Dengue fever continues to pose a significant public health threat in Malaysia, particularly in peri-urban districts undergoing rapid residential expansion. However, the extent to which housing structures influence dengue transmission remains poorly quantified. This study investigated the temporal, proportional, and spatial dynamics of dengue across five housing categories; landed properties, high-rise residential units, traditional/rural houses, institutional quarters, and others in Kuala Selangor from 2020 to 2024. A total of 5,426 laboratory-confirmed dengue cases obtained from the national e-Notifikasi system were geocoded and classified by housing type. Temporal trends were examined using weekly epidemic curves, proportional contributions were calculated for each housing category, and spatial clustering was assessed using Kernel Density Estimation (KDE) in ArcGIS Pro. Landed properties were the dominant transmission environment, contributing 73.4% of all cases and consistently driving major seasonal peaks during epidemiological weeks 20-35, coinciding with the southwest monsoon. High-rise residential areas accounted for 16.1% of cases and exhibited persistent low-level transmission throughout the year, indicating a potential role as an endemic reservoir between epidemic cycles. Traditional/rural houses (5.5%), institutional quarters (3.4%), and other categories (1.6%) contributed only sporadically. KDE mapping revealed persistent hotspots in central and southern Kuala Selangor, primarily within peri-urban landed housing estates, with smaller recurrent clusters in high-rise complexes. These findings demonstrate that housing typology is a critical determinant of dengue transmission risk. Landed properties amplify monsoon-driven outbreaks through abundant outdoor breeding habitats, while high-rise buildings sustain inter-epidemic transmission via sheltered, indoor breeding sites. Integrating housing-specific intelligence into Malaysia's Integrated Vector Management (IVM) framework can enable more targeted, proactive, and spatially adaptive dengue prevention strategies.
Dom et al. (Sat,) studied this question.