Seroprevalence and Risk Factors of Cytomegalovirus Infection among Healthy Sudanese Blood Donors Attending Central Blood Banks in Khartoum State
Description
A cross-sectional dataset comprising 400 blood donors from the Central Blood Bank in Khartoum State, Sudan, collected between July and December 2022, was analyzed. The dataset includes demographic, occupational, and clinical variables as well as serological results for Cytomegalovirus (CMV) antibodies. The key variables are summarized as follows: Age group: Donors were classified into four groups: ≤25 years (33.0%), 26–35 years (40.5%), 36–45 years (18.5%), and ≥46 years (8.0%). Gender: Predominantly male donors (90.8%), with female donors comprising 9.2%. Occupation: Categories included Unemployed (2.5%), Students (25.5%), Skilled Professionals (32.5%), Self-Employed (35.8%), and Workers (3.8%). Residence: Donors resided in Khartoum (37.5%), Omdurman (32.8%), Bahri (27.5%), or other cities (2.3%). Donor type: Family donors represented 54.5%, while voluntary donors accounted for 45.5%. Blood group: Distribution was A (28.0%), B (25.3%), AB (1.8%), and O (45.0%). Serological results: CMV IgG positivity was observed in 27.5% of donors, indicating prior exposure, and CMV IgM positivity in 10.0%, indicating recent or reactivated infection. Additional serological screening included HBV (1.8%) and Syphilis (2.3%). The dataset allows investigation of associations between CMV serostatus and demographic, occupational, and clinical factors using chi-square tests and multivariate logistic regression, consistent with standard epidemiological practices for transfusion-transmissible infections. A cross-sectional study of 400 blood donors at the Central Blood Bank in Khartoum assessed Cytomegalovirus (CMV) IgG and IgM seroprevalence. Donors were aged 18–60 years, predominantly male (90.8%), with data on age, gender, occupation, residence, donor type, and blood group. CMV IgG was positive in 27.5% and IgM in 10.0% of donors. Chi-square analysis showed no significant association between CMV seropositivity and age, gender, occupation, residence, or blood group (p > 0.05). Multivariate logistic regression indicated that family donors had lower odds of IgM positivity compared with voluntary donors (OR 0.48; 95% CI 0.24–0.98; p = 0.043), while no variables predicted IgG positivity. These results demonstrate a considerable prevalence of past and recent CMV infection among healthy donors, highlighting the risk of transfusion-transmitted CMV. Selective CMV screening and leukoreduction strategies are recommended to improve transfusion safety. Analyses were conducted using Python (pandas, scipy, statsmodels), with significance set at p < 0.05.
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Steps to reproduce
Steps to Reproduce Data Preparation: Load the raw dataset (CMV_Raw_400_Donors.csv) using pandas. Inspect for missing values and correct data types. Encode categorical variables as needed (e.g., gender, age group, occupation, donor type, blood group). Descriptive Analysis: Calculate frequencies and percentages for all categorical variables. Summarize CMV IgG and IgM seropositivity overall and stratified by donor characteristics. Bivariate Analysis: Perform Chi-square tests (or Fisher’s exact test if expected counts <5) to assess associations between CMV serostatus and donor variables. Multivariate Analysis: Fit logistic regression models for CMV IgG and IgM seropositivity using statsmodels or sklearn. Include predictors with p < 0.20 in bivariate analysis. Report odds ratios (ORs), 95% confidence intervals (CIs), and p-values. Visualization: Plot seropositivity by age, gender, occupation, and donor type using bar plots or stacked charts (seaborn or matplotlib). Optional: Create forest plots for logistic regression ORs. Statistical Significance: Consider p < 0.05 as statistically significant. Interpret results in the context of transfusion safety and CMV risk factors. Software Requirements: Python 3.x Libraries: pandas, numpy, scipy, statsmodels, matplotlib, seaborn
Institutions
- Omdurman Islamic University Faculty of Medicine and Health Sciences
- Research Institute for Tropical Medicine