Links between Transport, Air Quality and COVID-19 Spread in Bangladesh: Summary of Findings

Did COVID19 related policies affect the spread of the pandemic?

Yes they did. Regression analysis of daily new positive COVID-19 cases in Bangladesh reveals that many of the interventions had the desired effects in terms of reducing the spread of the pandemic. Although some of the restrictions were combined together at the beginning, the main interest is on the relative impacts of individual measures, which is presented here. The largest beneficial impact was derived from the full closure of offices and public transport. Since these two happened at the same time, their effects could not be estimated separately. The closure of shops at the beginning also had beneficial effects, but the effect was around 70% of the joint effects of full ‘office and public transport’ closure. This high impact was due to the heavy shopping prior to the Eid-ul-Fitr, when the restriction was lifted. Statistically, the operation of public transport system and offices at half capacity did not have any impact on the spread – this is possibly a result of lax implementation. Opening of garment factories earlier than other offices did not have a statistically significant adverse effect, but the large mobilization of people during the indecision of opening garment factories by the business leaders did. Somewhat surprisingly, the mandatory mask use regulation did not have any statistically significant effect. This is possibly because of the lax and inappropriate use of masks, and the risk-compensation due to increased mobility and interactions resulting from a sense of safety due to the mask regulation. Stricter implementations and effective messaging would likely have a significant impact. Eid-ul-Fitr increased the spread, likely due to the increased social interactions during the festivities. We did not get statistically significant effects for Eid-ul-Adha, possibly because mobility was already increasing due to the compulsory mask mandate. Fig. 3 on the relative effectiveness of different policies can be used for future intervention design, with the caveat that the results are dependent on the quality of the underlying data.