Publications

Reply to ?Should biomarker estimates of HIV incidence be adjusted?
Welte A, McWalter TA, Bärnighausen T

AIDS

(2009)

https://doi.org/10.1097/QAD.0b013e32832eff59
Is scaling up enough to curb the HIV epidemic in southern Africa?
Delva W, Temmerman M, Pretorius C

South African Medical Journal

(2009)

http://hdl.handle.net/10019.1/7027
Male circumcision for HIV prevention in high HIV prevalence settings: what can mathematical modelling contribute to informed decision making?
Auvert B, Porco TC, Dorrington R, Schmid G, Hankins C, Stover J, Raddad LA, Weiss H, Bollinger L, White P, Ghani A, White RG, Gray R, Hallet TB, Hargrove JW, Kahn JG, Welte A, Lohse N, Williams BG, Nagelkerke N

PLoS Medicine

(2009)

https://doi.org/10.1371/journal.pmed.1000109
AIDS among older children and adolescents in Southern Africa: projecting the time course and magnitude of the epidemic
Ferrand RA, Corbett EL, Wood R, Hargrove JW, Ndhlovu CE, Cowan FM, Gouws E, Williams BG

AIDS

(2009)

https://doi.org/10.1097/QAD.0b013e32833016ce
Monitoring the South African National Antiretroviral Treatment Programme, 2003 – 2007: The IeDEA Southern Africa Collaboration
Cornell M, Technau K, Fairall L, Wood R, Moultrie H, van Cutsem G, Giddy J, Mohapi L, Eley B, Macphail P, Prozesky H, Rabie H, Davies MA, Maxwell N, Boulle A, International epidemiologic Databases to Evaluate AIDS Southern Africa Collaboration

South African Medical Journal

(2009)

https://pubmed.ncbi.nlm.nih.gov/20073292
Improving the cost-effectiveness of artificial visual baits for controlling the tsetse fly Glossina fuscipes fuscipes
Lindh JM, Torr SJ, Vale GA, Lehane MJ

PLoS Neglected Tropical Diseases

(2009)

https://doi.org/10.1371/journal.pntd.0000474
HIV incidence in rural South Africa: comparison of estimates from longitudinal surveillance and cross-sectional cBED assay testing
Bärnighausen T, Wallrauch C, Welte A, McWalter TA, Mbizana N, Viljoen J, Graham N, Tanser FC, Puren A, Newell ML

PLoS One

(2009)

https://doi.org/10.1371/journal.pone.0003640
A simplified formula for inferring HIV incidence from cross-sectional surveys using a test for recent infection
Welte A, McWalter TA, Bärnighausen T

AIDS Research And Human Retroviruses

(2009)

https://doi.org/10.1089/aid.2008.0150
A tuberculosis model: The case of “reasonable” and “unreasonable” infectives
Nyabadza F, Mukwembi S, Rodrigues BG

Physica A: Statistical Mechanics and its Applications

(2009)

https://doi.org/10.1016/j.physa.2009.01.039
On the relationship between age, annual rate of infection, and prevalence of mycobacterium tuberculosis in a South African township
Pretorius C, Bacaër N, Williams BG, Robin W, Ouifki R

Clinical Infectious Diseases

(2009)

https://doi.org/10.1086/597357

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