SynthesisFrontiers in public health2022
Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning: A Systematic Review.
Synthesis in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk.BMC infectious diseases · 2023Pooled it
- Global Genomic Surveillance.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Rethinking Clinical Trial Design to Accelerate Therapeutics for Arboviral Epidemics.Open forum infectious diseases · 2026Article
- Spatio-temporal analysis of the distribution and co-circulation of dengue, chikungunya, and Zika in Medellín, Colombia, from 2013 to 2021.PLoS neglected tropical diseases · 2025Article
- Is Ghana Prepared for Another Arboviral Outbreak? Evaluating the 2024 Dengue Fever Outbreak in the Context of Past Yellow Fever, Influenza, and COVID-19 Outbreaks.Tropical medicine and infectious disease · 2025Review
- Modeling zoonotic and vector-borne viruses.Current opinion in virology · 2024Review
- Prediction of tuberculosis clusters in the riverine municipalities of the Brazilian Amazon with machine learning.Revista brasileira de epidemiologia = Brazilian journal of epidemiology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed by a combination of climatic, environmental, and human mobility factors. Arboviruses prediction models can be a support tool for decision-making by public health agents. In this study, we propose a systematic literature review to identify arboviruses prediction models, as well as models for their transmitter vector dynamics. To carry out this review, we searched reputable scientific bases such as IEE Xplore, PubMed, Science Direct, Springer Link, and Scopus. We search for studies published between the years 2015 and 2020, using a search string. A total of 429 articles were returned, however, after filtering by exclusion and inclusion criteria, 139 were included. Through this systematic review, it was possible to identify the challenges present in the construction of arboviruses prediction models, as well as the existing gap in the construction of spatiotemporal models.
Indexed as
Identifiers
What OpenQuestion holds
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.