Abstract
Genomics, combined with population mobility data, used to map importation and spatial spread of SARS-CoV-2 in high-income countries has enabled the implementation of local control measures. Here, to track the spread of SARS-CoV-2 lineages in Bangladesh at the national level, we analysed outbreak trajectory and variant emergence using genomics, Facebook ‘Data for Good’ and data from three mobile phone operators. We sequenced the complete genomes of 67 SARS-CoV-2 samples (collected by the IEDCR in Bangladesh between March and July 2020) and combined these data with 324 publicly available Global Initiative on Sharing All Influenza Data (GISAID) SARS-CoV-2 genomes from Bangladesh at that time. We found that most (85%) of the sequenced isolates were Pango lineage B.1.1.25 (58%), B.1.1 (19%) or B.1.36 (8%) in early-mid 2020. Bayesian time-scaled phylogenetic analysis predicted that SARS-CoV-2 first emerged during mid-February in Bangladesh, from abroad, with the first case of coronavirus disease 2019 (COVID-19) reported on 8 March 2020. At the end of March 2020, three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity in Bangladesh, combined with the mobility data, revealed that the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka (the capital of Bangladesh) and the rest of the country, disseminated three dominant viral lineages. Further analysis of an additional 85 genomes (November 2020 to April 2021) found that importation of variant of concern Beta (B.1.351) had occurred and that Beta had become dominant in Dhaka. Our interpretation that population mobility out of Dhaka, and travel from urban hotspots to rural areas, disseminated lineages in Bangladesh in the first wave continues to inform government policies to control national case numbers by limiting within-country travel.
Highlights
The COVID-19 pandemic has motivated countries around the world to obtain high-resolution data on the local spread of SARS-CoV-2 and arising variants of interest and variants of concern (VOCs)
Genomic surveillance of SARS-CoV-2 is commonplace in high-income countries but is highly necessary in low- and middle-income countries (LMICs), including Bangladesh, to guide within-country health policies pertinent to the pandemic
Bayesian phylodynamic analysis estimated that the mutation rate of the isolates from Bangladesh is 0.7 × 10−3 substitutions per site per year (~20 mutations per genome per year), which is consistent with global estimates[5]
Summary
The COVID-19 pandemic has motivated countries around the world to obtain high-resolution data on the local spread of SARS-CoV-2 and arising variants of interest and variants of concern (VOCs). Clonal expansion and community transmission surveillance, outside the capital Dhaka, remained challenging As a result, it has been unclear how the epidemic has spread in Bangladesh and what this means for the potential spread of SARS-CoV-2 variants, and the best use of interventions, including therapeutics and vaccines. Mobile phone data have been used extensively as a way to monitor the population behavioural response to the epidemic in real time, and to understand the human drivers of transmission[11,12] These new data streams may be powerful tools for monitoring the pandemic in LMICs, in which RT–PCR testing capacity is often highly constrained. It is essential that these variants and any newly emerging variants are observed and monitored by genomic surveillance in LMICs as well as in high-income countries (HICs) This is partly enabled through international data sharing on global databases such as GISAID
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