Measuring Australia's excess mortality by remoteness areas during the COVID-19 pandemic until December 2023

Measuring Australia's excess deaths by remoteness during the COVID-19 pandemic until December 2023

Released

28/02/2025

Source

Provisional Mortality Statistics, Jan - Nov 2024

Key statistics

Overview

This article provides weekly and annual excess mortality estimates for deaths occurring in Australia by remoteness areas until the end of December 2023.

The ABS has produced several reports on excess mortality during the COVID-19 pandemic. These provide statistics for Australia and states and territories. The most recent report provided estimates until the end of 2023. This article provides extra geographic detail for the first time, presenting excess mortality by ‘remoteness areas’ (i.e. for major cities, inner regional, outer regional, remote, and very remote parts of Australia).

Excess mortality is 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. Excess mortality measures can account for deaths due to COVID-19, potentially misclassified or undiagnosed COVID-19 deaths, and other mortality that may be indirectly related to the pandemic (e.g. relating to social isolation or changed access to health care).

This data is designed to provide further insights to excess mortality estimates previously produced by the ABS so it uses the same methods as those earlier reports. It’s designed to answer the research question: 'How does the number of deaths which has occurred since the beginning of the COVID-19 pandemic (2020-2023) compare to the number of deaths expected had the pandemic not occurred?'. Please see the Interpreting Results section in the previous article for more information.

Key points:

For all remoteness areas, the highest excess mortality was in 2022. This ranged from 3.4% in outer regional Australia to 13.4% in very remote Australia.
Excess mortality in all remoteness areas more than halved in 2023 compared to 2022. In outer regional Australia there was negative excess mortality of 1.1% (meaning there were fewer deaths than expected). The highest excess mortality in 2023 occurred in major cities (5.2%).
All remoteness areas except remote Australia experienced negative excess mortality in 2020. Inner regional and outer regional Australia also experienced negative excess mortality in 2021. The highest excess mortality in 2021 occurred in remote Australia (4.6%).

The following table provides a summary of excess mortality estimates by remoteness area expressed as the percentage above expected mortality for the years 2020-2023. Excess mortality estimates for Australia are included as a reference point.

Excess mortality as a percentage above expected by remoteness area, 2020-23
	2020	2021	2022	2023
Australia	-3.1	1.6	11.7	5.1
Major Cities	-2.5	2.4	12.9	5.2
Inner Regional	-4.4	-0.3	8.6	3.6
Outer Regional	-5.3	-1.7	3.4	-1.1
Remote	0.2	4.6	11.5	4.2
Very Remote	-4.3	2.9	13.4	2.5

Remoteness areas in Australia

The Australian Statistical Geography Standard (ASGS) Remoteness Structure divides Australia into five classes of remoteness which are characterised by a measure of relative geographic access to services. These five classes are Major cities of Australia, Inner regional Australia, Outer regional Australia, Remote Australia and Very remote Australia. The map below illustrates the relative size and location of the different remoteness areas.

Over 70% of Australia's population live in major cities (see Regional population). Nearly 20% live in inner regional areas, and under 10% live in outer regional areas. Just over 1% of Australia's population are in remote Australia, and under 1% live in very remote Australia. As the remoteness area structure relates to access to services not every state and territory has all five classes of remoteness included. For example, the Northern Territory and Tasmania have no areas considered as a major city (a capital city differs from a major city) and the Australian Capital Territory has no areas considered remote and very remote.

Map of ASGS Edition 3 Remoteness Areas for Australia

Image

Description

Map detailing the five different Remoteness Area classes which make up the Remoteness Structure. The map shows areas shaded in light to dark green colours, to demonstrate Very Remote Australia, Remote Australia, Outer Regional Australia, Inner Regional Australia and Major Cities of Australia respectively.

All-cause mortality rates by remoteness areas

Health status can differ by remoteness areas. Geographic location can affect access to health services (see Rural and remote health, AIHW, 2024). The graph below shows that age-standardised mortality rates are higher in rural and remote areas. Mortality rates increase with increasing remoteness. This trend has been consistent over time. The mortality rate of those living in very remote areas has consistently been over 1.4 times higher than those living in major cities over the last decade.

Age standardised death rates by remoteness areas, Australia, 2013-2023
	Major cities	Inner regional	Outer regional	Remote	Very remote
2013	520.3	575.5	601.3	610.5	762.9
2014	524.7	584.5	592.9	636.6	758.5
2015	529.0	594.2	617.4	657.6	756.6
2016	506.5	583.1	609.8	632.2	811.4
2017	513.3	579.0	610.5	645.9	817.6
2018	484.8	548.3	585.3	609.1	793.6
2019	488.9	553.6	585.1	602.3	748.5
2020	477.7	535.1	568.5	611.9	726.6
2021	484.8	540.7	576.3	616.4	780.4
2022	526.8	578.5	597.9	636.5	830.2
2023	485.6	548.4	573.9	584.6	739.2

Age standardised death rates by remoteness areas, Australia, 2013-2023

["","Major cities","Inner regional","Outer regional","Remote","Very remote"]

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a. Age-standardised death rate (SDR). Death rate per 100,000 standard estimated resident population as at 30 June.
b. Remoteness classification is based on area of usual residence.

COVID-19 associated mortality rates by remoteness areas

COVID-19 associated mortality rates have varied across remoteness areas across the pandemic. The table below shows that for 2020 and 2021 age-standardised COVID-19 mortality rates were highest in major cities. During these years there were five deaths associated with the virus in remote and very remote areas (a mortality rate was not produced for remote areas in these years due to the very small number of deaths). In 2020, there were zero COVID-19 associated deaths in very remote Australia. This changed in 2022 when those in very remote areas recorded the highest COVID-19 mortality rates. In 2022 and 2023, the rates were highest in very remote Australia. In 2023 the trend of COVID-19 associated mortality is the same as the trend for all-cause mortality. The rates increase with increasing remoteness (so rates are highest in very remote areas and lowest in major cities).

Age standardised death rates from or with COVID-19 by remoteness areas, Australia, 2020-2023
	2020	2021	2022	2023
Major cities	3.6	5.8	39.0	16.2
Inner regional	0.3	1.1	32.3	16.6
Outer regional	np	np	31.1	16.9
Remote	np	np	34.5	19.9
Very remote	0	np	41.9	20.3

a. Age-standardised death rate (SDR). Death rate per 100,000 standard estimated resident population as at 30 June.
b. SDRs based on small numbers are volatile and unreliable. SDRs based on less than 20 deaths have not been published.
c. Remoteness classification is based on area of usual residence.
d. COVID-19 associated deaths (also called ‘deaths from or with COVID-19’) are any deaths where COVID-19 has directly caused or significantly contributed to death.

Measuring excess mortality

Across the world, health and statistical authorities have sought to measure excess mortality during the COVID-19 pandemic. Different methodologies have been applied, with the goal to predict an expected number of deaths for a given year. Choice of model and baseline can markedly affect estimates of expected (and therefore excess) mortality. Estimating the expected future seasonality for deaths can be a challenge in many models. The suitability of a model can depend on factors such as country context, data quality and collection methods.

The ABS has adopted aspects of a methodology used by New South Wales (NSW) Health, applying a cyclical linear regression with a robust estimation procedure to produce both an expected number of deaths and a range of expected deaths. The ABS has applied this model to estimate age specific death rates (ASDRs) for certain age groups, and converted the expected death rates into an expected number of deaths for each age group. The ABS then added these across age groups to obtain an expected count for the total population. Using ASDRs accounts for changes in population size and age composition. For more information, please see the Methodology section.

Interpreting results

Considerations for interpreting information in this report

Outputs from excess mortality estimates will differ depending on the calculation applied and the scope of the input data. When interpreting the results in this report the following factors must be taken into consideration.

This report highlights weeks where excess deaths are statistically significant. In any given period, even if no temporary health hazards influence the number of deaths (such as community transmission of influenza or COVID-19), there is some natural variation in patterns of mortality. While the actual number of deaths may be different from the expected number of deaths, it should fall within an expected range (for the statistics in this article, there is a 95% chance that the expected number of deaths would lie between the upper and lower bounds of the confidence intervals). When actual observations (counts of death) exceed the upper threshold or drop below the lower threshold this indicates a statistically significant change in the pattern of mortality. The expected range should be used in conjunction with the percentage of excess mortality.
A single week above threshold does not necessarily suggest statistically significant excess mortality. Prolonged periods (2 or more weeks) where counts are outside thresholds suggest more strongly that the numbers of deaths are above or below normal.
Data is reported by date of death occurrence. Remoteness area analysis includes all deaths that occurred by 31 December 2023 and registered by 31 October 2024. Data may change as additional registrations are received by the ABS. For the Australia level data, the scope is deaths that occurred by 31 December 2023 and were registered and received by the ABS by 31 March 2024. This is because Australia level data is used as a reference point only and matches previously published counts. It is expected that Australia level data would be close to complete and any additional deaths received would make a limited difference to high level counts and estimates. Please refer to the ‘Timeliness and completeness of the data’ section of Provisional Mortality Statistics for more information.
The number of deaths by remoteness areas will not add to the Australian total. This is because some deaths can’t be assigned a remoteness area, for example because not enough address information is supplied to the ABS to identify the remoteness area.
Reported deaths from or with COVID-19 are identified from death certificates or coroner reports as part of the death registration process. There may be some deaths where COVID-19 was a contributing factor but it was not recorded on the death certificate (for example, the medical practitioner may be unaware of a present or past infection). If COVID-19 is not recorded on the death certificate it is not included in COVID-19 death tabulations presented.
The number of deaths associated with COVID-19 is the combination of deaths attributed as being due to COVID-19 (the virus caused complications leading directly to death) and deaths where COVID-19 contributed to death (these are deaths where there was another pathway to death, but the virus severely impacted the health of the deceased).

Weekly all-cause mortality: Australia

The ABS has previously published excess mortality at the national level in Measuring Australia's excess mortality during the COVID-19 pandemic until December 2023). It is included again in this article as a reference point for excess mortality estimates for the remoteness areas.

Excess mortality for Australia in 2023 was estimated at 5.1% above expected. This is a decrease compared to 2022, when excess mortality was 11.7%.
COVID-19 associated deaths (as identified on death certificates) were a key contributor to excess mortality in Australia from late 2021 through to 2023. Excess mortality during this period corresponded with peaks in COVID-19 waves.
Deaths were significantly lower than expected from the week beginning 1 June to mid-July 2020, dropping below lower thresholds. Winter months are typically associated with higher mortality. These decreases provide insights into how public health measures put in place to manage the COVID-19 pandemic impacted mortality.

Excess mortality by year, Australia, 2020-23
	2020	2021	2022	2023
Expected	170,046	169,048	170,933	173,121
Observed	164,805	171,823	190,955	181,865
Excess	-5,241	2,775	20,022	8,744
% Excess	-3.1	1.6	11.7	5.1
Reported deaths from or with COVID-19	916	1,448	13,317	5,952

a. Data is provisional and subject to change.
b. Years are based on a sum of International Organization for Standardisation (ISO) weeks. Weeks start on Monday, and week 1 always contains the 4th of January. There are 53 weeks in 2020. There are 52 weeks in 2021, 2022 and 2023.
c. Reported deaths 'from' or 'with' COVID-19 are as recorded on the death certificate.
d. Includes all deaths (both doctor and coroner certified) that occurred by 31 December 2023 and were registered and received by the ABS by 31 March 2024.

