Cases Of Lyme Disease Research Articles

1206. Effects of Climatic Variability on Lyme Disease Outbreaks in California

BackgroundClimate change has increased the risk of tick borne infections. The life cycle and prevalence of deer ticks are strongly influenced by temperature. Warmer temperatures associated with climate change are projected to increase the range of suitable tick habitats driving the spread of Lyme disease (LD). Short winters could also increase tick activity increasing the risk of exposure. This study examines the relationship between LD incidence and temperature-precipitation and their anomalies in CA counties.MethodsTrends and relationships of Lyme Disease (LD) cases and climatic factors were analyzed among the California counties from 2000 to 2019. Lyme disease tabulate data and climatic data were obtained from Centers for Disease Control, and NOAA, and Climate Data Guide respectively. Canonical correspondence analysis (CCA) was performed using variables: (i) LD cases, (ii) precipitation & anomaly, and temperature & anomaly. The CCA ordination explained the variability between LD cases and climatic variables. Biplots were used to visualize the associations between LD cases and climatic anomalies.ResultsWe compared the countywide LD cases in relation to climatic factors in California from 2000 to 2019. A total of 96 cases in 2000, 117 cases in 2009, and 144 cases in 2019 were reported in the 55 counties of California. Santa Clara reported the highest LD cases in 2003 (23 cases; 16%), followed by Los Angeles in 2013 (20 cases; 18%) and Santa Cruz in 2017 (19 cases; 13%). CCA ordination showed distinguishable clustering patterns between southern California counties (Santa Clara, Santa Cruz, Alameda, and San Diego) and northern coast and Klamath mountains range (Humboldt, Trinity, Shasta, and Siskiyou) regions (Fig. 1). Moderate mean annual temperature (56.5 °F - 62.5 °F) and temperature anomaly (3.8 °F - 5.5 °F) were the most important variable predictor for high LD outbreak. The CCA ordination shows the relationships between Lyme Disease and climatic variables for the 55 Counties of California. The bottom right circle represents Lyme cases positively correlated with temperature anomaly (3.8 °F - 5.5 °F) and moderate annual mean temperature (56.5 °F - 62.5 °F). The upper left circle represents Lyme cases negatively correlated with mean annual precipitation.ConclusionModerate temperature with low moist spell anomalies in the south neighboring CA counties showed a positive influence on LD outbreak. The climatic conditions in those areas suitable for Oak trees and masting acorn resulting in the establishment of tick and host (deer) populations. We recommend robust surveillance and lab testing for patients with a history of tick bites in these regions.Disclosures All Authors: No reported disclosures

LB17. Immunosequencing of the T-Cell Receptor Repertoire Reveals Signatures Specific for Diagnosis and Characterization of Early Lyme Disease

