scholarly journals Know Your Epidemic, Strengthen Your Response: Developing a New HIV Surveillance Architecture to Guide HIV Resource Allocation and Target Decisions (Preprint)

2017 ◽  
Author(s):  
Brian Rice ◽  
Travis Sanchez ◽  
Stefan Baral ◽  
Paul Mee ◽  
Keith Sabin ◽  
...  
Keyword(s):  
Public Health ◽  
Resource Allocation ◽  
Hiv Prevention ◽  
Surveillance Data ◽  
High Quality ◽  
Hiv Surveillance ◽  
Hiv Epidemic ◽  
Prevention And Treatment ◽  
Special Collection

UNSTRUCTURED To guide HIV prevention and treatment activities up to 2020, we need to generate and make better use of high quality HIV surveillance data. To highlight our surveillance needs, a special collection of papers in JMIR Public Health and Surveillance has been released under the title “Improving Global and National Responses to the HIV Epidemic Through High Quality HIV Surveillance Data.” We provide a summary of these papers and highlight methods for developing a new HIV surveillance architecture.

scholarly journals Using HIV Surveillance Data to Link People to HIV Medical Care, 5 US States, 2012-2015

2018 ◽  
Vol 133 (4) ◽  
pp. 385-391 ◽  
Author(s):  
John Beltrami ◽  
Odessa Dubose ◽  
Reginald Carson ◽  
Janet C. Cleveland
Keyword(s):  
Public Health ◽  
Hiv Prevention ◽  
Linkage To Care ◽  
Surveillance Data ◽  
Hiv Care ◽  
Performance Standard ◽  
Health Staff ◽  
Health Departments ◽  
Hiv Surveillance ◽  
Prevention Activities

Introduction: From 2012 through 2015, the Centers for Disease Control and Prevention (CDC) provided funding to 5 health departments for demonstration projects using HIV surveillance data to link people with newly diagnosed HIV to care. We assessed how well these health departments established linkage to care, how the demonstration projects helped them with this work, and if they sustained these activities after CDC funding ended. Materials and Methods: We obtained quantitative and qualitative data on linkage-to-care activities from health department communications and progress reports submitted to CDC. We calculated and combined linkage-to-care results for the 5 health departments, and we compared these results with the combined linkage-to-care results for 61 health departments that received CDC funding for routine HIV prevention activities (eg, HIV testing, linkage to and reengagement in HIV care, HIV partner services) and for the same 5 health departments when they used only routine HIV prevention activities for linkage to care. Results: Of 1269 people with a new HIV diagnosis at the 5 health departments, 1124 (89%) were linked to care, a result that exceeded the 2010-2015 National HIV/AIDS Strategy goal (85%), the CDC Funding Opportunity Announcement performance standard (80%), and combined results for the 61 health departments (63%) and the same 5 health departments (66%) using routine HIV prevention activities. Benefits of the projects were improved collaboration and coordination and more accurate, up-to-date surveillance data. All health departments continued linkage-to-care activities after funding ended. Practice Implications: Using HIV surveillance data to link people with HIV to care resulted in substantial clinical and public health benefits. Our observations underscore the importance of collaboration among medical providers, public health staff members, community-based organizations, and people with HIV to ensure the best possible clinical and public health outcomes.

scholarly journals A Data Visualization and Dissemination Resource to Support HIV Prevention and Care at the Local Level: Analysis and Uses of the AIDSVu Public Data Resource (Preprint)

2020 ◽  
Author(s):  
Patrick Sean Sullivan ◽  
Cory Woodyatt ◽  
Chelsea Koski ◽  
Elizabeth Pembleton ◽  
Pema McGuinness ◽  
...  
Keyword(s):  
Public Health ◽  
Population Based ◽  
Surveillance Data ◽  
Public Health Decision ◽  
Hiv Surveillance ◽  
Related Data ◽  
Health Decision Making ◽  
Hiv Epidemic ◽  
The Us ◽  
Health Decision

