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      Modeling and public health emergency responses: Lessons from SARS

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          Abstract

          Modelers published thoughtful articles after the 2003 SARS crisis, but had limited if any real-time impact on the global response and may even have inadvertently contributed to a lingering misunderstanding of the means by which the epidemic was controlled. The impact of any intervention depends on its efficiency as well 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 product of efficiency and efficacy was varied over the entire unit interval. Another mistake was repeatedly fitting otherwise appropriate gamma distributions to times to event regardless of whether they were stationary or not, particularly onset-isolation intervals whose progressive reduction evidently contributed to SARS control. By virtue of their unknown biology, newly-emerging diseases are more challenging than familiar human scourges. Influenza, for example, recurs annually and has been modeled more thoroughly than any other infectious disease. Moreover, models were integrated into preparedness exercises, during which working relationships were established that bore fruit during the 2009 A/H1N1 pandemic. To provide the most accurate and timely advice possible, especially about the possible impact of measures designed to control diseases caused by novel human pathogens, we must appreciate the value and difficulty of policy-oriented modeling. Effective communication of insights gleaned from modeling SARS will help to ensure that policymakers involve modelers in future outbreaks of newly-emerging infectious diseases. Accordingly, we illustrate the increasingly timely care-seeking by which, together with increasingly accurate diagnoses and effective isolation, SARS was controlled via heuristic arguments and descriptive analyses of familiar observations.

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          Most cited references18

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          Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong

          Summary Background Health authorities worldwide, especially in the Asia Pacific region, are seeking effective public-health interventions in the continuing epidemic of severe acute respiratory syndrome (SARS). We assessed the epidemiology of SARS in Hong Kong. Methods We included 1425 cases reported up to April 28, 2003. An integrated database was constructed from several sources containing information on epidemiological, demographic, and clinical variables. We estimated the key epidemiological distributions: infection to onset, onset to admission, admission to death, and admission to discharge. We measured associations between the estimated case fatality rate and patients’age and the time from onset to admission. Findings After the initial phase of exponential growth, the rate of confirmed cases fell to less than 20 per day by April 28. Public-health interventions included encouragement to report to hospital rapidly after the onset of clinical symptoms, contact tracing for confirmed and suspected cases, and quarantining, monitoring, and restricting the travel of contacts. The mean incubation period of the disease is estimated to be 6.4 days (95% Cl 5.2–7.7). The mean time from onset of clinical symptoms to admission to hospital varied between 3 and 5 days, with longer times earlier in the epidemic. The estimated case fatality rate was 13.2% (9.8–16.8) for patients younger than 60 years and 43.3% (35.2–52.4) for patients aged 60 years or older assuming a parametric γ distribution. A non-parametric method yielded estimates of 6.8% (4.0–9.6) and 55.0% (45.3–64.7), respectively. Case clusters have played an important part in the course of the epidemic. Interpretation Patients’age was strongly associated with outcome. The time between onset of symptoms and admission to hospital did not alter outcome, but shorter intervals will be important to the wider population by restricting the infectious period before patients are placed in quarantine. Published online May 7, 2003 http://image.thelancet.com/extras/03art4453web.pdf
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            Mitigation strategies for pandemic influenza in the United States.

            Recent human deaths due to infection by highly pathogenic (H5N1) avian influenza A virus have raised the specter of a devastating pandemic like that of 1917-1918, should this avian virus evolve to become readily transmissible among humans. We introduce and use a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million individuals for R(0) (the basic reproductive number) from 1.6 to 2.4. We model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) have on the timing and magnitude of this spread. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For R(0) < 1.9, our model suggests that the rapid production and distribution of vaccines, even if poorly matched to circulating strains, could significantly slow disease spread and limit the number ill to <10% of the population, particularly if children are preferentially vaccinated. Alternatively, the aggressive deployment of several million courses of influenza antiviral agents in a targeted prophylaxis strategy may contain a nascent outbreak with low R(0), provided adequate contact tracing and distribution capacities exist. For higher R(0), we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve similar limits on illness rates.
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              Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures.

              Severe acute respiratory syndrome (SARS) has been the first severe contagious disease to emerge in the 21st century. The available epidemic curves for SARS show marked differences between the affected regions with respect to the total number of cases and epidemic duration, even for those regions in which outbreaks started almost simultaneously and similar control measures were implemented at the same time. The authors developed a likelihood-based estimation procedure that infers the temporal pattern of effective reproduction numbers from an observed epidemic curve. Precise estimates for the effective reproduction numbers were obtained by applying this estimation procedure to available data for SARS outbreaks that occurred in Hong Kong, Vietnam, Singapore, and Canada in 2003. The effective reproduction numbers revealed that epidemics in the various affected regions were characterized by markedly similar disease transmission potentials and similar levels of effectiveness of control measures. In controlling SARS outbreaks, timely alerts have been essential: Delaying the institution of control measures by 1 week would have nearly tripled the epidemic size and would have increased the expected epidemic duration by 4 weeks.
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                Author and article information

                Contributors
                Journal
                Epidemics
                Epidemics
                Epidemics
                Elsevier
                1755-4365
                1878-0067
                28 January 2011
                March 2011
                28 January 2011
                : 3
                : 1
                : 32-37
                Affiliations
                [a ]Centers for Disease Control and Prevention, Atlanta, GA, USA
                [b ]Weill Cornell Medical College, New York, NY, USA
                [c ]National Institutes of Health, Bethesda, MD, USA
                Author notes
                [* ]Corresponding author at: 1600 Clifton Road, NE, Mail Stop A-34, Atlanta, GA 30333, USA. Tel.: +1 404 639 8780; fax: +1 404 639 1307. jglasser@ 123456cdc.gov
                Article
                S1755-4365(11)00002-8
                10.1016/j.epidem.2011.01.001
                7105002
                21420657
                207b300e-76b0-438a-bc36-b0e88969b456

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 8 March 2010
                : 19 January 2011
                : 20 January 2011
                Categories
                Article

                Public health
                decision support modeling,theoretical modeling,emerging infectious diseases,emergency preparedness

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