BackgroundChanging climate and demographic trends have led to recent increases in the incidence of tick-borne illnesses. Early diagnosis of Lyme disease (LD) is critical for initiation of antibiotics to mitigate symptoms and prevent late manifestations. In patients not presenting with a typical erythema migrans rash, 2-tiered serologic testing is recommended to support a diagnosis of LD. However, 2-tiered testing is limited by ambiguity in interpretation and low sensitivity in early disease, highlighting an unmet clinical need for alternative diagnostic approaches. We identified a clinical signal for early LD based on evaluation of the T-cell response to B. burgdorferi infection.MethodsWe immunosequenced T-cell receptor (TCR) repertoires in blood samples from 3 independent cohorts of patients with laboratory-confirmed or clinically diagnosed early LD and endemic/non-endemic controls to identify 251 public, LD-associated TCRs. These TCRs were used to train a classifier that identified early LD with 99% specificity. Classifier sensitivity was evaluated in 211 LD cases and 2631 endemic controls and compared to that of standard 2-tiered testing (STTT). Biologic specificity was assessed by correlating TCR assay scores with clinical measures and by mapping the antigen specificity of Lyme-associated TCRs to B. burgdorferi antigens.Figure 1. LD-associated TCRs distinguish cases (orange) from controls (blue) in training cohorts. (A) Logistic-growth curve used to define a scoring function. (B) Positive-call threshold (99th percentile in endemic controls). ResultsIn early LD, TCR testing demonstrated a 1.9-fold increase in sensitivity compared to STTT (56% vs 30%), with a 3.1-fold increase ≤4 days from the onset of symptoms (44% vs 14%). TCR positivity predicted subsequent seroconversion in 37% of initially STTT-negative patients, suggesting the T-cell response is detectable before the humoral response. While positivity for both tests declined following treatment, greater declines in posttreatment sensitivity were observed for STTT compared to TCR testing. Higher TCR scores were associated with measures of disease severity, including abnormal liver function tests, disseminated rash, and number of symptoms. A subset of LD-associated TCRs mapped to B. burgdorferi antigens, demonstrating the high specificity of a TCR immunosequencing approach. Figure 2. Validation of the TCR classifier in the JHU cohort and other holdout endemic controls. Distribution of model scores (A) and assay sensitivity (B). Model scores (C) and ROC (D) curves by serostatus. Figure 3. Clinical correlates of TCR scoring. (A) Liver function test; (B) lymphocyte count, (C) rash presentation, (D) number of symptoms. ConclusionT-cell-based testing has potential clinical utility as a sensitive and specific diagnostic for early LD, particularly in the initial days of illness.Disclosures Sudeb C. Dalai, MD, PhD, Adaptive Biotechnologies (Employee, Shareholder) Julia Greissl, PhD, Microsoft (Employee, Shareholder) Mitch Pesesky, PhD, Adaptive Biotechnologies (Employee, Shareholder) Allison W. Rebman, MPH, Global Lyme Alliance (Research Grant or Support)Steven and Alexandra Cohen Foundation (Research Grant or Support) Mark J. Soloski, PhD, NIH grant P30 AR070254 (Grant/Research Support)Steven and Alexandra Cohen Foundation (Research Grant or Support) Elizabeth J. Horn, PhD, Adaptive Biotechnologies (Research Grant or Support)Bay Area Lyme Foundation (Research Grant or Support)Lyme Disease Biobank (Employee)Steven and Alexandra Cohen Foundation (Research Grant or Support) Jennifer N. Dines, MD, Adaptive Biotechnologies (Employee, Shareholder) Rachel M. Gittelman, PhD, Adaptive Biotechnologies (Employee, Shareholder) Thomas M. Snyder, PhD, Adaptive Biotechnologies (Employee, Shareholder) Ryan O. Emerson, PhD, Adaptive Biotechnologies (Other Financial or Material Support, Employment with Adaptive Biotechnologies during the time of this study) Edward Meeds, PhD, Microsoft (Employee, Shareholder) Thomas Manley, MD, Adaptive Biotechnologies (Other Financial or Material Support, Declares employment with Adaptive Biotechnologies during the time of this study) Ian M. Kaplan, PhD, Adaptive Biotechnologies (Employee, Shareholder) Lance Baldo, MD, Adaptive Biotechnologies (Employee, Shareholder, Leadership Interest) Jonathan M. Carlson, PhD, Microsoft (Employee, Shareholder) Harlan S. Robins, PhD, Adaptive Biotechnologies (Board Member, Employee, Shareholder) John Aucott, MD, Adaptive Biotechnologies (Advisor or Review Panel member)Bay Area Lyme Foundation (Other Financial or Material Support, Scientific Advisory Board member)Department of Health and Human Services (Other Financial or Material Support, Past Chair, 2018, HHS Tick-borne Disease Working Group, Office of HIV/AIDS and Infectious Disease Policy, Office of the Assistant Secretary of Health)Expert testimony (Other Financial or Material Support, Expert testimony)Global Lyme Alliance (Research Grant or Support)Pfizer (Consultant)Steven and Alexandra Cohen Foundation (Research Grant or Support)Tarsus Pharmaceuticals (Consultant)

Risk factors for Lyme disease stage and manifestation using electronic health records

