COVID-19 in New Zealand and the impact of the national response: a descriptive epidemiological study
- et al.
Summary
Background
Methods
Findings
Interpretation
Funding
Introduction
There is an international imperative to provide evidence of the effectiveness of non-pharmaceutical interventions against COVID-19. Early evidence in Asia, including China, Singapore, and South Korea, showed COVID-19 control using combinations of movement restrictions, physical distancing, hygiene practices, and intensive case and contact detection and management.
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The WHO-China Mission recommended decisive government leadership to rapidly enhance surveillance and apply risk-based non-pharmaceutical interventions with effective population engagement.
However, it was unclear how well this could be implemented in societies with little experience of successfully containing a novel respiratory virus.
As evidence emerged that the unique nature of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) required distinct strategic approaches, New Zealand moved from a response guided by national influenza pandemic planning to a COVID-19-tailored approach focusing on suppression (stopping SARS-CoV-2 community spread) over mitigation (slowing down transmission),
with a goal of COVID-19 elimination, to reach very low or zero COVID-19 incidence.
Risk-informed border restrictions were implemented ahead of WHO advice before the first local case of COVID-19 was confirmed on Feb 28, 2020. Graduated suppression strategies were then applied, escalating to national lockdown (stay-at-home order with few exemptions) within 26 days.
This response has international relevance, particularly for other island nations, high-income and western settings, and countries with ethnic and social health inequities. New Zealand is a high-income remote Pacific island state of nearly 5 million people, with an ageing population and diverse ethnic structure: approximately 16% Indigenous Māori, 7% Pacific peoples, 15% Asian, and 62% European or other. Inequitable morbidity and mortality for Māori and Pacific peoples, seen during previous influenza pandemics, continue for many communicable diseases today.
COVID-19 ethnic and social disparities have been observed overseas.
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New Zealand’s response sought to prevent COVID-19 disparities and minimise transit of infection to lower-income Pacific countries.
Methods
Study population and periods
This descriptive epidemiological study examined a cohort of all confirmed and probable COVID-19 cases and all people tested for SARS-CoV-2 infection in New Zealand up to May 13, 2020, which marked the easing of the most restrictive non-pharmaceutical interventions, after which community transmission ceased. National COVID-19 case definitions applied. Confirmed cases required laboratory definitive evidence (ie, SARS-CoV-2 detection by validated molecular test). Probable cases were close contacts of confirmed cases with clinically compatible presentations where SARS-CoV-2 testing was inconclusive and other causes excluded. New Zealand’s communicable disease surveillance and response capabilities have been recently described
and details on the four national COVID-19 Alert Levels, their associated non-pharmaceutical interventions, and test and trace guidance have been published.
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Key features of the response timeline are outlined in the panel and figure 1, including non-pharmaceutical interventions required by Alert Levels and key surveillance changes.
Data sources
COVID-19 became legally notifiable from Jan 30, 2020. Suspected, probable, and confirmed case data were prospectively recorded on EpiSurv, the national notifiable diseases database, using a standardised COVID-19 case report form. All confirmed and probable case data were extracted on June 16, 2020, including age, sex, location, 2013 New Zealand Index of Deprivation (NZDep) quintile (where quintile 1 is least socioeconomically deprived and quintile 5 most deprived),
travel history, occupation, basis for case detection, course of infection or illness, underlying conditions, link to a confirmed case or outbreak, and notification and confirmation dates. Self-determined ethnicity was identified by linkage to the national patient demographics dataset. Ethnicity was grouped by prioritised classification in order of Māori, Pacific, Asian, and European or other, with the remaining cases classified as unknown.
Results of all SARS-CoV-2 molecular tests were extracted on June 3, 2020, from Éclair, the national SARS-CoV-2 test results repository, with the following metadata: age, sex, linked prioritised ethnicity,
District Health Board (DHB) location, and NZDep quintile.
