First report of Lyme disease in Nepal

Lyme Borreliosis, a public health concern in India: Findings of Borrelia burgdorferi serosurvey from two states

Background

Lyme borreliosis is a public health concern in India. The prevalence of the disease is still undetermined with major entomological and epidemiological gaps. The present study was conducted to determine the seropositivity of Borrelia burgdorferi in Sikkim and Arunachal Pradesh, India.

Methods

A cross-sectional serosurvey was conducted in Sikkim and Arunachal Pradesh. Data collection tools were developed and standardized for the collection of clinico-socio-demographic data. Sample size for each site was calculated using the formula for the estimation of a single proportion. Qualitative detection of IgG antibodies in serum samples was done using NovaLisa™ Lyme Borrelia IgG ELISA kit.

Results

A total of 793 participants were enrolled, 484 (61%) from Arunachal Pradesh and 309 (39%) from Sikkim. Out of 793 participants, 21 (2.7%), 22 (2.8%), 6 (0.8%), 29 (3.7%), 44 (5.5%), and 16 (2.1%) gave history of tick bite, rash, erythema migrans, migratory muscle pain, migratory joint pain, and numbness, respectively, in the past one year. The adjusted seroprevalence (for sensitivity and specificity of kit) for the study is 3.7 (2.4-5.2). No signs or symptoms were found to be associated with IgG ELISA positivity. The state-wise distribution of seropositivity for Arunachal Pradesh and Sikkim was 4.1 (95% CI: 2.5-6.3) and 2.3 (95% CI: 0.9-4.6), respectively.

Conclusion

This study establishes the state of Sikkim as a new endemic area in India of Lyme disease besides its already reported endemicity in Arunachal Pradesh. No association was conclusively established between symptoms of Lyme and IgG seropositivity emphasizing the need for detailed history taking and clinical suspicion in endemic areas.

Perception of Ticks and Tick-Borne Diseases Worldwide

In this comprehensive review study, we addressed the challenge posed by ticks and tick-borne diseases (TBDs) with growing incidence affecting human and animal health worldwide. Data and perspectives were collected from different countries and regions worldwide, including America, Europe, Africa, Asia, and Oceania. The results updated the current situation with ticks and TBD and how it is perceived by society with information bias and gaps. The study reinforces the importance of multidisciplinary and international collaborations to advance in the surveillance, communication and proposed future directions to address these challenges.

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis

BACKGROUND

Lyme disease is among the most reported tick-borne diseases worldwide, making it a major ongoing public health concern. An effective Lyme disease case reporting system depends on timely diagnosis and reporting by health care professionals, and accurate laboratory testing and interpretation for clinical diagnosis validation. A lack of these can lead to delayed diagnosis and treatment, which can exacerbate the severity of Lyme disease symptoms. Therefore, there is a need to improve the monitoring of Lyme disease by using other data sources, such as web-based data.

OBJECTIVE

We analyzed global Twitter data to understand its potential and limitations as a tool for Lyme disease surveillance. We propose a transformer-based classification system to identify potential Lyme disease cases using self-reported tweets.

METHODS

Our initial sample included 20,000 tweets collected worldwide from a database of over 1.3 million Lyme disease tweets. After preprocessing and geolocating tweets, tweets in a subset of the initial sample were manually labeled as potential Lyme disease cases or non-Lyme disease cases using carefully selected keywords. Emojis were converted to sentiment words, which were then replaced in the tweets. This labeled tweet set was used for the training, validation, and performance testing of DistilBERT (distilled version of BERT [Bidirectional Encoder Representations from Transformers]), ALBERT (A Lite BERT), and BERTweet (BERT for English Tweets) classifiers.

RESULTS

The empirical results showed that BERTweet was the best classifier among all evaluated models (average F1-score of 89.3%, classification accuracy of 90.0%, and precision of 97.1%). However, for recall, term frequency-inverse document frequency and k-nearest neighbors performed better (93.2% and 82.6%, respectively). On using emojis to enrich the tweet embeddings, BERTweet had an increased recall (8% increase), DistilBERT had an increased F1-score of 93.8% (4% increase) and classification accuracy of 94.1% (4% increase), and ALBERT had an increased F1-score of 93.1% (5% increase) and classification accuracy of 93.9% (5% increase). The general awareness of Lyme disease was high in the United States, the United Kingdom, Australia, and Canada, with self-reported potential cases of Lyme disease from these countries accounting for around 50% (9939/20,000) of the collected English-language tweets, whereas Lyme disease-related tweets were rare in countries from Africa and Asia. The most reported Lyme disease-related symptoms in the data were rash, fatigue, fever, and arthritis, while symptoms, such as lymphadenopathy, palpitations, swollen lymph nodes, neck stiffness, and arrythmia, were uncommon, in accordance with Lyme disease symptom frequency.

