Last data update: Jan 27, 2025. (Total: 48650 publications since 2009)
Records 1-30 (of 56 Records) |
Query Trace: Cramer E[original query] |
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State-level trends in access to Medicaid family planning services, 2008-2023
Williams AM , Saldarriaga EM , Cramer R . Health Serv Res 2024 OBJECTIVE: To characterize the landscape of policies that determine eligibility for family planning services through Medicaid programs and describe trends in eligibility and its determinants over time. DATA SOURCES AND STUDY SETTING: Secondary data were collected for all states in the United States for the years 2008 through 2023. Data on economic and demographic characteristics came from the American Community Survey (ACS). STUDY DESIGN: Our descriptive study characterized state adoptions of Medicaid family planning section 1115 waivers and state plan amendments (SPA) and their eligibility criteria. We then estimated the proportion of women aged 19-44 years who were eligible for family planning services through Medicaid and identified the key determinants of changes in eligibility, by state and year. DATA COLLECTION/EXTRACTION METHODS: Information on state Medicaid policies was extracted from documentation on the Centers for Medicare & Medicaid Services website. When estimating the eligible population sizes, the denominator was women aged 19-44 years, the group most likely to be eligible for Medicaid family planning programs. Supplemental data on program enrollment or utilization were collected from states' websites and reports. PRINCIPAL FINDINGS: Though eligibility limits for family planning through Medicaid generally increased over time, the proportion of women aged 19-44 years eligible for at least limited benefits decreased from 45.0% in 2012 to 39.4% in 2022, largely because of increases in household income. Trends varied considerably across states and by eligibility pathway. Among women with incomes below the poverty level, the proportion who were not eligible for Medicaid family planning services decreased from 6.3% in 2013 to 1.5% in 2022. CONCLUSIONS: Our data demonstrated substantial geographic and temporal variation in eligibility for family planning services through Medicaid. We identified key drivers of eligibility changes that may have important implications for health services analyses of means-tested public programs. |
Title evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations
Mathis SM , Webber AE , León TM , Murray EL , Sun M , White LA , Brooks LC , Green A , Hu AJ , Rosenfeld R , Shemetov D , Tibshirani RJ , McDonald DJ , Kandula S , Pei S , Yaari R , Yamana TK , Shaman J , Agarwal P , Balusu S , Gururajan G , Kamarthi H , Prakash BA , Raman R , Zhao Z , Rodríguez A , Meiyappan A , Omar S , Baccam P , Gurung HL , Suchoski BT , Stage SA , Ajelli M , Kummer AG , Litvinova M , Ventura PC , Wadsworth S , Niemi J , Carcelen E , Hill AL , Loo SL , McKee CD , Sato K , Smith C , Truelove S , Jung SM , Lemaitre JC , Lessler J , McAndrew T , Ye W , Bosse N , Hlavacek WS , Lin YT , Mallela A , Gibson GC , Chen Y , Lamm SM , Lee J , Posner RG , Perofsky AC , Viboud C , Clemente L , Lu F , Meyer AG , Santillana M , Chinazzi M , Davis JT , Mu K , Pastore YPiontti A , Vespignani A , Xiong X , Ben-Nun M , Riley P , Turtle J , Hulme-Lowe C , Jessa S , Nagraj VP , Turner SD , Williams D , Basu A , Drake JM , Fox SJ , Suez E , Cojocaru MG , Thommes EW , Cramer EY , Gerding A , Stark A , Ray EL , Reich NG , Shandross L , Wattanachit N , Wang Y , Zorn MW , Aawar MA , Srivastava A , Meyers LA , Adiga A , Hurt B , Kaur G , Lewis BL , Marathe M , Venkatramanan S , Butler P , Farabow A , Ramakrishnan N , Muralidhar N , Reed C , Biggerstaff M , Borchering RK . Nat Commun 2024 15 (1) 6289 Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble is the 2(nd) most accurate model measured by WIS in 2021-22 and the 5(th) most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change. |
Findings from the first year of a federally funded, direct-to-consumer HIV self-test distribution program - United States, March 2023-March 2024
Sanchez T , MacGowan RJ , Hecht J , Keralis JM , Ackah-Toffey L , Bourbeau A , Dana R , Lilo EA , Downey RS , Getachew-Smith H , Hannah M , Valencia R , Krebs E , Pingel ES , Gayden JJ , Norelli J , Mason Z , Mahn J , Cramer N , Bole R , Sullivan P , Nwaohiri AN , Stryker JE , Kourtis AP , DiNenno EA , Fanfair RN , Mermin JH , Delaney KP . MMWR Morb Mortal Wkly Rep 2024 73 (24) 558-564 In September 2022, CDC funded a nationwide program, Together TakeMeHome (TTMH), to expand distribution of HIV self-tests (HIVSTs) directly to consumers by mail through an online ordering portal. To publicize the availability of HIVSTs to priority audiences, particularly those disproportionately affected by HIV, CDC promoted this program through established partnerships and tailored resources from its Let's Stop HIV Together social marketing campaign. The online portal launched March 14, 2023, and through March 13, 2024, distributed 443,813 tests to 219,360 persons. Among 169,623 persons who answered at least one question on a postorder questionnaire, 67.9% of respondents were from priority audiences, 24.1% had never previously received testing for