Spatiotemporal Distribution of Cutaneous Leishmaniasis in Sri Lanka and Future Case Burden Estimates

Overview

Journal PLoS Negl Trop Dis

Specialties Infectious Diseases
Tropical Medicine

Date 2021 Apr 23

PMID 33891608

Citations 14

Authors

Nadira D Karunaweera

Sanath Senanayake

Samitha Ginige

Hermali Silva

Nuwani Manamperi

Nilakshi Samaranayake

Rajika Dewasurendra

Panduka Karunanayake

Deepa Gamage

Nissanka de Silva

Upul Senarath

Guofa Zhou

Affiliations

Soon will be listed here.

Abstract

Background: Leishmaniasis 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.

Methods: The 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.

Results: A 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.

Conclusions: The 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.

Citing Articles

Investigating disease awareness of cutaneous leishmaniasis in rural Sri Lanka to inform public health services: a cross-sectional study.

Gunasekara S, Agampodi T, Weerasinghe M, Fernando M, Price H, Wickramasinghe N BMJ Open. 2024; 14(11):e088714.

PMID: 39581720 PMC: 11590865. DOI: 10.1136/bmjopen-2024-088714.

Impact of climate and land use on the temporal variability of sand fly density in Sri Lanka: A 2-year longitudinal study.

Senanayake S, Liyanage P, Pathirage D, Siraj M, De Silva B, Karunaweera N PLoS Negl Trop Dis. 2024; 18(11):e0012675.

PMID: 39570981 PMC: 11620634. DOI: 10.1371/journal.pntd.0012675.

Salivary antigens rPagSP02 and rPagSP06 are a reliable composite biomarker for evaluating exposure to Phlebotomus argentipes in Sri Lanka.

Piyasiri S, Senanayake S, Smaranayake N, Doh S, Iniguez E, Valenzuela J Sci Rep. 2024; 14(1):25863.

PMID: 39468289 PMC: 11519893. DOI: 10.1038/s41598-024-77666-2.

Autochthonous Leishmaniasis Caused by Leishmania tropica, Identified by Using Whole-Genome Sequencing, Sri Lanka.

Silva H, Ferreira T, Muneeswaran K, Samarasinghe S, Alves-Ferreira E, Grigg M Emerg Infect Dis. 2024; 30(9):1872-1883.

PMID: 39174018 PMC: 11347009. DOI: 10.3201/eid3009.231238.

rPagSP02+rPagSP06 recombinant salivary antigen is a reliable biomarker for evaluating exposure to Phlebotomus argentipes in Sri Lanka.

Piyasiri S, Senanayake S, Samaranayake N, Doh S, Iniguez E, Kamhawi S Res Sq. 2024; .

PMID: 39070615 PMC: 11276025. DOI: 10.21203/rs.3.rs-4633976/v1.

References

Courtenay O, Peters N, Rogers M, Bern C . Combining epidemiology with basic biology of sand flies, parasites, and hosts to inform leishmaniasis transmission dynamics and control. PLoS Pathog. 2017; 13(10):e1006571. PMC: 5648254. DOI: 10.1371/journal.ppat.1006571. View

Chaves L, Pascual M . Climate cycles and forecasts of cutaneous leishmaniasis, a nonstationary vector-borne disease. PLoS Med. 2006; 3(8):e295. PMC: 1539092. DOI: 10.1371/journal.pmed.0030295. View

Bjornstad , Ims , Lambin . Spatial population dynamics: analyzing patterns and processes of population synchrony. Trends Ecol Evol. 1999; 14(11):427-432. DOI: 10.1016/s0169-5347(99)01677-8. View

Ellis C, Yahr R, Belinchon R, Coppins B . Archaeobotanical evidence for climate as a driver of ecological community change across the anthropocene boundary. Glob Chang Biol. 2014; 20(7):2211-20. DOI: 10.1111/gcb.12548. View

Golpayegani A, Moslem A, Akhavan A, Zeydabadi A, Mahvi A, Allah-Abadi A . Modeling of Environmental Factors Affecting the Prevalence of Zoonotic and Anthroponotic Cutaneous, and Zoonotic Visceral Leishmaniasis in Foci of Iran: a Remote Sensing and GIS Based Study. J Arthropod Borne Dis. 2018; 12(1):41-66. PMC: 6046107. View

Galgamuwa L, Dharmaratne S, Iddawela D . Leishmaniasis in Sri Lanka: spatial distribution and seasonal variations from 2009 to 2016. Parasit Vectors. 2018; 11(1):60. PMC: 5785883. DOI: 10.1186/s13071-018-2647-5. View

