Background: Several studies imply that influenza and other respiratory illness could lead to acute myocardial infarction (AMI), but data from low-income countries are scarce. We investigated the prevalence of recent respiratory illnesses and confirmed influenza in AMI patients, while also exploring their relationship with infarction severity as defined by ST-elevation MI (STEMI) or high troponin levels. Methods: This cross-sectional study, held at a Dhaka tertiary hospital from May 2017 to October 2018, involved AMI inpatients. The study examined self-reported clinical respiratory illnesses (CRI) in the week before AMI onset and confirmed influenza using baseline qRT-PCR. Results: Of 744 patients, 11.3% reported a recent CRI, most prominently during the 2017 influenza season (35.7%). qRT-PCR testing found evidence of influenza in 1.5% of 546 patients, with all positives among STEMI cases. Frequencies of CRI were higher in patients with STEMI and in those with high troponin levels, although these associations were not statistically significant after adjusting for other variables. The risk of STEMI was significantly greater during influenza seasons in unadjusted analysis (RR: 1.09, 95% CI: 1.02- 1.18), however, this relationship was not significant in the adjusted analysis (aRR: 1.03, 95% CI: 0.91- 1.16). Conclusions: In Bangladesh, many AMI patients had a recent respiratory illness history, with some showing evidence of influenza. However, these illnesses showed no significant relationship to AMI severity. Further research is needed to understand these associations better and to investigate the potential benefits of infection control measures and influenza vaccinations in reducing AMI incidence.

Between late December 2019 to early September 2020, over 10 million people globally were reportedly infected by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for the coronavirus disease-2019 (COVID-19). In Africa, more than 300,000 infection occurred within the period, from which several viral genetic sequences were generated. Phylogenetic reconstruction of genomic data can provide epidemiological inferences about time of pathogen introduction, epidemic growth rate and temporal-spatial spread of the infection during disease outbreak. In this work, we studied the genetic epidemiology of COVID-19 in Africa. Genetic sequence data of SARS-CoV-2 and metadata from African countries were obtained from open-source sequence database hosted by the GISAID initiative. Whole genome sequences were subjected to multiple sequence alignment, from which Maximum Likelihood phylogenetic tree was constructed based on the general time reversible model. Of the 227 genetic sequences obtained for 9 African countries (DRC=133, Senegal=23, South Africa=20, Ghana=15, Tunisia=6, Algeria=3, Gambia=3, Egypt=2 and Nigeria=2), 220 were whole genome sequences while 7 were partial genome sequences of the surface glycoprotein S. Phylogenetic analysis confirmed multiple introductions of the virus to the continent from multiple external sources prior to local adaptation and spread. The very close alignment of three viruses - Ghana/1659_S14/2020|EPI_ISL_422405, DRC/KN0054/2020|EPI_ISL_417437, and South_Africa/R05475/2020|EPI_ISL_435059 – to the reference Wuhan strain on the time tree, suggests possible introduction and circulation of the virus into the continent much earlier than when the first case was announced on February 15 2020. In conclusion, this study provided evidence to support multiple introductions of SARS-CoV-2 into Africa, and further suggests that the virus may have already been circulating in the continent prior to official reporting of the first case. Also, there is strong impression to infer likely genetic adaptation of the virus in the continent that may account for the close clustering of isolates from different countries.