BACKGROUND AIDSVu is a public resource for visualizing HIV surveillance data and other population-based information relevant to HIV prevention, care, policy, and impact assessment. OBJECTIVE The site, AIDSVu.org, aims to make data about the US HIV epidemic widely available, easily accessible, and locally relevant to inform public health decision making. METHODS AIDSVu develops visualizations, maps, and downloadable datasets using results from HIV surveillance systems, other population-based sources of information (eg, US Census and national probability surveys), and other data developed specifically for display and dissemination through the website (eg, pre-exposure prophylaxis [PrEP] prescriptions). Other types of content are developed to translate surveillance data into summarized content for diverse audiences using infographic panels, interactive maps, local and state fact sheets, and narrative blog posts. RESULTS Over 10 years, AIDSVu.org has used an expanded number of data sources and has progressively provided HIV surveillance and related data at finer geographic levels, with current data resources providing HIV prevalence data down to the census tract level in many of the largest US cities. Data are available at the county level in 48 US states and at the ZIP Code level in more than 50 US cities. In 2019, over 500,000 unique users consumed AIDSVu data and resources, and HIV-related data and insights were disseminated through nearly 4,000,000 social media posts. Since AIDSVu’s inception, at least 249 peer-reviewed publications have used AIDSVu data for analyses or referenced AIDSVu resources. Data uses have included targeting of HIV testing programs, identifying areas with inequitable PrEP uptake, including maps and data in academic and community grant applications, and strategically selecting locations for new HIV treatment and care facilities to serve high-need areas. CONCLUSIONS Surveillance data should be actively used to guide and evaluate public health programs; AIDSVu translates high-quality, population-based data about the US HIV epidemic and makes that information available in formats that are not consistently available in surveillance reports. Bringing public health surveillance data to an online resource is a democratization of data, and presenting information about the HIV epidemic in more visual formats allows diverse stakeholders to engage with, understand, and use these important public health data to inform public health decision making.

scholarly journals A Data Visualization and Dissemination Resource to Support HIV Prevention and Care at the Local Level: Analysis and Uses of the AIDSVu Public Data Resource

10.2196/23173 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e23173 ◽  
Author(s):  
Patrick Sean Sullivan ◽  
Cory Woodyatt ◽  
Chelsea Koski ◽  
Elizabeth Pembleton ◽  
Pema McGuinness ◽  
...  
Keyword(s):  
Public Health ◽  
Population Based ◽  
Surveillance Data ◽  
Public Health Decision ◽  
Hiv Surveillance ◽  
Related Data ◽  
Health Decision Making ◽  
Hiv Epidemic ◽  
The Us ◽  
Health Decision

Background AIDSVu is a public resource for visualizing HIV surveillance data and other population-based information relevant to HIV prevention, care, policy, and impact assessment. Objective The site, AIDSVu.org, aims to make data about the US HIV epidemic widely available, easily accessible, and locally relevant to inform public health decision making. Methods AIDSVu develops visualizations, maps, and downloadable datasets using results from HIV surveillance systems, other population-based sources of information (eg, US Census and national probability surveys), and other data developed specifically for display and dissemination through the website (eg, pre-exposure prophylaxis [PrEP] prescriptions). Other types of content are developed to translate surveillance data into summarized content for diverse audiences using infographic panels, interactive maps, local and state fact sheets, and narrative blog posts. Results Over 10 years, AIDSVu.org has used an expanded number of data sources and has progressively provided HIV surveillance and related data at finer geographic levels, with current data resources providing HIV prevalence data down to the census tract level in many of the largest US cities. Data are available at the county level in 48 US states and at the ZIP Code level in more than 50 US cities. In 2019, over 500,000 unique users consumed AIDSVu data and resources, and HIV-related data and insights were disseminated through nearly 4,000,000 social media posts. Since AIDSVu’s inception, at least 249 peer-reviewed publications have used AIDSVu data for analyses or referenced AIDSVu resources. Data uses have included targeting of HIV testing programs, identifying areas with inequitable PrEP uptake, including maps and data in academic and community grant applications, and strategically selecting locations for new HIV treatment and care facilities to serve high-need areas. Conclusions Surveillance data should be actively used to guide and evaluate public health programs; AIDSVu translates high-quality, population-based data about the US HIV epidemic and makes that information available in formats that are not consistently available in surveillance reports. Bringing public health surveillance data to an online resource is a democratization of data, and presenting information about the HIV epidemic in more visual formats allows diverse stakeholders to engage with, understand, and use these important public health data to inform public health decision making.

