Epidemiological and Time Series Analysis of Tuberculosis with Prediction during COVID-19 Pandemic using ARIMA Model: A Study from Churu District of Rajasthan

Abstract

Abstract As Tuberculosis (TB) is a major public health problem in India and to achieve the goal of TB elimination, it is important to assess the trend of TB cases and the impact of lockdowns and other restrictions imposed for control of COVID-19 in India on the National TB Elimination Programme. Hence, the present study aims to study the temporal trend of TB cases and assess the impact of lockdown on TB detection. A retrospective record-based study was conducted in a tertiary care institute of India. A time series analysis of TB cases from April 2018 to May 2020 was carried out. An Auto-Regressive Integrated Moving Averages (ARIMA) model was used to forecast TB cases during the lockdown period and the result was compared with actual cases detected. The statistical analysis was accomplished with R software. The time series analysis showed that the projected TB cases in April and May 2020 were 67 and 86, respectively, while the observed cases in these months were 35 and 76. The trend of TB cases during the study period showed no steady increase or decrease and the detection of TB has declined during the COVID-19 lockdown period. The TB cases peaked from April to June and males constitute the majority of TB cases.