A longitudinal survey for genome-based identification of SARS-CoV-2 in sewage water in selected lockdown areas of Lahore city, Pakistan; a potential approach for future smart lockdown strategy

Yaqub, T.; Nawaz, M.; Shabbir, M. Z.; Ali, M. A.; Altaf, I.; Raza, S.; Shabbir, M. A. B.; Ashraf, M. A.; Aziz, S. Z.; Cheema, S. Q.; Shah, M. B.; Hassan, S.; Rafique, S.; Sardar, N.; Mehmood, A.; Aziz, M. W.; Fazal, S.; Khan, N.; Khan, M. T.; Attique, M. M.; Asif, A.; Anwar, M.; Awan, N. A.; Younis, M. U.; Bhatti, M. A.; Tahir, Z.; Mukhtar, N.; Sarwar, H.; Rana, M. S.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has affected more than 15 million people and, as of 22 July 2019, caused deaths of more than 0.6 million individuals globally. With the excretion of SARS-CoV-2 in the stool of symptomatic and asymptomatic COVID-19 patients, its genome detection in the sewage water can be used as a powerful epidemiological tool to predict the number of positive cases in a population. This study was conducted to detect SARS-CoV-2 genome in sewage water during the lockdown. Sewage samples, from 28 pre-selected sites, were collected on alternate days from 13-25 July, 2020 from two selected areas [Johar Town (n = 05) and Township (n = 23)], where smart lockdown were implemented by the government authorities on 9th July, 2020. Genomic RNA was extracted and the SARS-CoV-2 was detected and quantified using commercially available kit through Real-Time PCR. Out of 28, sixteen samples were positive on day one while 19, 17, 23, 17, 05 and 09 samples were positive on day 3, 5, 7, 9, 11, and 13, respectively. These results indicate the decreasing viral copy load with the passage of time however few sites did not followed a clear pattern indicating the complexities in sewage water based surveillance i.e time of sampling. Hourly sampling from two sites for 24 hours also revealed the impact of time sampling time on detection of SARS-CoV-2 genome in sewage pipelines and lift/disposal stations. Results of current study indicate a possible role of sewage-based COVID-19 surveillance in monitoring and execution of smart lockdowns.