ArticlePLoS neglected tropical diseases2018
The role of case proximity in transmission of visceral leishmaniasis in a highly endemic village in Bangladesh.
Article in PLoS neglected tropical diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Long-term incidence of relapse and post-kala-azar dermal leishmaniasis after three different visceral leishmaniasis treatment regimens in Bihar, India.PLoS neglected tropical diseases · 2020Trial
- A modelling assessment of the impact of control measures on highly pathogenic avian influenza transmission in poultry in Great Britain.PLoS computational biology · 2026Article
- Spatial prediction of canine visceral leishmaniasis in an endemic urban area of Brazil.PloS one · 2025Article
- Inferring the regional distribution of Visceral Leishmaniasis incidence from data at different spatial scales.Communications medicine · 2024Article
- Challenges of using modelling evidence in the visceral leishmaniasis elimination programme in India.PLOS global public health · 2022Article
- Dynamics of inter-farm transmission of highly pathogenic avian influenza H5N6 integrating vehicle movements and phylogenetic information.Scientific reports · 2021Article
- Transmission Dynamics of African Swine Fever Virus, South Korea, 2019.Emerging infectious diseases · 2021Article
- Strengthening data collection for neglected tropical diseases: What data are needed for models to better inform tailored intervention programmes?PLoS neglected tropical diseases · 2021Article
- Visceral leishmaniasis outbreaks in Bihar: community-level investigations in the context of elimination of kala-azar as a public health problem.Parasites & vectors · 2021Article
- How modelling can help steer the course set by the World Health Organization 2021-2030 roadmap on neglected tropical diseases.Gates open research · 2021Article
- Article
- Precision Medicine in Control of Visceral Leishmaniasis Caused byFrontiers in cellular and infection microbiology · 2021Review
- Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India.PLoS neglected tropical diseases · 2020Article
- Insights from mathematical modelling and quantitative analysis on the proposed WHO 2030 targets for visceral leishmaniasis on the Indian subcontinent.Gates open research · 2019Article
- Age trends in asymptomatic and symptomatic Leishmania donovani infection in the Indian subcontinent: A review and analysis of data from diagnostic and epidemiological studies.PLoS neglected tropical diseases · 2018Review
- Visceral leishmaniasis: Spatiotemporal heterogeneity and drivers underlying the hotspots in Muzaffarpur, Bihar, India.PLoS neglected tropical diseases · 2018Article
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9 authors.
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Abstract
backgroundVisceral leishmaniasis (VL) is characterised by a high degree of spatial clustering at all scales, and this feature remains even with successful control measures. VL is targeted for elimination as a public health problem in the Indian subcontinent by 2020, and incidence has been falling rapidly since 2011. Current control is based on early diagnosis and treatment of clinical cases, and blanket indoor residual spraying of insecticide (IRS) in endemic villages to kill the sandfly vectors. Spatially targeting active case detection and/or IRS to higher risk areas would greatly reduce costs of control, but its effectiveness as a control strategy is unknown. The effectiveness depends on two key unknowns: how quickly transmission risk decreases with distance from a VL case and how much asymptomatically infected individuals contribute to transmission. METHODOLOGY/PRINCIPAL
findingsTo estimate these key parameters, a spatiotemporal transmission model for VL was developed and fitted to geo-located epidemiological data on 2494 individuals from a highly endemic village in Mymensingh, Bangladesh. A Bayesian inference framework that could account for the unknown infection times of the VL cases, and missing symptom onset and recovery times, was developed to perform the parameter estimation. The parameter estimates obtained suggest that, in a highly endemic setting, VL risk decreases relatively quickly with distance from a case-halving within 90m-and that VL cases contribute significantly more to transmission than asymptomatic individuals. CONCLUSIONS/SIGNIFICANCE: These results suggest that spatially-targeted interventions may be effective for limiting transmission. However, the extent to which spatial transmission patterns and the asymptomatic contribution vary with VL endemicity and over time is uncertain. In any event, interventions would need to be performed promptly and in a large radius (≥300m) around a new case to reduce transmission risk.
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