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Short-term real-time prediction of total number of reported..:
Reddy, Tarylee
;
Shkedy, Ziv
;
Janse van Rensburg, Charl
...
Reddy, T., Shkedy, Z., Janse van Rensburg, C. et al. Short-term real-time prediction of total number of reported COVID-19 cases and deaths in South Africa: a data driven approach. BMC Medical Research Methodology 21, 15 (2021). https://doi.org/10.1186/s12874-020-01165-x.. , 2021
Link:
http://hdl.handle.net/2263/81650
RT Journal T1 <Title>Short-term real-time prediction of total number of reported COVID-19 cases and deaths in South Africa : a data driven approach</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftunivpretoria:oai:repository.up.ac.za:2263_81650&Exemplar=1&LAN=DE A1 Reddy, Tarylee A1 Shkedy, Ziv A1 Janse van Rensburg, Charl A1 Mwambi, Henry A1 Debba, Pravesh A1 Zuma, Khangelani A1 Manda, S.O.M. (Samuel) PB BMC YR 2021 K1 Phenomenological models K1 Prediction K1 Richards model K1 COVID-19 pandemic K1 Coronavirus disease 2019 (COVID-19) K1 South Africa (SA) K1 Logistic growth model JF Reddy, T., Shkedy, Z., Janse van Rensburg, C. et al. Short-term real-time prediction of total number of reported COVID-19 cases and deaths in South Africa: a data driven approach. BMC Medical Research Methodology 21, 15 (2021). https://doi.org/10.1186/s12874-020-01165-x. LK http://hdl.handle.net/2263/81650 DO http://hdl.handle.net/2263/81650 SF ELIB - SuUB Bremen
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