Outcome measures
Cases were assigned to the five phases in two ways to assess different impacts. First, cases were assigned to a phase on the basis of the estimated date of SARS-CoV-2 infection (ie, the exposure period), defined as occurring one incubation period before symptom onset (or notification date, if data on symptom onset were unavailable). Uncertainty in incubation period was incorporated by replicate sampling (n=1000) from a Weibull distribution
with means and SEs pooled across replicates. Assigned exposure period was then used to assess the impacts of non-pharmaceutical intervention phases on disease transmission and the characteristics of cases affected. The estimated average daily incidence of New Zealand-acquired case infection was calculated as the number of non-imported cases divided by the number of days in the phase and the national estimated population size.
International arrival numbers,
Government Response Stringency Index values,
and population mobility changes were summarised for New Zealand. The Government Response Stringency Index is a composite indicator measuring the strictness of government policy responses to COVID-19. Population mobility changes were calculated using mobility data, with daily observed local resident mobility compared against median estimates for each weekday derived from a 4-week baseline (Feb 10–March 15, 2020) to calculate percentage changes.
Statistical analysis
Key time-to-event intervals were analysed by fitting parametric distributions using maximum likelihood estimation. Uncertainty intervals (UIs) for key parameters were calculated using bootstrapping techniques.
Sensitivity analysis of the inclusion of probable cases (standard national reporting practice) and exposure period based on notification date for 30 cases was assessed by repeating key study analyses with their exclusion. R (version 4·0.2) and STATA (version 15) were used for statistical analyses.
Role of the funding source
Results
1503 cases of COVID-19 were detected in New Zealand presenting from Feb 12 to May 10, 2020, of which 1153 (77%) were confirmed and 350 (23%) probable (figure 1; table 1). This was a cumulative incidence of 302·7 cases (95% CI 287·6–318·4) per million people. 95 (6·3%) people with COVID-19 were admitted to hospital, ten admitted to intensive care (0·7%), and 22 (1·5%) died (table 1). The estimated case infection rate per million people per day peaked in phase 2 at 8·5 (7·6–9·4) followed by a 62% decrease to 3·2 (2·8–3·7) in phase 3 (the first half of lockdown), progressively declining thereafter. The main source of infection was overseas acquisition, with the proportion attributable to importation declining from lockdown (ie, from phase 3 onwards). The results of sensitivity analysis with the exclusion of probable cases are shown in the appendix (pp 2–3), with no major impacts on study findings.
Total | Phase 1: Feb 2–March 15 | Phase 2: March 16–March 25 | Phase 3: March 26–April 10 | Phase 4: April 11–April 27 | Phase 5: April 18–May 13 | ||||||||