Comparison of all-cause baseline and COVID-19 period deaths against regression, Australia, January 2020 - December 2023 (a)(b)(c)
Week ending	95% bounds	Expected	Actual	Actual w/o reported COVID-19
05-Jan-20	2764\|3092	2,928	2,928	2,928
12-Jan-20	2750\|3078	2,914	2,903	2,903
19-Jan-20	2737\|3065	2,901	2,915	2,915
26-Jan-20	2730\|3058	2,894	3,010	3,010
02-Feb-20	2730\|3058	2,894	2,911	2,911
09-Feb-20	2729\|3057	2,893	2,918	2,918
16-Feb-20	2735\|3063	2,899	3,031	3,031
23-Feb-20	2747\|3075	2,911	3,059	3,059
01-Mar-20	2760\|3088	2,924	3,091	3,090
08-Mar-20	2778\|3106	2,942	2,999	2,997
15-Mar-20	2799\|3127	2,963	2,977	2,975
22-Mar-20	2824\|3152	2,988	3,096	3,093
29-Mar-20	2850\|3178	3,014	3,144	3,132
05-Apr-20	2900\|3230	3,065	3,218	3,195
12-Apr-20	2930\|3260	3,095	3,140	3,116
19-Apr-20	2963\|3293	3,128	3,084	3,073
26-Apr-20	2999\|3329	3,164	3,047	3,035
03-May-20	3035\|3365	3,200	3,032	3,018
10-May-20	3068\|3398	3,233	3,162	3,159
17-May-20	3105\|3435	3,270	3,154	3,150
24-May-20	3137\|3467	3,302	3,214	3,210
31-May-20	3169\|3499	3,334	3,178	3,178
07-Jun-20	3200\|3530	3,365	3,113	3,112
14-Jun-20	3228\|3558	3,393	3,129	3,129
21-Jun-20	3252\|3582	3,417	3,065	3,063
28-Jun-20	3275\|3605	3,440	3,058	3,057
05-Jul-20	3319\|3651	3,485	3,221	3,219
12-Jul-20	3332\|3664	3,498	3,201	3,197
19-Jul-20	3344\|3676	3,510	3,206	3,188
26-Jul-20	3351\|3683	3,517	3,334	3,284
02-Aug-20	3352\|3684	3,518	3,353	3,251
09-Aug-20	3352\|3684	3,518	3,400	3,292
16-Aug-20	3345\|3677	3,511	3,479	3,336
23-Aug-20	3337\|3669	3,503	3,312	3,206
30-Aug-20	3323\|3655	3,489	3,287	3,204
06-Sep-20	3303\|3635	3,469	3,296	3,241
13-Sep-20	3282\|3614	3,448	3,239	3,197
20-Sep-20	3256\|3588	3,422	3,103	3,073
27-Sep-20	3227\|3559	3,393	3,146	3,125
04-Oct-20	3224\|3560	3,392	3,190	3,177
11-Oct-20	3192\|3528	3,360	3,045	3,040
18-Oct-20	3155\|3491	3,323	3,007	3,004
25-Oct-20	3119\|3455	3,287	2,967	2,966
01-Nov-20	3082\|3418	3,250	3,038	3,037
08-Nov-20	3045\|3381	3,213	3,035	3,032
15-Nov-20	3006\|3342	3,174	3,136	3,134
22-Nov-20	2970\|3306	3,138	3,045	3,044
29-Nov-20	2934\|3270	3,102	2,960	2,958
06-Dec-20	2901\|3237	3,069	3,112	3,112
13-Dec-20	2869\|3205	3,037	3,008	3,008
20-Dec-20	2841\|3177	3,009	3,048	3,048
27-Dec-20	2813\|3149	2,981	3,069	3,068
03-Jan-21	2791\|3127	2,959	2,992	2,991
10-Jan-21	2794\|3134	2,964	3,032	3,032
17-Jan-21	2779\|3119	2,949	2,951	2,950
24-Jan-21	2766\|3106	2,936	3,150	3,150
31-Jan-21	2761\|3101	2,931	2,946	2,946
07-Feb-21	2758\|3098	2,928	3,073	3,072
14-Feb-21	2761\|3101	2,931	2,966	2,966
21-Feb-21	2769\|3109	2,939	2,939	2,939
28-Feb-21	2778\|3118	2,948	3,050	3,050
07-Mar-21	2796\|3136	2,966	3,072	3,072
14-Mar-21	2813\|3153	2,983	3,118	3,117
21-Mar-21	2837\|3177	3,007	3,090	3,090
28-Mar-21	2864\|3204	3,034	3,044	3,044
04-Apr-21	2893\|3231	3,062	3,092	3,091
11-Apr-21	2941\|3281	3,111	2,959	2,959
18-Apr-21	2973\|3313	3,143	3,260	3,259
25-Apr-21	3010\|3350	3,180	3,248	3,248
02-May-21	3046\|3386	3,216	3,276	3,276
09-May-21	3084\|3424	3,254	3,370	3,370
16-May-21	3119\|3459	3,289	3,371	3,371
23-May-21	3156\|3496	3,326	3,363	3,363
30-May-21	3191\|3531	3,361	3,518	3,518
06-Jun-21	3226\|3566	3,396	3,384	3,384
13-Jun-21	3256\|3596	3,426	3,568	3,568
20-Jun-21	3284\|3624	3,454	3,495	3,495
27-Jun-21	3309\|3649	3,479	3,458	3,458
04-Jul-21	3332\|3672	3,502	3,468	3,468
11-Jul-21	3370\|3714	3,542	3,547	3,545
18-Jul-21	3384\|3728	3,556	3,602	3,599
25-Jul-21	3396\|3740	3,568	3,627	3,623
01-Aug-21	3398\|3742	3,570	3,670	3,664
08-Aug-21	3398\|3742	3,570	3,478	3,463
15-Aug-21	3396\|3740	3,568	3,444	3,418
22-Aug-21	3387\|3731	3,559	3,509	3,486
29-Aug-21	3373\|3717	3,545	3,423	3,403
05-Sep-21	3354\|3698	3,526	3,497	3,449
12-Sep-21	3333\|3677	3,505	3,421	3,365
19-Sep-21	3307\|3651	3,479	3,496	3,422
26-Sep-21	3278\|3622	3,450	3,370	3,281
03-Oct-21	3248\|3592	3,420	3,535	3,426
10-Oct-21	3241\|3587	3,414	3,410	3,299
17-Oct-21	3205\|3551	3,378	3,360	3,258
24-Oct-21	3167\|3513	3,340	3,363	3,266
31-Oct-21	3126\|3472	3,299	3,339	3,234
07-Nov-21	3088\|3434	3,261	3,313	3,224
14-Nov-21	3047\|3395	3,221	3,190	3,125
21-Nov-21	3007\|3355	3,181	3,342	3,270
28-Nov-21	2969\|3317	3,143	3,263	3,218
05-Dec-21	2935\|3283	3,109	3,263	3,217
12-Dec-21	2900\|3248	3,074	3,198	3,162
19-Dec-21	2870\|3218	3,044	3,277	3,231
26-Dec-21	2843\|3191	3,017	3,391	3,327
02-Jan-22	2820\|3168	2,994	3,234	3,144
09-Jan-22	2821\|3171	2,996	3,336	3,141
16-Jan-22	2803\|3153	2,978	3,741	3,330
23-Jan-22	2792\|3142	2,967	3,895	3,306
30-Jan-22	2785\|3135	2,960	3,790	3,209
06-Feb-22	2784\|3134	2,959	3,749	3,267
13-Feb-22	2785\|3135	2,960	3,571	3,216
20-Feb-22	2792\|3142	2,967	3,420	3,163
27-Feb-22	2806\|3156	2,981	3,414	3,221
06-Mar-22	2820\|3170	2,995	3,384	3,260
13-Mar-22	2841\|3191	3,016	3,215	3,105
20-Mar-22	2865\|3215	3,040	3,356	3,237
27-Mar-22	2892\|3242	3,067	3,355	3,222
03-Apr-22	2922\|3272	3,097	3,421	3,260
10-Apr-22	2970\|3322	3,146	3,451	3,285
17-Apr-22	3004\|3356	3,180	3,381	3,173
24-Apr-22	3041\|3393	3,217	3,486	3,215
01-May-22	3080\|3432	3,256	3,501	3,247
08-May-22	3117\|3469	3,293	3,682	3,434
15-May-22	3154\|3506	3,330	3,801	3,520
22-May-22	3193\|3545	3,369	3,662	3,374
29-May-22	3229\|3581	3,405	3,783	3,487
05-Jun-22	3264\|3616	3,440	3,927	3,660
12-Jun-22	3295\|3647	3,471	4,045	3,764
19-Jun-22	3324\|3676	3,500	4,142	3,868
26-Jun-22	3348\|3700	3,524	4,009	3,737
03-Jul-22	3371\|3723	3,547	3,919	3,634
10-Jul-22	3407\|3761	3,584	4,127	3,800
17-Jul-22	3422\|3776	3,599	4,131	3,735
24-Jul-22	3430\|3784	3,607	4,156	3,671
31-Jul-22	3436\|3790	3,613	4,169	3,623
07-Aug-22	3437\|3791	3,614	4,218	3,742
14-Aug-22	3431\|3785	3,608	4,129	3,704
21-Aug-22	3422\|3776	3,599	3,944	3,619
28-Aug-22	3409\|3763	3,586	3,894	3,636
04-Sep-22	3392\|3746	3,569	3,737	3,532
11-Sep-22	3368\|3722	3,545	3,787	3,613
18-Sep-22	3343\|3697	3,520	3,703	3,555
25-Sep-22	3312\|3666	3,489	3,688	3,565
02-Oct-22	3280\|3634	3,457	3,424	3,324
09-Oct-22	3271\|3629	3,450	3,512	3,418
16-Oct-22	3236\|3594	3,415	3,475	3,403
23-Oct-22	3195\|3553	3,374	3,548	3,467
30-Oct-22	3156\|3514	3,335	3,323	3,255
06-Nov-22	3115\|3473	3,294	3,397	3,286
13-Nov-22	3074\|3432	3,253	3,509	3,408
20-Nov-22	3035\|3393	3,214	3,461	3,313
27-Nov-22	2995\|3353	3,174	3,509	3,344
04-Dec-22	2958\|3316	3,137	3,451	3,230
11-Dec-22	2924\|3282	3,103	3,608	3,356
18-Dec-22	2891\|3249	3,070	3,564	3,299
25-Dec-22	2865\|3223	3,044	3,605	3,294
01-Jan-23	2840\|3198	3,019	3,450	3,111
08-Jan-23	2840\|3202	3,021	3,490	3,177
15-Jan-23	2823\|3185	3,004	3,282	3,043
22-Jan-23	2813\|3175	2,994	3,325	3,151
29-Jan-23	2806\|3168	2,987	3,223	3,070
05-Feb-23	2803\|3165	2,984	3,366	3,260
12-Feb-23	2806\|3168	2,987	3,208	3,124
19-Feb-23	2813\|3175	2,994	3,294	3,211
26-Feb-23	2826\|3188	3,007	3,234	3,149
05-Mar-23	2842\|3204	3,023	3,296	3,218
12-Mar-23	2862\|3224	3,043	3,374	3,302
19-Mar-23	2888\|3250	3,069	3,411	3,320
26-Mar-23	2916\|3278	3,097	3,320	3,225
02-Apr-23	2946\|3308	3,127	3,298	3,200
09-Apr-23	2997\|3361	3,179	3,275	3,161
16-Apr-23	3034\|3398	3,216	3,474	3,344
23-Apr-23	3074\|3438	3,256	3,530	3,372
30-Apr-23	3110\|3474	3,292	3,498	3,349
07-May-23	3151\|3515	3,333	3,529	3,360
14-May-23	3190\|3554	3,372	3,768	3,584
21-May-23	3227\|3591	3,409	3,804	3,623
28-May-23	3264\|3628	3,446	3,830	3,638
04-Jun-23	3299\|3663	3,481	3,935	3,713
11-Jun-23	3333\|3697	3,515	3,709	3,484
18-Jun-23	3363\|3727	3,545	3,629	3,454
25-Jun-23	3388\|3752	3,570	3,855	3,709
02-Jul-23	3412\|3776	3,594	3,755	3,605
09-Jul-23	3458\|3824	3,641	3,823	3,696
16-Jul-23	3472\|3838	3,655	3,715	3,605
23-Jul-23	3483\|3849	3,666	3,734	3,646
30-Jul-23	3487\|3853	3,670	3,745	3,690
06-Aug-23	3487\|3853	3,670	3,640	3,570
13-Aug-23	3483\|3849	3,666	3,635	3,578
20-Aug-23	3474\|3840	3,657	3,688	3,632
27-Aug-23	3458\|3824	3,641	3,537	3,492
03-Sep-23	3439\|3805	3,622	3,509	3,470
10-Sep-23	3417\|3783	3,600	3,463	3,412
17-Sep-23	3391\|3757	3,574	3,550	3,510
24-Sep-23	3358\|3724	3,541	3,373	3,321
01-Oct-23	3324\|3690	3,507	3,449	3,401
08-Oct-23	3319\|3689	3,504	3,350	3,307
15-Oct-23	3280\|3650	3,465	3,535	3,481
22-Oct-23	3240\|3610	3,425	3,322	3,263
29-Oct-23	3198\|3568	3,383	3,315	3,248
05-Nov-23	3154\|3524	3,339	3,438	3,353
12-Nov-23	3115\|3485	3,300	3,514	3,401
19-Nov-23	3072\|3442	3,257	3,520	3,389
26-Nov-23	3033\|3403	3,218	3,378	3,249
03-Dec-23	2994\|3364	3,179	3,441	3,327
10-Dec-23	2958\|3330	3,144	3,404	3,271
17-Dec-23	2926\|3298	3,112	3,355	3,248
24-Dec-23	2897\|3269	3,083	3,402	3,301
31-Dec-23	2871\|3243	3,057	3,318	3,206

Comparison of all-cause baseline and COVID-19 period deaths against regression, Australia, January 2020 - December 2023 (a)(b)(c)

["Week ending","95% bounds","Expected","Actual","Actual w\/o reported COVID-19"]

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[]

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a. Data is provisional and will change as additional death registrations are received.
b. The baseline period generating the regression model is from 2013 to 2019. The prediction window begins in 2020.
c. Includes all deaths (both doctor and coroner certified) that occurred by 31 December 2023 and were registered and received by the ABS by 31 March 2024.

