COVID-19 disease severity and associated factors among Ethiopian patients: A study of the millennium COVID-19 care center

  1. Tigist W. Leulseged
  2. Kindalem G. Abebe
  3. Ishmael S. Hassen
  4. Endalkachew H. Maru
  5. Wuletaw C. Zewde
  6. Negat W. Chamiso
  7. Kalkidan T. Yegele
  8. Abdi B. Bayisa
  9. Dagne F. Siyoum
  10. Mesay G. Edo
  11. Edmialem G. Mesfin
  12. Meskerem N. Derejie
  13. Helina K. Shiferaw

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Abstract

The COVID-19 pandemic started a little later in Ethiopia than the rest of the world and most of the initial cases were reported to have a milder disease course and a favorable outcome. This changed as the disease spread into the population and the more vulnerable began to develop severe disease. Understanding the risk factors for severe disease in Ethiopia was needed to provide optimal health care services in a resource limited setting.

Objective

The study assessed COVID-19 patients admitted to Millennium COVID-19 Care Center in Ethiopia for characteristics associated with COVID-19 disease severity.

Methods

A cross-sectional study was conducted from June to August 2020 among 686 randomly selected patients. Chi-square test was used to detect the presence of a statistically significant difference in the characteristics of the patients based on disease severity (Mild vs Moderate vs Severe). A multinomial logistic regression model was used to identify factors associated with COVID-19 disease severity where Adjusted Odds ratio (AOR), 95% CIs for AOR and P-values were used for significance testing.

Results

Having moderate as compared with mild disease was significantly associated with having hypertension (AOR = 2 . 30 , 95%CI = 1 . 27 , 4 . 18) , diabetes mellitus (AOR = 2 . 61 , 95%CI = 1 . 31 , 5 . 19for diabetes mellitus) , fever (AOR = 6 . 12 , 95%CI = 2 . 94 , 12 . 72) and headache (AOR = 2 . 69 , 95%CI = 1 . 39 , 5 . 22) . Similarly, having severe disease as compared with mild disease was associated with age group (AOR = 4 . 43 , 95%CI = 2 . 49 , 7 . 85 for 40–59 years and AOR = 18 . 07 , 95%CI = 9 . 29 , 35 . 14for ≥ 60 years) , sex ( AOR = 1 . 84 , 95%CI = 1 . 12 , 3 . 03) , hypertension (AOR = 1 . 97 , 95%CI = 1 . 08 , 3 . 59) , diabetes mellitus (AOR = 3 . 93 , 95%CI = 1 . 96 , 7 . 85) , fever (AOR = 13 . 22 , 95%CI = 6 . 11 , 28 . 60) and headache (AOR = 4 . 82 , 95%CI = 2 . 32 , 9 . 98) . In addition, risk factors of severe disease as compared with moderate disease were found to be significantly associated with age group (AOR = 4 . 87 , 95%CI = 2 . 85 , 8 . 32 for 40–59 years and AOR = 18 . 91 , 95%CI = 9 . 84 , 36 . 331 for ≥ 60 years) , fever (AOR = 2 . 16 , 95%CI = 1 . 29 , 3 . 63) and headache (AOR = 1 . 79 , 95%CI = 1 . 03 , 3 . 11) .

Conclusions

Significant factors associated with severe COVID-19 in Ethiopia are being older than 60 years old, male, a diagnosis of hypertension, diabetes mellitus, and the presence of fever and headache. This is consistent with severity indicators identified by WHO and suggests the initial finding of milder disease in Ethiopia may have been because the first people to get COVID-19 in the country were the relatively younger with fewer health problems.

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  1. Version published to 10.1371/journal.pone.0262896
  2. ScreenIT

    SciScore for 10.1101/2020.10.09.20209999: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationThe data collection tool was pretested on 5% of randomly selected patients and their medical charts which were not included in the final data collection and necessary amendment on the data collection tool was made.
    Blindingnot detected.
    Power AnalysisSample Size Determination and Sampling Technique: The sample size to identify determinants of disease severity was determined using a double population proportion formula with the assumptions of; 95% confidence interval, power of 80%, the proportion of males who had severe disease as 0.80, proportion of females who had non-severe disease as 0.75 and considering a non-response rate of 10%.
    Sex as a biological variableSample Size Determination and Sampling Technique: The sample size to identify determinants of disease severity was determined using a double population proportion formula with the assumptions of; 95% confidence interval, power of 80%, the proportion of males who had severe disease as 0.80, proportion of females who had non-severe disease as 0.75 and considering a non-response rate of 10%.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data Management and Analysis: The extracted data were coded, entered into Epi-Info version 7.2.1.0, cleaned, stored, and exported to SPSS version 23.0 software for analysis.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.10.09.20209999 on medRxiv