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Sensitivity of Reverse Transcription Polymerase Chain Reaction Tests for Severe Acute Respiratory Syndrome Coronavirus 2 Through Time
AbstractBackgroundReverse transcription polymerase chain reaction (RT-PCR) tests are the gold standard for detecting recent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Reverse transcription PCR sensitivity varies over the course of an individual’s infection, related to changes in viral load. Differences in testing methods, and individual-level variables such as age, may also affect sensitivity.MethodsUsing data from New Zealand, we estimate the time-varying sensitivity of SARS-CoV-2 RT-PCR under varying temporal, biological, and demographic factors.ResultsSensitivity peaks 4–5 days postinfection at 92.7% (91.4%–94.0%) and remains over 88% between 5 and 14 days postinfection. After the peak, sensitivity declined more rapidly in vaccinated cases compared with unvaccinated, females compared with males, those aged under 40 compared with over 40s, and Pacific peoples compared with other ethnicities.ConclusionsReverse transcription PCR remains a sensitive technique and has been an effective tool in New Zealand’s border and postborder measures to control coronavirus disease 2019. Our results inform model parameters and decisions concerning routine testing frequency.
Early intervention is the key to success in COVID-19 control
New Zealand responded to the COVID-19 pandemic with a combination of border restrictions and an Alert Level (AL) system that included strict stay-at-home orders. These interventions were successful in containing an outbreak and ultimately eliminating community transmission of COVID-19 in June 2020. The timing of interventions is crucial to their success. Delaying interventions may reduce their effectiveness and mean that they need to be maintained for a longer period. We use a stochastic branching process model of COVID-19 transmission and control to simulate the epidemic trajectory in New Zealand's March–April 2020 outbreak and the effect of its interventions. We calculate key measures, including the number of reported cases and deaths, and the probability of elimination within a specified time frame. By comparing these measures under alternative timings of interventions, we show that changing the timing of AL4 (the strictest level of restrictions) has a far greater impact than the timing of border measures. Delaying AL4 restrictions results in considerably worse outcomes. Implementing border measures alone, without AL4 restrictions, is insufficient to control the outbreak. We conclude that the early introduction of stay-at-home orders was crucial in reducing the number of cases and deaths, enabling elimination.
A structured model for COVID-19 spread: modelling age and healthcare inequities
Abstract We use a stochastic branching process model, structured by age and level of healthcare access, to look at the heterogeneous spread of COVID-19 within a population. We examine the effect of control scenarios targeted at particular groups, such as school closures or social distancing by older people. Although we currently lack detailed empirical data about contact and infection rates between age groups and groups with different levels of healthcare access within New Zealand, these scenarios illustrate how such evidence could be used to inform specific interventions. We find that an increase in the transmission rates among children from reopening schools is unlikely to significantly increase the number of cases, unless this is accompanied by a change in adult behaviour. We also find that there is a risk of undetected outbreaks occurring in communities that have low access to healthcare and that are socially isolated from more privileged communities. The greater the degree of inequity and extent of social segregation, the longer it will take before any outbreaks are detected. A well-established evidence for health inequities, particularly in accessing primary healthcare and testing, indicates that Māori and Pacific peoples are at a higher risk of undetected outbreaks in Aotearoa New Zealand. This highlights the importance of ensuring that community needs for access to healthcare, including early proactive testing, rapid contact tracing and the ability to isolate, are being met equitably. Finally, these scenarios illustrate how information concerning contact and infection rates across different demographic groups may be useful in informing specific policy interventions.
Māori and Pacific people in New Zealand have a higher risk of hospitalisation for COVID-19.
AimsWe aim to quantify differences in clinical outcomes from COVID-19 infection in Aotearoa New Zealand by ethnicity and with a focus on risk of hospitalisation.MethodsWe used data on age, ethnicity, deprivation index, pre-existing health conditions and clinical outcomes on 1,829 COVID-19 cases reported in New Zealand. We used a logistic regression model to calculate odds ratios for the risk of hospitalisation by ethnicity. We also considered length of hospital stay and risk of fatality.ResultsAfter controlling for age and pre-existing conditions, we found that Māori have 2.50 times greater odds of hospitalisation (95% CI 1.39-4.51) than non-Māori non-Pacific people. Pacific people have three times greater odds (95% CI 1.75-5.33).ConclusionsStructural inequities and systemic racism in the healthcare system mean that Māori and Pacific communities face a much greater health burden from COVID-19. Older people and those with pre-existing health conditions are also at greater risk. This should inform future policy decisions including prioritising groups for vaccination.
