ArticleScientific reports2023
Projecting malaria elimination in Thailand using Bayesian hierarchical spatiotemporal models.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed, 12 citations in OpenAlex.
- Spatiotemporal epidemiology, geographic hotspots, and risk factor associations of drug-resistant tuberculosis incidence in Indonesia: a Bayesian hierarchical modelling approach.Infectious diseases of poverty · 2026Article
- Spatiotemporal epidemiology and associated risk factors of tuberculosis incidence and mortality in Indonesia 2017-2022: a nationwide space-time hierarchical analysis.Population health metrics · 2026Article
- Dynamic changes and early warning of peanuts aflatoxin BNPJ science of food · 2026Article
- Spatiotemporal epidemiology and hierarchical analysis of suicide mortality and associated risk factors in Thailand using national surveillance data during 1997-2021.Scientific reports · 2025Article
- Prospective observational study to assess the feasibility and safety of appropriateBMJ global health · 2025Observational
- Global spatiotemporal analysis of suicide epidemiology and risk factor associations from 2000 to 2019 using Bayesian space time hierarchical modeling.Scientific reports · 2025Article
- Comparative evaluation of spatiotemporal methods for effective dengue cluster detection with a case study of national surveillance data in Thailand.Scientific reports · 2024Article
- Identification of Bacteria and Viruses Associated with Patients with Acute Febrile Illness in Khon Kaen Province, Thailand.Viruses · 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
10 authors at 4 institutions in 2 countries.
Funding
Abstract
Thailand has set a goal of eliminating malaria by 2024 in its national strategic plan. In this study, we used the Thailand malaria surveillance database to develop hierarchical spatiotemporal models to analyze retrospective patterns and predict Plasmodium falciparum and Plasmodium vivax malaria incidences at the provincial level. We first describe the available data, explain the hierarchical spatiotemporal framework underlying the analysis, and then display the results of fitting various space-time formulations to the malaria data with the different model selection metrics. The Bayesian model selection process assessed the sensitivity of different specifications to obtain the optimal models. To assess whether malaria could be eliminated by 2024 per Thailand's National Malaria Elimination Strategy, 2017-2026, we used the best-fitted model to project the estimated cases for 2022-2028. The study results based on the models revealed different predicted estimates between both species. The model for P. falciparum suggested that zero P. falciparum cases might be possible by 2024, in contrast to the model for P. vivax, wherein zero P. vivax cases might not be reached. Innovative approaches in the P. vivax-specific control and elimination plans must be implemented to reach zero P. vivax and consequently declare Thailand as a malaria-free country.
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.