scholarly journals Health related factors contributing to COVID-19 fatality rates in various communities across the world

2021 ◽  
Vol 15 (09) ◽  
pp. 1263-1272
Author(s):  
Jamal Kareem Shakor ◽  
Rawand Abdulrahman Isa ◽  
Muhammed Babakir Mina ◽  
Salar Ibrahim Ali ◽  
Taib Ahmad Hama-Soor ◽  
...  

Introduction: Factors such as comorbidity, age and gender distribution are mostly related to hospitalization, numbers requiring intensive care and case fatality rate. In this review, the fatality rate of coronavirus disease 2019 (COVID-19) in different population health background according to comorbidity, age, gender distribution, and laboratory prognosis for COVID-19. Methodology: The current review was based on the data from copious studies that had homogeneity in relation to the review’s objectives. It included the newest studies from December 2019 to September 2020. The epidemiological reasons for the high morbidity and mortality rates among COVID-19 patients were analyzed in different countries. Results: The highest comorbidity prevalence of COVID-19 was recorded in the United States of America (USA) (93.9%) and Italy (68%). Among population health background factors, comorbidity was the most common cause of COVID-19 fatality in the USA. The mean age of the most COVID-19 fatalities was more than 60 years old. Most of the studies show that 60% of COVID-19 patients were male. The fatality rates for the age group of 80-89 years-old in Korea, China, and Italy were 8.7 %, 14.7 %, and 18.8 % respectively. Lymphocytopenia has been observed in 91% of COVID-19 death cases. C - reactive protein had increased in 40-60% of COVID-19 patients. Conclusions: Many factors contribute to COVID-19 severity and fatality rates. Comorbidity, age, and gender were the main reasons for the Case Fatality Rate. This review recommends to follow preventive measures for overcoming the challenges faced during this emerging pandemic disease.

PEDIATRICS ◽  
1950 ◽  
Vol 5 (5) ◽  
pp. 840-852
Author(s):  
JEROME L. KOHN ◽  
ALFRED E. FISCHER ◽  
HERBERT H. MARKS

Analysis of data on patients with pertussis during 1942-1946 obtained by means of a questionnaire from communicable disease hospitals and from health officers in a number of cities in the United States and Canada showed these results: Case fatality rates of patients admitted to hospitals for treatment have declined substantially in the period under review. This decline is general, both among infants under one year of age and among older children. In 1946, the case fatality rate of the infants hospitalized for the disease was 5.0% in those cities for which data for at least four years were available. This may be compared with the rate of 7.8% in 1942 and 11.1% in 1943. At ages one year and over, the rate was only 1.3% in 1946, as compared with 1.7% in 1942 and 3.7% in 1943. The rates in the hospitals with larger experiences were generally more favorable than in hospitals with smaller experiences. Despite the incomplete reporting of pertussis, which results in exaggerating the case fatality rate for the general population, the level of these rates in the community as a whole was lower than for hospitalized cases. This reflects the higher proportion of the severer cases in the hospitalized group. Indications are that in many places hospitalization is limited more and more to severe cases. Progress in the management of pertussis, especially of the severer cases admitted to hospitals, is believed to be the chief factor in the decline in case fatality of pertussis. A request contained in the questionnaire for an opinion on the severity of pertussis during the period studied elicited few replies, and these replies showed a division of opinion on the matter. It appears unlikely that there has been much of any change in the severity of the disease.


Author(s):  
Hua Zhang ◽  
Han Han ◽  
Tianhui He ◽  
Kristen E Labbe ◽  
Adrian V Hernandez ◽  
...  

