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MODELING AND PUBLIC HEALTH EMERGENCY RESPONSES: LESSONS FROM SARS

Abstract

Modelers published thoughtful articles after the 2003 SARS crisis but had limited if any real-time impact on the worldwide response and should even have inadvertently contributed to a lingering misunderstanding of how the epidemic was controlled. The impact of any intervention depends on its efficiency likewise as efficacy, and efficient isolation of infected individuals before they become symptomatic is difficult to imagine. Nonetheless, in exploring the possible impact of quarantine, the merchandise of efficiency and efficacy was varied over the whole unit interval. Another mistake was repeatedly fitting otherwise appropriate gamma distributions to times to event irrespective of whether or not they were stationary or not, particularly onset-isolation intervals whose progressive reduction evidently contributed to SARS control. Under their unknown biology, newly emerging diseases are more difficult than familiar human scourges. Influenza, as an example, recurs annually and has been modeled more thoroughly than the other communicable disease. Moreover, models were integrated into preparedness exercises, during which working relationships were established that bore fruit during the 2009 A/H1N1 pandemic. to supply the foremost accurate and timely advice possible, especially about the possible impact of measures designed to regulate diseases caused by novel human pathogens, we must appreciate the worth and difficulty of policy-oriented modeling. Effective communication of insights gleaned from modeling SARS will help to make sure that policymakers involve modelers in future outbreaks of newly-emerging infectious diseases. Accordingly, we illustrate the increasingly timely care-seeking by which, along with increasingly accurate diagnoses and effective isolation, SARS was controlled via heuristic arguments and descriptive analyses of familiar observations

Keywords
  • : Decision support modeling; theoretical modeling; emerging; infectious; disease emergency ;preparedness
References

Authors

  • Pro. Kermani P.D
    Affiliation:- a:1:{s:5:"en_US";s:81:"faculty In Department Of Geography In Adekunle Ajasin University at Ondo, Nigeria";}
  • Dr. Kalau P
    Affiliation:- faculty In Department Of Geography In Adekunle Ajas in University at Ondo, Nigeria..
  • Pro. Korngini O.M
    Affiliation:- faculty In Department Of Geography In Adekunle Ajasin University at Ondo, Nigeria..

How to Cite

P.D, P. K., P, D. K. ., & O.M, P. K. . (2021). MODELING AND PUBLIC HEALTH EMERGENCY RESPONSES: LESSONS FROM SARS. International Journal of Multidisciplinary Research and Studies, 4(04), 01–07. Retrieved from https://ijmras.com/index.php/ijmras/article/view/40

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