Could Lower Testosterone in Older Men Explain Higher COVID-19 Morbidity and Mortalities?

The health scourge imposed on humanity by the COVID-19 pandemic seems not to recede. This fact warrants refined and novel ideas analyzing different aspects of the illness. One such aspect is related to the observation that most COVID-19 casualties were older males, a tendency also noticed in the epidemics of SARS-CoV in 2003 and the Middle East respiratory syndrome in 2012. This gender-related difference in the COVID-19 death toll might be directly involved with testosterone (TEST) and its plasmatic concentration in men. TEST has been demonstrated to provide men with anti-inflammatory and immunological advantages. As the plasmatic concentration of this androgen decreases with age, the health benefit it confers also diminishes. Low plasmatic levels of TEST can be determinant in the infection’s outcome and might be related to a dysfunctional cell Ca2+ homeostasis. Not only does TEST modulate the activity of diverse proteins that regulate cellular calcium concentrations, but these proteins have also been proven to be necessary for the replication of many viruses. Therefore, we discuss herein how TEST regulates different Ca2+-handling proteins in healthy tissues and propose how low TEST concentrations might facilitate the replication of the SARS-CoV-2 virus through the lack of modulation of the mechanisms that regulate intracellular Ca2+ concentrations.

Opening Shot

Yuan-tsung Chen writes her memoir in the midst of growing unrest when in 2019 the Communist rulers try to pass an extradition law in Hong Kong’s Legislative Council. To begin with, they set about “reforming” middle schoolers’ education— for instance, through the Orwellian rewriting of the history of the Cultural Revolution, from the ten-year-long “cataclysm” (Hao Jie—浩劫‎) to the ten years of “arduous exploration and development achievement.” Even according to the official death toll, 1.7 million people perished in the Cultural Revolution. The dead had families or relatives, friends or lovers, so how many more lives were ruined? Yuan-tsung simply cannot accept such a whitewashing without a guilty conscience. She is fully aware of the consequences of confronting the untruth. Nevertheless, she decides to write what she witnessed, saw, and understood as truth.

Anatomy of a Regional Civil War: Guangxi, China, 1967–1968

During the violent early years of China’s Cultural Revolution, the province of Guangxi experienced by far the largest death toll of any comparable region. One explanation for the extreme violence emphasizes a process of collective killings focused on households in rural communities that were long categorized as class enemies by the regime. From this perspective, the high death tolls were generated by a form of collective behavior reminiscent of genocidal intergroup violence in Bosnia, Rwanda, and similar settings. Evidence from investigations conducted in China in the 1980s reveals the extent to which the killings were part of a province-wide suppression of rebel insurgents, carried out by village militia, who also targeted large numbers of noncombatants. Guangxi’s death tolls were the product of a counterinsurgency campaign that more closely resembled the massacres of communists and suspected sympathizers coordinated by Indonesia’s army in wake of the coup that deposed Sukarno in 1965.

Estimation of COVID-19 recovery and decease periods in Canada using delay model

We derive a novel model escorted by large scale compartments, based on a set of coupled delay differential equations with extensive delays, in order to estimate the incubation, recovery and decease periods of COVID-19, and more generally any infectious disease. This is possible thanks to some optimization algorithms applied to publicly available database of confirmed corona cases, recovered cases and death toll. In this purpose, we separate (1) the total cases into 14 groups corresponding to 14 incubation periods, (2) the recovered cases into 406 groups corresponding to a combination of incubation and recovery periods, and (3) the death toll into 406 groups corresponding to a combination of incubation and decease periods. In this paper, we focus on recovery and decease periods and their correlation with the incubation period. The estimated mean recovery period we obtain is 22.14 days (95% Confidence Interval (CI) 22.00–22.27), and the 90th percentile is 28.91 days (95% CI 28.71–29.13), which is in agreement with statistical supported studies. The bimodal gamma distribution reveals that there are two groups of recovered individuals with a short recovery period, mean 21.02 days (95% CI 20.92–21.12), and a long recovery period, mean 38.88 days (95% CI 38.61–39.15). Our study shows that the characteristic of the decease period and the recovery period are alike. From the bivariate analysis, we observe a high probability domain for recovered individuals with respect to incubation and recovery periods. A similar domain is obtained for deaths analyzing bivariate distribution of incubation and decease periods.

