What we would like to see on the Ministry of Health’s website to better inform progress on COVID-19 elimination

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Gordon Purdie, Nick Wilson, Michael G Baker

In this blog we analyse data from the Ministry of Health’s COVID-19 website and display a key graph that we think should be routinely on that website. We also detail a potentially more useful way to categorise case data so that the public and research community can better track progress on the path to COVID-19 elimination. Both the graphical and tabular presentation of case data need to emphasise the critical distinction between imported cases (who should be safely isolated in supervised quarantine facilities) and transmission within NZ that would threaten elimination status.

People infected with the coronavirus SARS-CoV-2 that causes COVID-19, and detected in NZ, belong to one of two broad groups: infected overseas or infected within NZ. The Ministry of Health (MoH) provides some data on confirmed and probable cases. We assume the cases in this database are mostly symptomatic cases. However, it is not necessarily all identified symptomatic cases in NZ because the dataset is not intended to include those who were diagnosed overseas and have been included in another country’s count reported to WHO (Press conference by Director General of Health, 23/4/20).

Graphing the separate contribution of imported and locally acquired COVID-19 infections

To demonstrate the value of improving the graphical presentation of COVID-19 cases on the MoH’s website, we graph below data from the MoH’s tabulated line listings of cases that includes an overseas travel variable (coded as yes, no or blank). We assume those with ‘yes’ are those who are thought to have been infected overseas or in transit to NZ. The figure below shows the number of cases reported each day divided into those with overseas travel (yes) in orange and those not (overseas travel no or blank) in red.

This figure shows that the proportion of reported cases associated with overseas travel has been decreasing, with an increasing proportion of cases being infected in NZ.

The overseas travel variable is ‘yes’ for 39% of cases, the same percentage that the MoH reports as imported cases (cases with a reported history of international travel within 14 days of symptom onset). The percentage of cases with overseas travel in the last two weeks is 16%. So there has been an increase in the proportion of all cases which are identified infections that are transmissions in NZ. But this could also partly be a consequence of more overseas travellers arriving in NZ with their infection having been identified and reported by a country they have come from (but such data are not reported by the MoH). Those with the overseas travel variable blank (13) have a similar distribution of report dates to those with the overseas travel variable as ‘no’.

Delays with reporting of cases amongst travellers

The following figure shows the distribution of the days between an overseas traveller’s arrival in NZ and the date that their case status was officially reported.

This duration is recorded for most overseas travellers. For 11% the duration is longer than 14 days. Since these are cases with a reported history of international travel within 14 days of onset, these represent durations between onset and reporting of up to at least 27 days, which is a concern from a disease control perspective. Furthermore, the 11% with a duration between arrival and report date of greater than 14 days is an underestimate of this proportion because more recent arrivals that will have a long duration have not been reported yet (only those with a short duration could be reported).

The NZ Government introduced further border measures on entry to NZ for flights which depart from another country after 9 April. These travellers must go into supervised quarantine facilities for a minimum of 14 days. Since then (21 days ago at the time of writing), for infections that have been reported, the duration between arrival and report date has ranged from 2 to 6 days.

The current border controls may be effective. Whereas following earlier 14 day self-isolation measures, travellers may have left self-isolation after the onset of symptoms and before their case was reported.

Improving the transmission categories used to classify and tabulate COVID-19 cases

NZ appears to be making good progress towards the elimination of infection from SARS-CoV-2. The number of new cases of infection has been declining during April (down to only 2 new cases on 30 April), while the amount of testing has been steadily increasing. Nevertheless, it is still unclear from the MoH website as to the extent to which new cases of COVID-19 in the last 24 hours or last week are either epidemiologically linked to other known cases, or have no known source.

To clarify such issues we present below a table template that we consider shows case data in a way that supports the elimination goal and identifies categories where action would be needed if cases were detected. It would also be useful to see the MoH provide a second version of the table presented based on onset date, instead of report date, to provide a better indication of distribution of infectious cases over time.

The most important distinction is between imported cases detected in travellers arriving in NZ and cases where transmission has occurred within this country. While quarantine measures remain in place at our points of entry, cases detected in arriving travellers should not be a threat to any elimination status. Indeed, we can expect such cases to continue and potentially increase depending on numbers of arrivals, their source countries and the intensity and distribution of the global COVID-19 pandemic. By contrast, the other categories of cases all threaten the country’s potential elimination status. Such cases should be carefully classified to help inform our containment efforts and identify improvements.

The term “community transmission” is ambiguous and probably not particularly helpful for defining elimination status. For a highly infectious virus like SARS-CoV-2, all transmission events in the susceptible NZ population would threaten elimination status. As noted in the table, some events would be of much greater concern than others, notably cases where the source of infection is unknown.

The categories presented here should ideally be used to also classify test data, including both test requests and results. That way it would be possible to calculate positivity proportions (%) in meaningful ways.

