Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever

A compartment and metapopulation model of Rocky Mountain spotted fever in southwestern United States and northern Mexico

Rocky Mountain spotted fever (RMSF) is a fatal tick-borne zoonotic disease that has emerged as an epidemic in western North America since the turn of the 21st century. Along the US south-western border and across northern Mexico, the brown dog tick, Rhipicephalus sanguineus, is responsible for spreading the disease between dogs and humans. The widespread nature of the disease and the ongoing epidemics contrast with historically sporadic patterns of the disease. Because dogs are amplifying hosts for the Rickettsia rickettsii bacteria, transmission dynamics between dogs and ticks are critical for understanding the epidemic. In this paper, we developed a compartment metapopulation model and used it to explore the dynamics and drivers of RMSF in dogs and brown dog ticks in a theoretical region in western North America. We discovered that there is an extended lag-as much as two years-between introduction of the pathogen to a naïve population and epidemic-level transmission, suggesting that infected ticks could disseminate extensively before disease is detected. A single large city-size population of dogs was sufficient to maintain the disease over a decade and serve as a source for disease in surrounding smaller towns. This model is a novel tool that can be used to identify high risk areas and key intervention points for epidemic RMSF spread by brown dog ticks.

Establishment and range expansion of Dermacentor variabilis in the northern Maritimes of Canada: Community participatory science documents establishment of an invasive tick species

Tick populations are dependent on a complex interplay of abiotic and biotic influences, many of which are influenced by anthropic factors including climate change. Dermacentor variabilis, the wood tick or American dog tick, is a hardy tick species that feeds from a wide range of mammals and birds that can transmit pathogens of medical and agricultural importance. Significant range expansion across North America has been occurring over the past decades;this study documents northwards range expansion in the Canadian Maritime provinces. Tick recoveries from passive surveillance between 2012 and 2021 were examined to assess northward population expansion through Atlantic Canada. At the beginning of this period, D. variabilis was abundant in the most southerly province, Nova Scotia, but was not considered established in the province to the north, New Brunswick. During the 10-year span covered by this study, an increasing number of locally acquired ticks were recovered in discrete foci, suggesting small established or establishing populations in southern and coastal New Brunswick. The pattern of population establishment follows the climate-driven establishment pattern of Ixodes scapularis to some extent but there is also evidence of successful seeding of disjunct populations in areas identified as sub-optimal for tick populations. Dogs were the most common host from which these ticks were recovered, which raises the possibility of human activity, via movement of companion animals, having a significant role in establishing new populations of this species. Dermacentor variabilis is a vector of several pathogens of medical and agricultural importance but is not considered to be a competent vector for Borrelia burgdorferi, the etiological agent of Lyme disease; our molecular analysis of a subset of D. variabilis for both B. burgdorferi and B. miyamotoi did not confirm any with Borrelia. This study spans the initial establishment of this tick species and documents the pattern of introduction, providing a relatively unique opportunity to examine the first stages of range expansion of a tick species.

A Scoping Review of Species Distribution Modeling Methods for Tick Vectors

Background

Globally, tick-borne disease is a pervasive and worsening problem that impacts human and domestic animal health, livelihoods, and numerous economies. Species distribution models are useful tools to help address these issues, but many different modeling approaches and environmental data sources exist.

Objective

We conducted a scoping review that examined all available research employing species distribution models to predict occurrence and map tick species to understand the diversity of model strategies, environmental predictors, tick data sources, frequency of climate projects of tick ranges, and types of model validation methods.

Design

Following the PRISMA-ScR checklist, we searched scientific databases for eligible articles, their references, and explored related publications through a graphical tool (www.connectedpapers.com). Two independent reviewers performed article selection and characterization using a priori criteria.

Results

We describe data collected from 107 peer-reviewed articles that met our inclusion criteria. The literature reflects that tick species distributions have been modeled predominantly in North America and Europe and have mostly modeled the habitat suitability for Ixodes ricinus (n = 23; 21.5%). A wide range of bioclimatic databases and other environmental correlates were utilized among models, but the WorldClim database and its bioclimatic variables 1–19 appeared in 60 (56%) papers. The most frequently chosen modeling approach was MaxEnt, which also appeared in 60 (56%) of papers. Despite the importance of ensemble modeling to reduce bias, only 23 papers (21.5%) employed more than one algorithm, and just six (5.6%) used an ensemble approach that incorporated at least five different modeling methods for comparison. Area under the curve/receiver operating characteristic was the most frequently reported model validation method, utilized in nearly all (98.9%) included studies. Only 21% of papers used future climate scenarios to predict tick range expansion or contraction. Regardless of the representative concentration pathway, six of seven genera were expected to both expand and retract depending on location, while Ornithodoros was predicted to only expand beyond its current range.

