Introduction:
Coronavirus disease 19 (Covid-19) is an infectious disease caused by the Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) which was initially identified in December 2019 before becoming a global pandemic. Human to human spread is the identified form of transmission while exact molecular pathways in this pathway are not fully understood [1, 2].
Respiratory diseases spread by the inhalation of droplets scattered by the infected person. Avoidance of social distancing, failure of using personal protective equipment, late detection of symptoms all contribute to the rapid spread of the disease, and increase the burden in the health system in Covid-19 pandemic [3]. The unexpected increase of infected patients had put tremendous pressure on health systems causing a capacity overload, the premature ending of medical supplies, and exhausted health professionals to name a few. This sudden increase of patients had caused also significant implications for non-Covid-19 patients such as failure of initiating proper workup and treatment of conditions [4].
Such an unexpected increase of patients is not foreseeable for the health system and there are several factors for this. First, modern medicine had faced this scale of the pandemic first time where a systematic approach is used to gather data about how the number of cases evolves across nations. Second, countermeasure for this pandemic, lockdowns, quarantines and curfews, are internationally applied for the first time with no previous experience. Third, as the number of cases increase with different increments between communities, prediction of the total number of cases can be challenging.
Time series analysis with autoregressive integrated moving averages (ARIMA) models was popularized by Box and Jenkins in 1970 with their Box-Jenkins approach [5]. By using only one variable measured in equally spaced points in time, forecasting can be made with the help of the model build using the variable. Time series are used in statistics, weather prediction, and econometrics to name a few. In medicine, time series are used to predict the number of patients admitted in previous studies [6, 7].
In this research, we explored whether ARIMA model is feasible to predict the number of cases for Covid-19 patients. The aim is to forecast the total number of patients in the United States of America (USA) using the time series model and this modeling can provide health systems to provide better health care to patients.