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Count | Estimate (95% CI) | Count | Estimate (95% CI) | Count | Estimate (95% CI) | Count | Estimate (95% CI) | Count | Estimate (95% CI) | Count | Estimate (95% CI) | ||
Exposure periods | |||||||||||||
Average estimated daily case infection rate | |||||||||||||
Cases per day | .. | .. | .. | 4·6 (4·0 to 5·4) | .. | 42·2 (37·9 to 46·9) | .. | 16·0 (14·0 to 18·4) | .. | 2·6 (1·9 to 3·6) | .. | 0·4 (0·1 to 0·9) | |
Cases per million people per day | .. | .. | .. | 0·9 (0·8 to 1·1) | .. | 8·5 (7·6 to 9·4) | .. | 3·2 (2·8 to 3·7) | .. | 0·5 (0·4 to 0·7) | .. | 0·1 (0·0 to 0·2) | |
Percentage rate change from previous phase | .. | .. | .. | .. | .. | 809% (642 to 1014) | .. | −62% (−68 to −54) | .. | −84% (−89 to −77) | .. | −87% (−95 to −63) | |
Total cases | 1503 | .. | 471 | .. | 672 | .. | 305 | .. | 48 | .. | 7 | .. | |
Source of infection | |||||||||||||
Imported case | 575 | 38% (36 to 41) | 271 | 58% (53 to 62) | 251 | 37% (33 to 41) | 49 | 16% (12 to 21) | 3 | 6·5% (1·8 to 21) | 1 | 9·3% (0·0 to 100) | |
Import-related case | 459 | 31% (28 to 33) | 100 | 21% (17 to 26) | 231 | 34% (31 to 38) | 119 | 39% (33 to 45) | 9 | 18% (9·0 to 33) | 0 | .. | |
Locally acquired case | 469 | 31% (29 to 34) | 100 | 21% (17 to 26) | 190 | 28% (25 to 32) | 137 | 45% (39 to 51) | 36 | 75% (59 to 86) | 6 | 89% (0·0 to 100) | |
High-risk worker | 237 | 16% (14 to 18) | 49 | 10% (7·7 to 14) | 88 | 13% (11 to 16) | 76 | 25% (20 to 31) | 20 | 42% (28 to 58) | 4 | 52% (16 to 86) | |
Health-care worker | 166 | 11% (9·6 to 13) | 33 | 7·0% (4·9 to 10) | 51 | 7·5% (5·6 to 10) | 62 | 20% (16 to 26) | 17 | 37% (23 to 53) | 3 | 40% (11 to 79) | |
Other | 71 | 4·7% (3·8 to 5·9) | 16 | 3·3% (1·9 to 5·7) | 38 | 5·6% (4·0 to 7·8) | 14 | 4·6% (2·6 to 8·2) | 3 | 5·6% (1·5 to 19) | 1 | 0·2% (0·0 to 100) | |
At least one underlying condition | 294 | 20% (18 to 22) | 87 | 18% (15 to 23) | 132 | 20% (16 to 23) | 63 | 21% (16 to 26) | 13 | 26% (15 to 42) | 0 | .. | |
Outcome | |||||||||||||
Hospital admission | 95 | 6·3% (5·2 to 7·7) | 32 | 6·8% (4·7 to 9·8) | 36 | 5·3% (3·7 to 7·6) | 21 | 6·8% (4·2 to 11) | 6 | 12% (5·0 to 28) | 0 | .. | |
ICU admission | 10 | 0·7% (0·4 to 1·2) | 3 | 0·7% (0·2 to 2·3) | 5 | 0·7% (0·3 to 1·9) | 1 | 0·0% (0·0 to 100) | 1 | 0·0% (0·0 to 100) | 0 | .. | |
Death | 22 | 1·5% (1·0 to 2·2) | 1 | 0·0% (0·0 to 100) | 6 | 0·9% (0·3 to 2·2) | 11 | 3·5% (1·8 to 6·7) | 4 | 7·6% (2·1 to 24) | 0 | .. | |
Presentation periods | |||||||||||||
Confirmed cases | 1153 | 77% (74 to 79) | 111 | 85% (77 to 90) | 588 | 85% (83 to 88) | 402 | 68% (64 to 71) | 40 | 53% (41 to 65) | 12 | 80% (52 to 96) | |
Probable cases | 350 | 23% (21 to 26) | 20 | 15% (9·6 to 23) | 100 | 15% (12 to 17) | 192 | 32% (29 to 36) | 35 | 47% (35 to 59) | 3 | 20% (4·3 to 48) | |
Total cases used as basis for case detection | 1503 | .. | 131 | .. | 688 | .. | 594 | .. | 75 | .. | 15 | .. | |
Contact tracing | 765 | 51% (48 to 53) | 39 | 30% (22 to 38) | 257 | 37% (34 to 41) | 393 | 66% (62 to 70) | 65 | 87% (77 to 93) | 11 | 73% (45 to 92) | |
Border | 39 | 2·6% (1·9 to 3·5) | 3 | 2·3% (0·5 to 6·5) | 24 | 3·5% (2·2 to 5·1) | 8 | 1·3% (0·6 to 2·6) | 3 | 4% (0·8 to 11) | 1 | 6·7% (0·2 to 32) | |
