My publisher e-mailed me this morning to tell me that my book, Computational Modeling of Infectious Disease, is now officially “published”. Camera-ready data is off to the printers, eBook versions are now available on the Elsevier website as well as on Amazon, hardcopy orders are starting to get fulfilled in the next weeks, libraries are getting their copies, the birds are singing and life is good.
It’s been a long journey to get to this point. However, it’s been an immensely worthwhile experience, and it’s been a privilege to be able to create something that will, hopefully, help us face a world that is only more likely to be imperiled by pandemics. As I write this, a Marburg haemorrhagic fever epidemic is emerging in Equatorial Guinea, there’s an outbreak of chikungunya in Paraguay and of course the silent epidemic of nosocomial multi-drug resistant pathogens keeps quietly sweltering. Many of us are “done” with COVID-19, but I doubt that COVID-19 is altogether done with us.
A critical read… Every public health official, every epidemiologist, every member of the public interested in pandemics, every person working on pandemic preparedness should read this book.Dr Deborah Birx, MD, former White House Coronavirus Response Coordinator
As humans, we have the unique privilege that we can think, organise and fight back. The techniques described in my book offer an additional string in our bow against pathogenic threats, whether natural or man-made. This is a book for everyone – to paraphrase an old proverb from my homeland, you may not be interested in epidemics, but epidemics are most definitely interested in you. As such, while the tone is that of a professional title, it is my hope that I have written a suitably accessible book for multiple audiences, including those who do not create but consume insights from computational epidemiology. This includes not only decision-makers, crisis planners and governmental authorities, but also the (wo)man on the Clapham omnibus. For his or her life is just as determined by calculations of risk, exposure and likelihood of harm as the welfare of a nation, and he or she just as much deserves to know how the figures that condemn them to another week of lockdown or a “circuit breaker” restriction or even individual post-exposure isolation come to be. For all its beauty, computational epidemiology is not magic. Everyone should have a chance to peek behind the curtain and understand what’s going on.
Great Falls, VA
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