Article Text

Original research
Risk factors for COVID-19 infection, disease severity and related deaths in Africa: a systematic review
  1. Hailay Abrha Gesesew1,2,
  2. Digsu Negese Koye3,
  3. Dagnachew Muluye Fetene4,
  4. Mulu Woldegiorgis4,
  5. Yohannes Kinfu5,6,
  6. Ayele Bali Geleto7,8,
  7. Yohannes Adama Melaku1,
  8. Hassen Mohammed9,10,
  9. Kefyalew Addis Alene11,12,13,
  10. Mamaru Ayenew Awoke14,
  11. Mulugeta Molla Birhanu15,16,
  12. Amanuel Tesfay Gebremedhin11,12,
  13. Yalemzewod Assefa Gelaw13,17,
  14. Desalegn Markos Shifti16,18,
  15. Muluken Dessalegn Muluneh19,20,
  16. Teketo Kassaw Tegegne18,21,
  17. Solomon Abrha5,22,
  18. Atsede Fantahun Aregay23,24,
  19. Mohammed Biset Ayalew25,26,
  20. Abadi Kahsu Gebre27,28,
  21. Kidane Tadesse Gebremariam2,29,30,
  22. Tesfaye Gebremedhin31,
  23. Lemlem Gebremichael22,32,
  24. Cheru Tesema Leshargie21,33,
  25. Getiye Dejenu Kibret21,34,
  26. Maereg Wagnew Meazaw7,
  27. Alemayehu Berhane Mekonnen35,36,
  28. Dejen Yemane Tekle2,37,
  29. Azeb Gebresilassie Tesema2,37,
  30. Fisaha Haile Tesfay2,38,
  31. Wubshet Tesfaye39,
  32. Befikadu Legesse Wubishet7,
  33. Berihun Assefa Dachew11,40,
  34. Akilew Awoke Adane40,41
  1. 1College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
  2. 2Scool of Public Health, Mekelle University, Mekelle, Ethiopia
  3. 3Department of Medicine at Royal Melbourne Hospital and Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
  4. 4Burnet Institute, Melbourne, Victoria, Australia
  5. 5Faculty of Health, University of Canberra, Canberra, Australian Capital Territory, Australia
  6. 6College of Medicine, Doha, Qatar
  7. 7Research Centre for Generational Health and Ageing, University of Newcastle, Newcastle, New South Wales, Australia
  8. 8School of Public Health, Haramaya University, College of Health and Medical Sciences, Harar, Ethiopia
  9. 9Vaccinology and Immunology Research Trials Unit, Women's and Children's Hospital, Adelaide, South Australia, Australia
  10. 10Robinson Research Institute, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
  11. 11School of Population Health, Curtin University, Perth, Western Australia, Australia
  12. 12Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, Perth, Western Australia, Australia
  13. 13Institute of Public Health, University of Gondar, Gondar, Ethiopia
  14. 14School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria, Australia
  15. 15Department of Medicine, Monash University, Melbourne, Victoria, Australia
  16. 16Saint Paul’s Hospital, Millennium Medical College, Addis Ababa, Ethiopia
  17. 17Population Child Health Research Group, School of Women’s & Children’s Health, UNSW, Sydney, New South Wales, Australia
  18. 18Faculty of Health and Medicine, The University of Newcastle, Callaghan, New South Wales, Australia
  19. 19School of Nursing and Midwifery, Western Sydney University, Penrith South, New South Wales, Australia
  20. 20Amref Health Africa in Ethiopia, Addis Ababa, Ethiopia
  21. 21College of Health Science, Debre Markos University, Debre Markos, Ethiopia
  22. 22Department of Pharmacology, Mekelle University, Mekelle, Ethiopia
  23. 23School of Nursing and Midwifery, Monash University, Melbourne, Victoria, Australia
  24. 24School of Nursing, Mekelle University, Mekelle, Ethiopia
  25. 25Department of Pharmacy, University of New England, Armidale, New South Wales, Australia
  26. 26Department of Clinical Pharmacy, University of Gondar, Gondar, Ethiopia
  27. 27School of Pharmacy, Mekelle University, Mekelle, Ethiopia
  28. 28School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
  29. 29School of Exercise and Nutrition Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
  30. 30Lifelong Health, South Australia Health and Medical Research Institute, Adelaide, South Australia, Australia
  31. 31Canberra School of Politics, University of Canberra, Canberra, Australian Capital Territory, Australia
  32. 32Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia
  33. 33School of Public Health, University of Technology Sydney, Sydney, New South Wales, Australia
  34. 34Faculty of Health, University of Technology Sydney, Sydney, New South Wales, Australia
  35. 35Institute for Health Transformation, Deakin University, Burwood, Victoria, Australia
  36. 36School of Pharmacy, University of Sydney, Sydney, New South Wales, Australia
  37. 37The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
  38. 38School of Health and Social development, Deakin University, Melbourne, Victoria, Australia
  39. 39Health research Institute, University of Canberra, Canberra, Australian Capital Territory, Australia
  40. 40Department of Epidemiology and Biostatistics, University of Gondar, Gondar, Ethiopia
  41. 41Telethon Kids Institute, The University of Western Australia, Nedlands, Western Australia, Australia
  1. Correspondence to Dr Hailay Abrha Gesesew; hailushepi{at}gmail.com

