Elham Nazari - Ph.D. Student of Medical Informatics, Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
Zahra Ebnehoseini - Ph.D. in Medical Informatics, Psychiatry and Behavioral Sciences Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
Hamed Tabesh - Ph.D. in Medical Informatics, Psychiatry and Behavioral Sciences Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

Introduction: Given, widespread COVID-۱۹ across the world a comprehensive literature review can be used to forecast COVID-۱۹ 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 ۱۰ 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 COVID-۱۹.Conclusion: Our findings will help researchers by a summary of evidence to present new ideas and further research especially for studies were focused on COVID-۱۹. Our results can improve the understanding of prediction methods for COVID-۱۹.

Forecasting, Prediction, Peak, Epidemic Diseases