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Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis
BACKGROUND: Phlebotomine sand flies serve as vectors for leishmaniasis, a major health concern, but a neglected tropical disease. The risk of vector activity is governed by climatic factors that vary in different geographic zones in the country. Thus, we aimed to quantify the effect of climatic vari...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10350229/ https://www.ncbi.nlm.nih.gov/pubmed/37461526 http://dx.doi.org/10.21203/rs.3.rs-3098746/v1 |
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author | Senanayake, Sanath C Liyanage, Prasad Pathirage, Dulani R.K. Siraj, M. F. Raushan Kolitha De Silva, B. G. D. Nissanka Karunaweera, Nadira D |
author_facet | Senanayake, Sanath C Liyanage, Prasad Pathirage, Dulani R.K. Siraj, M. F. Raushan Kolitha De Silva, B. G. D. Nissanka Karunaweera, Nadira D |
author_sort | Senanayake, Sanath C |
collection | PubMed |
description | BACKGROUND: Phlebotomine sand flies serve as vectors for leishmaniasis, a major health concern, but a neglected tropical disease. The risk of vector activity is governed by climatic factors that vary in different geographic zones in the country. Thus, we aimed to quantify the effect of climatic variables on sand fly vector activity in ten sentinel sites across Sri Lanka. METHODS: Mean rainfall, ambient temperature, relative humidity, wind speed, soil temperature, evaporation, sunshine hours, and vector densities were recorded at monthly intervals in each location from March 2018 to February 2020. The association between weather variables and sand fly densities was analysed using a two-staged hierarchical procedure; Distributed Lag Non-Linear (DLNM) modelling framework and the DLNM method implemented in the R package dlnm (version number 2.4.6). RESULTS: Moderate rainfall values up to 120 mm per month and increasing RH up to 82 at lag of 0 months along with increasing soil temperature and evaporation rate at lag of 2 months were associated with statistically significant increase in the sand fly activity. These associations were heterogeneous across study settings. Whereas increasing ambient and soil temperature, sunshine hours, evaporation rate appeared to reduce the sand fly activity homogeneously at lag of 0 month in all the study settings. CONCLUSIONS: The abundance of sand fly vectors varied in relation to selected climatic variables, either in real-time or with a time lag. This information can be utilized for predicting sand fly densities and for the development of effective strategies to prevent leishmaniasis transmission in specific settings. |
format | Online Article Text |
id | pubmed-10350229 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-103502292023-07-17 Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis Senanayake, Sanath C Liyanage, Prasad Pathirage, Dulani R.K. Siraj, M. F. Raushan Kolitha De Silva, B. G. D. Nissanka Karunaweera, Nadira D Res Sq Article BACKGROUND: Phlebotomine sand flies serve as vectors for leishmaniasis, a major health concern, but a neglected tropical disease. The risk of vector activity is governed by climatic factors that vary in different geographic zones in the country. Thus, we aimed to quantify the effect of climatic variables on sand fly vector activity in ten sentinel sites across Sri Lanka. METHODS: Mean rainfall, ambient temperature, relative humidity, wind speed, soil temperature, evaporation, sunshine hours, and vector densities were recorded at monthly intervals in each location from March 2018 to February 2020. The association between weather variables and sand fly densities was analysed using a two-staged hierarchical procedure; Distributed Lag Non-Linear (DLNM) modelling framework and the DLNM method implemented in the R package dlnm (version number 2.4.6). RESULTS: Moderate rainfall values up to 120 mm per month and increasing RH up to 82 at lag of 0 months along with increasing soil temperature and evaporation rate at lag of 2 months were associated with statistically significant increase in the sand fly activity. These associations were heterogeneous across study settings. Whereas increasing ambient and soil temperature, sunshine hours, evaporation rate appeared to reduce the sand fly activity homogeneously at lag of 0 month in all the study settings. CONCLUSIONS: The abundance of sand fly vectors varied in relation to selected climatic variables, either in real-time or with a time lag. This information can be utilized for predicting sand fly densities and for the development of effective strategies to prevent leishmaniasis transmission in specific settings. American Journal Experts 2023-06-28 /pmc/articles/PMC10350229/ /pubmed/37461526 http://dx.doi.org/10.21203/rs.3.rs-3098746/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Senanayake, Sanath C Liyanage, Prasad Pathirage, Dulani R.K. Siraj, M. F. Raushan Kolitha De Silva, B. G. D. Nissanka Karunaweera, Nadira D Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis |
title | Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis |
title_full | Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis |
title_fullStr | Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis |
title_full_unstemmed | Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis |
title_short | Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis |
title_sort | impact of climatic factors on temporal variability of sand fly abundance in sri lanka: longitudinal study (2018 to 2020) with two-stage hierarchical analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10350229/ https://www.ncbi.nlm.nih.gov/pubmed/37461526 http://dx.doi.org/10.21203/rs.3.rs-3098746/v1 |
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