Weekly all-cause mortality: Major cities

Excess mortality for major cities was highest in 2022, at 12.9% higher than expected. This compares to 11.7% excess mortality for Australia.
Excess mortality in 2023 was 5.2% higher than expected. The number of excess deaths decreased by almost 60% when compared to 2022.
There have been several prolonged periods where mortality in major cities has been higher than the expected range. These include December 2021 to September 2022, November 2022 to March 2023, May to June 2023 and November to December 2023.
Mortality was 2.5% lower than expected in 2020, with prolonged decreases occurring between June and October of that year.
COVID-19 associated mortality as recorded on death certificates has been a significant contributor to excess mortality in major cities each year. The virus accounted for just over two-thirds of excess mortality in 2022 and 2023.

Excess mortality by year, Major cities, 2020-23
	2020	2021	2022	2023
Expected	110,920	110,116	111,382	112,887
Observed	108,162	112,746	125,718	118,813
Excess	-2,758	2,630	14,336	5,926
% Excess	-2.5	2.4	12.9	5.2
Reported deaths from or with COVID-19	869	1,346	9,640	4,089

Comparison of all-cause baseline and COVID-19 period deaths against regression, Major cities, December 2019 - December 2023 (a)(b)(c)
Week ending	95% bounds	Expected	Actual	Actual w/o reported COVID-19
05-Jan-20	1769\|2037	1,903	1,865	1,865
12-Jan-20	1760\|2028	1,894	1,881	1,881
19-Jan-20	1755\|2023	1,889	1,920	1,920
26-Jan-20	1751\|2019	1,885	1,951	1,951
02-Feb-20	1752\|2020	1,886	1,873	1,873
09-Feb-20	1754\|2022	1,888	1,857	1,857
16-Feb-20	1762\|2030	1,896	1,957	1,957
23-Feb-20	1770\|2038	1,904	1,980	1,980
01-Mar-20	1780\|2048	1,914	2,010	2,009
08-Mar-20	1794\|2062	1,928	1,970	1,968
15-Mar-20	1808\|2076	1,942	1,935	1,933
22-Mar-20	1826\|2094	1,960	2,074	2,072
29-Mar-20	1844\|2112	1,978	2,106	2,096
05-Apr-20	1879\|2149	2,014	2,147	2,135
12-Apr-20	1900\|2170	2,035	2,039	2,021
19-Apr-20	1921\|2191	2,056	2,086	2,080
26-Apr-20	1944\|2214	2,079	2,039	2,031
03-May-20	1966\|2236	2,101	1,949	1,937
10-May-20	1990\|2260	2,125	2,070	2,067
17-May-20	2011\|2281	2,146	2,021	2,019
24-May-20	2034\|2304	2,169	2,080	2,077
31-May-20	2054\|2324	2,189	2,100	2,100
07-Jun-20	2072\|2342	2,207	2,051	2,050
14-Jun-20	2089\|2359	2,224	2,031	2,031
21-Jun-20	2105\|2375	2,240	2,024	2,024
28-Jun-20	2119\|2389	2,254	2,058	2,057
05-Jul-20	2142\|2414	2,278	2,091	2,090
12-Jul-20	2151\|2423	2,287	2,111	2,107
19-Jul-20	2159\|2431	2,295	2,074	2,056
26-Jul-20	2161\|2433	2,297	2,233	2,185
02-Aug-20	2161\|2433	2,297	2,235	2,134
09-Aug-20	2157\|2429	2,293	2,287	2,180
16-Aug-20	2152\|2424	2,288	2,317	2,175
23-Aug-20	2144\|2416	2,280	2,187	2,081
30-Aug-20	2133\|2405	2,269	2,189	2,106
06-Sep-20	2121\|2393	2,257	2,190	2,137
13-Sep-20	2106\|2376	2,241	2,140	2,099
20-Sep-20	2089\|2359	2,224	2,065	2,036
27-Sep-20	2069\|2339	2,204	2,057	2,037
04-Oct-20	2063\|2335	2,199	2,125	2,112
11-Oct-20	2037\|2309	2,173	1,930	1,925
18-Oct-20	2015\|2287	2,151	1,989	1,986
25-Oct-20	1991\|2263	2,127	1,964	1,963
01-Nov-20	1969\|2241	2,105	1,979	1,978
08-Nov-20	1943\|2215	2,079	2,006	2,003
15-Nov-20	1921\|2193	2,057	2,075	2,073
22-Nov-20	1897\|2169	2,033	1,994	1,993
29-Nov-20	1875\|2147	2,011	1,918	1,916
06-Dec-20	1855\|2127	1,991	2,087	2,087
13-Dec-20	1834\|2106	1,970	1,920	1,920
20-Dec-20	1815\|2087	1,951	2,018	2,018
27-Dec-20	1799\|2073	1,936	1,951	1,950
03-Jan-21	1784\|2058	1,921	1,956	1,955
10-Jan-21	1789\|2063	1,926	1,941	1,941
17-Jan-21	1778\|2054	1,916	1,939	1,938
24-Jan-21	1774\|2050	1,912	2,103	2,103
31-Jan-21	1770\|2046	1,908	1,894	1,894
07-Feb-21	1771\|2047	1,909	1,969	1,968
14-Feb-21	1775\|2051	1,913	1,955	1,955
21-Feb-21	1780\|2056	1,918	1,916	1,916
28-Feb-21	1790\|2064	1,927	1,986	1,986
07-Mar-21	1802\|2076	1,939	2,018	2,018
14-Mar-21	1816\|2090	1,953	2,006	2,005
21-Mar-21	1832\|2106	1,969	2,042	2,042
28-Mar-21	1851\|2125	1,988	1,960	1,960
04-Apr-21	1871\|2145	2,008	2,062	2,062
11-Apr-21	1904\|2180	2,042	1,951	1,951
18-Apr-21	1926\|2202	2,064	2,149	2,148
25-Apr-21	1950\|2226	2,088	2,136	2,136
02-May-21	1974\|2250	2,112	2,146	2,146
09-May-21	1997\|2273	2,135	2,195	2,195
16-May-21	2021\|2297	2,159	2,118	2,118
23-May-21	2044\|2320	2,182	2,225	2,225
30-May-21	2068\|2344	2,206	2,290	2,290
06-Jun-21	2088\|2364	2,226	2,194	2,194
13-Jun-21	2105\|2381	2,243	2,326	2,326
20-Jun-21	2122\|2398	2,260	2,349	2,349
27-Jun-21	2139\|2415	2,277	2,281	2,281
04-Jul-21	2151\|2427	2,289	2,333	2,333
11-Jul-21	2174\|2452	2,313	2,288	2,286
18-Jul-21	2181\|2459	2,320	2,349	2,346
25-Jul-21	2185\|2463	2,324	2,388	2,384
01-Aug-21	2185\|2463	2,324	2,427	2,421
08-Aug-21	2183\|2461	2,322	2,347	2,332
15-Aug-21	2181\|2459	2,320	2,264	2,239
22-Aug-21	2175\|2453	2,314	2,315	2,292
29-Aug-21	2163\|2441	2,302	2,196	2,179
05-Sep-21	2153\|2431	2,292	2,316	2,270
12-Sep-21	2135\|2413	2,274	2,228	2,176
19-Sep-21	2119\|2397	2,258	2,275	2,205
26-Sep-21	2098\|2376	2,237	2,276	2,192
03-Oct-21	2077\|2355	2,216	2,359	2,252
10-Oct-21	2066\|2346	2,206	2,257	2,149
17-Oct-21	2041\|2321	2,181	2,214	2,115
24-Oct-21	2017\|2297	2,157	2,222	2,134
31-Oct-21	1992\|2272	2,132	2,199	2,102
07-Nov-21	1967\|2247	2,107	2,148	2,072
14-Nov-21	1942\|2222	2,082	2,113	2,052
21-Nov-21	1917\|2197	2,057	2,228	2,160
28-Nov-21	1894\|2174	2,034	2,116	2,074
05-Dec-21	1872\|2152	2,012	2,163	2,123
12-Dec-21	1850\|2130	1,990	2,080	2,048
19-Dec-21	1832\|2112	1,972	2,136	2,096
26-Dec-21	1817\|2097	1,957	2,211	2,153
02-Jan-22	1804\|2084	1,944	2,147	2,068
09-Jan-22	1802\|2084	1,943	2,247	2,069
16-Jan-22	1792\|2074	1,933	2,605	2,232
23-Jan-22	1787\|2069	1,928	2,702	2,184
30-Jan-22	1785\|2067	1,926	2,532	2,039
06-Feb-22	1786\|2068	1,927	2,519	2,116
13-Feb-22	1790\|2072	1,931	2,398	2,116
20-Feb-22	1795\|2077	1,936	2,212	2,005
27-Feb-22	1804\|2086	1,945	2,226	2,090
06-Mar-22	1817\|2099	1,958	2,188	2,100
13-Mar-22	1833\|2115	1,974	2,075	1,992
20-Mar-22	1847\|2129	1,988	2,197	2,113
27-Mar-22	1867\|2149	2,008	2,228	2,125
03-Apr-22	1889\|2171	2,030	2,299	2,170
10-Apr-22	1921\|2205	2,063	2,247	2,123
17-Apr-22	1945\|2229	2,087	2,258	2,107
24-Apr-22	1967\|2251	2,109	2,344	2,136
01-May-22	1992\|2276	2,134	2,327	2,145
08-May-22	2018\|2302	2,160	2,434	2,249
15-May-22	2040\|2324	2,182	2,496	2,295
22-May-22	2066\|2350	2,208	2,415	2,209
29-May-22	2089\|2373	2,231	2,514	2,307
05-Jun-22	2109\|2393	2,251	2,602	2,416
12-Jun-22	2129\|2413	2,271	2,704	2,505
19-Jun-22	2147\|2431	2,289	2,751	2,558
26-Jun-22	2161\|2445	2,303	2,632	2,443
03-Jul-22	2174\|2458	2,316	2,576	2,379
10-Jul-22	2200\|2486	2,343	2,728	2,502
17-Jul-22	2208\|2494	2,351	2,630	2,379
24-Jul-22	2212\|2498	2,355	2,663	2,350
31-Jul-22	2213\|2499	2,356	2,740	2,387
07-Aug-22	2212\|2498	2,355	2,810	2,497
14-Aug-22	2207\|2493	2,350	2,737	2,464
21-Aug-22	2199\|2485	2,342	2,600	2,388
28-Aug-22	2189\|2475	2,332	2,549	2,384
04-Sep-22	2176\|2462	2,319	2,452	2,307
11-Sep-22	2160\|2446	2,303	2,481	2,356
18-Sep-22	2141\|2427	2,284	2,427	2,337
25-Sep-22	2120\|2406	2,263	2,423	2,336
02-Oct-22	2101\|2387	2,244	2,219	2,152
09-Oct-22	2092\|2380	2,236	2,297	2,238
16-Oct-22	2066\|2354	2,210	2,210	2,161
23-Oct-22	2039\|2327	2,183	2,315	2,252
30-Oct-22	2014\|2302	2,158	2,179	2,139
06-Nov-22	1987\|2275	2,131	2,184	2,108
13-Nov-22	1964\|2252	2,108	2,327	2,262
20-Nov-22	1936\|2224	2,080	2,234	2,136
27-Nov-22	1914\|2202	2,058	2,304	2,198
04-Dec-22	1891\|2179	2,035	2,246	2,086
11-Dec-22	1871\|2159	2,015	2,301	2,129
18-Dec-22	1851\|2139	1,995	2,376	2,200
25-Dec-22	1836\|2124	1,980	2,333	2,117
01-Jan-23	1821\|2109	1,965	2,225	1,990
08-Jan-23	1819\|2109	1,964	2,279	2,066
15-Jan-23	1812\|2102	1,957	2,130	1,972
22-Jan-23	1807\|2097	1,952	2,187	2,067
29-Jan-23	1804\|2094	1,949	2,105	2,000
05-Feb-23	1805\|2095	1,950	2,196	2,124
12-Feb-23	1808\|2098	1,953	2,080	2,020
19-Feb-23	1815\|2105	1,960	2,155	2,098
26-Feb-23	1824\|2114	1,969	2,125	2,068
05-Mar-23	1837\|2127	1,982	2,127	2,080
12-Mar-23	1852\|2142	1,997	2,225	2,179
19-Mar-23	1869\|2159	2,014	2,221	2,158
26-Mar-23	1888\|2178	2,033	2,163	2,102
02-Apr-23	1908\|2198	2,053	2,144	2,086
09-Apr-23	1945\|2237	2,091	2,104	2,034
16-Apr-23	1968\|2260	2,114	2,287	2,188
23-Apr-23	1992\|2284	2,138	2,300	2,195
30-Apr-23	2017\|2309	2,163	2,273	2,170
07-May-23	2044\|2334	2,189	2,329	2,206
14-May-23	2069\|2359	2,214	2,498	2,369
21-May-23	2093\|2383	2,238	2,493	2,369
28-May-23	2117\|2407	2,262	2,541	2,412
04-Jun-23	2138\|2428	2,283	2,579	2,425
11-Jun-23	2160\|2450	2,305	2,438	2,284
18-Jun-23	2176\|2468	2,322	2,358	2,234
25-Jun-23	2193\|2485	2,339	2,488	2,393
02-Jul-23	2204\|2496	2,350	2,422	2,323
09-Jul-23	2230\|2524	2,377	2,537	2,446
16-Jul-23	2238\|2532	2,385	2,458	2,383
23-Jul-23	2243\|2537	2,390	2,446	2,387
30-Jul-23	2244\|2538	2,391	2,447	2,407
06-Aug-23	2245\|2539	2,392	2,372	2,321
13-Aug-23	2238\|2532	2,385	2,363	2,332
20-Aug-23	2230\|2524	2,377	2,386	2,346
27-Aug-23	2218\|2512	2,365	2,355	2,321
03-Sep-23	2205\|2499	2,352	2,323	2,296
10-Sep-23	2188\|2482	2,335	2,262	2,223
17-Sep-23	2172\|2464	2,318	2,342	2,307
24-Sep-23	2151\|2443	2,297	2,135	2,099
01-Oct-23	2128\|2420	2,274	2,242	2,205
08-Oct-23	2119\|2413	2,266	2,160	2,131
15-Oct-23	2094\|2388	2,241	2,334	2,291
22-Oct-23	2067\|2361	2,214	2,209	2,167
29-Oct-23	2041\|2335	2,188	2,126	2,078
05-Nov-23	2011\|2307	2,159	2,253	2,199
12-Nov-23	1987\|2283	2,135	2,254	2,182
19-Nov-23	1961\|2257	2,109	2,312	2,234
26-Nov-23	1935\|2231	2,083	2,212	2,118
03-Dec-23	1913\|2209	2,061	2,252	2,170
10-Dec-23	1893\|2189	2,041	2,224	2,130
17-Dec-23	1873\|2169	2,021	2,155	2,077
24-Dec-23	1854\|2150	2,002	2,240	2,165
31-Dec-23	1840\|2136	1,988	2,167	2,087

