Our new paper in the Journal of the Royal Society Interface explores how ephemeral resources shape the disease transmission network of foragers attracted to those resources. The paper is motivated by a question Steve developed during his PhD research on anthrax outbreaks in plains zebra and the movement patterns of the black-backed jackals that scavenge those carcasses in Etosha National Park, Namibia. Jackals consume anthrax carcasses without getting sick; but huge aggregations of otherwise territorial jackals at carcasses (in the dozens) may facilitate transmission of diseases like rabies through aggressive interactions (see photo above). Using mathematical modeling and statistical analyses of jackal movement data, we show that the contact rate between jackals initially increases with the number of available carcasses, but then decreases as carcasses are so plentiful that there are fewer jackals sharing each carcass. Importantly, the resource density at which the jackal contact rate peaks depends on from how far away jackals can detect carcasses. This work was led by Becky Borchering at the University of Florida.
Borchering, Bellan, Flynn, Pulliam, Mckinley, Mckinley (2017). Resource-driven encounters among consumers and implications for the spread of infectious disease. Journal of the Royal Society Interface. (PDF)
I’m delighted to announce that Rachel (Race) Mercaldo has joined the lab as she finishes up the 1st year of her doctoral program in Epidemiology and Biostatistics. Read about Rachel’s background on our People page!
The 2017 Clinic on the Meaningful Modeling of Epidemiological Data (MMED) has come and gone, and left a wake of clinic faculty and participants happy to have spent two weeks together in beautiful Muizenberg, South Africa. This year we made a big push to help disseminate ICI3D teaching materials to a wider audience online. As part of this, we professionally recorded two days of MMED 2017. These video lectures, slides for all MMED 2017 lectures, and links to our R Tutorials Github repository can now be found on the ICI3D Figshare Collection. This provides resources lovingly polished by the ICI3D faculty (including many by Steve) over 8+ years in an open access, citable way.
We encourage those teaching or learning infectious disease ecology and epidemiology, or statistics to check these resources out! Please do cite us and let us know if you use them so we can keep records on their impact.
In a new paper in Proceedings of the Royal Society B, we investigated under what circumstances earlier initiation of antiretroviral therapy could decrease both the number of total new HIV infections and of new drug-resistant HIV infections amongst men who have sex with men (MSM) in San Francisco. Using a transmission model fit to data from this population, we find that this goal occurs when the second-line drug effectiveness (combination of resistance monitoring, biomedical drug efficacy, and adherence) exceeds 80%. However, these dual decreases in the number of new infections may misleadingly and seemingly paradoxically be accompanied by an increase in the proportion of new infections that are drug resistant. This work was led by Mingwang Shen, a PhD student visiting from Xi’an Jiaotong University, in close collaboration with Steve during Mingwang’s 2 year scholar exchange in Lauren Ancel Meyers’ Lab at The University of Texas at Austin.
Shen M, Xiao Y, Rong L, Meyers LA, and Bellan SE (2017). Early antiretroviral therapy and potent second-line drugs could decrease HIV incidence of drug resistance. Proc R Soc B. (postprint PDF, journal PDF) (Appendix)
Many studies have characterized the immune system recovery of HIV-infected patients following antiretroviral treatment, as evidenced by CD4+ cell count increases over time. Such analyses rarely have large enough samples to examine how patterns vary by sex and age.
In Means et al. 2016, published in PLOS ONE, we analyzed >200,000 observations of >30,000 individuals recorded by the outpatient monitoring system of the National AIDS Control Program in Tanzania. We found that older patients started treatment at higher CD4+ counts (i.e. earlier in disease progression) but experienced slower CD4+ recovery. We also found that earlier treatment initiation led to greater eventual CD4+ cell counts regardless of age or sex (figure below).
This publication arose from a group project initiated during the 2014 Clinic on the Meaningful Modeling of Epidemiological Data.
At the beginning of September Dr. Bellan began his appointment as an Assistant Professor in the Department of Epidemiology and Biostatistics, College of Public Health at the University of Georgia. He is very excited to join the fantastic infectious disease research community at UGA!