HIV, and 24.8% had not received testing in the past year. Among the subset of participants who initiated a follow-up survey, 88.3% used an HIVST themselves, 27.1% gave away an HIVST, 11.7% accessed additional preventive services, and 1.9% reported a new positive HIVST result. Mailed HIVST distribution can quickly reach large numbers of persons who have never received testing for HIV or have not received testing as often as is recommended. TTMH can help to achieve the goal of diagnosing HIV as early as possible and provides a path to other HIV prevention and care services. Clinicians, community organizations, and public health officials should be aware of HIVST programs, initiate discussions about HIV testing conducted outside their clinics or offices, and initiate follow-up services for persons who report a positive or negative HIVST result. |
A longitudinal analysis of COVID-19 prevention strategies implemented among US K-12 public schools during the 2021-2022 school year
Conklin S , McConnell L , Murray C , Pampati S , Rasberry CN , Stephens R , Rose I , Barrios LC , Cramer NK , Lee S . Ann Epidemiol 2024 PURPOSE: Examine how school-based COVID-19 prevention strategy implementation varied over time, including by local characteristics. METHODS: School administrators (n=335) from a nationally representative sample of K-12 public schools completed four surveys assessing COVID-19 prevention strategies at two-month intervals between October 2021 and June 2022. We calculated weighted prevalence estimates by survey wave. Generalized estimating equations (GEE) were used to model longitudinal changes in strategy implementation, accounting for school and county covariates. RESULTS: Opening doors/windows, daily cleaning, and diagnostic testing were reported by ≥50% of schools at each survey wave. Several strategies were consistently implemented across the 2021-2022 school year (i.e., daily cleaning, opening doors and windows, diagnostic testing) while other strategies increased initially and then declined (i.e., contact tracing, screening testing, on-campus vaccination) or declined consistently throughout the school year (i.e., mask requirement, classroom distancing, quarantine). Although longitudinal changes in strategy implementation did not vary by school characteristics, strategy implementation varied by urban-rural classification and school level throughout the school year. CONCLUSIONS: Strategies that were consistently implemented throughout the school year were also reported by a majority of schools, speaking toward their feasibility for school-based infection control and prevention and potential utility in future public health emergencies. |
Challenges of COVID-19 case forecasting in the US, 2020-2021
Lopez VK , Cramer EY , Pagano R , Drake JM , O'Dea EB , Adee M , Ayer T , Chhatwal J , Dalgic OO , Ladd MA , Linas BP , Mueller PP , Xiao J , Bracher J , Castro Rivadeneira AJ , Gerding A , Gneiting T , Huang Y , Jayawardena D , Kanji AH , Le K , Mühlemann A , Niemi J , Ray EL , Stark A , Wang Y , Wattanachit N , Zorn MW , Pei S , Shaman J , Yamana TK , Tarasewicz SR , Wilson DJ , Baccam S , Gurung H , Stage S , Suchoski B , Gao L , Gu Z , Kim M , Li X , Wang G , Wang L , Wang Y , Yu S , Gardner L , Jindal S , Marshall M , Nixon K , Dent J , Hill AL , Kaminsky J , Lee EC , Lemaitre JC , Lessler J , Smith CP , Truelove S , Kinsey M , Mullany LC , Rainwater-Lovett K , Shin L , Tallaksen K , Wilson S , Karlen D , Castro L , Fairchild G , Michaud I , Osthus D , Bian J , Cao W , Gao Z , Lavista Ferres J , Li C , Liu TY , Xie X , Zhang S , Zheng S , Chinazzi M , Davis JT , Mu K , Pastore YPiontti A , Vespignani A , Xiong X , Walraven R , Chen J , Gu Q , Wang L , Xu P , Zhang W , Zou D , Gibson GC , Sheldon D , Srivastava A , Adiga A , Hurt B , Kaur G , Lewis B , Marathe M , Peddireddy AS , Porebski P , Venkatramanan S , Wang L , Prasad PV , Walker JW , Webber AE , Slayton RB , Biggerstaff M , Reich NG , Johansson MA . PLoS Comput Biol 2024 20 (5) e1011200 During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making. |
The United States COVID-19 Forecast Hub dataset (preprint)
Cramer EY , Huang Y , Wang Y , Ray EL , Cornell M , Bracher J , Brennen A , Rivadeneira AJC , Gerding A , House K , Jayawardena D , Kanji AH , Khandelwal A , Le K , Mody V , Mody V , Niemi J , Stark A , Shah A , Wattanchit N , Zorn MW , Reich NG , US COVID-19 Forecast Hub Consortium , Lopez VK , Walker JW , Slayton RB , Johansson MA , Biggerstaff M . medRxiv 2021 2021.11.04.21265886 ![]() Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work. Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below: AIpert-pwllnod: Natural Sciences and Engineering Research Council of Canada; Caltech-CS156: Gary Clinard Innovation Fund; CEID-Walk: University of Georgia; CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook; COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health; Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information & Data Science Pilot Project; Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation; CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation; DDS-NBDS: NSF III-1812699; epiforecasts-ensemble1: Wellcome Trust (210758/Z/18/Z) FDANIHASU: supported by the Intramural Research Program of the NIH/NIDDK; GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowment, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. & Charlene Zalesky, and Claudia & Paul Raines, CDC MInD-Healthcare U01CK000531-Supplement; IHME: This work was supported by the Bill & Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096); Imperial-ensemble1: SB acknowledges funding from the Wellcome Trust (219415); Institute of Business Forecasting: IBF; IowaStateLW-STEM: NSF DMS-1916204, Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics; IUPUI CIS: NSF; JHU_CSSE-DECOM: JHU CSSE: National Science Foundation (NSF) RAPID Real-time Forecasting of COVID-19 risk in the USA. 2021-2022. Award ID: 2108526. National Science Foundation (NSF) RAPID Development of an interactive web-based dashboard to track COVID-19 in real-time. 2020. Award ID: 2028604; JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers for Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, & Infectious Disease Initiative (26798 Seed Grant); JHU_UNC_GAS-StatMechP ol: NIH NIGMS: R01GM140564; JHUAPL-Bucky: US Dept of Health and Human Services; KITmetricslab-select_ensemble: Daniel Wolffram gratefully acknowledges support by the Klaus Tschira Foundation; LANL-GrowthRate: LANL LDRD 20200700ER; MIT-Cassandra: MIT Quest for Intelligence; MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01; CA NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE); NotreDame-FRED: NSF RAPID DEB 2027718; NotreDame-mobility: NSF RAPID DEB 2027718; PSI-DRAFT: NSF RAPID Grant # 2031536; QJHong-Encounter: NSF DMR-2001411 and DMR-1835939; SDSC_ISG-TrendModel: The development of the dashboard was partly funded by the Fondation Privee des Hopitaux Universitaires de Geneve; UA-EpiCovDA: NSF RAPID Grant # 2028401; UChicagoCHATTOPADHYAY-UnIT: Defense Advanced Research Projects Agency (DARPA) #HR00111890043/P00004 (I. Chattopadhyay, University of Chicago); UCSB-ACTS: NSF RAPID IIS 2029626; UCSD_NEU-DeepGLEAM: Google Faculty Award, W31P4Q-21-C-0014; UMass-MechBayes: NIGMS #R35GM119582, NSF #1749854, NIGMS #R35GM119582; UMich-RidgeTfReg: This project is funded by the University of Michigan Physics Department and the University of Michigan Office of Research; UVA-Ensemble: National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and Virginia Dept of Health Grant VDH-21-501-0141; Wadnwani_AI-BayesOpt: This study is made possible by the generous support of the American People through the United States Agency for International Development (USAID). The work described in this article was implemented under the TRACETB Project, managed by WIAI under the terms of Cooperative Agreement Number 72038620CA00006. The contents of this manuscript are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government; WalmartLabsML-LogForecasting: Team acknowledges Walmart to support this study Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced are available online at https://github.com/reichlab/covid19-forecast-hub https://github.com/reichlab/covid19-forecast-hub |
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US (preprint)
Cramer EY , Ray EL , Lopez VK , Bracher J , Brennen A , Castro Rivadeneira AJ , Gerding A , Gneiting T , House KH , Huang Y , Jayawardena D , Kanji AH , Khandelwal A , Le K , Mühlemann A , Niemi J , Shah A , Stark A , Wang Y , Wattanachit N , Zorn MW , Gu Y , Jain S , Bannur N , Deva A , Kulkarni M , Merugu S , Raval A , Shingi S , Tiwari A , White J , Abernethy NF , Woody S , Dahan M , Fox S , Gaither K , Lachmann M , Meyers LA , Scott JG , Tec M , Srivastava A , George GE , Cegan JC , Dettwiller ID , England WP , Farthing MW , Hunter RH , Lafferty B , Linkov I , Mayo ML , Parno MD , Rowland MA , Trump BD , Zhang-James Y , Chen S , Faraone SV , Hess J , Morley CP , Salekin A , Wang D , Corsetti SM , Baer TM , Eisenberg MC , Falb K , Huang Y , Martin ET , McCauley E , Myers RL , Schwarz T , Sheldon D , Gibson GC , Yu R , Gao L , Ma Y , Wu D , Yan X , Jin X , Wang YX , Chen Y , Guo L , Zhao Y , Gu Q , Chen J , Wang L , Xu P , Zhang W , Zou D , Biegel H , Lega J , McConnell S , Nagraj VP , Guertin SL , Hulme-Lowe C , Turner SD , Shi Y , Ban X , Walraven R , Hong QJ , Kong S , van de Walle A , Turtle JA , Ben-Nun M , Riley S , Riley P , Koyluoglu U , DesRoches D , Forli P , Hamory B , Kyriakides C , Leis H , Milliken J , Moloney M , Morgan J , Nirgudkar N , Ozcan G , Piwonka N , Ravi M , Schrader C , Shakhnovich E , Siegel D , Spatz R , Stiefeling C , Wilkinson B , Wong A , Cavany S , España G , Moore S , Oidtman R , Perkins A , Kraus D , Kraus A , Gao Z , Bian J , Cao W , Lavista Ferres J , Li C , Liu TY , Xie X , Zhang S , Zheng S , Vespignani A , Chinazzi M , Davis JT , Mu K , Pastore YPiontti A , Xiong X , Zheng A , Baek J , Farias V , Georgescu A , Levi R , Sinha D , Wilde J , Perakis G , Bennouna MA , Nze-Ndong D , Singhvi D , Spantidakis I , Thayaparan L , Tsiourvas A , Sarker A , Jadbabaie A , Shah D , Della Penna N , Celi LA , Sundar S , Wolfinger R , Osthus D , Castro L , Fairchild G , Michaud I , Karlen D , Kinsey M , Mullany LC , Rainwater-Lovett K , Shin L , Tallaksen K , Wilson S , Lee EC , Dent J , Grantz KH , Hill AL , Kaminsky J , Kaminsky K , Keegan LT , Lauer SA , Lemaitre JC , Lessler J , Meredith HR , Perez-Saez J , Shah S , Smith CP , Truelove SA , Wills J , Marshall M , Gardner L , Nixon K , Burant JC , Wang L , Gao L , Gu Z , Kim M , Li X , Wang G , Wang Y , Yu S , Reiner RC , Barber R , Gakidou E , Hay SI , Lim S , Murray C , Pigott D , Gurung HL , Baccam P , Stage SA , Suchoski BT , Prakash BA , Adhikari B , Cui J , Rodríguez A , Tabassum A , Xie J , Keskinocak P , Asplund J , Baxter A , Oruc BE , Serban N , Arik SO , Dusenberry M , Epshteyn A , Kanal E , Le LT , Li CL , Pfister T , Sava D , Sinha R , Tsai T , Yoder N , Yoon J , Zhang L , Abbott S , Bosse NI , Funk S , Hellewell J , Meakin SR , Sherratt K , Zhou M , Kalantari R , Yamana TK , Pei S , Shaman J , Li ML , Bertsimas D , Skali Lami O , Soni S , Tazi Bouardi H , Ayer T , Adee M , Chhatwal J , Dalgic OO , Ladd MA , Linas BP , Mueller P , Xiao J , Wang Y , Wang Q , Xie S , Zeng D , Green A , Bien J , Brooks L , Hu AJ , Jahja M , McDonald D , Narasimhan B , Politsch C , Rajanala S , Rumack A , Simon N , Tibshirani RJ , Tibshirani R , Ventura V , Wasserman L , O'Dea EB , Drake JM , Pagano R , Tran QT , Ho LST , Huynh H , Walker JW , Slayton RB , Johansson MA , Biggerstaff M , Reich NG . medRxiv 2021 2021.02.03.21250974 ![]() Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information& Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. & Charlene Zalesky, and Claudia & Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill & Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, & Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44 |
State policies relevant to disease intervention specialists in the United States
Cramer R , Ludovic JA . Sex Transm Dis 2023 50 S14-s17 BACKGROUND: The functions of disease intervention specialists (DIS) represent core infectious disease control practices and have legal foundations in the United States. Although important for state and local health departments to understand this authority, these policies have not been systematically collected and analyzed. We analyzed the authority for investigation of sexually transmitted infections (STIs) across all 50 US states and the District of Columbia. METHODS: In January 2022, we collected state policies addressing the investigation of STIs using a legal research database. We coded these policies into a database on variables of interest: (1) whether the policy authorized/required investigation, (2) what type of infection triggers an investigation, (3) and the entity who is authorized/required to perform the investigation. RESULTS: All 50 US states and District of Columbia explicitly authorize/require investigation of cases of STI. Of these jurisdictions, 62.7% require investigations, 41% authorize investigations, and 3.9% both authorize and require investigations. Sixty-seven percent authorize/require investigations for cases of communicable disease (inclusive of an STI), 45.1% authorize/require investigations for cases of STIs generally, and 3.9% authorize/require investigations for cases of a specific STI. Eighty-two percent of jurisdictions authorize/require the state to investigate, 62.7% authorize/require local governments to investigate, and 39.2% authorize/require investigations by both state and local governments. CONCLUSIONS: State laws that establish authority or duties regarding the investigation of STIs differ across states. It may be useful for state and local health departments to examine these policies relative to the morbidity of their jurisdiction and their STI prevention priorities. |
The United States COVID-19 Forecast Hub dataset.
Cramer EY , Huang Y , Wang Y , Ray EL , Cornell M , Bracher J , Brennen A , Rivadeneira AJC , Gerding A , House K , Jayawardena D , Kanji AH , Khandelwal A , Le K , Mody V , Mody V , Niemi J , Stark A , Shah A , Wattanchit N , Zorn MW , Reich NG , US COVID-19 Forecast Hub Consortium , Lopez VK , Walker JW , Slayton RB , Johansson MA , Biggerstaff M . Sci Data 2022 9 (1) 462 ![]() ![]() Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages. |
Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States.
Ray EL , Brooks LC , Bien J , Biggerstaff M , Bosse NI , Bracher J , Cramer EY , Funk S , Gerding A , Johansson MA , Rumack A , Wang Y , Zorn M , Tibshirani RJ , Reich NG . Int J Forecast 2022 The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term burden of COVID-19 in the United States from many contributing teams. We study methods for building an ensemble that combines forecasts from these teams. These experiments have informed the ensemble methods used by the Hub. To be most useful to policy makers, ensemble forecasts must have stable performance in the presence of two key characteristics of the component forecasts: (1) occasional misalignment with the reported data, and (2) instability in the relative performance of component forecasters over time. Our results indicate that in the presence of these challenges, an untrained and robust approach to ensembling using an equally weighted median of all component forecasts is a good choice to support public health decision makers. In settings where some contributing forecasters have a stable record of good performance, trained ensembles that give those forecasters higher weight can also be helpful. |
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.
