There are currently more trials being conducted on the effectiveness of surgical masks and N95 respirators [32] , which will allow us to refine the assumptions made in the model. However, it must be noted that in order for masks to be effective they must be: (1) available, (2) affordable, (3) worn properly, (4) replaced or sanitized daily, and (5) N95 respirators should be fit-tested. Only 10% of the population would have to wear masks in order to reduce the percentage of cases by 20%. Facemasks are inexpensive, relatively easy to implement, and would not cause a large economic burden to society. Masks are a powerful tool and can be used by countries with limited supplies of antiviral drugs and vaccines. In addition, economically feasible preventative global mitigations will benefit the world as a whole. We can conclude from our model that N95 respirators if worn properly are an effective intervention strategy in reducing the spread of the pandemic (H1N1) 2009. Figure 8 . Sensitivity to Who Wears Masks. In order to achieve the greatest possible reduction in the cumulative number of cases both infectious individuals and susceptible and exposed individuals should wear masks. If only infectious individuals wear masks the number of cases is not significantly reduced. doi:10.1371/journal.pone.0009018.g008 Correcting the Actual Reproduction Number: A Simple Method to Estimate R(0) from Early Epidemic Growth Data The basic reproduction number, R(0), a summary measure of the transmission potential of an infectious disease, is estimated from early epidemic growth rate, but a likelihood-based method for the estimation has yet to be developed. The present study corrects the concept of the actual reproduction number, offering a simple framework for estimating R(0) without assuming exponential growth of cases. The proposed method is applied to the HIV epidemic in European countries, yielding R(0) values ranging from 3.60 to 3.74, consistent with those based on the Euler-Lotka equation. The method also permits calculating the expected value of R(0) using a spreadsheet. The basic reproduction number, R 0 , of an infectious disease is the average number of secondary cases generated by a single primary case in a fully susceptible population [1] . R 0 is the most widely used epidemiological measurement of the transmission potential in a given population. Statistical estimation of R 0 has been performed for various infectious diseases [2, 3] , aiming towards understanding the dynamics of transmission and evolution, and designing effective public health OPEN ACCESS intervention strategies. In particular, R 0 has been used for determining the minimum coverage of immunization, because the threshold condition to prevent a major epidemic in a randomly-mixing population is given by 1-1/R 0 [4] . In addition, R 0 gives an estimate of the so-called final size, i.e., the proportion of the population that will experience infection by the end of an epidemic [5, 6] .