Self-reported Long COVID and its Determinants in a Rural North Indian Adult Population: Lessons Learnt from the Pandemic
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Most studies on long COVID-19 symptoms (LCSs) are conducted in urban areas or hospital. To date, relevant evidence in LCS from community-based rural studies is lacking. Therefore, the present study aimed to investigate LCS and its determinants in a rural adult population of northern India. Methods: A cross-sectional study was conducted in a rural district, Jhajjar, Haryana in 2023. Forty clusters were covered from one randomly selected subdistrict. A semistructured questionnaire on the SurveyMonkey platform consisted of questions related to sociodemographic profile, health problems, pre-existing morbidity, LCS, and functional difficulties. The data regarding infection with COVID-19 were collected based on self-reported positive testing for SARS-CoV-2 on RT-PCR. Results: Out of the 3700 enumerated, 2954 (79.8%) were surveyed. The self-reported infection rate was 6.2% (183/2954, 95% CI: 5.3–7.1). Further, 23% (42/183, 95% CI: 17.01-29.7) of infected cases have LCS, whereas 1.4% (42/2954) of the study population have LCS. The prevalence of LCS was higher in females than in males (28.7% vs 17.7%). Weakness (14, 33.4%), weight loss (6,14.3%), memory problems (6, 14.3%), and headache (4, 9.5%) were common reported LCSs. Univariable analysis revealed a significantly lower risk of LCS in the age group of 26-35 years (OR 0.32, 95% CI: 0.10-0.83, P = 0.019). In contrast, higher risk was observed with lower education (OR 4.46, 95% CI: 1.47-13.78, P = 0.003), and pre-existing morbidities such as seeing difficulty (OR 2.91, 95% CI: 1.09-7.58, P = 0.021, difficulty in self-care (OR 3.72, 95% CI: 1.07-12.88, P = 0.021), and communication difficulties (OR 5.28, 95% CI: (0.76-45.74, P = 0.046). Conclusion: A higher probability of LCS is found among females of older age, participants with lesser education, and pre-existing comorbidities.
Authors: Suraj Singh Senjam, Garima Bansal, Souvik Manna, Yatan Pal Singh Balhara, Yashdeep Gupta, Animesh Ray, Neiwete Lomi
Institution: All India Institute of Medical Sciences
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $80
OpenAlex ID: W4416167641
