Understanding the state of the COVID‐19 pandemic relies on infection and mortality data. Yet official data may underestimate the actual cases due to limited symptoms and testing capacity. We offer a simulation‐based approach which combines various sources of data to estimate the magnitude of outbreak. Early in the epidemic we applied the method to Iran's case, an epicenter of the pandemic in winter 2020. Estimates using data up to March 20th, 2020, point to 916,000 (90% UI: 508 K, 1.5 M) cumulative cases and 15,485 (90% UI: 8.4 K, 25.8 K) total deaths, numbers an order of magnitude higher than official statistics. Our projections suggest that absent strong sustaining of contact reductions the epidemic may resurface. We also use data and studies from the succeeding months to reflect on the quality of original estimates. Our proposed approach can be used for similar cases elsewhere to provide a more accurate, early, estimate of outbreak state.

中文翻译：

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基于模拟的估计COVID-19在伊朗的早期传播：实际病例与确诊病例。

了解COVID-19大流行的状态取决于感染和死亡率数据。然而，由于症状和测试能力有限，官方数据可能低估了实际病例。我们提供了一种基于模拟的方法，该方法结合了各种数据源来估计爆发的程度。在该流行病的早期，我们将该方法应用于伊朗的病例（即2020年冬季大流行的中心）。使用截至2020年3月20日的数据进行估算，得出的累计病例为916,000（90％UI：508 K，150万），有15,485（ 90％的用户界面：8.4 K，25.8 K）总死亡人数，比官方统计数字高一个数量级。我们的预测表明，缺乏强有力的持续接触可以减少流行病的再次流行。我们还使用接下来几个月的数据和研究来反思原始估算的质量。