Conclusion

Species distribution modeling techniques are useful and widely employed tools for predicting tick habitat suitability and range movement. However, the vast array of methods, data sources, and validation strategies within the SDM literature support the need for standardized protocols for species distribution and ecological niche modeling for tick vectors.

Unexpected winter questing activity of ticks in the Central Midwestern United States

Unexpected questing activity of ticks was noted during the winter months of January and February in the Central Midwestern states of Kansas, Missouri, Oklahoma, and Arkansas. From nine geographically distinct locations, four species of ticks were collected using the flagging method, of which the lone star tick, Amblyomma americanum, was most abundant, followed by the American dog tick, Dermacentor variabilis, the Gulf coast tick, Amblyomma maculatum, and the Black legged tick, Ixodes scapularis. More A. americanum nymphs were caught questing than male or female adults. The winter activity of these medically important ticks in this region poses concern for public health and offers an insight into future tick activity in light of ongoing climate change. More studies on the seasonality of these tick species, and how different climate parameters affect their seasonal activity in this region are warranted and would be expected to benefit for both human and veterinary medicine.

Diversity and seasonality of host-seeking ticks in a periurban environment in the Central Midwest (USA)

Between March 2014 and February 2017, host-seeking ticks were collected during the late spring and summer months seasonally, and as well as continually through all seasons from several sites in a periurban environment in Pittsburg, Kansas, located in the Central Midwestern United States. All three post-emergent life-stages of Amblyomma americanum, and the adults of three other ticks viz. Dermacentor variabilis, A. maculatum, and Ixodes scapularis were collected using the flagging method, and were taxonomically identified using morphological and molecular methods. A total of 15946 ticks were collected from these sites. A vast majority of the ticks collected over the three-year study period was A. americanum (79.01%). The three other species collected included D. variabilis (13.10%), A. maculatum (7.15%), and Ixodes scapularis (0.73%). More female ticks of each species were collected throughout the study period from all sites, and a unimodal activity period was noted for all four species. The diversity, composition, and phenology of these medically significant tick species are discussed.

Effect of Temperature on Host Preference in Two Lineages of the Brown Dog Tick, Rhipicephalus sanguineus

Rhipicephalus sanguineus is a species complex of ticks that vector disease worldwide. Feeding primarily on dogs, members of the complex also feed incidentally on humans, potentially transmitting disease agents such as Rickettsia rickettsii, R. conorii, and Ehrlichia species. There are two genetic Rh. sanguineus lineages in North America, designated as the temperate and tropical lineages, which had occurred in discrete locations, although there is now range overlap in parts of California and Arizona. Rh. sanguineus in Europe are reportedly more aggressive toward humans during hot weather, increasing the risk of pathogen transmission to humans. The aim of this study was to assess the impact of hot weather on choice between humans and dog hosts among tropical and temperate lineage Rh. sanguineus individuals. Ticks in a two-choice olfactometer migrated toward a dog or human in trials at room (23.5°C) or high temperature (38°C). At 38°C, 2.5 times more tropical lineage adults chose humans compared with room temperature, whereas temperate lineage adults demonstrated a 66% reduction in preference for dogs and a slight increase in preference for humans. Fewer nymphs chose either host at 38°C than at room temperature in both lineages. These results demonstrate that risk of disease transmission to humans may be increased during periods of hot weather, where either lineage is present, and that hot weather events associated with climatic change may result in more frequent rickettsial disease outbreaks.

Scoping review of distribution models for selected Amblyomma ticks and rickettsial group pathogens

The rising prevalence of tick-borne diseases in humans in recent decades has called attention to the need for more information on geographic risk for public health planning. Species distribution models (SDMs) are an increasingly utilized method of constructing potential geographic ranges. There are many knowledge gaps in our understanding of risk of exposure to tick-borne pathogens, particularly for those in the rickettsial group. Here, we conducted a systematic scoping review of the SDM literature for rickettsial pathogens and tick vectors in the genus Amblyomma. Of the 174 reviewed articles, only 24 studies used SDMs to estimate the potential extent of vector and/or pathogen ranges. The majority of studies (79%) estimated only tick distributions using vector presence as a proxy for pathogen exposure. Studies were conducted at different scales and across multiple continents. Few studies undertook original data collection, and SDMs were mostly built with presence-only datasets from public database or surveillance sources. The reliance on existing data sources, using ticks as a proxy for disease risk, may simply reflect a lag in new data acquisition and a thorough understanding of the tick-pathogen ecology involved.

