Please note: I have decided to remove Figure 3 from this post as I confused myself with the ABS changes to baselines and mortality counts. I will be very soon posting a further analysis of Covid which will present information in a much improved manner.
Also, it is time for an update on Covid-19 and mortality.
I have looked at ABS data for Australia as a whole and for four states: New South Wales (which eased restrictions earlier than some thought wise); Queensland (which had rigid border restrictions, then opened at the start of the Omicron wave); Victoria (which had lax early restrictions then became overly rigid); and Western Australia (which maintained border restrictions until 4 March this year).
Changes in the way ABS collect and publish data complicate analysis. The ABS changed its baseline for calculations from January this year; and, as well, previous State and National mortality data now available for download is only for doctor certified deaths whereas 2022 State data is for total mortality figures (including data from coroners’ reports). This can be confusing. I work around this by calculating the percentage change from the baseline. The next figures illustrate this.
Figure 1: National Absolute Mortality (as certified by doctors)
The baseline changed in January 2022 as shown. There was a large step up in the baseline at the same time as the Omicron wave.
Figure 2: NSW Absolute Mortality (as certified by doctors to December 2021 then all deaths from January 2022))
Notice the huge jump- that’s why I calculate percentage change from the expected number or baseline.
Figure 3: National Percentage Change in Mortality (removed)
The percentage change shows the fluctuations in mortality as a result of the Covid-19 waves, lockdowns, international border closures, and influenza. There is nothing alarming about recent figures.
The next plot compares NSW with WA. NSW relaxed restrictions early and WA kept borders closed until March 2022.
Figure 4: Percentage Change in Mortality- NSW and WA
WA missed most of Omicron.
Figure 5: Percentage Change in Mortality- Qld and Victoria
Victoria had major problems with hotel quarantine in the second wave, then imposed very severe restrictions, but again had large Delta and Omicron outbreaks. Queensland may have had an “early” undetected first wave, a peak in Omicron, but had a larger than expected number of deaths in June 2022 due to a severe flu outbreak on top of already struggling public hospitals.
You will note the large weekly up and down spikes. This is probably due to late reporting of deaths by doctors and nursing homes. There was evidence of this in January this year in Queensland, when several weeks of nursing home deaths were added in one week. The next plot smooths the weekly data with a centred 5 week running mean.
Figure 6: 5 Week Centred Mean of Percentage Change in Mortality
I have indicated the Covid peaks.
Note:
Queensland’s possible early first wave, and Victoria’s second, Delta, and Omicron waves show clearly.
Omicron struck Queensland, NSW, and Victoria hard with 27% to 37% increase on expected mortality (5 week averaged).
Queensland had a large number of unexpected deaths in 2021, beginning well before vaccine rollout.
West Australia’s mortality figures are similar to other states, apart from largely missing Delta and Omicron.
The small peaks around weeks 68 -72 are not associated with vaccine rollout: vaccinations gathered speed after this time (early May 2021).
The ABS data does not show any large surge in unexplained deaths in 2022.
In this post I am looking at the pandemic experience across New South Wales, Victoria, Queensland, and South Australia, since the Queensland border was opened on 17 December 2021. Tasmania, the Northern Territory, and the ACT are excluded because their numbers so far are too low for useful analysis, and WA of course is still a hermit kingdom.
That site has excellent comparative charts, however I wanted to pick up on some points which are not so clear.
For some time Chief Health Officers have been warning that case numbers are a poor metric of Covid infections. Here’s why:
Figures 1 to 4 show 7 day running means of reported daily positive cases of Covid-19 for each state.
Figure 1: Queensland cases
Figure 2: New South Wales cases
Figure 3: Victorian cases
Figure 4: South Australian cases
Notice that the high point for all states was reached at about the same date, and cases in all states plummeted after the 20th January. (Victoria plummeted from the 15th.) All states gave up trying to keep up with the testing demand and Rapid Antigen Tests were as rare as hens’ teeth.
Case numbers we can then ignore: they may be two, three, or more times higher.
A better metric will be the seven day rolling mean number of people in hospital, in Intensive Care, or dying.
Figure 5: Queensland daily numbers in hospital
Hospitalisations peaked on Australia Day and are slowly falling.
Figure 6: NSW daily numbers in hospital
In NSW there was no distinct peak but hospitalisations have been gradually falling since 25 January.
