key: cord-0779182-grqij11o
authors: ALIMOHAMADI, YOUSEF; TOLA, HABTEYES HAILU; ABBASI-GHAHRAMANLOO, ABBAS; JANANI, MAJID; SEPANDI, MOJTABA
title: Case fatality rate of COVID-19: a systematic review and meta-analysis
date: 2021-07-30
journal: J Prev Med Hyg
DOI: 10.15167/2421-4248/jpmh2021.62.2.1627
sha: abbfd0e97811ebd36c1cbb41b0042125efb38d0a
doc_id: 779182
cord_uid: grqij11o

OBJECTIVE: The ongoing novel coronavirus disease 2019 (COVID-19) is the leading cause of morbidity and mortality due to its contagious nature and absence of vaccine and treatment. Although numerous primary studies reported extremely variable case fatality rate (CFR) of COVID-19, no review study attempted to estimate the CFR of COVID-19. The current systematic review and meta-analysis were aimed to assess the pooled CFR of COVID-19. METHODS: Electronic databases: PubMed, Science Direct, Scopus, and Google Scholar were searched to retrieve the eligible primary studies that reported CFR of COVID-19. Keywords: (“COVID-19”OR “COVID-2019” OR “severe acute respiratory syndrome coronavirus 2”OR “severe acute respiratory syndrome coronavirus 2” OR “2019-nCoV” OR “SARS-CoV-2” OR “2019nCoV” OR ((“Wuhan” AND (“coronavirus” OR “coronavirus”)) AND (2019/12[PDAT] OR 2020[PDAT]))) AND (“mortality “OR “mortality” OR (“case” AND “fatality” AND “rate”) OR “case fatality rate”) were used as free text and MeSH term in searching process. A random-effects model was used to estimate the CFR in this study. I(2) statistics, Cochran’s Q test, and T(2) were used to assess the functional heterogeneity between included studies. RESULTS: The overall pooled CFR of COVID 19 was 10.0%(95% CI: 8.0-11.0); P < 0.001; I(2) = 99.7). The pooled CFR of COVID-19 in general population was 1.0% (95% CI: 1.0-3.0); P < 0.001; I(2) = 94.3), while in hospitalized patients was 13.0% (95% CI: 9.0-17.0); P < 0.001, I(2) = 95.6). The pooled CFR in patients admitted in intensive care unit (ICU) was 37.0% (95% CI: 24.0-51.0); P < 0.001, I(2) = 97.8) and in patients older than 50 years was 19.0% (95% CI: 13.0-24.0); P < 0.001; I(2) = 99.8). CONCLUSION: The present review results highlighted the need for transparency in testing and reporting policies and denominators used in CFR estimation. It is also necessary to report the case’s age, sex, and the comorbidity distribution of all patients, which essential in comparing the CFR among different segments of the population.

The ongoing coronavirus 2019 (COVID-19) was initially reported from Wuhan, China, in December 2019. After few weeks, it has been involved in several countries and became a significant global public health problem [1] [2] [3] . World Health Organization (WHO) designated COVID-19 as a pandemic disease on March 11, 2020 (WHO, situational Report-52). The most known symptoms of COVID-19 are fever, cough, shortness of breathing, and occasional watery diarrhea [4] . Even though COVID-19 often causes mild symptoms compared to other respiratory infections, it can cause severe illness in certain groups of people, such as the elderly and people with major underlying health problems (cardiovascular disease and diabetes) [5] . There are two key parameters to understand the epidemiological features of an outbreak or epidemic. These are primary reproduction numbers (R 0 ) and casefatality rates (CFR) [6, 7] . The R 0 is an epidemiologic metric that has been used to assess the infectiveness of the agents that cause an outbreak. This index explains the average number of new cases generated from an infected person. The higher amount of R 0 indicates the highest transmissibility of the infection agent. An estimated R 0 of the COVID-19 virus is 3.32, which means one infected case can transmit the virus to 3 to 4 susceptible individuals [8] . CFR is another essential index that helps to understand the epidemiological characteristics of an outbreak. The CFR of COVID-19 is defined as the number of deaths in COVID-19 cases divided by the total number of people infected by COVID-19 [9] . Previously reported CFR of COVID-19 is highly variable. The primary cause of this heterogeneity could be varied as a result of surveillance systems sensitivity. Surveillance system sensitivity low due to more than 80% of cases does not show symptoms of the disease or show mild symptoms. Thus, cases missed by the surveillance system are not considered in the denominator and could lead to overestimation of CFR [10, 11] . Several primary studies have been conducted to estimate the CFR of COVID-19 across the world and reported extremely heterogeneous

