This git repo provides data sets used to support The Institute of Environmental Science & Research (ESR) wastewater surveillance programme testing for SARS-CoV-2 and wastewater dashboard. We provide wastewater SARS-CoV-2 concentrations, associated clinical case data and geographic metadata.
Funding for the dashboard and data repository was provided by the Ministry of Health.
The SARS-CoV-2 wastewater surveillance programme was launched to monitor and track potential cases of COVID-19 in Aotearoa. From 2020 this has aided Aotearoa's ability to identify potential outbreaks and is now being used to track viral load in communities and monitor variants. The methods used for the identifications of SARS-CoV-2 in wastewater are described in Hewitt et al 2022.
Wastewater sites are selected based on several factors including population and geographic coverage. New sites may be added over time and/or sampling may reduce in frequency or cease for other sites. Typically, samples are collected twice per week from larger wastewater catchments and once a week from smaller towns and communities. This is also subject to change.
Most samples are collected by an autosampler, which collects a small volume of wastewater at regular intervals over the course of a 25-hour period. When composite samplers are not available, 'grab' samples are collected. These range from a sample being taken at a single point in time, to 3 samples taken over 30 minutes, to multiple samples collected over a day. Grab samples represent only the composition of the sources at that time of collection and may not be as representative as a 24-hour composite sample. More variation may be expected with grab samples, samples collected from smaller catchments (an individual case can have a disproportionately large effect on overall viral level in small catchments) and from sites that are only sampled once per week.
The catchment polygons are not included. They are the intellectual property of the individual regional and city councils that operate the treatment plants that we sample from. Some are available publicly, otherwise if you are interested in obtaining specific GIS files for a site, we suggest contacting the relevant council.
The wastewater data shows the SARS-CoV-2 genome copies per litre measured from either an autosampler/grab sample (see lab analysis and methodology for more details). To preserve anonymity of sites with small populations we have excluded these from the site-specific data. These are however still included in the aggregated regional and national wastewater data.
For each sample location if more than one sample is taken this is averaged to get the average copies per person per day for the site that week. This is then normalised using population and wastewater flow.
For the regional aggregated data, the averaged and normalised site data is aggregated using a weighted mean. The weight applied to each site is calculated using site population divided by region population (for that week) making the site results proportional to the regional population. This weighting ensures small catchments are not over-represented and large catchments are not under-represented in the regional aggregation. A 7 day average of GC/person/day is then reported for Monday-Sunday.
For the national aggregated data, each week the averaged and normalised site data is aggregated using a weighted mean. The weight applied is calculated using site population divided by national population (for that week). This weighting like the regional aggregated data ensures small catchments are not over-represented and large catchments under-represented. A 7-day average of GC/person/day is then reported for Monday-Sunday.
Case numbers are calculated by summing up all the new cases reported to the Ministry of Health for that week. Cases are reported on a per-day basis because wastewater samples are generally representative of the viral load in the catchment for the preceding 24-hrs. The report date is aligned with what the Ministry of Health publishes on their website. The average number of new COVID-19 cases reported per day via are collected through NCTS or EpiSurv, when report date is not available the first non-null value from the fields onset date, lab sample date, lab confirmed detection date or earliest date.
cases_national.csv
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week_end_date: end of week date for week covered between Monday-Sunday (YYYY-MM-DD).
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case_7d_avg: average number of new COVID-19 cases reported per day using reported date. If not available, then the first non-null value for onset date, lab sample date, lab confirm detection or earliest date.
ww_national.csv
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week_end_date: end of week date for week covered between Monday-Sunday (YYYY-MM-DD).
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national_population: the sum of catchment populations covered by testing that week.
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copies_per_person_per_day: average of the SARS-CoV-2 genome copies per person per day. Calculated as an average of results from the previous 7 days. Raw SARS-CoV-2 genome copies results are normalised by catchment for population covered by i) catchment for population covered by testing and ii) wastewater flow into the wastewater treatment plant (WWTP) per day.
cases_regional.csv
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week_end_date: end of week date for week covered between Monday-Sunday (YYYY-MM-DD).
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Region: region name.
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case_7d_avg: average number of new COVID-19 cases reported per day using reported date. If not available, then the first non-null value for onset date, lab sample date, lab confirm detection or earliest date.
ww_regional.csv
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week_end_date: end of week date for week covered between Monday-Sunday (YYYY-MM-DD).
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Region: region name
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copies_per_person_per_day: average of the SARS-CoV-2 genome copies per person per day. Calculated as an average of results from the previous 7 days. Raw SARS-CoV-2 genome copies results are normalised by i) catchment for population covered by testing and ii) wastewater flow into the WWTP per day.
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n_site: number of sites within the region contributing to each week's data.
cases_site.csv
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week_end_date: end of week date for week covered between Monday-Sunday (YYYY-MM-DD).
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SampleLocation: wastewater testing site name, with two letter region code, underscore, site name (e.g., "AU_Rosedale").
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copies_per_person_per_day: average of the SARS-CoV-2 genome copies per person per day. Calculated as an average of results from the previous 7 days. Raw SARS-CoV-2 genome copies results are normalised by i) catchment for population covered by testing and ii) wastewater flow into the WWTP per day.
Note: Where meshblocks straddle a watershed between two catchments, the case will be reported for both catchments. To aggregate to higher geographic groupings, please use the cases_regional.csv or cases_national.csv files to avoid double counting.
ww_site.csv
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end of week date for week covered between Monday-Sunday (YYYY-MM-DD).
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SampleLocation: wastewater testing site name ("AU_Rosedale").
