Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study

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There is evidence globally that low-income communities experience higher levels of morbidity and mortality during the pandemic. Methods Age-standardized COVID-19 mortality in the eight sub-districts of Cape Town was compared by economic indicators taken from the most recent Census (unemployment rate, monthly income). Results The overall Standardized Death Rate (SDR) for COVID-19 in Cape Town was 1 640 per million, but there was wide variation across the different sub-districts. A linear relationship was seen between sub-districts with high poverty and high COVID-19 SDRs. Conclusions Low-income communities in Cape Town experienced higher levels of COVID-19 mortality. As we continue to contend with COVID-19, these communities need to be prioritized for access to quality health care." } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://gatesopenresearch.org/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://gatesopenresearch.org/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://gatesopenresearch.org/articles/5-90/v1", "name": "Higher COVID-19 mortality in low-income communities in the City of..." } } ] } Home Browse Higher COVID-19 mortality in low-income communities in the City of... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Hussey H, Zinyakatira N, Morden E et al. Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.12688/gatesopenres.13288.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] Hannah Hussey https://orcid.org/0000-0002-6199-0904 1,2 , Nesbert Zinyakatira 1,2 , Erna Morden 1 , [...] Muzzammil Ismail 1,2 , Masudah Paleker 1,3 , Jamy-Lee Bam 1 , Leslie London 2 , Andrew Boulle 1,2 , Mary-Ann Davies 1,2 Hannah Hussey https://orcid.org/0000-0002-6199-0904 1,2 , Nesbert Zinyakatira 1,2 , [...] Erna Morden 1 , Muzzammil Ismail 1,2 , Masudah Paleker 1,3 , Jamy-Lee Bam 1 , Leslie London 2 , Andrew Boulle 1,2 , Mary-Ann Davies 1,2 PUBLISHED 04 Jun 2021 Author details Author details 1 Health Intelligence, Western Cape Government: Health, Cape Town, South Africa 2 School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa 3 Division of Health Systems and Public Health, Stellenbosch University, Cape Town, South Africa Hannah Hussey Roles: Conceptualization, Formal Analysis, Project Administration, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Nesbert Zinyakatira Roles: Data Curation, Formal Analysis, Methodology, Writing – Review & Editing Erna Morden Roles: Data Curation, Writing – Review & Editing Muzzammil Ismail Roles: Visualization, Writing – Review & Editing Masudah Paleker Roles: Writing – Review & Editing Jamy-Lee Bam Roles: Data Curation, Writing – Review & Editing Leslie London Roles: Conceptualization, Supervision, Writing – Review & Editing Andrew Boulle Roles: Supervision, Writing – Review & Editing Mary-Ann Davies Roles: Supervision, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Coronavirus (COVID-19) collection. Abstract Background Cape Town, a South African city with high levels of economic inequality, has gone through two COVID-19 waves. There is evidence globally that low-income communities experience higher levels of morbidity and mortality during the pandemic. Methods Age-standardized COVID-19 mortality in the eight sub-districts of Cape Town was compared by economic indicators taken from the most recent Census (unemployment rate, monthly income). Results The overall Standardized Death Rate (SDR) for COVID-19 in Cape Town was 1 640 per million, but there was wide variation across the different sub-districts. A linear relationship was seen between sub-districts with high poverty and high COVID-19 SDRs. Conclusions Low-income communities in Cape Town experienced higher levels of COVID-19 mortality. As we continue to contend with COVID-19, these communities need to be prioritized for access to quality health care. READ ALL READ LESS Keywords COVID-19, mortality, low-income Corresponding Author(s) Hannah Hussey ( [email protected] ) Close Corresponding author: Hannah Hussey Competing interests: M.-A. D. reports grants from Viiv Healthcare, National Institutes of Health and Wellcome Trust. A. B. reports grants to their institution from National Institutes of Health, Bill and Melinda Gates Foundation, and Wellcome Trust; and nonfinancial support from United States Agency for International Development. Grant information: This work was supported by the Western Cape Provincial Health Data Centre (Western Cape Department of Health), the US National Institutes for Health (grant numbers R01 HD080465 and U01 AI069924), the Gates Foundation (grant numbers 1164272 and 119327), the United States Agency for International Development (grant number 72067418CA00023), and the Wellcome Trust (grant number 203135/Z/16/Z) (A.B). