A Computational Modeling Study of COVID-19 in Bangladesh

Abstract

The COVID-19 pandemic has spread globally. Only three cases in Bangladesh were reported on March 8, 2020. Here, we aim to predict the epidemic progression for 1 year under different scenarios in Bangladesh. We extracted the number of daily confirmed cases from March 8 to July 20, 2020. We considered the suspected-infected-removed (SIR) model and performed a maximum likelihood-based grid search to determine the removal rate (ɣ). The transmission was modeled as a stochastic random walk process, and sequential Monte Carlo simulation was run 100 times with bootstrap fits to infer the transmission rate (β) and R t. According to the simulation, the (real) peak daily incidence of 3,600 would be followed by a steady decline, reaching below 1,000 in late January 2021. Thus, the model predicted that there would still be more than 300 cases/day even after a year. However, with proper interventions, a much steeper decline would be achieved following the peak. If we apply a combined (0.8β, 1.2ɣ) intervention, there would be less than 100 cases by mid-October, only around five odd cases at the beginning of the year 2021, and zero cases in early March 2021. The predicted total number of deaths (in status quo) after 1 year would be 8,533 which would reduce to 3,577 if combined (0.8β, 1.2ɣ) intervention is applied. We have also predicted the ideal number of tests that Bangladesh should perform and based on that redid the whole simulation. The outcome, though worse, would be manageable with interventions according to the simulation.

Spatio-temporal estimation of basic and effective reproduction number of COVID-19 and post-lockdown transmissibility in Bangladesh

“…Our results are similar to previously reported R 0 in China [ 17 , 27 ] and neighboring country India [ 28 ]. After a week of nation-wide lockdown, R t decreased substantially from early April 2020 in Bangladesh, which corroborates with those of [ 29 , 30 ]. Our finding suggests that Bangladesh has seen an upheaval of R t in early February 2021, which corroborates with Abbott et al [ 31 ].…”

Short-term forecasting of the COVID-19 outbreak in India

“…Some studies have revealed how multiple variables contribute to the spread of the virus, 26 but with the inclusion of proper interventions, the spread of COVID-19 can be monitored. 27 However, it should be mentioned that this forecast is strongly related to the past pattern. The current situation in India represents a declining trend in daily reported infections.…”

Country-Level Governance Indicators as Predictors of COVID-19 Morbidity, Mortality, and Vaccination Coverage: An Exploratory Global Analysis

“… 11 Moreover, studies have shown that the increase in COVID-19 cases is due to a country’s poor governance, increased corruption, inadequate healthcare facilities, and weak public health communication. 12 , 13 The COVID-19 pandemic has tested healthcare systems and their structure for emergency responsiveness through their supply-chain response and high demand for ICU beds. 14 Thus far, many models of governance have shown poor response, especially in rural areas where the emergency support system has suffered severely with a shortage of medical supplies and poor treatment levels.…”