COVID19 Analytics – Mask Trash and Shoes a Major Spreader, Newsom & Fauci Being Odd, Florida Wins

Our weekly review of the current COVID data and country comparisons as well as other oddities such as Mask Litter, Trash Cans, and Shoes being unintended spreaders. All this under the guise of Amateur Python Analytics. Brief CSV File Request Code below (Pandas). That will allow you to pull Oxford University Data up to the current date. Enjoy 😉

This is a long one, next week I will make it A LOT shorter.

#covid19 #sarscov2 #data

Code Snippet:
import pandas as pd
import csv
import requests
younameit = pd.read_csv(‘https://covid.ourworldindata.org/data/owid-covid-data.csv’)

https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsduetocoronaviruscovid19comparedwithdeathsfrominfluenzaandpneumoniaenglandandwales/deathsoccurringbetween1januaryand31august2020

https://wwwnc.cdc.gov/eid/article/26/7/20-0885_article

https://www.eurekalert.org/pub_releases/2020-10/uoh-rci100120.php#.X3fUGZsAGM0.wordpress

https://www.cidrap.umn.edu/news-perspective/2020/04/commentary-masks-all-covid-19-not-based-sound-data

Vitamin D may be more effective than masks and distancing combined for COVID ?

Vitamin D may be more effective than masks and distancing combined for COVID ?

In patients older than 40 years they observed that those patients who were vitamin D sufficient were 51.5 percent less likely to die from the infection compared to patients who were vitamin D deficient or insufficient with a blood level of 25-hydroxyvitamin D less than 30 ng/mL.

Holick, who most recently published a study which found that a sufficient amount of vitamin D can reduce the risk of catching coronavirus by 54 percent, believes that being vitamin D sufficient helps to fight consequences from being infected not only with the corona virus but also other viruses causing upper respiratory tract illnesses including influenza. “There is great concern that the combination of an influenza infection and a coronal viral infection could substantially increase hospitalizations and death due to complications from these viral infections.”

#covid19 #sarscov2 #vitaminD

Kaufman HW, Niles JK, Kroll MH, Bi C, Holick MF (2020) SARS-CoV-2 positivity rates associated with circulating 25-hydroxyvitamin D levels. PLOS ONE 15(9): e0239252. https://doi.org/10.1371/journal.pone.0239252

Pandemic Charting – Weaponizing Uncertainty – Countries Do better with a Light touch – Python Data

COVID-19 Made worse By Social Distancing?

We are led to question whether the recommended social distancing measures to prevent SARS-CoV-2 transmission could increase the number of other serious instabilities. The breaking of the contagion pathways reduces the sharing of microorganisms between people, thus favoring dysbiosis, which, in turn, may increase the poor prognosis of the disease. #covid #microbiome #dysbiosis Célia P. F. Domingues, João S. Rebelo, Francisco Dionisio, Ana Botelho, Teresa Nogueira. The Social Distancing Imposed To Contain COVID-19 Can Affect Our Microbiome: a Double-Edged Sword in Human Health. mSphere, 2020; 5 (5) DOI: 10.1128/mSphere.00716-20 https://msphere.asm.org/content/5/5/e00716-20

Lockdowns a Complete Failure compared to controls – Countries that did not? Python Analysis Part 2

Part 2 as promised. We compare cases and death per million from industrialized countries which did little to nothing to Great Britain and the United States. The Data extrapolated is from: https://ourworldindata.org/coronaviru…
#covid19 #lockdown #socialdistancing