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2021 Hussey H et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Hussey H, Zinyakatira N, Morden E et al. Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.12688/gatesopenres.13288.1 ) First published: 04 Jun 2021, 5 :90 ( https://doi.org/10.12688/gatesopenres.13288.1 ) Latest published: 04 Jun 2021, 5 :90 ( https://doi.org/10.12688/gatesopenres.13288.1 ) Introduction South Africa is the most unequal country in the world, with a Gini Coefficient of 0.63 1 , 2 , and within its cities the same inequities prevail. Post-apartheid Cape Town is a highly divided and unequal city, with socio-economic characteristics still differing along geographic lines 3 . In 2016, the city’s population was 4 232 276 and the Gini coefficient was 0.61 4 . Since SARS-CoV-2 reached Cape Town in March 2020, the city has experienced two waves of COVID-19. The first wave peaked in June-July 2020, and the second more severe wave peaked in December 2020 – January 2021, and was driven largely by the new 501.YV2 (B1.351) variant 5 , 6 . Data from the United States (USA) has shown that low socio-economic status, and race as its proxy, were significantly associated with COVID-19 incidence and mortality 7 . Similar findings have been reported in the United Kingdom (UK) 8 – 10 . Data from Brazil and Mexico further support the idea that the poorest population groups have lower survival from COVID-19 9 , 10 . Cape Town Metro has eight geographic sub-districts. Due to the city’s apartheid history, inequity tends to follow these geographic boundaries and the majority of the population resides in the historically Black African and Coloured (mixed ancestry) areas towards the southeast of the city (see Figure 1 map) 11 . There is, however, still some heterogeneity within sub-districts. These low-income communities also tend to be overcrowded and denser, with less access to services like running water and electricity 2 . The populations in these areas are also younger, with for instance 1.6% of the population in Khayelitsha being over 65 years of age, compared to 7.3% in Northern 3 . Figure 1. Map of Cape Town Metro, with socio-economic index and population size taken from the 2011 Census 3 . Graphic courtesy of the Western Cape Department of Health. Since older age is the strongest risk factor for COVID-19 mortality 12 , crude mortality rates may mask inequities in COVID-19 outcomes as poorer populations tend to be younger. We therefore aimed to compare the age- and sex-standardized mortality in different geographical areas of Cape Town known to have different income levels. Methods This descriptive ecological study was done using aggregate data routinely reported as part of the Western Cape Department of Health’s COVID-19 Surveillance Response, from 1 March 2020 to 28 February 2021. The main outcome of interest was the COVID-19 standardized death rate (SDR) and the main exposures were the economic indicators, for each sub-district. COVID-19 deaths include all deaths ascertained by the services, or through linkage to the national population register in patients with civil identifiers available, in individuals with laboratory confirmed COVID-19 (either PCR or antigen positive). This is limited to deaths within 28-days of a COVID-19 diagnosis or within 14-days of being discharged following admission due to COVID-19, and excludes deaths manually flagged as incidental by case managers or identified as non-natural deaths on the population register. COVID-19 tests are performed in either the public National Health Laboratory Service or in various private laboratories. The Standardized Death Rate (SDR) is calculated by adjusting for the age and sex breakdown of each sub-district in the province, using the Western Cape Province as the standard population, using Microsoft Excel. Data on economic indicators was taken from the latest Census in 2011, which is publicly available online 3 . Unemployment was defined as “persons who did not work, but who looked for work and were available to work in the reference period”, and the labor force was defined as persons aged 15–64 years 3 . The 2011 Census classified households with monthly incomes below ZAR3200, which when converted at the average 2011 exchange rate is around US$ 440 13 . The co-morbidities amongst public sector patients are primarily reported from inferred health episodes at the Provincial Health Data Centre, where routine health data, such as laboratory tests and medication dispensed, is