ArticleParasites & vectors2019
Simple framework for real-time forecast in a data-limited situation: the Zika virus (ZIKV) outbreaks in Brazil from 2015 to 2016 as an example.
Article in Parasites & vectors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed.
- App-based epidemic game in a university campus reveals how risk perception and behavioral interventions shape disease transmission dynamics.Scientific reports · 2026Article
- Development of Lipopeptides as Orthoflavivirin Inhibitors with Low Micromolar Broad-Spectrum Antiorthoflaviviral Activity.Journal of medicinal chemistry · 2025Article
- A Gaussian-process approximation to a spatial SIR process using moment closures and emulators.Biometrics · 2024Article
- Effects of boosting and waning in highly exposed populations on dengue epidemic dynamics.Science translational medicine · 2023Article
- The influence of ambient air pollution on the transmission of tuberculosis in Jiangsu, China.Infectious Disease Modelling · 2023Article
- Modeling COVID-19 dynamics in the sixteen West African countries.Scientific African · 2022Article
- Response to Comments on "Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: a data-driven analysis in the early phase of the outbreak".International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022Article
- Article
- Shrinkage in serial intervals across transmission generations of COVID-19.Journal of theoretical biology · 2021Article
- Social determinants associated with Zika virus infection in pregnant women.PLoS neglected tropical diseases · 2021Article
- Measuring differences between phenomenological growth models applied to epidemiology.Mathematical biosciences · 2021Article
- Dynamics of the COVID-19 basic reproduction numbers in different countries.Science bulletin · 2021Article
- Ensemble bootstrap methodology for forecasting dynamic growth processes using differential equations: application to epidemic outbreaks.BMC medical research methodology · 2021Article
- Modelling the effects of the contaminated environments on tuberculosis in Jiangsu, China.Journal of theoretical biology · 2021Article
- Mid-Epidemic Forecasts of COVID-19 Cases and Deaths: A Bivariate Model Applied to the UK.Interdisciplinary perspectives on infectious diseases · 2021Article
- Estimating the serial interval of the novel coronavirus disease (COVID-19) based on the public surveillance data in Shenzhen, China, from 19 January to 22 February 2020.Transboundary and emerging diseases · 2020Article
- The Rapid Assessment and Early Warning Models for COVID-19.Virologica Sinica · 2020Review
- Covid-19 Outbreak Progression in Italian Regions: Approaching the Peak by the End of March in Northern Italy and First Week of April in Southern Italy.International journal of environmental research and public health · 2020Article
- Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020Article
- Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak.Journal of clinical medicine · 2020Article
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5 authors.
Funding
Abstract
backgroundIn 2015-2016, Zika virus (ZIKV) caused serious epidemics in Brazil. The key epidemiological parameters and spatial heterogeneity of ZIKV epidemics in different states in Brazil remain unclear. Early prediction of the final epidemic (or outbreak) size for ZIKV outbreaks is crucial for public health decision-making and mitigation planning. We investigated the spatial heterogeneity in the epidemiological features of ZIKV across eight different Brazilian states by using simple non-linear growth models.
resultsWe fitted three different models to the weekly reported ZIKV cases in eight different states and obtained an R
conclusionsOur simple models fitted the epidemic reasonably well and thus revealed the spatial heterogeneity in the epidemiological features across Brazilian states. The knowledge of the epidemic turning point is crucial for real-time projection of the outbreak size. Our real-time estimation framework is able to yield a reliable prediction of the final epidemic size.
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