ReviewTropical medicine and infectious disease2022
Dengue Prediction in Latin America Using Machine Learning and the One Health Perspective: A Literature Review.
Review in Tropical medicine and infectious disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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Who cites it
19 citing papers in PubMed, 43 citations in OpenAlex.
- Advances in mosquito-borne disease surveillance using machine learning.New microbes and new infections · 2026Article
- Integrating explainable AI and One Health: a new frontier in combating infectious diseases.EBioMedicine · 2026Article
- Impact of projected climate and socioeconomic scenarios on state-wise annual dengue incidence in India using ensemble models.PLoS neglected tropical diseases · 2026Article
- Article
- Construction of a public health emergency information system framework: A case study of Zhuhai city, China.PloS one · 2026Article
- Article
- Assessing dengue forecasting methods: a comparative study of statistical models and machine learning techniques in Rio de Janeiro, Brazil.Tropical medicine and health · 2025Article
- ARBOALVO: A Bayesian spatiotemporal learning and predictive model for dengue cases in the endemic Northeast city of Natal, Rio Grande do Norte, Brazil.PLoS neglected tropical diseases · 2025Article
- Emergence and expansion of dengue in Paltas: possible implications of the COVID-19 pandemic and climatic variations.Tropical medicine and health · 2025Article
- Article
- Wolbachia infection in natural mosquito populations from Argentina.Parasitology research · 2024Article
- Identifying the Drivers Related to Animal Reservoirs, Environment, and Socio-Demography of Human Leptospirosis in Different Community Types of Southern Chile: An Application of Machine Learning Algorithm in One Health Perspective.Pathogens (Basel, Switzerland) · 2024Article
- Compulsory Vaccination Coverage in 12 Sub-Saharan African Countries Two Years Following the COVID-19 Pandemic.Journal of community health · 2024Article
- Precision Prediction for Dengue Fever in Singapore: A Machine Learning Approach Incorporating Meteorological Data.Tropical medicine and infectious disease · 2024Article
- The One Health Concept.British journal of biomedical science · 2024Review
- Article
- Dengue as a Disease Threatening Global Health: A Narrative Review Focusing on Latin America and Brazil.Tropical medicine and infectious disease · 2023Review
- Immune system gene polymorphisms associated with severe dengue in Latin America: a systematic review.Revista do Instituto de Medicina Tropical de Sao Paulo · 2023Article
- Mapping the Spatiotemporal Distribution of Bovine Rabies in Colombia, 2005-2019.Tropical medicine and infectious disease · 2022Article
Corrections and comments
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Authors and funding
6 authors at 5 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dengue fever is a serious and growing public health problem in Latin America and elsewhere, intensified by climate change and human mobility. This paper reviews the approaches to the epidemiological prediction of dengue fever using the One Health perspective, including an analysis of how Machine Learning techniques have been applied to it and focuses on the risk factors for dengue in Latin America to put the broader environmental considerations into a detailed understanding of the small-scale processes as they affect disease incidence. Determining that many factors can act as predictors for dengue outbreaks, a large-scale comparison of different predictors over larger geographic areas than those currently studied is lacking to determine which predictors are the most effective. In addition, it provides insight into techniques of Machine Learning used for future predictive models, as well as general workflow for Machine Learning projects of dengue fever.
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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.