Successful contact tracing systems for COVID-19 rely on effective quarantine and isolation
Models of contact tracing often over-simplify the effects of quarantine and isolation on disease transmission. We develop a model that allows us to investigate the importance of these factors in reducing the effective reproduction number. We show that the reduction in onward transmission during quarantine and isolation has a bigger effect than tracing coverage on the reproduction number. We also show that intuitively reasonable contact tracing performance indicators, such as the proportion of contacts quarantined before symptom onset, are often not well correlated with the reproduction number. We conclude that provision of support systems to enable people to quarantine and isolate effectively is crucial to the success of contact tracing.
Managing the risk of a COVID-19 outbreak from border arrivals
In an attempt to maintain the elimination of COVID-19 in New Zealand, all international arrivals are required to spend 14 days in government-managed quarantine and to return a negative test result before being released. We model the testing, isolation and transmission of COVID-19 within quarantine facilities to estimate the risk of community outbreaks being seeded at the border. We use a simple branching process model for COVID-19 transmission that includes a time-dependent probability of a false-negative test result. We show that the combination of 14-day quarantine with two tests is highly effective in preventing an infectious case entering the community, provided there is no transmission within quarantine facilities. Shorter quarantine periods, or reliance on testing only with no quarantine, substantially increases the risk of an infectious case being released. We calculate the fraction of cases detected in the second week of their two-week stay and show that this may be a useful indicator of the likelihood of transmission occurring within quarantine facilities. Frontline staff working at the border risk exposure to infected individuals and this has the potential to lead to a community outbreak. We use the model to test surveillance strategies and evaluate the likely size of the outbreak at the time it is first detected. We conclude with some recommendations for managing the risk of potential future outbreaks originating from the border.
Model-free estimation of COVID-19 transmission dynamics from a complete outbreak
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. 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. Children under 10 years old are significantly under-represented in the case data. Children infected fewer people on average and had a lower probability of transmitting the disease in comparison to adults and the elderly. Imported cases infected fewer people on average and also had a lower probability of transmitting 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. Subclinical cases infected fewer individuals than clinical cases. After controlling for outliers serial intervals were approximated with a normal distribution (μ = 4.4 days, σ = 4.7 days). Border controls and strong social distancing measures, particularly when targeted at superspreading, play a significant role in reducing the spread of COVID-19.
Estimated inequities in COVID-19 infection fatality rates by ethnicity for Aotearoa New Zealand.
AimsThere is limited evidence as to how clinical outcomes of COVID-19 including fatality rates may vary by ethnicity. We aim to estimate inequities in infection fatality rates (IFR) in New Zealand by ethnicity.MethodsWe combine existing demographic and health data for ethnic groups in New Zealand with international data on COVID-19 IFR for different age groups. We adjust age-specific IFRs for differences in unmet healthcare need, and comorbidities by ethnicity. We also adjust for life expectancy reflecting evidence that COVID-19 amplifies the existing mortality risk of different groups.ResultsThe IFR for Māori is estimated to be 50% higher than that of non-Māori, and could be even higher depending on the relative contributions of age and underlying health conditions to mortality risk.ConclusionsThere are likely to be significant inequities in the health burden from COVID-19 in New Zealand by ethnicity. These will be exacerbated by racism within the healthcare system and other inequities not reflected in official data. Highest risk communities include those with elderly populations, and Māori and Pacific communities. These factors should be included in future disease incidence and impact modelling.
Twin peaks: The Omicron SARS-CoV-2 BA.1 and BA.2 epidemics in England
Rapid transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has led to record-breaking incidence rates around the world. The Real-time Assessment of Community Transmission-1 (REACT-1) study has tracked SARS-CoV-2 infection in England using reverse transcription polymerase chain reaction (RT-PCR) results from self-administered throat and nose swabs from randomly selected participants aged 5 years and older approximately monthly from May 2020 to March 2022. Weighted prevalence in March 2022 was the highest recorded in REACT-1 at 6.37% ( N = 109,181), with the Omicron BA.2 variant largely replacing the BA.1 variant. Prevalence was increasing overall, with the greatest increase in those aged 65 to 74 years and 75 years and older. This was associated with increased hospitalizations and deaths, but at much lower levels than in previous waves against a backdrop of high levels of vaccination.