used to infer health conditions 14 . The co-morbidities of private patients are reliant on manual capture, and there is the risk of under-ascertainment in this latter group. No ethics approval was sought for this study, as it relies upon aggregate data from routine reports. Results There were 7 643 total COVID-19 related deaths in the Cape Town Metro. The total crude death rate ranged from 1 217 in Northern, to 2 547 in Klipfontein. Adjusted for age, the total standardized death rate for COVID-19 was 1 640 per million overall but ranged from 920 in Northern to 2 686 in Khayelitsha sub-district ( Table 1 , Figure 2 ). Table 1. Total Number of COVID-19 deaths, Crude Death Rate (CDR) per million and Standardized Death Rate (SDR) per million in the Cape Town Metro, in each wave and by sub-district. Wave 1 Wave 2 Total 1 Mar - 31 Oct 2020 1 Nov - 28 Feb 2021 1 Mar - 28 Feb 2021 Ratio of Wave 2 to Wave 1 SDR Sub-district Total deaths CDR per million SDR per million Total deaths CDR per million SDR per million Total deaths CDR per million SDR per million Eastern 454 645 656 754 1070 1097 1208 1715 1753 1.67 Khayelitsha 404 913 1605 257 581 1080 661 1493 2686 0.67 Klipfontein 530 1292 1234 515 1255 1201 1045 2547 2435 0.97 Mitchells Plain 376 611 793 496 806 1022 872 1417 1815 1.29 Northern 195 417 313 374 800 608 569 1217 920 1.94 Southern 437 732 549 685 1148 867 1122 1880 1416 1.58 Tygerberg 503 689 695 797 1092 1110 1300 1781 1806 1.60 Western 349 553 529 517 819 790 866 1372 1319 1.49 METRO Total 3248 706 696 4395 956 943 7643 1662 1640 1.35 Figure 2. Total COVID-19 Standardized Death Rate (SDR) per million by sub-district. Graphic courtesy of the Western Cape Department of Health. Using the 2011 Census data, the eight sub-districts have differing levels of employment and monthly household income. Among the deceased COVID-19 cases, more private laboratory testing was done in the higher income sub-districts ( Table 2 ). The scatter plots ( Figure 3a and b ) show a linear positive relationship between increasing COVID-19 SDR in a sub-district and (a) percentage of unemployment and (b) percentage of low-income households in a sub-district. Table 2. Economic indicators (taken from 2011 Census 3 ) and test facility for deceased COVID-19 cases, by sub-district. Sub-district % Labor force (aged 15-64) unemployed % Households with monthly income ≤ ZAR3200 % Private testing for deceased COVID-19 cases Eastern 22 46 36.3 Khayelitsha 38 74 14 Klipfontein 32 59 23.9 Mitchells Plain 32 61 20.5 Northern 12 30 54.9 Southern 16 34 42.6 Tygerberg 25 45 29.7 Western 18 37 41.2 Figure 3a and 3b. Total COVID-19 Standardized Death Rate (SDR) and percent of labor force unemployed ( a ) and household monthly income ( b ), taken from the 2011 Census 3 , and plotted for each Cape Town Metro sub-district. Poorer sub-districts tended to be worse affected in the first wave with relative protection in the second wave. In contrast, wealthier sub-districts had a low SDR during the first wave but were worse affected in the second wave. A linear but inverse relationship was present between percentage unemployment rate in a sub-district and the ratio of Wave 2 to Wave 1 COVID-19 SDRs ( Figure 4 ). Figure 4. Ratio of Wave 2 to Wave 1 COVID-19 SDRs and percent of labor forced unemployed, by sub-district. For the deceased patients with COVID-19, different sub-districts also have differing age structures and co-morbidity burdens. Sub-districts with higher burdens of infectious diseases, particularly HIV and tuberculosis, tended to have younger COVID-19 deaths and an overall higher SDR ( Figure 5 and Figure 6 ). Figure 5. Age categories for the deceased COVID-19 patients, by sub-district. Figure 6. Known co-morbidities in deceased COVID-19 patients, by sub-district (note that tuberculosis includes both previous and current disease). Discussion The study suggests that low-income sub-districts had higher COVID-19 SDRs. The SDR for Khayelitsha was almost three times higher than that of Northern, a more affluent sub-district. This finding of a strong socio-economic gradient in COVID-19 mortality is consistent with an expanding literature, and explanations for this association are multifactorial. Individuals in low-income communities with crowded housing, a reliance on public transport and higher numbers of essential workers are less able to implement and maintain social distancing and non-pharmaceutical interventions (NPIs) 7 . And they therefore are more likely to get infected with COVID-19, as demonstrated in several South African seroprevalence studies 15 – 17 . A SARS-CoV-2 seroprevalence study performed by the South African blood service in four