COVID-19 Vaccine Effectiveness Against Long-COVID-19 Condition in Pakistan

OBJECTIVE: The objective of this study was to analyze the demographic characteristics, vaccination timing, and associated factors influencing the persistence or onset of long-COVID-19 symptoms among patients. METHODS: Data were collected anonymously from the Abbas Institute of Medical Sciences, with patients required to meet specific criteria, including having encounters with healthcare providers both before and after January 1, 2023. Patients diagnosed with COVID-19 were identified using ICD-9 or ICD-10 codes or positive test results. Long-COVID-19 cases were defined as those exhibiting symptoms 12-20 weeks post-diagnosis. Logistic regression and general linear models were employed to identify factors influencing long-COVID-19 outcomes, considering vaccination timing and demographic characteristics. RESULTS: The analysis involved 3,140 patients diagnosed with long-COVID-19. Results revealed significant associations between demographic characteristics and long-COVID-19 outcomes. Males exhibited higher odds compared to females, with younger age groups and individuals of Punjabi ethnicity showing increased odds of experiencing long-COVID-19 symptoms. However, no significant association was found between vaccination status and long-COVID-19 outcomes. Logistic regression analysis showed varying odds ratios associated with vaccination timing post-diagnosis, with notable increases observed within 0-4 weeks and 4-8 weeks post-diagnosis. The general linear model further confirmed these associations, highlighting the significance of age, gender, ethnicity, and comorbidities in predicting long-COVID-19 outcomes. CONCLUSION: The study underscores the importance of demographic factors and vaccination timing in understanding and predicting long-COVID-19 outcomes. These findings can inform targeted interventions and healthcare strategies aimed at mitigating the impact of long-COVID-19 and improving patient care and management. Further research is warranted to explore additional factors contributing to long-COVID-19 and to validate these findings in larger and more diverse populations.