Figure 7: Victoria daily numbers in hospital
Victoria’s peak was on 21 January.
Figure 8: South Australia daily numbers in hospital
South Australian hospitalisations stopped rising on 25 January with a slow fall since.
Figure 9: Queensland daily ICU and mortality numbers
Although Qld hospitalisations have declined, ICU numbers have remained at about 50 for two weeks. Deaths are also plateauing.
Figure 10: NSW daily ICU and mortality numbers
Despite a fall in the number of ICU patients, deaths are high, and it is still too early to see a peak.
Figure 11: Victoria daily ICU and mortality numbers
There is a similar situation in Victoria. While ICU numbers have fallen, deaths have plateaued over the last six days.
Figure 12: South Australia daily ICU and mortality numbers
Only in South Australia do we see a distinct fall in deaths, with a corresponding fall in ICU numbers. Let’s hope this continues. However, it is possible there is something different about the data reporting.
Across these states there appears to be a delay of from 7 to 10 days from the suspected peak in case numbers to hospital admission, and 14 to 16 days from peak in cases to death.
Of those admitted to hospital, the chance of going into ICU is:
Queensland: 1 in 17
NSW: 1 in 15
Victoria: 1 in 9
Sth Australia: 1 in 5 – 6
Once in ICU, the chance of dying is:
Queensland: 1 in 4 -5
NSW: 1 in 6
Victoria: 1 in 5
Sth Australia: 1 in 8
In Queensland, based on official case numbers, an individual testing positive (all ages and all vaccination states) has a 1 in 20 chance of being sick enough to go to hospital; 1 in 345 of being admitted to ICU; and 1 in 1,500 of dying. (For healthy, fit individuals under the age of 60 the chances will be considerably smaller.)
Conclusion 1: In these four states, we are almost over the worst, and the health systems have managed to cope (albeit with leave being cancelled and great stress on staff).
Conclusion 2: Covid-19 loves people to live in big cities, or to live in crowded conditions, or to have lowered immunity and chronic health conditions, or to be elderly. Nursing homes fit those last three conditions nicely. Many nursing home inmates also have Advanced Health Directives, many probably stipulating they do not wish to have resuscitation or ventilation. A high death toll in nursing homes is to be expected with a highly transmissible and nasty flu like Covid.
With the recent surge in Covid-19, here is a progress report without the hype from the media, and without the commentary from those who doubt the impact of the disease.
I am attempting to show how Covid-19 compares with other major diseases in one important aspect: mortality. How deadly is it?
To be certified as a Covid-19 fatality, Covid-19 must be the underlying cause of death- not dying of another condition while being positive for Covid. According to Covid-19 Mortality, 71.2% of people dying from Covid had pre-existing chronic conditions. The overall Case Fatality Rate (CFR) for Australia for COVID-19 as of 31 October 2021 was 1.0%, but while the CFR for those aged under 60 years was 0.1%, the CFR for males aged 90 years and over was close to 50%. 83% of people who died of Covid were over 70. It is therefore a relatively mild disease for younger people, but very severe for elderly and sick Australians.
I shall now tease out mortality statistics to show Covid in context.
Figure 1 shows weekly death tallies of deaths in which doctors certified Covid as being the underlying cause of death, and from November weekly death tallies from Our World in Data.
Figure 1: Weekly Covid Deaths from January 2020
Those who doubt the severity of Covid-19 often say that deaths from Covid are far less than from other causes. Figure 2 shows total deaths for the past two years to October as well as the average from 2015-2019 (as 2020 was very unusual), together with Covid deaths.
Figure 2: Covid-19 compared with all deaths per week
They have a point- to a point. Weekly deaths from Covid in 2020 and 2021 were tiny in comparison, but in 2022 have risen to be a fifth of the average number for this time of year. Breaking down the death toll to show separate diseases shows a different picture again.
Figure 3: Covid-19 and other major diseases
Clearly, Covid’s weekly death toll is already greater than all other major killers except cancer, and may overtake cancer in another couple of weeks. Thankfully we are close to the peak in eastern states.
Covid is a respiratory disease, but counted separately. How does it compare with other respiratory diseases? The next figure tracks Covid and total respiratory deaths, together with the average weekly deaths from respiratory illness from 2015 to 2019.
