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      Features of the urban environment associated with Aedes aegypti abundance in high-rise public apartments in Singapore: An environmental case-control study

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          Abstract

          Aedes aegypti abundance in residential estates is hypothesized to contribute to localised outbreaks of dengue in Singapore. Knowing the factors in the urban environment underlying high Ae. aegypti abundance could guide intervention efforts to reduce Ae. aegypti breeding and the incidence of dengue. In this study, objective data on Ae. aegypti abundance in public apartment blocks estimated by Singapore’s nationally representative Gravitrap surveillance system was obtained from the National Environmental Agency. Low and high abundance status public apartment blocks were classified based on the Gravitrap Aegypti Index, corresponding to the lowest and highest quartiles respectively. An environmental case-control study was conducted, wherein a blinded assessment of urban features hypothesised to form breeding habitats was conducted in 50 randomly sampled public apartment blocks with low and high abundance statuses each. Logistic regression was performed to identify features that correlated with abundance status. A multivariable logistic model was created to determine key urban features found in corridors and void decks which were predictive of the Ae. aegypti abundance status of the public apartment block. At a statistical level of significance of 0.20, the presence of gully traps [Odds Ratio (OR): 1.34, 95% Confidence Interval (CI): 1.10, 1.66], age of the public apartment block [OR: 2.23, 95% CI: 1.48, 3.60], housing price [OR: 0.33, 95% CI: 0.16, 0.61] and corridor cleanliness [OR: 0.67, 95% CI: 0.40, 1.07] were identified as important predictors of abundance status. To reduce Ae. aegypti abundance around public apartment blocks and potential onward dengue transmission, gully traps could be remodelled or replaced by other drainage types. Routine inspections of Ae. aegypti breeding should be targeted at older and low-income neighbourhoods. Campaigns for cleaner corridors should be promoted.

          Author summary

          Dengue outbreaks are frequent in Singapore. Controlling the mosquito population remains the principal method in preventing dengue transmission since safe and effective pharmaceutical interventions and vaccines have not been developed. Typical vector control campaigns that strive to reduce the mosquito population urge relevant stakeholders, including residents, town councils responsible for common areas, schools and construction site contractors, to remove stagnant water from their premises. However, breeding sites have been found at close proximity to but outside of homes, including containers, plants and drains, some of which are managed by residents, others by the government. This study investigates which urban features, which had previously been found to be common breeding habitats in homes and public areas, contributed most to the Ae. aegypti abundance of residential areas. We used objective Gravitrap surveillance data to estimate Ae. aegypti abundance and an exposure assessment tool to measure the presence of urban features. Findings from the study indicate that gully traps, age of high-rise housing blocks, housing unit price and corridor cleanliness were the most predictive of Ae. aegypti abundance. Both residents and the government should be enlisted to uphold effective vector control efforts.

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          Most cited references28

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          R: A language and environment for statistical computing

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            Purposeful selection of variables in logistic regression

            Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS) data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.
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              RStudio: Integrated development environment for R

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: SupervisionRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                PLOS Neglected Tropical Diseases
                Public Library of Science (San Francisco, CA USA )
                1935-2727
                1935-2735
                2 February 2023
                February 2023
                : 17
                : 2
                : e0011075
                Affiliations
                [1 ] Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
                [2 ] Environmental Health Institute, National Environmental Agency, Singapore
                [3 ] School of Biological Sciences, Nanyang Technological University, Singapore
                [4 ] Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
                Duke-NUS GMS, SINGAPORE
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-1878-9946
                Article
                PNTD-D-22-01253
                10.1371/journal.pntd.0011075
                9928025
                36730440
                3e9fe7dd-6daf-4829-8481-d3d0a64b7690
                © 2023 Fernandez et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 2 October 2022
                : 7 January 2023
                Page count
                Figures: 1, Tables: 4, Pages: 14
                Funding
                Funded by: Saw Swee Hock School of Public Health
                Award Recipient :
                SAF received support from the National University of Singapore School of Saw Swee Hock Practicum fund regarding transportation expenses for this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Tropical Diseases
                Neglected Tropical Diseases
                Dengue Fever
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Dengue Fever
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Forecasting
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Forecasting
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Aedes Aegypti
                Biology and Life Sciences
                Species Interactions
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Aedes Aegypti
                Biology and Life Sciences
                Zoology
                Entomology
                Insects
                Mosquitoes
                Aedes Aegypti
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Mosquitoes
                Aedes Aegypti
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Arthropoda
                Insects
                Mosquitoes
                Aedes Aegypti
                Earth Sciences
                Geography
                Human Geography
                Housing
                Social Sciences
                Human Geography
                Housing
                Biology and Life Sciences
                Organisms
                Bacteria
                Wolbachia
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Biology and Life Sciences
                Species Interactions
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Biology and Life Sciences
                Zoology
                Entomology
                Insects
                Mosquitoes
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Mosquitoes
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Arthropoda
                Insects
                Mosquitoes
                People and Places
                Geographical Locations
                Asia
                Singapore
                Ecology and Environmental Sciences
                Terrestrial Environments
                Urban Environments
                Custom metadata
                vor-update-to-uncorrected-proof
                2023-02-14
                The data underlying the results presented in the study are in Supporting Information S1 Dataset.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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