Context

With the arrival of the COVID19 virus in New Zealand, the ministry of health is tracking new cases and releasing daily updates on the situation on their webpage: https://www.health.govt.nz/our-work/diseases-and-conditions/covid-19-novel-coronavirus/covid-19-current-cases and https://www.health.govt.nz/our-work/diseases-and-conditions/covid-19-novel-coronavirus/covid-19-current-cases/covid-19-current-cases-details. Much of the information given in these updates are not in a machine-friendly format. The objective of this dataset is to provide NZ Minstry of Health COVID19 data in easy-to-use format.

Content

All data in this dataset has been acquired from the New Zealand Minstry of Health's 'COVID19 current cases' webpage, located here: https://www.health.govt.nz/our-work/diseases-and-conditions/covid-19-novel-coronavirus/covid-19-current-cases. The Ministry of Health updates their page daily, that will be the targeted update frequency for this dataset for the Daily Count of Cases dataset. The Case Details dataset which includes travel details on each case will be updated weekly.

Limitations of this dataset

The mission of this project is to reliably convey data that the Ministry of Health has reported in the most digestable format. Enrichment of data is currently out of scope.

Help improve this dataset

If you find any discrepancies between the Ministry of Health's data and this dataset, please provide your feedback as an issue on the git repo for this dataset: https://github.com/2kruman/COVID19-NZ-known-cases/issues.

Multilingual (EN, KO, IN, ES) corpus acquired from website (https://covid19.govt.nz/) of the New Zealand Government. It contains 250 TUs in total.

This 6MB download is a zip file containing 5 pdf documents and 2 xlsx spreadsheets. Presentation on COVID-19 and the potential impacts on employment

May 2020Waka Kotahi wants to better understand the potential implications of the COVID-19 downturn on the land transport system, particularly the potential impacts on regional economies and communities.

To do this, in May 2020 Waka Kotahi commissioned Martin Jenkins and Infometrics to consider the potential impacts of COVID-19 on New Zealand’s economy and demographics, as these are two key drivers of transport demand. In addition to providing a scan of national and international COVID-19 trends, the research involved modelling the economic impacts of three of the Treasury’s COVID-19 scenarios, to a regional scale, to help us understand where the impacts might be greatest.

Waka Kotahi studied this modelling by comparing the percentage difference in employment forecasts from the Treasury’s three COVID-19 scenarios compared to the business as usual scenario.

The source tables from the modelling (Tables 1-40), and the percentage difference in employment forecasts (Tables 41-43), are available as spreadsheets.

Arataki - potential impacts of COVID-19 Final Report

Employment modelling - interactive dashboard

The modelling produced employment forecasts for each region and district over three time periods – 2021, 2025 and 2031. In May 2020, the forecasts for 2021 carried greater certainty as they reflected the impacts of current events, such as border restrictions, reduction in international visitors and students etc. The 2025 and 2031 forecasts were less certain because of the potential for significant shifts in the socio-economic situation over the intervening years. While these later forecasts were useful in helping to understand the relative scale and duration of potential COVID-19 related impacts around the country, they needed to be treated with care recognising the higher levels of uncertainty.

The May 2020 research suggested that the ‘slow recovery scenario’ (Treasury’s scenario 5) was the most likely due to continuing high levels of uncertainty regarding global efforts to manage the pandemic (and the duration and scale of the resulting economic downturn).

The updates to Arataki V2 were framed around the ‘Slower Recovery Scenario’, as that scenario remained the most closely aligned with the unfolding impacts of COVID-19 in New Zealand and globally at that time.

Find out more about Arataki, our 10-year plan for the land transport system

May 2021The May 2021 update to employment modelling used to inform Arataki Version 2 is now available. Employment modelling dashboard - updated 2021Arataki used the May 2020 information to compare how various regions and industries might be impacted by COVID-19. Almost a year later, it is clear that New Zealand fared better than forecast in May 2020.Waka Kotahi therefore commissioned an update to the projections through a high-level review of:the original projections for 2020/21 against performancethe implications of the most recent global (eg International monetary fund world economic Outlook) and national economic forecasts (eg Treasury half year economic and fiscal update)The treasury updated its scenarios in its December half year fiscal and economic update (HYEFU) and these new scenarios have been used for the revised projections.Considerable uncertainty remains about the potential scale and duration of the COVID-19 downturn, for example with regards to the duration of border restrictions, update of immunisation programmes. The updated analysis provides us with additional information regarding which sectors and parts of the country are likely to be most impacted. We continue to monitor the situation and keep up to date with other cross-Government scenario development and COVID-19 related work. The updated modelling has produced employment forecasts for each region and district over three time periods - 2022, 2025, 2031.The 2022 forecasts carry greater certainty as they reflect the impacts of current events. The 2025 and 2031 forecasts are less certain because of the potential for significant shifts over that time.

