Predicting spatio-temporal dynamics of dengue using INLA (integrated nested laplace approximation) in Yogyakarta, Indonesia [PDF]
BMC Public HealthIntroduction Dengue is a mosquito-borne disease caused by the dengue virus, primarily transmitted by Aedes aegypti and Aedes albopictus. Its incidence fluctuates due to spatial and temporal factors, necessitating robust modeling approaches for prediction
Marko Ferdian Salim +2 more
doaj +4 more sources
Media Statistika, 2019 Poverty is a complex and multidimensional problem so that it becomes a development priority. Applications of poverty modeling in discrete data are still few and applications of the Bayesian paradigm are also still few.
Retsi Firda Maulina +2 more
doaj +3 more sources
Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models [PDF]
MethodsXCharacterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks.
Kristin J. Bondo +2 more
doaj +2 more sources
Bayesian spatio-temporal modeling for policy evaluation: Sensitivity of policy effect estimates in the context of COVID-19 stay-at-home orders. [PDF]
PLoS ONEThis study applies a Bayesian spatio-temporal model to demonstrate the sensitivity of policy effect estimates to spatial and temporal structure, using COVID-19 stay-at-home orders as a case study.
Pyung Kim +3 more
doaj +2 more sources
The association of climate-induced stressors on risk of negative sentiment: An analysis from 462 million geotagged tweets in Europe [PDF]
iScienceSummary: This study examines how climate-induced health risks influence negative sentiments on European social tweets from 2015 to 2022. Analyzing over 400 million tweets using NLP tools (NLTK, LIWC22) and spatial-temporal aggregation at the NUTS2 weekly
Tareq Al-Ahdal +10 more
doaj +2 more sources
JSTMapp: A web-based joint spatiotemporal modelling and mapping application for epidemiologists. [PDF]
PLoS ONEDisease mapping models help create disease risk maps, which public health policymakers can use to design disease control and monitoring programmes.
Alfred Ngwira +3 more
doaj +2 more sources
Spatio-temporal distribution, prediction and relationship of three major acute cardiovascular events: Out-of-hospital cardiac arrest, ST-elevation myocardial infarction and stroke [PDF]
Resuscitation PlusBackground: Predicting the incidence of time-sensitive cardiovascular diseases like out-of-hospital cardiac arrest (OHCA), ST-elevation myocardial infarction (STEMI), and stroke can reduce time to treatment and improve outcomes.
Angelo Auricchio +8 more
doaj +2 more sources
The impact of climatic factors on negative sentiments: An analysis of human expressions from X platform in Germany [PDF]
iScienceSummary: Expressions in social media can provide a rapid insight into people’s reactions to events, such as periods of climatic stress. This study explored the link between climatic stressors and negative sentiment on the X platform in Germany to inform ...
Tareq Al-Ahdal +6 more
doaj +2 more sources
Spatial analysis of road crash frequency using Bayesian models with Integrated Nested Laplace Approximation (INLA) [PDF]
Journal of Transportation Safety & Security, 2020 Improving traffic safety is a priority of most transportation agencies around the world. As part of traffic safety management strategies, efforts have focused on developing more accurate crash-frequency models and on identifying contributing factors in order to implement better countermeasures to improve traffic safety. Over time, models have increased
Romi Satria +2 more
openaire +2 more sources
Laplace approximation for conditional autoregressive models for spatial data of diseases
MethodsX, 2022 Conditional autoregressive (CAR) distributions are used to account for spatial autocorrelation in small areal or lattice data to assess the spatial risks of diseases.
Guiming Wang
doaj +1 more source