Statistical view of coronavirus (COVID-19) in Bangladesh

Introduction

On 31st December 2019, 27 cases of pneumonia of unknown disease were identified in Wuhan City, Hubei province in China [1] . The causative agent was identified from throat swab samples conducted by the Chinese Centre for Disease Control and Prevention (CCDC) on 7th January 2020, and was subsequently named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) [2] . The Chinese public health, clinical, and scientific communities took prompt response to allow for timely recognition of the new virus and shared the viral gene sequence to the world [4,5] . After that, in China about 82160 people were affected till now by this coronavirus disease. Chinese authorities initially reported that most patients in the Wuhan outbreak were epidemiologically linked to a large seafood and animal market [9] . The World Health Organization (WHO) has recently declared coronavirus disease 2019 (COVID-19) a public health emergency of international concern [2] . On January 30, 2020, the World Health Organization (WHO) declared the outbreak a Public Health Emergency of International Concern (PHEIC) [6] . On February 12, 2020, WHO named the disease caused by the novel coronavirus as Coronavirus Disease 2019 (COVID-19) [7,8] . Now more than 200 countries already affected by COVID-19 and infection have been reported in USA, UK, Thailand, Japan, Korea, Italy, Spain, France, India, Singapore, Malaysia, Bangladesh and so on. As of April 13, 2020, a total of 1853619 laboratory-confirmed cases had been documented globally [12] . Number of death also radically increased day by day in the world. In recent studies, the severity of some cases of Covid-19 mimicked that of SARSCoV. Given the rapid spread of Covid-19, we determined that an updated analysis of cases throughout mainland China might help identify the defining clinical characteristics and severity of the disease [3] . Bangladesh is a small in geographically and the most populous density country in the world. On 7 March, the first coronavirus case was detected after the tests were positive for COVID-19 in Bangladesh and was declared on the next day through a press conference. On 8 March, IEDCR director announced at a press conference in Dhaka that 2 men and 1 woman had tested positive for the coronavirus. The patients were aged between 20 and 35. Of them, two men were Italy returnees and the woman was a family member of one patient and got infected by coming in contact with him. From the first day of coronavirus detected in Bangladesh, its increase number of cases and number of death day by day. The government has lockdown all the sectors including educational sector as well. As the report of IEDCR, Bangladesh, 621 people were affected by COVID-19 and total number of death 34 on 13 April, 2020. So that, it's very alarming that what will be and how can be tackle the critical situation by the government of Bangladesh. The study has shown present situation of the disease and how can it grow up in future. Objectives I. To know the present status of novel coronavirus in Bangladesh. II. To show the affect of social life of the people of Bangladesh and planning as well. III. To forecast the cumulative total cases and death of Bangladesh by COVID 2019 for the next two months.

Data and Method

This study has been made some daily basis data (8 March to 15 April, 2020), collected from different website (World health organization, Health ministry of Bangladesh, IEDCR [11] etc) and total number of cases collected from IEDCR daily report. Considering two variables for the analysis such as total cases and total death further consider into cumulative total cases (CTC), cumulative total death (CTD).

Non linear exponential or logarithmic method

In many situations, linear trends may not be found in time series data, instead, the nature of trend may be curvilinear. In that case, straight line cannot express the data of cumulative total cases and total death. This type of pattern of trends can be better expressed by non linear method [12] . y = ab X log y = loga+xlogb Where, y = Dependent variable x = Independent variable (time) a = Constant and b= Change of slop

Exponential Smoothing Method

One can develop a better forecast using a given time series data, if it is possible to determine which components actually exist in the series. If the randomness is present in the data, it is required to smooth out the data to remove randomness. One of the simplest ways of removing the random or irregular fluctuation is to smooth the time series [12] . F t = αy t-1 + (1-α) F t-1 Where, F t = current period forecast F t-1 = last or previous period forecast α = a weight called smoothing constant, 0 ≤ α ≤1 y t-1 = last period observed value of the variable , F 1 = y 1 It has been used non linear exponential growth method to estimate the cumulative total cases and total death and predict the future estimation of affected people in Bangladesh and Chi-square test for checking significance of the variables. Finally, it was used exponential smoothing approach for forecasting to the next two months. Absolute changes of such virus during this period and what will be changed in future were estimated using MS excel and SPSS software 15.0 version. Various statistical tools such as descriptive analysis and non linear trend of exponential growth method were used to analysis the data.

Result and Discussion

Frequency distribution of total number of cases and total number of death by March, April-2020 There is strong positive correlation between of total number of cases and total number of death (r = 0.81). Comment: Since null hypothesis is rejected, so we may there is an association between of total number of cases and total number of death. Exponential Smoothing: Forecast value of cumulative frequency of total number of cases and total number of death for the next two months in Bangladesh:

References

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