scholarly journals A novel cohort analysis approach to determining the case fatality rate of COVID-19 and other infectious diseases

Author(s):  
Charit Samyak Narayanan

AbstractAs the Coronavirus contagion develops, it is increasingly important to understand the dynamics of the disease. Its severity is best described by two parameters: its ability to spread and its lethality. Here, we combine a mathematical model with a cohort analysis approach to determine the range of case fatality rates (CFR). We use a logistical function to describe the exponential growth and subsequent flattening of COVID-19 CFR that depends on three parameters: the final CFR (L), the CFR growth rate (k), and the onset-to-death interval (t0). Using the logistic model with specific parameters (L, k and t0), we calculate the number of deaths each day for each cohort. We build an objective function that minimizes the root mean square error between the actual and predicted values of cumulative deaths and run multiple simulations by altering the three parameters. Using all of these values, we find out which set of parameters returns the lowest error when compared to the number of actual deaths. We were able to predict the CFR much closer to reality at all stages of the viral outbreak compared to traditional methods. This model can be used far more effectively than current models to estimate the CFR during an outbreak, allowing for better planning. The model can also help us better understand the impact of individual interventions on the CFR. With much better data collection and labeling, we should be able to improve our predictive power even further.

2020 ◽  
Author(s):  
Charit Samyak Narayanan

AbstractThe COVID-19 contagion has developed at an alarming rate in the US and as of April 24, 2020, tens of thousands of people have already died from the disease. In the event of an outbreak like such, forecasting the extent of the mortality that will occur is crucial to aid the implementation of effective interventions. Mortality depends on two factors: the case fatality rate and the case incidence. We combine a cohort-based model that determines case fatality rates along with a modified logistic model that evaluates the case incidence to determine the number of deaths in all the US states over time; the model is also able to include the impact of interventions. Both models yield exceptional goodness-of-fit. The model predicted a range of death outcomes (79k to 246k) all of which are considerably greater than the figures presented in mainstream media. This model can be used more effectively than current models to estimate the number of deaths during an outbreak, allowing for better planning.


2020 ◽  
Author(s):  
Ahmed Youssef Kada

BACKGROUND Covid-19 is an emerging infectious disease like viral zoonosis caused by new coronavirus SARS CoV 2. On December 31, 2019, Wuhan Municipal Health Commission in Hubei province (China) reported cases of pneumonia, the origin of which is a new coronavirus. Rapidly extendable around the world, the World Health Organization (WHO) declares it pandemic on March 11, 2020. This pandemic reaches Algeria on February 25, 2020, date on which the Algerian minister of health, announced the first case of Covid-19, a foreign citizen. From March 1, a cluster is formed in Blida and becomes the epicentre of the coronavirus epidemic in Algeria, its total quarantine is established on March 24, 2020, it will be smoothly alleviated on April 24. A therapeutic protocol based on hydroxychloroquine and azithromycin was put in place on March 23, for complicated cases, it was extended to all the cases confirmed on April 06. OBJECTIVE This study aimed to demonstrate the effectiveness of hydroxychloroquin/azithromycin protocol in Algeria, in particular after its extension to all patients diagnosed COVID-19 positive on RT-PCR test. We were able to illustrate this fact graphically, but not to prove it statistically because the design of our study, indeed in the 7 days which followed generalization of therapeutic protocol, case fatality rate decrease and doubling time increase, thus confirming the impact of wide and early prescription of hydroxychloroquin/azithromycin protocol. METHODS We have analyzed the data collected from press releases and follow-ups published daily by the Ministry of Health, we have studied the possible correlations of these data with certain events or decisions having a possible impact on their development, such as confinement at home and its reduction, the prescription of hydroxychloroquine/azithromycin combination for serious patients and its extension to all positive COVID subjects. Results are presented in graphics, the data collection was closed on 31/05/2020. RESULTS Covid-19 pandemic spreads from February 25, 2020, when a foreign citizen is tested positive, on March 1 a cluster is formed in the city of Blida where sixteen members of the same family are infected during a wedding party. Wilaya of Blida becomes the epicentre of coronavirus epidemic in Algeria and lockdown measures taken, while the number of national cases diagnosed begins to increases In any event, the association of early containment measures combined with a generalized initial treatment for all positive cases, whatever their degree of severity, will have contributed to a reduction in the fatality rate of COVID 19 and a slowing down of its doubling time. CONCLUSIONS In Algeria, the rapid combination of rigorous containment measure at home and early generalized treatment with hydroxychloroquin have demonstrated their effectiveness in terms of morbidity and mortality, the classic measures of social distancing and hygiene will make it possible to perpetuate these results by reducing viral transmission, the only unknown, the reopening procedure which can only be started after being surrounded by precautions aimed at ensuring the understanding of the population. CLINICALTRIAL Algeria, Covid-19, pandemic, hydroxychloroquin, azithromycin, case fatality rate


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2872
Author(s):  
Miroslav Uhrina ◽  
Anna Holesova ◽  
Juraj Bienik ◽  
Lukas Sevcik