scholarly journals Working towards evidence-informed policy: Public health report Stockholm

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
V Bartelink ◽  
D Yacaman Mendez ◽  
A Lager
Keyword(s):  
Public Health ◽  
Resource Allocation ◽  
Scientific Literature ◽  
Decision Makers ◽  
High Quality ◽  
Public Health Report ◽  
The Public ◽  
Health Report ◽  
High Quality Evidence ◽  
Quality Evidence

Abstract Issue Public health problems and interventions are often addressed in sub-optimal ways by not prioritizing them based on the best available evidence. Description of the Problem The public health report 2019 for the Stockholm region aims to inform decision makers, politicians, and public health workers about the risk factors and diseases that account for the biggest part of the burden of disease with a clear focus on high quality evidence and communication of main messages. How did the public health report 2019 affect public health policy in the Stockholm region? Results The public health report 2019 influenced agenda setting, resource allocation and priority setting in the Stockholm region. Lessons We identified the following facilitating factors in the process, of which most also are supported in scientific literature, in chronological order: 1) understanding the policymaking context to be aware of windows of opportunity, 2) establishing relationships with relevant policymakers, engage with them routinely in the decision-making process, and being accessible for questions, 3) doing high-quality research by considering the latest scientific literature, multiple data sources and involving academic experts in the field, 4) communicating clear and relevant messages for generalists by translating research into easy-understandable texts and attractive figures, and 5) active dissemination of the report through multiple channels. In addition, the following barriers were identified: 1) the timeframe of the policymaking process was not in line with the research process, and 2) involving politicians in an early stage can potentially harm the objectivity of research in media messages. Key messages By focussing on major problems, high quality evidence and clear messages a public health report can contribute to more evidence-informed policy making. Engaging decision makers in the process of public health reporting is critical for the impact on agenda setting, resource allocation, and priority setting.

scholarly journals Improving HIV Surveillance Data for Public Health Action in Washington, DC: A Novel Multiorganizational Data-Sharing Method

2016 ◽  
Vol 2 (1) ◽  
pp. e3 ◽  
Author(s):  
Joanne Michelle F Ocampo ◽  
JC Smart ◽  
Adam Allston ◽  
Reshma Bhattacharjee ◽  
Sahithi Boggavarapu ◽  
...  
Keyword(s):  
Public Health ◽  
Data Sharing ◽  
Surveillance Data ◽  
Washington Dc ◽  
Public Health Action ◽  
Hiv Surveillance ◽  
Health Action

scholarly journals Impact of Cross-Jurisdictional Data Exchange on the Estimating of HIV Population Living in the District of Columbia (Preprint)

2018 ◽  
Author(s):  
Auntre Hamp ◽  
Rupali Doshi ◽  
Garret Lum ◽  
Adam Allston
Keyword(s):  
Data Sharing ◽  
Data Exchange ◽  
District Of Columbia ◽  
Surveillance Data ◽  
Health Departments ◽  
Hiv Surveillance ◽  
Residential Address ◽  
Hiv Epidemic ◽  
Persons Living With Hiv ◽  
The Impact