Practitioners’ attitudes and approaches to assessing comorbid depression among patients seeking assisted dying in New Zealand
Depressive disorders are prevalent among the terminally ill and often impact decision-making capacity. However, routine screening for depression is not currently included in assisted dying assessments. This qualitative study aimed to explore the attitudes and approaches of ten New Zealand assisted dying practitioners in assessing comorbid depression among patients seeking assisted dying. Four main themes emerged: (i) depression was viewed as a minor concern in patients seeking assisted dying, (ii) practitioners used informal approaches to assess depression, (iii) there was overlap in symptoms of terminal illness and depression, and (iv) there was opposition to introducing new mandatory processes to assess depression. This study highlights a generally informal, non-systematised approach to depression screening as part of the assisted dying assessment process. Additions to the process, including routine depression screening will require input from assisted dying stakeholders due to concern about barriers or delays for patients seeking this.
Awake Prone Positioning in Adults With COVID-19
ImportanceThe impact of awake prone positioning (APP) on clinical outcomes in patients with COVID-19 and acute hypoxemic respiratory failure (AHRF) remains uncertain.ObjectiveTo assess the association of APP with improved clinical outcomes among patients with COVID-19 and AHRF, and to identify potential effect modifiers.Data SourcesPubMed, Embase, the Cochrane Library, and ClinicalTrials.gov were searched through August 1, 2024.Study SelectionRandomized clinical trials (RCTs) examining APP in adults with COVID-19 and AHRF that reported intubation rate or mortality were included.Data Extraction and SynthesisIndividual participant data (IPD) were extracted according to PRISMA-IPD guidelines. For binary outcomes, logistic regression was used and odds ratio (OR) and 95% CIs were reported, while for continuous outcomes, linear regression was used and mean difference (MD) and 95% CIs were reported.Main Outcomes and MeasuresThe primary outcome was survival without intubation. Secondary outcomes included intubation, mortality, death without intubation, death after intubation, escalation of respiratory support, intensive care unit (ICU) admission, time from enrollment to intubation and death, duration of invasive mechanical ventilation, and hospital and ICU lengths of stay.ResultsA total of 14 RCTs involving 3019 patients were included; 1542 patients in the APP group (mean [SD] age, 59.3 [14.1] years; 1048 male [68.0%]) and 1477 in the control group (mean [SD] age, 59.9 [14.1] years; 979 male [66.3%]). APP improved survival without intubation (OR, 1.42; 95% CI, 1.20-1.68), and it reduced the risk of intubation (OR, 0.70; 95% CI, 0.59-0.84) and hospital mortality (OR, 0.77; 95% CI, 0.63-0.95). APP also extended the time from enrollment to intubation (MD, 0.93 days; 95% CI, 0.43 to 1.42 days). In exploratory subgroup analyses, improved survival without intubation was observed in patients younger than age 68 years, as well as in patients with a body mass index of 26 to 30, early implementation of APP (ie, less than 1 day from hospitalization), a pulse saturation to inhaled oxygen fraction ratio of 155 to 232, respiratory rate of 20 to 26 breaths per minute (bpm), and those receiving advanced respiratory support at enrollment. However, none of the subgroups had significant interaction with APP treatment. APP duration 10 or more hours/d within the first 3 days was associated with increased survival without intubation (OR, 1.85; 95% CI, 1.37-2.49).Conclusions and RelevanceThis IPD meta-analysis found that in adults with COVID-19 and AHRF, APP was associated with increased survival without intubation and with reduced risks of intubation and mortality, including death after intubation. Prolonged APP duration (10 or more hours/d) was associated with better outcomes.
Ethics of Identifying Individuals Involved in HIV Transmission Events by Phylogenetics in Molecular Surveillance
ABSTRACTMolecular HIV surveillance, involving the collection and analysis of HIV genome sequences, has become an integral part of public health programmes in high‐income countries. By employing phylogenetic analysis, molecular HIV surveillance can identify individuals and their positions within networks of HIV transmission. While the primary aim of molecular surveillance is to yield public health benefits, such as linking people to care and reducing transmission, it also poses risks and potential infringements on individual privacy and liberty. This paper examines the ethical implications of using phylogenetics to identify individuals involved in multiple transmission events in high‐income countries. Although public health responses tailored to such individuals can significantly reduce further transmission, these individuals often face multiple intersecting vulnerabilities and bear the greatest risks associated with molecular surveillance. We analyze the risks related to privacy, stigma, mistrust, criminalization, and liberty infringements, alongside the benefits of preventing further transmission and increasing healthcare engagement for people living with HIV. We conclude by outlining plausible and ethically acceptable policy options for molecular surveillance practice.