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Since the beginning of the COVID-19 pandemic, many dashboards have emerged asuseful tools to monitor the evolution of the pandemic, inform the public, andassist governments in decision making. Our goal is to develop a globallyapplicable method, integrated in a twice daily updated dashboard that providesan estimate of the trend in the evolution of the number of cases and deathsfrom reported data of more than 200 countries and territories, as well as aseven-day forecast. One of the significant difficulties to manage a quicklypropagating epidemic is that the details of the dynamic needed to forecast itsevolution are obscured by the delays in the identification of cases and deathsand by irregular reporting. Our forecasting methodology substantially relies onestimating the underlying trend in the observed time series using robustseasonal trend decomposition techniques. This allows us to obtain forecastswith simple, yet effective extrapolation methods in linear or log scale. Wepresent the results of an assessment of our forecasting methodology and discussits application to the production of global and regional risk maps.

Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide