Title of article :
a protocol of scoping review of peak point prediction methods for epidemic diseases: applicable to coronavirus 2019 prediction
Author/Authors :
nazari, elham mashhad university of medical sciences - faculty of medicine - department of medical informatics, mashhad, iran, islamic republic of , ebnehoseini, zahra mashhad university of medical sciences - psychiatry and behavioral sciences research center, mashhad, iran, islamic republic of , tabesh, hamed mashhad university of medical sciences - faculty of medicine - department of medical informatics, mashhad, iran, islamic republic of
Abstract :
introduction: given, widespread covid19 across the world a comprehensive literature review can be used to forecast covid19 peak in the countries. the present protocol study aimed to explore epidemic peak prediction models in communicable diseases. material and methods: this protocol study was conducted based on arksey and o malley s. this framework encompasses purpose and hypothesis, modeling, model achievements aspects. a systematic search of english in pubmed was conducted to identify relevant studies. in the pilot step, two reviewers independently extracted the variables from 10 eligible studies to develop a primary list of variables and a data extraction form. in the second step, all eligible studies were assessed by researchers. in the third step, two data extraction forms were combined. the data were extracted and categories were created based on frequency. qualitative and quantitative methods were used to synthesize the extracted data. results: the current study were focused on forecasting the epidemic peak time that is a worlds’ concern issue. the results of current scoping review on prediction methods for epidemic disease can provide foundational knowledge, and have important value for the prediction model studies of covid19. conclusion: our findings will help researchers by a summary of evidence to present new ideas and further research especially for studies were focused on covid19. our results can improve the understanding of prediction methods for covid19.
Keywords :
forecasting , prediction , peak , epidemic diseases ,
Journal title :
frontiers in health informatics
Journal title :
frontiers in health informatics