Health-care presentation | 693 | 46% (44 to 49) | 89 | 68% (59 to 76) | 405 | 59% (55 to 63) | 189 | 32% (28 to 36) | 7 | 9·3% (3·8 to 18) | 3 | 20% (4·3 to 48) | |
Other | 6 | 0·4% (0·1 to 0·9) | 0 | .. | 2 | 0·3% (0·0 to 1·0) | 4 | 0·7% (0·2 to 1·7) | 0 | .. | 0 | .. | |
Incidence rate of SARS-CoV-2 nucleic acid testing (tests per 100 000 person-days) | .. | .. | .. | 0·5 (0·5 to 0·5) | .. | 27·3 (26·9 to 27·8) | .. | 56·7 (56·1 to 57·2) | .. | 78·2 (77·6 to 78·8) | .. | 109·9 (109·1 to 110·6) | |
Percentage rate change from previous phase | .. | .. | .. | .. | .. | 5259% (4938 to 5600) | .. | 107% (103 to 111) | .. | 38% (36 to 40) | .. | 40% (39 to 42) |
Demographic characteristics were influenced by infection source, with 1034 (69%) imported and import-related cases, and by outbreak settings (table 2; figure 2). COVID-19 incidence was lowest in children for all sources (table 2). Overall, cases were predominantly female, aged 20–34 years, of European or other ethnicity, and had higher socioeconomic status (47% in NZDep quintiles 1–2). People of Māori ethnicity had the second-highest rate of import-related disease after people of European or other ethnicity (table 2), with 30 (46%) Māori cases in this group linked to New Zealand’s largest outbreak (see wedding in figure 2). Locally acquired cases showed female predominance, higher incidence among Asian and Pacific peoples, and distribution across deprivation quintiles (table 2). These characteristics, as well as major geographical trends, were evident in the demographics of major locally acquired outbreaks (figure 2).
Total | Imported | Import related | Locally acquired | ||||||||||
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Cases | Incidence risk per 100 000 (95% CI) | Relative risk (95% CI) | Cases | Incidence risk per 100 000 (95% CI) | Relative risk (95% CI) | Cases | Incidence risk per 100 000 (95% CI) | Relative risk (95% CI) | Cases | Incidence risk per 100 000 (95% CI) | Relative risk (95% CI) | ||
Sex | |||||||||||||
Female | 836 (56%) | 33·2 (31·1–35·6) | 1·22 (1·10–1·35) | 285 (50%) | 11·3 (10·1–12·7) | 0·96 (0·81–1·13) | 253 (55%) | 10·1 (8·9–11·4) | 1·20 (1–1·44) | 298 (64%) | 11·9 (10·6–13·3) | 1·70 (1·41–2·05) | |
Male | 667 (44%) | 27·2 (25·2–29·4) | 1 (ref) | 290 (50%) | 11·8 (10·5–13·3) | 1 (ref) | 206 (45%) | 8·4 (7·3–9·6) | 1 (ref) | 171 (36%) | 7·0 (6·0–8·1) | 1 (ref) | |
Age group | |||||||||||||
<1 year | 4 (0·3%) | 6·5 (2·4–17·2) | 0·14 (0·05–0·37) | 0 | .. | .. | 1 (0·2%) | 1·6 (0·2–11·5) | 0·15 (0·02–1·05) | 3 (0·6%) | 4·9 (1·6–15·1) | 0·41 (0·13–1·29) | |
1–4 years | 18 (1·2%) | 7·3 (4·6–11·6) | 0·16 (0·1–0·25) | 1 (0·2%) | 0·4 (0·1–2·9) | 0·02 (0·00–0·12) | 9 (2·0%) | 3·7 (1·9–7·0) | 0·33 (0·17–0·65) | 8 (1·7%) | 3·2 (1·6–6·5) | 0·28 (0·13–0·56) | |
5–19 years | 135 (9·0%) | 14·1 (11·9–16·7) | 0·30 (0·25–0·37) | 15 (2·6%) | 1·6 (0·9–2·6) | 0·07 (0·04–0·11) | 54 (12%) | 5·6 (4·3–7·3) | 0·51 (0·37–0·70) | 66 (14%) | 6·9 (5·4–8·8) | 0·58 (0·43–0·79) | |
20–34 years | 508 (34%) | 46·4 (42·5–50·6) | 1 (ref) | 258 (45%) | 23·6 (20·9–26·6) | 1 (ref) | 121 (26%) | 11·0 (9·2–13·2) | 1 (ref) | 129 (28%) | 11·8 (9·9–14·0) | 1 (ref) | |
