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Emerging Themes in Epidemiology
Published in: Emerging Themes in Epidemiology 1/2018

Open Access 01-12-2018 | Analytic perspective

The contributions and future direction of Program Science in HIV/STI prevention

Authors: Marissa Becker, Sharmistha Mishra, Sevgi Aral, Parinita Bhattacharjee, Rob Lorway, Kalada Green, John Anthony, Shajy Isac, Faran Emmanuel, Helgar Musyoki, Lisa Lazarus, Laura H. Thompson, Eve Cheuk, James F. Blanchard

Published in: Emerging Themes in Epidemiology | Issue 1/2018

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Abstract

Background

Program Science is an iterative, multi-phase research and program framework where programs drive the scientific inquiry, and both program and science are aligned towards a collective goal of improving population health.

Discussion

To achieve this, Program Science involves the systematic application of theoretical and empirical knowledge to optimize the scale, quality and impact of public health programs. Program Science tools and approaches developed for strategic planning, program implementation, and program management and evaluation have been incorporated into HIV and sexually transmitted infection prevention programs in Kenya, Nigeria, India, and the United States.

Conclusion

In this paper, we highlight key scientific contributions that emerged from the growing application of Program Science in the field of HIV and STI prevention, and conclude by proposing future directions for Program Science.
Literature
1.
Blanchard JF, Aral SO. Program Science: an initiative to improve the planning, implementation and evaluation of HIV/sexually transmitted infection prevention programmes. Sex Transm Infect. 2011;87(1):2–3.CrossRefPubMed
2.
Aral SO, Blanchard JF. The Program Science initiative: improving the planning, implementation and evaluation of HIV/STI prevention programs. Sex Transm Infect. 2012;88(3):157–9.CrossRefPubMed
3.
Leeman J, et al. Beyond “implementation strategies”: classifying the full range of strategies used in implementation science and practice. Implement Sci. 2017;12(1):125.CrossRefPubMedPubMedCentral
4.
Padian NS, et al. Implementation science for the US President’s Emergency Plan for AIDS Relief (PEPFAR). J Acquir Immune Defic Syndr. 2011;56(3):199–203.CrossRefPubMed
5.
6.
7.
Parkhurst J, Weller I, Kemp J. Getting research into policy, or out of practice, in HIV? Lancet. 2010;375(9724):1414–5.CrossRefPubMed
8.
Pinto RM, Wall MM, Spector AY. Modeling the structure of partnership between researchers and front-line service providers: strengthening collaborative public health research. J Mix Methods Res. 2014;8(1):83–106.CrossRefPubMed
9.
South J, Phillips G. Evaluating community engagement as part of the public health system. J Epidemiol Community Health. 2014;68(7):692–6.CrossRefPubMed
10.
De Cock KM, Jaffe HW, Curran JW. The evolving epidemiology of HIV/AIDS. AIDS. 2012;26(10):1205–13.CrossRefPubMed
11.
12.
Maartens G, Celum C, Lewin SR. HIV infection: epidemiology, pathogenesis, treatment, and prevention. Lancet. 2014;384(9939):258–71.CrossRefPubMed
13.
Cuadros DF, Awad SF, Abu-Raddad LJ. Mapping HIV clustering: a strategy for identifying populations at high risk of HIV infection in sub-Saharan Africa. Int J Health Geogr. 2013;12:28.CrossRefPubMedPubMedCentral
14.
Aral SO, Cates W Jr. Coverage, context and targeted prevention: optimising our impact. Sex Transm Infect. 2012;89(4):336–40.CrossRefPubMed
15.
Wilson D, Halperin DT. “Know your epidemic, know your response”: a useful approach, if we get it right. Lancet. 2008;372(9637):423–6.CrossRefPubMed
16.
17.
18.
McClarty LM, et al. Key Programme Science lessons from an HIV prevention ‘Learning Site’ for sex workers in Mombasa. Sex Transm Infect: Kenya; 2017.
19.
Obure CD, et al. Optimising the cost and delivery of HIV counselling and testing services in Kenya and Swaziland. Sex Transm Infect. 2012;88(7):498–503.CrossRefPubMedPubMedCentral
