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1.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.12.25.20248427

ABSTRACT

Aims. We aim to quantify differences in clinical outcomes from COVID-19 infection by ethnicity with a focus on risk of hospitalisation. Methods. We 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 consider length of hospital stay and risk of fatality. Results. M[a]ori have 2.5 times greater odds of hospitalisation than non-M[a]ori, non-Pacific people, after controlling for age and pre-existing conditions. Similarly, Pacific people have 3 times greater odds. Conclusions. Structural inequities and systemic racism in the healthcare system mean that M[a]ori 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.


Subject(s)
COVID-19
2.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.05.17.20104976

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 amongst 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. Well-established evidence for health inequities, particularly in accessing primary healthcare and testing, indicates that M[a]ori and Pacific peoples are at 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.


Subject(s)
COVID-19
3.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.04.20.20073437

ABSTRACT

There is limited evidence as to how COVID-19 infection fatality rates (IFR) may vary by ethnicity. We combine demographic and health data for ethnic groupings in Aotearoa New Zealand with international data on IFR for different age groups to estimate inequities in IFR by ethnicity. We find that, if age is the dominant factor determining IFR, estimated IFR for M[a]ori is around 50% higher than non-M[a]ori. If underlying health conditions are more important than age per se, then estimated IFR for M[a]ori is more than 2.5 times that of New Zealand European, and estimated IFR for Pasifika is almost double that of New Zealand European. IFRs for M[a]ori and Pasifika are likely to be increased above these estimates by racism within the healthcare system and other inequities not reflected in official data. IFR does not account for differences among ethnicities in COVID-19 incidence, which could be higher in M[a]ori and Pasifika as a result of crowded housing and higher inter-generational contact rates. These factors should be included in future disease incidence modelling. The communities at the highest risk will be those with elderly populations, and M[a]ori and Pasifika communities, where the compounded effects of underlying health conditions, socioeconomic disadvantage, and structural racism result in imbricated risk of contracting COVID-19, becoming unwell, and death.


Subject(s)
COVID-19
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