A Method of Estimating Time-to-Recovery for a Disease Caused by a Contagious Pathogen Such as SARS-CoV-2 Using a Time Series of Aggregated Case Reports.

During the outbreak of a disease caused by a pathogen with unknown characteristics, the uncertainty of its progression parameters can be reduced by devising methods that, based on rational assumptions, exploit available information to provide actionable insights. In this study, performed a few (~6) weeks into the outbreak of COVID-19 (caused by SARS-CoV-2), one of the most important disease parameters, the average time-to-recovery, was calculated using data publicly available on the internet (daily reported cases of confirmed infections, deaths, and recoveries), and fed into an algorithm that matches confirmed cases with deaths and recoveries. Unmatched cases were adjusted based on the matched cases calculation. The mean time-to-recovery, calculated from all globally reported cases, was found to be 18.01 days (SD 3.31 days) for the matched cases and 18.29 days (SD 2.73 days) taking into consideration the adjusted unmatched cases as well. The proposed method used limited data and provided experimental results in the same region as clinical studies published several months later. This indicates that the proposed method, combined with expert knowledge and informed calculated assumptions, could provide a meaningful calculated average time-to-recovery figure, which can be used as an evidence-based estimation to support containment and mitigation policy decisions, even at the very early stages of an outbreak.

Effectiveness of Favipiravir monotherapy in the treatment of COVID-19: real world data analysis from Thailand.

Background: Previous studies showed that Favipiravir, a selective viral ribonucleic acid dependent-ribonucleic acid polymerase inhibitor, exhibited a trend of clinical improvement within 14 days and promoted viral clearance by day 7, without reduction of mortality rate in COVID-19. Methods: During the COVID-19 pandemic, Department of Medical Services (Thailand) formulated National Clinical Treatment Guidelines for COVID-19 and approved Favipiravir to eight medical centres. After treatment with Favipiravir monotherapy, we compared real-world data analysis to supportive treatment without antiviral agents. Findings: We analysed 12,888 COVID-19 patients between June 1, 2021, and July 31, 2021. This group study excluded 66 asymptomatic and 4634 COVID-19 patients treated with other antiviral agents. The 4896 mild, 2357 moderate, and 935 severe COVID-19 patients were analysed. All patients neither had previous SARS-CoV-2 infection nor received an mRNA vaccine during study period. Favipiravir monotherapy reduced the 28-day mortality risk in severe COVID-19 by relative risk (RR) = 0.72 (95% CI 0.58-0.91 P = 0.006) after adjustment for aging and hypertension. However, in mild and moderate COVID-19, Favipiravir monotherapy did not significantly reduce 28-day mortality risk by RR = 0.59 (95% CI 0.06-5.43 P = 0.65) after adjustment for aging, and RR = 0.60 (95% CI 0.32-1.13 P = 0.11) after adjustment for aging and obesity, respectively. In the patient with recovery, Favipiravir monotherapy exhibited a shortening time to recovery when compared to supportive treatment without antiviral agents (mean ± SD by 9.6 ± 7.1 vs. 12.9 ± 7.6 days: P < 0.0001, 10.0 ± 5.9 vs. 12.4 ± 5.3 days: P < 0.0001, and 11.2 ± 7.8 vs. 13.1 ± 8.0 days: P < 0.0001 in mild, moderate, and severe COVID-19 respectively). Interpretation: Real-world data analysis showed that favipiravir monotherapy was superior to supportive treatment without antiviral agents in shortening the recovery time in surviving patients and significantly reducing 28-day mortality risk in severe COVID-19. Funding: Department of Medical Services, Ministry of Public Health, Thailand.

Advancing combination treatment with glycyrrhizin and boswellic acids for hospitalized patients with moderate COVID-19 infection: a randomized clinical trial.

Recent evidence points to a potential therapeutic role for glycyrrhizin(GR) and boswellic acids (BA) in the treatment of COVID-19 but conclusive evidence is lacking. Our aim is to investigate the efficacy of GR + BA versus placebo for the treatment of hospitalized patients with moderate SARS-CoV-2 or COVID-19 variants infection. The current study is a randomized, double-blind, placebo-controlled, single-center trial. Patients with SARS-CoV-2 or COVID-19 variants diagnosed by PCR test who were admitted to Sohag University hospital were eligible if they were at least 18 years of age and had moderate symptoms. Patients were randomly assigned to receive oral GR capsule (60 mg) and BA (200 mg) twice daily for 14 days or a matching placebo. All patients also received treatment with the institutional protocol for COVID-19. The primary outcome was mortality and time to recovery. Secondary outcome was clinical status score, 14 days after receiving study drugs. Adverse events from use of study drugs have been evaluated for up to 14 days. The trial is registered at ClinicalTrials.gov (Identifier NCT04487964). During the 6-month enrollment period (June-November, 2021) only 50 patients (54% women; median age 60 years, IQR 54-65) met eligibility and were randomly assigned. Evaluation of the primary outcome at 14 days showed that there were five deaths in the placebo group and no deaths in the GR + BA group. With regard to recovery time, it was significantly shorter (p = 0.0001) in the group receiving GR + BA capsule compared to the placebo group (median 7.0; IQR 6.0-8.0 days vs. median 12.5; IQR 12-20 days). Clinical status on the ordinal score scale as a secondary outcome showed a significant difference between the GR + BA group (median (IQR) score, 2 [2-3]) and placebo groups (mean (IQR) score, 3 [3-5.5]). There was a significant decrease in CRB (p = 0.000041) in GR + BA compared with the placebo group. In conclusion, this safe, inexpensive, antiviral, immunomodulating and anti-inflammatory combination may be considered for use in mild to moderate infections of SARS-CoV-2 or COVID-19 variants. The study is limited by the small sample size; therefore, larger randomized trials are required.