(Volume is kind of Choppy midpoint)
Additional Code: From Part 1:
datasw = data.loc[data.iso_code==’SWE’, :]
datagb = data.loc[data.iso_code==’GBR’, :]
dataus = data.loc[data.iso_code==’USA’, :]
datasg = data.loc[data.iso_code==’SGP’, :]
datajp = data.loc[data.iso_code==’JPN’, :]
datako = data.loc[data.iso_code==’KOR’, :]
datatw = data.loc[data.iso_code==’TWN’, :]
dataall = [datagb,dataus,datasw,datasg,datajp,datako, datatw]
dataall = pd.concat(dataall)
dataall
dataall.datetime = pd.to_datetime(dataall.date)
dataall.set_index(‘date’, inplace=True)
fig, ax = plt.subplots(figsize=(50,25))
dataall.groupby(‘iso_code’)[‘new_cases_smoothed_per_million’].plot(legend=True,fontsize = 20, linewidth=7.0)
ax.legend([‘Great Britain = Lockdown’,’Japan = No LD’, ‘South Korea = No LD’, ‘Singapore = LD JUNE -Migrant LD HIghest POP Density’, ‘Sweden = No LD’, ‘Taiwan = No LD’,’USA = Lockdown’],prop=dict(size=50))
comp = dataall.loc[‘2020-09-18’]
comp.set_index(“iso_code”, inplace=True)
comp= pd.DataFrame(comp[[‘total_cases_per_million’,’total_deaths_per_million’]])
plt.rc(‘legend’, fontsize=50)
comp.plot.bar(rot=0, figsize=(20,20),fontsize=30)

Pandemic Over? COVID-19 World data Amateur Python Analysis

From an educational perspective, we review current COVID-19 data and arrive look at lockdowns and population density appears to have no numerical effect currently on COVID-19. In any case, this is more about exploring the code from a beginner’s standpoint with Python and DataFrames.
#covid19 #pandemicover #coviddata
CSV files found here:
https://ourworldindata.org/coronaviru…
Code: (Had to remove the angle brackets)
import numpy as np
import pandas as pd
from scipy import stats
import statsmodels.api as sm
import matplotlib.pyplot as plt
import pandas as pd
from scipy.stats import spearmanr
from scipy.stats import kendalltau
from scipy.stats import pearsonr
from scipy import stats
import seaborn as sns
import warnings
warnings.filterwarnings(“ignore”)
#Pandemic
Claim Currently Invalid —Ralph Turchiano
data = pd.read_csv(‘owid-covid-data-19SEP2020.csv’)
data.info()
pd.set_option(‘max_columns’, None)
data.tail(5)
data[‘date’] = pd.to_datetime(data[‘date’])
data.info()
data_18SEP = data[data[‘date’]==’2020-09-18′]
data_ind = data_18SEP[data_18SEP[‘human_development_index’]=.8]
data_ind.head(10)
data_ind.drop([‘iso_code’,’continent’,’handwashing_facilities’,’stringency_index’,], axis=1, inplace=True)
data_ind.columns
data_ind[‘extreme_poverty’].fillna(0, inplace=True)
data_compare = pd.DataFrame([data.loc[37991],data.loc[41736]])
data_compare
data_compare.set_index(‘location’,inplace=True)
data_compare[‘total_cases_per_million’]
data_Swe_USA=pd.DataFrame(data_compare[[‘total_cases_per_million’,’new_cases_per_million’,’new_deaths_per_million’]])
data_Swe_USApd.DataFrame(data_compare[[‘total_cases_per_million’,’new_cases_per_million’,’new_deaths_per_million’]])
data_Swe_USA
data_ind.drop([‘date’,’new_cases’,’new_deaths’,’total_tests’, ‘total_tests_per_thousand’,
‘new_tests_per_thousand’, ‘new_tests_smoothed’, ‘new_tests’,
‘new_tests_smoothed_per_thousand’, ‘tests_per_case’,’tests_units’,’new_deaths_per_million’,’positive_rate’ ], axis=1, inplace=True)
data_ind.tail()
data_ind.dropna(inplace=True)
data_ind.corr(“kendall”)
data_18SEP.tail()
data_18SEP.loc[44310]
data_18SEP.loc[44310,[‘new_cases_smoothed_per_million’,’new_deaths_smoothed_per_million’]]
New =pd.DataFrame(data[[‘new_cases_smoothed_per_million’,’new_deaths_smoothed_per_million’]])
New.corr(‘kendall’)
dataw = data.loc[data[‘iso_code’] == ‘OWID_WRL’]
dataw
dataw.datetime = pd.to_datetime(data.date)
dataw.set_index(‘date’, inplace=True)
data_cl = pd.DataFrame(dataw[[‘new_deaths_smoothed’,’new_cases_smoothed’]])
data_cl.dropna(inplace=True)
data_cl.plot(figsize=(30,12))
data_cl.tail(20)