Data reuse caveats: as per license.

Additionally, please read / use this data in conjunction with the Infometrics and Martin Jenkins reports, to understand the uncertainties and assumptions involved in modelling the potential impacts of COVID-19.

COVID-19’s effect on industry and regional economic outcomes for NZ Transport Agency [PDF 620 KB]

Data quality statement: while the modelling undertaken is high quality, it represents two point-in-time analyses undertaken during a period of considerable uncertainty. This uncertainty comes from several factors relating to the COVID-19 pandemic, including:

a lack of clarity about the size of the global downturn and how quickly the international economy might recover differing views about the ability of the New Zealand economy to bounce back from the significant job losses that are occurring and how much of a structural change in the economy is required the possibility of a further wave of COVID-19 cases within New Zealand that might require a return to Alert Levels 3 or 4.

While high levels of uncertainty remain around the scale of impacts from the pandemic, particularly in coming years, the modelling is useful in indicating the direction of travel and the relative scale of impacts in different parts of the country.

Data quality caveats: as noted above, there is considerable uncertainty about the potential scale and duration of the COVID-19 downturn. Please treat the specific results of the modelling carefully, particularly in the forecasts to later years (2025, 2031), given the potential for significant shifts in New Zealand's socio-economic situation before then.

As such, please use the modelling results as a guide to the potential scale of the impacts of the downturn in different locations, rather than as a precise assessment of impacts over the coming decade.

Context

Its curious to learn more about my country. If covid-19 really did disappear or not for even a brief moment in new zealand.

Content

What's inside is more than just rows and columns. More analytics will have to be done and distribution analysis to find out what parts actually had no covid.

Acknowledgements

We wouldn't be here without https://nzcoviddashboard.esr.cri.nz/#!/ and stats NZ

Inspiration

Did covid actually disappear in parts of new zealand?

Bilingual (EN-IN) corpus acquired from website (https://covid19.govt.nz/) of the New Zealand Government

New Zealand recorded 2792 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, New Zealand reported 2282861 Coronavirus Cases. This dataset includes a chart with historical data for New Zealand Coronavirus Deaths.

Projected unemployment scenarios in NZ as a result of the COVID-19 pandemic and response to it (extracted from a NZ Treasury Report) [23, 30].

Learning outcomes:Students will gain an understanding of the global patterns of COVID-19 cases, and how this information changes over time.Students will also compare the COVID-19 data with the World Health Organisations health statistics.Other New Zealand GeoInquiry instructional material freely available at https://arcg.is/1GPDXe

Context

2020 has been the year of events (probably for the wrong reasons!). Covid has affected a large number of things and one of them is TRADE.

Content

This dataset contains the ffects of COVID-19 on trade is a weekly update on New Zealand’s daily goods trade with the world from 1 February 2020. Comparing the values with previous years shows the potential impacts of COVID-19.

Acknowledgements

STATS NZ

Inspiration

Curious to know the potential impact of COVID19 on New Zealand's Trade from 1 Feb to 12 Aug 2020 compared to previous years.

License

Creative Commons Attribution 4.0 International

Records of reported Counts of COVID-19 case counts in New Zealand from 2019-2021. Download is a zipped CSV file with readme.

New Zealand No. of Current CIRP Recipients: NZ European data was reported at 126.000 Number in Jan 2021. This records a decrease from the previous number of 1,056.000 Number for Dec 2020. New Zealand No. of Current CIRP Recipients: NZ European data is updated monthly, averaging 4,020.000 Number from Jun 2020 (Median) to Jan 2021, with 8 observations. The data reached an all-time high of 10,164.000 Number in Aug 2020 and a record low of 126.000 Number in Jan 2021. New Zealand No. of Current CIRP Recipients: NZ European data remains active status in CEIC and is reported by Ministry of Social Development. The data is categorized under Global Database’s New Zealand – Table NZ.G094: Monthly Benefit and Supplementary Assistance: COVID-19 Income Relief Payment Recipients (Discontinued).

