tetano
Editor, Senior Moderator
Int J Epidemiol
. 2025 Jun 11;54(4):dyaf093.
doi: 10.1093/ije/dyaf093. Estimating excess mortality during the Covid-19 pandemic in Aotearoa New Zealand
Michael J Plank[SUP] 1 [/SUP], Pubudu Senanayake[SUP] 1 2 [/SUP], Richard Lyon[SUP] 3 [/SUP]
Affiliations
Background: The excess mortality rate in Aotearoa New Zealand during the Covid-19 pandemic is frequently estimated to be among the lowest in the world. However, to facilitate international comparisons, many of the methods that have been used to estimate excess mortality do not use age-stratified data on deaths and population size, which may compromise their accuracy.
Methods: We used a quasi-Poisson regression model for monthly all-cause deaths among New Zealand residents, controlling for age, sex, and seasonality. We fitted the model to deaths data for 2014-19. We estimated monthly excess mortality for 2020-23 as the difference between actual deaths and projected deaths according to the model. We conducted sensitivity analysis on the length of the pre-pandemic period used to fit the model. We benchmarked our results against a simple linear regression on the standardized annual mortality rate.
Results: We estimated cumulative excess mortality in New Zealand in 2020-23 was 1040 [95% confidence interval (-1134, 2927)], equivalent to 0.7% (-0.8%, 2.0%) of expected mortality. Excess mortality was negative in 2020-21. The magnitude, timing, and age-distribution of the positive excess mortality in 2022-23 were closely matched with confirmed Covid-19 deaths.
Conclusions: Negative excess mortality in 2020-21 reflects very low levels of Covid-19 and major reductions in seasonal respiratory diseases during this period. In 2022-23, Covid-19 deaths were the main contributor to excess mortality, and there was little or no net non-Covid-19 excess. Overall, New Zealand experienced one of the lowest rates of pandemic excess mortality in the world.
Keywords: Poisson regression; SARS-CoV-2; age-standardized mortality rate; excess deaths; generalized linear model.
. 2025 Jun 11;54(4):dyaf093.
doi: 10.1093/ije/dyaf093. Estimating excess mortality during the Covid-19 pandemic in Aotearoa New Zealand
Michael J Plank[SUP] 1 [/SUP], Pubudu Senanayake[SUP] 1 2 [/SUP], Richard Lyon[SUP] 3 [/SUP]
Affiliations
- PMID: 40517754
- DOI: 10.1093/ije/dyaf093
Background: The excess mortality rate in Aotearoa New Zealand during the Covid-19 pandemic is frequently estimated to be among the lowest in the world. However, to facilitate international comparisons, many of the methods that have been used to estimate excess mortality do not use age-stratified data on deaths and population size, which may compromise their accuracy.
Methods: We used a quasi-Poisson regression model for monthly all-cause deaths among New Zealand residents, controlling for age, sex, and seasonality. We fitted the model to deaths data for 2014-19. We estimated monthly excess mortality for 2020-23 as the difference between actual deaths and projected deaths according to the model. We conducted sensitivity analysis on the length of the pre-pandemic period used to fit the model. We benchmarked our results against a simple linear regression on the standardized annual mortality rate.
Results: We estimated cumulative excess mortality in New Zealand in 2020-23 was 1040 [95% confidence interval (-1134, 2927)], equivalent to 0.7% (-0.8%, 2.0%) of expected mortality. Excess mortality was negative in 2020-21. The magnitude, timing, and age-distribution of the positive excess mortality in 2022-23 were closely matched with confirmed Covid-19 deaths.
Conclusions: Negative excess mortality in 2020-21 reflects very low levels of Covid-19 and major reductions in seasonal respiratory diseases during this period. In 2022-23, Covid-19 deaths were the main contributor to excess mortality, and there was little or no net non-Covid-19 excess. Overall, New Zealand experienced one of the lowest rates of pandemic excess mortality in the world.
Keywords: Poisson regression; SARS-CoV-2; age-standardized mortality rate; excess deaths; generalized linear model.