Figure 4: Covid-19 and respiratory disease mortality
Covid already not only exceeds the weekly respiratory deaths for any time in the last two years (which had very little influenza), but also the highest average for 2015-2019.
I used to think Covid-19 was just another nasty infectious flu. Not anymore. Here’s a comparison of Covid deaths with deaths due to influenza leading to pneumonia.
Figure 5: Covid-19 and influenza mortality
Already Covid-19 deaths are nine times the average for this time of year, and are also more than three times higher than the average in the peak of the winter flu season.
And WA has yet to open its border!
To compare mortality from diseases, the ABS calculates age-standardised death rates (SDRs) which “enable the comparison of death rates between populations with different age structures”. Rates are calculated per 100,000 population. Figure 2 shows death rates for the major diseases causing fatalities, including approximate (caution: not age- standardised) figures for Covid.
Figure 6: Death rates for Covid-19 and other major killers
Deaths will not stay at this high level for much longer. There are signs we are close to the peak of new cases, and deaths will peak a week or two after that. With Covid endemic in the community, mortality will fall to an unknown rate, and hospitalisations will become more easily manageable.
Make no mistake: this is a deadly disease! Take care!
It is likely that the real Covid19 death toll was at least double the official tally, and possibly hundreds more.
Despite this, there were 1,457 fewer deaths in the first six months of this year than last year.
The first lockdown worked- until the Victorian fiasco.
In this post I use the most recent Mortality data (released 1 October 2020) from the Australian Bureau of Statistics (ABS), up to 30 June 2020, and the most recent ABS Population data, to examine the effect of the Covid19 pandemic on Australian deaths. This period covers the whole of the first wave of the pandemic and gives interesting insights. Future data releases covering the second wave (with another 800 Covid19 deaths) will provide further illumination.
The ABS advises that the data are provisional and not complete as deaths subject to coroners’ inquests are not included, but with completeness percentages in the high 90s “meaningful comparison with historic counts” may be made.
Key statistics from the ABS:
68,986 doctor certified deaths occurred between 1 January 2020 and 30 June 2020.
Numbers of deaths have been below historical averages since mid May and below baseline minimums since the week ending 9 June.
Deaths from respiratory diseases and heart diseases were below historical minimum counts throughout June.
Figure 1: ABS chart of deaths and Covid19 infections
The peak of new coronavirus infections was in the week ending 31 March, with 2,428 new infections in that week (Week 13), and the peak in all mortality also occurred in that week. The following plot shows official Covid19 mortality (from Worldometers) peaking in Week 14.
Figure 2: Covid19 first wave deaths
The ABS says that the World Health Organisation (WHO) early in 2020 “directed that the new coronavirus strain be recorded as the underlying cause of death, i.e. the disease or condition that initiated the train of morbid events, when it is recorded as having caused death……..
……. Deaths due to COVID-19 are included in the total for all deaths certified by a doctor. They are not included in deaths due to respiratory diseases or any of the other specified causes.”
The first reported Covid19 death was on 1 March, (Week 9). In Week 14, one week after the peak in new infections, the peak in the first wave deaths occurred. In this post I define the first wave of the pandemic as Weeks 9 to 21. (The second wave commenced in Week 24.) Figure 3 shows Covid19 deaths in context. The duration of first wave deaths is indicated by the horizontal red line.
Figure 3: Covid19 and total deaths
Note the increase in total deaths in Weeks 12 to 15, and the insignificance of official Covid19 mortality by comparison. (Australia closed borders on 16 March- Week 11- and began restricting movement in the days following.)
The next graph compares 2020 mortality so far with the five previous years.
Figure 4: Total Australian deaths 2015 – 2020
This year’s peak in deaths also occurred in Weeks 12 to 15, at the height of the first wave infections.
You will also note Australia’s 2020 mortality levelled off well below previous years’ figures, which usually continue rising to peak in Winter and early Spring. Mortality figures for Weeks 27 to 52 will be very interesting. There was an unusual early surge in 2019, and a very large increase in deaths in Winter and Spring of 2017.
I now look at excess deaths. The ABS says:
“Measuring ‘excess’ deaths
Excess mortality is an epidemiological concept typically defined as the difference between the observed number of deaths in a specified time period and the expected numbers of deaths in that same time period. Estimates of excess deaths can provide information about the burden of mortality potentially related to the COVID-19 pandemic, including deaths that are directly or indirectly attributed to COVID-19.
