Abstract
The Hepatitis C virus (HCV) infection is a global health problem. Since
its discovery in 1989 it is estimated that 3% of the global population are
infected (approximately 180 million people), with approximately 3-4 million
new infections each year. HCV is transmitted by means of blood-blood
contact. The introduction of screening blood products in developed countries,
however, means that the injecting drug user (IDU) community is now at the
greatest risk of contracting the disease through the sharing of unsterilised
injecting equipment. With approximately 75% of those contracting the
disease progressing to chronic infection and death, the disease is a substantial
cause of morbidity and mortality. With no vaccination available, the future
economic burden is likely to be substantial. It is for this reason that the
greatest impact on the spread of Hepatitis C will come from the intervention
measures employed by health organisations worldwide.
Unfortunately, the epidemiology of the disease and the interactions in
the IDU population is difficult to study and understand. Using mathematical
modelling techniques it is possible to better understand the intricate relationship
between the risk behaviour of the IDU population and the biological properties
of the disease at its various stages. Furthermore, the likely impact of the
intervention strategies, treatment options, and diagnostic tools on the prevalence
of the disease in the IDU population can also be modelled. Using these
techniques it has been possible to construct a simple mathematical model
to describe the spread of HCV. An expression of the basic reproductive
number, R0 , has been found and the stability of equilibrium solutions has
been investigated.
its discovery in 1989 it is estimated that 3% of the global population are
infected (approximately 180 million people), with approximately 3-4 million
new infections each year. HCV is transmitted by means of blood-blood
contact. The introduction of screening blood products in developed countries,
however, means that the injecting drug user (IDU) community is now at the
greatest risk of contracting the disease through the sharing of unsterilised
injecting equipment. With approximately 75% of those contracting the
disease progressing to chronic infection and death, the disease is a substantial
cause of morbidity and mortality. With no vaccination available, the future
economic burden is likely to be substantial. It is for this reason that the
greatest impact on the spread of Hepatitis C will come from the intervention
measures employed by health organisations worldwide.
Unfortunately, the epidemiology of the disease and the interactions in
the IDU population is difficult to study and understand. Using mathematical
modelling techniques it is possible to better understand the intricate relationship
between the risk behaviour of the IDU population and the biological properties
of the disease at its various stages. Furthermore, the likely impact of the
intervention strategies, treatment options, and diagnostic tools on the prevalence
of the disease in the IDU population can also be modelled. Using these
techniques it has been possible to construct a simple mathematical model
to describe the spread of HCV. An expression of the basic reproductive
number, R0 , has been found and the stability of equilibrium solutions has
been investigated.
| Original language | English |
|---|---|
| Publication status | Published - 2009 |
| Event | 35'th Young Statisticians Meeting - Glasgow, United Kingdom Duration: 7 Apr 2009 → 8 Apr 2009 |
Conference
| Conference | 35'th Young Statisticians Meeting |
|---|---|
| Country | United Kingdom |
| City | Glasgow |
| Period | 7/04/09 → 8/04/09 |
Keywords
- hepatitis C
- mathematical modelling
- injecting
- drug users
Fingerprint Dive into the research topics of 'Mathematical modelling of the spread of hepatitis C in injecting drug users'. Together they form a unique fingerprint.
Cite this
Corson, S., Greenhalgh, D., & Hutchinson, S. (2009). Mathematical modelling of the spread of hepatitis C in injecting drug users. Poster session presented at 35'th Young Statisticians Meeting, Glasgow, United Kingdom.