Investigative Mathematical Modeling of Hospital Transmission of Hepatitis C (IMMHoTHep)

Hepatitis C virus (HCV) is a blood-borne virus and its major route of transmission include blood transfusion, medical injection and procedure, and injecting drug use. In Egypt, the origin of the HCV epidemic has been attributed to a mass treatment of schistosomiasis between 1960 and 1984, when intravenous injections with antimony salts were given to 3-5 million people older than 6 years of age. Insufficient sterilization of needles and syringes was considered to be responsible for HCV transmission at that time. In order to control the spread of HCV in Egypt, the Egyptian Ministry of Health and Population established the National Committee for the Control of Viral Hepatitis. By 2008, this committee developed a National Control Strategy for Viral Hepatitis which has recommended prevention and education campaigns targeting general population and also healthcare workers (HCW). In their occupational environment, HCWs are frequently exposed to multiple blood-borne pathogens, including HCV. Several risk factors for HCV acquisition among patients and HCWs within a hospital ward have been identified, including a high prevalence of HCV infection in the ward, understaffing, workplace characteristic, and human factors such as inexperience or unfamiliar with equipment. However, to the investigators' knowledge, the overall risk of HCV acquisition associated with hospital stay has never been evaluated in Egypt. Also, control measures to reduce the risk of HCV transmission in hospital settings, based on a global assessment of healthcare provider logistics and performance, have never been proposed in Egypt.

In this project, the investigators assume that HCV will be transmitted to both hospital staff and patients. Given the slow dynamics of the HCV epidemic, the investigators further hypothesize that, in the short term, the prevalence of HCV viremia among patients will be constant. Therefore, the investigators are led to conclude that HCV transmission risk may be inferred from a detailed description of individual trajectories of patients or staff within the hospital.