Africa is experiencing a dramatic epidemiological transition driven in opposite directions by continuing improvements in the management of traditional infectious diseases, concurrent exploding sexually transmitted infection and TB epidemics, and swift increases in the prevalence of chronic non-communicable diseases. With the following specific aims, this career development application fits into my long-term goal to contribute to understanding and eventually controlling pandemic sexually transmitted infections inAfrica. (1) To measure and understand the important component systems of a population affected by sexually transmitted infections through empirical investigation of hypotheses that relate core groups, concurrency in sexual relationships and migration to the transmission and spread of sexually transmitted infections. (2) To modify, enhance and build mathematical/computational models to represent and investigate populations affected by sexually transmitted infections by: 1) continuing to adapt Bayesian melding methods that account for uncertainty in model inputs and outputs to work with UNAIDS's non-age-specific estimation and projections package (EPP) model;2) to adapt and implement similar methods to work with a sexually transmitted infection-enabled age-specific cohort component projection model;3) to improve my existing sexually transmitted infection-enabled microsimulator by: a) adding new modules to handle social, sexual and migrant networks, b) adding new procedures based on Bayesian melding to i) account for uncertainty, ii) put reasonable limits on outputs, iii)produce predictive distributions for outputs, and iv) provide a standard, reproducible method to calibrate the simulator. (3) To simulate populations affected by sexually transmitted infections to understand and predict the overall effects of interventions. There are three proximate determinants of an infectious disease epidemic, the transmission probability/?, the contact structurec, and the duration of infectiousnessdsuggested by the relationship R0 = f3? c ?d for the number of secondary cases produced by a case. The simulator will be used to explore the relationships between these and the dynamics of sexually transmitted infection epidemics. Insight gained through this process will be used to simulate and prioritize possible real interventions. I have experience with this type of investigation and some of the skills necessary to address these specific aims. The career development component of this application is designed to expand my minimal knowledge and skills in three specific areas that are necessary to address these aims: 1) social network theory and modeling methods, 2) mathematical statistics and Bayesian statistics in particular, and 3) modem up-to-date software algorithm design and computer programming skills.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01HD057246-05
Application #
8288877
Study Section
Pediatrics Subcommittee (CHHD)
Program Officer
Newcomer, Susan
Project Start
2008-06-15
Project End
2013-09-30
Budget Start
2012-06-01
Budget End
2013-09-30
Support Year
5
Fiscal Year
2012
Total Cost
$126,305
Indirect Cost
$9,356
Name
University of Washington
Department
Social Sciences
Type
Schools of Arts and Sciences
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Clark, Samuel J; Houle, Brian (2014) Validation, replication, and sensitivity testing of Heckman-type selection models to adjust estimates of HIV prevalence. PLoS One 9:e112563
Sankoh, Osman; Sharrow, David; Herbst, Kobus et al. (2014) The INDEPTH standard population for low- and middle-income countries, 2013. Glob Health Action 7:23286
Sharrow, David J; Clark, Samuel J; Raftery, Adrian E (2014) Modeling age-specific mortality for countries with generalized HIV epidemics. PLoS One 9:e96447
Collinson, Mark A; White, Michael J; Bocquier, Philippe et al. (2014) Migration and the epidemiological transition: insights from the Agincourt sub-district of northeast South Africa. Glob Health Action 7:23514
Houle, Brian; Clark, Samuel J; Gómez-Olivé, F Xavier et al. (2014) The unfolding counter-transition in rural South Africa: mortality and cause of death, 1994-2009. PLoS One 9:e100420
Clark, Samuel J; Kahn, Kathleen; Houle, Brian et al. (2013) Young children's probability of dying before and after their mother's death: a rural South African population-based surveillance study. PLoS Med 10:e1001409
Houle, Brian; Stein, Alan; Kahn, Kathleen et al. (2013) Household context and child mortality in rural South Africa: the effects of birth spacing, shared mortality, household composition and socio-economic status. Int J Epidemiol 42:1444-54
Gomez-Olive, Francesc Xavier; Angotti, Nicole; Houle, Brian et al. (2013) Prevalence of HIV among those 15 and older in rural South Africa. AIDS Care 25:1122-8
Madhavan, Sangeetha; Schatz, Enid; Clark, Samuel et al. (2012) Child mobility, maternal status, and household composition in rural South Africa. Demography 49:699-718