence intervals (CIs) from univariable generalized linear models of host factors associated with pathogen detection in canine blood.

Factor	Pathogen
	Ehrlichia canis					Anaplasma platys
	N	% positive	PR	95% CI	P-value	N	% positive	PR	95% CI	P-value
Sex	288					288
Male	121	26(21.5)	1	–	–	121	70(57.9)	1	–	–
Female	167	27(16.2)	0.75	0.46–1.22	0.25	167	83(49.7)	0.85	0.69–1.07	0.17
Age (year)	271					271
0.1–2.0	137	34(24.8)	1.92	1.05–3.52	0.033*	137	78(56.9)	1.12	0.87–1.44	0.35
2.1–5.9	93	12(12.9)	1	–	–	93	47(50.5)	1	–	–
6.0+	41	6(14.6)	1.13	0.45–2.81	0.78	41	19(46.3)	0.91	0.62–1.35	0.66
Weight (kg)	288					288
0.1–6.0	42	8(19)	1.96	0.73–5.26	0.18	42	26(61.9)	1.12	0.81–1.57	0.47
6.1–10.9	62	6(9.7)	1	–	–	62	34(54.8)	1	–	–
11.0+	184	39(21.2)	2.19	1.01–6.26	0.049*	184	93(50.5)	0.92	0.70–1.20	0.55
	*Hemotropic Mycoplasma* spp.**					Hepatozoon spp.
Sex	287					288
Male	120	37(30.8)	1	–	–	121	27(22.3)	1	–	–
Female	167	45(26.9)	0.87	0.60–1.26	0.47	167	33(19.8)	0.88	0.56–1.39	0.59
Age (year)	270					271
0.1–2.0	137	31(22.6)	0.71	0.46–1.11	0.13	137	24(17.5)	1.01	0.57–1.81	0.96
2.1–5.9	92	29(31.5)	1	–	–	93	16(17.2)	1	–	–
6.0+	41	18(43.9)	1.39	0.88–2.20	0.16	41	10(24.4)	1.41	0.70–2.85	0.33
Weight (kg)	287					288
0.1–6.0	42	8(19)	0.73	0.34–1.56	0.43	42	3(7.1)	0.21	0.06–0.66	0.0077*
6.1–10.9	62	16(25.8)	1	–	–	62	21(33.9)	1	–	–
11.0+	183	58(31.7)	1.22	0.76–1.97	0.39	184	36(19.6)	0.57	0.36–0.91	0.018*
	*Babesia vogeli*					*Trypanosoma evansi*
Sex	288					287
Male	121	1(0.8)	1	–	–	121	0(0)	1	–	–
Female	167	9(5.4)	6.52	0.83–50.8	0.07	166	1(0.6)	0	0-Inf	0
Age (year)	271					270
0.1–2.0	137	5(3.6)	1.13	0.27–4.62	0.86	92	1(0.7)	0	0-Inf	0
2.1–5.9	93	3(3.2)	1	–	–	137	0(0)	1	–	–
6.0+	41	1(2.4)	0.75	0.08–7.95	0.81	41	0(0)	0	0-Inf	0
Weight (kg)	288					287
0.1–6.0	42	1(2.4)	0.73	0.06–7.88	0.80	62	1(2.4)	0	0-Inf	0
6.1–10.9	62	2(3.2)	1	–	–	42	0(0)	1	–	–
11.0+	184	7(3.8)	1.17	0.25–5.53	0.83	183	0(0)	0	0-Inf	0
	*Dirofilaria immitis*					*Brugia malayi*
Sex	287					288
Male	120	3(2.5)	1	–	–	121	2(1.7)	1	–	–
Female	167	3(1.8)	0.71	0.14–35.0	0.68	167	4(2.4)	1.44	0.27–7.79	0.67
Age (year)	270					271
2.1–5.9	93	1(1.1)	1	–	–	93	0(0)	1	–	–
0.1–2.0	137	5(3.6)	3.39	0.40–28.6	0.26	137	4(2.9)	0	0-Inf	0
6.0+	40	0(0)	0	0-Inf	0	41	2(4.9)	0	0-Inf	0
Weight (kg)	287					288
6.1–10.9	62	1(1.6)	1	–	–	62	1(1.6)	1	–	–
0.1–6.0	42	1(2.4)	1.47	0.09–23.0	0.78	42	0(0)	0	0-Inf	0
11.0+	183	4(2.2)	1.35	0.15–11.9	0.78	184	5(2.7)	1.68	0.20–1.41	0.63

Open in a new tab

The table shows prevalence ratios (PR) with 95% CIs and p-values (p < 0.05*) from GLMs assessing associations between host factors (age, sex, weight) and pathogen detection. Group 2 served as the reference. PR and CI were not estimated for groups with zero cases.