CONCLUSIONS

The study highlights the robustness of BERTweet and DistilBERT as classifiers for potential cases of Lyme disease from self-reported data. The results demonstrated that emojis are effective for enrichment, thereby improving the accuracy of tweet embeddings and the performance of classifiers. Specifically, emojis reflecting sadness, empathy, and encouragement can reduce false negatives.

Molecular Surveillance for Vector-Borne Bacteria in Rodents and Tree Shrews of Peninsular Malaysia Oil Palm Plantations

Many human clinical cases attributed to vector-borne pathogens are underreported in Malaysia, especially in rural localities where healthcare infrastructures are lacking. Here, 217 small mammals, consisting of rodents and tree shrews, were trapped in oil palm plantations in the Peninsular Malaysia states of Johor and Perak. Species identification was performed using morphological and DNA barcoding analyses, and 203 small mammals were included in the detection of selected vector-borne bacteria. The DNA extracted from the spleens was examined for Orientia tsutsugamushi, Borrelia spp., Bartonella spp. and Rickettsia spp. using established PCR assays. The small mammals collected in this study included Rattus tanezumi R3 mitotype (n = 113), Rattus argentiventer (n = 24), Rattus tiomanicus (n = 22), Rattus exulans (n = 17), Rattus tanezumi sensu stricto (n = 1) and Tupaia glis (n = 40). Orientia tsutsugamushi, Borrelia spp. and Bartonella phoceensis were detected in the small mammals with the respective detection rates of 12.3%, 5.9% and 4.9%. Rickettsia spp., however, was not detected. This study encountered the presence of both Lyme disease and relapsing fever-related borreliae in small mammals collected from the oil palm plantation study sites. All three microorganisms (Orientia tsutsugamushi, Borrelia spp. and Bartonella phoceensis) were detected in the R. tanezumi R3 mitotype, suggesting that the species is a competent host for multiple microorganisms. Further investigations are warranted to elucidate the relationships between the ectoparasites, the small mammals and the respective pathogens.

Tick infestation on the lower eyelid in an elderly female: a case report

This article presents a case of tick infestation of the lower eyelid. A 58-year-old female presented to Ophthalmology OPD at Nepalgunj medical college with a small whitish lesion on medial aspect of the left lower eyelid since 7 days. On a detailed ocular examination, a tick was found to be masquerading as a pustule. This case report emphasizes the relation of tropical diseases in ophthalmology and the subsequent need of understanding the pathophysiological aspect of tropical diseases to avoid further systemic complications.

Non-malarial febrile illness: a systematic review of published aetiological studies and case reports from Southern Asia and South-eastern Asia, 1980-2015

BACKGROUND

In the absence of definitive diagnosis, healthcare providers are likely to prescribe empirical antibacterials to those who test negative for malaria. This problem is of critical importance in Southern Asia (SA) and South-eastern Asia (SEA) where high levels of antimicrobial consumption and high prevalence of antimicrobial resistance have been reported. To improve management and guide further diagnostic test development, better understanding is needed of the true causative agents of fever and their geographical variability.

METHODS

We conducted a systematic review of published literature (1980-2015) to characterise the spectrum of pathogens causing non-malarial febrile illness in SA and SEA. We searched six databases in English and French languages: MEDLINE, EMBASE, Global Health (CABI) database, WHO Global Health Library, PASCAL, and Bulletin de la Société Française de Parasitologie (BDSP). Selection criteria included reporting on an infection or infections with a confirmed diagnosis, defined as pathogens detected in or cultured from samples from normally sterile sites, or serological evidence of current or past infection.

RESULTS

A total of 29,558 records from 19 countries in SA and SEA were screened, of which 2410 (8.1%) met the selection criteria. Bacterial aetiologies were reported in 1235 (51.2%) articles, viral in 846 (35.1%), parasitic in 132 (5.5%), and fungal in 54 (2.2%), and 143 (6.0%) articles reported more than one pathogen group. In descending order of frequency, Salmonella Typhi, Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and coagulase negative Staphylococcus were the commonly reported bacteria, while dengue virus, chikungunya virus, Japanese encephalitis virus, hepatitis B virus, and hepatitis C virus were common viral pathogens reported. Reports of rarely reported or emerging pathogens included a case report of Borrelia burgdorferi (Lyme disease) in India in 2010 and reports of Nipah virus in Singapore and India.

CONCLUSIONS

This review summarises the reported non-malaria pathogens that may cause febrile illness in SA and SEA. The findings emphasise the need of standardising the reporting of aetiological studies to develop effective, evidence-based fever management and improved surveillance. Research and development of diagnostic tools would benefit from up-to-date epidemiological reporting of the regional diversities of non-malaria fever aetiologies.

TRIAL REGISTRATION

PROSPERO registration, CRD42016049281.