BackgroundLittle is known about risk factors for early (e.g., erythema migrans) and disseminated Lyme disease manifestations, such as arthritis, neurological complications, and carditis. No study has used both diagnoses and free text to classify Lyme disease by disease stage and manifestation.MethodsWe identified Lyme disease cases in 2012–2016 in the electronic health record (EHR) of a large, integrated health system in Pennsylvania. We developed a rule-based text-matching algorithm using regular expressions to extract clinical data from free text. Lyme disease cases were then classified by stage and manifestation using data from both diagnoses and free text. Among cases classified by stage, we evaluated individual, community, and health care variables as predictors of disseminated stage (vs. early) disease using Poisson regression models with robust errors. Final models adjusted for sociodemographic factors, receipt of Medical Assistance (i.e., Medicaid, a proxy for low socioeconomic status), primary care contact, setting of diagnosis, season of diagnosis, and urban/rural status.ResultsAmong 7310 cases of Lyme disease, we classified 62% by stage. Overall, 23% were classified using both diagnoses and text, 26% were classified using diagnoses only, and 13% were classified using text only. Among the staged diagnoses (n = 4530), 30% were disseminated stage (762 arthritis, 426 neurological manifestations, 76 carditis, 95 secondary erythema migrans, and 76 other manifestations). In adjusted models, we found that persons on Medical Assistance at least 50% of time under observation, compared to never users, had a higher risk (risk ratio [95% confidence interval]) of disseminated Lyme disease (1.20 [1.05, 1.37]). Primary care contact (0.59 [0.54, 0.64]) and diagnosis in the urgent care (0.22 [0.17, 0.29]), compared to the outpatient setting, were associated with lower risk of disseminated Lyme disease.ConclusionsThe associations between insurance payor, primary care status, and diagnostic setting with disseminated Lyme disease suggest that lower socioeconomic status and less health care access could be linked with disseminated stage Lyme disease. Intervening on these factors could reduce the individual and health care burden of disseminated Lyme disease. Our findings demonstrate the value of both diagnostic and narrative text data to identify Lyme disease manifestations in the EHR.

Outer Surface Protein C Typing of Borrelia burgdorferi in the Tick Populations of the Upper Susquehanna River Basin, New York

Lyme disease, the most common zoonotic disease in the United States, is caused by the spirochete <em>Borrelia burgdorferi</em>. In order to manage and confront the notable rise in Lyme disease cases, it is crucial to cultivate a deeper understanding of <em>B. burgdorferi</em> and its genes. The outer surface protein C (<em>ospC</em>) gene is highly polymorphic and commonly used as a genetic marker due to its crucial role in establishing mammalian infection. We report novel data on the prevalence of <em>B. burgdorferi ospC genotypes</em> in the infected tick populations of the Upper Susquehanna River Basin of New York State. DNA extracted from 266 <em>Ixodes scapularis, the </em>blacklegged ticks, were tested for the presence of <em>ospC</em> gene and the positive samples were subjected to sequencing. The specific <em>ospC </em>genotype was identified for 56 positive samples which were infected with B. <em>burgdorferi</em> representing a single <em>ospC</em> genotype. A total of 12 <em>ospC </em>genotypes were identified in the 56 ticks, with genotypes I, K, and A being the most prevalent across the Upper Susquehanna River Basin with little variation among the six counties. The frequency distribution of <em>ospC </em>variants in this region is significantly different from the few previously studied regions in the Northeast. This research will have implications in the public health sector by providing assessment for Lyme disease risk in the Upper Susquehanna River Basin and insight into strain specific vaccines based on OspC. Further research can be done into the dispersion pattern of <em>B. burgdorferi </em>within the Upper Susquehanna River Basin, while also replicating this study for other regions.

Lyme disease in Poland in 2019.

