Question

Question:

An outbreak of betacoronavirus severe acute respiratory syndrome (SARS)-CoV-2 began in Wuhan, China in December 2019. COVID-19, the disease associated with SARS-CoV-2 infection, rapidly spread to produce a global pandemic. Since then many scientists around world try to understand the mechanism of the virus. One of the very important questions that the scientists are asking is that why there is a difference with respect to severity of the disease between infected individuals. We know some factors such as people with advanced age or underlying health conditions such as heart disease and diabetes are more likely to develop severe symptoms. But those do not explain the whole story, because there are plenty of young and healthy individuals with severe symptoms or old individuals with underlying health conditions with mild symptoms. Why might that be? Could genetics play a role? Because we know from past experiences that genetics is associated with susceptibility to infectious diseases such as particular HBB variants make people less susceptible to malaria, or particular CCR5 variants can protect people from HIV infection, or particular FUT2 variants prevent people to be infected by norovirus.

So, a) Please discuss the molecular mechanisms of the novel coronavirus and decide which human genes are possible candidates of most likely to influence severity of the disease.

b) Please discuss if the geographical location could affect the severity of the disease in terms of genetic variation and evolutionary migration patterns of humans.

Specific Instructions:  Provide at least 3 references in an appropriate format.  Use only scholarly research papers for referencing (magazines, blogs, and websites are not allowed).  Plagiarism or quotations are not allowed.  Word count scale: Minimum 200 words.

Please anyone?

Answer 1

A.

Molecular mechanism of infection in cells: The cellular entry of coronaviruses depends on the binding of proteins with viral spicules (S) to the cellular receptors and the priming of the S protein by the host cell proteases. The SARS-CoV-2 virus has been shown to use the ACE2 receptor from the level of pulmonary alveoli, for entry and an enzyme, TMPRSS2 serine protein for initiating protein S. A TMPRSS2 inhibitor approved for clinical use blocked entry and could be a treatment option. Some results revealed an important communication between SARS-CoV-2 and SARS-CoV. About 80% of COVID-19 infections are mild.

Patients with SARS-CoV-2 in convalescents exhibit a neutralizing antibody response that can be detected even at 24 months after infection and is largely directed against protein S. In addition, experimental SARS vaccines, including recombinant S protein and inactivated virus induce responses to neutralizing antibodies. Although confirmation of the infectious virus is recent, our results indicate that neutralizing high antibody responses against SARS-S may provide some protection against SARS-CoV-2 infection.

There are two types of rapid tests. One is the serological, immunological test (a drop of blood is taken from the finger, through the sting) and offers the results in 20-30 minutes. The antibody test produces positive results, in the case of infection, SARS-CoV-2, only after a few days if the antibodies have formed in the blood. These tests are not suitable for the detection of active infections in the early phase of the disease.

The second type of rapid test is the one obtained from the nasopharyngeal exudate, gives results in 20-30 minutes and aims to identify the viral antigen, being similar to the rapid flu tests. These rapid tests are more effective than serological tests because they are useful for both early diagnosis and early diagnosis of new coronavirus infection. No testing method is perfect.

Sequential Gene Method (NGS) Using SmartXGeneNGS Analyzer

SmartXGene intends to introduce automated sequencing analysis software into the future and impact of copy variants on a single 16S rRNA genome. In order to minimize the proportion of negative results, it is recommended to further test the samples collected from the respiratory apparatus in very suspicious cases and to check the sample quality.

Reverse transcription-polymerase chain reaction assay (RT-PCR)

RT-PCR assays identify the genetic fingerprint of the virus (viral genome), that is, RNA. There are several PCR platforms, the sample can be taken from respiratory secretions, nasopharyngeal exudate or bronchial aspirate.

The waiting time varies, depending on the platform used, from 45 minutes to 6 hours.

B.

Introduction

In December 2019, a new virus (initially called ‘Novel Coronavirus 2019-nCoV’ and later renamed to SARS-CoV-2) causing severe acute respiratory syndrome (coronavirus disease COVID-19) emerged in Wuhan, Hubei Province, China , and rapidly spread to other parts of China and other countries around the world, despite China’s massive efforts to contain the disease within Hubei.

