Does Lockdown work?
Admin | 8 June 2020
How do you combat a pandemic? Different strategies exist regarding this. After declaring a global crisis, WHO set out to provide it’s member states with protocols to help fight the spread of SARS-CoV-2. Different nations around the world took these and made their own interpretations as to what the most effective strategies would be. One such strategy was to implement a ‘lockdown’. While the specificities of a lockdown may vary, essentially this means that contact between individuals would be kept to a minimum. People would need to work from home as much as possible. Services not deemed ‘essential’ would be suspended and social gatherings would be a no-go. How effective is this strategy however?
Researchers at the Bhabha Atomic Research Centre were interested in the answers to this question as well. B.K. Sahoo and B.K. Sapra set out to develop a data driven model that would use existing data on the spread of the virus to extrapolate and predict the spread in the weeks and months to come. By June 1st 2020, the Indian Ministry of Health and Family Welfare confirmed a total of 190 535 cases of Covid-19 patients, with 91 819 recoveries and 5 394 deaths nationwide, with a relatively low fatality rate of 3.09%. To prepare for further infections and deaths, the authorities needed to have some idea on how the virus was going to spread.
To make predictions on the rate of infection after lockdown, the researchers created the equation: λi(t) = λ0e –(t/τ), where λ0 was the initial infection rate, t was time, and τ was the characteristic time of decrease. Plugging in real time data, and using this equation, the researchers were able to predict the change in the rate of infection with up to 90% accuracy. But why is this important? Using this information, we are able to predict the course of future pandemics. We are therefore able to make calculated decisions on what our lockdown regulations should include, how effective they are, predict how long a lockdown should last, and perhaps most importantly, better prepare our healthcare systems in order to cope with seemingly overwhelming patients. While this model has only been used recently, and for a relatively short period of time, it might make a world of difference in future catastrophes in epidemiology. What we can take away from this, if nothing else, is that in times of uncertainty, we must look to science!
Admin | 17 May 2020
As innovation accelerates and technology steams forward, one can only imagine what the world will look like 20, 30 or 40 years from now. Technology has been making our lives easier for decades now, but what else does it have in store. One might wonder what the future of medicine looks like, and how the likes of A.I. might influence that. A survey was carried out with participants that included experts in radiology, information technology and industry leaders. They were asked how they thought artificial intelligence would change their field of expertise in the future, and what they thought some important principles would be in the use of A.I. The vast majority (93%) agreed that A.I. decision making would need to be constantly scrutinised, and checks for validity should be mandatory. They agreed that A.I. would be important in future development of radiology and I.T. however did not have confidence in the results they expected to be produced by A.I., with just 25% of respondents having confidence in A.I. produced results. The lack of confidence from industry leaders in A.I. could mean that we have a longer wait than previously thought before our medical needs are left in the hands of A.I. driven systems. In summary, it may be awhile before you get called from the doctor’s waiting room by ‘Robo Doc’.
Read more on this here
Admin | 18 April 2020
Ever seen a movie where scientists develop nanobots capable of carrying out tasks on a microscopic level within the human body. Fiction right? Well, maybe not. Students at the Massachusetts Institute of Technology have this year been looking at techniques for improving vaccines. The immune system, roughly comprising of 3 major parts i.e; the physical barrier (skin), innate immunity (from birth) and adaptive, or acquired immunity have many different parts within themselves. The layer in focus in this article is the adaptive immunity. Ever had the ‘flu’ vaccine? Here, attenuated (weakened) samples of the current endemic pathogens are given to the patient. The acquired immune system makes contact with the antigen and synthesises new forms of existing antibodies so that upon reoccuring infection, the body will be better suited to fighting the pathogen. Given it’s attenuated state, the virus is not actually able to cause harm. Getting the body’s immune system to elicit a certain response to the vaccine, termed humoral immunity, can be tricky business. That is why scientists have created ‘adjuvents’, which essentially help the acquired immune system to respond in a desirable way. Now however, MIT is looking for better ways to create these responses, by the use of nanoparticles accompanying vaccines. As humoral immunisation is affected by a number of factors like particle size and antigen density, the particles in question are being studied to allow for creating in such a way that their induction by, and retention in lymph nodes is improved. Make particles too large, and they do not effectively enter lymph nodes. Make them too small, and they are not retained properly. The use of nano technology is helping us to find the right balance for the synthesised particles. While the right formulation has not yet been found for all of the common pathogens, MIT has given us an idea of which factors weigh most heavily when developing new vaccines, and will surely help in further immunology related studies.
Read more on this here