COVID-19 recovery rate and its association with development

Abstract

Objectives: The recovery rate is important to determine a country’s development towards controlling coronavirus. It is a function of myriad factors – death rate, cases requiring hospitalization, quality of care, and discharge policies, among others. India’s recovery rate is growing steadily from an earlier low of 10% to 11%. It is imperative to understand the determinants of recovery rate in a country to enable improvements in the same. Material and Methods: COVID-19 data have been compiled from several sources, including the Ministry of Health and Family Welfare, National Disaster Management Authority, and Indian Council of Medical Research and demographic and health data from Census of India, 2011, National Health Profile, 2019, and were used. The study uses linear regression to understand the relationship between recovery rate and development indicators in India. Results: Our analysis emphasizes the beneficial impacts of the health system and better economy on the recovery rate. Investment in health, urban stay, non-slum and non-poor population, and effective governance is instrumental in improving recovery rate. Conclusion: Scaling up health facilities and medical infrastructure, slum decongestion, focus on economically weaker sections, capacity building of health workers and ameliorating long-term investments in health, health research, and better quality of living are also essential to address recovery of COVID-19.

COVID-19 and Its Long-Term Neurological and Cognitive Implications: A Literature Review

“…This burden eventually influenced patient care, surgeries, and surgical outcomes [20]. The estimated recovery rate for COVID-19 is a function of death rates, cases requiring hospitalization, quality of care, and discharge policies [21]. However, recovery from COVID-19 infection often does not account for PACS, brain fog, and other neurological symptoms of COVID-19; it simply accounts for acquiring a negative PCR test.…”

Time-discrete SIR model for COVID-19 in Fiji

“…In this study, we have used a constant recovery rate, but in reality, recovery rates vary. Factors such as changes in socioeconomic factors, spending levels in medical infrastructure, the proportion of infected elderlies have effects on rates of recoveries [ 35 ]. As patients of different degrees of symptoms present themselves to medical authorities, the recovery rates of these cases will vary as well.…”

SIRSi-vaccine dynamical model for the Covid-19 pandemic

“…and Sansone et al. [75] , [76] ; the initial value for the recovered population was set to 90% of the initial sick population [77] , [78] ; the initial susceptible population was computed as . For the initial guess in the fitting process, bounded random values were considered for each free parameter.…”