Lyme disease is caused by Borrelia spirochetes transmitted by ticks of the genus Ixodes. In Poland, Lyme disease is the most common tick-borne disease. The entire territory of Poland is recognized by ECDC as an endemic area of Lyme disease. Environmental factors and climate change are responsible for the increase in the number of tick habitats, which leads to an increased risk of Lyme disease. The aim of the study is to present the epidemiological situation of Lyme disease in Poland in 2019 compared to the previous year. The analysis of the epidemiological situation of Lyme disease in Poland was based on data sent to NIPH NIH - NRI by voivodeship sanitary-epidemiological stations and published in the bulletin "Infectious diseases and poisoning in Poland in 2019." In 2019, 20,630 cases of Lyme disease were registered, and 1,701 people were hospitalized. Compared to 2018, there was a shift in the incidence from the first and second quarter to the fourth quarter. The highest incidence of 107.7 / 100,000 population was recorded in the Podlaskie voivodeship, which has belonged to the voivodeships with the highest incidence in the country for many years. Despite an increase in the total number of cases by 2.4% compared to 2018, the percentage of hospitalized cases was lower than in the previous year. Difficulties in the diagnosis of Lyme disease make it impossible to define an unequivocal trend in the epidemiological situation in Poland. A slight increase in the incidence may result from the growing number of infected ticks and a better understanding of the problem of Lyme diagnosis by doctors.

Post-Treatment Lyme Disease Syndrome: Need for Diagnosis and Treatment.

With the continued surge in Lyme disease cases, post-treatment Lyme disease syndrome (PTLDS) is becoming a more pressing health concern. The aim of this review is to identify comprehensive treatment strategies for PTLDS patients. Unfortunately, universal guidelines for diagnosing and treating PTLDS do not currently exist. Consequently, physicians cannot adequately address concerns of possible PTLDS patients. Patients are left suffering and searching for answers, and their activities of daily living and quality of life are adversely impacted. This review highlights that PTLDS clinical trials have focused mainly on treatment with antibiotics, yielding challenging results that lack consistency in inclusion criteria across trials. It will remain exceedingly difficult to extrapolate the outcomes of such studies if a standard for PTLDS diagnosis is not well-established. By focusing on treatment trials rather than establishing diagnostic criteria, research in this field ignores a critical step in investigating PTLDS. The first significant step is to create comprehensive guidelines for the diagnosis of PTLDS, which can generate uniformity and validate PTLDS treatment trials.

Tick abundance and life-stage segregation on the American black bear (Ursus americanus).

Tick abundance and diagnosed cases of tick-borne diseases have been increasing in the United States. American black bear (Ursus americanus) populations have also been increasing in the eastern United States. As a competent host of several species of ticks and a mammal capable of traveling long distances, the role of black bears as hosts for ticks requires further evaluation. Ectoparasite surveys were conducted on black bears in Pennsylvania to evaluate tick presence, abundance, spatial distribution, and association with Sarcoptes scabiei, the etiological agent of sarcoptic mange, on bears to better understand their role in tick ecology and to improve on-host surveillance techniques. Tick burden was evaluated using standard area sampling (10.16 × 10.16 cm squares) on pre-designated body regions on black bears from June 2018–December 2019. In total, 278 unique individual black bears were evaluated, with all ticks identified as Ixodes scapularis (n = 1976; 76.7% adults, 23.3% immatures). Tick presence differed by body region on bears, with the highest percentage of tick observations located on bear ears and muzzle. Ticks also partitioned on black bears by life-stage, with immature ticks primarily recorded on the lower extremities of bears and adult ticks primarily recorded on the front-quarters of bears. This includes the first known record of I. scapularis larvae parasitizing black bears, and observations of all three mobile life-stages concurrently parasitizing bears. Tick abundance was also statistically significant dependent on season, with the highest abundance of ticks recorded in spring and lowest abundance in fall. Adult ticks were less likely to be present on bears with mange. These data reveal the important role black bears may serve in tick ecology and dispersal as all three mobile life-stages of I. scapularis were found parasitizing a mammal capable of traveling far distances in a region with high numbers of Lyme disease cases.