of the nine provinces (Eastern Cape, Northern Cape, Free State and KwaZulu Natal) found substantial differences between different race groups, with Black African donors having seroprevalence rates above 60% and White donors having less than or around 20% 15 . While the authors note the limitations of using race as a proxy for socio-economic status, their study highlights the limitations of NPIs in communities with economic deprivation and high population density, or conversely how effective NPIs can be when they are feasible 15 . A study on shopping mall workers in Cape Town found a high seroprevalence was associated with informal housing, living in a sub-district with a low-income per household and having a low-earning occupation 16 . In a study from the USA, amongst those diagnosed with COVID-19, poverty was also associated with a higher risk of hospitalization and intensive care unit admission 18 . Because of upstream social determinants of health, low-income communities have higher rates of chronic diseases that put them at risk of severe COVID-19 disease 7 . Younger age is usually a protective factor for severe COVID-19 disease. However, data from the USA and UK has shown that in communities of color, people of younger ages were still at risk of COVID-19 mortality, because high rates of co-morbidities, such as diabetes and chronic lung , are concentrated in these poor communities 19 . The diagnosis and management of these chronic conditions is also inferior, as these same communities often lack access to quality care 20 . Data from a population-based study in the Western Cape during the first wave of the pandemic showed that older age, male sex and diabetes were strongly associated with COVID-19 mortality 12 . The study also found that HIV and current tuberculosis, both conditions strongly associated with poverty, were associated with COVID-19 mortality, with a 2.14 (95% confidence interval [CI] 1.70-2.70) and 2.70 (95% CI 1.81-4.04) adjusted hazard ratio, respectively 12 . A population-based study from the UK also found a strong association between HIV and COVID-19 mortality 21 . As data on co-morbidities is not collected in a standardized way across the public and private sectors for all cases diagnosed with COVID-19, this study was not able to formally assess the differing burdens of co-morbidities across the sub-districts. If individuals in low-income communities require in-patient treatment, they are more likely to access the relatively under-resourced public health sector. An analysis of COVID-19 in-hospital mortality in South Africa, found that admission to a public sector compared to a private sector facility was associated with increased risk of mortality (adjusted odds ratio of 1.6; 95% CI 1.4-1.8) 22 . This may be due to later presentations to hospital, as well as differences in access to and unequal availability of critical care and other specialized resources or interventions in the public sector. This study also showed that low-income sub-districts were worse affected in the first wave compared to the second wave, suggesting that infection in the first wave may have conferred some immunity. However, the science on re-infection is still very unclear, and particularly in the context of emerging variants, this should be interpreted cautiously 23 . Limitations of this study include its ecological nature, the lack of standardized co-morbidity data and the fact that the economic data is from 2011. However, while the percentages of individuals living in poverty in each sub-district might have changed with time, and even increased during the pandemic, a reduction in inequality between the sub-districts is unlikely to have occurred. The Western Cape Government reported increasing inequity in Cape Town from 2011 to 2018, with the Gini coefficient for the city increasing from 0.604 in 2011 to 0.617 in 2018 11 . An analysis of data from the National Income Dynamics Study (NIDS) in 2017 and the first wave of the NIDS-Coronavirus Rapid Mobile Survey (NIDS-CRAM) suggested that income-related health inequality in the COVID-19 era increased six-fold compared with what was obtained in 2017 24 . The COVID-19 pandemic has exposed the longstanding structural drivers of health inequities globally 25 . While all sectors of the population of Cape Town were affected by the pandemic, those living in low-income communities were at higher risk of SARS-CoV-2 infection and of COVID-19-related mortality. Health services need to be preferentially directed to those that need them the most, i.e. the poor. This is not only for COVID-19, but for any subsequent pandemic where low-income communities will remain vulnerable without improved access to care. It will however remain difficult to address the inequities of COVID-19 morbidity and mortality while poverty and income inequality persist. Data availability All data underlying the results are available as part of the article and no additional source data are required. Faculty Opinions recommended References 1. World Bank: Gini index (World Bank estimate). 