Abstract Background Previous studies have indicated coronavirus disease 2019 (COVID-19) patients with cancer have a high fatality rate. Methods We conducted a systematic review of studies that reported fatalities in COVID-19 patients with cancer. A comprehensive meta-analysis that assessed the overall case fatality rate and associated risk factors was performed. Using individual patient data, univariate and multivariable logistic regression analyses were used to estimate odds ratios (OR) for each variable with outcomes. Results We included 15 studies with 3019 patients, of which 1628 were men; 41.0% were from the United Kingdom and Europe, followed by the United States and Canada (35.7%), and Asia (China, 23.3%). The overall case fatality rate of COVID-19 patients with cancer measured 22.4% (95% confidence interval [CI] = 17.3% to 28.0%). Univariate analysis revealed age (OR = 3.57, 95% CI = 1.80 to 7.06), male sex (OR = 2.10, 95% CI = 1.07 to 4.13), and comorbidity (OR = 2.00, 95% CI = 1.04 to 3.85) were associated with increased risk of severe events (defined as the individuals being admitted to the intensive care unit, or requiring invasive ventilation, or death). In multivariable analysis, only age greater than 65 years (OR = 3.16, 95% CI = 1.45 to 6.88) and being male (OR = 2.29, 95% CI = 1.07 to 4.87) were associated with increased risk of severe events. Conclusions Our analysis demonstrated that COVID-19 patients with cancer have a higher fatality rate compared with that of COVID-19 patients without cancer. Age and sex appear to be risk factors associated with a poorer prognosis.


2009 ◽  
Vol 30 (11) ◽  
pp. 1036-1044 ◽  
Author(s):  
Omar M. AL-Rawajfah ◽  
Frank Stetzer ◽  
Jeanne Beauchamp Hewitt

Background.Although many studies have examined nosocomial bloodstream infection (BSI), US national estimates of incidence and case-fatality rates have seldom been reported.Objective.The purposes of this study were to generate US national estimates of the incidence and severity of nosocomial BSI and to identify risk factors for nosocomial BSI among adults hospitalized in the United States on the basis of a national probability sample.Methods.This cross-sectional study used the US Nationwide Inpatient Sample for the year 2003 to estimate the incidence and case-fatality rate associated with nosocomial BSI in the total US population. Cases of nosocomial BSI were defined by using 1 or more International Classification of Diseases, 9th Revision, Clinical Modification codes in the secondary field(s) that corresponded to BSIs that occurred at least 48 hours after admission. The comparison group consisted of all patients without BSI codes in their NIS records. Weighted data were used to generate US national estimates of nosocomial BSIs. Logistic regression was used to identify independent risk factors for nosocomial BSI.Results.The US national estimated incidence of nosocomial BSI was 21.6 cases per 1,000 admissions, while the estimated case-fatality rate was 20.6%. Seven of the 10 leading causes of hospital admissions associated with nosocomial BSI were infection related. We estimate that 541,081 patients would have acquired a nosocomial BSI in 2003, and of these, 111,427 would have died. The final multivariate model consisted of the following risk factors: central venous catheter use (odds ratio [OR], 4.76), other infections (OR, 4.61), receipt of mechanical ventilation (OR, 4.97), trauma (OR, 1.98), hemodialysis (OR, 4.83), and malnutrition (OR, 2.50). The total maximum rescaled R2 was 0.22.Conclusions.The Nationwide Inpatient Sample was useful for estimating national incidence and case-fatality rates, as well as examining independent predictors of nosocomial BSI.


2021 ◽  
Author(s):  
William A. Barletta

AbstractBackgroundDuring 2021 several new variants of the SARS-CoV-2 virus appeared with both increased levels of transmissibility and virulence with respect to the original wild variant. The Delta (B.1.617.2) variation, first seen in India, dominates COVID-19 infections in several large countries including the United States and India. Most recently, the Lambda variant of interest with increased resistance to vaccines has spread through much of South America.ObjectiveThis research explores the degree to which new variants of concern 1) generate spikes and waves of fluctuations in the daily case fatality rates (CFR) across countries in several regions in the face of increasing levels of vaccination of national populations and 2) may increase the vulnerability of persons with certain comorbidities.MethodsThis study uses new, openly available, epidemiological statistics reported to the relevant national and international authorities for countries across the Americas, Europe, Africa, Asia and the Middle East. Daily CFRs and correlations of fatal COVID-19 infections with potential cofactors are computed for the first half of 2021 that has been dominated by the wide spread of several “variants of concern” as denoted by the World Health Organization.ResultsThe analysis yields a new quantitative measure of the temporal dynamics of mortality due to SARS-CoV-2 infections in the form of variations of a proxy case fatality rate compared on a country to-country basis in the same region. It also finds minimal variation of correlation between the cofactors based on WHO data and on the average apparent case fatality rate.


BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e051506
Author(s):  
Francesca Fortunato ◽  
Domenico Martinelli ◽  
Sergio Lo Caputo ◽  
Teresa Santantonio ◽  
Vitangelo Dattoli ◽  
...  

ObjectivesThe present study aimed to explore differences in COVID-19 outcomes between male and female cases in the Apulian District of Foggia, Italy.Design and settingWe performed a retrospective epidemiological study among all COVID-19 confirmed cases that occurred in the Apulian District of Foggia from 29 February to 30 June 2020. The surveillance data from a regional registry (GIAVA-COVID) were used.Main outcomesThe main outcome measures were the proportion of hospitalisations, virus clearance and the case fatality rate.ResultsA total of 1175 cases (50.7% female; median age: 55 years) were identified among 55 131 tests performed. The proportion of hospitalisation with COVID-19 diagnosis was 45.4% in men versus 37.9% in women (p<0.01), while the average length of stay in hospitals was 31.3±14.6 days in women versus 26.8±14.4 days in men (p<0.01). The proportion of cases who achieved virus clearance was higher in women (84.2%; days to clearance: 28.0±12.1) than in men (79.3%; days to clearance: 29.4±12.9; p<0.05). Men were associated with a significantly higher risk of dying from COVID-19 than women (case fatality rate 16.1% vs 10.4%; p<0.01). The mean time, from diagnosis to death, was 14.5±14.4 days in women compared with 10.6±10.7 days in men (p<0.01). The male sex, age ≥55 years and presence of at least one underlying comorbidity significantly raised the risk of hospitalisation, persistent infection and death (p<0.05).ConclusionsThis study suggests that more attention should be paid to sex as a variable for the interpretation of COVID-19 data. Sex-disaggregated data will help clinicians to make appropriate patient-tailored medical decisions.


2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S65-S65
Author(s):  
Katharine Cooley ◽  
Shannon Fleck-Derderian ◽  
Christina Nelson

Abstract Background Plague meningitis is a rare but serious manifestation of infection with the bacterium Yersinia pestis. The risk factors, clinical evolution, and optimal treatment strategies of plague meningitis are not well understood, and data is limited to sporadic case reports. To advance knowledge of this condition and support clinical practice recommendations, we conducted a systematic review of published cases of plague meningitis. Methods We reviewed PubMed Central, Medline, Embase, and other databases for publications on plague meningitis in any language. Articles that contained reports of patients with plague meningitis plus information on patient outcome were included. Results Among 1,090 articles identified in our search, we found 54 articles describing 83 cases eligible for inclusion. Cases occurred between 1898 and 2015; mean age of patients was 20.5 years (range 6 wks - 64 yrs) and 65% were male. Most patients lived in the United States (23%), Argentina (18%), Vietnam (12%), or China (12%). Four patients (5%) had primary plague meningitis. More than half (59%) of patients developed meningitis secondary to primary bubonic plague; the remainder developed meningitis secondary to other or unknown forms of plague. Of patients with a bubo, 51% had an axillary bubo. The most common symptoms were fever (66%), nuchal rigidity (43%), and headache (35%); 23 patients had focal neurologic deficits such as cranial nerve abnormality. Case fatality rate was 96% (n=23/24) for patients who did not receive antimicrobial treatment and 42% (n=25/59) for patients treated with antimicrobials. Case fatality rate by antimicrobial received, including patients who received multiple antimicrobial classes, was 50% for sulfonamides (n= 38), 50% for fluoroquinolones (n=2), 19% for aminoglycosides (n=21), 11% for chloramphenicol (n=19), and 0% for tetracyclines (n=14). Conclusion Plague meningitis has a high fatality rate, but antimicrobial treatment can improve patient outcomes. Having an axillary bubo may be a risk factor for developing plague meningitis – in contrast to our findings, a recent analysis found that only 24% of patients with bubonic plague had buboes in the axillary region. Additional research would be helpful to investigate this association further. Disclosures All Authors: No reported disclosures


