Development of a dose-response model for SARS coronavirus

Area of Science:

• Virology
• Epidemiology
• Mathematical Modeling

Background:

• Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) poses a significant public health threat.
• Understanding SARS-CoV infectivity is crucial for risk assessment and control strategies.
• Existing models may not fully capture the dose-response relationship for SARS-CoV.

Purpose of the Study:

• To develop a robust dose-response model for SARS-CoV using pooled animal infection data.
• To estimate the infectivity of SARS-CoV and compare it with other coronaviruses.
• To apply the developed model to analyze real-world SARS outbreak epidemiological data.

Main Methods:

• Fitting pooled SARS-CoV and murine hepatitis virus infection data in mice to beta-Poisson and exponential models.
• Utilizing the maximum likelihood method for model parameter estimation.
• Applying the best-fit model to analyze epidemiological data from the 2003 Hong Kong SARS outbreak.

Main Results:

• The exponential model effectively described the SARS-CoV dose-response relationship (k=4.1 x 10^2).
• Estimated doses for 10% and 50% illness response were 43 and 280 PFU, respectively.
• SARS-CoV infectivity was comparable to human common cold coronavirus HCoV-229E and other animal coronaviruses.

Conclusions:

• The developed exponential model is the primary dose-response model for SARS-CoV.
• The model provides valuable insights into SARS-CoV infectivity and potential for reemergence.
• Analysis of the Hong Kong outbreak data suggested a dose range of 16-160 PFU/person.