COVID-19 Tracking Data API and Data Anomalies (No Correlations? Cases to Hospitalizations Increases)

Is there a correlation between Positive cases and Hospitalizations? Below is the API for python access, open to all who desire to filter the data. I want to just give easy access to all the beginner students data scientists out there, such as myself..Explore and Discover: **My Apologies It says High Def, but does not look High Def on video here**

Code: import matplotlib.pyplot as plt import pandas as pd from scipy import stats import statsmodels.api as sm import requests import time from IPython.display import clear_output response = requests.get(“https://covidtracking.com/api/v1/us/daily.csv”) covid = response.content ccc = open(“daily.csv”,”wb”) ccc.write(covid) ccc.close() df = pd.read_csv(“daily.csv”, index_col = ‘date’) df.head() data = df[[‘positiveIncrease’,’hospitalizedIncrease’]] dataT = df[[‘positiveIncrease’,’hospitalizedIncrease’,’hospitalizedCurrently’]] dataD = df[[‘hospitalizedIncrease’,’deathIncrease’]] dataT.head(20) plt.figure(figsize=(20,10)) Y = data[‘positiveIncrease’] X = data[‘hospitalizedIncrease’] plt.scatter(X,Y) plt.ylabel(“Tested Positive Increase”) plt.xlabel(“Hospitalization Increase”) plt.show() Y1 = sm.add_constant(Y) reg = sm.OLS(X, Y1).fit() reg.summary() data.plot(y=[‘hospitalizedIncrease’,’positiveIncrease’],xticks=data.index[0:len(data):30], rot=90, figsize=(20,10) ) for x in range(len(data)): plt.figure(figsize=(20,10)) plt.xticks( data.index.values[0:len(data):30], rotation = 90, fontsize=20 ) plt.plot(data.tail(x))

Honeysuckle Decoction Inhibits SARS-CoV-2

In a new study in Cell Discovery, Chen-Yu Zhang’s group at Nanjing University and two other groups from Wuhan Institute of Virology and the Second Hospital of Nanjing present a novel finding that absorbed miRNA MIR2911 in honeysuckle decoction (HD) can directly target SARS-CoV-2 genes and inhibit viral replication. Drinking of HD accelerate the negative conversion of COVID-19 patients.

#mir2911 #sarcov2 #honeysuckle

Zhou, L., Zhou, Z., Jiang, X. et al. Absorbed plant MIR2911 in honeysuckle decoction inhibits SARS-CoV-2 replication and accelerates the negative conversion of infected patients. Cell Discov 6, 54 (2020). https://doi.org/10.1038/s41421-020-00197-3

https://www.nature.com/articles/s41421-020-00197-3#ethics

An easier way to go vegan, Vitamin B12 CAN be produced during grain fermentation

The highest production was found in the rice bran (ca. 742 ng/g dw), followed by the buckwheat bran (ca. 631 ng/g dw), after fermentation. Meanwhile, the addition of L. brevis was able to dominate indigenous microbes during fermentation and thus greatly improve microbial safety during the fermentation of different grain materials. #b12 #vegan #fermentation https://helda.helsinki.fi/bitstream/handle/10138/317682/insitufo.pdf?sequence=1&isAllowed=y In situ fortification of vitamin B12 in grain materials by fermentation withPropionibacterium freudenreichii, Chong Xie ISBN 978-951-51-6355-4 (PAPERBACK) ISBN 978-951-51-6356-1 (PDF, http://ETHESIS.HELSINKI.FI) ISSN 0355-1180 UNIGRAFIA HELSINKI 2020

