Different Epidemic Curves for Severe Acute Respiratory Syndrome Reveal Similar Impacts of Control Measures

By Jacco Wallinga, P. Teunis. 2004

1,252 citations recorded by the source corpus.

Abstract 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.

Subfields: Epidemiology, Health, Modeling and Simulation

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Citations in the corpus

Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak (2020, neutral): “We reported that the mean R 0 of 2019-nCoV is likely to be from 2.24 (8-fold) to 3.58 (2-fold), and it is largely in the range of those of SARS, i.e., 2-5 [11, 18, 20], and MERS, i.e., 2.7-3.9 [12].”
Management of disease in wild mammals (2009, background): “If the form of the infectiousness function is known or can be reasonably assumed, there have been recent advances in using case notifications to estimate the effective reproduction number of the course of a completely observed (Wallinga and Teunis 2004) or truncated (Cauchemez et al.”
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Influence Maximization in Continuous Time Diffusion Networks (2012, methodology): “…effort in uncovering, understanding, and controlling diffusion and propagation processes in a broad range of domains: information propagation (Leskovec et al., 2007), social networks (Kempe et al., 2003), viral marketing (Richardson & Domingos, 2002), and epidemiology (Wallinga & Teunis, 2004).”
Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models (2008, background): “For example, the 2003 SARS epidemic appears to have been quenched through contact reduction (Wallinga and Teunis 2004, Riley et al. 2003, Lipsitch et al. 2003).”
Coronavirus Infections in Children Including COVID-19 (2020, background): “53 The overall reproductive number (R0) for SARS-CoV was estimated to be 0.3-2.9 37, 39, 40, 42, 43, 47 and for MERS-CoV to be 0.5-3.5 (Table 1) .”
Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases (2008, background): “Preparing for outbreaks of directly transmitted pathogens such as pandemic influenza [1] [2] [3] and SARS [4] [5] [6] [7] [8] [9] , and controlling endemic diseases such as tuberculosis and meningococcal diseases, are major public health priorities.”
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