Sample table for categorising and presenting regularly updated COVID-19 case data in NZ

Case transmission category Implications Last 24h Last 7 days Last 28 days Cumul-ative
Imported infections
Travellers to NZ (with these being in isolation until recovery) Does not impact on elimination status
Cases linked to imported infections1
Aircrew or airport staff, ship crews or seaport staff Failure of border quarantine systems
People who were infected as a household contact of a known infected traveller or airport/seaport worker Failure of border quarantine systems2
People who were infected as a contact of a known infected traveller (other than household contacts) or part of an outbreak linked to a traveller Failure of border quarantine systems2
Cases linked to spread within NZ1
People whose source of infection is unknown (and investigations have been exhausted) Potentially widespread transmission in NZ
People who were infected as a household contact of a known case (but where this case was not a traveller to NZ) Transmission within NZ2
People who were infected from a known case in the community (ie, epidemiologically linked and not in the above categories) or part of an outbreak linked to such a case Transmission within NZ2

Indicator of the effectiveness of contact tracing

People who were infected in a healthcare setting Failure of infection control2
People whose source of infection is unknown but investigations are still proceeding Uncertain importance but potentially widespread transmission within NZ
Potential cases linked to spread within NZ1
People identified as infected during systematic testing of asymptomatic populations who are more likely to be exposed to COVID-19, eg, healthcare workers, staff in quarantine facilities Implications depend on population, context, and test specificity.3

Could indicate widespread transmission within NZ

1 Cases in these categories contribute to the ‘not-imported’ grouping and would have implications for maintenance of any elimination status, depending on how that is defined.

2 The importance of these cases depends on whether these outbreaks are being successfully investigated and contained through rapid contract tracing and quarantine.

3 Testing of asymptomatic people will inevitably identify false positives which need to be evaluated before deciding whether they are ‘true’ cases.

 

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12 thoughts on “What we would like to see on the Ministry of Health’s website to better inform progress on COVID-19 elimination

  1. What I still don’t see addressed in your table is the dynamic of cases going from under investigation one day and linked on another day
    Every day we hear cases under investigation but can’t track what’s come if them

  2. Thanks for this level of detailed clarification of each new case of infection. It makes enormous sense to me. should we adopt this approach would there be some ongoing reshuffling of the numbers over a few days as more information arises or is this a pretty straight forward call ? Could all the data we have to date for all our cases be represented in this way

  3. Asymptomatic transmission of Covid-19 is thought to be as high as 50 percent and possibly as high as 90percent( santa clara study) . Yet aircrew are still not subject to two week quarantine on arrival in New Zealand. This represents a significant potential breach point in quarantine efforts.

  4. I concur with the authors that the information they ask for would better inform our officials and public. Another possible route of quarantine breach not coverd in the MOH guidleines are diplomatic staff, military, political and press attache staff who may enter the country now or in the future.

  5. Very useful. I’m no expert in this but these question have Also occurred to me. I encourage you to push the MOH to implement what you suggest.

  6. Very much agree with the need to put meaning to the numbers and present links. This can be done while respecting privacy. Hope your message gets heard and we will see more informative sub-classification from next week

  7. Smart work team , now how due we get Health Dept. to act with haste .Try and work out how many in Quarantine/managed isolation have tested positive since 9th April .I count 6 , PM says 25 .Which is it ?

  8. I would like to see if there was data on the number of days from (probable) infection to testing positive or considered probable. Quarantine is 14 days but in theory there are studies with much longer periods.

  9. Yes I completely agree with your ‘sample table’. Please can the data also be collected by ethnicity. Does anyone actually know where in NZ the cases that are presumed ‘community transmission’ are, when they were diagnosed, and whether they are still ‘active’? I have also been making charts/graphs from the MoH information, but there is not enough detail to know the answers to the above questions. There has been 1% ‘under investigation’ since 30 April, but I don’t know if it the same people that have been under investigation since 30 March (where 15% were under investigation) or different people. There has been 3-4% ‘locally acquired unknown source’ for several weeks, previously ‘community transmission’ but I don’t know if people have moved in and out of this group. I would like to know each day how many new cases are currently classified as each of these categories, and where they are, their ethnicity, and whether the cases are active or recovered.

  10. I also think there is a case for looking at the occupation of the person as they consider reducing the alerts level. Hospital staff is one to consider since the overwhelming of the critical care areas of health. There are good examples of data displays such as the John Hopkins University and CovidActNow that could be examples. The visuals should help all people be able to understand what is presented to them.

  11. I run https://covid19map.co.nz and collecting data on a daily basis has been incredibly frustrating. The format is forever changing and there is no clear relation between the daily overview and the spreadsheet that details each case.

    I too am tracking “X days back in NZ before contracting” and would like some clarity around confirmed dates – if someone can go over 40 days before returning a positive result does this mean they had COVID and are now simply testing positive because they possess the antibodies?

    Another vital piece of information that would provide valuable insight – tracking the relationship of each case – for example – if case #34 was linked to case #35 and how this transmission occurred. With this information we could effectively calculate the rate of transmission and the risks associated.

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