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

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))

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

Strawberry tree honey may inhibit colon cancer

Strawberry tree honey may inhibit colon cancer

Strawberry tree honey may inhibit colon cancer

Spanish and Italian researchers have proven that when honey from strawberry trees, a product typical of Mediterranean areas, is added to colon cancer cells grown in the laboratory, cell proliferation is stopped.

Sadia Afrin et al. Strawberry tree honey as a new potential functional food. Part 1: Strawberry tree honey reduces colon cancer cell proliferation and colony formation ability, inhibits cell cycle and promotes apoptosis by regulating EGFR and MAPKs signaling pathways, Journal of Functional Foods (2019). DOI: 10.1016/j.jff.2019.04.035

#strawberrytreehoney #coloncancer #cancer

https://www.sciencedirect.com/science/article/pii/S1756464619302221

Saffron as effective as stimulant medicines in treating ADHD

Saffron as effective as stimulant medicines in treating ADHD

Saffron as effective as stimulant medicines in treating ADHD

A new short-term pilot study in children and teens 6-17 years old with attention-deficit hyperactivity disorder (ADHD) has shown saffron to be as effective at controlling symptoms as methylphenidate, the commonly prescribed drug Ritalin.

Sara Baziar et al, Crocus sativus L. Versus Methylphenidate in Treatment of Children with Attention-Deficit/Hyperactivity Disorder: A Randomized, Double-Blind Pilot Study, Journal of Child and Adolescent Psychopharmacology (2019). DOI: 10.1089/cap.2018.0146

Complete Survival when lethal Bacteria are fed rather than killed (Proof of Concept )

Complete Survival when lethal Bacteria are fed rather than killed (Proof of Concept )

Complete Survival when lethal Bacteria are fed rather than killed (Proof of Concept )

Researchers report that giving mice dietary iron supplements enabled them to survive a normally lethal bacterial infection and resulted in later generations of those bacteria being less virulent. The approach demonstrates in preclinical studies that non-antibiotic-based strategies — such as nutritional interventions — can shift the relationship between the patient and pathogens away from antagonism and toward cooperation.

Karina K. Sanchez, Grischa Y. Chen, Alexandria M. Palaferri Schieber, Samuel E. Redford, Maxim N. Shokhirev, Mathias Leblanc, Yujung M. Lee, Janelle S. Ayres. Cooperative Metabolic Adaptations in the Host Can Favor Asymptomatic Infection and Select for Attenuated Virulence in an Enteric Pathogen. Cell, 2018; DOI: 10.1016/j.cell.2018.07.016

Hemp shows strong potential for treating cancer

Hemp shows strong potential for treating cancer

Hemp shows strong potential for treating cancer

Results from some of the first studies to examine hemp’s ability to fight cancer show that it might one day be useful as plant-based treatment for ovarian cancer.

KY Hemp-induced Modulation of Ovarian Cancer Cell Metastasis: Sara Biela, Annie Wang, and Wasana K. Sumanasekera The FASEB Journal 2018 32:1_supplement, 667.7-667.7

Total Pain Remission with Cold Open Water Swim

Total Pain Remission with Cold Open Water Swim

A short, sharp, cold water swim may offer an alternative to strong painkillers and physiotherapy to relieve severe persistent pain after surgery, suggest doctors in the journal BMJ Case Reports.

Cold forced open-water swimming: a natural intervention to improve postoperative pain and mobilisation outcomes? BMJ Case Reports 2018; doi:10.1136/bcr-2017-222236

Support for adjunctive vitamin C treatment in cancer

2009 study posted for filing

Contact: Amy Gleason Quarshie
agleason@liebertpub.com
914-740-2149
Mary Ann Liebert, Inc./Genetic Engineering News

New Rochelle, NY, March 5, 2009—Serious flaws in a recent study, which concluded that high doses of vitamin C reduce the effectiveness of chemotherapeutic drugs in the treatment of cancer, are revealed in the current issue of Alternative and Complementary Therapies, a journal published by Mary Ann Liebert, Inc. (www.liebertpub.com). This report is available free online at www.liebertpub.com/act

In the Medical Journal Watch column of the latest issue, Jack Challem, a personal nutrition coach and nutrition author from Tucson, Arizona, and a regular contributor to the Journal, challenges the findings of a study published in Cancer Research (2008;68:8031-8038), in which the authors conclude that vitamin C given to mice or cultured cells treated with common anti-cancer drugs reduces the antitumor effects of the chemotherapeutic agents.

Challem points out two main problems with the study: the oxidized form of vitamin C (dehydroascorbic acid) and not actual vitamin C (ascorbic acid) was used; and in the mouse experiments, the animals were given toxic doses of dehydroascorbic acid, a compound that is not used as a dietary supplement in humans.

“This study and the subsequent headlines [it generated] were a grievous disservice to physicians and patients with cancer,” says Challem. He adds that “considerable positive research…has shown striking benefits from high-dose vitamin C (ascorbic acid) in cancer cells and animals—and in actual human beings.”

High-dose intravenous vitamin C is a common form of alternative and complementary therapy for patients receiving chemotherapeutic drugs and is believed to help bring about tumor cell death. In addition, it may promote postsurgical healing by enhancing collagen formation, and increase tissue resistance to tumor spread.

Challem suggests that, “The ideal therapeutic approach would be to tailor individual treatment, including IV vitamin C, from a menu of options.”

 

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Alternative and Complementary Therapies is a bimonthly journal that publishes original research articles, reviews, and commentaries evaluating alternative therapies and how they can be integrated into clinical practice. Topics include botanical medicine, vitamins and supplements, nutrition and diet, mind-body medicine, acupuncture and Traditional Chinese Medicine, ayurveda, indigenous medicine systems, homeopathy, naturopathy, yoga and meditation, manual therapies, energy medicine, and spirituality and health. A complete table of contents and free sample issue may be viewed online at http://www.liebertpub.com/act

Mary Ann Liebert, Inc. (www.liebertpub.com), is a privately held, fully integrated media company known for establishing authoritative peer-reviewed journals in many promising areas of science and biomedical research, including The Journal of Alternative & Complementary Medicine, Medical Acupuncture, and Journal of Medicinal Food. Its biotechnology trade magazine, Genetic Engineering & Biotechnology News (GEN), was the first in its field and is today the industry’s most widely read publication worldwide. A complete list of the firm’s 60 journals, books, and newsmagazines is available at www.liebertpub.com

Mary Ann Liebert, Inc. 140 Huguenot St., New Rochelle, NY 10801-5215
Phone: (914) 740-2100 (800) M-LIEBERT Fax: (914) 740-2101
www.liebertpub.com