Comparison of all-cause baseline and COVID-19 period deaths against regression, Major cities, December 2019 - December 2023 (a)(b)(c)

["Week ending","95% bounds","Expected","Actual","Actual w\/o reported COVID-19"]

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Weekly all-cause mortality: Inner regional

Excess mortality for inner regional areas was highest in 2022 when mortality was 8.6% higher than expected. This is lower than the national excess mortality estimate (11.7%).
In 2023 excess mortality was estimated at 3.6% above expected. The number of excess deaths decreased by almost 60% when compared to 2022.
There have been several prolonged periods where mortality in inner regional Australia has been higher than the expected range, though these have been fewer and of shorter duration than those in major cities. These include January to March 2022, May to August 2022, and November 2022 to January 2023.
Mortality was mostly lower than expected in inner regional areas in both 2020 and 2021.
COVID-19 associated mortality as recorded on death certificates has been a significant contributor to excess mortality in inner regional areas since 2022. The virus accounted for over 70% of excess mortality in 2022 and over 90% in 2023.
Peaks in excess mortality corresponded with periods where higher numbers of deaths associated with COVID-19 were occurring in inner regional areas.

Excess mortality by year, Inner regional, 2020-23
	2020	2021	2022	2023
Expected	38,765	38,940	39,753	40,363
Observed	37,070	38,842	43,165	41,804
Excess	-1,695	-98	3,412	1,441
% Excess	-4.4	-0.3	8.6	3.6
Reported deaths from or with COVID-19	23	80	2,518	1,346

Comparison of all-cause baseline and COVID-19 period deaths against regression, Inner regional, December 2019 - December 2023 (a)(b)(c)
Week ending	95% bounds	Expected	Actual	Actual w/o reported COVID-19
05-Jan-20	602\|726	664	675	675
12-Jan-20	598\|722	660	682	682
19-Jan-20	596\|720	658	611	611
26-Jan-20	593\|717	655	665	665
02-Feb-20	592\|716	654	628	628
09-Feb-20	592\|716	654	702	702
16-Feb-20	592\|716	654	675	675
23-Feb-20	594\|718	656	701	701
01-Mar-20	596\|720	658	706	706
08-Mar-20	599\|723	661	682	682
15-Mar-20	605\|729	667	657	657
22-Mar-20	609\|733	671	656	655
29-Mar-20	617\|741	679	663	661
05-Apr-20	627\|753	690	709	700
12-Apr-20	634\|760	697	744	743
19-Apr-20	643\|769	706	684	683
26-Apr-20	651\|777	714	656	656
03-May-20	660\|786	723	700	700
10-May-20	667\|793	730	701	701
17-May-20	676\|802	739	776	775
24-May-20	684\|810	747	749	749
31-May-20	692\|818	755	682	682
07-Jun-20	699\|825	762	704	704
14-Jun-20	705\|831	768	724	724
21-Jun-20	715\|841	778	673	673
28-Jun-20	720\|846	783	679	679
05-Jul-20	731\|857	794	719	718
12-Jul-20	737\|863	800	713	713
19-Jul-20	738\|864	801	757	757
26-Jul-20	742\|868	805	740	739
02-Aug-20	743\|869	806	729	729
09-Aug-20	743\|869	806	731	730
16-Aug-20	742\|868	805	745	744
23-Aug-20	742\|868	805	762	762
30-Aug-20	738\|864	801	746	746
06-Sep-20	735\|861	798	710	708
13-Sep-20	731\|857	794	714	713
20-Sep-20	725\|851	788	686	685
27-Sep-20	720\|846	783	724	724
04-Oct-20	717\|845	781	705	705
11-Oct-20	710\|838	774	725	725
18-Oct-20	702\|830	766	663	663
25-Oct-20	695\|823	759	683	683
01-Nov-20	685\|813	749	699	699
08-Nov-20	677\|805	741	686	686
15-Nov-20	667\|795	731	686	686
22-Nov-20	660\|788	724	697	697
29-Nov-20	651\|779	715	655	655
06-Dec-20	641\|769	705	668	668
13-Dec-20	634\|762	698	717	717
20-Dec-20	628\|756	692	687	687
27-Dec-20	619\|747	683	749	749
03-Jan-21	614\|742	678	690	690
10-Jan-21	613\|741	677	691	691
17-Jan-21	610\|738	674	663	663
24-Jan-21	608\|736	672	678	678
31-Jan-21	605\|733	669	655	655
07-Feb-21	603\|731	667	725	725
14-Feb-21	603\|731	667	655	655
21-Feb-21	604\|732	668	675	675
28-Feb-21	606\|734	670	707	707
07-Mar-21	609\|737	673	706	706
14-Mar-21	613\|741	677	758	758
21-Mar-21	619\|747	683	705	705
28-Mar-21	625\|753	689	714	714
04-Apr-21	631\|759	695	689	689
11-Apr-21	644\|774	709	665	665
18-Apr-21	651\|781	716	755	755
25-Apr-21	659\|789	724	735	735
02-May-21	668\|798	733	761	761
09-May-21	678\|808	743	755	755
16-May-21	687\|817	752	818	818
23-May-21	696\|826	761	761	761
30-May-21	704\|834	769	799	799
06-Jun-21	712\|842	777	744	744
13-Jun-21	721\|851	786	838	838
20-Jun-21	729\|859	794	759	759
27-Jun-21	735\|865	800	776	776
04-Jul-21	740\|870	805	724	724
11-Jul-21	753\|883	818	849	849
18-Jul-21	756\|886	821	828	828
25-Jul-21	760\|890	825	817	817
01-Aug-21	762\|892	827	841	841
08-Aug-21	762\|892	827	723	723
15-Aug-21	762\|892	827	797	796
22-Aug-21	761\|891	826	765	765
29-Aug-21	760\|890	825	795	793
05-Sep-21	754\|884	819	790	789
12-Sep-21	750\|880	815	786	783
19-Sep-21	745\|875	810	798	793
26-Sep-21	739\|869	804	732	727
03-Oct-21	732\|862	797	783	781
10-Oct-21	729\|861	795	741	739
17-Oct-21	721\|853	787	764	762
24-Oct-21	713\|845	779	736	732
31-Oct-21	703\|835	769	780	773
07-Nov-21	694\|826	760	778	765
14-Nov-21	685\|817	751	663	659
21-Nov-21	674\|806	740	769	765
28-Nov-21	665\|797	731	754	753
05-Dec-21	658\|790	724	733	729
12-Dec-21	648\|780	714	728	725
19-Dec-21	640\|772	706	720	715
26-Dec-21	634\|766	700	772	766
02-Jan-22	627\|759	693	689	683
09-Jan-22	627\|761	694	754	741
16-Jan-22	621\|755	688	766	738
23-Jan-22	617\|751	684	785	732
30-Jan-22	616\|750	683	844	778
06-Feb-22	615\|749	682	800	741
13-Feb-22	614\|748	681	758	711
20-Feb-22	615\|749	682	790	762
27-Feb-22	618\|752	685	780	743
06-Mar-22	621\|755	688	755	738
13-Mar-22	626\|760	693	741	730
20-Mar-22	631\|765	698	769	744
27-Mar-22	638\|770	704	721	707
03-Apr-22	644\|776	710	741	724
10-Apr-22	656\|790	723	773	745
17-Apr-22	665\|799	732	752	718
24-Apr-22	674\|808	741	734	697
01-May-22	682\|816	749	785	736
08-May-22	691\|825	758	816	775
15-May-22	701\|835	768	872	812
22-May-22	711\|845	778	824	767
29-May-22	719\|853	786	852	785
05-Jun-22	729\|863	796	901	839
12-Jun-22	737\|871	804	931	880
19-Jun-22	743\|877	810	911	863
26-Jun-22	751\|885	818	895	834
03-Jul-22	756\|890	823	912	854
10-Jul-22	768\|902	835	919	843
17-Jul-22	772\|906	839	1,006	895
24-Jul-22	775\|909	842	1,007	886
31-Jul-22	777\|911	844	944	819
07-Aug-22	778\|912	845	941	834
14-Aug-22	777\|911	844	904	804
21-Aug-22	778\|912	845	908	823
28-Aug-22	775\|909	842	894	832
04-Sep-22	772\|906	839	852	804
11-Sep-22	766\|900	833	903	869
18-Sep-22	760\|894	827	837	794
25-Sep-22	753\|887	820	845	817
02-Oct-22	747\|881	814	804	781
09-Oct-22	744\|880	812	768	744
16-Oct-22	734\|870	802	835	822
23-Oct-22	726\|862	794	797	785
30-Oct-22	716\|852	784	763	744
06-Nov-22	706\|842	774	784	757
13-Nov-22	697\|833	765	777	754
20-Nov-22	685\|821	753	838	806
27-Nov-22	676\|812	744	794	753
04-Dec-22	668\|804	736	818	777
11-Dec-22	658\|794	726	869	819
18-Dec-22	652\|788	720	771	711
25-Dec-22	643\|779	711	831	761
01-Jan-23	637\|773	705	794	719
08-Jan-23	636\|772	704	801	732
15-Jan-23	632\|768	700	766	709
22-Jan-23	627\|763	695	727	684
29-Jan-23	625\|761	693	754	713
05-Feb-23	624\|760	692	747	724
12-Feb-23	624\|760	692	774	757
19-Feb-23	624\|760	692	744	723
26-Feb-23	627\|763	695	740	720
05-Mar-23	632\|768	700	788	770
12-Mar-23	636\|772	704	766	749
19-Mar-23	641\|777	709	781	766
26-Mar-23	646\|782	714	762	732
02-Apr-23	653\|789	721	767	737
09-Apr-23	665\|803	734	781	752
16-Apr-23	675\|813	744	741	726
23-Apr-23	682\|820	751	777	744
30-Apr-23	692\|830	761	839	806
07-May-23	702\|840	771	784	750
14-May-23	711\|849	780	853	817
21-May-23	721\|859	790	862	819
28-May-23	730\|868	799	875	834
04-Jun-23	738\|876	807	894	846
11-Jun-23	748\|886	817	870	811
18-Jun-23	754\|892	823	838	803
25-Jun-23	762\|900	831	908	868
02-Jul-23	768\|906	837	883	842
09-Jul-23	780\|918	849	826	807
16-Jul-23	784\|922	853	827	804
23-Jul-23	786\|924	855	869	845
30-Jul-23	788\|926	857	881	870
06-Aug-23	788\|926	857	879	864
13-Aug-23	788\|926	857	848	831
20-Aug-23	789\|927	858	833	824
27-Aug-23	785\|923	854	786	781
03-Sep-23	782\|920	851	781	771
10-Sep-23	779\|917	848	774	768
17-Sep-23	772\|910	841	787	779
24-Sep-23	765\|903	834	817	804
01-Oct-23	757\|895	826	810	800
08-Oct-23	754\|892	823	811	799
15-Oct-23	745\|883	814	804	794
22-Oct-23	737\|875	806	734	722
29-Oct-23	728\|866	797	768	755
05-Nov-23	715\|853	784	778	758
12-Nov-23	705\|845	775	841	809
19-Nov-23	695\|835	765	795	763
26-Nov-23	685\|825	755	771	743
03-Dec-23	677\|817	747	778	751
10-Dec-23	667\|807	737	780	759
17-Dec-23	659\|799	729	828	801
24-Dec-23	651\|791	721	809	784
31-Dec-23	644\|784	714	767	738

