Forecasting versus projection models in epidemiology: The case of the SARS epidemics

In this work we propose a simple mathematical model for the analysis of the impact of control measures against an emerging infection, namely, the severe acute respiratory syndrome (SARS). The model provides a testable hypothesis by considering a dynamical equation for the contact parameter, which drops exponentially with time, simulating control measures. We discuss the role of modelling in public health and we analyse the distinction between forecasting and projection models as assessing tools for the estimation of the impact of intervention strategies. The model is applied to the communities of Hong Kong and Toronto (Canada) and it mimics those epidemics with fairly good accuracy. The estimated values for the basic reproduction number, R(0), were 1.2 for Hong Kong and 1.32 for Toronto (Canada). The model projects that, in the absence of control, the final number of cases would be 320,000 in Hong Kong and 36,900 in Toronto (Canada). In contrast, with control measures, which reduce the contact rate to about 25% of its initial value, the expected final number of cases is reduced to 1778 in Hong Kong and 226 in Toronto (Canada). Although SARS can be a devastating infection, early recognition, prompt isolation, and appropriate precaution measures, can be very effective to limit its spread.