New Zealand Daily Border Crossing: Departures: Auckland data was reported at 12,974.000 Number in 15 Aug 2024. This records an increase from the previous number of 11,205.000 Number for 14 Aug 2024. New Zealand Daily Border Crossing: Departures: Auckland data is updated daily, averaging 11,738.000 Number from Jan 2016 (Median) to 15 Aug 2024, with 3150 observations. The data reached an all-time high of 21,024.000 Number in 22 Dec 2018 and a record low of 0.000 Number in 15 Jun 2020. New Zealand Daily Border Crossing: Departures: Auckland data remains active status in CEIC and is reported by New Zealand Customs Service. The data is categorized under Global Database’s New Zealand – Table NZ.Q027: Daily Border Crossing. [COVID-19-IMPACT]

New Zealand Daily Border Crossing: Arrivals: Auckland data was reported at 5,552.000 Number in 15 Aug 2024. This records a decrease from the previous number of 11,281.000 Number for 14 Aug 2024. New Zealand Daily Border Crossing: Arrivals: Auckland data is updated daily, averaging 11,831.000 Number from Jan 2016 (Median) to 15 Aug 2024, with 3150 observations. The data reached an all-time high of 20,688.000 Number in 20 Dec 2019 and a record low of 0.000 Number in 28 Jan 2023. New Zealand Daily Border Crossing: Arrivals: Auckland data remains active status in CEIC and is reported by New Zealand Customs Service. The data is categorized under Global Database’s New Zealand – Table NZ.Q027: Daily Border Crossing. [COVID-19-IMPACT]

Context

This Dataset presents New Zealand’s daily export trade with China from 27 January 2020. It compares 2020 values with those from previous years, to show the potential impacts of COVID-19 since its outbreak in late 2019.

We advise caution in making decisions based on this experimental data. Please send any comments to overseastrade@stats.govt.nz.

https://www.stats.govt.nz/experimental/provisional-indications-effects-of-coronavirus-outbreak-on-new-zealand-trade-with-china

Content

Imports from China The cumulative total value of imports from China alone in the past four weeks and one day to 29 February 2020 was about $775 million . This is about $169 million less than for the same period in 2019 .

Daily trade for 1 February–29 February 2020 (published 10 March 2020) Imports from China (experimental, published 10 March 2020) CSV files include imports from China, including key exports of meat, seafood, dairy, and forestry products. The data is provisional and should be regarded as an early, indicative estimate of intentions to export only, subject to revision. These are not official statistics, but an effort to provide the latest available trade data at a time of heightened interest in trade with China. The data compares the four weeks and a day up to 29 February 2020 against previous years. This allows for an estimate to be made of what may have happened to exports, if they had followed typical patterns in the past four weeks.

Acknowledgements

https://www.stats.govt.nz/experimental/provisional-indications-effects-of-coronavirus-outbreak-on-new-zealand-trade-with-china Photo by Andy Li on Unsplash

Inspiration

The Global trade impact of the Coronavirus (COVID-19) Epidemic . “The spread of the new coronavirus is a public health crisis that could pose a serious risk to the macro economy through the halt in production activities, interruptions of people's movement and cut-off of supply chains” - Japanese Finance Minister Taro Aso. G20 gathering in Riyadh, Saudi Arabia, February 24, 2020. " Besides its worrying effects on human life, the novel strain of coronavirus (COVID-19) has the potential to significantly slowdown not only the Chinese economy but also the global economy. China has become the central manufacturing hub of many global business operations. Any disruption of China’s output is expected to have repercussions elsewhere through regional and global value chains. https://unctad.org/en/PublicationsLibrary/ditcinf2020d1.pdf

Health loss (in HALYs) results for the base case (most likely unemployment scenario) (3% discount rate for the remaining life of the NZ population alive in 2011) for various COVID-19 pandemic-induced unemployment scenarios from the NZ Treasury.

IntroductionVasovagal reactions (VVRs) are common but complex donor adverse reactions (DAEs) in blood donations. VVRs have been extensively studied with a multitude of risk factors identified including young age, female gender and first-time donor status. How they may interplay remains obscure.MethodsA total of 1,984,116 blood donations and 27,952 immediate VVRs (iVVRs) and 1,365 delayed VVRs (dVVRs) reported between 2011 and 2021 in NZ were used in multivariate logistic regression analyses each concerning donations with iVVRs as cases and those free of DAEs as controls. For each analysis stepwise selection was used to identify the best model and risk factors carrying significant main effects and/or interactions. Identified interactions informed further in-depth regression analyses to dissect iVVR risk patterns.ResultsOver 95% of VVRs were iVVRs that had lower female preponderance and deferrals than dVVRs. iVVRs had a school seasonal pattern in whole blood donations driven by first-time donors from schools/colleges, and interactions between gender and age group differentiating the first-time from repeat donations. Subsequent regression analyses identified the known and novel risk factors of year and mobile collection sites and their interactions. iVVR rates were roundly elevated in 2020 and 2021 probably because of COVID-19 restrictions like facemask wearing. Exclusion of the 2020 and 2021 data removed the interactions with year, but confirmed interactions of gender with mobile collection sites (p = 6.2e-07) in first-time donations only and with age group in repeat donations only (p 

Context

The Covid-19 virus has had an adverse effect on all levels; from national to personal. The following dataset has the the entries of 55k trade activities during and pre Covid-19 spread for a comprehensive analytical study on the same.

