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In this study, an Expectation Maximisation algorithm is used to reconstruct the daily incidence of COVID-19 cases from weekly case counts. Using data from 13 US states that maintained mostly daily reporting of COVID-19 cases from March 2020 to February 2022, we evaluate forecasting performance by comparing models using the true daily incidence with those using reconstructed daily incidence. Our results show that forecasts generated from reconstructed incidence perform equally well as those generated using true daily incidence. 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