BACKGROUND Accurate HIV surveillance data is essential to monitoring the trends to end the HIV epidemic. Due to strict policies around data security and confidentiality, HIV surveillance data has not been routinely shared across jurisdictions, with the exception of a biannual case-by-case review process to identify and remove duplicate cases (Routine Interstate Duplicate Review, RIDR). HIV surveillance estimates for the District of Columbia (DC) are complicated by migration and care-seeking throughout the metropolitan area, which includes Maryland (MD) and Virginia (VA). To address gaps in HIV surveillance data, the health departments of DC, MD and VA established HIV surveillance data sharing agreements. While the Black Box (a privacy data integration tool external to the health departments) facilitated the secure exchange of data between DC, MD and VA, its previous iterations were limited by frequency and scope of information exchanged. The health departments of DC, MD and VA engaged in data sharing to further improve HIV surveillance estimates. OBJECTIVE The objectives of this evaluation were to assess the impact of cross-jurisdictional data-sharing on the estimation of persons living with HIV (PLWH) in DC and the reduction of cases in the RIDR process. METHODS The data sharing agreements established in 2014 allowed for the exchange of HIV case information (e.g. current residential address) and laboratory information (e.g. test types, result dates and results) from the enhanced HIV/AIDS Reporting System (eHARS). Regular data exchanges began in 2017. The participating jurisdictions transferred data (via secure file transfer protocol) for individuals having a residential address in a partnering jurisdiction at the time of HIV diagnosis and/or evidence of receiving HIV-related services at a facility located in a partnering jurisdiction. DC DOH compared the data received to the DC eHARS and imported updated data that matched to existing cases. Evaluation of changes in current residential address and HIV prevalence were conducted by comparing data before and after the HIV surveillance data exchanges. RESULTS After the HIV surveillance data exchange, an average of 390 fewer cases were estimated to be living in DC for each year from 2012 to 2016. Among cases with a residential status change, 66.4% of cases had relocated to MD and 19.8% had relocated to VA; the majority of these cases had relocated to counties bordering DC. Relocation in and out of DC differed by mode of transmission, race/ethnicity, age group and gender. After the data exchange, the volume of HIV cases needing RIDR decreased by 74% for DC-MD and 81% for DC-VA. CONCLUSIONS The HIV surveillance data exchange between the public health departments of DC, MD and VA reduced the number of cases misclassified as DC residents and reduced the number of cases needing RIDR. Continued data exchanges will enhance the ability of the DC DOH to monitor the local HIV epidemic.

scholarly journals Use of HIV Case Surveillance System to Design and Evaluate Site-Randomized Interventions in an HIV Prevention Study: HPTN 065

2012 ◽  
Vol 6 (1) ◽  
pp. 122-130 ◽  
Author(s):  
Deborah J Donnell ◽  
H Irene Hall ◽  
Theresa Gamble ◽  
Geetha Beauchamp ◽  
Angelique B Griffin ◽  
...  
Keyword(s):  
Hiv Prevention ◽  
Surveillance System ◽  
Viral Suppression ◽  
Laboratory Data ◽  
Linkage To Care ◽  
Baseline Data ◽  
Surveillance Data ◽  
Hiv Care ◽  
Hiv Surveillance ◽  
Hiv Test

Introduction:Modeling studies suggest intensified HIV testing, linkage-to-care and antiretroviral treatment to achieve viral suppression may reduce HIV transmission and lead to control of the epidemic. To study implementation of strategy, population-level data are needed to monitor outcomes of these interventions. US HIV surveillance systems are a potential source of these data.Methods:HPTN065 (TLC-Plus) Study is evaluating the feasibility of a test, linkage-to-care, and treat strategy for HIV prevention in two intervention communities - the Bronx, NY, and Washington, DC. Routinely collected laboratory data on diagnosed HIV cases in the national HIV surveillance system were used to select and randomize sites, and will be used to assess trial outcomes.Results:To inform study randomization, baseline data on site-aggregated study outcomes was provided from HIV surveillance data by New York City and Washington D.C. Departments of Health. The median site rate of linkage-to-care for newly diagnosed cases was 69% (IQR 50%-86%) in the Bronx and 54% (IQR 33%-71%) in Washington, D.C. In participating HIV care sites, the median site percent of patients with viral suppression (<400 copies/mL) was 57% (IQR 53%-61%) in the Bronx and 64% (IQR 55%-72%) in Washington, D.C.Conclusions:In a novel use of site-aggregated surveillance data, baseline data was used to design and evaluate site randomized studies for both HIV test and HIV care sites. Surveillance data have the potential to inform and monitor sitelevel health outcomes in HIV-infected patients.

scholarly journals What Should Health Departments Do with HIV Sequence Data?