In the month of June 2025, there were around ******* international visitor arrivals to Auckland, New Zealand, marking a decrease from the previous month. The significant recovery in visitor numbers from March 2022 onwards can be attributed to New Zealand re-opening its borders to travelers after a two-year COVID-19 lockout. Nonetheless, international visitor numbers to Auckland still have not recovered to the heights witnessed in December 2019, with over ******* international arrivals recorded.

Context

In October 2021 the World Health Organization (WHO) published an article about how Mental Health services have been pushed to the limit during the COVID-19 pandemic while stating that the next pandemic will be on mental health encouraging governments to increase their expenditure on Mental Health.

While searching for Mental Health service usage and expenditure in New Zealand we found that the information is spread in several excel spreadsheets from 2002 to 2020 with different sources, formats, and accessibility.

We then proceeded to gather some of the information provided by the New Zealand Ministry of health into 3 datasets that summarise the usage of these services in the last 20 years.

Inspiration

The main inspiration for this dataset was to find a way of building a continuous pipeline for future reference of Mental Health Service usage in New Zealand.

Our first approach was to match Government Expenditure and usage of Mental Health Services in NZ over the last years but finding information about specific government expenditure is hard to come by, So we decided to focus mostly in creating a solid dataframe about mental health service usage over the years.

Data Sources

Ministry of Health New Zealand

This data source was chosen for its ease of access and ability to web scrape.

Datasets were available from three sources: 1) Datasets from 2002 to 2008 2) Dataset of 2010 3) Dataset from 2011 to 2020

3 different crawlers were developed in order to maintain consistency over sources. Datasets from 2011 onwards are displayed in the ministry of health new Aggregated Data Site..

Datasets from 2002 were gathered from legacy sources on the list of reports by the ministry of health

The data provided in this data sets can be classified into 3 groups:

1) NZ Mental Health services usage by gender, age and ethnicity. 2) NZ Mental Health service usage by DHB's (District Health boards) 3) NZ Metal Health service usage by Service provided.

"Data is sourced from the Programme for the Integration of Mental Health Data (PRIMHD). PRIMHD contains Ministry of Health funded mental health and addiction service activity and outcomes data. The data is collected from district health boards (DHBs) and non-governmental organisations (NGOs).

PRIMHD data is used to report on what services are being provided, who is providing the services, and what outcomes are being achieved for health consumers across New Zealand's mental health sector. These reports enable better quality service planning and decision making by mental health and addiction service providers, at local, regional and national levels."

We have combined the data in the excel files provided by the MOH into a single data frame.

Intention of usage.

The idea behind the project is to have an incremental dataset for past and future reference, allow ease of access to timeseries information and better visibility.

Problems while gathering data.

We will divide the problems while gathering information into 2 categories: Downloading and Wrangling.

Downloading

The ministry of health releases an anual report on Mental Health since 2002, this reports are uploaded to the stats page of the Ministry of Health's website.

Reports from 2002 to 2007 have an aggregated site where they can be downlaoded programmatically. Reports from 2008 and 2010 have their individual site and had to be added manually to the download process. Reports from 2011 onwards have their own Mental Health page where they get uploaded every year. This website allows us to make incremental updates to the current dataset.

This 3 types of published papers required individual processes to download programmatically, 2 of them were scrapped from lists, and 1 of them manually added to the dataset.

While developing the download process for reports from 2011 we also find that some links were broken or required manual intervention, this had to be solved with exceptions for different years.

We developed parsers for this matter and expect changes in the future that can be solved by adding simple exceptions to new years given that they change, which at this stage is uncertain.

For the scraping part of the project we used R's rvest library.

Wrangling

The reports published by the Ministry of Health are given in excel format. R's tidiyverse and readxl libraries were used.

These reports are given in multi sheet excel files that have changed considerably over the years and had to be solved with individual parsers.

For this we...

New Zealand Jobseeker Support: Work Ready: Māori: Auckland Metro data was reported at 13,959.000 Number in Mar 2025. This records a decrease from the previous number of 14,085.000 Number for Feb 2025. New Zealand Jobseeker Support: Work Ready: Māori: Auckland Metro data is updated monthly, averaging 12,022.500 Number from Apr 2019 (Median) to Mar 2025, with 72 observations. The data reached an all-time high of 14,136.000 Number in Jan 2025 and a record low of 7,290.000 Number in Apr 2019. New Zealand Jobseeker Support: Work Ready: Māori: Auckland Metro data remains active status in CEIC and is reported by Ministry of Social Development. The data is categorized under Global Database’s New Zealand – Table NZ.G087: Monthly Benefit and Supplementary Assistance: Jobseeker Support. [COVID-19-IMPACT]