35–49 years | 299 (20%) | 32·6 (29·1–36·5) | 0·70 (0·61–0·81) | 90 (16%) | 9·8 (8·0–12·1) | 0·42 (0·33–0·53) | 101 (22%) | 11·0 (9·1–13·4) | 1·00 (0·77–1·30) | 108 (23%) | 11·8 (9·7–14·2) | 1·00 (0·77–1·29) | |
50–64 years | 343 (23%) | 37·6 (33·9–41·8) | 0·81 (0·71–0·93) | 132 (23%) | 14·5 (12·2–17·2) | 0·61 (0·50–0·76) | 120 (26%) | 13·2 (11·0–15·7) | 1·19 (0·93–1·53) | 91 (19%) | 10·0 (8·1–12·3) | 0·85 (0·65–1·11) | |
65–79 years | 157 (10%) | 26·5 (22·7–31·0) | 0·57 (0·48–0·68) | 76 (13%) | 12·8 (10·2–16·1) | 0·54 (0·42–0·70) | 38 (8·3%) | 6·4 (4·7–8·8) | 0·58 (0·40–0·84) | 43 (9·2%) | 7·3 (5·4–9·8) | 0·62 (0·44–0·87) | |
≥80 years | 39 (2·6%) | 21·5 (15·7–29·4) | 0·46 (0·33–0·64) | 3 (0·5%) | 1·7 (0·5–5·1) | 0·07 (0·02–0·22) | 15 (3·3%) | 8·3 (5·0–13·7) | 0·75 (0·44–1·28) | 21 (4·5%) | 11·6 (7·5–17·7) | 0·98 (0·62–1·56) | |
Ethnic group | |||||||||||||
Māori | 134 (8·9%) | 17·2 (14·5–20·4) | 0·49 (0·41–0·58) | 33 (5·7%) | 4·2 (3·0–6·0) | 0·27 (0·19–0·39) | 65 (14%) | 8·3 (6·5–10·6) | 0·74 (0·57–0·97) | 36 (7·7%) | 4·6 (3·3–6·4) | 0·55 (0·39–0·78) | |
Pacific peoples | 79 (5·3%) | 24·5 (19·7–30·6) | 0·70 (0·55–0·88) | 11(1·9%) | 3·4 (1·9–6·2) | 0·22 (0·12–0·40) | 11 (2·4%) | 3·4 (1·9–6·2) | 0·31 (0·17–0·56) | 57 (12%) | 17·7 (13·7–23·0) | 2·11 (1·58–2·81) | |
Asian | 183 (12%) | 23·8 (20·6–27·5) | 0·68 (0·58–0·79) | 39 (6·8%) | 5·1 (3·7–6·9) | 0·32 (0·23–0·45) | 34 (7·4%) | 4·4 (3·2–6·2) | 0·39 (0·28–0·56) | 110 (23%) | 14·3 (11·9–17·3) | 1·71 (1·36–2·13) | |
European or other | 1091 (73%) | 35·2 (33·2–37·4) | 1 (ref) | 484 (84%) | 15·6 (14·3–17·1) | 1 (ref) | 347 (76%) | 11·2 (10·1–12·4) | 1 (ref) | 260 (55%) | 8·4 (7·4–9·5) | 1 (ref) | |
Unknown | 16 (1·1%) | .. | .. | 8 (1·4%) | .. | .. | 2 (0·4%) | .. | .. | 6 (1·3%) | .. | .. | |
NZDep quintile | |||||||||||||
1 (least deprived) | 342 (23%) | 33·3 (30·0–37·1) | 1 (ref) | 167 (29%) | 16·3 (14·0–18·9) | 1 (ref) | 97 (21%) | 9·5 (7·8–11·5) | 1 (ref) | 78 (17%) | 7·6 (6·1–9·5) | 1 (ref) | |
2 | 362 (24%) | 36·2 (32·6–40·1) | 1·08 (0·94–1·26) | 153 (27%) | 15·3 (13·0–17·9) | 0·94 (0·75–1·17) | 107 (23%) | 10·7 (8·8–12·9) | 1·13 (0·86–1·49) | 102 (22%) | 10·2 (8·4–12·4) | 1·34 (1·00–1·80) | |
3 | 262 (17%) | 26·7 (23·6–30·1) | 0·80 (0·68–0·94) | 95 (17%) | 9·7 (7·9–11·8) | 0·59 (0·46–0·76) | 80 (17%) | 8·1 (6·5–10·1) | 0·86 (0·64–1·16) | 87 (19%) | 8·9 (7·2–10·9) | 1·16 (0·86–1·58) | |
4 | 279 (19%) | 28·7 (25·5–32·2) | 0·86 (0·73–1·01) | 88 (15%) | 9·0 (7·3–11·1) | 0·56 (0·43–0·72) | 96 (21%) | 9·9 (8·1–12·0) | 1·04 (0·79–1·38) | 95 (20%) | 9·8 (8·0–11·9) | 1·28 (0·95–1·73) | |
5 (most deprived) | 170 (11%) | 17·3 (14·9–20·1) | 0·52 (0·43–0·62) | 81 (14%) | 3·3 (2·3–4·6) | 0·2 (0·14–0·29) | 49 (11%) | 5·0 (3·8–6·6) | 0·53 (0·37–0·74) | 89 (19%) | 9·1 (7·4–11·1) | 1·19 (0·88–1·61) | |
Unknown | 88 (5·9%) | .. | .. | 40 (7·0%) | .. | .. | 30 (6·5%) | .. | .. | 18 (3·8%) | .. | .. | |
Total | 1503 (100%) | .. | .. | 575 (100%) | .. | .. | 459 (100%) | .. | .. | 469 (100%) | .. | .. |
