TY - JOUR
T1 - Assessing the associations between Aedes larval indices and dengue risk in Kalutara district, Sri Lanka
T2 - a hierarchical time series analysis from 2010 to 2019
AU - Liyanage, Prasad
AU - Tozan, Yesim
AU - Tissera, Hasitha Aravinda
AU - Overgaard, Hans J.
AU - Rocklöv, Joacim
N1 - Funding Information:
We would like to thank the Provincial Directors of Health—Western province and Dr. Udaya Isaac Rathnayake, the Regional Director of Health—Kalutara for their permission to carry out this study and their support throughout. We gratefully thank the public health staff of Kalutara, including all of the Medical Officers of Health, Public Health Inspectors and Health Entomology officers, for their support.
Funding Information:
Open access funding provided by Umeå University. This study was not funded. All data were obtained with the administrative approval of the Provincial Director of Health Service, Western Province, Sri Lanka. JR received funding from the Swedish Research Council Formas project ARBO-prevent (Grant No. 2018-01754). PL received a stipend for his Ph.D. program through the Swedish Research Council for Health, Working Life and Welfare (Grant No. 2006-1512) through the Department of Global Health and Epidemiology, Umeå University Sweden. HJO is supported by a grant from the Research Council of Norway (Grant No. 281077). The funders have no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript. All authors had full access to the full data in the study and accept responsibility to submit for publication.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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: [Figure not available: see fulltext.]
AB - 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: [Figure not available: see fulltext.]
KW - Aedes larval indices
KW - Dengue risk
KW - Kalutara
KW - Lags
KW - Sri Lanka
KW - Thresholds
UR - http://www.scopus.com/inward/record.url?scp=85135286901&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135286901&partnerID=8YFLogxK
U2 - 10.1186/s13071-022-05377-6
DO - 10.1186/s13071-022-05377-6
M3 - Article
AN - SCOPUS:85135286901
SN - 1756-3305
VL - 15
JO - Parasites and Vectors
JF - Parasites and Vectors
IS - 1
M1 - 277
ER -