Disease Outbreak Detection using Time Series Analysis

Abstract

Disease Outbreak Detection System is an online system that helps epidemiologist analyze the behavior of a certain disease outbreak by providing them prediction values for a specific time interval. The system is able to perform such feature with the aid of R software which performs computations of Time Series analysis using Autoregressive Moving Averages(ARMA) Model to generate values based on the present condition of the outbreak. These generated values will serve as basis to know how the outbreak will turn out thus giving the epidemiologist sufficient time to respond to major public health threats and formulate preventive measures to control and solve the outbreak.

The system has four main users.First is the National Epidemiological Center (NEC) medical officer. He can perform several computations such as ARIMA forecast and Partial AutoCorrelation Function in order to produce accurate prediction values. He can also assess the present condition of a certain outbreak by using several status indicators such as case mapping and graphs that would help identify the behaviour of the outbreak in a faster and easier way. Second is the Local Field Health officer. He is the one responsible in managing the case records stored in the system's database which in turn will be the basis in the assessment that will be conducted by the NEC medical officer. System Administrator is the next user. He's duty is to manage the user accounts of each registered users and also, he is responsible in managing the contents of the site. Lastly, the guest or the anonymous user. He is able to view the published health news about disease outbreaks.