3.4. Molecular confirmation and sequence analysis

PCR-positive samples were successfully sequenced to verify pathogen identity. The obtained sequences matched the expected gene regions (16S rRNA, 18S rRNA, ITS1, and COX1) and showed high nucleotide identity (99–100%) with reference sequences in the GenBank database, confirming species-level identification of Anaplasma platys, Ehrlichia canis, hemotropic Mycoplasma spp., Hepatozoon spp., Babesia vogeli, Dirofilaria immitis, Brugia malayi, and Trypanosoma evansi. All validated sequences were deposited in GenBank under the accession numbers PV875275-PV875291, PV889315-PV889320, PX072489-PX072497, PV876572-PV876579, PV876597-PV876606, PV876564-PV876569, PX092363-PX092368, and PV876607.

4. Discussion

This study reveals a notably high prevalence of hemoparasitic infections among free-roaming dogs in southern Thailand, with 77.04% of the sampled animals testing positive for at least one pathogen. The detected organisms included A. platys, E. canis, hemotropic Mycoplasma spp., Hepatozoon spp., Babesia vogeli, Trypanosoma evansi, Dirofilaria immitis, and Brugia malayi, with A. platys being the most frequently identified. These findings align with previous reports documenting the widespread presence of canine vector-borne pathogen (CVBPs) in Southeast Asia [27], [28], notably, the high prevalence of hemotropic Mycoplasma spp. (27.04%).

Spatial analysis demonstrated significant geographic heterogeneity, with infection hotspots concentrated in central and southwestern subdistricts, while individual pathogens showed distinct spatial clustering patterns. Demographic analysis further indicated that dog weight was associated with prevalence risk: heavier dogs (>11 kg) had higher prevalence of E. canis, whereas both very light (≤6 kg) and heavy dogs showed lower prevalence of Hepatozoon spp. compared with intermediate weight groups. Age also influenced E. canis infection, with younger dogs (0.1–2 years) exhibiting higher prevalence.

The observations in this study suggest underrecognized transmission dynamics of this pathogen in free-roaming dog populations. Statistical analysis using Chi-square analysis revealed significant spatial clustering. The zoonotic potential of some hemoparasites, particularly A. platys and E. canis, which have been associated with human infections via tick exposure [8], underscores significant public health concerns, especially in areas with dense free-roaming dog populations and high tick abundance. Co-infections were common, with 42.14% of infected dogs harboring multiple pathogens. These mixed infections are likely facilitated by shared tick vectors, especially Rhipicephalus sanguineus, which is capable of concurrently transmitting A. platys, E. canis, and Hepatozoon spp. [29]. The detection of triple and even quadruple infections highlights the complex epidemiological landscape of CVBPs in the region. Similar trends in mixed infections have been reported in neighboring countries such as Malaysia and Cambodia [20], [30].

The spatial distribution of hemoparasitic infections varied significantly across the five surveyed sub-districts, with the highest rates of both single and mixed infections observed in Chang and Khuan Lang. These differences are likely influenced by ecological variables such as local microclimates, host population density, and the abundance of vector species, all of which play crucial roles in shaping pathogen transmission patterns [31].

Despite the valuable epidemiological insights gained from this study, certain limitations must be acknowledged. Notably, clinical data were not collected from the dogs, limiting the ability to correlate infection status with clinical signs. Additionally, the absence of vector sampling constrains the understanding of entomological factors contributing to pathogen spread.

Nonetheless, the high overall prevalence of hemoparasitic infections and the frequent detection of co-infections underscore the urgent need for integrated control strategies. The spatial distribution of vector-borne and blood-borne pathogens in dogs from Songkhla Province, as visualized through Kernel Density Estimation (KDE), revealed pronounced spatial heterogeneity across the region. Notably, the central and southwestern subdistricts emerged as infection hotspots (Fig. 3A), likely reflecting the co-circulation of multiple pathogens within shared ecological zones. This pattern may be driven by environmental conditions that facilitate both pathogen persistence and vector proliferation, such as dense vegetation, the presence of free-roaming dog populations, and proximity to water bodies which have previously been associated with heightened vector activity [32]. These spatial patterns suggest that variations in environmental factors, vector distribution, and host characteristics may influence the heterogeneous distribution of hemoparasitic infections in the free-roaming dog populations [33].

When examined individually, each pathogen exhibited distinct spatial distribution patterns. A. platys and Hepatozoon spp. were predominantly concentrated in the north-central regions, likely indicating localized R.sanguineus tick habitats favorable for their transmission. These patterns align with previous studies suggesting that R. sanguineus, a major vector for both pathogens, thrives in warm, humid environments where vector control measures are often lacking [34].

