For more information on the wastewater surveillance program refer to the Queensland Health wastewater surveillance program results webpage: https://www.qld.gov.au/health/conditions/health-alerts/coronavirus-covid-19/current-status/wastewater or contact Queensland Health’s Water Unit at waterquality@health.qld.gov.au;Results from Queensland's wastewater surveillance program for SARS-CoV-2 (Q1 2021)<br/>Results from Queensland's wastewater surveillance for SARS-CoV-2 in 2020<br/>

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Most people with COVID-19 experience mild to moderate symptoms and recover without the need for special treatments. The SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) plays a crucial role in the viral life cycle, and as the active site of the RdRp is the most conserved and accessible region, targeting this region for inhibition of viral replication may be an effective therapeutic approach. Scientists worldwide have proposed the use of preexisting drugs against the novel coronavirus. However, the efficacy of these drugs is somewhat limited. Others reported repurposing the use of existing antiviral agents in order to reduce time and cost compared to de novo drug discovery. For this reason, in this study has been selected a series of ligands used as SARS-CoV-2 virus inhibitors such as: Abacavir, Acyclovir, Amprenavir, Ascorbic acid Vitamin C, Azithromycin, Baloxavir, Boceprevir, Cholecalciferol Vitamin D, Cidofovir, Edoxudine, Emtricitabine, Hydroxychoroquine, Remdesivir. These ligands were analyzed using molecular docking, molecular quantum similarity, and chemical reactivity indices defined within Density Funtional Theory framework. These studies allow to identify the main stabilizing interactions using the crystal structure of SARS-CoV-2 RNA-dependent RNA polymerase. The Molecular Quantum Similarity and Chemical reactivity shows new insights of these ligands that can be used in the COVID-19 treatments.

Datasets in this publication report the number of diagnoses with coronavirus disease (COVID-19) as reported by the Department of Health in Ireland. This includes new cases diagnosed per day and cumulative cases, as well as cases across age groups. The latter also include population estimates by age group for 2019 from Ireland's Central Statistics Office, in order to express cases per million population.

For the files YYYYMMDD_covid_ie_age_groups.csv, variable descriptions are as follows:

• age_group: Age groups, in years
• cases: Total cases of COVID-19 diagnosed in Ireland by age group, as per the Department of Health 
• pop_estimate: National population estimates by age group for 2019  in Ireland, as per the Central Statistics Office (Table 7 https://www.cso.ie/en/releasesandpublications/er/pme/populationandmigrationestimatesapril2019/), expressed in thousands.
• cases_per_million: Cases of COVID-19 diagnosed in Ireland by age group, expressed per 1 million individuals

For the files YYYYMMDD_covid_ie_daily_cases, variable descriptions are as follows:

• date: Date, in DD-MM-YYYY format
• daily_cases: New cases of COVID-19 diagnosed per day in Ireland, as per the Department of Health (https://www.gov.ie/en/news/7e0924-latest-updates-on-covid-19-coronavirus/)
• cumulative_cases: Cumulative number of COVID-19 cases in Ireland
• percent_daily_increase: New cases of COVID-19 diagnosed per day in Ireland as a percentage of cumulative number of cases up to that date.

Datasets in this publication report the number of diagnoses with coronavirus disease (COVID-19) as reported by the Department of Health in Ireland. This includes new cases diagnosed per day and cumulative cases, as well as cases across age groups. The latter also include population estimates by age group for 2019 from Ireland's Central Statistics Office, in order to express cases per million population.

For the files YYYYMMDD_covid_ie_age_groups.csv, variable descriptions are as follows:

• age_group: Age groups, in years
• cases: Total cases of COVID-19 diagnosed in Ireland by age group, as per the Department of Health 
• pop_estimate: National population estimates by age group for 2019  in Ireland, as per the Central Statistics Office (Table 7 https://www.cso.ie/en/releasesandpublications/er/pme/populationandmigrationestimatesapril2019/), expressed in thousands.
• cases_per_million: Cases of COVID-19 diagnosed in Ireland by age group, expressed per 1 million individuals

For the files YYYYMMDD_covid_ie_daily_cases, variable descriptions are as follows:

• date: Date, in DD-MM-YYYY format
• daily_cases: New cases of COVID-19 diagnosed per day in Ireland, as per the Department of Health (https://www.gov.ie/en/news/7e0924-latest-updates-on-covid-19-coronavirus/)
• cumulative_cases: Cumulative number of COVID-19 cases in Ireland
• percent_daily_increase: New cases of COVID-19 diagnosed per day in Ireland as a percentage of cumulative number of cases up to that date.

A search was performed on July 10 2020 in the Scopus database, covering the fields by title, abstract, and keywords, using the terms: COVID19, COVID-19, 2019 novel coronavirus, 2019 nCoV, SARS-CoV-2, 2019 new coronavirus, coronavirus disease 2019 and Wuhan coronavirus. All types of documents were considered. We obtained 26,705 documents, which were used to analyze the productivity, visibility, collaboration, and impact of the publications, in order to offer a clearer insight into the state of research, to know the entities with the greatest contribution to this field, and determine the most relevant studies from a scientometric point of view.