Characteristic features of Orissa super cyclone of 29th October, 1999 as observed through CDR Paradip

lkj & bl 'kks/k&Ik= esa 29 vDrwcj] 1999 esa mM+hlk ds rV ij vk, egkpØokr ds Øfed fodkl ds jsMkj ls izkIr gq, vfHky{k.kksa dks izysf[kr djus dk iz;kl fd;k x;k gSA 280800 ;w- Vh- lh- vkSj 290200 ;w- Vh- lh- ds e/; fy, x, 18 ?kaVs dh vof/k ds ih- ih- vkbZ- fp=ksa ls rS;kj fd, x, /kzqoh; vkjs[kksa ds fo’ys"k.k ls bl egkpØokr ds Øfed fodkl ds jkspd igyqvksa dk irk pyk gSA bl fo’ys"k.k ls izkIr gq, izcyhdj.k ds ladsr izs{k.k dh vU; iz.kkfy;ksa ds mi;ksx ls izkIr gq, fo’ys"k.kksa ds vuq:Ik ik, x, gSaA An attempt is made to document the radar observed features of evolution of super cyclone that hit Orissa on 29 October, 1999. Analysis of polar diagrams comprising of hourly PPI images taken between 280800 UTC and 290200 UTC reveals interesting aspects of development of this Super Cyclone in terms of waxing and waning of eye size in relation to intensification process. The smallest radius of maximum reflectivity is in conformity with the colossal death toll observed close to the track of the super cyclone. Structural changes observed through radar images are in conformity with intensify changes as seen through other observing systems.

Comparing Usa and Mexico Response to Covid as Well as Incidence and Death Toll for the First 6 Months from February 2020 to August 2020 and the Pandemic on June 1st 2021

Both Mexico and United States share a border as well as Mexico being the country with the most American citizens living abroad and United States housing millions of individuals of Mexican descent, Covid 19 has impacted the world and both countries health system Mexico having to deal with the impact of a pandemic with a much lower budget and personnel compared to United States and aswell United States having to deal with a pandemic occurring in a country with more 330,000,000 persons of all type of ethnicities United states has being the country with the most cases confirmed of covid 19 in the World in this article we will compare the first 6 months of covid 19 in Mexico as well as in the United States and current data for nowadays of Covid 19.

KwaZulu-Natal instability weakens South African state

Significance The incarceration of former President Jacob Zuma sparked looting, destruction of critical infrastructure and denial of strategic communication routes. Inter-communal confrontations in Indian areas near Durban helped to boost the provincial death toll to 251, as against 76 in the more populous Gauteng Province. KZN’s demographic, historical, economic and strategic features make its stability particularly precarious. Impacts The ANC will likely lose vote share in KZN in upcoming municipal elections. KZN is the most likely location for any repeat of the July uprising. The proliferation of local militias during the July uprising will further erode state authority.

Early days of the pandemic—The association of economic and socio-political country characteristics with the development of the COVID-19 death toll

This article examines cross-national differences in growth of deaths by COVID-19 over time in the first phase of the pandemic, during the time period of 31st December 2019 to 2nd April 2020. We seek to understand and explain country level reaction in the initial period of the pandemic. We explore socio-economic and socio-political country characteristics as determinants of deaths per day and we examine whether country characteristics act as moderating factors for different growth patterns of deaths per day over time. The country characteristics include variables about economy, globalization, health care and demography. We examine data published by the European Center of Disease Prevention and Control (ECDC) in combination with World Bank data and a webscraping approach. Using a conditional growth model specified as a multilevel regression model with deaths by COVID-19 per day as the outcome variable, we show that economic variables are not significantly associated with decrease or increase of deaths by COVID-19. In contrast, variables about national health care mitigate the impact of the pandemic. Demography shows expected effects with an increase of growth of deaths in countries with a higher percentage of people older than 65 years. Globalization predicts the death toll as well: Social interaction between people is deadly on a short-term scale (in the form of tourism). Our results mirror frequent demands for global investment in national health systems.