A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data

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What do we know about the COVID-19 epidemic in Iran?

Despite being among the first countries after China to be hit by the COVID-19 pandemic, the Iranian epidemic did not attract the same attention as many other East Asian and European countries did throughout 2020 and 2021. One of the main reasons for this has been the lack of province-level data on the number of reported COVID-19 cases and deaths and scarcity of serological, epidemiological, and genomic data. As a result, the transmission dynamics across the country have largely remained unknown, until now. 

Early analyses of mobility and genomic data (mainly from passengers with a travel link to Iran) revealed that the Iranian epidemic started nearly two months before when the first cases were reported with multiple independent introductions of the virus into the country throughout 2020 [1, 2]. As of May 2022, Iran has experienced 6 epidemic waves with the fourth and fifth waves being dominated by the Alpha and Delta variants of concern (VOCs), respectively [3] - although there is currently not enough genomic data on the sixth wave, like many other countries around the world, it is very likely to have been dominated by the Omicron variant of SARS-CoV-2.

In a previous work [4], we tried to get round the shortfall in COVID-19 statistics in Iran by analysing the seasonal all-cause mortality data from Iran’s National Organization for Civil Registration (NOCR) with the aim of measuring the true burden of disease and estimating the number of infections across the country. We found good agreement between our estimates of attack rates based on excess mortality and serological data for 18 cities across Iran [5].  However, the assumption that all excess deaths can be directly associated with COVID-19 has not been critically appraised in any lower income settings. More specifically, estimates of attack rates based on excess mortality could be biased or inaccurate without accounting for the impact of public health and social measures and the increased chance of reinfection over time due to waning immunity and emergence of VOCs. Neglecting these factors can also result in the underestimation of the potential of the virus for continued transmission. 

In this study, we provided a systematic framework for reconstructing COVID-19 transmission dynamics using excess mortality data that accounts for such factors to estimate the attack rates, number of daily hospital admissions, deaths, and reinfection rates of SARS-CoV-2 across Iran, for the first time.

What does our study add to the understanding of the Iranian epidemic?

We found signs of limited detection of COVID-19 infections and deaths in Iran with approximately half of deaths attributable to COVID-19 not being reported. Several provinces showed significant levels of excess mortality from early February 2020 suggesting that, in agreement with previous phylogenetic and epidemiological studies [2], the epidemic likely started in late December to early January. We also found sustained transmission of the virus across the country with 11 provinces estimated to be reaching close to or higher than 100% attack rate. Similarly, we estimate between 10% to 25% of individuals to be reinfected over the course of 20 months since the start of the pandemic and before the emergence of Omicron. 

We also showed excellent agreement between our model estimates and representative, province-level seroprevalence measurements across the country as well as the pattern of daily hospital admissions in all the 31 provinces of Iran throughout the pandemic. Despite a relatively young age structure in Iran, our analysis revealed that the infection fatality ratio (IFR) in most provinces is comparable to high-income countries with a larger percentage of older adults, suggesting that limited access to medical services, coupled with undercounting of COVID-19-related deaths, can have a significant impact on accurate estimation of COVID-19 fatalities. 

What are the broader implications of our study?

Our analysis opens up the possibility for a detailed reconstruction of the COVID-19 transmission dynamics not just for Iran but any other country with adequate information on all-cause mortality. All-cause mortality was able to provide a more complete understanding of the epidemic that Iran has experienced as well as provide a more nuanced understanding of how herd immunity thresholds changed throughout the epidemic. The recent WHO analysis of global excess deaths associated with the pandemic [6] reveals that a large proportion of COVID-19 deaths have occurred undetected in many countries. Applying our framework in these countries may similarly help characterize the levels of immunity in these countries and help explain why the pandemic appeared to play out so differently across the world.

Finally, our findings of high attack rates in several provinces in Iran showed that herd immunity through natural infection has not been achieved in the population despite sustained transmission since the start of the pandemic. Indeed, the fact that Iran experienced yet another wave after Delta with the Omicron variant (not included in our analysis) with possibly as many deaths as the first 2 waves is a testament that controlling COVID-19 by increasing infections is an elusive goal [7].


  1. Eden K, et al. (2020) An emergent clade of SARS-CoV-2 linked to returned travellers from Iran. Virus Evolution, 6(1): veaa027.
  2. Ghafari M, et al. (2021) Lessons for preparedness and reasons for concern from the early COVID-19 epidemic in Iran. Epidemics, 36: 100472.
  3. Yavarian J, et al. (2022) Whole genome sequencing of SARS-CoV2 strains circulating in Iran during five waves of pandemic. PLoS ONE, 17(5): e0267847. 
  4. Ghafari M, Kadivar A, Katzourakis A (2021) Excess deaths associated with the Iranian COVID-19 epidemic: A province-level analysis. International Journal of Infectious Diseases, 107: 101-115.
  5. Ghafari M, Kadivar A, Katzourakis A (2021) Estimates of anti-SARS-CoV-2 antibody seroprevalence in Iran. Lancet Infectious Diseases, 21: 602-603.
  6. Estimates of Excess Mortality Associated With COVID-19 Pandemic (as of 25 March 2022). Geneva: World Health Organization. 5 May 2022 [cited 11 May 2022]. URL: https://www.who.int/data/stories/global-excess-deaths-associated-with-covid-19-january-2020-december-2021
  7. Morens DM, Folkers GK. Fauci AS (2022) The concept of classical herd immunity may not apply to COVID-19. Infectious Diseases; (published online 21 March)  https://doi.org/10.1093/infdis/jiac109.

Mahan Ghafari

Postdoctoral Research Scientist, Big Data Institute, University of Oxford

Virus evolution and infectious disease epidemiology.