Evidence map›Paper›PMID 41673121›Full record

ArticleScientific reports2026

Drone-based composite risk mapping reveals vegetation-shade interaction and housing typology as key determinants of Aedes habitat risk.

Zulfadli Mahfodz, Agus Naba, Pradeep Isawasan, Mohd Azuraidi Osman, Nazri Che Dom

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zulfadli MahfodzCentre of Environmental Health & Safety, Faculty of Health Sciences, Universiti Teknologi MARA (UiTM), UITM Selangor, Puncak Alam, 42300, Selangor, Malaysia.
Agus NabaDepartment of Physics, University of Brawijaya, Veteren Street, Malang, 65145, Indonesia.
Pradeep IsawasanFaculty of Computer and Mathematical Sciences, Perak Branch, Universiti Teknologi MARA, Tapah Campus, Perak, 35400, Malaysia.
Mohd Azuraidi OsmanDepartment of Cell and Molecular Biology, Faculty of Biotechnology & Biomolecular Sciences, Universiti Putra Malaysia, Serdang, 43400, Selangor, Malaysia.
Nazri Che DomCentre of Environmental Health & Safety, Faculty of Health Sciences, Universiti Teknologi MARA (UiTM), UITM Selangor, Puncak Alam, 42300, Selangor, Malaysia. nazricd@uitm.edu.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Persistent dengue transmission in tropical cities reflects a complex interplay between environmental microclimates and urban housing structure that supports Aedes mosquito breeding. This study applies drone-based microhabitat risk mapping integrated with a biologically defined Composite Risk Index (CRI) to quantify fine-scale environmental drivers of Aedes habitat risk across distinct residential typologies in Sect.  24, Shah Alam, Malaysia. High-resolution RGB imagery obtained using a DJI Phantom 4 Pro was processed to derive the Brightness Index (BI) as a proxy for shade intensity and the Excess Green Index (ExG) as an indicator of vegetation density. These indices were integrated a priori into a CRI to operationalise known ecological conditions favourable for Aedes. Spatial analysis revealed a consistent risk gradient, with terrace housing exhibiting higher Composite Risk Index (CRI) values than flat complexes (low-density terrace (Teres D) > dense terrace (Teres B) > medium-rise (Flat H) > high-rise (Flat B)), demonstrating that housing typology modulates the spatial expression of microhabitat risk rather than vegetation presence alone. Model calibration showed high predictive agreement (R² = 0.91), with the top 20% of CRI-ranked pixels capturing 65% of observed breeding-prone zones, indicating strong spatial discriminative performance. These findings highlight that vegetation-shade coupling, expressed through housing morphology, governs Aedes habitat persistence and that drone-based microclimate mapping provides a precision surveillance tool for spatially targeted dengue control.

Indexed as

AedesDengueEcosystemHousingMosquito VectorsUnmanned Aerial DevicesAnimalsHumansMalaysiaAedes habitat riskComposite risk index (CRI)Drone-based microhabitat risk mappingHousing typologyVegetation–shade interaction

Identifiers

PMID41673121
PMCPMC12895016

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.