TY - JOUR
T1 - Lead time of early warning by wastewater surveillance for COVID-19
T2 - Geographical variations and impacting factors
AU - Kumar, Manish
AU - Jiang, Guangming
AU - Thakur, Alok Kumar
AU - Chatterjee, Shreya
AU - Bhattacharya, Tanushree
AU - Mohapatra, Sanjeeb
AU - Chaminda, Tushara
AU - Vithanage, Meththika
AU - Tyagi, Vinay Kumar
AU - More Authors, null
PY - 2022
Y1 - 2022
N2 - The global data on the temporal tracking of the COVID-19 through wastewater surveillance needs to be comparatively evaluated to generate a proper and precise understanding of the robustness, advantages, and sensitivity of the wastewater-based epidemiological (WBE) approach. We reviewed the current state of knowledge based on several scientific articles pertaining to temporal variations in COVID-19 cases captured via viral RNA predictions in wastewater. This paper primarily focuses on analyzing the WBE-based temporal variation reported globally to check if the reported early warning lead-time generated through environmental surveillance is pragmatic or latent. We have compiled the geographical variations reported as lead time in various WBE reports to strike a precise correlation between COVID-19 cases and genome copies detected through wastewater surveillance, with respect to the sampling dates, separately for WASH and non-WASH countries. We highlighted sampling methods, climatic and weather conditions that significantly affected the concentration of viral SARS-CoV-2 RNA detected in wastewater, and thus the lead time reported from the various climatic zones with diverse WASH situations were different. Our major findings are: i) WBE reports around the world are not comparable, especially in terms of gene copies detected, lag-time gained between monitored RNA peak and outbreak/peak of reported case, as well as per capita RNA concentrations; ii) Varying sanitation facility and climatic conditions that impact virus degradation rate are two major interfering features limiting the comparability of WBE results, and iii) WBE is better applicable to WASH countries having well-connected sewerage system.
AB - The global data on the temporal tracking of the COVID-19 through wastewater surveillance needs to be comparatively evaluated to generate a proper and precise understanding of the robustness, advantages, and sensitivity of the wastewater-based epidemiological (WBE) approach. We reviewed the current state of knowledge based on several scientific articles pertaining to temporal variations in COVID-19 cases captured via viral RNA predictions in wastewater. This paper primarily focuses on analyzing the WBE-based temporal variation reported globally to check if the reported early warning lead-time generated through environmental surveillance is pragmatic or latent. We have compiled the geographical variations reported as lead time in various WBE reports to strike a precise correlation between COVID-19 cases and genome copies detected through wastewater surveillance, with respect to the sampling dates, separately for WASH and non-WASH countries. We highlighted sampling methods, climatic and weather conditions that significantly affected the concentration of viral SARS-CoV-2 RNA detected in wastewater, and thus the lead time reported from the various climatic zones with diverse WASH situations were different. Our major findings are: i) WBE reports around the world are not comparable, especially in terms of gene copies detected, lag-time gained between monitored RNA peak and outbreak/peak of reported case, as well as per capita RNA concentrations; ii) Varying sanitation facility and climatic conditions that impact virus degradation rate are two major interfering features limiting the comparability of WBE results, and iii) WBE is better applicable to WASH countries having well-connected sewerage system.
KW - SARS-CoV-2
KW - Temporal and spatial variation
KW - WBE
KW - Seasonality
KW - COVID-19
UR - http://www.scopus.com/inward/record.url?scp=85127110864&partnerID=8YFLogxK
U2 - 10.1016/j.cej.2022.135936
DO - 10.1016/j.cej.2022.135936
M3 - Review article
SN - 0009-2460
VL - 441
JO - Chemical Engineering
JF - Chemical Engineering
M1 - 135936
ER -