Cramer EY , Ray EL , Lopez VK , Bracher J , Brennen A , Castro Rivadeneira AJ , Gerding A , Gneiting T , House KH , Huang Y , Jayawardena D , Kanji AH , Khandelwal A , Le K , Mühlemann A , Niemi J , Shah A , Stark A , Wang Y , Wattanachit N , Zorn MW , Gu Y , Jain S , Bannur N , Deva A , Kulkarni M , Merugu S , Raval A , Shingi S , Tiwari A , White J , Abernethy NF , Woody S , Dahan M , Fox S , Gaither K , Lachmann M , Meyers LA , Scott JG , Tec M , Srivastava A , George GE , Cegan JC , Dettwiller ID , England WP , Farthing MW , Hunter RH , Lafferty B , Linkov I , Mayo ML , Parno MD , Rowland MA , Trump BD , Zhang-James Y , Chen S , Faraone SV , Hess J , Morley CP , Salekin A , Wang D , Corsetti SM , Baer TM , Eisenberg MC , Falb K , Huang Y , Martin ET , McCauley E , Myers RL , Schwarz T , Sheldon D , Gibson GC , Yu R , Gao L , Ma Y , Wu D , Yan X , Jin X , Wang YX , Chen Y , Guo L , Zhao Y , Gu Q , Chen J , Wang L , Xu P , Zhang W , Zou D , Biegel H , Lega J , McConnell S , Nagraj VP , Guertin SL , Hulme-Lowe C , Turner SD , Shi Y , Ban X , Walraven R , Hong QJ , Kong S , van de Walle A , Turtle JA , Ben-Nun M , Riley S , Riley P , Koyluoglu U , DesRoches D , Forli P , Hamory B , Kyriakides C , Leis H , Milliken J , Moloney M , Morgan J , Nirgudkar N , Ozcan G , Piwonka N , Ravi M , Schrader C , Shakhnovich E , Siegel D , Spatz R , Stiefeling C , Wilkinson B , Wong A , Cavany S , España G , Moore S , Oidtman R , Perkins A , Kraus D , Kraus A , Gao Z , Bian J , Cao W , Lavista Ferres J , Li C , Liu TY , Xie X , Zhang S , Zheng S , Vespignani A , Chinazzi M , Davis JT , Mu K , Pastore YPiontti A , Xiong X , Zheng A , Baek J , Farias V , Georgescu A , Levi R , Sinha D , Wilde J , Perakis G , Bennouna MA , Nze-Ndong D , Singhvi D , Spantidakis I , Thayaparan L , Tsiourvas A , Sarker A , Jadbabaie A , Shah D , Della Penna N , Celi LA , Sundar S , Wolfinger R , Osthus D , Castro L , Fairchild G , Michaud I , Karlen D , Kinsey M , Mullany LC , Rainwater-Lovett K , Shin L , Tallaksen K , Wilson S , Lee EC , Dent J , Grantz KH , Hill AL , Kaminsky J , Kaminsky K , Keegan LT , Lauer SA , Lemaitre JC , Lessler J , Meredith HR , Perez-Saez J , Shah S , Smith CP , Truelove SA , Wills J , Marshall M , Gardner L , Nixon K , Burant JC , Wang L , Gao L , Gu Z , Kim M , Li X , Wang G , Wang Y , Yu S , Reiner RC , Barber R , Gakidou E , Hay SI , Lim S , Murray C , Pigott D , Gurung HL , Baccam P , Stage SA , Suchoski BT , Prakash BA , Adhikari B , Cui J , Rodríguez A , Tabassum A , Xie J , Keskinocak P , Asplund J , Baxter A , Oruc BE , Serban N , Arik SO , Dusenberry M , Epshteyn A , Kanal E , Le LT , Li CL , Pfister T , Sava D , Sinha R , Tsai T , Yoder N , Yoon J , Zhang L , Abbott S , Bosse NI , Funk S , Hellewell J , Meakin SR , Sherratt K , Zhou M , Kalantari R , Yamana TK , Pei S , Shaman J , Li ML , Bertsimas D , Skali Lami O , Soni S , Tazi Bouardi H , Ayer T , Adee M , Chhatwal J , Dalgic OO , Ladd MA , Linas BP , Mueller P , Xiao J , Wang Y , Wang Q , Xie S , Zeng D , Green A , Bien J , Brooks L , Hu AJ , Jahja M , McDonald D , Narasimhan B , Politsch C , Rajanala S , Rumack A , Simon N , Tibshirani RJ , Tibshirani R , Ventura V , Wasserman L , O'Dea EB , Drake JM , Pagano R , Tran QT , Ho LST , Huynh H , Walker JW , Slayton RB , Johansson MA , Biggerstaff M , Reich NG . Proc Natl Acad Sci U S A 2022 119 (15) e2113561119 ![]() SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action. |
Characterizing financial sustainability of sexually transmitted disease clinics through insurance billing practices
Pearson WS , Chan PA , Cramer R , Gift TL . J Public Health Manag Pract 2021 28 (4) 358-365 CONTEXT: Sexually transmitted infections (STIs) continue to increase in the United States. Publicly funded sexually transmitted disease (STD) clinics provide important safety net services for communities at greater risk for STIs. However, creating financially sustainable models of STI care remains a challenge. OBJECTIVE: Characterization of clinic insurance billing practices and patient willingness to use insurance. DESIGN: Cross-sectional survey assessment of clinic administrators and patients. SETTING: Twenty-six STD clinics and 4138 patients attending these clinics in high STD morbidity metropolitan statistical areas in the United States. PARTICIPANTS: Clinic administrators and patients of these clinics. INTERVENTION: Survey assessment. MAIN OUTCOME MEASURE: Insurance billing practices of STD clinics and patient insurance status and willingness to use their insurance. RESULTS: Fifteen percent of clinics (4/26) indicated that they billed only Medicaid, 58% (15/26) billed both Medicaid and private insurance, 27% (7/26) did not bill for any health insurance, and none (0%) billed only private