2021 [cited 2021 Apr 12]. Reference Source 2. International Bank for Reconstruction and Development / The World Bank: Overcoming Poverty and inequality in South Africa - An assessment of Drivers, Constraints and Opportunities. 2018. Reference Source 3. Statistics South Africa: Cape Town census and population statistics. 2011. Reference Source 4. Western Cape Government: Socio-economic profile. City of Cape Town. 2017. Reference Source 5. Tegally H, Wilkinson E, Giovanetti M, et al. : Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa. medRxiv. 2020; 2020.12.21.20248640. Publisher Full Text 6. Jassat W, Cohen C, Mudara C, et al. : Multivariable analysis comparing in-hospital mortality in the first and second wave of Covid-19 in three districts of South Africa. Covid-19 Spec Public Heal Surveill Bull. 2021; 18 (6). Reference Source 7. Karmakar M, Lantz PM, Tipirneni R: Association of Social and Demographic Factors With COVID-19 Incidence and Death Rates in the US. JAMA Netw Open. 2021; 4 (1): e2036462. PubMed Abstract | Publisher Full Text | Free Full Text 8. Office for National Statistics: Coronavirus (COVID-19) related deaths by ethnic group, England and Wales - : 2 March 2020 to 10 April 2020. 2020 [cited 2021 Mar 4]. Reference Source 9. Millán-Guerrero RO, Caballero-Hoyos R, Monárrez-Espino J: Poverty and survival from COVID-19 in Mexico. J Public Health (Oxf). 2020; fdaa228. PubMed Abstract | Publisher Full Text | Free Full Text 10. Martins-Filho PR, de Souza Araújo AA, Quintans-Júnior LJ, et al. : COVID-19 fatality rates related to social inequality in Northeast Brazil: a neighbourhood-level analysis. J Travel Med. 2020 [cited 2021 Feb 25]; 27 (7): taaa128. PubMed Abstract | Publisher Full Text | Free Full Text 11. Western Cape Government - Health: Western Cape Burden of Disease - Rapid Review Update 2019. 2020. Reference Source 12. Boulle A, Davies MA, Hussey H, et al. : Risk factors for COVID-19 death in a population cohort study from the Western Cape Province, South Africa. Clin Infect Dis. 2020 [cited 2021 Feb 3]; ciaa1198. PubMed Abstract | Publisher Full Text | Free Full Text 13. South African Reserve Bank: Selected Historical Rates. [cited 2021 Apr 14]. Reference Source 14. Boulle A, Heekes A, Tiffin N, et al. : Data centre profile: The provincial health data centre of the western cape province, South Africa. Int J Popul Data Sci. 2019; 4 (2): 1143. PubMed Abstract | Publisher Full Text | Free Full Text 15. Sykes W, Mhlanga L, Swanevelder R, et al. : Prevalence of anti-SARS-CoV-2 antibodies among blood donors in Northern Cape, KwaZulu-Natal, Eastern Cape, and Free State provinces of South Africa in January 2021. Res Sq. 2021 [cited 2021 Feb 25]; rs.3.rs-233375. PubMed Abstract | Publisher Full Text | Free Full Text 16. Shaw JA, Meiring M, Cummins T, et al. : Higher SARS-CoV-2 seroprevalence in workers with lower socioeconomic status in Cape Town, South Africa. Musuka G, editor. PLoS One. 2021 [cited 2021 Mar 1]; 16 (2): e0247852. PubMed Abstract | Publisher Full Text | Free Full Text 17. Hsiao M, Davies MA, Kalk E, et al. : SARS-CoV-2 seroprevalence in the Cape Town metropolitan sub-districts after the peak of infections. Covid-19 Spec Public Heal Surveill Bull. 2020; 18 (Supplementary Issue 5). Reference Source 18. Muñoz-Price LS, Nattinger AB, Rivera F, et al. : Racial Disparities in Incidence and Outcomes Among Patients With COVID-19. JAMA Netw Open. 2020; 3 (9): e2021892. PubMed Abstract | Publisher Full Text | Free Full Text 19. Klugman KP, Zewdu S, Mahon BE, et al. : Younger ages at risk of Covid-19 mortality in communities of color [version 1; peer review: 2 approved]. Gates Open Res. F1000 Research Ltd; 2020; 4 : 69. PubMed Abstract | Publisher Full Text | Free Full Text 20. Kruk ME, Gage AD, Arsenault C, et al. : High-quality health systems in the Sustainable Development Goals era: time for a revolution. Lancet Glob Health. Elsevier Ltd; 2018; 6 (11): e1196–e1252. PubMed Abstract | Publisher Full Text | Free Full Text 21. Bhaskaran K, Rentsch CT, MacKenna B, et al. : HIV infection and COVID-19 death: a population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform. Lancet HIV. 2021; 8 (1): e24–e32. PubMed Abstract | Publisher Full Text | Free Full Text 22. Jassat W, Mudara C, Ozougwu L, et al. : Increased mortality among individuals hospitalised with COVID-19 during the second wave in South Africa. medRxiv. 