Improving the reproduction number calculation by treating for daily variations of SARS-CoV-2 cases
Drewes, H.; Flaeschner, G.; Moeller, P.
Show abstract
The Covid-19 pandemic impacted the human life all over the globe, starting in the year of its emergence, 2019, and in the following years. A epidemiological key indicator that gained particular recognition in politics and decision making is the time-dependent reproduction number Rt, which is commonly calculated by institutions responsible for disease control following a method presented by Cori et. al. Here, we propose an improved as well as an alternative method, which make the calculation more stable against oscillations arising from daily variations in testing. Both methods can be used without great statistical knowledge or effort. The methods provides a smoother result without increasing the time-lag, and provides an advantage particular in the timeframe of weeks, which might serve as a better ground for forecasts and the raising of alarms.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Performance of early warning signals for disease re-emergence: a case study on COVID-19 data 95%
- A mechanistic and data-driven reconstruction of the time-varying reproduction number: Application to the COVID-19 epidemic 95%
- Inferring age-specific differences in susceptibility to and infectiousness upon SARS-CoV-2 infection based on Belgian social contact data 94%
Similar papers in this journal
- Modelling the epidemic growth of preprints on COVID-19 and SARS-CoV-2 93%
- Worldwide clustering and infection cycles as universal features of multiscale stochastic processes in the SARS-CoV-2 pandemic 91%
- Social heterogeneity drives complex patterns of the COVID-19 pandemic: insights from a novel Stochastic Heterogeneous Epidemic Model (SHEM) 90%
Similar papers in this journal
- Nowcasting and Forecasting COVID-19 Waves: The Recursive and Stochastic Nature of Transmission 94%
- Reports of deaths are an exaggeration: German (PCR-test-positive) fatality counts during the SARS-CoV-2 era in the context of all-cause mortality 94%
- Estimating COVID-19 cases and outbreaks on-stream through phone-calls 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.