20.
Peeling RW, Mabey D, Ballard RC. Introducing new diagnostics into STI control programmes: the importance of programme science. Sex Transm Infect. 2013;89(2):115–9.CrossRefPubMed
21.
Wilson D. International AIDS policy choices for a changing financing landscape. Sex Transm Infect. 2011;87(Suppl 1):A11.CrossRef
22.
Centers for Disease Control and Prevention, Improving Sexually Transmitted Disease Programs through Assessment, Assurance, Policy Development, and Prevention Strategies (STD AAPPS CDC-RFA-PS14-1402), Division of Sexually Transmitted Diseases Prevention, Editor. 2013: Atlanta.
23.
Reza-Paul S, et al. Sex worker-led structural interventions in India: a case study on addressing violence in HIV prevention through the Ashodaya Samithi collective in Mysore. Indian J Med Res. 2012;135:98–106.CrossRefPubMedPubMedCentral
24.
Lorway R, Khan S. Reassembling epidemiology: mapping, monitoring and making-up people in the context of HIV prevention in India. Soc Sci Med. 2014;112:51–62.CrossRefPubMed
25.
Gray RH, Wawer MJ, Kigozi G. Programme science research on medical male circumcision scale-up in sub-Saharan Africa. Sex Transm Infect. 2013;89(5):345–9.CrossRefPubMed
26.
Emmanuel F, Isac S, Blanchard JF. Using geographical mapping of key vulnerable populations to control the spread of HIV epidemics. Expert Rev Anti Infect Ther. 2013;11(5):451–3.CrossRefPubMed
27.
National STI, Control Programme AIDS, Council NAC. Geographic mapping of most at risk populations for HIV (MARPs) in Kenya. Nairobi: NASCOP, NACC; 2012.
28.
Karnataka Health Promotion Trust. Mapping of High Risk Groups (HRG) in Karnataka, India. Karnataka State Report. Bangalore: Karnataka Health Promotion Trust; 2010.
29.
National Agency for the Control of AIDS. HIV epidemic appraisals in Nigeria: evidence for prevention programme planning and implementation. Data from the first eight states. Abuja: National Agency for the Control of AIDS; 2013.
30.
National AIDS Control Program (NACP). Mapping of key populations at higher risk of HIV round IV. v: Ministry of Health; 2012.
31.
UNAIDS. Local Epidemics Issues Brief. Geneva: UNAIDS; 2014.
32.
33.
Anderson SJ, et al. Maximising the effect of combination HIV prevention through prioritisation of the people and places in greatest need: a modelling study. Lancet. 2014;384(9939):249–56.CrossRefPubMed
34.
35.
Bradford JB, Coleman S, Cunningham W. HIV system navigation: an emerging model to improve HIV care access. AIDS Patient Care STDS. 2007;21(Suppl 1):S49–58.PubMedCrossRef
36.
Prudden HJ, et al. Can the UNAIDS modes of transmission model be improved? A comparison of the original and revised model projections using data from a setting in West Africa. AIDS. 2013;27(16):2623–35.CrossRefPubMedPubMedCentral
37.
Mishra, S., et al., Validation of the Modes of Transmission Model as a tool to prioritize HIV prevention targets: a comparative modeling analysis. submitted., 2012.
38.
Mishra S, et al. Distinguishing sources of HIV transmission from the distribution of newly acquired HIV infections: why is it important for HIV prevention planning? Sex Transm Infect. 2014;90(1):19–25.CrossRefPubMed
39.
Schwartländer B, et al. Towards an improved investment approach for an effective response to HIV/AIDS. The Lancet. 2011;377(9782):2031–41.CrossRef
40.
41.
Ramesh BM, et al. Changes in risk behaviours and prevalence of sexually transmitted infections following HIV preventive interventions among female sex workers in five districts in Karnataka state, south India. Sex Transm Infect. 2010;86(Suppl 1):i17–24.CrossRefPubMedPubMedCentral
42.
Isac S, et al. Changes in HIV and syphilis prevalence among female sex workers from three serial cross-sectional surveys in Karnataka state, South India. BMJ Open. 2015;5(3):e007106.CrossRefPubMedPubMedCentral
43.
