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COVID-19 in New Zealand and the impact of the national response: a descriptive epidemiological study
Open accessAbstract
BACKGROUND: In early 2020, during the COVID-19 pandemic, New Zealand implemented graduated, risk-informed national COVID-19 suppression measures aimed at disease elimination. We investigated their impacts on the epidemiology of the first wave of COVID-19 in the country and response performance measures. METHODS: We did a descriptive epidemiological study of all laboratory-confirmed and probable cases of COVID-19 and all patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New Zealand from Feb 2 to May 13, 2020, after which time community transmission ceased. We extracted data from the national notifiable diseases database and the national SARS-CoV-2 test results repository. Demographic features and disease outcomes, transmission patterns (source of infection, outbreaks, household transmission), time-to-event intervals, and testing coverage were described over five phases of the response, capturing different levels of non-pharmaceutical interventions. Risk factors for severe outcomes (hospitalisation or death) were examined with multivariable logistic regression and time-to-event intervals were analysed by fitting parametric distributions using maximum likelihood estimation. FINDINGS: 1503 cases were detected over the study period, including 95 (6·3%) hospital admissions and 22 (1·5%) COVID-19 deaths. The estimated case infection rate per million people per day peaked at 8·5 (95% CI 7·6-9·4) during the 10-day period of rapid response escalation, declining to 3·2 (2·8-3·7) in the start of lockdown and progressively thereafter. 1034 (69%) cases were imported or import related, tending to be younger adults, of European ethnicity, and of higher socioeconomic status. 702 (47%) cases were linked to 34 outbreaks. Severe outcomes were associated with locally acquired infection (crude odds ratio [OR] 2·32 [95% CI 1·40-3·82] compared with imported), older age (adjusted OR ranging from 2·72 [1·40-5·30] for 50-64 year olds to 8·25 [2·59-26·31] for people aged ≥80 years compared with 20-34 year olds), aged residential care residency (adjusted OR 3·86 [1·59-9·35]), and Pacific peoples (adjusted OR 2·76 [1·14-6·68]) and Asian (2·15 [1·10-4·20]) ethnicities relative to European or other. Times from illness onset to notification and isolation progressively decreased and testing increased over the study period, with few disparities and increasing coverage of females, Māori, Pacific peoples, and lower socioeconomic groups. INTERPRETATION: New Zealand's response resulted in low relative burden of disease, low levels of population disease disparities, and the initial achievement of COVID-19 elimination. FUNDING: Ministry of Business Innovation and Employment Strategic Scientific Investment Fund, and Ministry of Health, New Zealand.
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“Other countries, such as Australia and New Zealand, have shown how early and effective lockdowns, combined with geographical isolation and travel restrictions, have kept transmission low throughout the study period.18, 55, 56”
From Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis (2022) · cites this paper as [56]
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Lauer, S. A., Grantz, K. H., Bi, Q., Jones, F. K., Zheng, Q., Meredith, H. R., Azman, A. S., Reich, N. G., & Lessler, J. (2020) · Annals of Internal Medicine · doi:10.7326/m20-0504 · Cited by 5,970
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Metadata
- Authors
- Jefferies, S., French, N., Gilkison, C., Graham, G., Hope, V., Marshall, J., McElnay, C., McNeill, A., Muellner, P., Paine, S., Prasad, N., Scott, J., Sherwood, J., Yang, L., & Priest, P.
- Affiliations
- New Zealand Institute for Public Health and Forensic Science (NZ)
- Massey University (NZ)
- Ministry of Health (NZ)
- University of Otago (NZ)
- Corresponding author
- Jefferies, Sarah
- ORCID
- Venue
- The Lancet Public Health
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 5
- Issue
- 11
- Pages
- e612-e623
- ISSN
- 2468-2667 (ISSN-L)
- PMC
- PMC7553903
- OpenAlex
- W3093036788
- Cited by
- 349
- References
- 25
- Citations by year
- 2026: 7 · 2025: 23 · 2024: 31 · 2023: 45 · 2022: 62 · 2021: 174 · 2020: 7
- FWCI
- 11.45
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Public Health (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Ministry of Health, New Zealand
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- COVID-19 pandemic, SARS-CoV-2, New Zealand, non-pharmaceutical interventions, lockdown, imported infections, household transmission, community outbreak, severe outcomes, hospitalization, mortality, risk factors, residential care, Pacific Islanders, socioeconomic status, test coverage, infection rate, response performance, first wave, survival analysis
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, COVID-19 Testing, Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Humans, Infant, Male, Middle Aged, New Zealand, Pneumonia, Viral, Risk Factors, Epidemiologic Studies, Coronavirus Infections, Clinical Laboratory Techniques, Young Adult, Pandemics
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