Modelling the prevalence of hepatitis C virus amongst blood donors in Libya: An investigation of providing a preventive strategy

Abstract

Aim: To determine hepatitis C virus (HCV) seroprevalence among the Libyan population using blood donors and applying the autoregressive integrated moving average (ARIMA) model to predict future trends and formulate plans to minimize the burden of HCV infection.

Methods: HCV positive cases were collected from 1008214 healthy blood donors over a 6-year period from 2008 to 2013. Data were used to construct the ARIMA model to forecast HCV seroprevalence among blood donors. The validity of the model was assessed using the mean absolute percentage error between the observed and fitted seroprevalence. The fitted ARIMA model was used to forecast the incidence of HCV beyond the observed period for the year 2014 and further to 2055.

Results: The overall prevalence of HCV among blood donors was 1.8%, varying over the study period from 1.7% to 2.5%, though no significant variation was found within each calendar year. The ARIMA model showed a non-significant auto-correlation of the residuals, and the prevalence was steady within the last 3 years as expressed by the goodness-of-fit test. The forecast incidence showed an increase in HCV seropositivity in 2014, ranging from 500 to 700 per 10000 population, with an overall prevalence of 2.3%-2.7%. This may be extended to 2055 with minimal periodical variation within each 6-year period.

Conclusion: The applied model was found to be valuable in evaluating the seroprevalence of HCV among blood donors, and highlighted the growing burden of such infection on the Libyan health care system. The model may help in formulating national policies to prevent increases in HCV infection and plan future strategies that target the consequences of the infection.

Keywords: Autoregressive integrated moving average model; Blood donors; Hepatitis C virus; Libya.

Figure 1

Correlogram and partial correlogram for a case structure control used for autoregressive integrated moving average model. A: ACF; B: Partial ACF. ACF: Autocorrelation function.

Figure 2

Residual plots for the final autoregressive integrated moving average (2, 1, 7) model of hepatitis C virus seroprevalence among volunteer blood donors in Libya, 2008-2013. A: ACF; B: Partial ACF. Lines indicate 95%CI. ACF: Autocorrelation function.

Figure 3

Number of observed and forecast hepatitis C virus seropositive volunteers among blood donors in Libya, 2008-2013. Date: Period of observation (months: 2008-2013); Number: Estimated number of HCV seropositive/month. UCL: Upper confidence limit; LCL: Lower confidence limit; HCV: Hepatitis C virus.

Figure 4

Modeled prevalence (not exclusive¹) of hepatitis C virus infection by 6-year period, Libya, 2008-2055. ¹Estimates assume stable risk populations and HCV infection risks and do not adjust for treatment. HCV: Hepatitis C virus.