scholarly journals Estimation of the basic reproduction number, average incubation time, asymptomatic infection rate, and case fatality rate for COVID-19: Meta-analysis and sensitivity analysis

2020 ◽  
Author(s):  
Wenqing He ◽  
Grace Y. Yi ◽  
Yayuan Zhu
Keyword(s):  
Confidence Interval ◽  
Basic Reproduction Number ◽  
Incubation Time ◽  
Case Fatality Rate ◽  
Reproduction Number ◽  
Meta Analysis ◽  
Case Fatality ◽  
Asymptomatic Infection ◽  
Fatality Rate ◽  
The Basic Reproduction Number

AbstractThe coronavirus disease 2019 (COVID-19) has been found to be caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, comprehensive knowledge of COVID-19 remains incomplete and many important features are still unknown. This manuscripts conduct a meta-analysis and a sensitivity study to answer the questions: What is the basic reproduction number? How long is the incubation time of the disease on average? What portion of infections are asymptomatic? And ultimately, what is the case fatality rate? Our studies estimate the basic reproduction number to be 3.15 with the 95% interval (2.41, 3.90), the average incubation time to be 5.08 days with the 95% confidence interval (4.77, 5.39) (in day), the asymptomatic infection rate to be 46% with the 95% confidence interval (18.48%, 73.60%), and the case fatality rate to be 2.72% with 95% confidence interval (1.29%, 4.16%) where asymptomatic infections are accounted for.

scholarly journals SEIHCRD Model for COVID-19 spread scenarios, disease predictions and estimates the basic reproduction number, case fatality rate, hospital, and ICU beds requirement

2020 ◽  
Author(s):  
Avaneesh Singh ◽  
Manish Kumar Bajpai
Keyword(s):  
Basic Reproduction Number ◽  
Case Fatality Rate ◽  
Reproduction Number ◽  
Case Fatality ◽  
The United States ◽  
Fatality Rate ◽  
Hospital Beds ◽  
The Impact ◽  
Over Time ◽  
The Basic Reproduction Number

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.

scholarly journals The first wave of the SARS-CoV-2 epidemic in Tuscany (Italy): A SI2R2D compartmental model with uncertainty evaluation

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250029
Author(s):  
Michela Baccini ◽  
Giulia Cereda ◽  
Cecilia Viscardi
Keyword(s):  
Basic Reproduction Number ◽  
Compartmental Model ◽  
Reproduction Number ◽  
Case Fatality ◽  
Parametric Bootstrap ◽  
Model Parameters ◽  
Fatality Rate ◽  
Epidemic Curve ◽  
Plausible Values ◽  
The Basic Reproduction Number

With the aim of studying the spread of the SARS-CoV-2 infection in the Tuscany region of Italy during the first epidemic wave (February-June 2020), we define a compartmental model that accounts for both detected and undetected infections and assumes that only notified cases can die. We estimate the infection fatality rate, the case fatality rate, and the basic reproduction number, modeled as a time-varying function, by calibrating on the cumulative daily number of observed deaths and notified infected, after fixing to plausible values the other model parameters to assure identifiability. The confidence intervals are estimated by a parametric bootstrap procedure and a Global Sensitivity Analysis is performed to assess the sensitivity of the estimates to changes in the values of the fixed parameters. According to our results, the basic reproduction number drops from an initial value of 6.055 to 0 at the end of the national lockdown, then it grows again, but remaining under 1. At the beginning of the epidemic, the case and the infection fatality rates are estimated to be 13.1% and 2.3%, respectively. Among the parameters considered as fixed, the average time from infection to recovery for the not notified infected appears to be the most impacting one on the model estimates. The probability for an infected to be notified has a relevant impact on the infection fatality rate and on the shape of the epidemic curve. This stresses the need of collecting information on these parameters to better understand the phenomenon and get reliable predictions.

scholarly journals Estimation of novel coronavirus ( COVID ‐19) reproduction number and case fatality rate: A systematic review and meta‐analysis

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Tanvir Ahammed ◽  
Aniqua Anjum ◽  
Mohammad Meshbahur Rahman ◽  
Najmul Haider ◽  
Richard Kock ◽  
...  
Keyword(s):  
Systematic Review ◽  
Case Fatality Rate ◽  
Reproduction Number ◽  
Meta Analysis ◽  
Case Fatality ◽  
Fatality Rate ◽  
Novel Coronavirus

scholarly journals Meta-analysis and metaregression of risk factors associated with mortality in hip fracture patients during the COVID-19 pandemic

