scholarly journals Epidemiological waves - types, drivers and modulators in the COVID-19 pandemic

2022 ◽  
Author(s):  
John Harvey ◽  
Bryan Chan ◽  
Tarun Srivastava ◽  
Alexander E. Zarebski ◽  
Pawel Dlotko ◽  
...  
Keyword(s):  
Time Series ◽  
Case Fatality ◽  
Mathematical Epidemiology ◽  
Government Interventions ◽  
Case Fatality Ratio ◽  
Mortality Burden ◽  
Early Implementation ◽  
National Conversation ◽  
Pharmaceutical Interventions ◽  
General Time

Introduction: A discussion of 'waves' of the COVID-19 epidemic in different countries is a part of the national conversation for many, but there is no hard and fast means of delineating these waves in the available data and their connection to waves in the sense of mathematical epidemiology is only tenuous. Methods: We present an algorithm which processes a general time series to identify substantial, significant and sustained periods of increase in the value of the time series, which could reasonably be described as 'observed waves'. This provides an objective means of describing observed waves in time series. Results: The output of the algorithm as applied to epidemiological time series related to COVID-19 corresponds to visual intuition and expert opinion. Inspecting the results of individual countries shows how consecutive observed waves can differ greatly with respect to the case fatality ratio. Furthermore, in large countries, a more detailed analysis shows that consecutive observed waves have different geographical ranges. We also show how waves can be modulated by government interventions and find that early implementation of non-pharmaceutical interventions correlates with a reduced number of observed waves and reduced mortality burden in those waves. Conclusion: It is possible to identify observed waves of disease by algorithmic methods and the results can be fruitfully used to analyse the progression of the epidemic.

scholarly journals Accounting for underreporting in mathematical modelling of transmission and control of COVID-19 in Iran

2020 ◽  
Author(s):  
Meead Saberi ◽  
Homayoun Hamedmoghadam ◽  
Kaveh Madani ◽  
Helen M. Dolk ◽  
Andrei S. Morgan ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Estimation Method ◽  
Case Fatality ◽  
Transmission Model ◽  
School Closures ◽  
The Public ◽  
Case Fatality Ratio ◽  
And Control ◽  
The Impact ◽  
Pharmaceutical Interventions

SUMMARYBackgroundIran has been the hardest hit country by the outbreak of SARS-CoV-2 in the Middle East with 74,877 confirmed cases and 4,683 deaths as of 15 April 2020. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant under-reporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. We use a mathematical epidemic model utilizing official confirmed data and estimates of underreporting to understand how transmission in Iran has been changing between February and April 2020.MethodsWe developed a compartmental transmission model to estimate the effective reproduction number and its fluctuations since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method also accounts for the underreporting due to low case ascertainment by estimating the percentage of symptomatic cases using delay-adjusted case fatality ratio based on the distribution of the delay from hospitalization-to-death.FindingsOur estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60 – 1.87) on 1 March 2020 to 0.69 (95% CI 0.68-0.70) on 15 April 2020, due to various non-pharmaceutical interventions including school closures, a ban on public gatherings including sports and religious events, and full or partial closure of non-essential businesses. Based on these estimates and given that a near complete containment is no longer feasible, it is likely that the outbreak may continue until the end of the 2020 if the current level of physical distancing and interventions continue and no effective vaccination or therapeutic are developed and made widely available.InterpretationThe series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19 within the studied time period. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead the public health decisions, policy makers, and general public especially in the earlier stages of the outbreak.FundingNil.

scholarly journals An economic evaluation of Influenza and COVID -19 pandemic prevention and control interventions: a systematic review

2020 ◽  
Author(s):  
Amanuel Yigezu ◽  
Mezgebu Yitayal ◽  
Alemnesh Mirkuzie ◽  
Zekarias Getu ◽  
Alemayehu Hailu
Keyword(s):  
Public Health ◽  
Economic Evaluation ◽  
Prevention And Control ◽  
Case Fatality ◽  
Cost Effective ◽  
School Closure ◽  
Case Fatality Ratio ◽  
Health Measures ◽  
And Control ◽  
Pharmaceutical Interventions

