ArticleEpidemiology and infection2017
Real-time parameter estimation of Zika outbreaks using model averaging.
Article in Epidemiology and infection, 2017. 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.
- Modeling the positive testing rate of COVID-19 in South Africa using a semi-parametric smoother for binomial data.Frontiers in public health · 2023Article
- Ensemble bootstrap methodology for forecasting dynamic growth processes using differential equations: application to epidemic outbreaks.BMC medical research methodology · 2021Article
- Short-term real-time prediction of total number of reported COVID-19 cases and deaths in South Africa: a data driven approach.BMC medical research methodology · 2021Article
- Exploring the Pattern of Early COVID-19 Transmission Caused by Population Migration Based on 14 Cities in Hubei Province, China.Risk management and healthcare policy · 2021Article
- Large-scale Lassa fever outbreaks in Nigeria: quantifying the association between disease reproduction number and local rainfall.Epidemiology and infection · 2020Article
- Discrete time forecasting of epidemics.Infectious Disease Modelling · 2020Article
- 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.Parasites & vectors · 2019Article
- Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia.International journal of environmental research and public health · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early prediction of the final size of any epidemic and in particular for Zika disease outbreaks can be useful for health authorities in order to plan the response to the outbreak. The Richards model is often been used to estimate epidemiological parameters for arboviral diseases based on the reported cumulative cases in single- and multi-wave outbreaks. However, other non-linear models can also fit the data as well. Typically, one follows the so called post selection estimation procedure, i.e., selects the best fitting model out of the set of candidate models and ignores the model uncertainty in both estimation and inference since these procedures are based on a single model. In this paper we focus on the estimation of the final size and the turning point of the epidemic and conduct a real-time prediction for the final size of the outbreak using several non-linear models in which these parameters are estimated via model averaging. The proposed method is applied to Zika outbreak data in four cities from Colombia, during the outbreak ocurred in 2015-2016.
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.