Abstract
Background New Zealand had 1499 cases of COVID-19 before eliminating transmission of the virus. Extensive contract tracing during the outbreak has resulted in a dataset of epidemiologically linked cases. This data contains useful information about the transmission dynamics of the virus, its dependence on factors such as age, and its response to different control measures.
Method We use Monte-Carlo network construction techniques to provide an estimate of the number of secondary cases for every individual infected during the outbreak. We then apply standard statistical techniques to quantify differences between groups of individuals.
Findings Children under 10 years old are significantly under-represented in the case data. Children infected fewer people on average and had a lower secondary attack rate in comparison to adults and the elderly. Imported cases infected fewer people on average and had a lower secondary attack rate than domestically acquired cases. Superspreading is a significant contributor to the epidemic dynamics, with 20% of cases among adults responsible for 65-85% of transmission. Asymptomatic cases infected fewer individuals than clinical cases. Serial intervals are approximately normally distributed (μ = 5.0 days, σ = 5.7 days). Early isolation and quarantine of cases reduced secondary transmission rates.
Interpretation Border controls and strong social distancing measures, particularly when targeted at superspreading, play a significant role in reducing the spread of COVID-19.
Funding Te Pūnaha Matatini, the New Zealand Centre of Research Excellence in complex systems. New Zealand Ministry of Business, Innovation and Employment.
Evidence before this study The basic reproduction number for COVID-19 is between 2 and 4, although there is substantial individual variation in the level of infectiousness and number of secondary cases. There is evidence that superspreading represents a significant component of COVID-19 transmission. Many estimates of key epidemiological parameters are either based on modelling assumptions or come from incomplete data that may be subject to sampling bias.
Added value of this study Our study provides model-free estimates of key epidemiological parameters for COVID-19 from a comprehensive dataset on a complete outbreak. These include time-varying effective reproduction number, age-dependent secondary attack rates, serial interval, and the relative contribution of superspreading to transmission. Our results are less sensitive to modelling assumptions than many existing estimates and from a more complete dataset.
Implications of all the available evidence Superspreading is a significant contribution to overall transmission of COVID-19 with 20% of cases among adults responsible for 65-85% of transmission. Children under 10 years old are less infectious than adults on average and less likely to be superspreaders. Asymptomatic infections tend to infect fewer people than symptomatic cases. Population-wide social distancing, particularly when targeted at superspreading, and early isolation are effective ways of reducing the spread of COVID-19.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
All authors of this work were supported with funding from the New Zealand Ministry of Business, Innovation and Employment and Te Punaha Matatini, the New Zealand Centre for Research Excellence in Complex Systems
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This work was overseen and approved by the Ministry of Health, New Zealand.
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Paper in collection COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv
The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, University of Washington, and Vrije Universiteit Amsterdam.
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