Individual-Based Simulation Models of HIV Transmission: Reporting Quality and Recommendations

Background: Individual-based modeling is a growing technique in the HIV transmission and prevention literature, but insufficient attention has been paid to formally evaluate the quality of reporting in this field. We present reporting recommendations for individual-based models for HIV treatment and prevention, assess the quality of reporting in the existing literature, and comment on the contribution of this model type to HIV policy and prediction. Methods: We developed reporting recommendations for individual-based HIV transmission mathematical models, and through a systematic search, used them to evaluate the reporting in the existing literature. We identified papers that employed individual-based simulation models and were published in English prior to December 31, 2012. Articles were included if the models they employed simulated and tracked individuals, simulated HIV transmission between individuals in a particular population, and considered a particular treatment or prevention intervention. The papers were assessed with the reporting recommendations. Findings: Of 214 full text articles examined, 32 were included in the evaluation, representing 20 independent individual-based HIV treatment and prevention mathematical models. Manuscripts universally reported the objectives, context, and modeling conclusions in the context of the modeling assumptions and the model’s predictive capabilities, but the reporting of individual-based modeling methods, parameterization and calibration was variable. Six papers discussed the time step used and one discussed efforts to maintain internal validity in coding. Conclusion: Individual-based models represent detailed HIV transmission processes with the potential to contribute to inference and policy making for many different regions and populations. The rigor in reporting of assumptions, methods, and calibration of individual-based models focused on HIV transmission and prevention varies greatly. Higher standards for reporting of statistically rigorous calibration and model assumption testing need to be implemented to increase confidence in existing and future modeling results

Differences in health behaviors and health outcomes among non-Hispanic Whites and Arab Americans in a population-based survey in California

Abstract Background Few population-based studies of Arab American health behaviors and outcomes exist outside of Michigan. We aimed to provide prevalence estimates of health behaviors and outcomes for Arab Americans and compare them to non-Hispanic Whites in California. Methods We used data from the 2003–2016 California Health Interview Surveys. We determined Arab American ethnicity using an algorithm that considered place of birth of the respondent or parent and use of Arabic language at home. Survey-weighted frequencies, chi-squared statistics, and logistic regression analyses were used to compare Arab Americans and non-Hispanic Whites on socioeconomic indicators, health behaviors and health outcomes. Multivariable models were adjusted for age, education level, and insurance status. Results Arab Americans had higher prevalence of no insurance, living below the federal poverty level, and home ownership than non-Hispanic Whites despite high levels of education and low unemployment prevalence. Arab Americans had reduced odds of alcohol consumption (OR: 0.33, 95% CI: 0.24, 0.45), binge drinking (OR: 0.28, 95% CI: 0.19, 0.40), and suicidal ideation (OR: 0.41, 0.25, 0.66) when compared to non-Hispanic Whites in multivariable models. Arab Americans had decreased odds of hypertension (OR: 0.64, 95% CI: 0.50, 0.83) and increased odds of diabetes (OR: 2.03, 95% CI: 1.23, 3.34) when compared to non-Hispanic Whites in multivariable models. Conclusions Arab Americans in California participate in less risky health behaviors and have better health outcomes than non-Hispanic Whites, except with regards to diabetes. Future work aiming to understand the health of Arab Americans should allow for self-identification and less reliance on country of origin and language use at home for sample selection.https://deepblue.lib.umich.edu/bitstream/2027.42/152127/1/12889_2019_Article_7233.pd

The Health of Arab Americans in the United States: An Updated Comprehensive Literature Review