Testing increased over the study period among all demographic groups (figure 3; appendix pp 6–7). Females had consistently higher testing rates than males (figure 3). In phase 1, testing rates were highest in people of Asian ethnicity, adults aged 20–34 years, and people of higher socioeconomic status (figure 3; appendix pp 6–7). Subsequently, Pacific peoples, adults aged 50–64 years, and people of lower socioeconomic status had higher rates. People younger than 20 years of age had lower testing rates in every phase (appendix pp 6–7).
Discussion
New Zealand experienced one of the lowest cumulative case counts, incidence, and mortality among higher-income countries in its first wave of COVID-19 following early implementation and rapid escalation of national COVID-19 suppression strategies.
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New Zealand effectively achieved control with progressive, risk-informed border closures reducing the burden of imported disease driving the epidemic. This was followed, only 15 days after first case confirmation, by a phase of rapid escalation of non-pharmaceutical interventions to national lockdown. This 10-day escalation phase had the highest average daily case infection rate during the study period. Within 2 weeks, lockdown was associated with a substantial reduction in daily case infection rate and improving response performance measures: the majority of cases were detected by contact tracing, and there were decreasing average times to case notification and isolation and increasing population testing with effective targeting of higher-risk groups.
Enhancements in response capacity also supported de-escalation decisions. The daily test positivity was less than 5% from March 29 (day 4 of lockdown), as recommended by WHO before easing of restrictions, and only 25 cases of asymptomatic infection were detected despite routine testing of asymptomatic contacts, population testing surveys targeting asymptomatic and high-risk groups, and high testing rates by phase 5. Moreover, despite full de-escalation to Alert Level 1 on June 9, New Zealand effectively eliminated COVID-19, as currently defined,
to very low numbers detected at border quarantine facilities for an extended period.
Furthermore, rapid suppression of community transmission limited overall disease disparities for populations most vulnerable to severe outcomes. Most cases were linked to imported cases, with predominant features of healthy travellers: younger adults, European ethnicity, and higher socioeconomic status. Locally acquired disease was less common, but tended to reach more vulnerable populations (ie, older people, ARC residents, and minority ethnic groups) and was associated with more severe outcomes. Female case predominance in this group probably relates to the settings where locally acquired outbreaks occurred, including a girls’ school, and ARC facilities where residents and carers were more likely to be female, but is potentially influenced by testing bias. Higher female testing incidence might reflect female predominance in certain high-risk groups targeted for testing, such as health-care workers, which is also considered a potential reason for slight female case predominance described in England.