Jayaraman GC, et al. Demographic changes and trends in risk behaviours, HIV and other sexually transmitted infections among female sex workers in Bangalore, India involved in a focused HIV preventive intervention. Sex Transm Infect. 2013;89(8):635–41.CrossRefPubMed
44.
Reza-Paul S, et al. Declines in risk behaviour and sexually transmitted infection prevalence following a community-led HIV preventive intervention among female sex workers in Mysore, India. AIDS. 2008;22:S91–100.CrossRefPubMed
45.
46.
Gurnani V, et al. An integrated structural intervention to reduce vulnerability to HIV and sexually transmitted infections among female sex workers in Karnataka state, south India. BMC Public Health. 2011;11:755.CrossRefPubMedPubMedCentral
47.
Beattie TS, et al. Violence against female sex workers in Karnataka state, south India: impact on health, and reductions in violence following an intervention program. BMC Public Health. 2010;10:476.CrossRefPubMedPubMedCentral
48.
Argento E, et al. Confronting structural violence in sex work: lessons from a community-led HIV prevention project in Mysore, India. AIDS Care. 2011;23(1):69–74.CrossRefPubMed
49.
Lazarus L, Reza-Paul S, Pasha A, Jairam S, Hafeez Ur Rahman S, O’Neil J, Lorway R. Exploring the role of community-based peer support in improving access to care and antiretroviral treatment for sex workers in Mysore India. J HIV/AIDS Soc Serv. 2012;11(2):152–68.CrossRef
50.
NASCOP, N.A.S.C.P. Most-at-risk-populations; unveiling new evidence for accelerated programming. Nairobi: National AIDS & STI Control Progamme- NASCOP; 2012.
51.
National AIDS and STI Control Programme, Key Population Data Collection Tools in Kenya. Reference Manual. 2014, National AIDS and STI Control Programme: Nairobi.
52.
Mishra S, et al. Characterizing sexual histories of women before formal sex-work in south India from a cross-sectional survey: implications for HIV/STI prevention. BMC Public Health. 2012;12:829.CrossRefPubMedPubMedCentral
53.
Becker ML, et al. Rates and determinants of HIV-attributable mortality among rural female sex workers in northern Karnataka, India. Int J STD AIDS. 2012;23(1):36–40.CrossRefPubMed
54.
Cheuk E, Mishra S, Becker M. Mapping and estimating the population size of young women engaged in casual, transactional and formal sex work in Mombasa, Kenya and Dnipropetrovsk, Ukraine, in Program Science Symposium, International Society for Sexually Transmitted Diseases Research. Australia: Brisbane; 2015.
55.
56.
Boily MC, Lowndes C, Alary M. The impact of HIV epidemic phases on the effectiveness of core group interventions: insights from mathematical models. Sex Transm Infect. 2002;78(Suppl 1):i78–90.CrossRefPubMedPubMedCentral
57.
McLaren L, McIntyre L, Kirkpatrick S. Rose’s population strategy of prevention need not increase social inequalities in health. Int J Epidemiol. 2010;39(2):372–7.CrossRefPubMed
58.
Baral S, et al. Burden of HIV among female sex workers in low-income and middle-income countries: a systematic review and meta-analysis. Lancet Infect Dis. 2012;12(7):538–49.CrossRefPubMed
59.
Shannon K, et al. HIV infection among female sex workers in concentrated and high prevalence epidemics: why a structural determinants framework is needed. Curr Opin HIV AIDS. 2014;9(2):174–82.CrossRefPubMedPubMedCentral
60.
Anderson R, May R. Infectious diseases of humans: dynamics and control. Oxford: Oxford University Press; 1991.
61.
Garnett GP, et al. Mathematical models in the evaluation of health programmes. Lancet. 2011;378(9790):515–25.CrossRefPubMed
Metadata
Title
The contributions and future direction of Program Science in HIV/STI prevention
Authors
Marissa Becker
Sharmistha Mishra
Sevgi Aral
Parinita Bhattacharjee
Rob Lorway
Kalada Green
John Anthony
Shajy Isac
Faran Emmanuel
Helgar Musyoki
Lisa Lazarus
Laura H. Thompson
Eve Cheuk
James F. Blanchard
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Emerging Themes in Epidemiology / Issue 1/2018
Electronic ISSN: 1742-7622
DOI
https://doi.org/10.1186/s12982-018-0076-8

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