Abstract

Objective The aim of this study was to provide a comprehensive evidence on risk factors for transmission, disease severity and COVID-19 related deaths in Africa.

Design A systematic review has been conducted to synthesise existing evidence on risk factors affecting COVID-19 outcomes across Africa.

Data sources Data were systematically searched from MEDLINE, Scopus, MedRxiv and BioRxiv.

Eligibility criteria Studies for review were included if they were published in English and reported at least one risk factor and/or one health outcome. We included all relevant literature published up until 11 August 2020.

Data extraction and synthesis We performed a systematic narrative synthesis to describe the available studies for each outcome. Data were extracted using a standardised Joanna Briggs Institute data extraction form.

Results Fifteen articles met the inclusion criteria of which four were exclusively on Africa and the remaining 11 papers had a global focus with some data from Africa. Higher rates of infection in Africa are associated with high population density, urbanisation, transport connectivity, high volume of tourism and international trade, and high level of economic and political openness. Limited or poor access to healthcare are also associated with higher COVID-19 infection rates. Older people and individuals with chronic conditions such as HIV, tuberculosis and anaemia experience severe forms COVID-19 leading to hospitalisation and death. Similarly, high burden of chronic obstructive pulmonary disease, high prevalence of tobacco consumption and low levels of expenditure on health and low levels of global health security score contribute to COVID-19 related deaths.

Conclusions Demographic, institutional, ecological, health system and politico-economic factors influenced the spectrum of COVID-19 infection, severity and death. We recommend multidisciplinary and integrated approaches to mitigate the identified factors and strengthen effective prevention strategies.

  • public health
  • epidemiology
  • respiratory medicine (see thoracic medicine)
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Strengths and limitations of this study

  • Effective public health interventions against the COVID-19 pandemic require strong evidence on the risk factors associated with the disease.

  • The present study is the first African-focused comprehensive systematic review of its kind on a wide range of risk factors associated with the entire spectrum of COVID-19 in the Africa region.

  • Titles and abstracts of all publications identified by the search criteria were screened by two independent reviewers of the team.

  • Full-text articles were appraised using the Joanna Briggs Institute critical appraisal tools.

  • The available data did not allow us to carry out meta-analysis nor firmly establish causal relationships in the present study.