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case_7d_avg: An average of the SARS-CoV-2 genome copies per person per day. Raw SARS-CoV-2 genome copies results are normalised by catchment for population covered by testing and normalised for wastewater flow per day. Calculated as an average of results from the previous 7 days.
sites.csv
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SampleLocation: wastewater testing site name, with two letter region code, underscore, site name (e.g., "AU_Rosedale").
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DisplayName: display name used for reporting ("Rosedale").
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SampleType: sampling method used; autosampler or grab.
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Latitude: The latitude of the sampling location, typically a wastewater treatment plant.
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Longitude: The longitude of the sampling location, typically a wastewater treatment plant.
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Population: The estimated population covered by the wastewater catchment area.
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Region: name of region that site is located in.
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shp_label: a unique identifier for the catchment polygons.
variants_last_two_weeks.csv
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variant: variant name
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DisplayName: site display name used on the variants chart.
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detected: boolean (true or false) to indicate whether the variant was detected
Note: Wastewater samples may contain a mixture of SARS-CoV-2 variants from many infected individuals. The results show the proportion of variants detected at the national level. The proportion of each variant in wastewater is a proxy for the proportion of each variant in the community. Variant analysis is only performed on a subset of samples from select wastewater sites - referred to as 'sentinel sites'. National variant proportions are calculated as the mean of the sentinel sites weighted by site population. For further guidance, please refer to the 'Estimated variant prevalence' notes on the ‘About’ page of the
For further guidance, please refer to the 'Estimated variant prevalence' notes on the wastewater dashboard.
ww_data_all.csv
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SampleLocation: wastewater testing site name, with two letter region code, underscore, site name (e.g., "AU_Rosedale").
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sars_gcl: The amount of SARS-CoV-2 genome copies per litre of wastewater.
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Result: Either "Detected" if SARS-CoV-2 was identified in the wastewater sample or "Not detected".
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copies_per_person_per_day: average of the SARS-CoV-2 genome copies per person per day. Calculated as an average of results fro mthe previous 7 days. Raw SARS-CoV-2 genome copies results are normalised by i) catchment for population covered by testing and ii) wastewater flow into the WWTP per day.
Samples are sent from each wastewater treatment plant to ESR. Processing first involves separating the solids from liquid by centrifugation, followed by eluting the virus from the solids. The virus from the solids is then combined with that in the liquid phase and concentrated to a small volume by polyethylene glycol (PEG) precipitation. The viral RNA is extracted. The presence of SARS-CoV-2 RNA in the sample is then determined using RT-qPCR (reverse transcription-quantitative polymerase chain reaction) with the N-gene of the SARS-CoV-2 viral genome. SARS-CoV-2 is considered detected when any of the RT-qPCR replicates are positive. A result of not detected means that SARS-CoV-2 RNA is either absent from the sample, or at a level in the wastewater that is too low to be detected.
When SARS-CoV-2 RNA is detected by RT-qPCR, the concentration in the sample is calculated and converted from genome copy per reaction into genome copies per litre of wastewater (i.e., raw data). The unit conversion considers the initial sample volume, final volume of the concentrate used for RNA extraction, final volume of the eluted RNA, and amount of RNA used in the RT-qPCR template. Low amounts of SARS-CoV-2 RNA in a sample may not be able to be accurately quantified and are recorded as 500 genome copies/L.
If you would like to use this data, please cite: COVID-19 Data Repository by the Institute of Environmental Science and Research", and the url: https://github.com/ESR-NZ/covid_in_wastewater
For academic publications, cite the following paper:
Hewitt, Joanne, et al. "Sensitivity of wastewater-based epidemiology for detection of SARS-CoV-2 RNA in a low prevalence setting." Water Research 211 (2022): 118032. https://doi.org/10.1021/acsestwater.1c00434
This work represents the combined efforts of many individuals and organisations.
We thank the teams across the country who collect the wastewater and associated metadata that underpins this work.
ESR acknowledges the support of councils and wastewater providers across New Zealand who provide us with samples and staff in the public health services in New Zealand who provide us with data from their regions. This work is funded by the Ministry of Health.
- This dataset is owned by the Institute of Environmental Science and Research Limited and licensed for reuse under the Creative Commons Attribution 4.0 International licence. This license means that you are free to copy, distribute and adapt the material, as long as you attribute it to the Institute of Environmental Science and Research Limited and abide by the other license terms. This license does not apply to any logos and trade marks on this website – these specific elements may not be reused without the Institute of Environmental Science and Research Limited's prior written consent.
- If you wish to use the data, you must attribute it as the "COVID-19 Data Repository by the Institute of Environmental Science and Research", and the url: https://github.com/ESR-NZ/covid_in_wastewater
- You may use our application programming interface ("API") to facilitate access to the dataset, whether through a separate website or through another type of software application.
- You may not represent or imply that the Institute of Environmental Science and Research Limited has approved or endorsed the manner or purpose of your use or reproduction of the dataset.
- The Institute of Environmental Science and Research Limited reserves the right at any time in its sole discretion to modify or discontinue (temporarily or permanently) this website, the dataset, and any means of accessing the dataset, with or without prior notice to you.
Data is shared solely for the benefit of the Ministry of Health (MoH), Public Health Service Providers and other Third Party Beneficiaries as defined in the Contract between ESR and the MoH. ESR does not accept any legal liability or responsibility for use of information contained in this repository by any other person or organisation.
The Institute of Environmental Science and Research (ESR) is a Crown Research Institute in Aotearoa. ESR provides science services and research capability across several science disciplines including Public Health, Forensics, Water and the Environment, Genomics and Social Science.