Two-Tier Lyme Disease Serology in Children with Previous Lyme Disease

Background: A history of Lyme disease can complicate the interpretation of Lyme disease serology in acutely symptomatic patients. Materials and Methods: We prospectively enrolled children undergoing evaluation for Lyme disease in the emergency department of one of eight participating Pedi Lyme Net centers. We selected symptomatic children with a Lyme disease history (definite, probable, or none) as well as an available research biosample. We defined a Lyme disease case with either an erythema migrans (EM) lesion or positive two-tier serology with compatible symptoms. Using a generalized estimating equation, we examined the relationship between time from previous Lyme disease diagnosis and current Lyme disease after adjustment for patient demographics and symptoms as well as clustering by center. Results: Of 2501 prospectively enrolled study patients, 126 (5.0%) reported a history of definite or probable Lyme disease. Of these children with previous Lyme disease, 47 met diagnostic criteria for Lyme disease at the time of enrollment (37.3%; 95% confidence interval [CI] 29.1-45.7%); 2 had an EM lesion, and 45 had positive two-tier Lyme disease serology. Over time from the previous Lyme disease diagnosis, the less likely the patient met diagnostic criteria for Lyme disease (adjusted odds ratio 0.62 per time period; 95% CI 0.46-0.84). Conclusions: For children with a history of Lyme disease before enrollment, one-third met the diagnostic criteria for acute Lyme disease with a declining rate over time from previous Lyme disease diagnosis. Novel Lyme disease diagnostics are needed to help distinguish acute from previous Lyme disease.

Estimating the population health burden of Lyme disease in Ontario, Canada: a microsimulation modelling approach.

Background:If untreated, Lyme disease can lead to long-term sequelae and post-treatment Lyme disease syndrome (PTLDS), resulting in reduced health-related quality of life. The objective of this study was to develop a microsimulation model to estimate the population-level health burden of Lyme disease in Ontario, Canada.Methods:We developed a Lyme disease history model using microsimulation, simulating 100 000 people (mean age 37.6 yr, 51% female) from 2017 in Ontario over a lifetime risk of infection and time horizon. We extracted the sensitivity and specificity of the 2-tier testing recommended by the Canadian Public Health Laboratory Network, probabilities and health state utility values from the published literature and health administrative data. Our reported outcomes from our stochastic analysis include diagnosed cases of Lyme disease (stratified by stage), undiagnosed infections, sequelae, individuals with PTLDS and quality-adjusted life-years (QALYs) lost.Results:Our model estimated 333 (95% confidence interval [CI] 329–337) infections over the lifetime of 100 000 simulated people (mean age 37.6 yr, 51% female), with 92% (95% CI 91%–93%) of infections diagnosed. Of those 308 people with Lyme Disease diagnoses, 67 (95% CI 65–69) developed sequelae (e.g., arthritic, cardiac, neurologic sequelae), and 34 (95% CI 33–35) developed PTLDS. Lyme disease resulted in a loss of 84.5 QALYs (95% CI 82.9–86.2) over the lifetime of the simulated cohort. Sensitivity and scenario analysis showed that increasing incidence rates of Lyme disease, potential underreporting, duration of PTLDS and quality of life (health state utility) associated with PTLDS had the greatest impact on health burden.Interpretation:Lyme disease contributes considerable health burden in terms of QALYs lost. Our analysis provides evidence to understand the disease burden and lays the foundation to assess the cost-effectiveness of pharmaceutical and nonpharmaceutical interventions.

Effects of COVID-19 Pandemic on Reported Lyme Disease, United States, 2020

Surveys indicate US residents spent more time outdoors in 2020 than in 2019, but fewer tick bite–related emergency department visits and Lyme disease laboratory tests were reported. Despite ongoing exposure, Lyme disease case reporting for 2020 might be artificially reduced due to coronavirus disease–associated changes in healthcare-seeking behavior.

Эпидемиологические и эпизоотические особенности болезни Лайма в 2019 году в Украине

Актуальность. Наличие семи видов Borrelia burgdorferi s.l. с патогенным потенциалом в Украине оставляет актуальным проведение ежегодного анализа заболевания болезнью Лайма. Цель: проанализировать эпидемиологические и эпизоотические особенности болезни Лайма в 2019 году в Украине. Материалы и методы. Использовались государственные отраслевые статистические отчеты. Для статистического анализа применялись пакеты R-3.5.1 и Past 3.17. Результаты. В 2019 году пик заболевания сместился на июль. Среди больных доля детей в возрасте до 4 лет уменьшилась в 3,5 раза и в 5,67 раза — доля детей школьного возраста. Возросло количество больных мужчин. В 2 раза увеличился процент людей с тяжелым течением болезни и достиг показателя в 1,87 %. За пределами Украины заразились люди в 103 случаях на территории 21 государства мира. Приведен алгоритм действий после обнаружения присосавшегося иксодового клеща. Выводы. В 2019 году зарегистрировано 4482 случая заболевания болезнью Лайма (10,62 на 100 тыс.). Интенсивный показатель по Украине превышен в 10 областях и г. Киеве. Удельный вес заболеваемости жителей городов постепенно уменьшается.

