Sociodemographic, economic, physical, and mental health status of previously hospitalised patients with COVID-19 symptoms in Bangladesh: Protocol for a mixed-method study

INTRODUCTION: Not much is known about the long-term consequences of COVID-19, popularly known as long COVID. This is particularly so in terms of patterns and clusters of symptoms over time, sociodemographic and economic characteristics of patients, and related clinical history. This is crucial for resource-constrained health systems such as Bangladesh to address long COVID as a forthcoming challenge. This protocol aims to investigate the consequences of COVID-19 over time for physical and mental health and how these are associated with demographic and socio-economic factors. METHODS AND ANALYSIS: This mixed-method study collected information on all patients with symptoms of COVID-19 admitted to and discharged after recovery from a COVID-19-dedicated hospital in Bangladesh (N = 942), from April to December 2020. The sources of data were admission records and discharge certificates from the hospital for clinical history, cross-sectional survey on physical and mental health (assessed by DASS21 scale)-related symptoms and socioeconomic changes after recovery, and qualitative in-depth interviews on experiences of COVID-19. Interviews were conducted over the phone. Quantitative analysis was done to estimate the prevalence of physical and mental health consequences of COVID-19 after recovery and the association with socio-economic and demographic information. The qualitative analysis was performed using a thematic analysis approach. DISCUSSION: It is imperative to understand the post-COVID consequences and related health and non-health aspects to inform evidence-based policymaking, especially for resource-poor contexts such as Bangladesh. Given the dearth of evidence in this regard, the proposed study will contribute to bridging this knowledge gap. It is important to note that this study is one of the few which presents information on post-COVID-19 consequences in the context of low- and middle-income countries and the first in Bangladesh.