2021; 2021.03.09.21253184. Publisher Full Text 23. Cele S, Gazy I, Jackson L, et al. : Escape of SARS-CoV-2 501Y.V2 variants from neutralization by convalescent plasma. medRxiv. 2021; 2021.01.26.21250224. Publisher Full Text 24. Nwosu CO, Oyenubi A: Income-related health inequalities associated with the coronavirus pandemic in South Africa: A decomposition analysis. Int J Equity Health. 2021 [cited 2021 Apr 21]; 20 (1): 21. PubMed Abstract | Publisher Full Text | Free Full Text 25. Paremoer L, Nandi S, Serag H, et al. : Covid-19 pandemic and the social determinants of health. BMJ. BMJ Publishing Group; 2021; 372 : n129 . PubMed Abstract | Publisher Full Text | Free Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 04 Jun 2021 ADD YOUR COMMENT Comment Author details Author details 1 Health Intelligence, Western Cape Government: Health, Cape Town, South Africa 2 School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa 3 Division of Health Systems and Public Health, Stellenbosch University, Cape Town, South Africa Hannah Hussey Roles: Conceptualization, Formal Analysis, Project Administration, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Nesbert Zinyakatira Roles: Data Curation, Formal Analysis, Methodology, Writing – Review & Editing Erna Morden Roles: Data Curation, Writing – Review & Editing Muzzammil Ismail Roles: Visualization, Writing – Review & Editing Masudah Paleker Roles: Writing – Review & Editing Jamy-Lee Bam Roles: Data Curation, Writing – Review & Editing Leslie London Roles: Conceptualization, Supervision, Writing – Review & Editing Andrew Boulle Roles: Supervision, Writing – Review & Editing Mary-Ann Davies Roles: Supervision, Writing – Review & Editing Competing interests M.-A. D. reports grants from Viiv Healthcare, National Institutes of Health and Wellcome Trust. A. B. reports grants to their institution from National Institutes of Health, Bill and Melinda Gates Foundation, and Wellcome Trust; and nonfinancial support from United States Agency for International Development. Grant information This work was supported by the Western Cape Provincial Health Data Centre (Western Cape Department of Health), the US National Institutes for Health (grant numbers R01 HD080465 and U01 AI069924), the Gates Foundation (grant numbers 1164272 and 119327), the United States Agency for International Development (grant number 72067418CA00023), and the Wellcome Trust (grant number 203135/Z/16/Z) (A.B). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (1) version 1 Published: 04 Jun 2021, 5:90 https://doi.org/10.12688/gatesopenres.13288.1 Copyright © 2021 Hussey H et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads Gates Open Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Hussey H, Zinyakatira N, Morden E et al. Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.12688/gatesopenres.13288.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 04 Jun 2021 Views 0 Cite How to cite this report: de Gruchy J. Reviewer Report For: Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.21956/gatesopenres.14527.r30740 ) The direct URL for this report is: https://gatesopenresearch.org/articles/5-90/v1#referee-response-30740 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 07 Jul 2021 Jeanelle de Gruchy , Tameside Council, Ashton-under-Lyne, UK; Association of Directors of Public Health (UK), Ashton-under-Lyme, UK Approved VIEWS 0 https://doi.org/10.21956/gatesopenres.14527.r30740 A descriptive ecological study with routine data showing the association of COVID-19 mortality and economic inequality in Cape Town. An important, timely study. Methods, strengths and limitations are well set out and discussed. The difference between SDR ... Continue reading READ ALL A descriptive ecological study with routine data showing the association of COVID-19 mortality and economic inequality in Cape Town. An important, timely study. Methods, strengths and limitations are well set out and discussed. The difference between SDR in the first and second waves is difficult to explain, especially as it is not in line with the main finding. Would there have been a sufficiently high enough population infected in the first wave to provide protection to that extent in the second wave? (the seroprevalence study gives some indication that it is high in these communities, but it's unclear what period the study covered, and its limitation is it wasn't in the Western Cape). It would be good to explore alternate explanations to the one already offered. In the discussion of in-patient treatment, it would be helpful to provide