Introduction

The COVID-19 is a recently emerged viral disease caused by a novel single-stranded enveloped RNA (RNA) virus, known as SARS-CoV-2.1 Since the first COVID-19 case was identified in Wuhan province in China, in late December 2019, the virus has rapidly spread across the world and declared a global pandemic on 11 March 2020.2 As of 10 January 2021, the number of confirmed COVID-19 cases in the world has reached over 89.44 million with nearly 1.92 million deaths.3 Despite the late start of the pandemic, infection rate in Africa has been increasing exponentially with a total of 2.95 million confirmed cases and more than 70 thousand deaths as of 10 January 2021.4 The majority of reported cases in Africa were from South Africa and Egypt, while countries in Central Africa had recorded the least.

Given that the pandemic is caused by a novel strain of coronavirus with unknown original host,5 in the early stage of the outbreak, the risk factors associated with its transmission routes, severity and fatality risks were unclear. Several studies have been conducted to better understand the prognosis of the disease, though the level of uncertainty on viral shedding, transmissibility and disease severity remains high.6 Evidence indicates that the susceptibility to infection, being seriously ill and the risk of death are influenced by individual-level characteristics such as sociodemographic factors,7 behavioural traits8 and pre-existing medical conditions.9

While the number of people affected by the virus in Africa remains to be the lowest by global standards, which in part may be linked to the youthful age structure of the population and partly to the limited capacity for large scale testing,10 it is anticipated that the pandemic may have a profound impact in the region. First and foremost, Africa’s health system is fragile. In addition, preventive strategies such as social distancing and hand washing, which have proved effective in reducing transmission in the rest of the world, are less likely to be practical in the region due to prevailing sociocultural and economic circumstances.11 Compared with other regions, Africa is home to a large number of people living in substandard housing, which are mostly dense, inadequately ventilated and have limited access to direct water supply. The way of life in the region is largely communal. People tend to attend weddings, religious and funeral services in large numbers. Such societal and environmental factors along with the lack of awareness and access to preventive measures and the potential for low level of adherence (even when the resources are available) mean that the region will have the highest number of vulnerable populations for COVID-19 infection.12

Many countries have undertaken strict measures such as banning of public gatherings, complete lockdown of social and economic activities and closure of borders to prevent importation of cases.13 The number of new cases, however, continues to rise11 creating considerable pressure on the healthcare system.14 In the absence of effective vaccine or therapy, the ability to effectively control the spread of the pandemic hence depends on effective monitoring of new cases and on better understanding of the factors related to modes of transmission and severity of the disease. A comprehensive systematic review of African-focused COVID-19 related studies is required to strengthen public health measures and response plan against the pandemic in the continent. This review aims to provide a comprehensive evidence on risk factors for transmission, disease severity and COVID-19 related deaths in Africa.

Methods

Australia-based Ethiopian Researchers Network

At the beginning of April, 2020, a time when the COVID-19 pandemic was spreading across the globe, a group of more than 50 Australian-based Ethiopian researchers, who are active academic faculties in Australian institutions along with Ethiopian PhD students, established a working group on ‘Ethiopia and the COVID-19 pandemic’ to examine various dimensions and consequences of COVID-19 in Ethiopia. Specifically, the working group focused on four distinct thematic areas: (1) on understanding the epidemiology of COVID-19 in Ethiopia and around the globe and synthesising the lessons for the country, (2) assessing opportunities for reimagining the health system for COVID-19 pandemic response, (3) identifying potential pharmaceutical and non-pharmaceutical interventions and (4) measuring socioeconomic impact of COVID-19 in Ethiopia to support the Ethiopian government’s effort to mitigate the deadly impact of the pandemic on the population. As part of the project under the first thematic area, we conducted a systematic review to synthesise the available evidence on COVID-19 in Africa on factors affecting infection rates, severity and related deaths.

