ArticlePLoS neglected tropical diseases2019
Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data.
Article in PLoS neglected tropical diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Oviposition Behavior ofInsects · 2025Article
- Epidemiological Investigation of Infectious Diseases at the Domestic-Synanthropic-Wild Animal Interface Reveals Threats to Endangered Species Reintroduction in AlUla, Saudi Arabia.Veterinary sciences · 2025Article
- Article
- Widespread geographic distribution of Aedes aegypti (Diptera: Culicidae) kdr variants in Panama.Journal of medical entomology · 2024Article
- The bibliometric landscape of infectious disease research in Panama (1990-2019).Dialogues in health · 2023Review
- Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction numberHeliyon · 2023Article
- Comparing the space-time patterns of high-risk areas in different waves of COVID-19 in Hong Kong.Transactions in GIS : TG · 2021Article
- Assessing the Effect of Climate Variables on the Incidence of Dengue Cases in the Metropolitan Region of Panama City.International journal of environmental research and public health · 2021Article
- Integrating Spatial Modelling and Space-Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan.International journal of environmental research and public health · 2021Article
- A syndromic surveillance tool to detect anomalous clusters of COVID-19 symptoms in the United States.Scientific reports · 2021Article
- The role of heterogenous environmental conditions in shaping the spatiotemporal distribution of competingBiological invasions · 2021Article
- Detecting space-time clusters of COVID-19 in Brazil: mortality, inequality, socioeconomic vulnerability, and the relative risk of the disease in Brazilian municipalities.Journal of geographical systems · 2021Article
- Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo.The Lancet regional health. Western Pacific · 2020Article
- Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States.Spatial and spatio-temporal epidemiology · 2020Article
- Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters.Applied geography (Sevenoaks, England) · 2020Article
- Article
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which may result in inaccurate risk projection when several vector species are present, and when little is known about their likely role in local transmission. Here, we integrate 13 years of dengue case surveillance and associated Aedes occurrence data across 462 localities in 63 districts to estimate the risk of infection in the Republic of Panama. Our exploratory space-time modelling approach detected the presence of five clusters, which varied by duration, relative risk, and spatial extent after incorporating vector species as covariates. The Ae. aegypti model contained the highest number of districts with more dengue cases than would be expected given baseline population levels, followed by the model accounting for both Ae. aegypti and Ae. albopictus. This implies that arbovirus case surveillance coupled with entomological surveillance can affect cluster detection and risk estimation, potentially improving efforts to understand outbreak dynamics at national scales.
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