information of the proportionate use of public and private sector in the sub-districts. The final paragraph rightly focuses on equitable access to health services. It would be good to consider whether there are any other recommendations to mitigate the high exposure and transmission in these communities, e.g. how effective were non-pharmaceutical interventions, e.g. did essential workers have access to personal protective equipment. For subsequent health threats, tackling the high levels of obesity and non-pharmaceutical diseases would also be important. Finally, inequitable access to vaccination is likely to be a critical driver of higher COVID-19 SDRs in poorer communities. Minor points: Introduction section, 3rd paragraph footnote for findings in the UK should only be reference 8? Methods section, 3rd paragraph last sentence meaning is unclear. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Public health expert with extensive experience of managing COVID-19 in the UK. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT de Gruchy J. Reviewer Report For: Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.21956/gatesopenres.14527.r30740 ) The direct URL for this report is: https://gatesopenresearch.org/articles/5-90/v1#referee-response-30740 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Klugman KP. Reviewer Report For: Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.21956/gatesopenres.14527.r30741 ) The direct URL for this report is: https://gatesopenresearch.org/articles/5-90/v1#referee-response-30741 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 10 Jun 2021 Keith P. Klugman , Bill & Melinda Gates Foundation, Seattle, WA, USA Approved VIEWS 0 https://doi.org/10.21956/gatesopenres.14527.r30741 This article provides an ecological analysis of poverty and lack of access as associated with increased COVID mortality in Cape Town, South Africa. The strengths and limitations of the study design are well discussed. The lack ... Continue reading READ ALL This article provides an ecological analysis of poverty and lack of access as associated with increased COVID mortality in Cape Town, South Africa. The strengths and limitations of the study design are well discussed. The lack of access to COVID diagnostics in the private sector by poorer communities may have substantially reduced the apparent numbers of COVID deaths and reduced the differences recorded in this study - the study therefore is likely a minimal assessment of the magnitude of poverty on COVID mortality risk - this point could be added to the discussion. The significantly higher attack rate in Khayalitsha in the first wave relative to the second does suggest some degree of longer term protection - given the importance of the beta COV in the second wave this deserves some additional comment - there are some data to suggest that although short term exposure to wave 1 infection may not be protective from wave 2, that longer term antibodies which are affinity matured may be more protective, as suggested in this analysis. Given the bias against testing in poorer communities, have the authors been able to look at the relationship between wealth of districts and all cause excess mortality during these time periods of maximal virus circulation? Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: Although I am employed by the Bill and Melinda Gates Foundation, I was not directly involved in the funding or design of this study. This did not constitute a perceived conflict of interest for me and I confirm that this did not affect my ability to write an objective and unbiased review of the article. Reviewer Expertise: Infectious diseases, epidemiology and microbiology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Klugman KP. Reviewer Report For: Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.21956/gatesopenres.14527.r30741 ) The direct URL for this report is: https://gatesopenresearch.org/articles/5-90/v1#referee-response-30741 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 04 Jun 2021 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 Version 1 04 Jun 21 read read Keith P. Klugman , Bill & Melinda Gates Foundation, Seattle, USA Jeanelle de Gruchy , Tameside Council, Ashton-under-Lyne, UK; Association of Directors of Public Health (UK), Ashton-under-Lyme, UK Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2021 de Gruchy J. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 07 Jul 2021 | for Version 1 Jeanelle de Gruchy , Tameside Council, Ashton-under-Lyne, UK; Association of Directors of Public Health (UK), Ashton-under-Lyme, UK 0 Views copyright © 2021 de Gruchy J. