Transmission Dynamics of Visceral Leishmaniasis in the Indian Subcontinent – A Systematic Literature Review
Bibliographic record
Abstract
BACKGROUND: As Bangladesh, India and Nepal progress towards visceral leishmaniasis (VL) elimination, it is important to understand the role of asymptomatic Leishmania infection (ALI), VL treatment relapse and post kala-azar dermal leishmaniasis (PKDL) in transmission. METHODOLOGY/ PRINCIPAL FINDING: We reviewed evidence systematically on ALI, relapse and PKDL. We searched multiple databases to include studies on burden, risk factors, biomarkers, natural history, and infectiveness of ALI, PKDL and relapse. After screening 292 papers, 98 were included covering the years 1942 through 2016. ALI, PKDL and relapse studies lacked a reference standard and appropriate biomarker. The prevalence of ALI was 4-17-fold that of VL. The risk of ALI was higher in VL case contacts. Most infections remained asymptomatic or resolved spontaneously. The proportion of ALI that progressed to VL disease within a year was 1.5-23%, and was higher amongst those with high antibody titres. The natural history of PKDL showed variability; 3.8-28.6% had no past history of VL treatment. The infectiveness of PKDL was 32-53%. The risk of VL relapse was higher with HIV co-infection. Modelling studies predicted a range of scenarios. One model predicted VL elimination was unlikely in the long term with early diagnosis. Another model estimated that ALI contributed to 82% of the overall transmission, VL to 10% and PKDL to 8%. Another model predicted that VL cases were the main driver for transmission. Different models predicted VL elimination if the sandfly density was reduced by 67% by killing the sandfly or by 79% by reducing their breeding sites, or with 4-6y of optimal IRS or 10y of sub-optimal IRS and only in low endemic setting. CONCLUSION/ SIGNIFICANCE: There is a need for xenodiagnostic and longitudinal studies to understand the potential of ALI and PKDL as reservoirs of infection.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".