monthly archives: April 2020

Professionals in physical contact with other persons are at the greatest risk of contracting the virus. Health care workers are in close proximity to their patients. On a daily basis, they encounter symptomatic patients who seek medical attention. Even the asymptomatic patients could potentially carry the virus. Therefore, they are at a much higher risk compared to other professions. As much as this information sounds obvious, it is crucial to always keep it in mind considering the challenges they are facing and mainly the shortage in appropriate supply and PPE to keep them safe.

Gamio, Lazaro. The workers who face the greatest coronavirus risk, The New-York Times, March 15, 2020. 

Original article: https://www.nytimes.com/interactive/2020/03/15/business/economy/coronavirus-worker-risk.html

Even though the number of cases is still increasing in Italy as seen on the linear graph, the data plotted on a logarithmic scale provides a better picture of the spread of the virus showing that the infection rate is no longer exponential in Italy whereas it is increasing in the United States. Therefore, the logarithmic scale highlights that the crisis measures that were implemented by the Italian government are showing some positive results, but that there is no sign of the spread slowing down in the United States.

“Those skyrocketing curves tell an alarming story. But logarithmic graphs can help reveal when the pandemic begins to slow.”

– Kenneth Chang 

Chang K., A Different Way to Chart the Spread of Coronavirus. The New York Times, March 20 2020 

Original article: https://www.nytimes.com/2020/03/20/health/coronavirus-data-logarithm-chart.html

Mathematical modelling is broadly used to justify restrictive measures implemented to prevent infection transmission and ultimately death. Some studies recently published show insufficient data, forgetting to include the sudden rise in the number of infections expected after the lifting of measures.

“Once transmission rates return to normal, the epidemic will proceed largely as it would have without mitigations, unless a significant fraction of the population is immune (either because they have recovered from the infection or because an effective vaccine has been developed), or the infectious agent has been completely eliminated, without risk of reintroduction.”

– Wesley Pegden, associate professor, Department of mathematical Sciences, Carnegie Mellon University

Maria Chikina, Wesley Pegden, A call to honesty in pandemic modeling, Medium Magazine, March 29, 2020

Original article : https://medium.com/@wpegden/a-call-to-honesty-in-pandemic-modeling-5c156686a64b

Different strategies are employed worldwide to face the reality of hospital and intensive care unit (ICU) restricted capacity. China, for instance, did not wait long to implement restrictive measures, like city lockdowns and school closures. On the other hand, England first believed that being too restrictive too early would lead to a large second epidemic once measures were lifted. They finally applied restrictive measures after a sudden rise of infected cases.

Behind these different defensible measures lie mathematical computer simulation models applied to the epidemiology of infectious disease. These mathematical models were used to model the Ebola and Zika viruses in the past.

There is still debate among scientists about which mathematical model most accurately represents characteristics of SARS-CoV-2 and the affected population, and about the scope of such models within government authority restriction plans.

Martin Enserink, Kai Kupferschmidt, Mathematics of life and death: How disease models shape national shutdowns and other pandemic policies, Science magazine, March 25, 2020

Original article : https://www.sciencemag.org/news/2020/03/mathematics-life-and-death-how-disease-models-shape-national-shutdowns-and-other?

Scientists from academic, independent and government labs around the world have been able to compile data regarding the genomic sequencing data of SARS-CoV-2 virus. Seen as the backbone of the virus, the genome of SARS-CoV-2 is made of approximately 30 000 base pairs. Virus strain is defined as a specific base pair sequence. A potential vaccine development in the near future requires fully understanding that sequence. Note that the mutagenic potential of a virus is a limiting factor in the development of a vaccine. For now, the virus does not seem to evolve rapidly.

“The virus mutates so slowly that the virus strains are fundamentally very similar to each other.”

– Charles Chiu, a professor of medicine and infectious disease at the University of California, San Francisco School of Medicine.

Elizabeth Weine, 8 strains of the coronavirus are circling the globe. Here’s what clues they’re giving scientists, USA today, March 27, 2020

Original article : https://www.usatoday.com/story/news/nation/2020/03/27/scientists-track-coronavirus-strains-mutation/5080571002/