Inferring incidence from prevalence, the example of HIV in Baltimore, USA
Supervisors: Dr. Deirdre Hollingsworth, Dr. Lousie Dyson, Dr Oliver Laeyendecker (Johns
Hopkins, USA)
Research objectives
The aim of this research would be to understand the dynamics of HIV in Baltimore, USA through
cross-sectional surveillance of HIV and two coinfections. In performing this research, we expect
to develop better tools for estimating underlying incidence of infection from repeated crosssectional surveys of the prevalence of infection which could be applied to multiple infections.
Research context & modelling considerations
Transmission of HIV in Baltimore is ongoing, with a recent decline in diagnoses. There is a need
to understand these dynamics in terms of underlying changes in behaviour, such as declines in
intravenous drug use (associate with hepatitis C virus (HCV) transmission) and shifts in sexual
risk behaviour (associated with herpes simplex virus (HSV) transmission). Through analysing
cross-sectional data on prevalence of these three infections, we aim to understand which shifts
in behaviour are affecting the HIV epidemic.
Estimating incidence from repeated surveys of prevalence is an area of epidemiological research
with a long history, particularly in the area of childhood infections [1]. However, application to
HIV is more challenging due to the long infection period and variable behaviour over a lifetime.
There are methods for using cross-sectional prevalence surveys to estimate incidence [2], but
these have not been used in conjunction with co-infection models and data in this way before.
There is therefore scope for methodological advances, as well as public health relevant results.
External collaboration and data
This project will be performed in close collaboration with Dr Oliver Laeyendecker from Johns
Hopkins University, USA. Dr Laeyendecker has been a collaborator of Hollingsworth’s for many
years [3]. The data for this project has already been shared, and some initial analyses have been
performed as part of an MMath project (2015/16), but this has only touched a small part of the
potential analyses of the data.
Every 3-6 years, a cross-sectional sample of those attending the emergency department of Johns
Hopkins University Hospital in Baltimore are tested for HIV, hepatitis C virus and herpes simplex
virus. These tests are individually linked, with additional data on age and ethnic group. They
give an indication of the shifts in HCV incidence to older age groups due to declining intravenous
drug use and difference age shifts for HIV an HSV in particular ethnic groups.
Application to the real world: who will benefit?
The analyses in this MSc project will provide important insights on the dynamics of HIV in
Baltimore, and will therefore have impact on local HIV control policy. This project will also
provide methodological insight on the use of cross-sectional prevalence surveys to infer
incidence of new infection, and area of ongoing research across the HIV field.
Avenues for PhD research
The project can be taken in a number of different directions, depending on the results of the
analysis and the interests of the student and collaborators. Potential avenues include


Developing tools for inferring incidence from cross-sectional prevalence surveys using
different diagnostic markers.
Developing models of co-infection, in particular HIV with HCV and HSV, and
understanding how their dynamics
References
[1] Whitaker, H. J., & Farrington, C. P. (2004). Infections with varying contact rates: application
to varicella. Biometrics, 60(3), 615-623.
[2] Hall, H. Irene, et al. "Estimation of HIV incidence in the United States." Jama 300.5 (2008):
520-529.
[3] Hollingsworth, T. D., Laeyendecker, O., Shirreff, G., et al. (2010). HIV-1 transmitting couples
have similar viral load set-points in Rakai, Uganda. PLoS Pathog, 6(5), e1000876.