Comparison of all-cause baseline and COVID-19 period deaths against regression, Inner regional, December 2019 - December 2023 (a)(b)(c)

["Week ending","95% bounds","Expected","Actual","Actual w\/o reported COVID-19"]

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[]

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Weekly all-cause mortality: Outer regional

Outer regional Australia recorded the lowest excess mortality during the pandemic. The only year with excess mortality recorded was 2022, when excess mortality was estimated at 3.4% higher than expected. This was the lowest percentage of excess mortality recorded across all remoteness areas in that year.
There have been very few weeks where mortality in outer regional Australia has been higher than the expected range. This happened in February to March 2022 and June to August 2022.
COVID-19 associated mortality was the main contributor to excess mortality in 2022. In that year, excess mortality is estimated at 601 deaths for outer regional areas. In 2022 986 people living in outer regional areas died from or with COVID-19.

Excess mortality by year, Outer regional, 2020-23
	2020	2021	2022	2023
Expected	17,111	17,208	17,700	18,157
Observed	16,204	16,914	18,301	17,965
Excess	-907	-294	601	-192
% Excess	-5.3	-1.7	3.4	-1.1
Reported deaths from or with COVID-19	18	20	986	548

Comparison of all-cause baseline and COVID-19 period deaths against regression, Outer regional, December 2019 - December 2023 (a)(b)(c)
Week ending	95% bounds	Expected	Actual	Actual w/o reported COVID-19
05-Jan-20	261\|337	299	311	311
12-Jan-20	260\|336	298	273	273
19-Jan-20	260\|336	298	318	318
26-Jan-20	258\|334	296	311	311
02-Feb-20	258\|334	296	338	338
09-Feb-20	257\|333	295	289	289
16-Feb-20	257\|333	295	335	335
23-Feb-20	260\|336	298	315	315
01-Mar-20	260\|336	298	303	303
08-Mar-20	261\|337	299	291	291
15-Mar-20	261\|337	299	326	326
22-Mar-20	262\|338	300	307	307
29-Mar-20	264\|340	302	309	309
05-Apr-20	269\|345	307	291	290
12-Apr-20	272\|348	310	303	299
19-Apr-20	276\|352	314	257	255
26-Apr-20	278\|354	316	298	295
03-May-20	281\|357	319	313	311
10-May-20	285\|361	323	319	319
17-May-20	287\|363	325	300	299
24-May-20	290\|366	328	324	323
31-May-20	291\|367	329	337	337
07-Jun-20	295\|371	333	293	293
14-Jun-20	298\|374	336	306	306
21-Jun-20	300\|376	338	303	302
28-Jun-20	302\|378	340	267	267
05-Jul-20	307\|383	345	343	343
12-Jul-20	308\|384	346	316	316
19-Jul-20	309\|385	347	308	308
26-Jul-20	311\|387	349	295	294
02-Aug-20	311\|387	349	328	327
09-Aug-20	311\|387	349	324	324
16-Aug-20	311\|387	349	351	351
23-Aug-20	310\|386	348	304	304
30-Aug-20	310\|386	348	296	296
06-Sep-20	309\|385	347	332	332
13-Sep-20	306\|382	344	317	317
20-Sep-20	304\|380	342	294	294
27-Sep-20	302\|378	340	298	297
04-Oct-20	301\|379	340	299	299
11-Oct-20	299\|377	338	328	328
18-Oct-20	298\|376	337	293	293
25-Oct-20	294\|372	333	256	256
01-Nov-20	292\|370	331	303	303
08-Nov-20	287\|365	326	284	284
15-Nov-20	284\|362	323	305	305
22-Nov-20	282\|360	321	299	299
29-Nov-20	279\|357	318	314	314
06-Dec-20	277\|355	316	293	293
13-Dec-20	273\|351	312	308	308
20-Dec-20	271\|349	310	287	287
27-Dec-20	268\|346	307	307	307
03-Jan-21	266\|344	305	285	285
10-Jan-21	267\|345	306	325	325
17-Jan-21	266\|344	305	282	282
24-Jan-21	265\|343	304	310	310
31-Jan-21	264\|342	303	335	335
07-Feb-21	264\|342	303	309	309
14-Feb-21	264\|342	303	305	305
21-Feb-21	263\|341	302	313	313
28-Feb-21	263\|341	302	300	300
07-Mar-21	264\|342	303	293	293
14-Mar-21	265\|343	304	286	286
21-Mar-21	267\|345	306	294	294
28-Mar-21	270\|348	309	305	305
04-Apr-21	272\|350	311	282	282
11-Apr-21	277\|355	316	287	287
18-Apr-21	279\|357	318	295	295
25-Apr-21	282\|360	321	306	306
02-May-21	285\|363	324	313	313
09-May-21	290\|368	329	363	363
16-May-21	291\|369	330	366	366
23-May-21	294\|372	333	329	329
30-May-21	297\|375	336	358	358
06-Jun-21	301\|379	340	371	371
13-Jun-21	303\|381	342	337	337
20-Jun-21	307\|385	346	322	322
27-Jun-21	309\|387	348	339	339
04-Jul-21	311\|389	350	328	328
11-Jul-21	314\|392	353	343	343
18-Jul-21	318\|396	357	362	362
25-Jul-21	319\|397	358	355	355
01-Aug-21	320\|398	359	330	330
08-Aug-21	320\|398	359	336	336
15-Aug-21	320\|398	359	330	330
22-Aug-21	320\|398	359	358	358
29-Aug-21	318\|396	357	375	375
05-Sep-21	316\|394	355	329	329
12-Sep-21	315\|393	354	338	338
19-Sep-21	313\|391	352	349	349
26-Sep-21	311\|389	350	300	299
03-Oct-21	309\|387	348	354	354
10-Oct-21	308\|388	348	321	319
17-Oct-21	306\|386	346	326	325
24-Oct-21	302\|382	342	329	325
31-Oct-21	299\|379	339	301	300
07-Nov-21	295\|375	335	315	315
14-Nov-21	294\|374	334	352	352
21-Nov-21	290\|370	330	294	294
28-Nov-21	287\|367	327	335	333
05-Dec-21	283\|363	323	304	303
12-Dec-21	281\|361	321	309	308
19-Dec-21	279\|359	319	345	343
26-Dec-21	276\|356	316	339	339
02-Jan-22	274\|354	314	332	327
09-Jan-22	274\|354	314	285	282
16-Jan-22	273\|353	313	298	288
23-Jan-22	272\|352	312	348	330
30-Jan-22	271\|351	311	350	330
06-Feb-22	271\|351	311	353	337
13-Feb-22	271\|351	311	336	317
20-Feb-22	270\|350	310	361	341
27-Feb-22	271\|351	311	348	333
06-Mar-22	271\|351	311	366	352
13-Mar-22	274\|354	314	339	327
20-Mar-22	277\|357	317	327	320
27-Mar-22	278\|358	318	335	320
03-Apr-22	280\|360	320	324	312
10-Apr-22	286\|366	326	340	332
17-Apr-22	289\|369	329	300	280
24-Apr-22	291\|371	331	340	317
01-May-22	294\|374	334	313	296
08-May-22	298\|378	338	362	343
15-May-22	299\|379	339	364	345
22-May-22	304\|384	344	350	328
29-May-22	308\|388	348	357	340
05-Jun-22	310\|390	350	348	329
12-Jun-22	314\|394	354	350	323
19-Jun-22	315\|395	355	405	374
26-Jun-22	318\|398	358	403	381
03-Jul-22	320\|400	360	342	313
10-Jul-22	323\|405	364	397	377
17-Jul-22	325\|407	366	412	381
24-Jul-22	326\|408	367	405	362
31-Jul-22	327\|409	368	410	353
07-Aug-22	327\|409	368	385	337
14-Aug-22	327\|409	368	421	372
21-Aug-22	327\|409	368	359	337
28-Aug-22	326\|408	367	375	351
04-Sep-22	326\|408	367	361	349
11-Sep-22	324\|406	365	330	317
18-Sep-22	321\|403	362	362	350
25-Sep-22	318\|400	359	347	340
02-Oct-22	317\|399	358	323	314
09-Oct-22	317\|399	358	374	366
16-Oct-22	314\|396	355	352	344
23-Oct-22	312\|394	353	353	348
30-Oct-22	309\|391	350	314	307
06-Nov-22	304\|386	345	342	334
13-Nov-22	301\|383	342	337	325
20-Nov-22	298\|380	339	325	313
27-Nov-22	295\|377	336	339	329
04-Dec-22	293\|375	334	315	301
11-Dec-22	288\|370	329	358	335
18-Dec-22	286\|368	327	342	316
25-Dec-22	283\|365	324	356	332
01-Jan-23	281\|363	322	363	335
08-Jan-23	281\|363	322	321	293
15-Jan-23	280\|362	321	323	301
22-Jan-23	279\|361	320	343	331
29-Jan-23	278\|360	319	296	287
05-Feb-23	278\|360	319	364	354
12-Feb-23	278\|360	319	293	283
19-Feb-23	278\|360	319	311	304
26-Feb-23	278\|360	319	297	288
05-Mar-23	279\|361	320	317	305
12-Mar-23	280\|362	321	323	314
19-Mar-23	281\|363	322	349	336
26-Mar-23	284\|366	325	335	329
02-Apr-23	287\|369	328	318	308
09-Apr-23	292\|376	334	321	308
16-Apr-23	295\|379	337	382	369
23-Apr-23	297\|381	339	368	349
30-Apr-23	300\|384	342	340	325
07-May-23	304\|388	346	348	337
14-May-23	308\|392	350	346	330
21-May-23	311\|395	353	364	351
28-May-23	313\|397	355	350	331
04-Jun-23	316\|400	358	380	359
11-Jun-23	320\|404	362	341	329
18-Jun-23	323\|407	365	363	349
25-Jun-23	326\|410	368	382	368
02-Jul-23	328\|412	370	368	358
09-Jul-23	332\|416	374	390	378
16-Jul-23	334\|418	376	364	355
23-Jul-23	335\|419	377	358	348
30-Jul-23	337\|421	379	350	347
06-Aug-23	337\|421	379	323	319
13-Aug-23	337\|421	379	359	351
20-Aug-23	337\|421	379	395	388
27-Aug-23	335\|419	377	349	341
03-Sep-23	333\|417	375	341	337
10-Sep-23	332\|416	374	358	352
17-Sep-23	330\|414	372	349	349
24-Sep-23	328\|412	370	354	352
01-Oct-23	326\|410	368	340	336
08-Oct-23	325\|409	367	318	315
15-Oct-23	323\|407	365	334	332
22-Oct-23	319\|403	361	327	322
29-Oct-23	316\|400	358	385	377
05-Nov-23	312\|396	354	350	339
12-Nov-23	309\|393	351	347	335
19-Nov-23	305\|389	347	353	333
26-Nov-23	303\|387	345	362	349
03-Dec-23	299\|383	341	348	341
10-Dec-23	297\|381	339	359	340
17-Dec-23	293\|377	335	349	340
24-Dec-23	290\|374	332	318	312
31-Dec-23	288\|372	330	342	333