health insurance companies. Of 4138 patients surveyed, just more than one-half of patients (52.6%) were covered by some form of health insurance. More than one-half (57.2%) of all patients covered by health insurance indicated that they would be willing to use their health insurance for that visit. After adjusting for patient demographics and clinic characteristics, the patients covered by government insurance were 3 times as likely (odds ratio: 3.16; 95% confidence interval, 2.44-4.10) than patients covered by private insurance to be willing to use their insurance for their visit. CONCLUSION: Opportunities exist for sustainable STI services through the enhancement of billing practices in STD clinics. The STD clinics provide care to large numbers of individuals who are both insured and who are willing to use their insurance for their care. As Medicaid expansion continues across the country, efforts focused on improving reimbursement rates for Medicaid may improve financial sustainability of STD clinics. |
Increasing Access to HIV Testing Through Direct-to-Consumer HIV Self-Test Distribution - United States, March 31, 2020-March 30, 2021.
Hecht J , Sanchez T , Sullivan PS , DiNenno EA , Cramer N , Delaney KP . MMWR Morb Mortal Wkly Rep 2021 70 (38) 1322-1325 During 2019, approximately 34,800 new HIV infections occurred in the United States (1), and it is estimated that approximately 80% of HIV transmission occurs from persons who either do not know they have HIV infection or are not receiving regular care (2). Since 2006, CDC has recommended that persons who are disproportionately affected by HIV (including men who have sex with men [MSM]) should test for HIV at least annually (3,4). However, data from multiple sources indicate that these recommendations are not being fully implemented (5,6). TakeMeHome, a novel public-private partnership to deliver HIV self-testing kits to persons seeking HIV testing in the United States, was launched during March 2020 as home care options for testing became increasingly important during the COVID-19 pandemic. The initiation of the program coincided with the national COVID-19 Public Health Emergency declaration, issuance of stay-at-home orders, and other restrictions that led to disruption of traditional HIV testing services. During March 31, 2020-March 30, 2021, 17 state and local health departments participating in the program allowed residents of their jurisdictions to order test kits. Marketing for TakeMeHome focused on reaching gay, bisexual, and MSM through messages and embedded links in gay dating applications. Most participants in the program reported that they had either never tested for HIV (36%) or that they had last tested >1 year before receiving their self-test kit (56%). After receiving the self-test kit, >10% of respondents reported accessing additional prevention services. Health departments can increase options for HIV testing by distributing publicly funded self-test kits to persons without proximate access to clinic-based testing or who prefer to test at home. Increased and regular HIV testing among MSM will help meet annual testing goals. |
A New Call to Action to Combat an Old Nemesis: Addressing Rising Congenital Syphilis Rates in the United States
Machefsky AM , Loosier PS , Cramer R , Bowen VB , Kersh EN , Tao G , Gift TL , Hogben M , Carry M , Ludovic JA , Thorpe P , Bachmann LH . J Womens Health (Larchmt) 2021 30 (7) 920-926 Congenital syphilis (CS) is on the rise in the United States and is a growing public health concern. CS is an infection with Treponema pallidum in an infant or fetus, acquired via transplacental transmission when a pregnant woman has untreated or inadequately treated syphilis. Pregnant women with untreated syphilis are more likely to experience pregnancies complicated by stillbirth, prematurity, low birth weight, and early infant death, while their children can develop clinical manifestations of CS such as hepatosplenomegaly, bone abnormalities, developmental delays, and hearing loss. One of the ways CS can be prevented is by identifying and treating infected women during pregnancy with a benzathine penicillin G regimen that is both appropriate for the maternal stage of syphilis and initiated at least 30 days prior to delivery. In this article we discuss many of the challenges faced by both public health and healthcare systems with regards to this preventable infection, summarize missed opportunities for CS prevention, and provide practical solutions for future CS prevention strategies. |
Association of Children's Mode of School Instruction with Child and Parent Experiences and Well-Being During the COVID-19 Pandemic - COVID Experiences Survey, United States, October 8-November 13, 2020.
