scholarly journals Omicron Impact in India: An Early Analysis of the Ongoing COVID-19 Third Wave

2022 ◽  
Author(s):  
Rajesh Ranjan
Keyword(s):  
Rapid Growth ◽  
Case Fatality Rate ◽  
Reproduction Number ◽  
Case Fatality ◽  
Sir Model ◽  
Third Wave ◽  
Fatality Rate ◽  
Sequencing Data ◽  
The Third ◽  
Second Wave

India is currently experiencing the third wave of COVID-19, which began on around 28 Dec. 2021. Although genome sequencing data of a sufficiently large sample is not yet available, the rapid growth in the daily number of cases, comparable to South Africa, United Kingdom, suggests that the current wave is primarily driven by the Omicron variant. The logarithmic regression suggests the growth rate of the infections during the early days in this wave is nearly four times than that in the second wave. Another notable difference in this wave is the relatively concurrent arrival of outbreaks in all the states; the effective reproduction number (Rt) although has significant variations among them. The test positivity rate (TPR) also displays a rapid growth in the last 10 days in several states. Preliminary estimates with the SIR model suggest that the peak to occur in late January 2022 with peak caseload exceeding that in the second wave. Although the Omicron trends in several countries suggest a decline in case fatality rate and hospitalizations compared to Delta, a sudden surge in active caseload can temporarily choke the already stressed healthcare India is currently experiencing the third wave of COVID-19, which began on around 28 Dec. 2021. Although genome sequencing data of a sufficiently large sample is not yet available, the rapid growth in the daily number of cases, comparable to South Africa, United Kingdom, suggests that the current wave is primarily driven by the Omicron variant. The logarithmic regression suggests the growth rate of the infections during the early days in this wave is nearly four times than that in the second wave. Another notable difference in this wave is the relatively concurrent arrival of outbreaks in all the states; the effective reproduction number (Rt) although has significant variations among them. The test positivity rate (TPR) also displays a rapid growth in the last 10 days in several states. Preliminary estimates with the SIR model suggest that the peak to occur in late January 2022 with peak caseload exceeding that in the second wave. Although the Omicron trends in several countries suggest a decline in case fatality rate and hospitalizations compared to Delta, a sudden surge in active caseload can temporarily choke the already stressed healthcare infrastructure. Therefore, it is advisable to strictly adhere to COVID-19 appropriate behavior for the next few weeks to mitigate an explosion in the number of infections.

scholarly journals Impact of COVID-19 Variants on the Second Wave in India and Subsequent Discretion of Possibilities of the Third Wave

2021 ◽  
pp. 115-126
Author(s):  
Sudarshan Ramaswamy ◽  
Meera Dhuria ◽  
Sumedha M. Joshi ◽  
Deepa H Velankar
Keyword(s):  
Herd Immunity ◽  
Sir Model ◽  
The Other ◽  
Third Wave ◽  
Focal Points ◽  
Current Analysis ◽  
The Third ◽  
The Impact ◽  
Second Wave ◽  
Insight Into

Introduction: Epidemiological comprehension of the COVID-19 situation in India can be of great help in early prediction of any such indications in other countries and possibilities of the third wave in India as well. It is essential to understand the impact of variant strains in the perspective of the rise in daily cases during the second wave – Whether the rise in cases witnessed is due to the reinfections or the surge is dominated by emergence of mutants/variants and reasons for the same. Overall objective of this study is to predict early epidemiological indicators which can potentially lead to COVID-19 third wave in India. Methodology: We analyzed both the first and second waves of COVID-19 in India and using the data of India’s SARS-CoV-2 genomic sequencing, we segregated the impact of the Older Variant (OV) and the other major variants (VOI / VOC).  Applying Kermack–McKendrick SIR model to the segregated data progression of the epidemic in India was plotted in the form of proportion of people infected. An equation to explain herd immunity thresholds was generated and further analyzed to predict the possibilities of the third wave. Results: Considerable difference in ate of progression of the first and second wave was seen. The study also ascertains that the rate of infection spread is higher in Delta variant and is expected to have a higher threshold (>2 times) for herd immunity as compared to the OV. Conclusion: Likelihood of the occurrence of the third wave seems unlikely based on the current analysis of the situation, however the possibilities cannot be ruled out. Understanding the epidemiological details of the first and second wave helped in understanding the focal points responsible for the surge in cases during the second wave and has given further insight into the future.

scholarly journals Covid-19 Fatality Rate in Third World Countries: A Review of Environmental Challenges and Impacts on Public Health and Human Security

2021 ◽  
Vol 9 (1) ◽  
pp. 39-44
Author(s):  
Chukwuemeka E. Etodike ◽  
◽  
Elsie C. Ekeghalu ◽  
Kelechi Johnmary Ani ◽  
Emmanuel Mutambara
Keyword(s):  
Public Health ◽  
Case Fatality Rate ◽  
Third World ◽  
Case Fatality ◽  
Personal Hygiene ◽  
Fatality Rate ◽  
Environmental Challenges ◽  
The Third ◽  
The Third World ◽  
Sanitary Conditions

The novel coronavirus is far from being over; with the case-fatality rate (CFR) hitting more than 16,500 globally as of July, there is a worry that despite the fact that the global CFR curve is showing signs of flattening, the environmental peculiarities of the third world countries may be abetting global efforts towards containing the virus. Therefore, this review x-rayed these peculiarities in the light of their current concern in public health as per their contribution to the persistent surge in CFR in most developing nations. Given that the virus is transmitted via droplets, the review focused on how the state of public and environmental challenges such as air as well as water pollution and personal hygiene could be abetting the surge in coronavirus infections and morbidity. The review revealed, among other things, that challenges associated with poor sanitary conditions, lack of potable water, unventilated environments, air pollution, and poor inter-personal hygiene are devastating challenges in the fight against the pandemic. The implication is that since these conditions are systematic in nature, it may take more than average effort and public sacrifice to checkmate the case-fatality rate of the virus in the third world. Therefore, call for studies is necessary to establish empiricism for CFR patterns and ratio across areas in deplorable environmental and sanitary conditions.