Comparison of all-cause baseline and COVID-19 period deaths against regression, Outer regional, December 2019 - December 2023 (a)(b)(c)

["Week ending","95% bounds","Expected","Actual","Actual w\/o reported COVID-19"]

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[]

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Weekly all-cause mortality: Remote

Due to the low number of weekly deaths in remote and very remote Australia, modelling by individual age groups was not possible (population is controlled for to enable comparisons). Predicting an expected number of deaths from a small base can lead to volatility. This is evident from the range of the expected numbers - the upper and lower bounds are wider to account for this high variation.
Excess mortality was highest in 2022 at 11.5% higher than expected, similar to the 11.7% recorded nationally.
Excess mortality was 4.2% higher than expected in 2023. The number of excess deaths decreased by over 60% when compared to 2022.
For most of the pandemic, mortality in remote Australia has been in the expected range of variation.
COVID-19 associated mortality as recorded on death certificates has been a significant contributor to excess mortality in remote Australia since 2022. The virus accounted for approximately half of the excess mortality in 2022 and 80% in 2023.
In 2020 and 2021 there were very low numbers of deaths associated with COVID-19 for those in outer regional areas.

Excess mortality by year, Remote, 2020-23
	2020	2021	2022	2023
Expected	1,822	1,809	1,830	1,861
Observed	1,826	1,893	2,041	1,940
Excess	4	84	211	79
% Excess	0.2	4.6	11.5	4.2
Reported deaths from or with COVID-19	np	np	106	64

Comparison of all-cause baseline and COVID-19 period deaths against regression, Remote, December 2019 - December 2023 (a)(b)(c)
Week ending	95% bounds	Expected	Actual	Actual w/o reported COVID-19
05-Jan-20	20\|45	33	39	39
12-Jan-20	20\|45	33	28	28
19-Jan-20	20\|45	33	40	40
26-Jan-20	20\|45	32	46	46
02-Feb-20	20\|45	32	42	42
09-Feb-20	20\|45	32	36	36
16-Feb-20	20\|45	32	37	37
23-Feb-20	20\|45	32	27	27
01-Mar-20	20\|45	33	37	37
08-Mar-20	20\|45	33	28	28
15-Mar-20	20\|45	33	30	30
22-Mar-20	20\|45	33	30	30
29-Mar-20	21\|45	33	34	34
05-Apr-20	21\|46	33	40	40
12-Apr-20	21\|46	33	30	30
19-Apr-20	21\|46	34	23	22
26-Apr-20	21\|46	34	31	31
03-May-20	22\|46	34	33	33
10-May-20	22\|47	34	35	35
17-May-20	22\|47	34	26	26
24-May-20	22\|47	35	33	33
31-May-20	22\|47	35	41	41
07-Jun-20	23\|47	35	36	36
14-Jun-20	23\|48	35	39	39
21-Jun-20	23\|48	35	41	40
28-Jun-20	23\|48	36	29	29
05-Jul-20	23\|48	36	34	34
12-Jul-20	23\|48	36	29	29
19-Jul-20	24\|48	36	34	34
26-Jul-20	24\|48	36	40	40
02-Aug-20	24\|49	36	35	35
09-Aug-20	24\|49	36	33	33
16-Aug-20	24\|49	36	31	31
23-Aug-20	24\|49	36	38	38
30-Aug-20	24\|49	36	29	29
06-Sep-20	24\|49	36	38	38
13-Sep-20	24\|48	36	37	37
20-Sep-20	23\|48	36	36	36
27-Sep-20	23\|48	36	34	34
04-Oct-20	23\|48	36	38	38
11-Oct-20	23\|48	36	37	37
18-Oct-20	23\|48	35	40	40
25-Oct-20	23\|48	35	28	28
01-Nov-20	23\|47	35	30	30
08-Nov-20	22\|47	35	34	34
15-Nov-20	22\|47	35	42	42
22-Nov-20	22\|47	34	30	30
29-Nov-20	22\|47	34	41	41
06-Dec-20	22\|46	34	38	38
13-Dec-20	21\|46	34	32	32
20-Dec-20	21\|46	34	33	33
27-Dec-20	21\|46	33	36	36
03-Jan-21	21\|46	33	28	28
10-Jan-21	21\|46	33	45	45
17-Jan-21	21\|46	33	34	34
24-Jan-21	21\|45	33	32	32
31-Jan-21	20\|45	33	34	34
07-Feb-21	20\|45	33	45	45
14-Feb-21	20\|45	33	25	25
21-Feb-21	20\|45	33	21	21
28-Feb-21	20\|45	33	32	32
07-Mar-21	20\|45	33	32	32
14-Mar-21	21\|45	33	43	43
21-Mar-21	21\|46	33	27	27
28-Mar-21	21\|46	33	37	37
04-Apr-21	21\|46	33	32	32
11-Apr-21	21\|46	34	33	33
18-Apr-21	21\|46	34	32	32
25-Apr-21	22\|46	34	47	47
02-May-21	22\|47	34	32	32
09-May-21	22\|47	34	36	36
16-May-21	22\|47	35	42	42
23-May-21	22\|47	35	27	27
30-May-21	23\|48	35	51	51
06-Jun-21	23\|48	35	37	37
13-Jun-21	23\|48	35	39	39
20-Jun-21	23\|48	36	45	45
27-Jun-21	23\|48	36	39	39
04-Jul-21	24\|48	36	42	42
11-Jul-21	24\|49	36	43	43
18-Jul-21	24\|49	36	39	39
25-Jul-21	24\|49	36	29	29
01-Aug-21	24\|49	37	45	45
08-Aug-21	24\|49	37	45	45
15-Aug-21	24\|49	37	27	27
22-Aug-21	24\|49	37	31	31
29-Aug-21	24\|49	37	29	29
05-Sep-21	24\|49	37	38	38
12-Sep-21	24\|49	36	36	36
19-Sep-21	24\|49	36	41	41
26-Sep-21	24\|49	36	37	37
03-Oct-21	24\|49	36	14	14
10-Oct-21	23\|49	36	56	56
17-Oct-21	23\|48	36	29	29
24-Oct-21	23\|48	36	37	37
31-Oct-21	23\|48	35	28	28
07-Nov-21	23\|48	35	45	45
14-Nov-21	23\|48	35	28	28
21-Nov-21	22\|47	35	29	29
28-Nov-21	22\|47	35	41	41
05-Dec-21	22\|47	34	41	40
12-Dec-21	22\|47	34	39	39
19-Dec-21	22\|47	34	46	46
26-Dec-21	21\|46	34	38	38
02-Jan-22	21\|46	34	41	41
09-Jan-22	21\|46	34	24	24
16-Jan-22	21\|46	33	47	47
23-Jan-22	21\|46	33	28	28
30-Jan-22	21\|46	33	34	32
06-Feb-22	21\|46	33	39	38
13-Feb-22	21\|46	33	43	40
20-Feb-22	21\|46	33	33	32
27-Feb-22	21\|46	33	33	32
06-Mar-22	21\|46	33	46	44
13-Mar-22	21\|46	33	22	20
20-Mar-22	21\|46	34	30	28
27-Mar-22	21\|46	34	47	46
03-Apr-22	21\|46	34	33	32
10-Apr-22	22\|47	34	55	54
17-Apr-22	22\|47	34	44	41
24-Apr-22	22\|47	34	43	42
01-May-22	22\|47	35	37	35
08-May-22	22\|47	35	45	44
15-May-22	23\|48	35	34	34
22-May-22	23\|48	35	41	39
29-May-22	23\|48	36	30	26
05-Jun-22	23\|48	36	43	42
12-Jun-22	23\|48	36	33	31
19-Jun-22	24\|49	36	40	38
26-Jun-22	24\|49	36	48	47
03-Jul-22	24\|49	36	46	45
10-Jul-22	24\|49	37	44	41
17-Jul-22	24\|49	37	46	45
24-Jul-22	24\|49	37	51	44
31-Jul-22	24\|50	37	38	33
07-Aug-22	24\|50	37	47	41
14-Aug-22	24\|50	37	35	32
21-Aug-22	24\|50	37	44	40
28-Aug-22	24\|50	37	41	35
04-Sep-22	24\|50	37	40	39
11-Sep-22	24\|50	37	36	35
18-Sep-22	24\|49	37	39	37
25-Sep-22	24\|49	37	38	37
02-Oct-22	24\|49	37	38	38
09-Oct-22	24\|49	36	34	32
16-Oct-22	24\|49	36	42	42
23-Oct-22	24\|49	36	46	45
30-Oct-22	23\|49	36	27	26
06-Nov-22	23\|48	36	48	48
13-Nov-22	23\|48	36	37	36
20-Nov-22	23\|48	35	36	31
27-Nov-22	22\|48	35	42	38
04-Dec-22	22\|47	35	43	38
11-Dec-22	22\|47	35	39	35
18-Dec-22	22\|47	34	39	37
25-Dec-22	22\|47	34	46	43
01-Jan-23	22\|47	34	27	26
08-Jan-23	21\|47	34	54	52
15-Jan-23	21\|47	34	37	36
22-Jan-23	21\|46	34	37	36
29-Jan-23	21\|46	34	29	29
05-Feb-23	21\|46	34	28	24
12-Feb-23	21\|46	34	37	36
19-Feb-23	21\|46	34	43	42
26-Feb-23	21\|46	34	39	38
05-Mar-23	21\|46	34	36	36
12-Mar-23	21\|47	34	27	27
19-Mar-23	21\|47	34	23	23
26-Mar-23	22\|47	34	31	31
02-Apr-23	22\|47	34	34	34
09-Apr-23	22\|47	35	37	33
16-Apr-23	22\|47	35	37	32
23-Apr-23	22\|48	35	44	42
30-Apr-23	23\|48	35	27	26
07-May-23	23\|48	35	30	28
14-May-23	23\|48	36	37	34
21-May-23	23\|48	36	46	44
28-May-23	23\|49	36	35	31
04-Jun-23	24\|49	36	47	45
11-Jun-23	24\|49	36	30	30
18-Jun-23	24\|49	37	37	35
25-Jun-23	24\|49	37	43	41
02-Jul-23	24\|50	37	60	57
09-Jul-23	25\|50	37	40	37
16-Jul-23	25\|50	37	41	39
23-Jul-23	25\|50	37	35	35
30-Jul-23	25\|50	38	39	39
06-Aug-23	25\|50	38	43	42
13-Aug-23	25\|50	38	45	44
20-Aug-23	25\|50	38	47	47
27-Aug-23	25\|50	38	31	30
03-Sep-23	25\|50	38	39	39
10-Sep-23	25\|50	37	38	38
17-Sep-23	25\|50	37	35	33
24-Sep-23	25\|50	37	37	37
01-Oct-23	24\|50	37	33	33
08-Oct-23	24\|50	37	35	35
15-Oct-23	24\|50	37	37	37
22-Oct-23	24\|49	37	33	33
29-Oct-23	24\|49	36	28	28
05-Nov-23	24\|49	36	39	38
12-Nov-23	23\|49	36	44	42
19-Nov-23	23\|48	36	38	37
26-Nov-23	23\|48	36	30	30
03-Dec-23	23\|48	35	45	42
10-Dec-23	23\|48	35	40	38
17-Dec-23	22\|48	35	25	25
24-Dec-23	22\|48	35	37	37
31-Dec-23	22\|47	35	41	39