Viruses ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1018
Author(s):  
Ethan Romero-Severson ◽  
Arshan Nasir ◽  
Thomas Leitner
Keyword(s):  
Public Health ◽  
Sequence Data ◽  
Public Health Practice ◽  
Health Benefit ◽  
Routine Care ◽  
Health Departments ◽  
Genetic Sequencing ◽  
Hiv Surveillance ◽  
Hiv Epidemic ◽  
Health Authorities

Many countries and US states have mandatory statues that require reporting of HIV clinical data including genetic sequencing results to the public health departments. Because genetic sequencing is a part of routine care for HIV infected persons, health departments have extensive sequence collections spanning years and even decades of the HIV epidemic. How should these data be used (or not) in public health practice? This is a complex, multi-faceted question that weighs personal risks against public health benefit. The answer is neither straightforward nor universal. However, to make that judgement—of how genetic sequence data should be used in describing and combating the HIV epidemic—we need a clear image of what a phylogenetically enhanced HIV surveillance system can do and what benefit it might provide. In this paper, we present a positive case for how up-to-date analysis of HIV sequence databases managed by health departments can provide unique and actionable information of how HIV is spreading in local communities. We discuss this question broadly, with examples from the US, as it is globally relevant for all health authorities that collect HIV genetic data.

scholarly journals Opening the ‘black box’ of collaborative improvement: a qualitative evaluation of a pilot intervention to improve quality of malaria surveillance data in public health centres in Uganda

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Eleanor Hutchinson ◽  
Susan Nayiga ◽  
Christine Nabirye ◽  
Lilian Taaka ◽  
Nelli Westercamp ◽  
...  
Keyword(s):  
Public Health ◽  
Quality Improvement ◽  
Health Workers ◽  
Qualitative Evaluation ◽  
Surveillance Data ◽  
Malaria Surveillance ◽  
High Quality ◽  
Self Reflection ◽  
Health Centres

Abstract Background Demand for high-quality surveillance data for malaria, and other diseases, is greater than ever before. In Uganda, the primary source of malaria surveillance data is the Health Management Information System (HMIS). However, HMIS data may be incomplete, inaccurate or delayed. Collaborative improvement (CI) is a quality improvement intervention developed in high-income countries, which has been advocated for low-resource settings. In Kayunga, Uganda, a pilot study of CI was conducted in five public health centres, documenting a positive effect on the quality of HMIS and malaria surveillance data. A qualitative evaluation was conducted concurrently to investigate the mechanisms of effect and unintended consequences of the intervention, aiming to inform future implementation of CI. Methods The study intervention targeted health workers, including brief in-service training, plus CI with ‘plan-do-study-act’ (PDSA) cycles emphasizing self-reflection and group action, periodic learning sessions, and coaching from a CI mentor. Health workers collected data on standard HMIS out-patient registers. The qualitative evaluation (July 2015 to September 2016) included ethnographic observations at each health centre (over 12–14 weeks), in-depth interviews with health workers and stakeholders (n = 20), and focus group discussions with health workers (n = 6). Results The results suggest that the intervention did facilitate improvement in data quality, but through unexpected mechanisms. The CI intervention was implemented as planned, but the PDSA cycles were driven largely by the CI mentor, not the health workers. In this context, characterized by a rigid hierarchy within the health system of limited culture of self-reflection and inadequate training and supervision, CI became an effective form of high-quality training with frequent supervisory visits. Health workers appeared motivated to improve data collection habits by their loyalty to the CI mentor and the potential for economic benefits, rather than a desire for self-improvement. Conclusions CI is a promising method of quality improvement and could have a positive impact on malaria surveillance data. However, successful scale-up of CI in similar settings may require deployment of highly skilled mentors. Further research, focusing on the effectiveness of ‘real world’ mentors using robust study designs, will be required to determine whether CI can be translated effectively and sustainably to low-resource settings.

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