Verlenden JV , Pampati S , Rasberry CN , Liddon N , Hertz M , Kilmer G , Viox MH , Lee S , Cramer NK , Barrios LC , Ethier KA . MMWR Morb Mortal Wkly Rep 2021 70 (11) 369-376 In March 2020, efforts to slow transmission of SARS-CoV-2, the virus that causes COVID-19, resulted in widespread closures of school buildings, shifts to virtual educational models, modifications to school-based services, and disruptions in the educational experiences of school-aged children. Changes in modes of instruction have presented psychosocial stressors to children and parents that can increase risks to mental health and well-being and might exacerbate educational and health disparities (1,2). CDC examined differences in child and parent experiences and indicators of well-being according to children's mode of school instruction (i.e., in-person only [in-person], virtual-only [virtual], or combined virtual and in-person [combined]) using data from the COVID Experiences nationwide survey. During October 8-November 13, 2020, parents or legal guardians (parents) of children aged 5-12 years were surveyed using the NORC at the University of Chicago AmeriSpeak panel,* a probability-based panel designed to be representative of the U.S. household population. Among 1,290 respondents with a child enrolled in public or private school, 45.7% reported that their child received virtual instruction, 30.9% in-person instruction, and 23.4% combined instruction. For 11 of 17 stress and well-being indicators concerning child mental health and physical activity and parental emotional distress, findings were worse for parents of children receiving virtual or combined instruction than were those for parents of children receiving in-person instruction. Children not receiving in-person instruction and their parents might experience increased risk for negative mental, emotional, or physical health outcomes and might need additional support to mitigate pandemic effects. Community-wide actions to reduce COVID-19 incidence and support mitigation strategies in schools are critically important to support students' return to in-person learning. |
Addressing the STI epidemic through the Medicaid program: A roadmap for states and managed care organizations
Seiler N , Horton K , Pearson WS , Cramer R , Adil M , Bishop D , Heyison C . Public Health Rep 2021 137 (1) 5-10 Chlamydia, gonorrhea, and syphilis are all detectable and treatable, yet rates of these 3 bacterial sexually transmitted infections (STIs) are soaring in the United States. 1 If left untreated, both chlamydia and gonorrhea can lead to costly and burdensome complications, including pelvic inflammatory disease and infertility.2,3 Untreated primary syphilis can lead to severe sequelae including death, and congenital syphilis can lead to miscarriage, stillbirth, prematurity, low birthweight, and death.4,5 People who develop these complications because of untreated STIs have high medical costs throughout their lifetime.6,7 Although rates of chlamydia, gonorrhea, and syphilis have been rising among all racial/ethnic groups, African American and Latinx people have persistently higher burdens of infection than White people. 8 |
Differences in rapid increases in county-level COVID-19 incidence by implementation of statewide closures and mask mandates - United States, June 1-September 30, 2020.
Dasgupta S , Kassem AM , Sunshine G , Liu T , Rose C , Kang G , Silver R , Maddox BLP , Watson C , Howard-Williams M , Gakh M , McCord R , Weber R , Fletcher K , Musial T , Tynan MA , Hulkower R , Moreland A , Pepin D , Landsman L , Brown A , Gilchrist S , Clodfelter C , Williams M , Cramer R , Limeres A , Popoola A , Dugmeoglu S , Shelburne J , Jeong G , Rao CY . Ann Epidemiol 2021 57 46-53 BACKGROUND AND OBJECTIVE: Community mitigation strategies could help reduce COVID-19 incidence. In a national county-level analysis, we examined the probability of being identified as a county with rapidly increasing COVID-19 incidence (rapid riser identification) during the summer of 2020 by implementation of mitigation policies prior to the summer, overall and by urbanicity. METHODS: We analyzed county-level data on rapid riser identification during June 1-September 30, 2020 and statewide closures and statewide mask mandates starting March 19 (obtained from state government websites). Poisson regression models with robust standard error estimation were used to examine differences in the probability of rapid riser identification by implementation of mitigation policies (P-value<.05); associations were adjusted for county population size. RESULTS: Counties in states that closed for 0-59 days were more likely to become a rapid riser county than those that closed for >59 days, particularly in nonmetropolitan areas. The probability of becoming a rapid riser county was 43% lower among counties that had statewide mask mandates at reopening (adjusted prevalence ratio [aPR] = 0.57; 95% confidence intervals [CI] = 0.51-0.63); when stratified by urbanicity, associations were more pronounced in nonmetropolitan areas. CONCLUSIONS: These results underscore the potential value of community mitigation strategies in limiting the COVID-19 spread, especially in nonmetropolitan areas. |
Patterns of posttraumatic stress symptoms among international humanitarian aid workers
Greene-Cramer BJ , Hulland EN , Russell SP , Eriksson CB , Lopes-Cardozo B . Traumatology 2020 27 (2) 177-184 Most studies of mental health in humanitarian aid workers have found low levels of posttraumatic stress disorder, making it hard to disaggregate and look at differences between subgroups. This study sought to identify the risk and protective factors associated with resistant, resilient, and nonresilient trajectories of stress response over time that could be used to inform more targeted training and organizational support programs for aid workers. Aid workers from 19 qualifying humanitarian organizations who aged >=18 years and were to deploy for 3 to 12 months completed questionnaires at 3 time points (pre, post, and follow-up). We identified 3 unique groups (nonresilient, resistant, and resilient) using latent class growth analysis and identified predictors of subgroup classification using multivariate logistic regression. Single individuals were less likely to be in the resilient group than in the resistant group compared to coupled individuals. Individuals with one prior deployment were three times more likely to be nonresilient than resistant compared to individuals with no previous deployments. There was no significant difference in resistant, resilient, and nonresilient classification for individuals with >2 deployments. Findings suggest a need for supplemental training and psychosocial support post the first deployment as well as resources focused on potential this should be cumulative rather than accumulative effects of stress and trauma exposure for more seasoned deployers. (PsycInfo Database Record (c) 2020 APA, all rights reserved) |