Black raspberries show promise for reducing skin inflammation, allergies

More COVID Research Information Censored

More COVID Research Censored CDC and the WHO, to my dismay, are either directly or indirectly controlling the flow of information and research, possibly creating an echo chamber of bias. The level of censorship is getting so out of control; it is highly likely now it may be resulting in harm in a variety of societal dimensions. As well as the Freedom to Speech is becoming rapidly stratified among those in positions of wealth, power, or fame, It is becoming painfully apparent that self-proclaimed thought leaders may not be behooving us in times of crisis, manufactured, self-inflicted, or real. At the very least, by not reviewing and growing from our errors, we are, in all essence, committed to repeating them. Freedom of Speech, in its most basic form, is simply the freedom to speak. Take that right away from one, and you build a case to take it away from all, for, of course, your own protection. #censorship #freedomofspeech #covid

100% Cure Rate Pancreatic Cancer Experimental Study Animal Model

100% Cure Rate Pancreatic Cancer Experimental Study Animal Model

100% Cure Rate Pancreatic Cancer Experimental Study Animal Model

A research team reports that combining a type of radiation therapy with immunotherapy not only cures pancreatic cancer in mice, but appears to reprogram the immune system to create an ‘immune memory’ in the same way that a vaccine keeps the flu away. The result is that the combination treatment also destroyed pancreatic cells that had spread to the liver, a common site for metastatic disease.

#il-12 #sbrt #pancraticcancercure

Bradley N. Mills, Kelli A. Connolly, Jian Ye, Joseph D. Murphy, Taylor P. Uccello, Booyeon J. Han, Tony Zhao, Michael G. Drage, Aditi Murthy, Haoming Qiu, Ankit Patel, Nathania M. Figueroa, Carl J. Johnston, Peter A. Prieto, Nejat K. Egilmez, Brian A. Belt, Edith M. Lord, David C. Linehan, Scott A. Gerber. Stereotactic Body Radiation and Interleukin-12 Combination Therapy Eradicates Pancreatic Tumors by Repolarizing the Immune Microenvironment. Cell Reports, 2019; 29 (2): 406 DOI: 10.1016/j.celrep.2019.08.095

https://www.cell.com/cell-reports/fulltext/S2211-1247(19)31157-X?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS221112471931157X%3Fshowall%3Dtrue

Pancreatic cancer, il-12, sbrt, stereotactic body radiotherapy, pancreas, cancer, aggressive, advanced, study, CD8, treatment, immune system, vaccine, cancer vaccine, liver cancer, metastatic

A grape constituent protects against Lung cancer

A grape constituent protects against Lung cancer

A grape constituent protects against Lung cancer

A team of scientists studied a well-known natural product, resveratrol, which is found in grapes and in red wine. While its chemopreventive properties against cancers affecting the digestive tract have been documented by previous studies, resveratrol has so far shown no effect on lung cancers. Thanks to nasal administration, the UNIGE team obtained very promising results in a study conducted in mice.

Aymeric Monteillier, Aymone Voisin, Pascal Furrer, Eric Allémann, Muriel Cuendet. Intranasal administration of resveratrol successfully prevents lung cancer in A/J mice. Scientific Reports, 2018; 8 (1) DOI: 10.1038/s41598-018-32423-0

Probiotics in Children reduced antibiotic prescriptions up to 53%

Probiotics in Children reduced antibiotic prescriptions up to 53%

Probiotics in Children reduced antibiotic prescriptions up to 53%

Researchers found that when the results from twelve studies were pooled together, infants and children were 29% percent less likely to have been prescribed antibiotics if they received probiotics as a daily health supplement. When the analysis was repeated with only the highest quality studies, this percentage increased to 53%.

Sarah King, Daniel Tancredi, Irene Lenoir-Wijnkoop, Kelsie Gould, Hailey Vann, Grant Connors, Mary Ellen Sanders, Jeffrey A Linder, Andi L Shane, Dan Merenstein; Does probiotic consumption reduce antibiotic utilization for common acute infections? A systematic review and meta-analysis, European Journal of Public Health, , cky185, https://doi.org/10.1093/eurpub/cky185

Children, infants, probiotics, antibiotics, Lactobacillus, Bifidobacterium, illness, treatment, study