Main Article Content
A novel compartmental model is proposed to project the COVID-19 dynamics in Bangladesh. The exposed population is divided into two classes: tested and not tested. Model parameters are estimated by fitting the output with empirical COVID-19 data of Bangladesh from 7 April 2020 to 15 June 2020. It is found that even if 90% of exposed individuals are tested, number of unidentified cases (recovered or dead) is 3 to 4 times than that of identified cases. As of 15 June 2020, Bangladesh is using the Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) based test to detect the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The impact of false negative rate of this test on unidentified infection is analyzed. It is found that the year-end total recoveries (deaths) surges 700 (800) times if the false negative rate is doubled. Periodic lockdown and relaxation intervals are incorporated by defining the effective contact rate (β) as a periodic function of time. Impact of lockdown is perspicuous from the periodic fluctuation of the basic reproduction number ( ). It is observed that a 90-day-lockdwon reduces the final outcome by 3% while a 30-day-lockdwon increases it by 2%. On other hand, casualties are 10 to 100 times worse in case of no lockdown even with less than half effective contact rate. Analysis of strictness of isolation reveals that a 12.5% increase in the strictness coefficient reduces the exposed population 2.5 times whereas a 37.5% decrease in it intensifies the outcome nearly 9 times. Projections up to 6 April 2021 suggests that the epidemic will reach its peak in Bangladesh in August 2020.
Li Q,Guan X,Wu P, Wang X, Zhou L, Tong Y, et al., Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. New Engl. J. Med. 2020;382(13):1199-1207.
World Health Organization, Coronavirus disease (COVID-19) outbreak; 2020.
Available:https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19(Accessed 11 April 2020).
World Health Organization, Coronavirus disease (COVID-19) pandemic, 2020.
Available:https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/novel-coronavirus-2019-ncov(Accessed 11 April 2020).
Ngonghala CN, Iboi E, Eikenberry S, Scotch M, MacIntyre CR, Bonds MH, et al., Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus. Math Biosci. 2020;325:108364.
Worldometer, COVID-19 Coronavirus Pandemic; 2020.
coronavirus/ (Accessed 16 June 2020).
World Health Organization, Modes of transmission of virus causing COVID-19: implications for IPC precaution recommendations; 2020.
-implications-for-ipc-precaution-recommendations(Accessed 15 May 2020).
World Health Organization, COVID-19;2020.
Available:http://www.emro.who.int/health-topics/corona-virus/questions-and-answers.html(Accessed 21 June 2020).
Ambikapathy B, Krishnamurthy K, Mathematical Modelling to Assess the Impact of Lockdown on COVID-19 Transmission in India: Model Development and Validation. JMIR Public Health Surveill. 2020;6(2):19368.
Chatterjee K, Chatterjee K, Kumar A, Shankar S. Healthcare impact of COVID-19 epidemic in India: A stochastic mathematical model. Med J Armed Forces India;2020.
Marimuthu B. Nagappa N. Sharma S. Basu, Chopra KK, COVID-19 and tuberculosis: A mathematical model based forecasting in Delhi, India. Indian J Tuberc. 2020;67(2):177-181.
Huang Q, Kang YS, Mathematical Modeling of COVID-19 Control and Prevention Based on Immigration Population Data in China: Model Development and Validation. JMIR Public Health Surveill. 2020;6(2):18638.
Kim S, Seo YB, Jung E. Prediction of COVID-19 transmission dynamics using a mathematical model considering behavior changes in Korea. Epidemiol Health. 2020;42:2020026.
Acuña-Zegarra MA, Santana-Cibrian M, Velasco-Hernandez JX, Modeling behavioral change and COVID-19 containment in Mexico: A trade-off between lockdown and compliance.Mathematical Biosciences,2020;325:108370.
K. Liang, Mathematical model of infection kinetics and its analysis for COVID-19, SARS and MERS. Infect Genet Evol. 2020;82:104306.
Ng KY, Gui MM, COVID-19: Development of a robust mathematical model and simulation package with consideration for ageing population and time delay for control action and resusceptibility. Physica D. 2020;411:132599.
Tang Y, Serdan TDA, Masi LN,Tang S, Gorjao R, Hirabara SM, Epidemiology of COVID-19 in Brazil: using a mathematical model to estimate the outbreak peak and temporal evolution. Emerg Microbes Infect. 2020:1-11.
