ArticlePLoS neglected tropical diseases2021
Spatiotemporal distribution of cutaneous leishmaniasis in Sri Lanka and future case burden estimates.
Article in PLoS neglected tropical diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- A conceptual model for healthcare-seeking research and interventions in cutaneous leishmaniasis.International journal for equity in health · 2026Article
- Understanding the complexity of cutaneous leishmaniasis patient journey in endemic rural Sri Lanka: a qualitative study.BMC infectious diseases · 2025Article
- A 12-year analysis of seasonal patterns and disease dynamics ofSaudi medical journal · 2025Article
- Trend analysis and spatiotemporal distribution of leishmaniasis disease incidence in Sri Lanka: A detailed review from 2009 to 2023.PLoS neglected tropical diseases · 2025Review
- Global, regional, and national burden of Visceral leishmaniasis, 1990-2021: findings from the global burden of disease study 2021.Parasites & vectors · 2025Article
- Article
- Impact of climate and land use on the temporal variability of sand fly density in Sri Lanka: A 2-year longitudinal study.PLoS neglected tropical diseases · 2024Article
- Salivary antigens rPagSP02 and rPagSP06 are a reliable composite biomarker for evaluating exposure to Phlebotomus argentipes in Sri Lanka.Scientific reports · 2024Article
- Autochthonous Leishmaniasis Caused by Leishmania tropica, Identified by Using Whole-Genome Sequencing, Sri Lanka.Emerging infectious diseases · 2024Article
- rPagSP02+rPagSP06 recombinant salivary antigen is a reliable biomarker for evaluating exposure to Phlebotomus argentipes in Sri Lanka.Research square · 2024Article
- Comparative Analysis ofMicroorganisms · 2024Article
- Risk Factor Analysis of Cutaneous Leishmaniasis in Sri Lanka through a Nationwide Survey.The American journal of tropical medicine and hygiene · 2024Article
- Modelling spatiotemporal patterns of visceral leishmaniasis incidence in two endemic states in India using environment, bioclimatic and demographic data, 2013-2022.PLoS neglected tropical diseases · 2024Article
- The use of recombinant K39, KMP11, and crude antigen-based indirect ELISA as a serological diagnostic tool and a measure of exposure for cutaneous leishmaniasis in Sri Lanka.Parasitology research · 2023Article
- 'We do not rush to the hospital for ordinary wounds (suḷu tuvāla)': A qualitative study on the early clinical manifestations of cutaneous leishmaniasis and associated health behaviours in rural Sri Lanka.PLoS neglected tropical diseases · 2023Article
- Assessment of knowledge and perceptions on leishmaniasis: An island-wide study in Sri Lanka.PLoS neglected tropical diseases · 2022Article
- ELISA-based evaluation of antibody response to Leishmania in a region endemic for cutaneous leishmaniasis.Parasite immunology · 2022Article
- Community Engagement in Cutaneous Leishmaniasis Research in Brazil, Ethiopia, and Sri Lanka: A Decolonial Approach for Global Health.Frontiers in public health · 2022Article
- Treatment failure to sodium stibogluconate in cutaneous leishmaniasis: A challenge to infection control and disease elimination.PloS one · 2021Article
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12 authors.
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Abstract
backgroundLeishmaniasis is a neglected tropical vector-borne disease, which is on the rise in Sri Lanka. Spatiotemporal and risk factor analyses are useful for understanding transmission dynamics, spatial clustering and predicting future disease distribution and trends to facilitate effective infection control.
methodsThe nationwide clinically confirmed cutaneous leishmaniasis and climatic data were collected from 2001 to 2019. Hierarchical clustering and spatiotemporal cross-correlation analysis were used to measure the region-wide and local (between neighboring districts) synchrony of transmission. A mixed spatiotemporal regression-autoregression model was built to study the effects of climatic, neighboring-district dispersal, and infection carryover variables on leishmaniasis dynamics and spatial distribution. Same model without climatic variables was used to predict the future distribution and trends of leishmaniasis cases in Sri Lanka.
resultsA total of 19,361 clinically confirmed leishmaniasis cases have been reported in Sri Lanka from 2001-2019. There were three phases identified: low-transmission phase (2001-2010), parasite population buildup phase (2011-2017), and outbreak phase (2018-2019). Spatially, the districts were divided into three groups based on similarity in temporal dynamics. The global mean correlation among district incidence dynamics was 0.30 (95% CI 0.25-0.35), and the localized mean correlation between neighboring districts was 0.58 (95% CI 0.42-0.73). Risk analysis for the seven districts with the highest incidence rates indicated that precipitation, neighboring-district effect, and infection carryover effect exhibited significant correlation with district-level incidence dynamics. Model-predicted incidence dynamics and case distribution matched well with observed results, except for the outbreak in 2018. The model-predicted 2020 case number is about 5,400 cases, with intensified transmission and expansion of high-transmission area. The predicted case number will be 9115 in 2022 and 19212 in 2025.
conclusionsThe drastic upsurge in leishmaniasis cases in Sri Lanka in the last few year was unprecedented and it was strongly linked to precipitation, high burden of localized infections and inter-district dispersal. Targeted interventions are urgently needed to arrest an uncontrollable disease spread.
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