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Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis. / Chapman, L.A.C.; Spencer, S.E.F.; Pollington, T.M. et al.
In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 117, No. 41, 13.10.2020, p. 25742-25750.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Chapman, LAC, Spencer, SEF, Pollington, TM, Jewell, CP, Mondal, D, Alvar, J, Hollingsworth, TD, Cameron, MM, Bern, C & Medley, GF 2020, '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, vol. 117, no. 41, pp. 25742-25750. https://doi.org/10.1073/pnas.2002731117

APA

Chapman, L. A. C., Spencer, S. E. F., Pollington, T. M., Jewell, C. P., Mondal, D., Alvar, J., Hollingsworth, T. D., Cameron, M. M., Bern, C., & Medley, G. F. (2020). 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, 117(41), 25742-25750. https://doi.org/10.1073/pnas.2002731117

Vancouver

Chapman LAC, Spencer SEF, Pollington TM, Jewell CP, Mondal D, Alvar J et al. 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. 2020 Oct 13;117(41):25742-25750. Epub 2020 Sept 24. doi: 10.1073/pnas.2002731117

Author

Chapman, L.A.C. ; Spencer, S.E.F. ; Pollington, T.M. et al. / Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis. In: Proceedings of the National Academy of Sciences of the United States of America. 2020 ; Vol. 117, No. 41. pp. 25742-25750.

Bibtex

@article{44b9a9c39dfb49218c61032ca0ed04e6,
title = "Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis",
abstract = "Understanding of spatiotemporal transmission of infectious diseases has improved significantly in recent years. Advances in Bayesian inference methods for individual-level geo-located epidemiological data have enabled reconstruction of transmission trees and quantification of disease spread in space and time, while accounting for uncertainty in missing data. However, these methods have rarely been applied to endemic diseases or ones in which asymptomatic infection plays a role, for which additional estimation methods are required. Here, we develop such methods to analyze longitudinal incidence data on visceral leishmaniasis (VL) and its sequela, post-kala-azar dermal leishmaniasis (PKDL), in a highly endemic community in Bangladesh. Incorporating recent data on VL and PKDL infectiousness, we show that while VL cases drive transmission when incidence is high, the contribution of PKDL increases significantly as VL incidence declines (reaching 55% in this setting). Transmission is highly focal: 85% of mean distances from inferred infectors to their secondary VL cases were ",
keywords = "Bayesian inference, Post-kala-azar dermal leishmaniasis, Spatiotemporal transmission, Transmission tree, Visceral leishmaniasis",
author = "L.A.C. Chapman and S.E.F. Spencer and T.M. Pollington and C.P. Jewell and D. Mondal and J. Alvar and T.D. Hollingsworth and M.M. Cameron and C. Bern and G.F. Medley",
year = "2020",
month = oct,
day = "13",
doi = "10.1073/pnas.2002731117",
language = "English",
volume = "117",
pages = "25742--25750",
journal = "Proceedings of the National Academy of Sciences of the United States of America",
issn = "0027-8424",
publisher = "National Academy of Sciences",
number = "41",

}

RIS

TY - JOUR

T1 - Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis

AU - Chapman, L.A.C.

AU - Spencer, S.E.F.

AU - Pollington, T.M.

AU - Jewell, C.P.

AU - Mondal, D.

AU - Alvar, J.

AU - Hollingsworth, T.D.

AU - Cameron, M.M.

AU - Bern, C.

AU - Medley, G.F.

PY - 2020/10/13

Y1 - 2020/10/13

N2 - Understanding of spatiotemporal transmission of infectious diseases has improved significantly in recent years. Advances in Bayesian inference methods for individual-level geo-located epidemiological data have enabled reconstruction of transmission trees and quantification of disease spread in space and time, while accounting for uncertainty in missing data. However, these methods have rarely been applied to endemic diseases or ones in which asymptomatic infection plays a role, for which additional estimation methods are required. Here, we develop such methods to analyze longitudinal incidence data on visceral leishmaniasis (VL) and its sequela, post-kala-azar dermal leishmaniasis (PKDL), in a highly endemic community in Bangladesh. Incorporating recent data on VL and PKDL infectiousness, we show that while VL cases drive transmission when incidence is high, the contribution of PKDL increases significantly as VL incidence declines (reaching 55% in this setting). Transmission is highly focal: 85% of mean distances from inferred infectors to their secondary VL cases were

AB - Understanding of spatiotemporal transmission of infectious diseases has improved significantly in recent years. Advances in Bayesian inference methods for individual-level geo-located epidemiological data have enabled reconstruction of transmission trees and quantification of disease spread in space and time, while accounting for uncertainty in missing data. However, these methods have rarely been applied to endemic diseases or ones in which asymptomatic infection plays a role, for which additional estimation methods are required. Here, we develop such methods to analyze longitudinal incidence data on visceral leishmaniasis (VL) and its sequela, post-kala-azar dermal leishmaniasis (PKDL), in a highly endemic community in Bangladesh. Incorporating recent data on VL and PKDL infectiousness, we show that while VL cases drive transmission when incidence is high, the contribution of PKDL increases significantly as VL incidence declines (reaching 55% in this setting). Transmission is highly focal: 85% of mean distances from inferred infectors to their secondary VL cases were

KW - Bayesian inference

KW - Post-kala-azar dermal leishmaniasis

KW - Spatiotemporal transmission

KW - Transmission tree

KW - Visceral leishmaniasis

U2 - 10.1073/pnas.2002731117

DO - 10.1073/pnas.2002731117

M3 - Journal article

VL - 117

SP - 25742

EP - 25750

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

SN - 0027-8424

IS - 41

ER -