Covid-19 data dashboard launched to help public understand virus risks
The dashboard also gives 'metrics to prepare for future outbreaks, and monitoring Covid-19 hospital admissions'.
Picture: iStock.
The South African Covid-19 Modelling Consortium (SACMC) and the National Institute for Communicable Diseases (NICD) have launched a Covid-19 data dashboard to assist the public to understand the risks of the virus so they can “make educated decisions”.
The #SACMCEpidemicExplorer is a dashboard built by the SACMC to explore the #COVID19 epidemic in SA, analysing resurgence risk, presenting metrics to prepare for future outbreaks & monitoring #COVID19 hospital admissions. Find out more here: https://t.co/yWfGtYeHKJ pic.twitter.com/4cBecehQcR
— NICD (@nicd_sa) December 15, 2020
The SACMC Epidemic Explorer dashboard includes figures and analyses used to monitor the epidemic at the district and provincial level, and identify second waves.
#COVID19 The following elements contributed to the development of the SACMC dashboard, namely case threshold metric, sustained increase monitoring and hospital admissions data. #StopThe2ndWave pic.twitter.com/NoQjiaLoQZ
— NICD (@nicd_sa) December 15, 2020
The dashboard also gives “metrics to prepare for future outbreaks, and monitoring Covid-19 hospital admissions”.
The SACMC Epidemic Explorer dashboard explores the #COVID19 epidemic in South Africa, analysing resurgence risk, presenting metrics to prepare for future outbreaks, and monitoring #COVID19 hospital admissions. https://t.co/GRkSMjFzqE pic.twitter.com/ltJOYL3XcP
— NICD (@nicd_sa) December 15, 2020
“This open access dashboard presents a subset of the metrics used to support the planning efforts of the government of South Africa. The public can use it to assess the Covid-19 risk level in any district in the country. This dashboard is best viewed on a computer. If viewing on a mobile device, zoom in to see plots in detail. If the dashboard is idle for more than 10 minutes, it will time out. Please refresh your browser to load it again.”
The importance of a 2nd wave means our health system needs to prepare for a surge in #COVID-19 cases or hospitalisations. And the public also needs this data to make responsible decisions relating to their travel and risk. #StopThe2ndWave pic.twitter.com/fQxpxGeA1z
— NICD (@nicd_sa) December 15, 2020
The data used for resurgence analysis is from the NICD NMC-SS case linelist and is updated on a weekly basis.
Still wondering how the country reached the 2nd #COVID19 wave? Check out the following graph from the South African COVID-19 Modelling Consortium (SACMC). #StopThe2ndWave pic.twitter.com/1aO5HiblEk
— NICD (@nicd_sa) December 15, 2020
“Case data should be interpreted in conjunction with test positivity, growth rates and other metrics that are not presented here.
SACMC experts reveal the dashboard metrics and talk to the #COVID19 hospital admissions in the Eastern Cape Province. #StopThe2ndWave pic.twitter.com/plPt4YEu2p
— NICD (@nicd_sa) December 15, 2020
“Provincial, district and sub-district case allocations are mapped primarily according to residential address, or alternatively the facility where the sample was collected. Missing data and procedures for extracting and geocoding address data may result in allocation errors, particularly at more granular spatial resolutions [ie, below province level]. While provincial allocations of cases are complete and robust, district data are available for ~87% of cases and sub-district allocations for only ~70% of cases. In order to make the most of available data, the SACMC Epidemic Explorer utilises the laboratory report date to calculate the resurgence metrics.
The SA #COVID19 Modelling Consortium (SACMC) team is live right now introducing the dashboard to media, to assist the public in better understanding the risks. #StopThe2ndWave pic.twitter.com/SWvDpBya2O
— NICD (@nicd_sa) December 15, 2020
The number of Covid-19 hospital admissions is may change from day to day as facilities go back and capture historical data.
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“At any given point in time, data on some discharges and deaths are in the process of being updated. Therefore, we have right censored the data by three days to account for this. Furthermore, incomplete data submissions and delays in updating admission and outcome data in the DATCOV system could influence the interpretation of data.”
Compiled by Makhosandile Zulu
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