Abstract Background: COVID-19 causes more 1.3 million deaths globally in just nine months. Influenza is a virus with respiratory symptoms, fever, and systemic symptoms very similar to COVID 19. Various public health measures have been taken by governments and health authorities to prevent and control the pandemics. This study aimed to review the economic evaluation of public health measures against COVID-19 and influenza pandemics.Methods: We performed a systematic review of the literature to identify full economic evaluation studies on Influenza and COVID-19 pandemic published from 1998-2020. We built an exhaustive database search strategy. The search was done in Pubmed, Web of Science, EMBASE databases, and grey literature. We extracted data from selected studies using a structured data collection form after conducting a risk of bias assessment. Narrative summary tables were used to present the result and characteristics of eligible studies. Furthermore, we converted findings of studies that reported their outcome in costs per case averted and death averted into costs per life-year gained. All cost and Cost-effectiveness ratios were converted to 2019 US dollars using the exchange rate and GDP deflator. The study was registered in PROSPERO with registration No. CRD42020192384.Results: The review revealed that most of the studies were conducted in high-income countries, and only few of the studies were on non-pharmaceutical interventions. Stockpiling drugs for the treatment of sick patients was found cost-effective in most of the studies. Treatment with antiviral drugs and vaccination were found very cost-effective. The addition of school closure to other interventions was considered cost-effective only for a pandemic with a high case fatality ratio. Almost all interventions were sensitive to the infectivity and severity of the pandemic. Most of the studies were also cost-effective from the societal perspective indicating a higher net societal benefit from the pandemic prevention and control strategies.Conclusion: In conclusion, most of the interventions were cost-effective under various scenarios while school closure was cost-effective under a 'high case-fatality 'ratio' scenario only. Furthermore, the level of the pandemic's infectivity and severity were the key drivers of the cost-effectiveness of both pharmaceutical and non-pharmaceutical interventions.

A Note on Estimating the Case Fatality Ratio for Novel Corona Virus Disease (Covid-19)

Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Prafulla Kumar Swain
Keyword(s):  
Confidence Interval ◽  
Graphical Representation ◽  
Virus Disease ◽  
Case Fatality ◽  
Case Fatality Ratio ◽  
Healthcare Planning ◽  
Robust Estimates ◽  
University Of Oxford ◽  
Pros And Cons ◽  
Death Cases

Background: In this paper an attempt has been made to estimate the Case Fatality Ratio (CFR) for coronavirus disease of India and few selected countries. and Also, highlighted the pros and cons of obtaining crude and adjusted CFR of COVID-19 pandemic. Material and Methods: Data extracted from WHO situation report and University of Oxford website have been used for this analysis. The CFR and its 95% confidence interval were computed, trend and bar plot was used for graphical representation. Results: The worldwide crude CFR stands 6.73% (95% CI 6.69 to 6.76) based on 21, 83, 877 confirmed and 1,46,872 death cases(as on 17th April,2020). Belgium was highest CFR 13.95% as compared to others. However, India’s CFR was found to be around 3.26% (as on 17th April, 2020). Conclusion: In conclusion, the estimation and interpretation of CFR is critical in response to ongoing COVID-19. The initial CFR estimates are subject to change, still it is useful for healthcare planning over the coming months. Moreover, the precise and robust estimates of CFR will be available only at the end of the epidemic.

Covid-19 Cases in India: A Visual Exploratory Data Analysis Model (Preprint)

2020 ◽  
Author(s):  
Jayesh S
Keyword(s):  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Case Fatality ◽  
Public Health Emergency ◽  
Virus Spread ◽  
Analysis Model ◽  
Case Fatality Ratio ◽  
First Case ◽  
Exploratory Data ◽  
The Government

UNSTRUCTURED Covid-19 outbreak was first reported in Wuhan, China. The deadly virus spread not just the disease, but fear around the globe. On January 2020, WHO declared COVID-19 as a Public Health Emergency of International Concern (PHEIC). First case of Covid-19 in India was reported on January 30, 2020. By the time, India was prepared in fighting against the virus. India has taken various measures to tackle the situation. In this paper, an exploratory data analysis of Covid-19 cases in India is carried out. Data namely number of cases, testing done, Case Fatality ratio, Number of deaths, change in visits stringency index and measures taken by the government is used for modelling and visual exploratory data analysis.