Search strategy

This systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.15 Potentially eligible articles were systematically searched and retrieved from Medline, PubMed and Scopus up to 11 August 2020. The following search terms, tailored to each database were used: “COVID-19” OR “coronavirus disease” OR “SARS-COV-2” OR “2019 novel coronavirus” OR “2019-nCoV” AND “Africa”. The full search strategy is summarised in online supplemental appendix 1. We used Medical Subject Headings terms to identify synonyms and text words in the appropriate syntax of each database. The search was not limited by date of publication or study design. Reference lists of included studies were manually searched for additional relevant articles. Moreover, preprint articles from the MedRxiv and BioRxiv databases were also accessed to ensure wider coverage. However, search was restricted to studies conducted in Africa and the English language only.

Study selection criteria

The titles and abstracts of all publications identified by the search criteria were screened by two independent reviewers of the team (AAA and BAD) to retrieve full texts for all relevant studies. Full-text articles were appraised using the Joanna Briggs Institute (JBI)16 critical appraisal tools17 (online supplemental appendix 2). All studies published in English and reported at least one risk factor and/or one health outcome were included in the review. We excluded letters to editors, correspondence, editorials and case studies. However, we included global studies that reported findings from any country in Africa.

Sociodemographic, lifestyle and behavioural, climate variables and chronic comorbid conditions, which can be at a community or national level, were considered as risk factors. Whereas COVID-19 infection rates, level of severity and COVID-19 related deaths were considered as outcomes. We adopted the definition of terms as reported in each of the included studies. Severity was referred for cases that required hospitalisation and are at high risk of death.

Data extraction

Seven members of the research team (HG, DNK, DMF, MW, ATG, BAD and AAA) extracted needed data using a standardised JBI data extraction form17 (online supplemental appendix 3). The extracted data included study authors, setting, population characteristics, study design, outcome and main findings on one or more risk factors and reported measure of association between risk factors and outcomes.

Quality and risk of bias assessment in individual studies

The JBI tools17 were used to assess the methodological quality and risk of bias (in design, conduct and analysis) of included studies (online supplemental appendix 2). The tool is used to assess the inclusion criteria, measurement of exposure and outcome variables, confounding adjustment and appropriateness of statistical analysis. All authors who participated in the data extraction also assessed the quality of studies that they extracted.

Data synthesis

A systematic narrative synthesis was conducted to describe the available studies separately for each outcome. Four steps were applied in synthesising the data: (1) reading findings and results of each study systematically and comprehensively and assessing for relevance; (2) developing a preliminary synthesis through describing each included study, grouping findings by infection, severity and death and tabulate results to identify patterns; (3) organise factors linked to the outcomes described in step 2 and thematise items around themes; and (4) explore the relationships of each factor within and among themes. Meta-analysis was not conducted because of the small number of studies identified for selected risk factors.

Patient and public involvement

Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Results

Description of studies

The combined search terms identified 651 records (figure 1). After removing duplicates (n=52) and unrelated studies (n=584), 53 records were eligible for full-text screening. Finally, 15 studies7–9 18–29 met the inclusion criteria and were included in this systematic review. Table 1 presents the main characteristics and outcomes of these studies. Four studies were exclusively on Africa.9 18 21 22 Two studies7 29 assessed susceptibility to COVID-19 infection, nine studies7 9 18 20 22–25 28 evaluated COVID-19 infection, three studies7 19 21 examined severity of COVID-19 infection and four studies8 24 26 27 assessed COVID-19 related death. Four studies assessed more than one outcome.7 21 24 27 As described in table 1, most studies (13) were conducted among the general population. Study designs such as modelling (n=7), cross-sectional (n=2), genetics (n=1), survey (n=4) and spatio-temporal analysis (n=1) were used in the included studies. The number of participants of those included studies for review ranges from 446 to 1.7 billion participants—the studies with the largest sample size were modelling related studies. We have annexed the quality score of all included studies in online supplemental appendix 4.

