filmov
tv
Wastewater Surveillance in the Management of Covid 19: Experiences from Three Countries
Показать описание
Webinar presented and hosted by the Academy of Science of South Africa (ASSAf) and the South African Medical Research Council (SAMRC) on 31 August 2021.
Since the advent of the COVID-19 pandemic, wastewater surveillance for SARS-CoV-2 RNA has emerged to be an important tool in the management of the disease. The viral RNA can be isolated in wastewater around one to two weeks before it is usually detected through human testing at community level. Direct correlations have been found between the concentrations of SARS-CoV-2 RNA in wastewater and the number of cases of COVID-19 in a particular wastewater catchment area, providing the basis for a COVID-19 Early Warning System. Being relatively affordable and reliable, the tool appears to be particularly valuable in settings where epidemiological data are not available, to establish and adjust public health management strategies.
In this Webinar, the experiences, challenges encountered, and lessons learned in the course of rolling out wastewater surveillance programmes in the United Kingdom, South Africa and Nigeria are discussed, including preliminary information on the tracking of SARS-CoV-2 variants in wastewater.
Webinar Content
Moderator: Professor Angela Mathee, South African Medical Research Council (SAMRC)
Welcome and Introductory Remarks: Professor Himla Soodyall, Academy of Science of South Africa
Wastewater-Based Epidemiology for SARS-CoV-2 in Nigeria: Prospects, Pursuits and Challenges: Professor Vincent Chigor, University of Nigeria
Wastewater surveillance in the fight to curb COVID-19 in South Africa: Dr Renee Street, South African Medical Research Council (SAMRC)
The use of wastewater-based epidemiology (WBE) to track circulating SARS-CoV-2 variant in Cape Town, South Africa: Professor Rabia Johnson and Dr Pritika Ramharack, South African Medical Research Council (SAMRC)
Use of wastewater analysis to evaluate the incidence of SARS-CoV-2 in the UK population: Dr Kata Farkas, Bangor University
Since the advent of the COVID-19 pandemic, wastewater surveillance for SARS-CoV-2 RNA has emerged to be an important tool in the management of the disease. The viral RNA can be isolated in wastewater around one to two weeks before it is usually detected through human testing at community level. Direct correlations have been found between the concentrations of SARS-CoV-2 RNA in wastewater and the number of cases of COVID-19 in a particular wastewater catchment area, providing the basis for a COVID-19 Early Warning System. Being relatively affordable and reliable, the tool appears to be particularly valuable in settings where epidemiological data are not available, to establish and adjust public health management strategies.
In this Webinar, the experiences, challenges encountered, and lessons learned in the course of rolling out wastewater surveillance programmes in the United Kingdom, South Africa and Nigeria are discussed, including preliminary information on the tracking of SARS-CoV-2 variants in wastewater.
Webinar Content
Moderator: Professor Angela Mathee, South African Medical Research Council (SAMRC)
Welcome and Introductory Remarks: Professor Himla Soodyall, Academy of Science of South Africa
Wastewater-Based Epidemiology for SARS-CoV-2 in Nigeria: Prospects, Pursuits and Challenges: Professor Vincent Chigor, University of Nigeria
Wastewater surveillance in the fight to curb COVID-19 in South Africa: Dr Renee Street, South African Medical Research Council (SAMRC)
The use of wastewater-based epidemiology (WBE) to track circulating SARS-CoV-2 variant in Cape Town, South Africa: Professor Rabia Johnson and Dr Pritika Ramharack, South African Medical Research Council (SAMRC)
Use of wastewater analysis to evaluate the incidence of SARS-CoV-2 in the UK population: Dr Kata Farkas, Bangor University
0:58:46
3:11:40
0:01:45
0:30:17
0:30:41
0:07:18
0:01:37
0:02:40
0:46:41
1:02:21
1:19:42
0:57:29
0:05:24
0:53:05
1:06:51
0:19:58
1:06:46
0:03:41
0:24:33
1:01:34
1:44:20
0:59:12
0:36:34