Knowledge, Attitudes, and Practices Related to Rocky Mountain Spotted Fever in Hermosillo, México

Rocky Mountain spotted fever (RMSF) is a serious disease in northwest Mexico, particularly in low-income communities. This study aimed to evaluate RMSF-related knowledge, attitudes, and practices in an endemic urban area with a high burden of the disease. A cross-sectional study design using a non-probabilistic household survey was conducted with 400 residents in Hermosillo, Mexico. Primary themes assessed included dog and tick-related exposure, RMSF knowledge, healthcare-seeking behavior, sociodemographic data, and household information. The majority (59%) of those surveyed had heard about RMSF, although only 36% of RMSF-aware respondents knew any RMSF symptoms. Among RMSF-aware respondents, 26% did not know or were unsure of prevention strategies. Individuals in the low socioeconomic status (SES) stratum were less likely to have heard about RMSF (odds ratio [OR]: 0.39; 95% CI: 0.25-0.59), use dog collars or any other product to avoid ticks (OR: 0.40; 95% CI: 0.17-0.99), or check their dogs for ticks (OR: 0.25; 95% CI: 0.09-0.74). The likelihood of observing high numbers of free-roaming dogs in their neighborhood was four times higher in the low SES stratum (OR: 4.19; 95% CI: 2.10-8.38) than in the high SES stratum. These findings emphasize the need for an integrative community approach to improve early recognition of symptoms and knowledge of prevention strategies, particularly in low SES neighborhoods.

Assessing the current and future potential geographic distribution of the American dog tick, Dermacentor variabilis (Say) (Acari: Ixodidae) in North America

The American dog tick, Dermacentor variabilis, is a veterinary- and medically- significant tick species that is known to transmit several diseases to animal and human hosts. The spatial distribution of this species in North America is not well understood, however; and knowledge of likely changes to its future geographic distribution owing to ongoing climate change is needed for proper public health planning and messaging. Two recent studies have evaluated these topics for D. variabilis; however, less-rigorous modeling approaches in those studies may have led to erroneous predictions. We evaluated the present and future distribution of this species using a correlative maximum entropy approach, using publicly available occurrence information. Future potential distributions were predicted under two representative concentration pathway (RCP) scenarios; RCP 4.5 for low-emissions and RCP 8.5 for high-emissions. Our results indicated a broader current distribution of this species in all directions relative to its currently known extent, and dramatic potential for westward and northward expansion of suitable areas under both climate change scenarios. Implications for disease ecology and public health are discussed.

The effects of climate change on infectious diseases with cutaneous manifestations

Background

Anthropogenic climate change affects the burden of infectious diseases via several interconnected mechanisms. In recent years, there has been greater awareness of the ways in which climate-sensitive infectious diseases pose a growing threat to global public health.

Objective

This study aimed to categorize and describe the effects of climate change on infectious diseases with skin manifestations.

Methods

A scoping review of the MEDLINE and PubMed online databases for climate-sensitive infections was performed in February and March 2020. A representative selection of conditions with skin manifestations was included in this review.

Results

Several representative climate-sensitive infectious diseases were identified in each of the following categories: vector-borne infectious diseases, infectious diseases associated with extreme weather events, and infectious diseases linked to human migration.

Conclusion

Climate variables directly influence the survival and reproduction of infectious microorganisms, their vectors, and their animal reservoirs. Due to sustained warmer temperatures at higher latitudes, climate change has expanded the geographic range of certain pathogenic microbes. More frequent climate change-related extreme weather events create circumstances where existing infectious microorganisms flourish and novel infections emerge. Climate instability is linked to increased human migration, which disrupts health care infrastructure as well as the habitats of microbes, vectors, and animal reservoirs and leads to widespread poverty and overcrowding. Dermatologists should understand that climate change will affect the burden and geographic distribution of infectious diseases, many of which have cutaneous signs and might be encountered in their regular practice.