Table 1

Characteristics of studies (n=15 studies) included in the systematic review

Figure 1

PRISMA flow diagram. Figure 1 describes the flow diagram of the search strategy. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Factors affecting COVID-19 infection, severity and related death

Demographic, institutional, economic, environmental, health system policy, lifestyle and political factors were reported to have an effect on prevention and spread of COVID-19, so were the presence and level of chronic conditions.7–9 18–29 For example, we found that COVID-19 infection and related deaths were affected by political democracy and economic openness as measured by volume of imports of goods and services and international tourism. Furthermore, high rate of comorbid conditions was positively correlated with COVID-19 infection and related death, with people having one or more chronic conditions experiencing severe form of the disease. A detailed summary of all the relevant factors affecting the infection, severity and mortality related to COVID-19 is presented in table 2.

Table 2

Factors associated with COVID-19 infection, severity and related death in Africa

Quality and risk of bias assessment

Detailed results of the methodological quality and risk of bias assessment of individual studies according to the JBI tool are reported in online supplemental appendix 4. In summary, five (34%) studies scored 100%, six (40%) studies scored 80%–89% and three (20%) studies scored 70%–79%. Excluding studies with low scores did not materially change the results.

Discussion

The systematic review presents a comprehensive summary of the current evidence on risk factors of COVID-19 infection, severity and related deaths in Africa. Demographic, institutional, political and ecological factors were linked with high COVID-19 infection rates in Africa. The study also revealed that severe forms of COVID-19 were associated with comorbidities and specific demographic characteristics. Health system organisation and policy, politico-economic situation, prevalence of chronic conditions and lifestyle factors increase the risk of deaths associated with COVID-19.

African countries that heavily rely on international trade and tourism were likely to have higher infection rates than other countries in the region.23 24 As anticipated, the rate of COVID-19 infection was higher among densely populated countries given that the disease is mainly spread through close contact with infected persons.30 31 A similar finding was observed elsewhere.32

African countries enjoying a stable political democracy have an open economy and well-connected air and road network were found to have a higher risk of COVID-19 infection.20 23 This could be attributed to the fact that countries with strong democracy have a laissez-faire administrative system, where people are not obliged to obey and practice some public health measures that may infringe freedom of movement and the pursuit of happiness. Democratic systems also go hand in hand with law and order and a higher than average disposable income, which create opportunities for leisure and work-related travels both internally and internationally, which increase the risk of COVID-19 transmission. In addition, countries with open economies and high transport connectivity are characterised by high mobility, facilitating spread of the disease.

The studies included in this review reported mixed findings with regards to the effect of temperature on COVID-19 infection. For example, the current review indicated that people living in countries with warmer temperature are less likely to acquire infection.23 33 Contrary to this observation, some African countries such as Egypt, which enjoys warm weather through the year, are highly affected by the virus as compared with other African countries with relatively cooler temperature.34 Yao and colleagues, however,35 demonstrated that temperature had no significant association with COVID-19 infection. As highlighted in the study,32 further investigation is required to determine the role of weather on transmission and spread of COVID-19.

Age, particularly being an older person, was associated with more severe forms of COVID-19 at admission to hospital.36 This might be explained by weaker immunity among older people. Patients with coinfections such as TB are more likely to experience severe forms of COVID-19.21 TB infection is common in low-resource settings and among older adults with pre-existing conditions resulting in high vulnerability to severe form of COVID-19 infection.19 37 Evidence on the effect of COVID-19 on people with HIV and malaria is limited.38 A study by Karmen-Tuohy et al39 showed that being infected with HIV at the time of acquiring COVID-19 does not significantly increase the severity of illness or the risk of complications. However, further research is warranted as the available evidence is inconclusive. Most importantly, given the high burden of HIV and malaria in the Africa region, the molecular, genetic, clinical and environmental implications of COVID-19 on people living with HIV and malaria should be explored in greater detail.

