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Background : For diseases like Covid-19, where it has been difficult to identify the true number of infected people, or where the number of known cases is heavily influenced by the number of tests performed, hospitalizations and deaths play a significant role in understanding the epidemic and in determining the appropriate response. However, the Covid-19 deaths data reported by some countries display a significant weekly variability, which can make the interpretation and use of the death data in analysis and modeling difficult.    Methods : We derive the mathematical relationship between the series of new daily deaths by reporting date and the series of deaths by death date. We then apply this formalism to the corresponding time-series reported by Sweden during the Covid-19 pandemic.    Results : The practice of reporting new deaths daily, as is standard procedure during an outbreak in most countries and regions, should be viewed as a time-dependent filter, modulating the underlying true death curve. After having characterized the Swedish reporting process, we show how smoothing of the Swedish reported daily deaths series results in a curve distinctly different from the true death curve. We also comment on the use of nowcasting methods.    Conclusions : Modelers and analysts using the series of new daily deaths by reporting date should take extra care when it is highly variable and when there is a significant reporting delay. It might be appropriate to instead use the series of deaths by death date combined with a nowcasting algorithm as basis for their analysis.

On the use of real-time reported mortality data in modelling and analysis during an epidemic outbreak