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Famous Chris von Csefalvay Quotes

“Any subject whose history ranges from pump handles on London's Broad Street, tide tables, naval gunfire and models of social segregation is bound to have rich parentage. It took 'a village' to beget computational epidemiology: as a true multi-disciplinary subject, it evolved at the crossroads of mathematics, computation, statistics and medicine, with some contributions from systems biology, virology, microbiology, game theory, geography and perhaps even the social sciences.”

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Book:Computational Modeling of Infectious Disease: With Applications in Python
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“Few diseases have had an impact on human evolution, culture and society on par with malaria. It is one of the oldest documented infectious diseases. Indeed, it has been hypothesised that the protective effect bestowed by a heterozygous sickle cell allele explains its survival to the modern day. As such, malaria has left its footprint on human evolution in a profound way few other diseases have. Yet its true origins were the matter of considerable controversy. The clue is in the name – the prevailing theory until Ross's discovery was that malaria resulted from 'mala aria', that is, 'bad air'. It took the advent of modern evidence-based medical science to challenge this 'miasma theory'. Ross's elucidation of the role of mosquitoes in the lifecycle of malaria has opened up a new subject for epidemiological consideration: the vector-borne disease.”

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Book:Computational Modeling of Infectious Disease: With Applications in Python
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“higher antimicrobial loads will result in a lower total pathogenic load but also a lower involvement of the immune system and therefore less immunity in the long run (as indeed has been empirically demonstrated in a number of experiments summarised in a sweeping review by Benoun (2016)). Thus, while rapid and aggressive antimicrobial treatment is sometimes appropriate, the long-term absence of ensuing CD4+ immunity is its cost.”

Immune SystemAntibioticsEpidemiologyImmunologyAntibiotic Resistance
Book:Computational Modeling of Infectious Disease: With Applications in Python
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