This paper deals with the impact of content on the perceived video quality evaluated using the subjective Absolute Category Rating (ACR) method. The assessment was conducted on eight types of video sequences with diverse content obtained from the SJTU dataset. The sequences were encoded at 5 different constant bitrates in two widely video compression standards H.264/AVC and H.265/HEVC at Full HD and Ultra HD resolutions, which means 160 annotated video sequences were created. The length of Group of Pictures (GOP) was set to half the framerate value, as is typical for video intended for transmission over a noisy communication channel. The evaluation was performed in two laboratories: one situated at the University of Zilina, and the second at the VSB—Technical University in Ostrava. The results acquired in both laboratories reached/showed a high correlation. Notwithstanding the fact that the sequences with low Spatial Information (SI) and Temporal Information (TI) values reached better Mean Opinion Score (MOS) score than the sequences with higher SI and TI values, these two parameters are not sufficient for scene description, and this domain should be the subject of further research. The evaluation results led us to the conclusion that it is unnecessary to use the H.265/HEVC codec for compression of Full HD sequences and the compression efficiency of the H.265 codec by the Ultra HD resolution reaches the compression efficiency of both codecs by the Full HD resolution. This paper also includes the recommendations for minimum bitrate thresholds at which the video sequences at both resolutions retain good and fair subjectively perceived quality.


2020 ◽  
Vol 10 (03) ◽  
pp. e342-e345
Author(s):  
Jacques Balayla ◽  
Ariane Lasry ◽  
Yaron Gil ◽  
Alexander Volodarsky-Perel

AbstractOver the last 30 years, the caesarean section rate has reached global epidemic proportions. This trend is driven by multiple factors, an important one of which is the use and inconsistent interpretation of the electronic fetal monitoring (EFM) system. Despite its introduction in the 1960s, the EFM has not definitively improved neonatal outcomes, yet it has since significantly contributed to a seven-fold increase in the caesarean section rate. As we attempt to reduce the caesarean rates in the developed world, we should consider focusing on areas that have garnered little attention in the literature, such as physician sensitization to the poor predictive power of the EFM and the research method biases that are involved in studying the abnormal heart rate patterns—umbilical cord pH relationship. Herein, we apply Bayes theorem to different clinical scenarios to illustrate the poor predictive power of the EFM, as well as shed light on the principle of protopathic bias, which affects the classification of research outcomes among studies addressing the effects of the EFM on caesarean rates. We propose and discuss potential solutions to the aforementioned considerations, which include the re-examination of guidelines with which we interpret fetal heart rate patterns and the development of noninvasive technologies that evaluate fetal pH in real time.


2021 ◽  
pp. 216769682110251
Author(s):  
Samantha G. Farris ◽  
Mindy M. Kibbey ◽  
Erick J. Fedorenko ◽  
Angelo M. DiBello

The psychological effect of the pandemic and measures taken in response to control viral spread are not yet well understood in university students; in-depth qualitative analysis can provide nuanced information about the young adult distress experience. Undergraduate students ( N = 624) in an early US outbreak “hotspot” completed an online narrative writing about the impact and distress experienced due to the COVID-19 pandemic. Data were collected April-May 2020. A random selection of 50 cases were sampled for thematic analysis. Nine themes were identified: viral outbreak distress, fear of virus contraction/transmission, proximity to virus, dissatisfaction with public response, physical distancing distress, social distancing distress, academic and school-related distress, disruptive changes in health behavior and routines, financial strain and unemployment, worsening of pre-existing mental health problems, and social referencing that minimizes distress. Future work is needed to understand the persistence of the distress, in addition to developing methods for assessment, monitoring, and mitigation of the distress.


2020 ◽  
Vol 12 (2) ◽  
pp. 220 ◽  
Author(s):  
Han Xiao ◽  
Fenzhen Su ◽  
Dongjie Fu ◽  
Qi Wang ◽  
Chong Huang

Long time-series monitoring of mangroves to marine erosion in the Bay of Bangkok, using Landsat data from 1987 to 2017, shows responses including landward retreat and seaward extension. Quantitative assessment of these responses with respect to spatial distribution and vegetation growth shows differing relationships depending on mangrove growth stage. Using transects perpendicular to the shoreline, we calculated the cross-shore mangrove extent (width) to represent spatial distribution, and the normalized difference vegetation index (NDVI) was used to represent vegetation growth. Correlations were then compared between mangrove seaside changes and the two parameters—mangrove width and NDVI—at yearly and 10-year scales. Both spatial distribution and vegetation growth display positive impacts on mangrove ecosystem stability: At early growth stages, mangrove stability is positively related to spatial distribution, whereas at mature growth the impact of vegetation growth is greater. Thus, we conclude that at early growth stages, planting width and area are more critical for stability, whereas for mature mangroves, management activities should focus on sustaining vegetation health and density. This study provides new rapid insights into monitoring and managing mangroves, based on analyses of parameters from historical satellite-derived information, which succinctly capture the net effect of complex environmental and human disturbances.


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