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Change Point Modeling of COVID-19 Transmission in Bangladesh

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Change Point Modeling of COVID-19 Transmission in Bangladesh ISSN: 2577 - 8005 Research article Medical & Clinical Research Change Point Modeling of COVID-19 Transmission in Bangladesh Brijesh P Singh*1, Tapan K Roy2 and Aalok Ranjan Chaurasia3 1Department of Statistics, Institute of Science, Banaras Hindu *Corresponding author University, Varanasi, India Brijesh P Singh, Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, India 2Department of Population Science and Human Resource Development, Rajshahi University, Rajshahi, Bangladesh Submitted: 18 Dec 2020; Accepted: 24 Dec 2020; Published: 31 Dec 2020 3Aalok Ranjan Chaurasia, MLC Foundation, 51, Lake City Farms (Ganesh Puri), Kalkheda Road, Neelbad, Bhopal, India Abstract Background: COVID-19 pandemic is recognized as a significant threat to human health in 2020 in Bangladesh. Without emergence of effective medicine and vaccine it is very difficult to control the transmission of the COVID-19. Thus, identifying and monitoring the trajectory in the COVID-19 pandemic continuously is very important to assess the action taken to contain this pandemic and to have a further decision. Methods and Material: In this context, this study tries to find out the trend of daily reported confirmed cases of COVID-19 in Bangladesh. The 174 days’ daily data have been taken from the website of worldometer Bangladesh from 10 March to 30 August, 2020 for the analysis. To analyze the trends and to identify significant changes in trends joinpoint regression analysis has been used. Results: The number of cases increased by the rate of 4.98 percent per day in Bangladesh, however, from 11th June to 30th August i.e. for 81 days, the growth rate is found negative means we observed a decline in the COVID-19 cases per day with the rate of -0.6 percent. Conclusions: Evidence suggests that there is an impact of lockdown that slow down the spread of COVID-19 daily cases in Bangladesh. Keywords: COVID-19 Pandemic, Jointpoint Regression, Average Daily Percent Change, Bayesian Information Criterion. Introduction confirmed cases increased sharply and it passed the 10000 mark by A new virus introduced in December 2019, called the severe acute 5 May 2020 and the 50000 mark by 2 June 2020. respiratory syndrome corona virus 2 (SARS-CoV-2) caused a disease outbreak in China [1]. It was first discovered in the city of WHO’s and many other researchers advised that COVID-19 Wuhan, the provincial capital of Hupei province in central China, disease is currently a significant threat to developing and poor in the middle of December 27th. This virus can remain dormant country [3-6]. In a study, Imperial College of London model, a for 2 to 7 days after being infected in the body and can be infected projection report says that in Bangladesh, the Corona pandemic can with another person’s body during this time [2]. COVID-19 be infected with a total of eight million [7]. In addition, BRAC’s pandemic has challenged resource allocation and management research model, projects that Corona virus can kill 5 million system, especially in public health domain in Bangladesh as well people in Bangladesh [8]. Without inventing vaccination or proper as the health professionals is threatened by the super-spreading treatment, how we control the transmission of the COVID-19 is behavior of novel corona virus due to risk of infection. From the one of the most admitted questions with that people are facing right beginning government declared “lockdown” throughout the nation now. Until such treatments are developed, some policies termed as in order to protect the population on 23 March when the confirmed isolation, quarantine, lockdown, and social distancing would give cases were 33. The nation-wide lockdown continued up to 30 May a stunning direction to control the epidemic outbreak [9]. and prepared some necessary steps to spread awareness to keep this syndrome away from them. On 6 April 2020, more than 100 The advancement of COVID-19 presents a challenge for data confirmed cases of COVID-19 were reported which increased to scientists to model it as the epidemiological characteristics 500 by 12 April 2020 and crossed over 1000 on 14 April 2020 of the disease are yet to be fully explained. No treatments for (doubled within 2 days). Since then, the number of daily reported COVID-19 and no vaccine, at present are available to protect from Med Clin Res, 2020 www.medclinres.org Volume 5 | Issue 12 | 86 novel corona virus. The uncertainty regarding the advancement goal of the joinpoint regression analysis is not only to provide of COVID-19 pandemic therefore creates additional pressure the statistical model that best fits the time series data but also, the on the epidemiologists and public health experts on how to purpose is to provide that model which best summarizes the trend control it. In such circumstances, the forecasting COVID-19 in the data [13]. case is very important for planning and implementing infection containment and pandemic control measures. The trend analysis Let yi denotes the reported COVID-19 positive cases on day ti such of daily reported confirmed cases of COVID-19 is essential due that t1<t2<...