Mathematical Modelling of an epidemic

• • • Watch this space for more on epidemic modelling in the future.
Meanwhile, a few interesting articles • • •

World Switzerland Scotland Pakistan HCC risk

Modelling of global epidemic as guide in health planning

‘Scaling up prevention and treatment towards the elimination of hepatitis C: a global mathematical model’, by Heffernan et al, 2019 (full text) features a dynamic transmission model for 190 countries. They estimated the impact of six prevention and treatment interventions, including different sequences, using a Baysian framework. According to this model:

“by 2030, interventions that reduce risk of transmission in the non-PWID population by 80% and increase coverage of harm reduction services to 40% of PWID could avert 14·1 million (95% credible interval 13·0–15·2) new infections. … A comprehensive package of prevention, screening, and treatment interventions could avert 15·1 million (13·8–16·1) new infections and 1·5 million (1·4–1·6) cirrhosis and liver cancer deaths, corresponding to an 81% (78–82) reduction in incidence and a 61% (60–62) reduction in mortality compared with 2015 baseline.”

They conclude that reducing global burden requires successful prevention interventions, as well as outreach screening. Prevention priorities are blood safety, infection control, harm reduction for PWUD. Finding patients with extensive screening and link to treatment for all are also necessary. Key high-burden countries including China, India, and Pakistan will influence the global burden of hepatitis C and its consequences.

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Modelling HCV epidemiology in Switzerland

The increases in diagnosis and treatment rates necessary to reach the hepatitis elimination goals in Switzerland were shown by modelling. The current epidemiology of hepatitis C virus was modelled in three regions of Switzerland, as an aid to achieving the goals of the Swiss Hepatitis Strategy.
According to the study, elimination of chronic hepatitis C infection in eastern (region of St Gallen), western (region of Geneva) and northern (region of Zurich) Switzerland is possible by 2030. However, the current rate at which cases of hepatitis C are identified and treated is not sufficient.
Read the full research article on the Swiss Medical Weekly website.
Rusch, U., Robbins, S., Razavi, H., Vernazza, P., Blach, S., Bruggmann, P., Müllhaupt, B., Negro, F., and Semela, D. (2019) Microelimination of chronic hepatitis C in Switzerland: modelling the Swiss Hepatitis Strategy goals in eastern, western and northern regions. Swiss Medical Weeklyhttps://doi.org/10.4414/smw.2019.14694.

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Retrospective modelling shows peak incidence, transmission patterns

Modellers reconstruct HCV’s arrival in Scotland using phylogenetics, geographic information science (GIS) and Bayesian analysis. Different genotypes are tracked after they are introduced to Glasgow from the global pool. The peak of incidence appears to have been in the 1980s.
This kind of analysis is important to understand transmission, and what has contributed to interrupting it. For microelimination, it is critical to understand networks of transmission, and the dynamics of links between them. This kind of analysis can also be used to prioritise the discovery and treatment of people with resistant variants. It can to used to most convincingly evaluate the effectiveness of current and future interventions as well. With thorough evaluations, microelimination techniques can be refined and adapted to different circumstances.
Click here for full text of McNaughton et al., Spatiotemporal reconstruction of the introduction of hepatitis C virus into Scotland and its subsequent regional transmission, in the Journal of Virology, in 2015

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Using modelling to make policy choices in Pakistan

Aaron Lim et al modelled the hepatitis C epidemic in Pakistan, showing different scenarios
Click here for slides, full text of the paper is here. They projected the HCV epidemic under different treatment scenarios, showing how concentrating case-finding and treatment could more quickly reduce the epidemic. They showed that substantial scale-up in treatment can be minimized (from 880,000 to 525 000 per year) through scaling up prevention interventions and targeting treatment to people with cirrhosis and people who inject drugs.

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Modelling HCC risk in treated patients

Estimated 3-year risk of hepatocellular carcinoma, modelled using recent research in patients treated for HCV. (George N. Ioannou et al, 2018, Journal of Hepatology) This calculator is intended for use by treatment providers, not for patients. It has not been validated in patients without HCV treatment. Access is provided for educational purposes only, through this site and links to other sites. Content is not recommended or endorsed by any doctor or healthcare provider. The information and content provided are not substitutes for medical or professional care. Diagnostic evaluation for HCC among patients with abnormal screening results should include either multiphasic CT or MRI. Find the calculator here.