Associations between high burden health conditions and trends in mortality during the COVID-19 pandemic – insights from integrated routine health information in the Western Cape, South Africa.
1
School of Public Health, University of Cape Town, Cape Town, South Africa
2
Health Intelligence, Western Cape Department of Health and Wellness, Cape Town, South Africa
3
Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
4
Centre for Actuarial Research, University of Cape Town, Cape Town, South Africa
Popul. Med. 2026;8(Supplement Supplement 1):A3845
ABSTRACT
BACKGROUND:
The majority of excess deaths during the Coronavirus disease 2019 (COVID-19) pandemic are widely thought to be due to undiagnosed COVID-19, rather than disruptions in the provision of and access to healthcare, but there are limited cause-of-death data to substantiate this.
METHODS:
This study used integrated routine health information in the Western Cape province of South Africa to investigate the potential contribution of undiagnosed COVID-19 to increases in mortality during four COVID-19 waves, through the exploration of differential increases in mortality in patients with health conditions which have different known interactions with COVID-19 mortality. We conducted a time series analysis using Poisson regression models of weekly deaths among deidentified pre-pandemic public sector healthcare users aged 20 years or older who were potentially linkable to a research copy of the national population register.
RESULTS:
Over 105 pandemic weeks 81 272 natural deaths occurred among 2 228 166 individuals. The four COVID-19 waves were associated with a 15% increase in natural mortality among people without known COVID-19 (wave adjusted incidence rate ratio [aIRR]=1.15 [95% Confidence Interval 1.12,1.18]), with the highest mortality associations observed among those with advanced age (>=80 years wave aIRR=1.20 [1.14,1.26]), diabetes mellitus (aIRR=1.25 [1.21,1.30]), hypertension (aIRR=1.18 [1.14,1.21]) and chronic kidney disease (aIRR=1.15 [1.11,1.20]). These groups were also at highest risk of death due to known COVID-19 (>=80 years aIRR=27.12; diabetes mellitus aIRR=32.70; hypertension aIRR=29.78 and chronic kidney disease aIRR=25.50).
CONCLUSIONS:
Changes in non-COVID-19 mortality for each well-defined high burden health condition aligned with estimated and published COVID-19 mortality associations, and remained consistent across several sensitivity analyses, supporting the hypothesis that undiagnosed COVID-19 was a major contributing factor to observed excess deaths. Service disruptions are less likely to have resulted in such similar and consistent risk distributions, especially considering the heterogeneity of disruptions within waves and across time.
The majority of excess deaths during the Coronavirus disease 2019 (COVID-19) pandemic are widely thought to be due to undiagnosed COVID-19, rather than disruptions in the provision of and access to healthcare, but there are limited cause-of-death data to substantiate this.
METHODS:
This study used integrated routine health information in the Western Cape province of South Africa to investigate the potential contribution of undiagnosed COVID-19 to increases in mortality during four COVID-19 waves, through the exploration of differential increases in mortality in patients with health conditions which have different known interactions with COVID-19 mortality. We conducted a time series analysis using Poisson regression models of weekly deaths among deidentified pre-pandemic public sector healthcare users aged 20 years or older who were potentially linkable to a research copy of the national population register.
RESULTS:
Over 105 pandemic weeks 81 272 natural deaths occurred among 2 228 166 individuals. The four COVID-19 waves were associated with a 15% increase in natural mortality among people without known COVID-19 (wave adjusted incidence rate ratio [aIRR]=1.15 [95% Confidence Interval 1.12,1.18]), with the highest mortality associations observed among those with advanced age (>=80 years wave aIRR=1.20 [1.14,1.26]), diabetes mellitus (aIRR=1.25 [1.21,1.30]), hypertension (aIRR=1.18 [1.14,1.21]) and chronic kidney disease (aIRR=1.15 [1.11,1.20]). These groups were also at highest risk of death due to known COVID-19 (>=80 years aIRR=27.12; diabetes mellitus aIRR=32.70; hypertension aIRR=29.78 and chronic kidney disease aIRR=25.50).
CONCLUSIONS:
Changes in non-COVID-19 mortality for each well-defined high burden health condition aligned with estimated and published COVID-19 mortality associations, and remained consistent across several sensitivity analyses, supporting the hypothesis that undiagnosed COVID-19 was a major contributing factor to observed excess deaths. Service disruptions are less likely to have resulted in such similar and consistent risk distributions, especially considering the heterogeneity of disruptions within waves and across time.
| eISSN: | 2654-1459 |
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