ABSTRACT
BackgroundDuring New Zealands first outbreak in early 2020 the Southern Region had the highest per capita SARS-CoV-2 infection rate. PCR testing was initially limited by a narrow case definition and limited laboratory capacity, so cases may have been missed. ObjectivesTo evaluate the Abbott(R) SARS-CoV-2 IgG nucleocapsid assay, alongside spike-based assays, and to determine the frequency of antibodies among PCR-confirmed and probable cases, contacts, and higher risk individuals in the Southern Region of NZ. Study designPre-pandemic sera (n=300) were used to establish assay specificity and sera from PCR-confirmed SARS-CoV-2 patients (n=78) to establish sensitivity. For prevalence analysis, all samples (n=1214) were tested on the Abbott assay, and all PCR-confirmed cases (n=78), probable cases (n=9), and higher risk individuals with grey-zone (n=14) or positive results (n=11) were tested on four additional SARS-CoV-2 serological assays. ResultsThe median time from infection onset to serum collection for PCR-confirmed cases was 14 weeks (range 11-17 weeks). The Abbott assay demonstrated a specificity of 99.7% (95% CI, 98.2%-99.99%) and a sensitivity of 76.9% (95% CI, 66.0%-85.7%). Spike-based assays demonstrated superior sensitivity ranging 89.7-94.9%. Nine previously undiagnosed sero-positive individuals were identified, and all had epidemiological risk factors. ConclusionsSpike-based assays demonstrated higher sensitivity than the Abbott IgG assay, likely due to temporal differences in antibody persistence. No unexpected SARS-CoV-2 infections were found in the Southern region of NZ, supporting the elimination status of the country at the time this study was conducted.
ABSTRACT
The effective reproduction number, Reff, is the average number of secondary cases infected by a primary case, a key measure of the transmission potential for a disease. Compared to many countries, New Zealand has had relatively few COVID-19 cases, many of which were caused by infections acquired overseas. This makes it difficult to use standard methods to estimate Reff. In this work, we use a stochastic model to simulate COVID-19 spread in New Zealand and report the values of Reff from simulations that gave best fit to case data. We estimate that New Zealand had an effective reproduction number Reff = 1.8 for COVID-19 transmission prior to moving into Alert Level 4 on March 25 2020 and that after moving into Alert level 4 this was reduced to Reff = 0.35. Our estimate Reff = 1.8 for reproduction number before Alert Level 4, is relatively low compared to other countries. This could be due, in part, to measures put in place in early-to mid-March, including: the cancellation of mass gatherings, the isolation of international arrivals, and employees being encouraged to work from home.
ABSTRACT
AimsWe aimed to determine the length of time from the last detected case of SARS-CoV-2 infection before elimination can be assumed at a country level in an island nation. MethodsA stochastic version of the SEIR model Covid SIM v1.1 designed specifically for COVID-19 was utilised. It was populated with data for the case study island nation of New Zealand (NZ) along with relevant parameters sourced from the NZ and international literature. This included a testing level for symptomatic cases of 7,800 tests per million people per week. ResultsIt was estimated to take between 27 and 33 days of no new detected cases for there to be a 95% probability of epidemic extinction. This was for effective reproduction numbers (Re) in the range of 0.50 to 1.0, which encompass such controls as case isolation (the shorter durations relate to low Re values). For a 99% probability of epidemic extinction, the equivalent time period was 37 to 44 days. In scenarios with lower levels of symptomatic cases seeking medical attention and lower levels of testing, the time period was up to 53 to 91 days (95% level). ConclusionsIn the context of a high level of testing, a period of around one month of no new notified cases of COVID-19 would give 95% certainty that elimination of SARS-CoV-2 transmission had been achieved.
ABSTRACT
AimsWe aimed to determine the effectiveness of surveillance using testing for SARS-CoV-2 to identify an outbreak arising from a single case of border control failure at a country level. MethodsA stochastic version of the SEIR model CovidSIM v1.1 designed specifically for COVID-19 was utilised. It was seeded with New Zealand (NZ) population data and relevant parameters sourced from the NZ and international literature. ResultsFor what we regard as the most plausible scenario with an effective reproduction number of 2.0, the results suggest that 95% of outbreaks from a single imported case would be detected in the period up to day 33 after introduction. At the time point of detection, there would be a median number of 6 infected cases in the community (95%UI: 1-68). To achieve this level of detection, an on-going programme of 7,800 tests per million people per week for the NZ population would be required. The vast majority of this testing (96%) would be of symptomatic cases in primary care settings and the rest in hospitals. Despite the large number of tests required, there are plausible strategies to enhance testing yield and cost-effectiveness eg, (i) adjusting the eligibility criteria via symptom profiles; (ii) and pooling of test samples. ConclusionsThis model-based analysis suggests that a surveillance system with a very high level of routine testing is probably required to detect an emerging or re-emerging SARS-CoV-2 outbreak within one month of a border control failure in a nation.