… counts of deaths for 2020 are compared to an average number of deaths recorded over the previous 5 years (2015-2019). These average or baseline counts serve as a proxy for the expected number of deaths, so comparisons against baseline counts can provide an indication of excess mortality. “
However, Australia’s population has increased by nearly two million from March quarter 2015 to March quarter 2020 (from 23,745,629 to 25,649,985). This has a large impact on calculations. Mortality rate per 1,000 head of population is a better measure. Figure 5 shows mortality rates for recent years.
The method I have used is different from the ABS methodology because of the population increase and is based on mortality rates rather than absolute numbers of deaths.
I have calculated the mortality rate per 1,000 people for each of the 2015-2019 years (using the population for the March quarters of those years), and similarly for the 2020 data. I then multiply the average of the 2015-2019 mortality rates by the 2020 March quarter population to obtain an estimate of predicted deaths for 2020. Subtracting this from the actual 2020 number gives an estimate of excess deaths. An excess death figure of zero indicates the mortality rate is no different from previous years. The next figure shows plots of actual and expected deaths for the first half of 2020.
Figure 6: Predicted and actual deaths
Figure 7 is my plot of excess deaths to 30 June.
Figure 7: Estimated Excess Mortality
Excess and actual deaths peaked in Weeks 12 to 15, with weeks 13 and 14 nearly 200 above the expected level- but there were only 56 official Covid19 deaths in those weeks. Officially, Covid19 was involved in 29 deaths in Week 14, 12 each in Weeks 13 and 15 and only 3 in Week 12. It is possible that Covid19 deaths were being vastly under-reported in March.
By the end of June estimated excess deaths were at minus 349, 11.5% below the expected number for Week 26. Actual deaths in the first half of the year were 1,457 fewer than for the same period in 2019.
States and Territories:
Figure 8 shows actual numbers of deaths for all states and territories.
Figure 8: 2020 mortality numbers for each state
Mortality figures are dominated by New South Wales, followed by Victoria and Queensland. Figure 9 shows excess deaths.
Figure 9: Excess mortality by states
Smaller states had smaller changes in excess mortality, although Western Australia had a peak of 54 excess deaths in Week 13. Figure 10 shows excess deaths for the larger states only.
Figure 10: Excess deaths in the large eastern states
Peaks in excess deaths occurred between Weeks 9 to 17, but note earlier peaks in New South Wales and Queensland 7 or 8 weeks before the pandemic peak, with Queensland much higher than New South Wales, largely counteracted by Victoria, and a peak in Victoria in Weak 11, counteracted by New South Wales. There was a third peak in Weeks 17 to 19, coinciding with another peak in Covid19 deaths. Remember these numbers are additional to Covid19 deaths. And officially Queensland had only seven Covid19 deaths, almost certainly due to under-reporting.
Age at death
Figure 11 shows the ages at which excess deaths occurred.
Figure 11: Excess mortality by age
People aged from 0 to 44 years were not affected by the large changes in death rates in older age groups, but there was an increase in excess deaths in the 45 to 64 age bracket in Week 13, at the height of Covid19 infections, as Figure 12 shows. That looks suspicious, but may be chance.
Figure 12: Excess deaths for younger cohorts
The majority of excess deaths were in older age groups, as Figure 13 shows.
Figure 13: Excess deaths for older Australians
There was a peak of 132 excess deaths in those 85 years and over in Week 14, but in Week 13 there were 146 excess deaths in those aged 65 to 84. There were additional substantial peaks in earlier weeks as well. It was not a good first half of the year for senior citizens, but excess deaths for all age groups were well below expected numbers by June.
Cause of death
A death certificate lists all causes of death, and with elderly people these can be three or more. It is very likely that a person over 85 may die of pneumonia (classified as a respiratory illness), but may also have any or all of dementia, diabetes, cerebrovascular disease, ischaemic heart disease, and cancer. However, the ABS asks doctors to report the (one) underlying cause of death, and since earlier this year, Covid19 as the underlying cause “when it is recorded as having caused death.”
Figure 14 compares all respiratory deaths with Covid19.
Figure 14: Covid19 and respiratory deaths
Influenza and pneumonia are subsets of respiratory illness, and the next figure shows interesting excess mortality data for 2020.