Background: Arab Americans are a historically understudied minority group in the United States and their health needs and risks have been poorly documented. We aim to provide an updated comprehensive review of the literature on Arab American physical and mental health and provide suggestions for future work in this field.Methods: A comprehensive review of the English language medical and public health literature published prior to 2017 identified through multiple database searches was conducted with search terms describing Arab Americans and health outcomes and behaviors. The literature was qualitatively summarized by health behavior (vaccination, tobacco use, drug and alcohol use, and physical activity), health outcome (diabetes, mental health, cardiovascular disease, cancer, women's, and child health), and populations at increased risk of poor health outcomes (adolescents and the elderly).Results: The majority of studies identified exploring Arab American health have been published since 2009 with an increase in the number of longitudinal and intervention studies done with this population. The majority of research is being undertaken among individuals living in ethnic enclaves due to the lack of an ethnic or racial identifier that may help identify Arab Americans from population-based studies. Studies highlight the conflicting evidence in the prevalence of diabetes and cardiovascular disease based on study sample, an increased understanding of cancer incidence and barriers to identification, and an increased level of knowledge regarding mental health and sexual health needs in the population. Information on health behaviors has also increased, with a better understanding of physical activity, alcohol and drug use, and vaccination.Conclusion: More research on Arab American health is needed to identify risks and needs of this marginalized population given the current social and political climate in the United States, especially with regard to acculturation status and immigrant generation status. We provide recommendations on approaches that may help improve our understanding of Arab American health

Development, Calibration and Performance of an HIV Transmission Model Incorporating Natural History and Behavioral Patterns: Application in South Africa

Understanding HIV transmission dynamics is critical to estimating the potential population-wide impact of HIV prevention and treatment interventions. We developed an individual-based simulation model of the heterosexual HIV epidemic in South Africa and linked it to the previously published Cost-Effectiveness of Preventing AIDS Complications (CEPAC) International Model, which simulates the natural history and treatment of HIV. In this new model, the CEPAC Dynamic Model (CDM), the probability of HIV transmission per sexual encounter between short-term, long-term and commercial sex worker partners depends upon the HIV RNA and disease stage of the infected partner, condom use, and the circumcision status of the uninfected male partner. We included behavioral, demographic and biological values in the CDM and calibrated to HIV prevalence in South Africa pre-antiretroviral therapy. Using a multi-step fitting procedure based on Bayesian melding methodology, we performed 264,225 simulations of the HIV epidemic in South Africa and identified 3,750 parameter sets that created an epidemic and had behavioral characteristics representative of a South African population pre-ART. Of these parameter sets, 564 contributed 90% of the likelihood weight to the fit, and closely reproduced the UNAIDS HIV prevalence curve in South Africa from 1990–2002. The calibration was sensitive to changes in the rate of formation of short-duration partnerships and to the partnership acquisition rate among high-risk individuals, both of which impacted concurrency. Runs that closely fit to historical HIV prevalence reflect diverse ranges for individual parameter values and predict a wide range of possible steady-state prevalence in the absence of interventions, illustrating the value of the calibration procedure and utility of the model for evaluating interventions. This model, which includes detailed behavioral patterns and HIV natural history, closely fits HIV prevalence estimates

Can the Heterosexual HIV Epidemic be Eliminated in South Africa Using Combination Prevention? A Modeling Analysis

Little is known about how combining efficacious HIV prevention interventions could lead to HIV elimination. We used an agent-based simulation model, the HIV Calibrated Dynamic Model (HIV-CDM), to assess the potential for HIV elimination in South Africa. We examined several scenarios (from continuation of current status quo to perfect targets) with differing combinations of male condoms, adult male circumcision, HIV testing, and early antiretroviral therapy (ART). We varied parameters including: proportion of adult males circumcised, frequency of condom use in sex acts, HIV test acceptance, linkage to care, ART initiation criteria, ART suppression rates, and loss to follow up. Maintaining current levels of combination prevention will lead to increasing HIV incidence and prevalence while the perfect combination scenario is projected to eliminate HIV on a 50-year time scale from 2013 to 2063. Perfecting testing and treatment, without changing condom use or circumcision rates, resulted in 89% incidence reduction but not elimination. Universal adult male circumcision alone resulted in a 21% incidence reduction within 20 years. Substantial decreases in HIV incidence are possible from sufficient uptake of both primary prevention and ART, but with continuation of the status quo, HIV elimination in South Africa is unlikely within a 50-year time scale