Cochran's Q test's heterogeneity in the CFR of COVID-19 between different studies was assessed with a significance level of P < 0.1 and I 2 statistic with values > 75% [12] . A random-effects meta-analysis model was used to estimate pooled CFR because of the presence of high heterogeneity (I 2 = 99.7% and Cochran's Q (p < 0.001). The univariate metaregression model was used to assess the effect of sample size on the heterogeneity of pooled CFR. Publication bias was evaluated by Beggs and Eggers tests. Also, the risk of bias analysis performed using the Newcastle-Ottawa Scale for observational studies [13] . Data were analyzed by STATA v 11 (StataCorp, College Station, TX, USA). Figure 1 depicts the study selection procedure. A total of 516 records were retrieved through electronic databases search, and 324 identified articles after removing 192 pieces due to duplication and irrelevance for the review purpose. The second stape 236 articles were excluded after the title and abstract screeded for the inclusion and exclusion criteria. Of the remaining 88 articles, 49 articles were excluded due to a lack of relevant information or not original articles. Finally, 39 articles reported CFR of COVID-19 were included in the final analysis ( Fig. 1 and Table 1 ). The Median and IQR( Interquartile range) of reported CFR rate were 8.7%(23.0-1.0). The Minimum and Maximum reported CFR were 0 and 70.6% respectivly (Fig. 2) . The overall pooled estimated CFR of COVID-19 was 10.0% (95% CI: 8.0-11.0; P < 0.001, I 2 = 99.7) (Fig. 2) . The pooled estimated CFR of COVID-19 among general population was 1.0% (95% CI: 1.0-3.0; P < 0.001, I 2 = 94.3), while in hospitalised patients 13.0% (95% CI: 9.0-17.0; P < 0.001, I 2 = 95.6) (Fig. 2) . The pooled estimated CFR of COVID-19 in the patients admited to ICU was 37.0% (95% CI: 24.0-51.0; P < 0.001, I 2 = 97.8), and in patients younger than 50 years 3.0% (95% CI: 0.0-6.0; P < 0.001, I 2 = 99.2), while the CFR was 19.0% (95% CI: 13.0-24.0; P < 0.001, I 2 = 99.8) in patients older than 50 years (Fig. 2 and Table 2 ). Based Tab. I. Included studies in the current meta-analysis. on Beggs test there was no publication bias(P = 0.2), but the Eggers tests was shown the presence of publication bias (P < 0.001). Moreover, based on metaregresion regression analysis, ample size was not significantly associated with heatrogeneity of pooled estimated CFR (P = 0.31) (Fig. 3 ).

The present study systematically reviewed the available literature to estimate the overall pooled CFR COVID-19 and specific subpopulations in patients admitted in hospital, ICU, and old. Based on 39 studies that fulfilled this study, the overall estimated pooled CFR of COVID-19 was 10.0%. The pooled CRF was only 1.0% in the general population, while 29% in patients admitted in ICU and 15% in hospitalized patients.

Although there is limited information on COVID-19 CFR, some primary studies have been reported CFR in different countries with various target populations. For example, the studies reported from Italy have indicated a 9.26% CFR of COVID-19 [47, 50] . Moreover, studies reported from Spain and France have reported 6.16 and 4.21% CFR, respectively [47, 50] . Furthermore, a study reported from Iran shown that 7.9% of CFR, while the study reported from Turkey indicated 2.0% CFR of COVD-19 [47, 50] . Compared to the previous studies cited above, our meta-analysis finding, based on primary studies reported from different countries, indicated CFR with a wide range. This difference between our CFR with its broad range and the previous study could be due to the target population difference. Moreover, it might be due to case/death finding and reporting capacity between the countries where the primary studies were reported. Furthermore, case and death reporting in some countries might be influenced by political decisions. Thus, these probable reasons could affect the overall estimation of CFR, which could impact the actual epidemiological feature of the disease. CFR of COVID-19 ranges between 4 and 11% among hospitalized adult patients in different countries based on previous studies [51] . The present study showed that high (13%) CFR in hospital admitted patients. The present study was also revealed that CFR in patients admitted to ICU was 37%. In contrast to our findings, a case series study reported from Seattle indicated high CFR (50%) among critically ill patients [32] . Moreover, a study reported from Washington state the highest CFR (67%) in patients admitted to ICU. Thus the health background of patients admitted to ICU could be an essential factor related to death [52] . For example, among patients admitted to ICU in Washington, 86% have comorbidities such as chronic kidney disease and congestive heart failure [52] . High CFR among patients admitted to ICU is mainly attributable to comorbidities and old age, which exacerbate the morbidity that leads to poor outcomes in patients admitted to ICU. Patients with comorbidities and old age demand great attention to recover from COVID-19, and more evidence requires better understanding to inform health care [32] . The present meta-analysis revealed a significant difference in CFR in the age group younger than 50 years and older (3.0 vs 19%). In Italy, CFR was 52.3 in patients more aged than 80 years and 35.6 in 70-79 years old [9] . Similarly, in Chinese, CFR was high among the most aging patients [53] . Besides CFR differences in age groups, the overall CFR reported from Italy (7.2%) is substantially higher than in China (2.3%) [9, 53] . The difference in CFR is not only related to age, rather other factors such as. Occupation, gender, and clinical comorbid could be contributed to high CFR in the old age group. A better method to preventing possible misconceptions about age effect on CFR in COVID-19 patients direct age adjustment could be a solution. Several factors could affect on mortality of COVID-19 in different settings due to health system capacity, age variation, the burden of chronic diseases, perception regarding COVID-19, and other unknown factors. For instance, the majority of COVID-19 confirmed cases in Italy are in old proportion. Moreover, most deaths due to COVID-19 in Italy are among geriatric, male patients with comorbidity [9] . In addition, the number of symptoms the cases shown is probably affected by death due to COVID-19. For example, some patients have only one or three main symptoms of COVID-19, but some patients reveal more than three symptoms which most probably affects the death due to COVID-19. Thus, advanced, indepth analyses are required to explore the effect of the number of signs on fatalities associated with COVID-19.

