Abstract

Background: Bangladesh is among the top fifteen SARS-CoV-2 (COVID-19) affected countries in the world. However, the country has the lowest testing capacity per million in that group. Faced with growing pressure to continue livelihoods, Bangladesh government lifted the lockdown abruptly, costing an immediate surge in the virus caseload. Against this backdrop, there is a dire need to derive data-driven planning, for mitigation and management of COVID-19 cases in Bangladesh – prioritizing the efficient allocation of limited resources. Utilizing publicly available data, this paper introduces a contagion risk (CR) index, which can work as a credible proxy to detect potential virus hotspots – aiding policymakers with proper planning. Methods: Grounded on disease spreadability vectors, we derived the CR-Index at the district level, based on nine variables across five domains: socio-economy, demography, occupation, migration, and health infrastructure. The CR-Index is validated against the district wise COVID-19 cases across the study period. Findings: CR-Index is positively correlated with district-wise COVID-19 cases across the pandemic period (average correlation is 0.65, p-value 0.001). The proposed CR-Index can predict seven out of the top ten COVID-19 caseload districts of Bangladesh. Week-by-week regressions also show similar findings. Interpretation: The CR-Index proposed in this paper could work as the foundation to consider zone-specific mobility restriction measures in Bangladesh, which can be an effective solution to balance economic activities while limiting disease spread. This index gives developing country planners a viable alternative to economy-wide shutdown policy and can be replicated with available national statistics for other countries.Funding Statement: None.Declaration of Interests: The authors declare no competing interests.

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