ArticlePLOS global public health2026
Spatiotemporal patterns and entomological predictors of dengue transmission in Urban Surat, India (2016-2020): A surveillance-based risk modelling study.
Article in PLOS global public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dengue fever is an increasing public health concern in urban India due to rapid urbanization, inadequate vector control, and underreporting of cases. Surat, a densely populated city in Gujarat, has remained a recurrent dengue hotspot, yet detailed spatiotemporal patterns and entomological determinants of transmission remain insufficiently explored. This study aimed to assess spatiotemporal patterns of dengue transmission in Surat and identify entomological and demographic predictors of elevated vector density to guide targeted urban interventions. A retrospective longitudinal analysis was conducted using five years of dengue surveillance data (January 2016-December 2020). A total of 1,658 laboratory-confirmed dengue cases reported to the sentinel surveillance system of the Surat Municipal Corporation were included. Monthly entomological surveillance assessed vector indices-House Index (HI), Container Index (CI), and Breteau Index (BI)-across administrative zones. Associations were examined using chi-square analysis, and binomial logistic regression identified predictors of moderate-to-high vector density (HI ≥ 1%) considering temporal, spatial, and demographic variables. Model performance was evaluated using receiver operating characteristic analysis. During the study period, reported dengue incidence declined from 11.1 to 2.2 cases per 100,000 population; however, elevated vector indices persisted, particularly in the South and South-East zones. Approximately 36% of cases occurred in households located in areas with HI ≥ 1%. Adolescents and young adults (median age 21.7 years) were disproportionately affected. Public sector facilities reported 2.6 times more cases than private providers (p < 0.001), suggesting substantial underreporting. Logistic regression identified year, month, zone, and age as significant predictors of elevated vector density (p < 0.001). The model showed moderate discrimination (AUC = 0.688), high specificity (87.3%), and low sensitivity (35.9%). Despite declining reported incidence, persistently high larval indices and post-monsoon peaks indicate ongoing transmission risk, emphasizing the need for zone-specific vector control and strengthened surveillance systems.
Identifiers
What OpenQuestion holds
Registered trials
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.