Figure15: Excess deaths due to respiratory causes
Note the peak in respiratory deaths at the height of pandemic infections, but an earlier peak some four weeks previously. It is likely that Covid19 was not correctly reported to the ABS by all doctors until Week 14 or 15- doctors are human too. Since the first wave and the increase in personal hygiene, social distancing and little travel, deaths have remained well below previous years.
Figure 16: Ischaemic heart and cerebrovascular disease excess deaths
This plot illustrates the advances in medicine: ischaemic heart disease in 2020 had fewer deaths than expected for all of the first six months apart from a peak in Week 7. Cerebrovascular disease (chiefly strokes) also had fewer deaths than expected except for Week 14 (so was potentially related to Covid19), and another peak in Week 24.
Figure 17 plots excess deaths caused by the common co-morbidities of Covid19, dementia and diabetes.
Figure 17: Excess deaths caused by dementia, diabetes, and Covid19
Diabetes and Dementia excess deaths were also higher than expected during the first wave, but there was another large surge in excess deaths with dementia as a cause weeks earlier.
Conclusions:
With the caveat that the ABS mortality figures are provisional, and putting together figures for various states, ages, and causes of death, some conclusions may be drawn:-
Either a mystery respiratory illness or undiagnosed Covid19 was widespread in the eastern states amongst elderly people weeks before the peak of first wave deaths, possibly arriving from cruise ships.
There were probably many more Covid19 deaths and infections than reported. It is likely that the real Covid19 death toll was at least double the official tally, and possibly hundreds more.
Social distancing, good hygiene, and travel restrictions have caused a large decrease in mortality in May and June by restricting the spread of many common illnesses. The first lockdown worked- until the Victorian fiasco.
The net effect of the first wave of the Covid19 pandemic on Australian mortality was negative. Covid19, and public health responses to it, resulted in a lower death toll in the first half of 2020. This lower death toll was not just in relative (mortality rate) terms but also in absolute terms: there were 1,457 fewer deaths in the first six months of this year than last year.
ABS data for the second half of the year will be released around April 2021 and will provide much better information about excess mortality for all states (and Victoria in particular), for all age groups, and for all causes.
I include an appendix with raw mortality data for 2015 -2020.
Appendix: Raw mortality data for all causes 2015 – 2020.
Figure 18: Respiratory mortality
Note the typical winter and spring surge in respiratory deaths, mainly due to influenza outbreaks in cold months. There was an early surge in 2019 and a very large surge in 2017 which will skew means for those weeks. Median mortality rate may be more appropriate than means.
Figure 19: Ischaemic heart disease mortality
Heart disease mortality has been below previous years for most of the first 26 weeks.
Figure 20: Cerebrovascular disease mortality
Cerebrovascular disease (stroke) deaths peaked during the first wave of Covid19 but have been mostly near the bottom of the range of previous years, with a second peak in June.
Figure 21: Dementia mortality
Deaths with dementia as a cause have increased over the years. A peak in dementia deaths coincided with Covid19 but deaths have been in the normal range since then.
Figure 22: Diabetes mortality
A peak in diabetes deaths coincided with the peak in Covid19 infections and deaths, and was much higher than expected. At the end of June deaths were in the range of previous years.
Figure 23: Cancer mortality
Cancer deaths have increased over the years and 2020 remains within the expected range. You may note there is no winter increase in cancer mortality.
We are all going to die, nothing is surer. “Nobody knows the day or the hour”, but one thing is clear: we are more likely to die in winter than in summer.
Death by unnatural causes (suicide, accident, bushfire, disaster, even acute illness) can come to otherwise healthy people of any age. Death by natural causes is more predictable.
Those vulnerable to death are the elderly, very young babies, those with chronic illness (e.g. asthma, diabetes) and weakened immunity, and those with respiratory and circulatory illness.
Analysing mortality is made difficult because the sample population is always changing. Excess deaths in one month may be followed by further excess deaths in the following month, or because so many vulnerable people have already died, there will be fewer than expected deaths in the next month or months, or even the next couple of winters. Similarly, if fewer than expected deaths occur, there will be a larger cohort of the vulnerable in the following months, getting older and with probably poorer health. Population growth, aging, migration, improved vaccines, and public education programs all play a part as well.
