Highlights • This is the first province-level study to examine COVID-19-related deaths in Iran. • There were nearly 59 000 extra deaths during the epidemic until September 21, 2020. • Some provinces such as Qom and Golestan reached >50% exposure to SARS-CoV-2. • Eighteen provinces recorded significant levels of excess mortality during the fall of 2019. Objective There has been no province-level data on the number of coronavirus disease 2019 (COVID-19)-related deaths in Iran since the start of the pandemic. This study was performed to estimate the number of COVID-19 deaths and population-level exposure per province using seasonal all-cause mortality data. Methods Time-series data were collected from the National Organization for Civil Registration on the seasonal all-cause mortality from spring 2015 to summer 2020 (from March 21, 2015 to September 21, 2020), in accordance with the Solar Hijri (SH) calendar, to estimate the expected number of seasonal deaths for each province using a piecewise linear regression model. A population-weighted infection fatality ratio was then applied to estimate the level of exposure per province during this period. Results From the start of winter to the end of summer (from December 22, 2019 to September 21, 2020), there were a total of 58 900 (95% confidence interval 46 900–69 500) excess deaths across all 31 provinces, with 27% (95% confidence interval 20–34%) estimated nationwide exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In particular, Qom and Golestan were among the hardest-hit provinces, with nearly 57% exposure, while another 27 provinces showed significant levels of excess mortality in at least one season with >20% population-level exposure to the virus. Unexpectedly high levels of excess mortality were also detected during fall 2019 (from September 23 to December 21, 2019) across 18 provinces, unrelated and prior to the start of the COVID-19 pandemic. Conclusions This study quantified the pattern of spread of COVID-19 across the country and identified areas with the largest epidemic growth requiring the most immediate interventions.
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