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DOI 10.3389/fpubh.2025.1416273

Медицинская библиотека · Frontiers in public health · 2025

Deep learning analysis of long COVID and vaccine impact in low- and middle-income countries (LMICs): development of a risk calculator in a multicentric study.

Shaheen Ahmed, Shaheen Nour, Long COVID Collaboration Study Group in the LMICs, Shoib Sheikh, Saeed Fahimeh, Buhari Mudathiru, Bharmauria Vishal, Flouty Oliver

СтатьяМногоцентровое исследованиеНаблюдательное исследованиеПеревод в очереди

Аннотация

BACKGROUND

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global pandemic affecting millions worldwide. This study aims to bridge the knowledge gap between acute and chronic symptoms, vaccination impact, and associated factors in patients across different low- and middle-income countries (LMICs).

MATERIALS AND

METHODS

The study included 2,445 participants aged 18 years and older, testing positive for COVID-19. Data collection involved screening for medical histories, testing records, symptomatology, and persistent symptoms. Validated instruments, including the DePaul Symptom Questionnaire (DSQ-2) and the Patient Health Questionnaire-9 (PHQ-9), were used. We applied a self-supervised and unsupervised deep neural network to extract features from the questionnaire. Gradient boosted machines (GBM) model was used to build a risk calculator for chronic fatigue syndrome (CFS), depression, and prolonged COVID-19 symptoms.

RESULTS

Out of the study cohort, 68.1% of the patients had symptoms lasting longer than 2 weeks. The most frequent symptoms were loss of smell (46.8%), dry cough (40.1%), loss of taste (37.8%), headaches (37.2%), and sore throat (28.9%). The patients also reported high rates of depression (47.7%), chronic fatigue (6.5%), and infection after vaccination (23.7%). Factors associated with CFS included sex, age, and smoking. Vaccinated individuals demonstrated lower odds of experiencing prolonged COVID-19 symptoms, CFS, and depression. The predictive models achieved a high area under the curve (AUC) scores of 0.87, 0.82, and 0.74, respectively.

CONCLUSION

The findings underscore the significant burden of long-term symptoms such as chronic fatigue and depression, affecting a considerable proportion of individuals post-infection. Moreover, the study reveals promising insights into the potential benefits of vaccination in mitigating the risk of prolonged COVID-19 symptoms, CFS, and depression. Overall, this research contributes valuable knowledge towards comprehensive management and prevention efforts amidst the ongoing global pandemic.

CLINICAL TRIAL REGISTRATION: Clinical trials.gov, NCT05059184.

Для цитирования: Shaheen Ahmed, Shaheen Nour, Long COVID Collaboration Study Group in the LMICs, Shoib Sheikh, Saeed Fahimeh, Buhari Mudathiru, Bharmauria Vishal, Flouty Oliver. Deep learning analysis of long COVID and vaccine impact in low- and middle-income countries (LMICs): development of a risk calculator in a multicentric study.. Frontiers in public health. 2025. DOI: 10.3389/fpubh.2025.1416273.

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