Conversely, Mycoplasma spp. and B. vogeli showed broader distributions with multiple clusters across central and southern areas. This may be attributed to their broader host and vector ranges, as well as alternative transmission pathways such as iatrogenic or vertical routes [1].

Ehrlichia canis and Trypanosoma evansi exhibited a more restricted spatial distribution, confined to specific localized zones. Regarding T. evansi, the limited occurrence may be influenced by unique ecological conditions and vector or host constraints, as the transmission of T. evansi likely relies on hematophagous insects such as biting flies, which are unevenly distributed across the landscape [28], [35]. The restricted distribution of E. canis is more difficult to explain as its vector the same as for A. platys and Hepatozoon spp.

The spatial distribution of filarial nematodes such as D. immitis and B. malayi was characterized by two distinct clusters, indicating the presence of separate transmission foci. These clusters may be associated with localized mosquito breeding sites or micro-environmental variations that support the persistence of vector populations [2], [21], [36].

Brugia malayi has recognized zoonotic potential, causing lymphatic filariasis in humans. Its presence in dogs highlights the importance of monitoring canine populations as potential reservoirs, particularly in endemic areas, and underscores the relevance of integrating One Health approaches in surveillance and control programs. The spatial clustering observed in Khuan Lang and Khuan Sato subdistricts may reflect local vector density and environmental conditions favorable for mosquito-borne transmission, suggesting that targeted vector control and community health interventions in these hotspots could effectively reduce both human and canine infection risks [16], [21], [23].

This study showed that age and weight significantly affected the likelihood of infection by E. canis and Hepatozoon spp.

For E. canis, dogs aged 0.1 to 2.0 years had a much higher prevalence than older dogs. This backs up previous research showing that younger dogs are at greater risk for tick-borne infections. Their immune systems are still developing, and they spend more time outdoors. [7], [37]. Furthermore, our finding that heavier dogs (>11 kg) had a higher risk of infection is significant. It should be noted, however, that breed information and body condition scores (BCS) were not available in this study, which limits interpretation of absolute body weight. The significance of body weight may also vary with age, as younger dogs naturally weigh less than adults. Inclusion of age as a covariate in the multivariable models helps to partially account for these effects. Previous studies have not often discussed body weight. However, similar patterns have been seen with outdoor activity and tick infestation. [10], [38]. On the contrary, our findings revealed that dogs weighing less than 6 kg and those exceeding 11 kg had a lower frequency of Hepatozoon spp. infection compared to dogs in the 6–10.9 kg range. The reasons of findings on weight influence remains unclear. More ecological and behavioral studies are needed to clarify these relationships. For other pathogens studied, including A. platys, B. vogeli, and D. immitis, no significant demographic links were found. This suggests that infection risk may depend more on ecological and environmental factors [17], rather than just by host age, sex, or weight.

Statistical analysis using Chi-square analysis revealed significant spatial clustering for E. canis, A. platys, hemotropic Mycoplasma spp., and Hepatozoon spp. (Table 3).

Anaplasma platys exhibited a relatively uniform distribution across the study sites for instance, 82.76% in Thung Tam Sao, 56.25% in Saton, 50% in Chang, and 49.45% in Khuan Lang with no statistically significant differences among locations. This widespread occurrence is consistent with the broad distribution of R. sanguineus, a cosmopolitan tick species known to efficiently transmit A. platys, E. canis, and H. canis in tropical regions [29]. The highest prevalence of Hepatozoon spp. was observed in Chang Subdistrict (85.29%), indicating a focal distribution despite the wide distribution of R. sanguineus, the main vector of Hepatozoon canis [29]. E. canis was most commonly detected in Khuan Lang Subdistrict (28.57%), with no cases identified in Saton, Chang, or Thung Ian, which is surprising in comparison to the wide distribution of A. platys infection despite sharing the same R.sanguineus vector [39].

Thung Tam Sao showed an exceptionally high prevalence of hemotropic Mycoplasma spp. (72.41%), significantly higher than in other areas. This intense clustering may reflect high dog population density or immunosuppressive effects of co-infections that facilitate pathogen transmission [10], [20], [40]. Filarial nematodes were most detected in Khuan Lang (6.59%), which is consistent with the presence of localized mosquito vector activity in the area. This underscores the importance of maintaining active surveillance even for infrequently detected pathogens [2], [35].

Most pathogens were identified only to the genus level, potentially obscuring finer-scale epidemiological trends. Future studies incorporating advanced molecular techniques, such as next-generation sequencing or multilocus sequence typing, could improve taxonomic resolution and pathogen characterization. The analysis of seasonal patterns in infection prevalence and vector activity was not included in this survey. Longitudinal studies would better capture temporal dynamics and inform transmission risk.

