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JMIR Public Health Surveill. 2018 Apr 3;4(2):e36. doi: 10.2196/publichealth.9344.

Strengthening Routine Data Systems to Track the HIV Epidemic and Guide the Response in Sub-Saharan Africa.

Author information

1
Social and Environmental Health Research, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
2
Centre for Infectious Disease Epidemiology and Research, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
3
Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, United States.
4
Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
5
Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
6
Global Health Sciences, University of California San Francisco, San Francisco, CA, United States.
7
Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States.

Abstract

The global HIV response has entered a new phase with the recommendation of treating all persons living with HIV with antiretroviral therapy, and with the goals of reducing new infections and AIDS-related deaths to fewer than 500,000 by 2020. This new phase has intensive data requirements that will need to utilize routine data collected through service delivery platforms to monitor progress toward these goals. With a focus on sub-Saharan African, we present the following priorities to improve the demand, supply, and use of routine HIV data: (1) strengthening patient-level HIV data systems that support continuity of clinical care and document sentinel events; (2) leveraging data from HIV testing programs; (3) using targeting data collection in communities and among clients; and (4) building capacity and promoting a culture of HIV data quality assessment and use. When fully leveraged, routine data can efficiently provide timely information at a local level to inform action, as well as provide information at scale with wide geographic coverage to strengthen estimation efforts.

KEYWORDS:

HIV; cascade; clinical; data; monitoring; prevention; program; quality assessment; sub-Saharan Africa; surveillance; systems; testing; treatment

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