A descriptive epidemiological study of the incidence of newly diagnosed Lyme disease cases in a UK primary care cohort, 1998-2016.

BACKGROUND: Primary care is likely to see the highest number of Lyme disease patients. Despite this, there is limited published data regarding Lyme disease patients accessing primary care in the UK. We aim to describe trends in the incidence of a new diagnosis, and demographics of patients identified in a primary care electronic health database. METHODS: A descriptive epidemiological study of Lyme disease coded patients in UK primary care. 3725 patients coded for Lyme disease during 1998-2016 were identified within The Health Improvement Network (THIN). Incidence rates and the demographics of cases identified were described. Poisson regression was used to analyse socio-demographic characteristics of the cases. RESULTS: There was an increase in annual crude incidence rates, peaking in 2015 at 5.47 (95% CI 4.85-6.14) cases per 100,000 population per year. Multivariable analysis showed there were significant differences in the ages of those affected, incidence of a new diagnosis rose as deprivation levels improved, and that there was a higher incidence of cases living in rural areas compared to urban areas. There was no significant difference between sexes for the UK. Cases were significantly more likely to identify with being white compared to the national population. CONCLUSIONS: An increasing incidence of patients newly coded with Lyme disease related Read codes was identified using data from a UK national primary care database. By comparing these incidence figures with national laboratory-confirmed surveillance data, a multiplication factor of 2.35 (95%CI 1.81-2.88) can be calculated in order to estimate the annual number of cases seen in primary care. The significant socio-demographic variables associated with a Lyme disease diagnosis likely reflect a complex interplay of socio-economic issues, which needs to be further explored. Future work is needed to examine the treatment and management of patients within this database.

Mapping tweets to a known disease epidemiology; a case study of Lyme disease in the United Kingdom and Republic of Ireland.

BACKGROUND: Analysis of social media is an emerging method with potential as a tool for disease surveillance. Twitter may offer a route for surveillance by using tweeting habits as a proxy for disease incidence. Previous work has focused on temporal patterns and have proven to be successful. However, the identification of geographical patterns has been limited by a combination of Twitter's data collection policies and by exploring diseases that have a high prevalence and high levels of awareness with the public. We propose that, by performing a restricted geographical search strategy on a disease with a relatively low incidence, one may be able to explore spatial patterns. Here, Lyme disease in the United Kingdom and the Republic of Ireland is used as a case example. OBJECTIVE: To explore whether the tweeting habits of British and Irish Twitter users matched the known spatio-temporal epidemiology of Lyme disease in these respective countries. METHODS: All Tweets containing the word 'Lyme' were collected between the 1st of July 2017 and the 30th June 2018, restricted by geography (a 375-mile radius around the geographical centre of Great Britain) and by language (English-only tweets). Tweets were removed which referred to locations that included 'Lyme' within their name (e.g. Lyme Regis). Only original tweets were analysed. Daily and monthly time series were created and compared to national Lyme disease surveillance figures. A map of the number of Twitter users tweeting about Lyme disease per 100,000 population per local authority was created. This was formerly compared to national surveillance data for England and Wales using an exploratory spatial data analysis approach. RESULTS: During the study period, 13,757 original tweets containing the word 'Lyme', and excluding place names relating to Lyme, were collected. The mean number of daily tweets was 38 (range: 12-276). There was strong seasonality with the highest number of tweets in the summer, this matched the known epidemiology of Lyme disease. Of the 5212 of users who tweeted about Lyme disease, 51.8% had a user profile location that could be matched to a local authority in the United Kingdom or Republic of Ireland. The mean number of Twitter users tweeting about Lyme disease per 100,000 population per local authority was 3.7. The areas with the highest incidence were south-west England and the Highlands of Scotland. When comparing these figures to English and Welsh Lyme disease surveillance figures they showed a significant positive spatial correlation (p = 0.002). CONCLUSIONS: The tempo-spatial pattern of Twitter users tweeting about Lyme disease matches the known disease epidemiology. The degree of geographical concordance between Twitter users' locations and national surveillance reports, indicate that Twitter has the potential to be used in to identify potential disease hotspots based on the levels of social media 'noise'. There is scope for further work to test the robustness of Twitter as an adjunct 'measure of concern' disease surveillance tool. However, caution must be taken as national media stories can skew data and Twitter users may not provide reliable facts in the data that they share on the platform.

Characteristics and patient pathways of Lyme disease patients: a retrospective analysis of hospital episode data in England and Wales (1998-2015).

