New knol on the estimate of H1N1 cases in Mexico at the early stage of the pandemic

We recently published a knol in PLoS Currents Influenza about the estimate of H1N1 cases in Mexico at the early stage of the pandemic conducted with GLEaM:

Estimate of Novel Influenza A/H1N1 cases in Mexico at the early stage of the pandemic with a spatially structured epidemic model
V Colizza, A Vespignani, N Perra, C Poletto, B Gonçalves, H Hu, D Balcan, D Paolotti, W Van den Broeck, M Tizzoni, P Bajardi, JJ Ramasco. PLoS Currents: Influenza. 2009 Nov 11:RRN1129.

Determining the number of cases in an influenza epidemic represents a great challenge. Reliable figures for the actual number of cases are key to properly assess several parameters, such as mortality, morbidity or hospitalization rates. This is particularly relevant during the early phase of an outbreak, in order to better inform decision making process. Surveillance of cases inevitably suffers of several biases overall leading to an underascertainment of influenza cases. For example, many cases showing mild symptoms might not seek for medical attention, and would therefore not be included in the counting of cases. Moreover, the monitoring of cases is expected to change with time. After the initial alert at the beginning of an outbreak, an enhanced surveillance system is expected to have a large monitoring capacity. However, this situation changes with time, due to the large increase in the number of cases and the majority of resources being dedicated to the severe patients. This leads to an ascertainment mainly focused on the most severe cases, with the number of confirmed cases being a gross underestimation of the actual number of people infected by influenza. A significant example is provided by the time evolution of the monitored cases in Mexico during the first months of the epidemic: two studies [1] [2] have assessed the size of the epidemic in the country and both of them found a significant underascertainment of the confirmed cases as reported by the mexican authorities. [3]

In order to address this point we use GLEaM to simulate the epidemic spreading and compute the number of cases in Mexico at the end of April and the beginning of May. We calibrate our model with a maximum likelihood estimate of the infection parameters, fitting the empirical arrival dates of the first infected in the countries seeded from Mexico (a detailed description of the estimate procedure is reported here). This allows us to provide an ab-initio calculation of the number of cases in Mexico independently by the estimation precedure. In the Table below the number of infectious individuals obtained in our simulations is reported, comparing it with the same number obtained in Refs [1][2] and with the confirmed cases reported by mexican authorities.

Number of symptomatic cases in Mexico (Apr. the 30th)
Simulation Results [121,000 - 1,394,000]
Lower bound range of Ref. [2]113,000-375,000
Estimate of Ref. [1]*2,000 – 280,000
Mexican official report [3] (confirmed cases)3,350
Predictions of GLEaM for the size of the epidemic in Mexico on April 30 in thousands of cases and comparison with other approaches and with empirical data. The simulations are obtained with our infectious parameter estimates (a detailed description of the estimate procedure is reported here) and show the 95% reference range over 2,000 stochastic realizations. The results are compared with the lower bound estimate range in [2], the estimate provided in Ref. [1] and the number of confirmed cases given by official reports [3]. *The interval provided for Ref.[1] is obtained by merging the results reported in the paper under different assumptions and including the 95% CI.

Despite the different approximations used here and in Refs. [1][2], the three approaches are providing support to the possibility of a reporting ratio of infected cases in Mexico as low as 1 in 100. This finding is important when evaluating the massive amount of data which are now being collected in a large number of countries around the world. We can easily imagine that the reporting rate as well as the estimate of the cumulative attack rate in most of the countries could be easily underestimated in similar cases.

[1] Fraser C, Donnelly CA, Cauchemez S, Hanage WP, Van Kerkhove MD, et al. Pandemic Potential of a Strain of Influenza A (H1N1): Early Findings. Science 2009, 324: 1557-1561.
[2] Lipsitch M, La jous M, O’Hagan JJ, Cohen T, Miller JC, et al. Use of Cumulative Incidence of Novel Influenza A/H1N1 in Foreign Travelers to Estimate Lower Bounds on Cumulative Incidence in Mexico. PLoS ONE , 2009 4: e6895.
[3] Secretaria de Salud, Mexico. Situation actual de la epidemia, Oct 12, 2009.
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