Li Q, Tang B, Bragazzi NL, Xiao Y, J Wu, Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability. Mathematical Biosciences. 2020;325:108378.
Xue L, Jing S, Miller JC, Sun W, Li H, Estrada-Franco JG, et al., A data-driven network model for the emerging COVID-19 epidemics in Wuhan, Toronto and Italy. Mathematical Biosciences.
Kermack WO, McKendrick AG. A contribution to the mathematical theory of epidemics.1927;115(772):700-721.
Institute of Epidemiology, Disease Control and Research, Bangladesh Covid-19 Update. Covid-19 Vital Statistics. Timeline; 2020.Available:https://iedcr.gov.bd/(Accessed 10 June 2020).
Kamruzzaman M, Sakib SN, Bangladesh imposes total lockdown over COVID-19; 2020.Available:https://www.aa.com.tr/en/asia-pacific/
bangladesh-imposes-total-lockdown-over-covid-19/1778272(Accessed 18 May 2020).
S. Mamun, Containing Covid-19: Bangladesh takes no strict action during danger period; 2020.Available:https://www.dhakatribune.com/health/coronavirus/2020
/06/20/containing-covid-19-bangladesh-takes-no-strict-action-during-danger-period(Accessed 21 June 2020).
Worldometer, Bangladesh Coronavirus Cases; 2020.Available:https://www.worldometers.info
/coronavirus/country/bangladesh/(Accessed 21 June 2020).
Chowdhury R, Heng K, Shawon MSR, Goh G, Okonofua D, Ochoa-Rosales C, et al., Dynamic interventions to control COVID-19 pandemic: a multivariate prediction modelling study comparing 16 worldwide countries. European Journal of Epidemiology. 2020;35(5):389-399.
Kucirka LM, Lauer SA, Laeyendecker O, Boon D, Lessler J, Variation in False-Negative Rate of Reverse Transcriptase Polymerase Chain Reaction–Based SARS-CoV-2 Tests by Time Since Exposure. Annals of Internal Medicine; 2020.
R. Hannah, Which countries are most densely populated?; 2019.
%20completing%20the%20top%20five(Accessed 12 June 2020).
GitHub, Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE; 2020.
Available:https://github.com/CSSEGISandData/COVID-19(Accessed 16 June 2020).
Hannah R, Esteban OO, Diana B, Edouard M, Joe H, Bobbie M, et al., Coronavirus (COVID-19) Testing; 2020. Available:https://ourworldindata.org/coronavirus-testing(Accessed 16 June 2020).
United Nations, Department of Economic and Social Affairs, Population Division (2019). World Population Prospects; 2019.
Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al., The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine. 2020;172(9):577-582.
Del Rio C, Malani PN. COVID-19—New Insights on a Rapidly Changing Epidemic. JAMA. 2020;323(14):1339-1340.
Lai CC, Shih TP, Ko WC, Tang HJ, Hsueh PR. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges. International Journal of Antimicrobial Agents. 2020;55(3):105924.
Ferguson N, Laydon D, Nedjati Gilani G, Imai N, Ainslie K, Baguelin M, et al. Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand; 2020.
World Health Organization, WHO Director-General's opening remarks at the media briefing on COVID-19; 2020.
Available:https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---24-february-2020(Accessed 16 June 2020).
Van den P. Driessche and J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Mathematical Biosciences. 2002;180(1): 29-48.
Diekmann O, Heesterbeek JAP, Metz JAJ, On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations. Journal of Mathematical Biology.1990;28(4):365-382.
Ghani AC, Donnelly CA, Cox DR, Griffin JT, Fraser C, Lam TH, et al., Methods for Estimating the Case Fatality Ratio for a Novel, Emerging Infectious Disease. American Journal of Epidemiology. 2005;162(5):479-486.
Thanh Le T Fau Z, Andreadakis A. Andreadakis Z Fau, Kumar R, Kumar A Fau. Gómez Román S. Gómez Román R Fau, Tollefsen M. Tollefsen S Fau, Saville S. Saville M Fau, Mayhew et al., The COVID-19 vaccine development landscape. (1474-1784 (Electronic)).