For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
Inviting an author to review:
Self-reported and measured sleep duration: how similar are they?
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
0
views
48
references
 Top references
cited by
2
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      93
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Assessing the associations between Aedes larval indices and dengue risk in Kalutara district, Sri Lanka: a hierarchical time series analysis from 2010 to 2019

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Dengue is a major public health problem in Sri Lanka.  Aedes vector surveillance and monitoring of larval indices are routine, long-established public health practices in the country. However, the association between Aedes larval indices and dengue incidence is poorly understood. It is crucial to evaluate lagged effects and threshold values of Aedes larval indices to set pragmatic targets for sustainable vector control interventions.

          Methods

          Monthly  Aedes larval indices and dengue cases in all 10 Medical Officer of Health (MOH) divisions in Kalutara district were obtained from 2010 to 2019. Using a novel statistical approach, a distributed lag non-linear model and a two-staged hierarchical meta-analysis, we estimated the overall non-linear and delayed effects of the Premise Index (PI), Breteau Index (BI) and Container Index (CI) on dengue incidence in Kalutara district. A set of MOH division-specific variables were evaluated within the same meta-analytical framework to determine their moderator effects on dengue risk. Using generalized additive models, we assessed the utility of Aedes larval indices in predicting dengue incidence.

          Results

          We found that all three larval indices were associated with dengue risk at a lag of 1 to 2 months. The relationship between PI and dengue was homogeneous across MOH divisions, whereas that with BI and CI was heterogeneous. The threshold values of BI, PI and CI associated with dengue risk were 2, 15 and 45, respectively. All three indices showed a low to moderate accuracy in predicting dengue risk in Kalutara district.

          Conclusions

          This study showed the potential of vector surveillance information in Kalutara district in developing a threshold-based, location-specific early warning system with a lead time of 2 months. The estimated thresholds are nonetheless time-bound and may not be universally applicable. Whenever longitudinal vector surveillance data areavailable, the methodological framework we propose here can be used to estimate location-specific Aedes larval index thresholds in any other dengue-endemic setting.

          Graphical Abstract

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13071-022-05377-6.

          Related collections

          Most cited references48

          • Record: found
          • Abstract: not found
          • Article: not found

          Measuring inconsistency in meta-analyses.

          Julian P. T. Higgins, Simon Thompson, Jonathan Deeks … (2003)
          Article 0 comments Cited 9768 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The global distribution and burden of dengue

            Samir Bhatt, Peter W. Gething, Oliver J Brady … (2013)
            Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes 1 . For some patients dengue is a life-threatening illness 2 . There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread 3 . The contemporary worldwide distribution of the risk of dengue virus infection 4 and its public health burden are poorly known 2,5 . Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanisation. Using cartographic approaches, we estimate there to be 390 million (95 percent credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of clinical or sub-clinical severity). This infection total is more than three times the dengue burden estimate of the World Health Organization 2 . Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help guide improvements in disease control strategies using vaccine, drug and vector control methods and in their economic evaluation. [285]
            Article 0 comments Cited 1444 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Assessing heterogeneity in meta-analysis: Q statistic or I2 index?

              Tania Huedo-Medina, Julio Sánchez-Meca, Fulgencio Marín-Martínez … (2006)
              In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q test. However, the Q test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the I(2) index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the Q test and the confidence interval around the I(2) index are compared by means of a Monte Carlo simulation. The results show the utility of the I(2) index as a complement to the Q test, although it has the same problems of power with a small number of studies.
              Article 0 comments Cited 690 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Prasad Liyanage: prasadgliyanage@gmail.com
                Yesim Tozan: tozan@nyu.edu
                Hasitha Aravinda Tissera: dr_korelege@yahoo.co.uk
                Hans J. Overgaard: hans.overgaard@nmbu.no
                Joacim Rocklöv: joacim.rockloev@uni-heidelberg.de
                Journal
                Journal ID (nlm-ta): Parasit Vectors
                Journal ID (iso-abbrev): Parasit Vectors
                Title: Parasites & Vectors
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1756-3305
                Publication date (Electronic): 3 August 2022
                Publication date PMC-release: 3 August 2022
                Publication date Collection: 2022
                Volume: 15
                Electronic Location Identifier: 277
                Affiliations
                [1 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Department of Epidemiology and Global Health, , Umeå University, ; Umeå, Sweden
                [2 ]GRID grid.466905.8, Ministry of Health, ; Colombo, Sri Lanka
                [3 ]GRID grid.137628.9, ISNI 0000 0004 1936 8753, School of Global Public Health, , New York University, ; New York, NY 10003 USA
                [4 ]GRID grid.19477.3c, ISNI 0000 0004 0607 975X, Faculty of Science and Technology, , Norwegian University of Life Sciences, ; Ås, Norway
                [5 ]GRID grid.9786.0, ISNI 0000 0004 0470 0856, Department of Microbiology, Faculty of Medicine, , Khon Kaen University, ; Khon Kaen, Thailand
                [6 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Department of Public Health and Clinical Medicine, Section of Sustainable Health, , Umeå University, ; SE-901 87 Umeå, Sweden
                [7 ]GRID grid.7700.0, ISNI 0000 0001 2190 4373, Heidelberg Institute of Global Health & the Interdisciplinary Center for Scientific Computing, , University of Heidelberg, ; Heidelberg, Germany
                Article
                Publisher ID: 5377
                DOI: 10.1186/s13071-022-05377-6
                PMC ID: 9351248
                PubMed ID: 35922821
                SO-VID: e0b65a9e-fff2-4108-b1aa-9cfbc046e720
                Copyright © © The Author(s) 2022
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 18 March 2022
                Date accepted : 26 June 2022
                Funding
                Funded by: Swedish Research Council for Health, Working Life and Welfare
                Award ID: 2006-1512
                Award Recipient :
                Funded by: Swedish Research Council Formas project ARBO-prevent
                Award ID: 2018–01754
                Award Recipient :
                Funded by: Umea University
                Open Access :

                Open access funding provided by Umea University.

                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2022

                ScienceOpen disciplines: Parasitology
                Keywords: dengue risk,aedes larval indices,lags,thresholds,kalutara,sri lanka
                Data availability:
                ScienceOpen disciplines: Parasitology
                Keywords: dengue risk, aedes larval indices, lags, thresholds, kalutara, sri lanka

                Comments

                Comment on this article

                scite_

                Similar content93

                See all similar

                Cited by2

                See all cited by

                Most referenced authors737

                See all reference authors