Generally, patients with underlining chronic conditions are at a higher risk of having sever COVID-19 and related mortality. For instance, a study conducted by Cox et al38 revealed greater risk and severe forms of COVID-19 in patients with COPD. Findings of a meta-analysis of seven studies conducted in China also reported significant association between COVID-19 and hypertension, chronic respiratory disease and cardiovascular disease.40 These findings imply that countries with a high burden of chronic conditions are more likely to have more severe cases of COVID-19. People who died of COVID-19 had chronic hypertension, COPD and cardiovascular comorbidities than recovered patients.8 41 History of tobacco use was found to be associated with increased risk of COVID-19 death.8 42 Additionally, Zhou and colleagues43 found that 50% of patients who died of COVID-19 had a history of secondary bacterial infections. Chen and colleagues44 also reported that bacterial and fungal coinfections increase the risk of COVID-19 related mortality. Thus, public health and medical services responding to the pandemic in Africa should be equipped with resources that enable the identification of cases with underlining chronic conditions and provide tailored interventions.

The present review revealed that countries with effective healthcare system such as a strong disease prevention, case detection and response programme and have a strong global health security system in pace had lower case fatality rate.27 This was supported by a WHO report that the COVID-19 pandemic is straining health systems worldwide as health facilities have been overstretched and unable to operate effectively due to increased burden for health facilities and healthcare workers.45 Importantly, higher per capita expenditure on health significantly reduces the risk of COVID-19 deaths.26 This could be attributed to the fact that a strong health system with sufficient resources is both adaptive, resilient and often has the required manpower and facilities to respond to the higher demand for medical staff and supplies in treating COVID-19 cases.

The study has the following limitations. First, the results reported in the paper with respect to associated factors do not necessarily imply causality as most of the included studies were based on either cross-country or cross-sectional designs that are not suitable for studying causal relationships. Second, we have used hospital admission as one of the indicators of severity, but this may not be a sufficient criterion given that in some countries, especially in the early stage of the pandemic, all symptomatic patients were systematically hospitalised to avoid transmission. Third, included articles were limited to those written in English. Fourth, there is still limited evidence on COVID-19 in countries Africa (some of the included studies are even preprint and others are modelling based studies), and the review was unable to provide a stratified analysis by regions—authors of the modelling studies have already noted some limitations of the modelling studies. Future research on COVID-19 in the region and beyond should focus on robust epidemiological study designs that are suitable to capture causal relationships and long-term impacts of the disease.

Conclusions

This systematic review demonstrated that several demographic, institutional, political,economic, environmental, lifestyle and health system factors as well as comorbid conditions increased the risk infection, severe forms of COVID-19 and deaths related to the virus in the Africa region. The impacts of these factors should be factored in by African governments and their development partners while designing tailored and targeted interventions to mitigate effects of the disease in the region. Implementing complete lockdown measures for an extended period in African countries is difficult or at least not as easy as in western countries due to the region’s unique social and economic settings. Alternative and effective measures such as mandatory face mask use and strong contact tracing system could be the most feasible interventions to contain the pandemic in the region.46 However, it should be noted that even with a complete adherence to such public health measures, governments can only expect to mitigate the spread of the virus in the region. Eventually, safe and effective vaccines and drugs are required to end this pandemic.

Acknowledgments

We are grateful for the authors of included studies. We did not receive any specific grant for this research.

References

Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Footnotes

  • BAD and AA are joint senior authors.

  • Twitter @Gesesew, @FisahaHaile

  • BAD and AA contributed equally.

  • Contributors HAG, DNK, DMF, MW, YK, ABG, YAM, HM, KAA, MAA, MMB, ATG, YAG, DMS, MDM, TKT, SA, AFA, MBA, AKG, KG, TG, LG, CTL, GDK, MWM, ABM, DYT, AGT, FHT, WT, BLW, BAD and AAA conceived the idea. BAD, DNK and AAA performed search strategy. HAG, DNK, DMF, MW, ATG, BAD and AAA screened and extracted data. DMF and MW drafted introduction, DNK drafted methods, HAG drafted results, and ATG and YAM drafted discussion and conclusion. All authors critically review and approve the manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information. All data relevant to the study are included in the article or uploaded as supplementary information.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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