In this analysis, I use mortality and population data from the Australian Bureau of Statistics (ABS), and temperature data from the Bureau of Meteorology (BOM), for Victoria, as it is a small and compact state which is subject to large temperature changes and also severe heat waves. Monthly mortality data are difficult to find, so this study is restricted to the period January 2002 to December 2011. A 10 year period is hardly sufficient for meaningful averages, however some useful insights can be found.
Mortality statistics are available by month, but population figures are by quarter, therefore I interpolated estimated monthly population figures based on three month growth.
Firstly, this plot shows the total deaths for every month from January 2002 to December 2011.
Fig. 1:
Note the seasonal spikes and dips. The apparent increase in deaths can be compared with Victoria’s population increase:
Fig.2:
By dividing the total deaths by the population in thousands we can calculate the death rate:
Fig. 3:
Note the mortality rate has decreased, and that, in spite of heatwaves, bushfires, and flu pandemics, 2009 had a lower death rate than 2008.
Because months have varying numbers of days, a better analysis can be made by calculating the Daily Death Rate for each month (by dividing each monthly rate by 31, 30, 29, or 28 days).
Fig. 4:
For the state of Victoria for the 10 years to 2011, on average more deaths occurred for each day in August than for any other month. The lowest Daily Death Rate was in February.
Now compare with monthly averages (2002 to 2011) for maximum and minimum temperatures:
Fig. 5:
The death rate peak lags July temperature by about a month. Cooler months (June to September) are deadlier than warmer (December to April).
The relationship with temperature can be shown with scatter plots:
Fig. 6:
Fig. 7:
Which merely reinforce that deaths are more likely in winter!
Now we look at the question of estimating how many deaths are likely in a given period, by multiplying the average daily death rate for each month by the number of days in each month and by the estimated total population for each month. By subtracting this figure from the actual number of deaths we get a mortality “anomaly”. The following graph shows this anomaly for each year:
Fig. 8:
And each month:
Fig. 9:
Note the peaks in the winters of 2002 and 2003, and also in the summer of 2008-2009. Note also that both graphs show that in spite of a killer heatwave, the Black Saturday bushfire, and the swine flu pandemic, deaths in 2009 were below what could be expected.
To put the anomaly for January 2009 into context, we can compare actual daily deaths per 1,000 population for all months from 2002 to 2011:
Fig. 10:
Note that the extreme figure for January 2009, while extremely high for January, is still below those of the lowest extremes of June, July, and August.
Perhaps higher mortality in the winter months is coincidence and due to some other factor than temperature- seasonal flu incidence for example. I now look at the month of August with the highest average mortality rate:
Fig. 11:
There is fairly decent correlation showing that for every degree warmer in minima, the August death toll will be around 150 less than expected.
February, with the lowest rate:
Fig. 12:
Even in summer, warmer minima mean fewer deaths.
In summer, do higher maxima cause more deaths?
Fig. 13:
Even including the 173 deaths in the Black Saturday bushfires in the 200 extra deaths for February 2009, there is no trend.
January, whose data include the 2009 heatwave:
Fig. 14:
A very small trend, but the 2009 heatwave outlier is obvious and skews the data. (Victorian health authorities say there were 374 excess deaths in the week to 1 February 2009).
Extreme heatwaves are indeed killers. Normal hot summers up to two degrees above average are not.
Conclusion:
Improved public health measures, influenza vaccines, and improved public awareness – plus warmer winters- have led to a decrease in the Victorian mortality rate in the period 2002-2011.
Extreme heatwaves are dangerous in Victoria and cause hundreds of extra deaths especially amongst the elderly (>75 years old). However, these are rare events. Severe and Extreme Heatwaves are newsworthy precisely because they are unusual.
Normal Victorian winters are even more dangerous with on average 17.5% more deaths in winter than summer every year, but because this is normal and expected, this regular annual spike in deaths is unremarkable and not newsworthy- much less regarded as a natural disaster. While 374 excess deaths in a week in a heatwave is shocking, even with these included, the highest January’s Daily Death Rate (in 2009) is below that of the lowest of any winter month.
Warmer minimum temperatures are associated with lower death rates at all times of the year, but especially in August in Victoria, where for every degree of extra warmth, about 150 fewer deaths can be expected. I hope, for the sake of those who are sick or elderly, that we have a warm winter this year.
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