The impact of Pandemic COVID-19 on cases of Borreliosis infection in 2020

Borreliosis (Lyme borreliosis; Lyme disease) is a zoonotic disease caused by spirochetes from the genus Borrelia. In humans, the accidental host of ticks, the infection is transmitted by the bite of the tick - the spirochetes are present in the salivary glands of the tick. Any of the three forms of tick: larva, nymph and adult can be responsible for infection. The most common threats to humans are Borrelia burgdorferii sensu stricto, Borrelia garinii and Borrelia afzelii occurring mainly in Europe. Lyme disease is a complex, multi-stage disease and progresses in 3 stages. The targeted treatment of Lyme disease is based on the administration of antibiotics. The introduction of antibiotics in the early stages of Lyme borreliosis offers a good chance of a complete cure. Lyme disease is a major epidemiological problem in the world. In Europe, the average number of cases per year remains at 65,400. In Poland, the number of infections annually reaches several tens of thousands. According to the National Institute of Hygiene of Poland, which keeps statistics of epidemiological reports, a total of 83,495 people fell sick with Lyme disease in Poland between 2016 and 2019. Whereas in 2020, the number of cases of Lyme disease decreased to 12933. The reason for this is undoubtedly the COVID-19 pandemic, which has dominated health care and focused all the attention of medical workers. This review shows that Lyme borreliosis is a dangerous disease with a high risk of complications. A quick diagnosis is crucial in the therapeutic process. An algorithm should be developed in order to distinguish other diseases from Lyme disease and thus enable an early reaction and treatment.

Spatio-temporal modeling for confirmed cases of lyme disease in Virginia

Epidemiological data often include characteristics such as spatial and/or temporal dependencies and excess zero counts, which pose modeling challenges. Excess zeros in such data may arise from imperfect detection and/or relative rareness of the disease in a given location. Here, we studied the spatio-temporal variation in annual Lyme disease cases in Virginia from 2001-2016 and modeled the disease with a spatio-temporal hierarchical Bayesian model. Using observed ecological and environmental covariates, we constructed a predictive model for the disease spread over space and time, including spatial and temporal random effects. We considered several different models and found that the negative binomial hurdle model performs the best for such epidemiological data. Among the various ecological predictors, the North-South (V component) of winds and relative humidity significantly contributed to predicting the Lyme cases. Our model results provide important insights on the spread of the disease in Virginia and the proposed modeling framework offers epidemiologists and health policymakers a useful tool for improving disease preparedness and control plans for the future.

COVID-19 and the Consequences of Anchoring Bias.

Suspicion of coronavirus disease in febrile patients might lead to anchoring bias, causing misdiagnosis of other infections for which epidemiologic risks are present. This bias has potentially severe consequences, illustrated by cases of human granulocytic anaplasmosis and Lyme disease in a pregnant woman and human granulocytic anaplasmosis in another person.

Relations of peri-residential temperature and humidity in tick-life-cycle-relevant time periods with human Lyme disease risk in Pennsylvania, USA