Spatio-Temporal Dynamics of Tick-Borne Diseases in North-Central Wisconsin from 2000-2016

Lyme disease is a well-recognized public health problem in the USA, however, other tick-borne diseases also have major public health impacts. Yet, limited research has evaluated changes in the spatial and temporal patterns of non-Lyme tick-borne diseases within endemic regions. Using laboratory data from a large healthcare system in north-central Wisconsin from 2000-2016, we applied a Kulldorf's scan statistic to analyze spatial, temporal and seasonal clusters of laboratory-positive cases of human granulocytic anaplasmosis (HGA), babesiosis, and ehrlichiosis at the county level. Older males were identified as the subpopulation at greatest risk for non-Lyme tick-borne diseases and we observed a statistically significant spatial and temporal clustering of cases (p < 0.05). HGA risk shifted from west to east over time (2000-2016) with a relative risk (RR) ranging from 3.30 to 11.85, whereas babesiosis risk shifted from south to north and west over time (2004-2016) with an RR ranging from 4.33 to 4.81. Our study highlights the occurrence of non-Lyme tick-borne diseases, and identifies at-risk subpopulations and shifting spatial and temporal heterogeneities in disease risk. Our findings can be used by healthcare providers and public health practitioners to increase public awareness and improve case detection.

Potential Spatial Distribution of the Newly Introduced Long-horned Tick, Haemaphysalis longicornis in North America

The North American distributional potential of the recently invaded tick, Haemaphysalis longicornis, was estimated using occurrence data from its geographic range in other parts of the world and relevant climatic data sets. Several hundred candidate models were built using a correlative maximum entropy approach, and best-fitting models were selected based on statistical significance, predictive ability, and complexity. The median of the best-fitting models indicates a broad potential distribution for this species, but restricted to three sectors—the southeastern United States, the Pacific Northwest, and central and southern Mexico.

Large-scale health disparities associated with Lyme disease and human monocytic ehrlichiosis in the United States, 2007-2013

Promoting health equity is a fundamental public health objective, yet health disparities remain largely overlooked in studies of vectorborne diseases, especially those transmitted by ticks. We sought to identify health disparities associated with Lyme disease and human monocytic ehrlichiosis, two of the most pervasive tickborne diseases within the United States. We used general linear mixed models to measure associations between county-level disease incidence and six variables representing racial/ethnic and socioeconomic characteristics of counties (percent white non-Hispanic; percent with a bachelors degree or higher; percent living below the poverty line; percent unemployed; percent of housing units vacant; per capita number of property crimes). Two ecological variables important to tick demography (percent forest cover; density of white-tailed deer) were included in secondary analyses to contextualize findings. Analyses included data from 2,695 counties in 37 states and the District of Columbia during 2007-2013. Each of the six variables was significantly associated with the incidence of one or both diseases, but the direction and magnitude of associations varied by disease. Results suggested that the incidence of Lyme disease was highest in counties with relatively higher proportions of white and more educated persons and lower poverty and crime rates; the incidence of human monocytic ehrlichiosis was highest in counties with relatively higher proportions of white and less educated persons, higher unemployment rates and lower crime rates. The percentage of housing units vacant was a strong positive predictor for both diseases with a magnitude of association comparable to those between incidence and the ecological variables. Our findings indicate that racial/ethnic and socioeconomic disparities in disease incidence appear to be epidemiologically important features of Lyme disease and human monocytic ehrlichiosis in the United States. Steps to mitigate encroachment of wild flora and fauna into areas with vacant housing might be warranted to reduce disease risk.

A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Borrelia burgdorferi, causative agent of Lyme disease, in domestic dogs within the contiguous United States

This paper models the prevalence of antibodies to Borrelia burgdorferi in domestic dogs in the United States using climate, geographic, and societal factors. We then use this model to forecast the prevalence of antibodies to B. burgdorferi in dogs for 2016. The data available for this study consists of 11,937,925 B. burgdorferi serologic test results collected at the county level within the 48 contiguous United States from 2011-2015. Using the serologic data, a baseline B. burgdorferi antibody prevalence map was constructed through the use of spatial smoothing techniques after temporal aggregation; i.e., head-banging and Kriging. In addition, several covariates purported to be associated with B. burgdorferi prevalence were collected on the same spatio-temporal granularity, and include forestation, elevation, water coverage, temperature, relative humidity, precipitation, population density, and median household income. A Bayesian spatio-temporal conditional autoregressive (CAR) model was used to analyze these data, for the purposes of identifying significant risk factors and for constructing disease forecasts. The fidelity of the forecasting technique was assessed using historical data, and a Lyme disease forecast for dogs in 2016 was constructed. The correlation between the county level model and baseline B. burgdorferi antibody prevalence estimates from 2011 to 2015 is 0.894, illustrating that the Bayesian spatio-temporal CAR model provides a good fit to these data. The fidelity of the forecasting technique was assessed in the usual fashion; i.e., the 2011-2014 data was used to forecast the 2015 county level prevalence, with comparisons between observed and predicted being made. The weighted (to acknowledge sample size) correlation between 2015 county level observed prevalence and 2015 forecasted prevalence is 0.978. A forecast for the prevalence of B. burgdorferi antibodies in domestic dogs in 2016 is also provided. The forecast presented from this model can be used to alert veterinarians in areas likely to see above average B. burgdorferi antibody prevalence in dogs in the upcoming year. In addition, because dogs and humans can be exposed to ticks in similar habitats, these data may ultimately prove useful in predicting areas where human Lyme disease risk may emerge.