BACKGROUND: Lyme disease is a tick-borne disease of increasing global importance. There is scant information on Lyme disease patient demographics in England and Wales, and how they interact with the National Health Service (NHS). Our aims were to explore the demographic characteristics of Lyme disease patients within the Hospital Episode Statistics (HES) and Patient Episode Database for Wales (PEDW), and to describe patient pathways. METHODS: Data from 1st January 1998 to 31st December 2015 was retrieved from the two administrative hospital datasets (HES and PEDW), based on patients coded with Lyme disease. Information was collected on demographic characteristics, home address and case management. Incidence rates were calculated, and demographics compared to the national population. RESULTS: Within HES and PEDW, 2361 patients were coded with Lyme disease. There was a significant increase (p < 0.01) in incidence from 0.08 cases/100,000 in 1998, to 0.53 cases/100,000 in 2015. There was a bimodal age distribution, patients were predominantly female, white and from areas of low deprivation. New cases peaked annually in August, with higher incidence rates in southern central and western England. Within hospital admission data (n = 2066), most cases were either referred from primary care (28.8%, n = 596) or admitted via accident and emergency (A&E) (29.5%, n = 610). This population entering secondary care through A&E suggest a poor understanding of the recommended care pathways for symptoms related to Lyme disease by the general population. CONCLUSIONS: These data can be used to inform future investigations into Lyme disease burden, and patient management within the NHS. They provide demographic information for clinicians to target public health messaging or interventions.

GP coding behaviour for non-specific clinical presentations: a pilot study.

BACKGROUND: Clinical coding is an integral part of primary care. Disease incidence studies based on primary care electronic health records (EHRs) rely on the accuracy of these codes. Current code validation methods are not appropriate for non-specific conditions and provide limited information about GPs' decision-making behaviour around coding. Qualitative methods could offer insight into decision-making behaviour around coding of patients with non-specific conditions. AIM: To investigate the decision-making behaviour of GPs when applying Read codes to non-specific clinical presentations, using Lyme disease as a case example. DESIGN & SETTING: A pilot study was undertaken, involving masked semi-structured interviews of eight GPs in the North West of England. METHOD: Semi-structured interviews were carried out based on 11 clinical cases representative of Lyme disease presentations. Discrete answers were described descriptively. Interview transcripts were analysed using a thematic approach. RESULTS: Themes underpinning GPs' coding behaviour included: GP personal and professional experience; clinical evidence; diagnostic uncertainty; professional integrity and defensive practice; and patient-sourced health information and beliefs. GPs placed Lyme disease on their differential diagnosis list for five cases; in only two cases would GPs select a Lyme disease related Read code. CONCLUSION: GPs were reluctant to code with specific diagnostic Read codes when they were presented with patients with vague or unfamiliar symptomology. This masked questionnaire methodology offers a new approach to validate incidence figures, based on Read codes of non-specific conditions. The reluctance to code poses many problems for primary care EHRs research. Further research is needed to understand what drives GPs' coding behaviour.

Study of general practitioner consultations for tick bites at high, medium and low incidence areas for Lyme borreliosis in England and Wales.

Lyme borreliosis (LB) is a tick-borne disease caused by Borrelia burgdorferi sensu lato complex. In Europe, it is predominately transmitted by the sheep tick, Ixodes ricinus. Compared with other European countries, the United Kingdom (UK) is considered to have a low incidence of LB, although this varies regionally. To determine whether an association exists between tick bite consultations and LB incidence in the UK, retrospective questionnaires were sent to general practitioners (GPs) in high (Wiltshire), medium (Cumbria) and low (Wales) incidence areas. During 2011, the greatest incidence of consultations for tick bites was reported by GPs in Cumbria (204 consultations per 100,000 inhabitants), followed by Wiltshire (160 per 100,000 population) and Wales (54 per 100,000 population). In Wiltshire and Cumbria, GPs predominantly provided advice on tick removal, whilst Welsh GPs mostly advised patients on tick bite prevention. Focusing on Cumbria during 2011-2013, 72.5% of GPs removed ticks from patients (incidence of 101 consultations per 100,000 population), and more GPs diagnosed LB based on clinical features than laboratory-confirmed diagnoses. To date, this is the first study to investigate the incidence of tick bite consultations and LB in England and Wales.

The demographics and geographic distribution of laboratory-confirmed Lyme disease cases in England and Wales (2013-2016): an ecological study.

OBJECTIVE: Lyme disease is a tick-borne disease of increasing incidence and public concern across the Northern Hemisphere. However, the socio-demographics and geographic distribution of the population affected in England and Wales are poorly understood. Therefore, the proposed study was designed to describe the demographics and distribution of laboratory-confirmed cases of Lyme disease from a national testing laboratory. DESIGN: An ecological study of routinely collected laboratory surveillance data. SETTING: Public Health England's national Lyme disease testing laboratory. PARTICIPANTS: 3986 laboratory-confirmed cases of Lyme disease between 2013 and 2016. RESULTS: In England and Wales, the incidence of laboratory-confirmed Lyme disease rose significantly over the study period from 1.62 cases per 100 000 in 2013 to 1.95 cases per 100 000 in 2016. There was a bimodal age distribution (with peaks at 6-10 and 61-65 years age bands) with a predominance of male patients. A significant clustering of areas with high Lyme disease incidence was located in southern England. An association was found between disease incidence and socioeconomic status, based on the patient's resident postcode, with more cases found in less deprived areas. Cases were disproportionately found in rural areas compared with the national population distribution. CONCLUSIONS: These results suggest that Lyme disease patients originate from areas with higher socioeconomic status and disproportionately in rural areas. Identification of the Lyme disease hotspots in southern England, alongside the socio-demographics described, will enable a targeted approach to public health interventions and messages.