Estimating hepatitis C prevalence in New York City using surveillance data, a spreadsheet model, and simulations /
Estimating the prevalence of chronic hepatitis C virus infection is essential for setting screening and treatment targets and for monitoring progress toward elimination. Others have used population health surveys to estimate hepatitis C prevalence. Our case study describes why we selected a differen...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
London :
SAGE Publications Ltd,
2020.
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| Series: | SAGE Research Methods Cases: Medicine and Health.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | Estimating the prevalence of chronic hepatitis C virus infection is essential for setting screening and treatment targets and for monitoring progress toward elimination. Others have used population health surveys to estimate hepatitis C prevalence. Our case study describes why we selected a different foundational data source--public health surveillance data--and how we chose and applied a spreadsheet modeling method for combining surveillance data with other inputs to estimate hepatitis C prevalence with 95% certainty levels for New York City in 2015. We identified inputs considered to be known without error (i.e., number of unique people diagnosed with hepatitis C who were alive as of 2015 and with no report of negative RNA) and uncertain inputs (i.e., percentages of infected persons who had spontaneously cleared the virus; had been cured pre-2014 by treatment with interferon before highly effective, direct-acting antiviral medications became widely available; and were undiagnosed). We constructed a spreadsheet model and used Oracle Crystal Ball, a Microsoft Excel add-in, to run simulations drawing from probability distributions for uncertain inputs. Formula errors were identified via colleague and peer review and corrected prepublication. Challenges included a large degree of uncertainty in the literature for one key input, an inability to produce very recent estimates (given data availability lags), and an inability to produce estimates stratified by demographic characteristics (given the lack of demographic data in some inputs). Other health departments with similar hepatitis C surveillance systems can apply these methods to estimate prevalence and allocate resources for screening, care, and cure. |
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| Physical Description: | 1 online resource. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781529725179 1529725178 |