How weather affects tick development and behavior and human Lyme disease remains poorly understood. We evaluated relations of temperature and humidity during critical periods for the tick lifecycle with human Lyme disease. We used electronic health records from 479,344 primary care patients in 38 Pennsylvania counties in 2006–2014. Lyme disease cases (n = 9657) were frequency-matched (5:1) by year, age, and sex. Using daily weather data at ~4 km2 resolution, we created cumulative metrics hypothesized to promote (warm and humid) or inhibit (hot and dry) tick development or host-seeking during nymph development (March 1–May 31), nymph activity (May 1–July 30), and prior year larva activity (Aug 1–Sept 30). We estimated odds ratios (ORs) of Lyme disease by quartiles of each weather variable, adjusting for demographic, clinical, and other weather variables. Exposure-response patterns were observed for higher cumulative same-year temperature, humidity, and hot and dry days (nymph-relevant), and prior year hot and dry days (larva-relevant), with same-year hot and dry days showing the strongest association (4th vs. 1st quartile OR = 0.40; 95% confidence interval [CI] = 0.36, 0.43). Changing temperature and humidity could increase or decrease human Lyme disease risk.

Changing Trends in Age and Sex Distributions of Lyme Disease-United States, 1992-2016.

Lyme disease is the most common vector-borne disease in the United States and is characterized by a bimodal age distribution and male predominance. We examined trends in reported cases during a 25-year period to describe changes in the populations most affected by Lyme disease in the United States. We examined demographic characteristics of people with confirmed cases of Lyme disease reported to the Centers for Disease Control and Prevention during 1992-2016 through the National Notifiable Diseases Surveillance System. We grouped cases into 5-year periods (1992-1996, 1997-2001, 2002-2006, 2007-2011, 2012-2016). We calculated the average annual incidence by age and sex and used incidence rate ratios (IRRs) to describe changes in Lyme disease incidence by age and sex over time. We converted patient age at time of illness into patient birth year to ascertain disease patterns according to birth cohorts. The incidence of Lyme disease in the United States doubled from 1992-1996 to 2012-2016 (IRR = 1.74; 95% CI, 1.70-1.78) and increased disproportionately among males; IRRs were 39%-89% higher among males than among females for most age groups. During the study period, children aged 5-9 years were most frequently and consistently affected. In contrast, the average age of adults with Lyme disease increased over time; of all adults, people born during 1950-1964 were the most affected by Lyme disease. Our findings suggest that age-related behaviors and susceptibilities may drive infections among children, and the shifting peak among adults likely reflects a probability proportional to the relative size of the baby boom population. These findings can inform targeted and efficient public health education and intervention efforts.

Tick-Borne Surveillance Patterns in Perceived Non-Endemic Geographic Areas: Human Tick Encounters and Disease Outcomes.

Recent scholarship supports the use of tick bite encounters as a proxy for human disease risk. Extending entomological monitoring, this study was designed to provide geographically salient information on self-reported tick bite encounters by survey respondents who concomitantly reported a Lyme disease (LD) diagnosis in a state perceived as non-endemic to tick-borne illness. Focusing on Texas, a mixed-methods approach was used to compare data on tick bite encounters from self-reported LD patients with county-level confirmed cases of LD from the U.S. Centers for Disease Control and Prevention (CDC), as well as serological canine reports. A greater proportion of respondents reported not recalling a tick bite in the study population, but a binomial test indicated that this difference was not statistically significant. A secondary analysis compared neighboring county-level data and ecological regions. Using multi-layer thematic mapping, our findings indicated that tick bite reports accurately overlapped with the geographic patterns of those patients previously known to be CDC-positive for serological LD and with canine-positive tests for Borrelia burgdorferi, anaplasmosis, and ehrlichiosis, as well as within neighboring counties and ecological regions. LD patient-reported tick bite encounters, corrected for population density, also accurately aligned with official CDC county hot-spots. Given the large number of counties in Texas, these findings are notable. Overall, the study demonstrates that direct, clinically diagnosed patient reports with county-level tick bite encounter data offer important public health surveillance measures, particularly as it pertains to difficult-to-diagnose diseases where testing protocols may not be well established. Further integration of geo-ecological and socio-demographic factors with existing national epidemiological data, as well as increasingly accessible self-report methods such as online surveys, will contribute to the contextual information needed to organize and implement a coordinated public health response to LD.