Higher male mortality reported overseas was not seen in New Zealand,
,
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and although the crude OR for severe outcomes was slightly higher for males, this estimate was imprecise and did not persist after multivariable adjustment. In keeping with some international findings, children appeared to have had a lesser role in household transmission and outbreaks—even at a school—in New Zealand, despite intensive testing of asymptomatic contacts.
,
However, with lower national testing rates in children, detection bias cannot be excluded.
High-risk workers and indigenous Māori people did not appear to be disproportionately affected in the first wave. Rapid control of community transmission through mandatory physical distancing provided time to enhance the response, including prioritised testing of higher-risk groups, also ensuring that COVID-19 did not overburden health system capacity. Nonetheless, after adjustment for confounders, older people, ARC residents, people reporting at least one underlying condition, and Asian and Pacific peoples were at higher risk of severe outcomes than other populations. These findings align with international risk associations.
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Our study supports the ongoing need for the response to address systemic barriers, such as health-care access, to achieving equitable health outcomes for minority and higher-risk groups, particularly in the absence of elimination.
New Zealand’s border response has implications for island states where borders can be more readily controlled. Samoa and Fiji, for example, also exercised early border closures to non-citizens and non-residents, aligning with strategies effective during the 1918 pandemic, and so far maintain zero or very low COVID-19 counts.
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While clearly effective in limiting disease importation, there remain questions about the costs and sustainability of these measures. Although New Zealand-based research before the pandemic suggested a net health economic benefit from complete border closure in a modelled pandemic scenario,
the potential indirect health effects of the national response are under surveillance and the net impacts yet to be determined. Cost-effectiveness analysis lay outside the scope of our study but focused research in this area is essential. Furthermore, Taiwan has shown that COVID-19 control can be achieved in the absence of complete border closure, although using advanced technological systems and ongoing strict disease suppression strategies in a society that had already normalised some of these measures from previous novel virus exposures.
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Finally, the speed and intensity of the national response to limit the epidemic is unprecedented internationally; New Zealand had the fastest trajectory to reach the highest country score in the Government Response Stringency Index.
The observed impact of lockdown on inhibiting disease transmission aligns with reproductive number estimates for before and after lockdown produced for New Zealand and other countries.
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It is likely this early, intense response, which also enabled relatively rapid easing while maintaining strict border controls, prevented the burden of disease experienced in other high-income countries with slower lockdown implementation, including Australia, the UK, and Italy—the latter initially taking mitigation approaches.
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Integral to New Zealand’s response has been decisive governance, effective communication, and high population compliance—in an earthquake-prone country, communities and emergency management systems are primed for disaster response.
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This study has methodological advantages. It uses two comprehensive national datasets: one employing standardised national case questionnaires prospectively applied to every notified case for the primary purpose of COVID-19 surveillance, and the other recording every SARS-CoV-2 test done using nationally validated methodology. Moreover, data were extracted for the study period in mid-June, enabling completeness, and preventing right censoring of the epidemic curve. Furthermore, following the end of the study period, case numbers remained very low, including a 25-day period where no cases were notified.
Data sharing
Supplementary Material
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Supplementary appendix
References
- 1.
Evaluation of the effectiveness of surveillance and containment measures for the First 100 Patients with COVID-19 in Singapore—January 2–February 29, 2020.
MMWR Morb Mortal Wkly Rep. 2020; 69: 307-311
- 2.
Report of the WHO-China Joint Mission on coronavirus disease 2019 (COVID-19).
World Health Organization, Geneva2020
- 3.
COVID-19 in South Korea.
Postgrad Med J. 2020; 96: 399-402
- 4.
How will country-based mitigation measures influence the course of the COVID-19 epidemic?.
Lancet. 2020; 395: 931-934
- 5.
Report 9: impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand.
Imperial College London, London2020
- 6.
