Estimation of Effective Reproduction Number for COVID-19 in Bangladesh and its districts

  1. Al-Ekram Elahee Hridoy
  2. Mohammad Naim
  3. Edris Alam
  4. Nazim Uddin Emon
  5. Imrul Hasan Tipo
  6. Shekh Md. Shajid Hasan Tusher
  7. Safaet Alam
  8. Mohammad Safiqul Islam

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Abstract

Background

Bangladesh is going through an unprecedented crisis since the onset of the COVID-19 pandemic. Throughout the COVID-19 pandemic, the reproduction number of COVID-19 swarmed in the scientific community and public media due to its simplicity in explaining an infectious disease dynamic. This paper aims to estimate the effective reproduction number (Rt) for COVID-19 over time in Bangladesh and its districts using reported cases.

Methods

Adapted methods derived from Bettencourt and Ribeiro (2008), which is a sequential Bayesian approach using the compartmental Susceptible-Infectious-Recovered (SIR) model, have been used to estimate Rt.

Results

As of July 21, the mean Rt is 1.32(0.98-1.70, 90% HDI), with a median of 1.16(0.99-1.34 90% HDI). The initial Rt of Bangladesh was 3, whereas the Rt on the day of imposing nation-wide lockdown was 1.47, at the end of lockdown phase 1 was 1.06, at the end of lockdown phase 2 was 1.33. Each phase of nation-wide lockdown has contributed to the decline of effective reproduction number (Rt) for Bangladesh by 28.44%, and 26.70%, respectively, implying moderate effectiveness of the epidemic response strategies.

Interpretation and Conclusion

The mean Rt fell by 13.55% from May 31 to July 21, 2020, despite easing of lockdown in Bangladesh. The Rt continued to fall below the threshold value one steadily from the beginning of July and sustained around 1. The mean Rt fell by 13.55% from May 31 to July 21, 2020, despite easing of lockdown in Bangladesh. As of July 21, the current estimate of Rt is 1.07(0.92-1.15: 90% HDI), meaning that an infected individual is spreading the virus to an average of one other, with 0.07 added chance of infecting a second individual. This whole research recommends two things- broader testing and careful calibration of measures to keep Rt a long way below the crucial threshold one.

Highlights

  • As of July 21, the mean Rt and growth factor is 1.32 and 1.02, respectively.

  • Each phase of nation-wide lockdown has contributed to the decline of effective reproduction number (Rt) for Bangladesh by 28.44%, and 26.70%, respectively, implying moderate effectiveness of the epidemic response strategies.

  • The Rt of Bangladesh was below 1 for only 20 days, which was observed during May 24- 25, June 19-21, from June 30 to July 6, July 9-12, and July 16-19,2020.

  • The initial Rt of Bangladesh was 3, whereas the Rt on the day of imposing nation-wide lockdown was 1.47, at the end of lockdown phase-1 was 1.06, at the end of lockdown phase-2 was 1.33.

  • The mean Rt fell by 13.55% from May 31 to July 21, 2020, despite easing of lockdown in Bangladesh.

  • The Rt continued to fall below the threshold value one steadily from the beginning of July and sustained around one.

  • We suspect that a low testing rate may influence the constant decline of Rt below threshold value 1 in the course of July.

  • The mean Rt fell by 13.55% from May 31 to July 21, 2020, despite easing of lockdown in Bangladesh.

  • As of July 21, the current estimate of Rt is 1.07(0.92-1.15: 90% HDI), meaning that an infected individual is spreading the virus to an average of one other, with 0.07 added chance of infecting a second individual.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.04.20168351: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The calculations and visualizations were generated using NumPy, pandas, matplotlib, SciPy stats and interpolation packages of Python 3.
    NumPy
    suggested: (NumPy, RRID:SCR_008633)
    matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)
    SciPy
    suggested: (SciPy, RRID:SCR_008058)
    Python
    suggested: (IPython, RRID:SCR_001658)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations: Comparatively to other Rt estimation models, adapted Bettencourt and Ribeiro methods 22,23 can lead to biased Rt estimates when the underlying dynamics of a pathogen are not well understood as reported by Gostic et al.26 The model may face limitations associated with data uncertainties such as differences in testing, inconsistent, delayed reporting, and low number cases, and high variability at the district level. It is worth noting that there is a delayed, inconsistent, and lower infection report of cases at the district level, that might overestimate Rt at the district level. The results are impacted by testing rate, increases, and decreases in the testing rate will increase and decrease reproduction number estimates, respectively. However, calculating an approximate Rt using available data may provide valuable insights into the dynamics of the COVID-19 outbreak in Bangladesh. Follow up: As the COVID-19 pandemic is already continuing in Bangladesh, despite no nation-wide lockdown in place, schools, college, universities remained close till now, and it is important to watch daily Rt for Bangladesh to set up comprehensive strategies by policy-makers. Given the urgency of the COVID-19 situation in Bangladesh, a daily Rt estimation for COVID-19 in Bangladesh can be found at (https://wolf-dev.github.io/rt/).

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.08.04.20168351v1 on medRxiv