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IntroductionCoxiella burnetii (C. burnetii)-infected livestock and wildlife have been epidemiologically linked to human Q fever outbreaks. Despite this growing zoonotic threat, knowledge of coxiellosis in wild animals remains limited, and studies to understand their epidemiologic role are needed. In C. burnetii-endemic areas, ticks have been reported to harbor and spread C. burnetii and may serve as indicators of risk of infection in wild animal habitats. Therefore, the aim of this study was to compare molecular techniques for detecting C. burnetii DNA in ticks.MethodsIn total, 169 ticks from wild animals and cattle in wildlife conservancies in northern Kenya were screened for C. burnetii DNA using a conventional PCR (cPCR) and two field-friendly techniques: Biomeme’s C. burnetii qPCR Go-strips (Biomeme) and a new C. burnetii PCR high-resolution melt (PCR-HRM) analysis assay. Results were evaluated, in the absence of a gold standard test, using Bayesian latent class analysis (BLCA) to characterize the proportion of C. burnetii positive ticks and estimate sensitivity (Se) and specificity (Sp) of the three tests.ResultsThe final BLCA model included main effects and estimated that PCR-HRM had the highest Se (86%; 95% credible interval: 56–99%), followed by the Biomeme (Se = 57%; 95% credible interval: 34–90%), with the estimated Se of the cPCR being the lowest (24%, 95% credible interval: 10–47%). Specificity estimates for all three assays ranged from 94 to 98%. Based on the model, an estimated 16% of ticks had C. burnetii DNA present.DiscussionThese results reflect the endemicity of C. burnetii in northern Kenya and show the promise of the PCR-HRM assay for C. burnetii surveillance in ticks. Further studies using ticks and wild animal samples will enhance understanding of the epidemiological role of ticks in Q fever.

Stressors over the lifespan can contribute to physiological dysregulation, or allostatic load. Allostatic load has been studied in humans using allostatic load indices (ALIs) for over 25 years, but the same methods are rarely applied to other species. We constructed an ALI for zoo-housed western lowland gorillas, chimpanzees, and bonobos and tested potential predictors of and health outcomes associated with allostatic load. Allostatic load scores ranged from 0–6 for gorillas and chimpanzees and 0–7 for bonobos. Age was significantly associated with allostatic load in gorillas and chimpanzees but not bonobos. Cumulative stressful events were positively associated with allostatic load in chimpanzees. Wild-caught gorillas had higher allostatic load than zoo-born conspecifics, but rearing differences between zoo-born animals were not significant for any species. Age may affect associations of allostatic load with stressful events and birthplace as results change when it is included as a covariate. Allostatic load was not retained in best-fit models for risk of all-cause morbidity, cardiac disease, or mortality risk. Some analyses herein were limited by the use of retrospective data, such as reason for sample collection and length of records provided for individual animals. Nevertheless, these data indicate additional research is needed to optimize ALIs for non-human primates.

[This corrects the article DOI: 10.1371/journal.pone.0230802.].

Abstract Background Nonhuman primates (NHPs) play a significant role in zoonotic spill-overs, serving as either reservoirs, or amplifiers, of multiple neglected tropical diseases, including tick-borne infections. Anaplasma phagocytophilum are obligate intracellular bacteria of the family Anaplasmatacae, transmitted by Ixodid ticks and cause granulocytic anaplasmosis (formerly known as Human Granulocytic Ehrlichiosis (HGE)) in a wide range of wild and domestic mammals and humans too. The aim of this study was to determine whether Anaplasma phagocytophilum was circulating in olive baboons and vervet monkeys in Laikipia County, Kenya. Results Some 146 blood samples collected from olive baboons and 18 from vervet monkeys from Mpala Research Center and Ol jogi Conservancy in Laikipia County were screened for the presence of Anaplasma species using conventional Polymerase Chain Reaction (PCR), and then A. phagocytophilum was confirmed by sequencing using conventional PCR targeting 16S rRNA. This study found an overall prevalence of 18.3% for Anaplasma species. DNA sequences confirmed Anaplasma phagocytophilum in olive baboons for the first time in Kenya. Conclusion This study provides valuable information on the endemicity of A. phagocytophilum bacteria in olive baboons in Kenya. Future research is needed to establish the prevalence and public health implications of zoonotic A. phagocytophilum isolates and the role of nonhuman primates as reservoirs in the region.