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Firas J. Raheman ◽  
Djamila M. Rojoa ◽  
Jvalant Nayan Parekh ◽  
Reshid Berber ◽  
Robert Ashford
Keyword(s):  
Hip Fracture ◽  
Hip Fractures ◽  
Case Fatality Rate ◽  
Excess Mortality ◽  
Meta Analysis ◽  
Case Fatality ◽  
Pooled Analysis ◽  
Fatality Rate ◽  
Increased Risk ◽  
The Impact

AbstractIncidence of hip fractures has remained unchanged during the pandemic with overlapping vulnerabilities observed in patients with hip fractures and those infected with COVID-19. We aimed to investigate the independent impact of COVID-19 infection on the mortality of these patients. Healthcare databases were systematically searched over 2-weeks from 1st–14th November 2020 to identify eligible studies assessing the impact of COVID-19 on hip fracture patients. Meta-analysis of proportion was performed to obtain pooled values of prevalence, incidence and case fatality rate of hip fracture patients with COVID-19 infection. 30-day mortality, excess mortality and all-cause mortality were analysed using a mixed-effects model. 22 studies reporting 4015 patients were identified out of which 2651 (66%) were assessed during the pandemic. An excess mortality of 10% was seen for hip fractures treated during the pandemic (OR 2.00, p = 0.007), in comparison to the pre-pandemic controls (5%). Estimated mortality of COVID-19 positive hip fracture patients was four-fold (RR 4.59, p < 0.0001) and 30-day mortality was 38.0% (HR 4.73, p < 0.0001). The case fatality rate for COVID-19 positive patients was 34.74%. Between-study heterogeneity for the pooled analysis was minimal (I2 = 0.00) whereas, random effects metaregression identified subgroup heterogeneity for male gender (p < 0.001), diabetes (p = 0.002), dementia (p = 0.001) and extracapsular fractures (p = 0.01) increased risk of mortality in COVID-19 positive patients.

scholarly journals An epidemiological investigation of the 2019 suspected pertussis outbreak in northwestern Nigeria

2021 ◽  
Vol 9 ◽  
pp. 205031212110083
Author(s):  
Omoleke Semeeh ◽  
Biniam Getachew ◽  
Yusuf Taofik ◽  
Lukman Surajudeen ◽  
Assad Hassan ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Disease Transmission ◽  
Attack Rate ◽  
Odds Ratio ◽  
Case Fatality Rate ◽  
Adjusted Odds Ratio ◽  
Case Fatality ◽  
Immunization Coverage ◽  
Fatality Rate ◽  
Vaccine Preventable Diseases

Introduction: In 2019, we investigated the profile of the cases and controls and the determinants of pertussis transmission in Kebbi State, Northwestern Nigeria, to inform better immunization and surveillance strategies. Methods: Community-based unmatched case–control study and review of the 2019 pertussis routine surveillance data in the affected settlements in the state were conducted. A total of 52 suspected cases of pertussis and 107 control from two local government areas in Kebbi State were recruited. Data were analyzed using descriptive and inferential statistics. Results: The highest attack rate was observed among between 1- and 4-year age group followed by children less than 1-year old, and the least attack rate was among those above 15 years. The overall attack rate and the case fatality rate were 2.10% and 0.10%, respectively. A higher attack rate was observed among women, whereas the case fatality rate was more among males. From the community survey, we observed that the cases were less likely to have pertussis vaccination history (adjusted odds ratio = 0.28, 95% confidence interval = 0.11–0.74) compared with the controls. Knowing pertussis prevention methods were found protective for pertussis transmission (adjusted odds ratio = 0.14, 95% confidence interval = 0.04–0.45). Conclusion: This study showed the vulnerability of children under 5 years, especially under 1 year, to vaccine-preventable diseases in rural populations, where “real” immunization coverage is sub-optimal, and the dominant socio-demographic factors are supportive of disease transmission. We found immunization and knowledge of the preventive measures to be protective against pertussis outbreaks. Therefore, routine immunization services must be intensified to improve coverage and prevent future pertussis outbreak(s).

scholarly journals Crimean-Congo hemorrhagic fever-induced liver injury: a systematic review and meta-analysis

2021 ◽  
Author(s):  
Sawai Singh Rathore ◽  
Ade Harrison Manju ◽  
Qingqing Wen ◽  
Manush Sondhi ◽  
Reshma Pydi ◽  
...  
Keyword(s):  
Liver Injury ◽  
Case Fatality Rate ◽  
Meta Analysis ◽  
Case Series ◽  
Case Fatality ◽  
Hemorrhagic Fever ◽  
Fatality Rate ◽  
High Case Fatality Rate ◽  
Crimean Congo Hemorrhagic Fever ◽  
Pooled Prevalence