Inclusion of Middle Eastern and North African populations in diabetes clinical research

The need for diverse representation in clinical trials has recently been reinforced by the Food and Drug Administration\u27s (FDA) guidance for industry entitled, Diversity Plans to Improve Enrollment of Participants from Underrepresented Racial and Ethnic Populations in Clinical Trials. By ensuring inclusion of underrepresented racial and ethnic minority populations in clinical trials, results can be more generalizable and the safety and efficacy can be accurately assessed within the diverse U.S. population. Limitations exist in the interpretation and implementation of clinical trial results reported using the current racial and ethnic categories, as these standards do not reflect the true diversity of the U.S. population. This is particularly true for the Middle Eastern and North African (MENA) population, which is usually overlooked given the lack of an established category. Although the international MENA region demonstrates the highest prevalence of diabetes in the world at 12.2%, the actual prevalence among MENA individuals living in the U.S. may be hidden within the White category. Therefore, data on the MENA population should be disaggregated from data within the White category to not only unmask health disparities, but also to ensure adequate representation in clinical trials. This paper discusses the importance of appropriate representation and inclusion of the MENA population in diabetes clinical trials, which is a critical public health issue domestically and globally

Accounting for historical injustices in mathematical models of infectious disease transmission: An analytic overview

Differences in infectious disease risk, acquisition, and severity arise from intersectional systems of oppression and resulting historical injustices that shape individual behavior and circumstance. We define historical injustices as distinct events and policies that arise out of intersectional systems of oppression. We view historical injustices as a medium through which structural forces affect health both directly and indirectly, and are thus important to study in the context of infectious disease disparities. In this critical analysis we aim to highlight the importance of incorporating historical injustices into mathematical models of infectious disease transmission and provide context on the methodologies to do so. We offer two illustrations of elements of model building (i.e., parameterization, validation and calibration) that can allow for a better understanding of health disparities in infectious disease outcomes. Mathematical models that do not recognize the historical forces that underlie infectious disease dynamics inevitably lead to the individualization of our focus and the recommendation of untenable individual-behavioral prescriptions to address the burden of infectious disease

Understanding differences within ethnic group designation: comparing risk factors and health indicators between Iranian and Arab Americans in Northern California

Abstract Background The Middle Eastern and North African (MENA) ethnic group is a diverse group composed of two primary subsets in the United States: Iranian and Arab Americans. We aimed to compare health risk factors, chronic health conditions, and mental health conditions of Iranian and Arab American adults in Northern California. Methods We used cross-sectional electronic health record (EHR) data from a 2016 Northern California health plan study cohort to compare adults classified as Iranian or Arab American based on ethnicity, language, or surname. We produced age-standardized prevalence estimates of obesity, smoking, hyperlipidemia, prediabetes, diabetes, hypertension, depression, and anxiety for Iranian and Arab American men and women by age group (35–44, 45–64, and 65–84) and overall (35–84). We used generalized linear models to calculate prevalence ratios (PR) to compare Iranian and Arab American adults ages 35–84 on all health indicators. Results Compared to Arab Americans, Iranian Americans had a lower prevalence of obesity (PR: 0.77, 95% confidence interval, CI: 0.73, 0.82), current smoking (PR: 0.80, 95% CI: 0.73, 0.89), and ever smoking (PR: 0.95, 95% CI: 0.91, 0.99), but a higher prevalence of hyperlipidemia (PR: 1.09, 95% CI: 1.06, 1.12), prediabetes (PR: 1.12, 95% CI: 1.09, 1.16), depression (PR; 1.41, 95% CI: 1.30, 1.52), and anxiety (PR: 1.52, 95% CI: 1.42, 1.63). Similar patterns were observed for men and women. Conclusion This work supports the need to collect granular data on race and ethnicity within the MENA ethnic group to improve identification in clinical care settings and population health reporting to better address the physical and mental health needs of different MENA subgroups.http://deepblue.lib.umich.edu/bitstream/2027.42/173496/1/12889_2021_Article_11121.pd