Time to recovery and its predictors among COVID-19 positive patients admitted to treatment centers of Southwestern Ethiopian hospitals. A multicenter retrospective cohort study.

Background: Nowadays, coronavirus disease is a leading cause of death. Therefore, the study aimed to assess the time to recovery and its predictors among Covid-19 positive patients. Methods: A hospital-based retrospective cohort study was conducted among 300 COVID-19 patients admitted to Southwestern Ethiopian hospital COVID-19 treatment centers from August 7, 2020 to February 7, 2022. Kaplan Meier was used to estimate the survival time and the Log-rank test was used to compare the survival time between groups of categorical variables. The multivariable survival regression model was used to identify a significant predictor of time to recovery among COVID-19 patients at a P value â©½ 0.05 with a 95% CI. Result: In this study, 92% of patients admitted to Jimma University COVID-19 treatment center and Mettu Karl Comprehensive Specialized Hospital COVID-19 treatment center were recovered from COVID-19 after a maximum of 33 days of follow-up. The overall incidence density was 11.99/100 PD (person day) with a 95% CI of [11.273, 12.719] per 100 PD after a total of 3452 PD observations. The median time of recovery from COVID-19 was 10 days. Age (AHR = 1.945, 95% CI: 1.157, 3.268), hypertension (AHR = 1.856, 95% CI, 1.30, 2.63), diabetes (AHR = 1.406, 95% CI, 1.05, 1.84), being critical (0.298, 2039, 0.434), cancer (AHR = 3.050, 95% CI, 1.172, 7.943), and tuberculosis (AHR = 2.487, 95% CI, 1.504, 4.110) were found to be independent predictors of time to recovery of COVID-19 patients. Conclusion: A total of 92% of patients were recovered within 10 days of the median time. Age, hypertension, diabetes mellitus, tuberculosis, severity of the case, cancer, and the presence of acute kidney injury were predictors of recovery time of COVID-19 patients. Therefore, healthcare providers should give strict follow-up and priority to elderly patients with chronic illnesses and those under supportive care.

Time to Recovery from Covid-19 and Its Predictors Among Patients Admitted to Treatment Centers of Southern Nations Nationalities and Peoples Region (SNNPR), ETHIOPIA: Multi-Center Retrospective Cohort Study.

Background: The world is currently facing a pandemic of Coronavirus Disease 2019 (Covid-19). It has caused significant morbidity and mortality. So far little is known about recovery time (prolonged hospital stay) from Covid-19 and its determinants in Ethiopia as well as in the study area. Therefore, the aim of this study was to determine time to recovery from Covid-19, and identify predictors of time to recovery among patients admitted to treatment centers of Southern Nations Nationalities and Peoples Region (SNNPR). Methods and Materials: A facility-based retrospective cohort study was conducted among Covid-19 patients admitted to care centers of SNNPR from May 30, 2020 to October 15, 2021. A sample of 845 patients was included in the study. Summarization of the data was done using mean (standard deviation) and median (inter quartile range). Kaplan-Meier Survival Curve was used to estimate recovery time from Covid-19 and the independent effects of covariates on recovery time was analyzed using multivariable Cox-proportional hazard model. Results: The incidence density of recovery was 8.24 per 100 person-days (95% CI: 7.67, 8.85). The overall median recovery time was 10 days (IQR: 8-16 days). Critical stage of Covid-19 (aHR = 0.19, 95% CI: 0.12, 0.29), severe stage of Covid-19 (aHR = 0.40, 95% CI: 0.29, 0.56), mechanical ventilation (aHR = 0.20, 95% CI: 0.073, 0.56) and treatment center (aHR = 0.68, 95% CI: 0.51, 0.90) were significant predictors of recovery rate among Covid-19 patients. Conclusion: The median time to recovery from Covid-19 was relatively short. The incidence density of recovery was 8.24 per 100 person-days. The hazard of recovery was lower for patients at higher levels of Covid-19 severity and for patients in need of mechanical ventilation. Early identification of severity levels of the patients is required at the time of admission. Special attention, critical follow-up and management is warranted for patients at higher levels of Covid-19 severity.

Predictors and time to recovery from COVID-19 among patients attended at the treatment centers in Ekiti State, South West, Nigeria.

Introduction: time to clinical recovery from COVID-19 infection and associated factors has not been explored in Nigeria. This study was conducted to assess the predictors and time to recovery from COVID-19 among patients attended to at the treatment centers in Ekiti State, South West. Methods: a facility-based retrospective cohort study was conducted between March 2020 to October 2021. Laboratory confirmed COVID-19 positive test result of 586 patients receiving treatment at the treatment centres in Ekiti were included. Data were extracted from COVID-19 intake forms and medical records of patients. Data were analysed using descriptive statistics and survival analysis methods including Cox proportional hazards regression model. Level of significance was set at 5%. Results: the mean age of the patients was 43.46 (SD 0.74) years. Forty-seven percent (47%) of the patients were aged 25-44 years, fifty-one percent (51%) were males. The median recovery time of COVID-19 patients was 21 days (IQR: 14-23). Being a male-patient (95% CI 20.46-21.54), older age (95% CI 20.14-21.86), not admitted in the hospital (95% CI 22.74-23.26), and associated multiple co-morbidities (95% CI 17.65-28.35) were associated with delayed recovery time. Predictors of recovery time of patients from COVID-19 infection were admission status (aHR: 0.71, 95%CI 0.56-0.88; p=0.002) and symptoms on admission (aHR: 0.81, 95%CI 0.66-0.99; p=0.020). Conclusion: patients with comorbidities, older and those not admitted were more likely to have a delayed clinical recovery from COVID-19. Knowledge of the predictors might help health professionals in risk stratification and better management of patients with COVID-19.