The Keds Are Alright: Community Collection of Ticks (Ixodida: Ixodidae) and Keds (Diptera: Hippoboscidae) From Hunter-Harvested Deer

Abstract Deer keds [Lipoptena cervi (L. 1758)] are ectoparasitic and hematophagous dipterans. Originally native to Northern Europe, L. cervi records in the United States begin in 1907 when they were found in Pennsylvania and New Hampshire. Subsequently, they have been recorded from several states and parasitize many native cervids (Artiodactyla: Cervidae) including white-tailed deer [Odocoileus virginianus (Zimmerman 1780)]. Concurrently, blacklegged ticks [Ixodes scapularis (Say 1821)], and cases of Lyme disease are increasing in prevalence in the Northeast. The continued expansion and increase in vectors and vector-borne diseases present an opportunity for study and community outreach. We used a combination of active and passive collection techniques, using deer hunters as community scientists, to collect ectoparasites of deer in Pennsylvania over two hunting seasons (2018–2019, 2019–2020). Community scientists were recruited through Facebook groups, e-mail, and hunting clubs. In total, 1,226 L. cervi and 1,954 I. scapularis were collected from white-tailed deer harvested by the community and deer processors across both hunting seasons. The community collected 298 L. cervi and 472 I. scapularis during the 2018–2019 season. In the same season, 529 L. cervi and 577 I. scapularis were collected from deer processors. For the 2019–2020 season, 225 L. cervi and 381 I. scapularis were collected by the community and 174 L. cervi and 524 I. scapularis were collected from deer processors. Benefits and drawbacks were identified for each collection method and a combination of both methods was found to be most effective in gathering specimens without sacrificing standardization.

Environmental Correlates of Lyme Disease Emergence in Southwest Virginia, 2005-2014.

Lyme disease is the most common tick-borne disease in North America. Though human infection is mostly transmitted in a limited geography, the range has expanded in recent years. One notable area of recent expansion is in the mountainous region of southwestern Virginia. The ecological factors that facilitate or constrain the range of human Lyme disease in this region remain uncertain. To evaluate this further, we obtained ecological data, including remotely sensed data on forest structure and vegetation, weather data, and elevation. These data were aggregated within the census block groups of a 9,153 km2 area around the cities of Blacksburg and Roanoke, VA, an area with heterogeneous Lyme disease transmission. In this geographic area, 755 individuals were reported to have Lyme disease in the 10 yr from 2006 to 2015, and these cases were aggregated by block group. A zero-inflated negative binomial model was used to evaluate which environmental variables influenced the abundance of Lyme disease cases. Higher elevation and higher vegetation density had the greatest effect size on the abundance of Lyme disease. Measures of forest edge, forest integrity, temperature, and humidity were not associated with Lyme disease cases. Future southward expansion of Lyme disease into the southeastern states may be most likely in ecologically similar mountainous areas.

Prevalence and prediction of Lyme disease in Hainan province.

Lyme disease (LD) is one of the most important vector-borne diseases worldwide. However, there is limited information on the prevalence and risk analysis using correlated factors in the tropical areas. A total of 1583 serum samples, collected from five hospitals of Hainan Province, were tested by immunofluorescence assay (IFA) and western blot (WB) analyses using anti-Borrelia burgdorferi antibodies. Then, we mapped the distribution of positive rate (by IFA) and the spread of confirmed Lyme patients (by WB). Using ArcGIS, we compiled host-vector-human interactions and correlated data as risk factor layers to predict LD risk in Hainan Province. There are three LD hotspots, designated hotspot I, which is located in central Hainan, hotspot II, which contains Sanya district, and hotspot III, which lies in the Haikou-Qiongshan area. The positive rate (16.67% by IFA) of LD in Qiongzhong, located in hotspot I, was higher than that in four other areas. Of confirmed cases of LD, 80.77% of patients (42/52) whose results had been confirmed by WB were in hotspots I and III. Hotspot II, with unknowed prevalence of LD, need to be paid more attention considering human-vector interaction. Wuzhi and Limu mountains might be the most important areas for the prevalence of LD, as the severe host-vector and human-vector interactions lead to a potential origin site for LD. Qiongzhong is the riskiest area and is located to the east of Wuzhi Mountain. In the Sanya and Haikou-Qiongshan area, intervening in the human-vector interaction would help control the prevalence of LD.