Comparison of all-cause baseline and COVID-19 period deaths against regression, Remote, December 2019 - December 2023 (a)(b)(c)

["Week ending","95% bounds","Expected","Actual","Actual w\/o reported COVID-19"]

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[]

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Weekly all-cause mortality: Very remote

Due to the low number of weekly deaths in remote and very remote Australia, modelling by individual age groups was not possible (population is controlled for to enable comparisons). Predicting an expected number of deaths from a small base can lead to volatility. This is evident from the range of the expected numbers - the upper and lower bounds are wider to account for this high variation.
Very remote Australia recorded the highest proportion of excess mortality in 2022 at 13.4%. This decreased by just over 80% in 2023.
Excess mortality for very remote Australia in 2023 was estimated at 2.5% above expected, down from 13.4% in 2022.
For most of the pandemic, mortality in very remote Australia has been in the expected range of variation.
COVID-19 associated mortality (as recorded on death certificates) accounted for about 40% of excess mortality in 2022. This was a slightly lower proportion than recorded in other remoteness areas. The virus accounted for almost all excess mortality in 2023.
No deaths were recorded on death certificates as being due to COVID-19 for people living in very remote areas in 2020.

Excess mortality by year, Very remote, 2020-23
	2020	2021	2022	2023
Expected	1,114	1,099	1,116	1,137
Observed	1,066	1,131	1,265	1,165
Excess	-48	32	149	28
% Excess	-4.3	2.9	13.4	2.5
Reported deaths from or with COVID-19	0	np	60	29

Comparison of all-cause baseline and COVID-19 period deaths against regression, Very remote, December 2019 - December 2023 (a)(b)(c)
Week ending	95% bounds	Expected	Actual	Actual w/o reported COVID-19
05-Jan-20	11\|29	20	19	19
12-Jan-20	11\|29	20	23	23
19-Jan-20	11\|29	20	13	13
26-Jan-20	11\|29	20	23	23
02-Feb-20	11\|29	20	17	17
09-Feb-20	11\|29	20	25	25
16-Feb-20	11\|29	20	14	14
23-Feb-20	11\|29	20	19	19
01-Mar-20	11\|29	20	20	20
08-Mar-20	11\|29	20	10	10
15-Mar-20	11\|29	20	17	17
22-Mar-20	11\|29	20	23	23
29-Mar-20	11\|29	20	22	22
05-Apr-20	11\|29	20	20	20
12-Apr-20	11\|29	20	15	15
19-Apr-20	11\|30	20	22	22
26-Apr-20	12\|30	21	14	14
03-May-20	12\|30	21	22	22
10-May-20	12\|30	21	23	23
17-May-20	12\|30	21	26	26
24-May-20	12\|30	21	24	24
31-May-20	12\|30	21	12	12
07-Jun-20	12\|31	21	18	18
14-Jun-20	13\|31	22	22	22
21-Jun-20	13\|31	22	21	21
28-Jun-20	13\|31	22	17	17
05-Jul-20	13\|31	22	21	21
12-Jul-20	13\|31	22	23	23
19-Jul-20	13\|31	22	24	24
26-Jul-20	13\|31	22	21	21
02-Aug-20	13\|31	22	22	22
09-Aug-20	13\|31	22	19	19
16-Aug-20	13\|31	22	22	22
23-Aug-20	13\|31	22	16	16
30-Aug-20	13\|31	22	23	23
06-Sep-20	13\|31	22	18	18
13-Sep-20	13\|31	22	25	25
20-Sep-20	13\|31	22	12	12
27-Sep-20	13\|31	22	26	26
04-Oct-20	13\|31	22	15	15
11-Oct-20	13\|31	22	19	19
18-Oct-20	13\|31	22	16	16
25-Oct-20	12\|31	22	29	29
01-Nov-20	12\|30	21	18	18
08-Nov-20	12\|30	21	20	20
15-Nov-20	12\|30	21	24	24
22-Nov-20	12\|30	21	19	19
29-Nov-20	12\|30	21	26	26
06-Dec-20	12\|30	21	19	19
13-Dec-20	12\|30	21	22	22
20-Dec-20	11\|29	20	19	19
27-Dec-20	11\|29	20	19	19
03-Jan-21	11\|29	20	28	28
10-Jan-21	11\|29	20	22	22
17-Jan-21	11\|29	20	26	26
24-Jan-21	11\|29	20	14	14
31-Jan-21	11\|29	20	17	17
07-Feb-21	11\|29	20	20	20
14-Feb-21	11\|29	20	19	19
21-Feb-21	11\|29	20	11	11
28-Feb-21	11\|29	20	25	25
07-Mar-21	11\|29	20	15	15
14-Mar-21	11\|29	20	20	20
21-Mar-21	11\|29	20	19	19
28-Mar-21	11\|29	20	23	23
04-Apr-21	11\|29	20	23	23
11-Apr-21	11\|29	20	18	18
18-Apr-21	12\|30	21	22	22
25-Apr-21	12\|30	21	21	21
02-May-21	12\|30	21	18	18
09-May-21	12\|30	21	15	15
16-May-21	12\|30	21	20	20
23-May-21	12\|30	21	18	18
30-May-21	12\|30	21	14	14
06-Jun-21	13\|31	22	31	31
13-Jun-21	13\|31	22	17	17
20-Jun-21	13\|31	22	17	17
27-Jun-21	13\|31	22	21	21
04-Jul-21	13\|31	22	37	37
11-Jul-21	13\|31	22	13	13
18-Jul-21	13\|31	22	18	18
25-Jul-21	13\|31	22	33	33
01-Aug-21	13\|31	22	23	23
08-Aug-21	13\|31	22	21	21
15-Aug-21	13\|31	22	18	18
22-Aug-21	13\|31	22	28	28
29-Aug-21	13\|31	22	22	22
05-Sep-21	13\|31	22	19	19
12-Sep-21	13\|31	22	22	21
19-Sep-21	13\|31	22	28	28
26-Sep-21	13\|31	22	20	20
03-Oct-21	13\|31	22	20	20
10-Oct-21	13\|31	22	32	32
17-Oct-21	13\|31	22	25	24
24-Oct-21	13\|31	22	29	29
31-Oct-21	13\|31	22	26	26
07-Nov-21	12\|30	21	23	23
14-Nov-21	12\|30	21	29	29
21-Nov-21	12\|30	21	20	20
28-Nov-21	12\|30	21	15	15
05-Dec-21	12\|30	21	17	17
12-Dec-21	12\|30	21	35	35
19-Dec-21	12\|30	21	26	26
26-Dec-21	12\|30	21	27	27
02-Jan-22	11\|29	20	19	19
09-Jan-22	11\|29	20	16	16
16-Jan-22	11\|29	20	14	14
23-Jan-22	11\|29	20	25	25
30-Jan-22	11\|29	20	23	23
06-Feb-22	11\|29	20	32	30
13-Feb-22	11\|29	20	25	23
20-Feb-22	11\|29	20	21	20
27-Feb-22	11\|29	20	24	20
06-Mar-22	11\|29	20	27	24
13-Mar-22	11\|29	20	32	30
20-Mar-22	11\|29	20	24	23
27-Mar-22	11\|29	20	19	19
03-Apr-22	11\|30	21	17	16
10-Apr-22	12\|30	21	31	28
17-Apr-22	12\|30	21	19	18
24-Apr-22	12\|30	21	20	19
01-May-22	12\|30	21	27	24
08-May-22	12\|30	21	19	18
15-May-22	12\|30	21	23	23
22-May-22	12\|31	21	26	25
29-May-22	13\|31	22	23	22
05-Jun-22	13\|31	22	21	21
12-Jun-22	13\|31	22	24	22
19-Jun-22	13\|31	22	31	30
26-Jun-22	13\|31	22	25	25
03-Jul-22	13\|31	22	23	23
10-Jul-22	13\|32	22	29	28
17-Jul-22	13\|32	23	23	22
24-Jul-22	14\|32	23	21	20
31-Jul-22	14\|32	23	30	24
07-Aug-22	14\|32	23	22	20
14-Aug-22	14\|32	23	24	23
21-Aug-22	14\|32	23	28	27
28-Aug-22	14\|32	23	25	24
04-Sep-22	14\|32	23	27	27
11-Sep-22	14\|32	23	21	21
18-Sep-22	13\|32	23	28	28
25-Sep-22	13\|32	22	25	25
02-Oct-22	13\|31	22	27	26
09-Oct-22	13\|31	22	24	24
16-Oct-22	13\|31	22	24	22
23-Oct-22	13\|31	22	29	29
30-Oct-22	13\|31	22	32	31
06-Nov-22	13\|31	22	24	24
13-Nov-22	13\|31	22	24	24
20-Nov-22	12\|31	22	22	21
27-Nov-22	12\|30	21	25	21
04-Dec-22	12\|30	21	18	18
11-Dec-22	12\|30	21	23	21
18-Dec-22	12\|30	21	21	20
25-Dec-22	12\|30	21	29	27
01-Jan-23	12\|30	21	29	27
08-Jan-23	12\|30	21	21	19
15-Jan-23	12\|30	21	16	15
22-Jan-23	11\|30	21	22	20
29-Jan-23	11\|30	21	27	27
05-Feb-23	11\|30	20	22	22
12-Feb-23	11\|30	20	16	15
19-Feb-23	11\|30	20	21	19
26-Feb-23	11\|30	21	21	21
05-Mar-23	11\|30	21	26	26
12-Mar-23	11\|30	21	24	23
19-Mar-23	12\|30	21	25	22
26-Mar-23	12\|30	21	13	13
02-Apr-23	12\|30	21	26	26
09-Apr-23	12\|30	21	21	21
16-Apr-23	12\|30	21	17	17
23-Apr-23	12\|30	21	21	21
30-Apr-23	12\|31	21	16	15
07-May-23	12\|31	22	27	27
14-May-23	13\|31	22	29	28
21-May-23	13\|31	22	28	26
28-May-23	13\|31	22	20	19
04-Jun-23	13\|31	22	26	25
11-Jun-23	13\|31	22	28	26
18-Jun-23	13\|32	22	23	22
25-Jun-23	13\|32	23	25	23
02-Jul-23	14\|32	23	15	15
09-Jul-23	14\|32	23	25	24
16-Jul-23	14\|32	23	24	24
23-Jul-23	14\|32	23	26	26
30-Jul-23	14\|32	23	26	25
06-Aug-23	14\|32	23	20	20
13-Aug-23	14\|32	23	14	14
20-Aug-23	14\|32	23	24	24
27-Aug-23	14\|32	23	15	15
03-Sep-23	14\|32	23	26	26
10-Sep-23	14\|32	23	29	28
17-Sep-23	14\|32	23	26	26
24-Sep-23	14\|32	23	27	27
01-Oct-23	14\|32	23	32	32
08-Oct-23	14\|32	23	23	23
15-Oct-23	13\|32	23	22	22
22-Oct-23	13\|32	22	20	20
29-Oct-23	13\|31	22	20	20
05-Nov-23	13\|31	22	24	24
12-Nov-23	13\|31	22	25	25
19-Nov-23	13\|31	22	30	29
26-Nov-23	13\|31	22	11	11
03-Dec-23	12\|31	22	29	28
10-Dec-23	12\|31	21	18	18
17-Dec-23	12\|31	21	19	19
24-Dec-23	12\|30	21	14	13
31-Dec-23	12\|30	21	20	20

Comparison of all-cause baseline and COVID-19 period deaths against regression, Very remote, December 2019 - December 2023 (a)(b)(c)

["Week ending","95% bounds","Expected","Actual","Actual w\/o reported COVID-19"]

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Methodology

The analysis of 2020-2023 mortality data is based on a model developed by Serfling¹⁰ and later adapted by the US Center for Disease Control (CDC) and the Centre for Epidemiology and Evidence at New South Wales Ministry of Health Health (NSW Health). This section provides an overview of how the model has been developed over time, key aspects of the model, and how the model has been adapted and applied by the ABS in this analysis.