5. Conclusion

This study highlights a high prevalence and diversity of hemoparasitic infections among free-roaming dogs in southern Thailand, with 77.04% of samples testing positive for at least one pathogen. Anaplasma platys was the most common, followed by hemotropic Mycoplasma spp., Hepatozoon spp., and E. canis, with over 40% of infected dogs harboring co-infections. Significant associations between infection status and distinct spatial patterns, suggest that both host characteristics and environmental conditions influence pathogen distribution. The high prevalence of infection highlights the importance of integrated control strategies, including free-roaming dog management, tick control, and public awareness.

CRediT authorship contribution statement

Rittidet kongtawee: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis. Witchuta Junsiri: Writing – original draft, Methodology, Investigation. Duriyang Narapakdeesakul: Writing – original draft, Methodology, Investigation. Anyarat Thiptara: Writing – original draft, Resources, Methodology, Investigation. Frederic Beugnet: Writing – original draft, Methodology, Investigation. Piyanan Taweethavonsawat: Writing – review & editing, Validation, Supervision, Project administration, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Ethical approval

The Institutional Biosafety Committee (IBC) and Institutional Animal Care and Use Committee (IACUC) approved the present study for pathogen study and biosafety protocols (Permit IBC No. 2531002) and the use of animals in scientific research (Permit IACUC No. 2431092), as mandated by the Faculty of Veterinary Science, Chulalongkorn University.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used Chat GPT in order to improve readability and language. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

Funding

This research was supported by the Second Century Fund (C2F), Chulalongkorn University and the Thailand Science Research and Innovation Fund, Chulalongkorn University (FOOD_FF_69_195_3100_017), Thailand.

Declaration of competing interest

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.

Acknowledgments

The authors gratefully acknowledge the staff of the Veterinary Parasitology Unit, Faculty of Veterinary Science, Chulalongkorn University, for their support, and extend special thanks to Dr. Chalida Sri-in for her assistance with statistical analysis. Financial support from the Second Century Fund (C2F), Chulalongkorn University, is also gratefully acknowledged. The authors would like to express their sincere gratitude to Dr. Arun Chumkaeo for his support in providing the dogs’ information and data for this study.

Footnotes

^{Appendix A}

Supplementary data to this article can be found online at https://doi.org/10.1016/j.onehlt.2026.101365.

Appendix A. Supplementary data

Supplementary material

mmc1.docx^{(39.9KB, docx)}

Data availability

All data generated or analyzed during this study are included in this published article and its supplementary files. The partial nucleotide sequences obtained in this study were deposited in the GenBank ® (https://www.ncbi.nlm.nih.gov/nuccore) database under the following accession numbers: PV889315-PV889320 (for E. canis (16 s rRNA)), PV875275-PV875291 (for A. platys (16 s rRNA)), PX072489-PX072497 (for Hemotropic Mycoplasma spp. (16 s rRNA)), PV876572-PV876579 (for Hepatozoon spp. (18 s rRNA)), PV876597-PV876606 (for Babesia vogeli (18 s rRNA)), PV876607 (for Trypanosoma evansi (ITS1)), PV876564-PV876569 (for Dirofilaria immitis (COX1)), and PX092363-PX092368 (for Brugia malayi (COX1)).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary material

mmc1.docx^{(39.9KB, docx)}

Data Availability Statement

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PERMALINK

High burden and spatial clustering of canine hemoparasitic infections in southern Thailand: A molecular survey of free-roaming dogs

Rittidet kongtawee

Witchuta Junsiri

Duriyang Narapakdeesakul

Anyarat Thiptara

Frederic Beugnet

Piyanan Taweethavonsawat

Abstract

Graphical abstract

Highlights

1. Introduction

2. Materials and methods

2.1. Study area and sample collection

Fig. 1.

2.2. DNA extraction & DNA amplification

Table 1.

2.3. Molecular identification procedure

2.4. Quantum geographic information system analysis (QGIS)

2.5. Statistical analysis

3. Results

3.1. Prevalence of canine vector-borne pathogens (CVBPs)

Table 2.

Fig. 2.

3.2. Spatial distribution of pathogens

Table 3.

Fig. 3.

3.3. Impact of host demographics on pathogen detection rates

Table 4.

3.4. Molecular confirmation and sequence analysis

4. Discussion

5. Conclusion

CRediT authorship contribution statement

Ethical approval

Declaration of generative AI and AI-assisted technologies in the writing process

Funding

Declaration of competing interest

Acknowledgments

Footnotes

Appendix A. Supplementary data

Data availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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