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 Decreased Case Fatality Rate of COVID-19 in the Second Wave: a study in 53 countries.

2020 ◽  
Author(s):  
Guihong Fan ◽  
Zhichun Yang ◽  
Qianying Lin ◽  
Shi Zhao ◽  
Lin Yang ◽  
...  
Keyword(s):  
Case Fatality Rate ◽  
Case Fatality ◽  
Fatality Rate ◽  
Second Wave

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 A broken bone no longer a burden to carry: a destination in sight

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Saabea Owusu Konadu ◽  
Dominic Konadu-Yeboah ◽  
Gilda Opoku ◽  
Obed Nyarko Ofori
Keyword(s):  
Cause Of Death ◽  
Case Fatality Rate ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Case Fatality ◽  
Fatality Rate ◽  
Road Traffic Accidents ◽  
The Third

Worldwide the third leading cause of death among persons under 40 years is attributed to trauma(1). In Ghana road traffic accidents have a case fatality rate of about 17%(3). Over the years with interventions and policies by AO Alliance the burden and morbidity following trauma especially road traffic accidents have reduced; with a destination in sight where a broken bone is no longer a burden to carry.

scholarly journals Novel Uses of Three-Parameter Logistic Models and First-Derivative Models for the Coronavirus Disease (COVID-19) Epidemic in the United States, in Three Distinct Scenarios

2020 ◽  
Author(s):  
Bishoy T. Samuel
Keyword(s):  
Logistic Model ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Logistic Models ◽  
The United States ◽  
Fatality Rate ◽  
First Derivative ◽  
The Third ◽  
Variable Versus ◽  
Growth Deceleration

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.

scholarly journals Genetic association of TMPRSS2 rs2070788 polymorphism with COVID-19 Case Fatality Rate among Indian populations

2021 ◽  
Author(s):  
RUDRA KUMAR PANDEY ◽  
Anshika Srivastava ◽  
Prajjval Pratap Singh ◽  
Gyaneshwer Chaubey
Keyword(s):  
Case Fatality Rate ◽  
Disease Susceptibility ◽  
Genetic Relatedness ◽  
South Asians ◽  
Case Fatality ◽  
Next Generation Sequencing Data ◽  
Fatality Rate ◽  
Sequencing Data ◽  
Significant Positive Association ◽  
Populations At Risk

SARS-CoV2, the causative agent for COVID-19, an ongoing pandemic, engages the ACE2 receptor to enter the host cell through S protein priming by a serine protease, TMPRSS2. Variation in the TMPRSS2 gene may account for the difference in population disease susceptibility. The haplotype-based genetic sharing and structure of TMPRSS2 among global populations have not been studied so far. Therefore, in the present work, we used this approach with a focus on South Asia to study the haplotypes and their sharing among various populations worldwide. We have used next-generation sequencing data of 393 individuals and analysed the TMPRSS2 gene. Our analysis of genetic relatedness for this gene showed a closer affinity of South Asians with the West Eurasian populations therefore, host disease susceptibility and severity particularly in the context of TMPRSS2 will be more akin to West Eurasian instead of East Eurasian. This is in contrast to our prior study on ACE2 gene which shows South Asian haplotypes have a strong affinity towards West Eurasians. Thus ACE2 and TMPRSS2 have an antagonistic genetic relatedness among South Asians. We have also tested the SNPs frequencies of this gene among various Indian state populations with respect to the case fatality rate. Interestingly, we found a significant positive association between the rs2070788 SNP (G Allele) and the case fatality rate in India. It has been shown that the GG genotype of rs2070788 allele tends to have a higher expression of TMPRSS2 in the lung compared to the AG and AA genotypes, thus it might play a vital part in determining differential disease vulnerability. We trust that this information will be useful in underscoring the role of the TMPRSS2 variant in COVID-19 susceptibility and using it as a biomarker may help to predict populations at risk.

scholarly journals The SIR model towards the data

2021 ◽  
Vol 136 (8) ◽  
Author(s):  
Ignazio Lazzizzera
Keyword(s):  
Generation Time ◽  
Reproduction Number ◽  
Removal Rate ◽  
Sir Model ◽  
Infectious Period ◽  
Third Wave ◽  
Real Numbers ◽  
The Third ◽  
Study Case ◽  
Good Agreement

AbstractIn this work, the SIR epidemiological model is reformulated so to highlight the important effective reproduction number, as well as to account for the generation time, the inverse of the incidence rate, and the infectious period (or removal period), the inverse of the removal rate. The aim is to check whether the relationships the model poses among the various observables are actually found in the data. The study case of the second through the third wave of the Covid-19 pandemic in Italy is taken. Given its scale invariance, initially the model is tested with reference to the curve of swab-confirmed infectious individuals only. It is found to match the data, if the curve of the removed (that is healed or deceased) individuals is assumed underestimated by a factor of about 3 together with other related curves. Contextually, the generation time and the removal period, as well as the effective reproduction number, are obtained fitting the SIR equations to the data; the outcomes prove to be in good agreement with those of other works. Then, using knowledge of the proportion of Covid-19 transmissions likely occurring from individuals who didn’t develop symptoms, thus mainly undetected, an estimate of the real numbers of the epidemic is obtained, looking also in good agreement with results from other, completely different works. The line of this work is new, and the procedures, computationally really inexpensive, can be applied to any other national or regional case besides Italy’s study case here.

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