Big geospatial data and data-driven methods for urban dengue risk forecasting: a review
With advancements in big geospatial data and artificial intelligence, multi-source data and
diverse data-driven methods have become common in dengue risk prediction …
diverse data-driven methods have become common in dengue risk prediction …
Harmonizing Multisource Data to Inform Vector-Borne Disease Risk Management Strategies
In the last few decades, we have witnessed the emergence of new vector-borne diseases
(VBDs), the globalization of endemic VBDs, and the urbanization of previously rural VBDs …
(VBDs), the globalization of endemic VBDs, and the urbanization of previously rural VBDs …
Joint spatial modeling of the risks of co-circulating mosquito-borne diseases in ceará, brazil
Mosquito-borne diseases such as dengue and chikungunya have been co-circulating in the
Americas, causing great damage to the population. In 2021, for instance, almost 1.5 million …
Americas, causing great damage to the population. In 2021, for instance, almost 1.5 million …
Analysis of the correlation between climatic variables and Dengue cases in the city of Alagoinhas/BA
The Aedes aegypti mosquito is the main vector of dengue and is a synanthropic insect and
due to its anthropophilic nature, it has specific reproductive needs. In addition to that, it also …
due to its anthropophilic nature, it has specific reproductive needs. In addition to that, it also …
Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil
Dengue virus remains a significant public health challenge in Brazil, and seasonal
preparation efforts are hindered by variable intra-and interseasonal dynamics. Here, we …
preparation efforts are hindered by variable intra-and interseasonal dynamics. Here, we …
Gaussian process nowcasting: application to COVID-19 mortality reporting
Updating observations of a signal due to the delays in the measurement process is a
common problem in signal processing, with prominent examples in a wide range of fields …
common problem in signal processing, with prominent examples in a wide range of fields …
Time series clustering to improve dengue cases forecasting with deep learning
Dengue fever represents a public health problem and accurate forecasts can help
governments take the best preventive actions. As the volume of data provided continuously …
governments take the best preventive actions. As the volume of data provided continuously …
Bayesian spatial functional data clustering: applications in disease surveillance
Our method extends the application of random spanning trees to cases where the response
variable belongs to the exponential family, making it suitable for a wide range of real-world …
variable belongs to the exponential family, making it suitable for a wide range of real-world …
Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times
Background As controlling malaria transmission remains a public-health challenge in the
Brazilian Amazon basin, the National Surveillance System for Malaria (SIVEP-MALARIA) …
Brazilian Amazon basin, the National Surveillance System for Malaria (SIVEP-MALARIA) …
[HTML][HTML] A Platform for Data-Centric, Continuous Epidemiological Analyses (EpiGraphHub): Descriptive Analysis
Background Guaranteeing durability, provenance, accessibility, and trust in open data sets
can be challenging for researchers and organizations that rely on public repositories of data …
can be challenging for researchers and organizations that rely on public repositories of data …