COVID-19 health and disability system response plan.
Ministry of Health, Wellington2020
- 7.
Differential mortality rates by ethnicity in 3 influenza pandemics over a century, New Zealand.
Emerg Infect Dis. 2012; 18: 71-77
- 8.
Disparities in the risk and outcomes of COVID-19.
Public Health England, London2020
- 9.
Racial disparity of coronavirus disease 2019 (COVID-19) in African American communities.
J Infect Dis. 2020; 222: 890-893
- 10.
Joint external evaluation of IHR core capacities of New Zealand: mission report: 26–30 November 2018.
World Health Organization, Geneva2019
- 11.
New Zealand COVID-19 alert levels summary.
https://covid19.govt.nz/assets/resources/tables/COVID-19-alert-levels-summary.pdf
Date accessed: June 22, 2020 - 12.
Updated advice for health professionals: novel coronavirus (COVID-19).Date accessed: March 14, 2020
- 13.
NZDep91: a New Zealand index of deprivation.
Aust N Z J Public Health. 1998; 22: 835-837
- 14.
HISO 10001:2017 ethnicity data protocols.
https://www.health.govt.nz/publication/hiso-100012017-ethnicity-data-protocols
Date: Oct 6, 2017Date accessed: April 14, 2020 - 15.
The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: Estimation and application.
Ann Intern Med. 2020; 172: 577-582
- 16.
Provisional international travel statistics: daily arrivals and departures data.Date: 2013Date accessed: May 16, 2020
- 17.
Oxford COVID-19 government response tracker.
https://www.bsg.ox.ac.uk/research/research-projects/coronavirus-government-response-tracker
Date accessed: July 20, 2020 - 18.
A leisurely look at the bootstrap, the jackknife, and cross-validation.
Am Stat. 1983; 37: 36-48
- 19.
Coronavirus disease 2019 (COVID-19) situation report—121.Date: July 29, 2020Date accessed: May 21, 2020
- 20.
The New Zealand COVID-19 intelligence dashboard. Institute of Environmental Science and Research.
https://esr2.cwp.govt.nz/our-expertise/covid-19-response
Date accessed: July 21, 2020 - 21.
Association of public health interventions with the epidemiology of the COVID-19 outbreak in Wuhan, China.
JAMA. 2020; 323: 1915-1923
- 22.
High impact of COVID-19 in long-term care facilities, suggestion for monitoring in the EU/EEA, May 2020.
Euro Surveill. 2020; 252000956
- 23.
COVID-19: we must not forget about Indigenous health and equity.
Aust N Z J Public Health. 2020; 44: 253-256
- 24.
Protective effect of maritime quarantine in South Pacific jurisdictions, 1918-19 influenza pandemic.
Emerg Infect Dis. 2008; 14: 468-470
- 25.
Economic evaluation of border closure for a generic severe pandemic threat using New Zealand Treasury methods.
Aust N Z J Public Health. 2018; 42: 444-446
- 26.
Response to COVID-19 in Taiwan: big data analytics, new technology, and proactive testing.
JAMA. 2020; 323: 1341-1342
- 27.
Effective reproduction number for COVID-19 in Aotearoa New Zealand. Te Pūnaha Matatini 2020.Date: May 22, 2020Date accessed: July 21, 2020
- 28.
The effect of large-scale anti-contagion policies on the COVID-19 pandemic.
Nature. 2020; 584: 262-267
- 29.
Early analysis of the Australian COVID-19 epidemic.
eLife. 2020; 9e58785
- 30.
The UK’s public health response to COVID-19.
BMJ. 2020; 369m1932
- 31.
Pandemic leadership: Lessons from New Zealand’s approach to COVID-19.
Leadership. 2020; 16: 279-293
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Figures
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Figure 1Key features of the New Zealand COVID-19 epidemic and response timeline
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Figure 2COVID-19 cumulative incidence by DHB, indicating epicentres and summary characteristics of the ten largest COVID-19 outbreaks
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Figure 3Incidence rates of SARS-CoV-2 testing by sex and response phase (A) and by ethnic group and response phase (B)
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