Historical development of model

Historically this type of model has been used to estimate excess mortality caused by influenza.

As early as 1932, Collins determined that excess mortality during winter months in the United States of America (USA) was a consequence of epidemic influenza and therefore could be used as an indicator for the recognition of influenza outbreaks.²

In 1963, Serfling described a cyclic regression model, based on the seasonal pattern of pneumonia and influenza (P&I) deaths, to infer excess deaths due to influenza.¹⁰

Since then, models based on Serfling's have been applied in a number of temperate countries (USA,³,⁴ France,⁴ Australia,⁴ and Italy⁵) to demonstrate that excess mortality occurring during winter months is associated with the pandemic and seasonal epidemics of influenza.

The CDC took the approach further and established the 122 Cities Surveillance System to provide timely, prospective information on excess mortality due to influenza. ⁶,⁷

The New South Wales mortality surveillance was included as part of the routine Influenza Surveillance Program prior to COVID-19 and used an adaptation of the Serfling model to monitor for influenza epidemics. This system primarily monitored the proportion of influenza positive specimens among all respiratory specimens from the major public health laboratories, the proportion of emergency department visits diagnosed with influenza, and outbreaks of influenza reported to Public Health Units by residential care facilities.⁹

Aspects of the Serfling model and its implementations

The Serfling model uses historical data to predict current patterns of mortality. This enables the identification of any deviation from that prediction that may signal an influenza epidemic. In developing this model, Serfling recognised that past influenza epidemics could overly influence the regression, limiting the ability of the model to identify any new epidemic. For this reason, Serfling excluded past epidemics when fitting the model.

An important feature of this methodology is the identification of a threshold that can be used as the upper and/or lower limit for the data. Observations that lie between these upper and lower limits are considered to be normal. The chosen threshold will vary depending on the desired specificity of the analysis and the methods used for calculation. In statistics there are default or familiar thresholds used in measuring these boundaries such as 1.96 standard errors either side of the mid-point.

An upper threshold was chosen to define the upper limit of the expected number of deaths in the absence of an influenza epidemic. This upper threshold was calculated as the predicted number of deaths in a given week plus a constant multiple of the standard error of the time series (the differences between each value predicted by the model and the actual observed values, or the 'model residuals'). Serfling chose the constant multiple to be 1.64 standard errors, and considered 2 consecutive weeks above the threshold to indicate epidemic behaviour.¹⁰

The NSW Health model used for the Influenza Surveillance Program is based on the Serfling model. This variant of the model fits a cyclic linear regression to data for the previous 5 calendar years and then forecasts the current year's time series from data up to the end of the previous year.

Data source

Please see the methodology section of Provisional Mortality Statistics for a description of the scope of data used in this model.

ABS adaptation of the model

The ABS has applied key characteristics of the model used in the New South Wales Influenza Surveillance Program. The ABS model is also based on the application of a cyclic linear regression model to the time series of weekly age-specific death rates. The model has been applied to both doctor certified and coroner referred deaths from all causes.

The approach used by the ABS involves use of a 'robust' estimation procedure for fitting the model. Epidemics can cause increased mortality which leads to outliers in time series data. By down-weighting outliers it aims to fit the model to patterns of mortality that are expected to occur in the absence of an epidemic. This robust regression down-weights the influence of extreme observations (outliers) and is applied to a seven-year baseline time series (weeks commencing on a Monday). Some additional adjustments were made to extreme outliers, for example the 2017 influenza season. This adjustment involved applying a missing value to some age groups across some weeks where the actual rate was unusually high. This was done separately for each jurisdiction.

The cyclical regression model includes: a linear time term, t, with values 1, 2, 3, ... for each week of the time series. Also included are annual seasonal harmonic variables to describe the cyclical seasonal background pattern. The harmonic variables are functions of the week number, t, and the periodicity in the same units – in this case, yearly (52 weeks). The 2 harmonic variables in this case are: sine(2π t/52) and cosine(2π t/52). For years with 53 weeks these harmonic terms have been divided by 53 instead of 52. The harmonic terms reflect the fact that the number of deaths is usually higher in winter than in summer.

The final model was:

\(Expected(proportion)=A+Bt+CSin(2πt/52)+DCos(2πt/52)\)

where A, B, C and D, are the coefficients calculated from the regression. Previous versions of this model also include a time squared term. This term was removed as it resulted in increasingly unrealistic output as the prediction window extended further from the modelling window.

To evaluate the approach, the model was fitted using PROC ROBUSTREG in SAS Software with the simplest, default 'M estimation' method.¹² The PROC SCORE procedure was then used to forecast values for 2020-2023. The standard error and threshold is derived from the stdi option in PROC ROBUSTREG which is run a second time with the 2020-2023 results attached.

Threshold identification

Identifying the threshold at which to signal excess mortality will vary depending on the goals of the research, application of the method, and seasonality of diseases of interest. Several national statistical organisations are using different models including Farrington surveillance algorithms, z -scores and prediction intervals to inform such thresholds.

A method for calculating the threshold for this analysis was selected which had a broader application and was more easily interpreted across a range of conditions, namely 1.96 standard errors or a 95% confidence interval. Use of the 95% confidence interval does introduce the expectation that random weekly variation could lead to counts that exceed thresholds 5% of the time. As such, individual weeks that exceed thresholds should be interpreted with caution. However, any prolonged period of weeks, 2 or more, exceeding the expected range can suggest excess mortality has been signalled.

The SAS function PROC ROBUSTREG offers the STDI parameter to calculate the 'standard error of prediction' of the model¹² which is used to define 1 standard error. The standard error of prediction is a more logical choice for assigning the threshold of excess mortality than the root mean square error (standard error of the model residuals) because it incorporates not only the variance of the residuals but also the variance of the model parameter estimates. This provides an estimate of the expected variability of the observed values in the absence of an epidemic.

Determining the baseline

Choosing the reference period (i.e. the number of years in the baseline) is important as it can change the expected number of deaths. When selecting the reference period key attributes were required:

There needed to be enough input available to predict the number of deaths from 2020-2023. As the paper is looking at excess mortality in the absence of the pandemic, no data from 2020-2023 is part of the reference period when predicting the expected number of deaths. Estimates of excess mortality are more accurate for years that are closer to the reference period.
A stable and clear mortality trend needed to be identified. This was particularly important as the model used is a harmonic with trend, meaning the pattern of death should be stable over a period to estimate an expected trend accurately.
The baseline period needed to be applied consistently across jurisdictions.

To make the decision, a sensitivity analysis was conducted. This analysis tested three reference periods: 2010-2019, 2013-2019 and 2015-2019. Standardised death rates were used to determine which years to test (these are presented below). Each baseline produced slightly different expected counts of deaths, which altered the % excess figures. The ABS decided to implement 2013-2019 as the predictor reference period. This baseline was chosen because:

There was a large decline in mortality between 2017 and 2018. This is likely due to the severe influenza season in 2017 causing some mortality displacement in 2018. Mortality displacement is an epidemiological concept which describes the phenomenon of a period of very high mortality being followed by a period of low mortality. Even controlling for 2017, the model was overcompensating for the rate of decline during 2015-2019, resulting in a very low number of expected deaths in 2022 and 2023.
Not all jurisdictions experienced a severe influenza season in 2017. Western Australia for example, had higher mortality rates in 2015 and 2016. Variability across jurisdictions meant that 2015-2019 had different outcomes across jurisdictions.
Western Australia had steeper declines in mortality rates between 2015-2016 and 2017 compared to other jurisdictions. Starting the baseline at the highest mortality points was overstating the rate of decline in WA and resulting in a very low number of expected deaths in 2022 and 2023. This was also affected by the model – as a harmonic with trend model is being used, volatility in the input trend affected the expected number of deaths.
For smaller jurisdictions with low numbers of weekly deaths, adding additional years onto the baseline provided a more stable trend.
There was some excess mortality in 2014, 2015 and 2017. Adjustments were made to outliers to control for these. 2013 was a year of stable mortality where no adjustments had to be made across any jurisdictions.
2010-2019 and 2013-2019 produced similar results. However, there is less population change to account for from 2013 onwards. This was especially important for smaller jurisdictions where age adjustment was not as precise due to small numbers.
This model will also be used for analysis of diseases. There were a number of coding changes in 2013. Starting the reference period ensures continuity of time series for this analysis.

Modelling rates

Weekly mortality rates were calculated for 2013-2019 to predict expected weekly rates of death for 2020-2023. Rates were then converted to numbers for ease of interpretation.

Age groups selected for modelling ASDRs went through a number of assessments including:

A consistent number of deaths each week, ideally at least 20 deaths per week in the age group.
Population to be used as denominators should have at least 30 people in each age group.

Final age groups vary by jurisdiction based on the above criteria. Where possible, age groups were modelled separately up to 95 years and over (Australia, New South Wales, Victoria and Queensland). For South Australia and Western Australia age groups were modelled up to 90 years and over. In Tasmania age groups were modelled to 85 years and over. Weekly numbers of deaths for the Northern Territory and the Australian Capital Territory were too small to allow robust age-specific rates to be calculated, and crude rates (total population) were used instead.

Consideration was given to whether age-specific rates or age-standardised rates should be modelled. Both age-specific rates and age-standardised rates control for the age composition of a population and take into account growth rates within a population over time. Age-specific rates show the intensity of deaths within a population and express real-life mortality and population loss. Age-standardised rates are a modelled rate, standardised against a hypothetical population to enable comparison across cohorts. As comparison was not the main focus, age-specific rates were chosen as the model input.

Adjustment to Victorian death data

Every week there is typically a small number of death records where it is not possible to assign a remoteness area. This may be due to the death of a person who usually lived overseas, or inadequate detail of the usual residence of the deceased. During 2018 the Victorian Registry of Births, Deaths and Marriages implemented new software that resulted in several weeks of data where a higher than usual number of records did not have sufficient address details supplied to the ABS to allocate these records to a remoteness area. For this publication, 551 records for deaths that occurred in Victoria within week 18 and week 25 of 2018 have had their remoteness area imputed based on the average distribution by remoteness area by age for Victoria for the 10 weeks beginning in week 27 of 2018.

References

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11. The ROBUSTREG procedure. SAS/STAT(R) 12.3 User's Guide. Cary (USA): SAS Institute, 2013. Available from: https://support.sas.com/documentation/onlinedoc/stat/123/rreg.pdf

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Data downloads

Excess mortality, Remoteness areas, Jan 2013 - Dec 2023

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