<tn. Then the joinpoint regression model is defined as to the declaration of the nation-wide lockdown in Bangladesh on 23 March 2020 has significantly decelerated the progress of ln yi=+αβ11 tuu + δ 1 1 + δ 2 2 ++.... δjj u + ε i (1) COVID-19 pandemic in the country. It has even been argued that re-imposing the harsh restrictions as part of the lockdown across −> the nation is only way of stopping or decelerating the progress of where ()tjj k if tj k j u j = COVID-19 pandemic in spite of the fact that the socio-economic 0 otherwise cost of lockdown across the nation that is quite complex and exorbitant. It has repeatedly been stressed that because of serious social and economic implications of the nation-wide lockdown, it and k1<k2.......<kj are joinpoints. The details of joinpoint regression cannot be prolonged. analysis are given elsewhere (Kim et al., 2004). A review of the daily reporting of the confirmed COVID-19 cases Joinpoint regression analysis is used when the temporal trend of in Bangladesh shows that up to 13 March 2020, only 3 confirmed an amount, like incidence, prevalence and mortality is of interest cases were found. However, during the period 14 March 2020 [14, 15]. However, this method has generally been applied with the through 14 April 2020, the daily reported confirmed cases were calendar year as the time scale [16-19]. The joinpoint regression highly inconsistent. For analysis purpose, the irregular fluctuations analysis can also be applied in epidemiological studies in which in daily reporting of confirmed cases of COVID-19 resulting from the starting date can be easily established such as the day when the inconsistencies in reporting are to be removed before any the disease is detected for the first time as is the case in the analysis of the trend in the reported confirmed cases of COVID-19. present analysis [20]. Estimated regression coefficients (β) were Moving average is an approach to reduce the impact of observing calculated for the trends extracted from the joinpoint regression. inconsistency in the analysis of the trend in daily reporting cases of Additionally, the average daily percent change (ADPC), calculated confirmed COVID-19 instead of actual daily reported confirmed as a geometric weighted average of the daily percent changes cases of COVID-19. Such approach has been applied in this study [21]. The joinpints are selected based on the data-driven Bayesian for proper analysis. To minimize the effect of irregular fluctuations Information Criterion (BIC) method [22]. in the reporting of COVID-19 cases in the trend analysis, five-day moving average has been used instead of daily reported confirmed The equation for computing the BIC for a k-joinpoints regression cases of COVID-19. is: SSE( k ) 2( k+× 1) ln( n ) Tracing and monitoring continuously the trajectory of the BIC ( k ) = ln + (2) COVID-19 pandemic are very important to assess for the action nn taken to contain this pandemic and to have a further decision. We provide the trends and significant changes in the coronavirus Where SSE is the sum of squared errors of the k-joinpoints disease 2019 (COVID-19) outbreak in Bangladesh for about 150 regression model and n is the number of observations. The model days, from 08 March to 06 August, 2020. Since the daily data in which has the minimum value of BIC(k) is selected as the final Bangladesh is more or less inconsistent thus 5 days moving average model. There are other methods also for identifying the joinpoints is used to smooth the data. Therefore, in fact from 10 March to 04 such as permutation test method and the weighted BIC methods. August, 2020 is used for analysis. These daily data have been taken Relative merits and demerits of different methods of identifying from the website worldometer (2020) Bangladesh. For the analysis, the joinpoints are discussed elsewhere [23]. The permutation test we used the number of confirmed COVID-19 cases data posted in method is regarded as the best method but it is computationally the official website of the worldometer data for Bangladesh. To very intensive. It controls the error probability of selecting the analyze the temporal trends and to identify important changes in wrong model at a certain level (i.e. 0.05). The BIC method, on the the trends of the COVID-19 outbreak joinpoint regression is used other hand, is less complex computationally. in China and in India; here in this study we performed a joinpoint regression analysis in Bangladesh to understand the pattern of In the present case, data on the reported confirmed cases of COVID-19 [10, 11].
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