Rickettsial diseases and scrub typhus constitute a group of the oldest known vector-borne diseases. The cosmopolitan distribution of the vectors that transmit rickettsiae and orientiae leads to a worldwide prevalence of these diseases. Despite their significant historical status, detection and diagnosis of these diseases are still evolving today. Serological methods remain among the most prevalent techniques used for the detection/diagnosis of rickettsial diseases and scrub typhus. Molecular techniques have been instrumental in increasing the sensitivity/specificity of diagnosis, identifying new Rickettsia and Orientia species and have enhanced epidemiological capabilities when used in combination with serological methods. In this review, we discuss these techniques and their associated pros and cons.

Ts65Dn mice inherit a marker chromosome, T(17 16 )65Dn, producing segmental trisomy for orthologs of about half of the genes on human chromosome 21. These mice display a number of phenotypes that are directly comparable to those in humans with trisomy 21 and are the most widely used animal model of Down syndrome (DS). However, the husbandry of Ts65Dn mice is complicated. Males are sterile, and only 20-40% of the offspring of Ts65Dn mothers are trisomic at weaning. The lower-than-expected frequency of trisomic offspring has been attributed to losses at meiosis, during gestation and at postnatal stages, but no systematic studies support any of these suppositions. We show that the T( 17 16 )65Dn marker chromosome is inherited at expected frequency and is fully compatible with development to midgestation. Disproportional loss of trisomic offspring occurs in late gestation and continues through birth to weaning. Different maternal H2 haplotypes are significantly associated with the frequency of trisomy at weaning in patterns different from those reported previously. The proportion of trisomic mice per litter decreases with age of the Ts65Dn mother. These results provide the first statistical and numerical evidence supporting the prenatal and perinatal pattern of loss in the Ts65Dn mouse model of DS.

Rickettsia asembonensis, the most well-characterized rickettsia of the Rickettsia felis-like organisms (RFLO), is relatively unknown within the vector-borne diseases research community. The agent was initially identified in peri-domestic fleas from Asembo, Kenya in an area in which R. felis was associated with fever patients. Local fleas collected from domestic animals and within homes were predominately infected with R. asembonensis with < 10% infected with R. felis. Since the identification of R. asembonensis in Kenya, it has been reported in other locations within Africa, Asia, the Middle East, Europe, North America, and South America. With the description of R. asembonensis-like genotypes across the globe, a need exists to isolate these R. asembonensis genotypes in cell culture, conduct microscopic, and biological analysis, as well as whole genome sequencing to ascertain whether they are the same species. Additionally, interest has been building on the potential of R. asembonensis in infecting vertebrate hosts including humans, non-human primates, dogs, and other animals. The current knowledge of the presence, prevalence, and distribution of R. asembonensis worldwide, as well as its arthropod hosts and potential as a pathogen are discussed in this manuscript.

The American dog tick, Dermacentor variabilis (Say) (Acari: Ixodidae), is a vector for several human disease-causing pathogens such as tularemia, Rocky Mountain spotted fever, and the understudied spotted fever group rickettsiae (SFGR) infection caused by Rickettsia montanensis. It is important for public health planning and intervention to understand the distribution of this tick and pathogen encounter risk. Risk is often described in terms of vector distribution, but greatest risk may be concentrated where more vectors are positive for a given pathogen. When assessing species distributions, the choice of modeling framework and spatial layers used to make predictions are important. We first updated the modeled distribution of D. variabilis and R. montanensis using maximum entropy (MaxEnt), refining bioclimatic data inputs, and including soil variables. We then compared geospatial predictions from five species distribution modeling frameworks. In contrast to previous work, we additionally assessed whether the R. montanensis positive D. variabilis distribution is nested within a larger overall D. variabilis distribution, representing a fitness cost hypothesis. We found that 1) adding soil layers improved the accuracy of the MaxEnt model; 2) the predicted ‘infected niche’ was smaller than the overall predicted niche across all models; and 3) each model predicted different sizes of suitable niche, at different levels of probability. Importantly, the models were not directly comparable in output style, which could create confusion in interpretation when developing planning tools. The random forest (RF) model had the best measured validity and fit, suggesting it may be most appropriate to these data.