Focusing on the utility of ticks as xenosurveillance sentinels to expose circulating pathogens in Kenyan drylands, host-feeding ticks collected from wild ungulates [buffaloes, elephants, giraffes, hartebeest, impala, rhinoceros (black and white), zebras (Grévy’s and plains)], carnivores (leopards, lions, spotted hyenas, wild dogs), as well as regular domestic and Boran cattle were screened for pathogens using metagenomics. A total of 75 host-feeding ticks [Rhipicephalus (97.3%) and Amblyomma (2.7%)] collected from 15 vertebrate taxa were sequenced in 46 pools. Fifty-six pathogenic bacterial species were detected in 35 pools analyzed for pathogens and relative abundances of major phyla. The most frequently observed species was Escherichia coli (62.8%), followed by Proteus mirabilis (48.5%) and Coxiella burnetii (45.7%). Francisella tularemia and Jingmen tick virus (JMTV) were detected in 14.2 and 13% of the pools, respectively, in ticks collected from wild animals and cattle. This is one of the first reports of JMTV in Kenya, and phylogenetic reconstruction revealed significant divergence from previously known isolates and related viruses. Eight fungal species with human pathogenicity were detected in 5 pools (10.8%). The vector-borne filarial pathogens (Brugia malayi, Dirofilaria immitis, Loa loa), protozoa (Plasmodium spp., Trypanosoma cruzi), and environmental and water-/food-borne pathogens (Entamoeba histolytica, Encephalitozoon intestinalis, Naegleria fowleri, Schistosoma spp., Toxoplasma gondii, and Trichinella spiralis) were detected. Documented viruses included human mastadenovirus C, Epstein-Barr virus and bovine herpesvirus 5, Trinbago virus, and Guarapuava tymovirus-like virus 1. Our findings confirmed that host-feeding ticks are an efficient sentinel for xenosurveillance and demonstrate clear potential for wildlife-livestock-human pathogen transfer in the Kenyan landscape.

Physiological data can provide valuable information about the health and welfare of animals. Unfortunately, few validated assays and a lack of information on species-typical levels of circulating biomarkers for wildlife make the measurement, interpretation, and practical application of such data difficult. We validated commercially available kits and calculated reference intervals (herein called “value ranges”) for dehydroepiandrosterone-sulfate (DHEA-S), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) in a sample of zoo-housed western lowland gorillas due to the roles these biomarkers play in stress and immune responses. For each biomarker, we present species-specific value ranges for a sample of gorillas in human care (n = 57). DHEA-S did not vary significantly by sex or age, while IL-6 was higher in males and older gorillas and TNF-α was higher in females but not associated with age. We also compared non-clinical with clinical samples (n = 21) to explore whether these biomarkers reflect changes in health status. There was no significant difference between clinical and non-clinical samples for DHEA-S, but both IL-6 and TNF-α were significantly higher in gorillas showing clinical symptoms or prior to death. Additional work is needed to improve our understanding of normal versus clinical variation in these biomarkers, and we encourage continued efforts to identify and validate additional biomarkers that can be used to inform assessments of health and welfare in wildlife.

A majority of emerging infectious diseases (EIDs) are zoonotic, mainly caused through spillover events linked to human-animal interactions. We conducted a survey-based human behavioral study in Laikipia County, Kenya, which is characterized by a dynamic human-wildlife-livestock interface. Questionnaires that assessed human-animal interactions, sanitation, and illnesses experienced within the past year were distributed to 327 participants among five communities in Laikipia. This study aimed to 1) describe variation in reported high-risk behaviors by community type and 2) assess the relationship between specific behaviors and self-reported illnesses. Behavioral trends were assessed in R via Fisher's exact tests. A generalized linear mixed model with Lasso penalization (GLMMLasso) was used to assess correlations between behaviors and participants' self-reported illness within the past year, with reported behaviors as independent variables and reported priority symptoms as the outcome. Reported behaviors varied significantly among the study communities. Participants from one community (Pastoralist-1) were significantly more likely to report eating a sick animal in the past year (p< 0.001), collecting an animal found dead to sell in the past year (p

The recent emergence of bat-borne zoonotic viruses warrants vigilant surveillance in their natural hosts. Of particular concern is the family of coronaviruses, which includes the causative agents of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and most recently, Coronavirus Disease 2019 (COVID-19), an epidemic of acute respiratory illness originating from Wuhan, China in December 2019. Viral detection, discovery, and surveillance activities were undertaken in Myanmar to identify viruses in animals at high risk contact interfaces with people. Free-ranging bats were captured, and rectal and oral swabs and guano samples collected for coronaviral screening using broadly reactive consensus conventional polymerase chain reaction. Sequences from positives were compared to known coronaviruses. Three novel alphacoronaviruses, three novel betacoronaviruses, and one known alphacoronavirus previously identified in other southeast Asian countries were detected for the first time in bats in Myanmar. Ongoing land use change remains a prominent driver of zoonotic disease emergence in Myanmar, bringing humans into ever closer contact with wildlife, and justifying continued surveillance and vigilance at broad scales.