Background: Crimean-Congo hemorrhagic fever (CCHF) is a fatal acute tick-borne viral infection and a substantial emerging global public health threat. This illness has a high case fatality rate of up to 40%. The liver is one of the important target organs of the CCHF virus. Objective: The aim of this meta-analysis to evaluate the correlation between CCHF  and liver injury and draw more generalized inferences about the abnormal serum markers of liver injury such as alanine aminotransferase (ALT), aspartate aminotransferase (AST) in CCHF patients. Methods: A literature search was accomplished for published eligible articles with MEDLINE/PubMed and Embase databases. All eligible observational studies and case series were included from around the world. The inclusion criteria were articles describing liver injury biomarkers AST and ALT amongst patients diagnosed with CCHF. Results: Data from 18 studies, consisting of 1238 patients with CCHF  were included in this meta-analysis. The overall pooled prevalence of at least one raised liver injury biomarker was 77.95% (95% CI, I2 = 88.50%, p < 0.0001). Similarly, pooled prevalence of elevated AST and ALT was 85.92% (95% CI, I2 = 85.27%,  p < 0.0001) and 64.30% (95% CI, I2 = 88.32%,  p < 0.0001) respectively.  Both Egger and Begg-Mazumdar’s tests detected no apparent publication bias in all three meta-analyses(p > 0.05).  Conclusion: These elevated liver injury biomarkers have been identified as significant prognostic factors. Hence, Physicians must recognize and continuously monitor these biomarkers, since these aid early stratification of prognosis and the prevention of severe outcomes in infection with such a high case fatality rate.

scholarly journals APLIKASI MODEL EPIDEMIK SEIAR-SEI PADA PENYEBARAN PENYAKIT MALARIA DENGAN INFEKSI ASIMTOMATIK DAN SUPER INFEKSI

2018 ◽  
Vol 15 (2) ◽  
pp. 67
Author(s):  
Stella Maryana Belwawin
Keyword(s):  
Equilibrium Point ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Asymptomatic Infection ◽  
Endemic Equilibrium ◽  
Asymptomatic Infections ◽  
The Stability ◽  
Super Infection ◽  
The Basic Reproduction Number

AbstractThis aim of this study is to determine the point of equilibrium and analyze the stability of SEIAR-SEI model on malaria disease with asymptomatic infection, super infection and the effect of the mosquito's life cycle. This study also aim is to measure the sensitivity of the spread of malaria to the parameters of asymptomatic infections, the rate of treatment, and the rate of birth of mosquitoes through the magnitude of . The method in this research is deductively, through several stage, such as  determination of disease-free equilibrium point and endemic equilibrium point, determination of basic reproduction number (), analyze of the basic reproduction number sensitivity of the spread of malaria to the parameters of asymptomatic infections, the rate of treatment, and the rate of birth of mosquitoes. The endemic equilibrium point was obtained using rule of Descartes. The result show that the change in the value of parameter , , and  has effect on the basic reproduction number (). Treatment factors in the human population influence the elimination of malaria in a population. Whereas asymptomatic infection factors and the birth rate of adult mosquitoes influence the increase in malaria infection. Keywords:  Malaria, asymptomatic infection, super infection, basic reproduction number, rule of descrates. AbstrakPenelitian ini bertujuan menentukan titik keseimbangan dan menganalisis kestabilan dari model SEIAR_SEI pada penyakit malaria dengan pengaruh infeksi asimtomatik, super infeksi, dan siklus hidup nyamuk. Penelitian ini juga bertujuan mengukur tingkat sensitivitas penyebaran penyakit malaria terhadap parameter infeksi asimtomatik, laju pengobatan, serta laju kelahiran nyamuk.melalu besaran .  Metode yang digunakan dalam penelitian ini adalah metode deduktif dengan langkah-langkah : menentukan titik keseimbangan bebas penyakit dan endemik dan menentukan bilangan reproduksi dasar ). Analisis sensitivitas bilangan reproduksi dasar dilakukan terhadap parameter infeksi asimtomatik, pengobatan, dan laju kelahiran nyamuk. Tititk keseimbangan endemik diperoleh dengan aturan descrates. Hasil yang diperoleh menunjukkan parameter , , dan  berpengaruh terhadap bilangan reproduksi dasar (). Faktor pengobatan berpengaruh terhadap eliminasi penyakit malaria. Sedangkan faktor infeksi asimtomatik dan laju kelahiran nyamuk dewasa berpengaruh terhadap peningkatan infeksi penyakit malaria. Kata kunci: Malaria, Infeksi Asimtomatik, Super Infeksi, Bilangan Reproduksi Dasar, Aturan Descrates . 

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