Prior findings suggested that CFR of COVID-19 seems to be less deadly compared to Bird flu, Ebola, SARS, and MERS , However, it becomes a global economic and public health concern [47, 54] . In most patients, COVID-19 shows mild symptoms, which hid the burden of the disease and facilitate transmission in the community rapidly [47] . Thus, media should play a significant role in enhancing health literacy because the unique characteristics of COVID-19 make the general community at risk. Some undetected or delayed cases could probably lead to underestimation of CFR of COVID-19. Underestimation could be linked to the level of the general public and politicians' preparedness and mitigation.

The pooled estimate CFR of COVID-19 in this review is considerably high and differs between different patient groups. The CFR was higher in patients admitted in ICU and older than 50 years. Moreover, the present review results highlighted the need for transparency in testing and reporting policies and denominators used in CFR estimation. It is also necessary to report the case's age, sex, and comorbidity distribution of all patients, which is essential in comparing the CFR among different population segments.

Ethics clearance was not sought because this review was based on published articles.

Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in IRAN: a single center study

Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China

Understanding of COVID-19 based on current evidence

Early estimation of the case fatality rate of COVID-19 in mainland China: a data-driven analysis

Transmission potential and severity of COVID-19 in South Korea

Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures

Basic reproduction number: an important indicator for the future of the COVID-19 epidemic in Iran

Estimate of the basic reproduction number for COVID-19: a systematic review and meta-analysis

Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy

The many estimates of the COVID-19 case fatality rate

Kucharski AJ. Estimating the infection and case fatality ratio for coronavirus disease (COVID-19) using age-adjusted data from the outbreak on the Diamond Princess cruise ship

Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China

The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses

Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy region, Italy

Updated understanding of the outbreak of 2019 novel coronavirus (2019-nCoV) in Wuhan

Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy

Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

SARS-CoV-2 in Spanish intensive care units: early experience with 15-day survival in Vitoria

Comparison of hospitalized patients with ARDS caused by COVID-19 and H1N1

Clinical characteristics and outcomes of patients undergoing surgeries during the incubation period of COVID-19 infection

Transmission potential and severity of COVID-19 in South Korea

Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan

Characteristics of COVID-19 infection in Beijing

Clinical features of COVID-19 in elderly patients: a comparison with young and middle-aged patients

Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COV-ID-19

A cross-sectional comparison of epidemiological and clinical features of patients with coronavirus disease (COVID-19) in Wuhan and outside Wuhan, China

Early epidemiological analysis of the 2019-nCoV outbreak based on a crowdsourced data

Preparedness is essential for Western Pacific Islands during the COVID-19 Pandemic

A Trial of Lopinavir-Ritonavir in Adults Hospitalized with Severe COVID-19

Covid-19 in critically ill patients in the Seattle region -case series

Compassionate use of remdesivir for patients with severe Covid-19

Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicentre) and outside Hubei (non-epicentre): a nationwide analysis of China

Prognostic value of NT-proBNP in patients with severe COVID-19

Hospitalization and critical care of 109 decedents with COVID-19 pneumonia in Wuhan

Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series

COVID-19 in a designated infectious diseases hospital outside Hubei Province, China

Clinical features and short-term outcomes of 102 patients with coronavirus disease 2019 in Wuhan, China

Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province

Epidemiologic features and clinical course of patients infected with SARS-CoV-2 in Singapore

Clinical features of 69 cases with coronavirus disease

Epidemiology of Covid-19 in a long-term care facility in King County, Washington

Association between platelet parameters and mortality in coronavirus disease 2019: retrospective cohort study

Clinical characteristics and outcomes of older patients with coronavirus disease 2019 (COVID-19) in Wuhan, China: a single-centered, retrospective study

Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia

Cross-country comparison of case fatality rates of COVID-19/SARS-COV-2

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Clinical characteristics of coronavirus disease 2019 in China

COVID-19 Coronavirus Pandemic. Available at

A review of coronavirus disease-2019 (COVID-19)

Characteristics and outcomes of 21 critically ill patients with COVID-19 in Washington State

The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) -China

Coronavirus disease 2019: What we know

Funding sources: this research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

The authors declare no conflict of interest.

YA and MS: conception of the idea, data analysis, Manuscript writing, HHT, AAGH and MJ: searching, data extraction, manuscript writing. All authors read and approved the final manuscript.