scholarly journals Correlates of SARS-CoV-2 Variants on Deaths, Case Incidence and Case Fatality Ratio among the Continents for the Period of 1 December 2020 to 15 March 2021

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1061
Author(s):  
Wajdy J. Al-Awaida ◽  
Baker Jawabrah Al Hourani ◽  
Samer Swedan ◽  
Refat Nimer ◽  
Foad Alzoughool ◽  
...  
Keyword(s):  
Negative Correlation ◽  
Significant Positive Correlation ◽  
Vaccine Development ◽  
Case Fatality ◽  
Significant Negative Correlation ◽  
Reference Sequence ◽  
Genome Sequences ◽  
Positive Correlation ◽  
Case Fatality Ratio ◽  
Epidemiological Surveys

The outbreak of coronavirus disease 2019 (COVID-19), by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has quickly developed into a worldwide pandemic. Mutations in the SARS-CoV-2 genome may affect various aspects of the disease including fatality ratio. In this study, 553,518 SARS-CoV-2 genome sequences isolated from patients from continents for the period 1 December 2020 to 15 March 2021 were comprehensively analyzed and a total of 82 mutations were identified concerning the reference sequence. In addition, associations between the mutations and the case fatality ratio (CFR), cases per million and deaths per million, were examined. The mutations having the highest frequencies among different continents were Spike_D614G and NSP12_P323L. Among the identified mutations, NSP2_T153M, NSP14_I42V and Spike_L18F mutations showed a positive correlation to CFR. While the NSP13_Y541C, NSP3_T73I and NSP3_Q180H mutations demonstrated a negative correlation to CFR. The Spike_D614G and NSP12_P323L mutations showed a positive correlation to deaths per million. The NSP3_T1198K, NS8_L84S and NSP12_A97V mutations showed a significant negative correlation to deaths per million. The NSP12_P323L and Spike_D614G mutations showed a positive correlation to the number of cases per million. In contrast, NS8_L84S and NSP12_A97V mutations showed a negative correlation to the number of cases per million. In addition, among the identified clades, none showed a significant correlation to CFR. The G, GR, GV, S clades showed a significant positive correlation to deaths per million. The GR and S clades showed a positive correlation to number of cases per million. The clades having the highest frequencies among continents were G, followed by GH and GR. These findings should be taken into consideration during epidemiological surveys of the virus and vaccine development.

scholarly journals Regional Variability in COVID-19 Case Fatality Rate in Canada, February–December 2020

2021 ◽  
Vol 18 (4) ◽  
pp. 1839
Author(s):  
Eunha Shim
Keyword(s):  
British Columbia ◽  
Case Fatality Rate ◽  
Case Reports ◽  
Case Fatality ◽  
Health Interventions ◽  
Fatality Rate ◽  
Older Individuals ◽  
Regional Variability ◽  
Provincial Level ◽  
Mortality Burden

A total of 475,214 COVID-19 cases, including 13,659 deaths, had been recorded in Canada as of 15 December 2020. The daily reports of confirmed cases and deaths in Canada prior to 15 December 2020 were obtained from publicly available sources and used to examine regional variations in case fatality rate (CFR). Based on a factor of underestimation and the duration of time from symptom onset to death, the time-delay adjusted CFR for COVID-19 was estimated in the four most affected provinces (Quebec, Ontario, Alberta, and British Columbia) and nationwide. The model-based adjusted CFR was higher than the crude CFR throughout the pandemic, primarily owing to the incorporation in our estimation of the delay between case reports and deaths. The adjusted CFR in Canada was estimated to be 3.36% nationwide. At the provincial level, the adjusted CFR was the highest in Quebec (5.13%)—where the proportion of deaths among older individuals was also the highest among the four provinces—followed by Ontario (3.17%), British Columbia (1.97%), and Alberta (1.13%). Provincial-level variations in CFR were considerable, suggesting that public health interventions focused on densely populated areas and elderly individuals can ameliorate the mortality burden of the COVID-19 pandemic.

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