scholarly journals Changes to the sample design and weighting methods of a public health surveillance system to also include persons not receiving HIV medical care

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243351
Author(s):  
Christopher H. Johnson ◽  
Linda Beer ◽  
R. Lee Harding ◽  
Ronaldo Iachan ◽  
Davia Moyse ◽  
...  

Objectives The Medical Monitoring Project (MMP) is a public health surveillance system that provides representative estimates of the experiences and behaviors of adults with diagnosed HIV in the United States. In 2015, the sample design and frame of MMP changed from a system that only included HIV patients to one that captures the experiences of persons receiving and not receiving HIV care. We describe methods investigated for calculating survey weights, the approach chosen, and the benefits of using a dynamic surveillance registry as a sampling frame. Methods MMP samples adults with diagnosed HIV from the National HIV Surveillance System, the HIV case surveillance registry for the United States. In the methodological study presented in this manuscript, we compared methods that account for sample design and nonresponse, including weighting class adjustment vs. propensity weighting and a single-stage nonresponse adjustment vs. sequential adjustments for noncontact and nonresponse. We investigated how best to adjust for non-coverage using surveillance data to post-stratify estimates. Results After assessing these methods, we chose as our preferred procedure weighting class adjustments and a single-stage nonresponse adjustment. Classes were constructed using variables associated with respondents’ characteristics and important survey outcomes, chief among them laboratory results available from surveillance that served as a proxy for medical care. Conclusions MMPs weighting procedures reduced sample bias by leveraging auxiliary information on medical care available from the surveillance registry sampling frame. Expanding MMPs population of focus provides important information on characteristics of persons with diagnosed HIV that complement the information provided by the surveillance registry. MMP methods can be applied to other disease registries or population-monitoring systems when more detailed information is needed for a population, with the detailed information obtained efficiently from a representative sample of the population covered by the registry.

2021 ◽  
pp. e1-e7
Author(s):  
Randall L. Sell ◽  
Elise I. Krims

Public health surveillance can have profound impacts on the health of populations, with COVID-19 surveillance offering an illuminating example. Surveillance surrounding COVID-19 testing, confirmed cases, and deaths has provided essential information to public health professionals about how to minimize morbidity and mortality. In the United States, surveillance has also pointed out how populations, on the basis of geography, age, and race and ethnicity, are being impacted disproportionately, allowing targeted intervention and evaluation. However, COVID-19 surveillance has also highlighted how the public health surveillance system fails some communities, including sexual and gender minorities. This failure has come about because of the haphazard and disorganized way disease reporting data are collected, analyzed, and reported in the United States, and the structural homophobia, transphobia, and biphobia acting within these systems. We provide recommendations for addressing these concerns after examining experiences collecting race data in COVID-19 surveillance and attempts in Pennsylvania and California to incorporate sexual orientation and gender identity variables into their pandemic surveillance efforts. (Am J Public Health. Published online ahead of print June 10, 2021: e1–e7. https://doi.org/10.2105/AJPH.2021.3062727 )


2020 ◽  
Vol 47 (6) ◽  
pp. 845-849
Author(s):  
Barbara Baquero ◽  
Carmen Gonzalez ◽  
Magaly Ramirez ◽  
Erica Chavez Santos ◽  
India J. Ornelas

The COVID-19 pandemic has exposed, and intensified, health inequities faced by Latinx in the United States. Washington was one of the first U.S. states to report cases of COVID-19. Public health surveillance shows that 31% of Washington cases are Latinx, despite being only 13% of the state population. Unjust policies related to immigration, labor, housing, transportation, and education have contributed to both past and existing inequities. Approximately 20% of Latinx are uninsured, leading to delays in testing and medical care for COVID-19, and early reports indicated critical shortages in professional interpreters and multilingual telehealth options. Washington State is taking action to address some of these inequities. Applying a health equity framework, we describe key factors contributing to COVID-19–related health inequities among Latinx populations, and how Washington State has aimed to address these inequities. We draw on these experiences to make recommendations for other Latinx communities experiencing COVID-19 disparities.


2021 ◽  
Vol 40 (1) ◽  
pp. 61-79
Author(s):  
Carmela Alcántara ◽  
Shakira F. Suglia ◽  
Irene Perez Ibarra ◽  
A. Louise Falzon ◽  
Elliot McCullough ◽  
...  

Author(s):  
Noelle M. Cocoros ◽  
Candace C. Fuller ◽  
Sruthi Adimadhyam ◽  
Robert Ball ◽  
Jeffrey S. Brown ◽  
...  

2017 ◽  
Vol 133 (1) ◽  
pp. 45-54 ◽  
Author(s):  
Alfonso Rodriguez-Lainz ◽  
Mariana McDonald ◽  
Maureen Fonseca-Ford ◽  
Ana Penman-Aguilar ◽  
Stephen H. Waterman ◽  
...  

Objective: Despite increasing diversity in the US population, substantial gaps in collecting data on race, ethnicity, primary language, and nativity indicators persist in public health surveillance and monitoring systems. In addition, few systems provide questionnaires in foreign languages for inclusion of non-English speakers. We assessed (1) the extent of data collected on race, ethnicity, primary language, and nativity indicators (ie, place of birth, immigration status, and years in the United States) and (2) the use of data-collection instruments in non-English languages among Centers for Disease Control and Prevention (CDC)–supported public health surveillance and monitoring systems in the United States. Methods: We identified CDC-supported surveillance and health monitoring systems in place from 2010 through 2013 by searching CDC websites and other federal websites. For each system, we assessed its website, documentation, and publications for evidence of the variables of interest and use of data-collection instruments in non-English languages. We requested missing information from CDC program officials, as needed. Results: Of 125 data systems, 100 (80%) collected data on race and ethnicity, 2 more collected data on ethnicity but not race, 26 (21%) collected data on racial/ethnic subcategories, 40 (32%) collected data on place of birth, 21 (17%) collected data on years in the United States, 14 (11%) collected data on immigration status, 13 (10%) collected data on primary language, and 29 (23%) used non-English data-collection instruments. Population-based surveys and disease registries more often collected data on detailed variables than did case-based, administrative, and multiple-source systems. Conclusions: More complete and accurate data on race, ethnicity, primary language, and nativity can improve the quality, representativeness, and usefulness of public health surveillance and monitoring systems to plan and evaluate targeted public health interventions to eliminate health disparities.


2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Rhonda A. Lizewski ◽  
Howard Burkom ◽  
Joseph Lombardo ◽  
Christopher Cuellar ◽  
Yevgeniy Elbert ◽  
...  

While other surveillance systems may only use death and admissions as severity indicators, these serious events may overshadow the more subtle severity signals based on appointment type, disposition from an outpatient setting, and whether that patient had to return for care if they their condition has not improved.  This abstract discusses how these additional data fields were utilized in a fusion model to improve the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE).


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