A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Ehrlichia species in domestic dogs within the contiguous United States

Background

Dogs in the United States are hosts to a diverse range of vector-borne pathogens, several of which are important zoonoses. This paper describes factors deemed to be significantly related to the prevalence of antibodies to Ehrlichia spp. in domestic dogs, including climatic conditions, geographical factors, and societal factors. These factors are used in concert with a spatio-temporal model to construct an annual seroprevalence forecast. The proposed method of forecasting and an assessment of its fidelity are described.

Methods

Approximately twelve million serological test results for canine exposure to Ehrlichia spp. were used in the development of a Bayesian approach to forecast canine infection. Data used were collected on the county level across the contiguous United States from routine veterinary diagnostic tests between 2011–2015. Maps depicting the spatial baseline Ehrlichia spp. prevalence were constructed using Kriging and head-banging smoothing methods. Data were statistically analyzed to identify factors related to antibody prevalence via a Bayesian spatio-temporal conditional autoregressive (CAR) model. Finally, a forecast of future Ehrlichia seroprevalence was constructed based on the proposed model using county-level data on five predictive factors identified at a workshop hosted by the Companion Animal Parasite Council and published in 2014: annual temperature, percentage forest coverage, percentage surface water coverage, population density and median household income. Data were statistically analyzed to identify factors related to disease prevalence via a Bayesian spatio-temporal model. The fitted model and factor extrapolations were then used to forecast the regional seroprevalence for 2016.

Results

The correlation between the observed and model-estimated county-by-county Ehrlichia seroprevalence for the five-year period 2011–2015 is 0.842, demonstrating reasonable model accuracy. The weighted correlation (acknowledging unequal sample sizes) between 2015 observed and forecasted county-by-county Ehrlichia seroprevalence is 0.970, demonstrating that Ehrlichia seroprevalence can be forecasted accurately.

Conclusions

The forecast presented herein can be an a priori alert to veterinarians regarding areas expected to see expansion of Ehrlichia beyond the accepted endemic range, or in some regions a dynamic change from historical average prevalence. Moreover, this forecast could potentially serve as a surveillance tool for human health and prove useful for forecasting other vector-borne diseases.

Heterogeneous Associations of Ecological Attributes with Tick-Borne Rickettsial Pathogens in a Periurban Landscape

The variations in prevalence levels of two tick-borne rickettsial pathogens, Ehrlichia chaffeensis and Ehrlichia Ewingii, in a periurban environment were evaluated along with their ecological determinants. Tick life stage and sex, month of tick collection, landscape fragmentation, and ecological covariates specific to pasture and woodland sites were considered as explanatory covariates. Questing lone star ticks (Amblyomma americanum) were collected by flagging for an hour once every week during mid-April through mid-August in years 2013 and 2014. A total of 4357 adult and nymphal ticks (woodland = 2720 and pasture = 1637) were collected and assessed for pathogen prevalence by molecular methods. Female A. americanum ticks were more infected with E. chaffeensis than males or nymphs in woodland areas [♂ = 6.05%; ♀ = 12.0%; nymphs = 2.09%] and pastures [♂ = 8.05%; ♀ = 12.03%; nymphs = 3.33%], and the prevalence was influenced by edge density in the landscape. Higher E. ewingii infection was noted among female A. americanum ticks within woodland areas [♂ = 1.89%; ♀ = 2.14%; nymphs = 1.57%], but no such difference was evident in pastures [♂ = 1.03%; ♀ = 1.33%; nymphs = 1.12%]. Prevalence of E. ewingii was influenced by edge contrast index, and the percentage of pasture perimeter that was less than 20 meters from woodland areas. This study elucidates the complexity of tick-borne pathogen ecology and points to the need for further studies on the role of reservoir hosts, particularly that played by small vertebrates, which is not fully understood in the region.