2020 ◽  
Author(s):  
Avaneesh Singh ◽  
Manish Kumar Bajpai

We have proposed a new mathematical method, SEIHCRD-Model that is an extension of the SEIR-Model adding hospitalized and critical twocompartments. SEIHCRD model has seven compartments: susceptible (S), exposed (E), infected (I), hospitalized (H), critical (C), recovered (R), and deceased or death (D), collectively termed SEIHCRD. We have studied COVID- 19 cases of six countries, where the impact of this disease in the highest are Brazil, India, Italy, Spain, the United Kingdom, and the United States. SEIHCRD model is estimating COVID-19 spread and forecasting under uncertainties, constrained by various observed data in the present manuscript. We have first collected the data for a specific period, then fit the model for death cases, got the values of some parameters from it, and then estimate the basic reproduction number over time, which is nearly equal to real data, infection rate, and recovery rate of COVID-19. We also compute the case fatality rate over time of COVID-19 most affected countries. SEIHCRD model computes two types of Case fatality rate one is CFR daily and the second one is total CFR. We analyze the spread and endpoint of COVID-19 based on these estimates. SEIHCRD model is time-dependent hence we estimate the date and magnitude of peaks of corresponding to the number of exposed cases, infected cases, hospitalized cases, critical cases, and the number of deceased cases of COVID-19 over time. SEIHCRD model has incorporated the social distancing parameter, different age groups analysis, number of ICU beds, number of hospital beds, and estimation of how much hospital beds and ICU beds are required in near future.


Author(s):  
Giovanna Deiana ◽  
Antonio Azara ◽  
Marco Dettori ◽  
Fiorenzo Delogu ◽  
Gavino Vargiu ◽  
...  

This study aims to underline the clinical characteristics of patients who died after testing positive for SARS-CoV-2 infection in one region of Italian and to evaluate the influence of underlying health conditions on the fatal outcome. A matched case-control study was designed by analyzing the data regarding positive subjects observed up to April 21, 2020. The case fatality rate was 7.9%, with a higher proportion of deaths in men than women. The specific standardized mortality ratio was 0.15—0.13 for males and 0.2 for females, showing that mortality is much lower than expected. Cardiovascular diseases, chronic lung diseases and diabetes mellitus showed a significant association with the outcome. Although the case fatality rate in Sardinia in regard to age and gender patterns seems to be similar to that for Italy as a whole, its quantitative value was far lower than the national one and possible explanations might include the genetic characteristics of the Sardinian population or the immediate closure of its borders as soon as the epidemic started. Our results highlighted that lethality is strongly dependent on the presence of multiple concomitant serious diseases. It is important to have epidemiological strategies for effective guidance on public health actions in order to improve chances of survival.


2020 ◽  
Author(s):  
Bishoy T. Samuel

Abstract Background:Forecasting the current coronavirus disease (COVID-19) epidemic in the United States necessitates novel mathematical models for accurate predictions. This paper examines novel uses of three-parameter logistic models and first-derivative models through three distinct scenarios that have not been examined in the literature as of July 14, 2020.Methods:Using publicly available data, statistical software was used to conduct a non-linear least-squares estimate to generate a three-parameter logistic model, with a subsequently generated first-derivative model. In the first scenario a logistic model was used to examine the natural log of COVID-19 cases as the dependent variable (versus day number), on July 11 and May 1. Independent t-test analyses were used to test comparative coefficient differences across models. In the second scenario, a first-derivative model was derived from a base three-parameter logistic model for April 27, examining time to peak mortality and decrease in case fatality rate. In the third scenario, a first-derivative model of mortality through July 11 as the dependent variable, versus confirmed cases, was generated to look at case fatality rate relative to increasing cases.Results:All models generated were statistically significant with R2 > 99%. The logistic models in the first scenario best predicted time to growth deceleration in the natural log of cases in the U.S. (slowing of exponential growth), estimated at March 11, 2020. For the May 1 data, independent t-test analyses of comparative coefficients across models were useful to track improvements from implemented public health measures. The first-derivative model in the second scenario on April 27, when the epidemic was more controlled, showed peak mortality around April 12-13, with a case fatality rate of < 1,000 deaths and trending down. The first-derivative model in the third scenario estimated a near-zero case fatality rate to occur at 4 million confirmed cases. It has not been affected by fluctuations in mortality from June 29 through July 11.Conclusion:Three-parameter logistic models and first-derivative models have utility in predicting time to growth deceleration, and case fatality rates relative to cases. They can objectively assess improvements of implemented epidemiologic measures and have applicable public health safety implications.


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