AIMC Topic: Disease Outbreaks
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Deep neural networks for endemic measles dynamics: Comparative analysis and integration with mechanistic models.
PLoS computational biology
Nov 21, 2024
Measles is an important infectious disease system both for its burden on public health and as an opportunity for studying nonlinear spatio-temporal disease dynamics. Traditional mechanistic models often struggle to fully capture the complex nonlinear...
The fuzzy system ensembles entomological, epidemiological, demographic and environmental data to unravel the dengue transmission risk in an endemic city.
BMC public health
Sep 27, 2024
BACKGROUND: The effectiveness of dengue control interventions depends on an effective integrated surveillance system that involves analysis of multiple variables associated with the natural history and transmission dynamics of this arbovirus. Entomol...
Geospatial and Temporal Analysis of Avian Influenza Risk in Thailand: A GIS-Based Multi-Criteria Decision Analysis Approach for Enhanced Surveillance and Control.
Transboundary and emerging diseases
Sep 13, 2024
Avian influenza (AI) is a viral infection that profoundly affects global poultry production. This study aimed to identify the spatial and temporal factors associated with AI in Thailand, using a geographic information system (GIS)-based multi-criteri...
Prediction of measles cases in US counties: A machine learning approach.
Vaccine
Sep 7, 2024
BACKGROUND: Although measles was declared eliminated from the United States in 2000, the frequency of measles outbreaks has increased in recent years. The ability to predict the locations of future cases could aid efforts to prevent and contain measl...
Modelling bluetongue and African horse sickness vector (Culicoides spp.) distribution in the Western Cape in South Africa using random forest machine learning.
Parasites & vectors
Aug 21, 2024
BACKGROUND: Culicoides biting midges exhibit a global spatial distribution and are the main vectors of several viruses of veterinary importance, including bluetongue (BT) and African horse sickness (AHS). Many environmental and anthropological factor...
Prevalence of Avian Influenza Virus in Atypical Wild Birds Host Groups during an Outbreak of Highly Pathogenic Strain EA/AM H5N1.
Transboundary and emerging diseases
Jul 29, 2024
The global outbreak of highly pathogenic avian influenza (HPAI) H5N1 Eurasian lineage goose/Guangdong clade 2.3.4.4b virus that was detected in North America in 2021 is the largest in history and has significantly impacted wild bird populations and d...
Machine learning approach as an early warning system to prevent foodborne Salmonella outbreaks in northwestern Italy.
Veterinary research
Jun 5, 2024
Salmonellosis, one of the most common foodborne infections in Europe, is monitored by food safety surveillance programmes, resulting in the generation of extensive databases. By leveraging tree-based machine learning (ML) algorithms, we exploited dat...
Mathematical analysis and prediction of future outbreak of dengue on time-varying contact rate using machine learning approach.
Computers in biology and medicine
Jun 4, 2024
This article introduces a novel mathematical model analyzing the dynamics of Dengue in the recent past, specifically focusing on the 2023 outbreak of this disease. The model explores the patterns and behaviors of dengue fever in Bangladesh. Incorpora...
Mapping African Swine Fever and Highly Pathogenic Avian Influenza Outbreaks along the Demilitarized Zone in the Korean Peninsula.
Transboundary and emerging diseases
May 30, 2024
The Korean Demilitarized Zone (DMZ) is one of the world's most preserved habitats for wild animals and migratory birds. The area also plays a major role in the spread of infectious animal diseases, in particular, African swine fever (ASF) and highly ...
Integrating gated recurrent unit in graph neural network to improve infectious disease prediction: an attempt.
Frontiers in public health
May 20, 2024
OBJECTIVE: This study focuses on enhancing the precision of epidemic time series data prediction by integrating Gated Recurrent Unit (GRU) into a Graph Neural Network (GNN), forming the GRGNN. The accuracy of the GNN (Graph Neural Network) network wi...
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