Ticks as a potential vector for spotted fever group Rickettsiae (SFGR): An epidemiological study from Wayanad district, South India
Bibliographic record
Abstract
Ticks are the known vectors of Spotted Fever Group Rickettsia (SFGR), a pathogen responsible for several tick-borne diseases. Wayanad, a hilly district in Kerala, India, has reported recurring cases of these diseases, prompting this epidemiological study. The study was conducted from October 2022 to December 2023, and aimed to find the geographical distribution of ticks in forest-adjacent areas and evaluate their role as potential SFGR vectors. A total of 520 ticks were collected from animals (Cows, Buffaloes, Goats and Dogs) in 23 locations in Wayanad district, with Haemaphysalis bispinosa emerging as the most abundant species, accounting for 79.2 % of the total ticks collected. Haemaphysalis spinigera and Haemaphysalis turturis represented 18.2 % and 2.3 % of the ticks, respectively. Using nested PCR to target the gltA and ompA genes, SFGR-DNA was detected exclusively in H. bispinosa pools . In total, 52.17 % of the sampled areas contained ticks positive for SFGR. Of the 516 ticks screened, 408 ticks from 40 pools of H. bispinosa were found positive for SFGR. The Minimum Infection Rate (MIR) was highest in Zone-1 (10.7 %), followed by Zone-2 (9.69 %) and Zone-3 (9.52 %). The current study is the first of its kind to report the presence of SFGR in South India which has significant public health concerns as it is a neglected tropical disease. Molecular characterization and sequencing are further recommended along with continuous surveillance of tick vectors and the implementation of preventive strategies in this region. • Minimum Infection Rate • Spotted Fever Group Rickettsiae • Tick-borne pathogens • Arthropod vectors • Neglected tropical disease • The study detected the presence of SFGR (Spotted Fever Group Rickettsia) in tick species South India. • Haemaphysalis bispinosa was the most abundant species (79.2 %). • Haemaphysalis spinigera (18.2 %) and Haemaphysalis turturis (2.3 %) were less prevalent. • SFGR-DNA was detected only in H. bispinosa pools using nested PCR targeting the gltA and ompA genes. • 52.17 % of sampled areas had SFGR-positive ticks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".