BMC Public Health (Sep 2024)

Disparities in age and gender-specific SARS-CoV-2 diagnostic testing trends: a retrospective study from Pakistan

  • Najia Karim Ghanchi,
  • Kiran Iqbal Masood,
  • Muhammad Farrukh Qazi,
  • Shahira Shahid,
  • Asghar Nasir,
  • Syed Faisal Mahmood,
  • Zeeshan Ansar,
  • Muhammad Imran Nisar,
  • Zahra Hasan

DOI
https://doi.org/10.1186/s12889-024-19958-w
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 7

Abstract

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Abstract Background Pakistan reported 1.57 million COVID-19 cases between 2020 and 2022, based on approximately 30.6 million SARS-CoV-2 RT-PCR (reverse-transcription polymerase chain reaction) tests conducted. This study utilized data from one of the largest in-country testing facilities, Aga Khan University Hospital (AKUH) in Karachi, Pakistan, to explore gender and age-related in RT-PCR testing patterns. Methods We conducted a retrospective review of SARS-CoV-2 RT-PCR test data extracted from AKUH clinical laboratory records between February 2020 and February 2022. Gender and age distributions were examined in the context of testing patterns across the period. Multivariate regression models assessed independent associations between COVID-19 positivity and key variables. Results We reviewed 470,249 RT-PCR tests, finding that most tests were in those aged 21–40 years (48.1%). Overall, COVID-19 test positivity was 20.6%. In all, 57.7% were performed for males, predominant amongst those tested across all age groups and waves. Females had significantly lower odds of testing positive for COVID-19 (OR: 0.9; 95% CI: 0.9-1.0). However, when adjusted for gender, age and pandemic phases, the positivity rates between males and females were the same. The odds of a positive result increased significantly with age; individuals aged > 80 years had 2.5 times higher odds of testing positive than those aged 0–10 years (aOR 2.5, 95% CI 2.3–2.7). Conclusions The analysis indicates a consistent male dominance in COVID-19 testing, with higher positivity rates in older age groups. Our study highlight the importance of examining demographic characteristics in disease associated data especially, representation of females amongst cohorts.

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