Ding F, Wang Q, Fu J, Chen S, Hao M, Ma T . Risk factors and predicted distribution of visceral leishmaniasis in the Xinjiang Uygur Autonomous Region, China, 2005-2015. Parasit Vectors. 2019; 12(1):528. PMC: 6839266. DOI: 10.1186/s13071-019-3778-z. View

Herrera G, Teheran A, Pradilla I, Vera M, Ramirez J . Geospatial-temporal distribution of Tegumentary Leishmaniasis in Colombia (2007-2016). PLoS Negl Trop Dis. 2018; 12(4):e0006419. PMC: 5906026. DOI: 10.1371/journal.pntd.0006419. View

Koenig . Spatial autocorrelation of ecological phenomena. Trends Ecol Evol. 1999; 14(1):22-26. DOI: 10.1016/s0169-5347(98)01533-x. View

10.

Ranasinghe S, Wickremasinghe R, Munasinghe A, Hulangamuwa S, Sivanantharajah S, Seneviratne K . Cross-sectional study to assess risk factors for leishmaniasis in an endemic region in Sri Lanka. Am J Trop Med Hyg. 2013; 89(4):742-9. PMC: 3795106. DOI: 10.4269/ajtmh.12-0640. View

11.

Gajapathy K, Peiris L, Goodacre S, Silva A, Jude P, Surendran S . Molecular identification of potential leishmaniasis vector species within the Phlebotomus (Euphlebotomus) argentipes species complex in Sri Lanka. Parasit Vectors. 2014; 6(1):302. PMC: 3853795. DOI: 10.1186/1756-3305-6-302. View

12.

Nikonahad A, Khorshidi A, Ghaffari H, Ebrahimi Aval H, Miri M, Amarloei A . A time series analysis of environmental and metrological factors impact on cutaneous leishmaniasis incidence in an endemic area of Dehloran, Iran. Environ Sci Pollut Res Int. 2017; 24(16):14117-14123. DOI: 10.1007/s11356-017-8962-0. View

13.

Poche D, Grant W, Wang H . Visceral Leishmaniasis on the Indian Subcontinent: Modelling the Dynamic Relationship between Vector Control Schemes and Vector Life Cycles. PLoS Negl Trop Dis. 2016; 10(8):e0004868. PMC: 4990243. DOI: 10.1371/journal.pntd.0004868. View

14.

Melchior L, Brilhante A, Chiaravalloti-Neto F . Spatial and temporal distribution of American cutaneous leishmaniasis in Acre state, Brazil. Infect Dis Poverty. 2017; 6(1):99. PMC: 5461694. DOI: 10.1186/s40249-017-0311-5. View

15.

Bhunia G, Kesari S, Chatterjee N, Kumar V, Das P . Spatial and temporal variation and hotspot detection of kala-azar disease in Vaishali district (Bihar), India. BMC Infect Dis. 2013; 13:64. PMC: 3577657. DOI: 10.1186/1471-2334-13-64. View

16.

Chaves L, Calzada J, Valderrama A, Saldana A . Cutaneous leishmaniasis and sand fly fluctuations are associated with el niño in panamá. PLoS Negl Trop Dis. 2014; 8(10):e3210. PMC: 4183471. DOI: 10.1371/journal.pntd.0003210. View

17.

Semage S, Pathirana K, Agampodi S . Cutaneous leishmaniasis in Mullaitivu, Sri Lanka: a missing endemic district in the leishmaniasis surveillance system. Int J Infect Dis. 2014; 25:53-5. DOI: 10.1016/j.ijid.2014.03.1382. View

18.

Li Y, Zheng C . Associations between Meteorological Factors and Visceral Leishmaniasis Outbreaks in Jiashi County, Xinjiang Uygur Autonomous Region, China, 2005-2015. Int J Environ Res Public Health. 2019; 16(10). PMC: 6571646. DOI: 10.3390/ijerph16101775. View

19.

Tabasi M, Alesheikh A . Spatiotemporal Variability of Zoonotic Cutaneous Leishmaniasis Based on Sociodemographic Heterogeneity. The Case of Northeastern Iran, 2011-2016. Jpn J Infect Dis. 2020; 74(1):7-16. DOI: 10.7883/yoken.JJID.2020.048. View

20.

Karunaweera N, Ginige S, Senanayake S, Silva H, Manamperi N, Samaranayake N . Spatial Epidemiologic Trends and Hotspots of Leishmaniasis, Sri Lanka, 2001-2018. Emerg Infect Dis. 2019; 26(1):1-10. PMC: 6924882. DOI: 10.3201/eid2601.190971. View