Last data update: Jun 20, 2025. (Total: 49421 publications since 2009)
Records 1-5 (of 5 Records) |
Query Trace: Jacobson EU[original query] |
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Assessing the impact of COVID-19 on HIV outcomes in the United States: A modeling study
Viguerie A , Jacobson EU , Hicks KA , Bates L , Carrico J , Honeycutt A , Lyles C , Farnham PG . Sex Transm Dis 2024 BACKGROUND: The COVID-19 pandemic impacted sexual behaviors and the HIV continuum-of-care in the United States, reducing HIV testing and diagnosis, and use of pre-exposure prophylaxis (PrEP) and antiretroviral therapy (ART). We aim to understand the future implications of these effects through a modeling study. METHODS: We first ran our compartmental model of HIV transmission in the US accounting for pandemic-related short-term changes in transmission behavior and HIV prevention and care provision in 2020-2021 only. We then ran a comparison scenario that did not apply pandemic effects but assumed a continuation of past HIV prevention and care trends. We compared results from the two scenarios through 2024. RESULTS: HIV incidence was 4·4% lower in 2020-21 for the pandemic scenario compared with the no-pandemic scenario due to reduced levels of transmission behavior, despite reductions in HIV prevention and care caused by the pandemic. However, reduced care led to less viral load suppression among people with HIV (PWH) in 2020 and, in turn, our model resulted in a slightly greater incidence of 2·0% from 2022-24 in the COVID-19 scenario, as compared to the non-COVID scenario. DISCUSSION: Disruptions in HIV prevention and care services during COVID-19 may lead to somewhat higher post-pandemic HIV incidence, than assuming pre-pandemic trends in HIV care and prevention continued. These results underscore the importance of continuing to increase HIV prevention and care efforts in the coming years. |
Optimizing HIV prevention efforts to achieve EHE incidence targets
Jacobson EU , Hicks KA , Carrico J , Purcell DW , Green TA , Mermin JH , Farnham PG . J Acquir Immune Defic Syndr 2022 89 (4) 374-380 BACKGROUND: A goal of the US Department of Health and Human Services' Ending the HIV Epidemic (EHE) in the United States initiative is to reduce the annual number of incident HIV infections in the United States by 75% within 5 years and by 90% within 10 years. We developed a resource allocation analysis to understand how these goals might be met. METHODS: We estimated the current annual societal funding [$2.8 billion (B)/yr] for 14 interventions to prevent HIV and facilitate treatment of infected persons. These interventions included HIV testing for different transmission groups, HIV care continuum interventions, pre-exposure prophylaxis, and syringe services programs. We developed scenarios optimizing or reallocating this funding to minimize new infections, and we analyzed the impact of additional EHE funding over the period 2021-2030. RESULTS: With constant current annual societal funding of $2.8 B/yr for 10 years starting in 2021, we estimated the annual incidence of 36,000 new cases in 2030. When we added annual EHE funding of $500 million (M)/yr for 2021-2022, $1.5 B/yr for 2023-2025, and $2.5 B/yr for 2026-2030, the annual incidence of infections decreased to 7600 cases (no optimization), 2900 cases (optimization beginning in 2026), and 2200 cases (optimization beginning in 2023) in 2030. CONCLUSIONS: Even without optimization, significant increases in resources could lead to an 80% decrease in the annual HIV incidence in 10 years. However, to reach both EHE targets, optimization of prevention funding early in the EHE period is necessary. Implementing these efficient allocations would require flexibility of funding across agencies, which might be difficult to achieve. |
Optimal allocation of societal HIV prevention resources to reduce HIV incidence in the United States
Sansom SL , Hicks KA , Carrico J , Jacobson EU , Shrestha RK , Green TA , Purcell DW . Am J Public Health 2020 111 (1) e1-e8 Objectives. To optimize combined public and private spending on HIV prevention to achieve maximum reductions in incidence.Methods. We used a national HIV model to estimate new infections from 2018 to 2027 in the United States. We estimated current spending on HIV screening, interventions that move persons with diagnosed HIV along the HIV care continuum, pre-exposure prophylaxis, and syringe services programs. We compared the current funding allocation with 2 optimal scenarios: (1) a limited-reach scenario with expanded efforts to serve eligible persons and (2) an ideal, unlimited-reach scenario in which all eligible persons could be served.Results. A continuation of the current allocation projects 331 000 new HIV cases over the next 10 years. The limited-reach scenario reduces that number by 69%, and the unlimited reach scenario by 94%. The most efficient funding allocations resulted in prompt diagnosis and sustained viral suppression through improved screening of high-risk persons and treatment adherence support for those infected.Conclusions. Optimal allocations of public and private funds for HIV prevention can achieve substantial reductions in new infections. Achieving reductions of more than 90% under current funding will require that virtually all infected receive sustained treatment. (Am J Public Health. Published online ahead of print November 19, 2020: e1-e8. https://doi.org/10.2105/AJPH.2020.305965). |
Unintended costs and consequences of school closures implemented in preparation for Hurricane Isaac in Harrison County School District, Mississippi, August-September 2012
Zheteyeva Y , Rainey JJ , Gao H , Jacobson EU , Adhikari BB , Shi J , Mpofu JJ , Bhavnani D , Dobbs T , Uzicanin A . PLoS One 2017 12 (11) e0184326 INTRODUCTION: School closures, while an effective measure against the spread of disease during a pandemic, may carry unintended social and economic consequences for students and families. We evaluated these costs and consequences following a 4-day school closure in Mississippi's Harrison County School District (HCSD). METHODS: In a survey of all households with students enrolled in HCSD, we collected information on difficulties related to the school closure, including interruption of employment and pay, loss of access to subsidized school meals, and arrangement of alternative childcare. We analyzed this information in the context of certain demographic characteristics of the survey respondents and households, such as race, level of education, and income. We also estimated the average number of lost work days and documented the childcare alternatives chosen by households affected by the school closure. RESULTS: We received 2,229 (28.4%) completed surveys from an estimated 7,851 households eligible to participate. About half (1,082 [48.5%]) of the households experienced at least some difficulty during the closure, primarily in three areas: uncertainty about duration of the closure, lost income, and the effort of arranging alternate childcare. Adults working outside the home, particularly the major wage earner in the household, were more likely to suffer lost income while schools were closed, an effect mitigated by paid leave benefits. Difficulty arranging childcare was reported most frequently by respondents with lower levels of education and households with younger children. Beyond the top three concerns expressed by households in HCSD, the survey also shed light on the issue of food insecurity when subsidized school meals are not available. Reported by 17.9% of households participating in the subsidized school lunch program, difficulty providing meals during the closure was associated with higher numbers of dependent children, selection of "other" as the race of the household respondent, and lower levels of education. CONCLUSION: To help prevent undue financial hardship in families of school children, public health authorities and school administrators should provide recommendations for childcare alternatives and paid leave or remote work options during prolonged school closures, particularly to households in which all adults work outside of the home. |
Modeling in real time during the Ebola response
Meltzer MI , Santibanez S , Fischer LS , Merlin TL , Adhikari BB , Atkins CY , Campbell C , Fung IC , Gambhir M , Gift T , Greening B , Gu W , Jacobson EU , Kahn EB , Carias C , Nerlander L , Rainisch G , Shankar M , Wong K , Washington ML . MMWR Suppl 2016 65 (3) 85-9 To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html). |
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