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions A descriptive ecological study with routine data showing the association of COVID-19 mortality and economic inequality in Cape Town. An important, timely study. Methods, strengths and limitations are well set out and discussed. The difference between SDR in the first and second waves is difficult to explain, especially as it is not in line with the main finding. Would there have been a sufficiently high enough population infected in the first wave to provide protection to that extent in the second wave? (the seroprevalence study gives some indication that it is high in these communities, but it's unclear what period the study covered, and its limitation is it wasn't in the Western Cape). It would be good to explore alternate explanations to the one already offered. In the discussion of in-patient treatment, it would be helpful to provide information of the proportionate use of public and private sector in the sub-districts. The final paragraph rightly focuses on equitable access to health services. It would be good to consider whether there are any other recommendations to mitigate the high exposure and transmission in these communities, e.g. how effective were non-pharmaceutical interventions, e.g. did essential workers have access to personal protective equipment. For subsequent health threats, tackling the high levels of obesity and non-pharmaceutical diseases would also be important. Finally, inequitable access to vaccination is likely to be a critical driver of higher COVID-19 SDRs in poorer communities. Minor points: Introduction section, 3rd paragraph footnote for findings in the UK should only be reference 8? Methods section, 3rd paragraph last sentence meaning is unclear. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Public health expert with extensive experience of managing COVID-19 in the UK. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) de Gruchy J. Peer Review Report For: Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.21956/gatesopenres.14527.r30740) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://gatesopenresearch.org/articles/5-90/v1#referee-response-30740 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2021 Klugman K. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 10 Jun 2021 | for Version 1 Keith P. Klugman , Bill & Melinda Gates Foundation, Seattle, WA, USA 0 Views copyright © 2021 Klugman K. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This article provides an ecological analysis of poverty and lack of access as associated with increased COVID mortality in Cape Town, South Africa. The strengths and limitations of the study design are well discussed. The lack of access to COVID diagnostics in the private sector by poorer communities may have substantially reduced the apparent numbers of COVID deaths and reduced the differences recorded in this study - the study therefore is likely a minimal assessment of the magnitude of poverty on COVID mortality risk - this point could be added to the discussion. The significantly higher attack rate in Khayalitsha in the first wave relative to the second does suggest some degree of longer term protection - given the importance of the beta COV in the second wave this deserves some additional comment - there are some data to suggest that although short term exposure to wave 1 infection may not be protective from wave 2, that longer term antibodies which are affinity matured may be more protective, as suggested in this analysis. Given the bias against testing in poorer communities, have the authors been able to look at the relationship between wealth of districts and all cause excess mortality during these time periods of maximal virus circulation? Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests Although I am employed by the Bill and Melinda Gates Foundation, I was not directly involved in the funding or design of this study. This did not constitute a perceived conflict of interest for me and I confirm that this did not affect my ability to write an objective and unbiased review of the article. Reviewer Expertise Infectious diseases, epidemiology and microbiology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Klugman KP. Peer Review Report For: Higher COVID-19 mortality in low-income communities in the City of Cape Town – a descriptive ecological study [version 1; peer review: 2 approved] . Gates Open Res 2021, 5 :90 ( https://doi.org/10.21956/gatesopenres.14527.r30741) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://gatesopenresearch.org/articles/5-90/v1#referee-response-30741 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. 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