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

Abstract

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.

Keywords: COVID-19; LMICs; chronic fatigue syndrome; depression; hospitalization; long COVID; post-acute sequelae; vaccination.

Figure 1

Geographic distribution of patients by country. Color gradient interpretation: yellow-green: highest number of patients (>600). Teal-blue: moderate number of patients (200–600). Dark purple: lowest number of patients (<200). Geographic representation: highest patient representation: Egypt, Pakistan, Syria, India. Moderate representation: Afghanistan, Iran, Libya, Yemen. Lower representation: Algeria, West Bank and Gaza, UAE, Turkey, Qatar, Sudan.

Figure 2

Reported Symptoms of COVID-19 Infection. The horizontal bar chart illustrates the prevalence of various reported symptoms among individuals with COVID-19. Each bar represents the percentage of participants who reported experiencing the given symptom. The number beside the bar indicates the number of cases representing that percentage.

Figure 3

Receiver Operating Characteristic (ROC) Curves for Prediction Models. ROC curves for three predictive models evaluating (A) symptom duration, (B) chronic fatigue, and (C) depression. The models compared include AutoML (red), GBM (green), and GBM grid ensemble (blue). The x-axis represents the false positive rate, and the y-axis represents the true positive rate.