Compared to the 2002/2003 SARS-CoV and the 2012–2014 MERS-CoV (Middle East Respiratory Syndrome-related coronavirus), the COVID-19 coronavirus spread strikingly fast. While MERS took about two and a half years to infect 1000 people, and SARS took roughly 4 months, the novel SARS-CoV-2 reached that figure in just 48 days. On 30 January 2020, the World Health Organization (WHO) declared that the new SARS-CoV-2 coronavirus outbreak constitutes a Public Health Emergency of International Concern (PHEIC) .

As with the original SARS-CoV epidemic of 2002/2003 and with seasonal influenza geographic information systems (GIS) and methods, including, among other application possibilities, online real- or near-real-time mapping of disease cases and of social media reactions to disease spread, predictive risk mapping using population travel data, and tracing and mapping super-spreader trajectories and contacts across space and time (see, as an example, the first diagram in , are proving indispensable for our timely understanding of the new disease source, dynamics and epidemiology, and in shaping our effective response to it.

Indeed, health professionals have long considered conventional mapping, and more recently geographic information systems (GIS), as critical tools in tracking and combating contagion. The earliest map visualisation of the relationship between place and health was in 1694 on plague containment in Italy . The value of maps as a communication tool blossomed over the next 225 years in the service of understanding and tracking infectious diseases, such as yellow fever, cholera and the 1918 influenza pandemic. From the 1960s, when computerised geographic information systems were born, the possibilities for analysing, visualising and detecting patterns of disease dramatically increased again. A 2014 review of the health GIS literature found that 248 out of 865 included papers (28.7%) focused on infectious disease mapping .

Since then we have seen a revolution in applied health geography through Web-based tools , Now, as we deploy these tools to protect human lives, we can ingest big data from their sources and display results in interactive and near-real-time dashboards. These online dashboards have become a pivotal source of information during the COVID-19 outbreak.

The World Health Organization dashboard

The WHO directs and coordinates international health, combating communicable diseases through surveillance, preparedness and response, and applying GIS technology to this work. On 26 January 2020, the WHO unveiled its ArcGIS Operations Dashboard for COVID-19, which also maps and lists coronavirus cases and total number of deaths by country and Chinese province, with informational panels about the map and its data resources.

Prior to 18 February 2020, the WHO and JHU CSSE dashboards had some interesting differences. Each had a vastly different total case count as can be seen in (both taken on 16 February 2020). The WHO dashboard reflected laboratory-confirmed cases, whereas JHU CSSE included cases diagnosed using a symptom array plus chest imaging (accounting for some 18,000 additional reports). However, as of 19 February 2020, both dashboards are in sync, displaying similar total case counts.

HealthMap: analysing and mapping online informal sources

Founded in 2006, HealthMap is run by a team of researchers, epidemiologists and software developers at Boston Children’s Hospital, USA, and uses online media sources for real-time surveillance of emerging public health threats. HealthMap collates outbreak data from a range of sources, including news media (e.g., via Google News), social media, validated official alerts (e.g., from the WHO) and expert-curated accounts . HealthMap’s interactive map for SARS-CoV-2 available at offers near-real-time geolocated updates from these sources to better understand the progression of the pandemic .

China’s coronavirus ‘close contact detector’ geosocial app and public service platform

While government travel restrictions initiate social distancing, it is now possible for individuals to further the cause by using a dedicated app that provides a detailed spatial scale to support informed personal decisions about self-quarantine and seeking medical treatment. Co-launched by China’s National Health Commission and China Electronics Technology Group Corporation, the ‘close contact detector’ app/platform uses big data from public authorities about the movement of people (public transport data covering flights and trains [booking a train seat in China requires the input of ID information]), as well as disease case records, to check if the user has had any close contact with a person confirmed or suspected to have been infected in the recent past .The platform can inform the user based on her/his location and recent movements whether s/he has within the last 2 weeks (the assumed incubation period of COVID-19) worked together, shared a classroom, lived in the same building, or travelled by train (all passengers and crew members in the same carriage) or plane (cabin staff and passengers within three rows of an infected person) with a person confirmed or suspected to have the virus. ‘Close contact detector’ can be accessed via three of the most popular mobile social and payment apps in China, namely Alipay, WeChat and QQ.