Using mixed methods and multidisciplinary research to strengthen policy assessments focusing on populations at high risk for sexually transmitted diseases
Thompson K , Cramer R , LaPollo AB , Hubbard SH , Chesson HW , Leichliter JS . Public Health Rep 2020 135 32s-37s Examination of complex public health policy issues can benefit from a mixed methods approach led by multidisciplinary teams.1,2 Evolving problems confronted by law and public health inherently demand dynamic perspectives from diverse fields. However, in practice, professionals often succumb to established ways of approaching an issue within their own disciplines and areas of expertise.3 The mixed methods approach uses quantitative and qualitative research methods to provide a more comprehensive understanding of a research question than any single method could provide. A key advantage of using a mixed methods approach is that the concurrent, coordinated design can offset the weaknesses of either individual approach. Although quantitative research may be inadequate to understand the context in which a phenomenon occurs, qualitative research alone may invoke subjectivity and may not yield generalizable findings. Therefore, the scientific study of the effects of public health law necessitates a multidisciplinary approach.4 A multidisciplinary approach draws on the diverse subject matter expertise, training, and skills of partners from various fields. |
Noncommunicable disease burden among conflict-affected adults in Ukraine: A cross-sectional study of prevalence, risk factors, and effect of conflict on severity of disease and access to care
Greene-Cramer B , Summers A , Lopes-Cardozo B , Husain F , Couture A , Bilukha O . PLoS One 2020 15 (4) e0231899 BACKGROUND: There is limited research on noncommunicable diseases (NCDs) in humanitarian settings despite the overall global burden and disproportionate growth in many conflicts and disaster-prone settings. This study aimed to determine the prevalence of NCDs and assess the perceived effect of conflict on NCD severity and access to treatment among conflict-affected adults (>/= 30 years) in Ukraine. METHODS AND FINDINGS: We conducted two population-representative, stratified, cross-sectional household surveys: one among adult internally displaced people (IDPs) throughout Ukraine and one among adults living in Donbas in eastern Ukraine. One randomly selected adult per household answered questions about their demographics, height and weight, diagnosed NCDs, access to medications and healthcare since the conflict began, as well as questions assessing psychological distress, trauma exposure, and posttraumatic stress disorder. More than half of participants reported having at least one NCD (55.7% Donbas; 59.8% IDPs) A higher proportion of IDPs compared to adults in Donbas experienced serious psychological distress (29.9% vs. 18.7%), interruptions in care (9.7-14.3% vs. 23.1-51.3%), and interruptions in medication than adults in Donbas (14.9-45.6% vs. 30.2-77.5%). Factors associated with perceived worsening of disease included psychological distress (p: 0.002-0.043), displacement status (IDP vs. Donbas) (p: <0.001-0.011), interruptions in medication (p: 0.002-0.004), and inability to see a doctor at some point since the start of the conflict (p: <0.001-0.008). CONCLUSIONS: Our study found a high burden of NCDs among two conflict-affected populations in Ukraine and identified obstacles to accessing care and medication. Psychological distress, interruptions to care, and interruptions in medication were all reported by a higher proportion of IDPs than adults in Donbas. There is a need for targeted policies and programs to support the unique needs of displaced conflict-affected individuals in Ukraine that address the economic and perceived barriers to NCD treatment and care. |
State policies in the United States impacting drug-related convictions and their consequences in 2015
Cramer R , Hexem S , Thompson K , LaPollo AB , Chesson HW , Leichliter JS . Drug Sci Policy Law 2019 5 Background: Criminal justice system involvement has been associated with health issues, including sexually transmitted disease. Both incarceration and sexually transmitted disease share associations with various social conditions, including poverty, stigma, and drug use. Methods: United States state laws (including Washington, D.C.) regarding drug possession and consequences of drug-related criminal convictions were collected and coded. Drug possession policies focused on mandatory sentences for possession of marijuana, crack cocaine and methamphetamines. Consequences of drug-related convictions included ineligibility for public programmes, ineligibility for occupational licences and whether employers may ask prospective employees about criminal history. We analysed correlations between state sexually transmitted disease rates and percentage of a state's population convicted of a felony. Results: First-time possession of marijuana results in mandatory incarceration in one state; first-time possession of crack cocaine or methamphetamines results in mandatory incarceration in 12 (23.5%) states. Many states provide enhanced punishment upon a third possession conviction. A felony drug conviction results in mandatory ineligibility for the Supplemental Nutrition Assistance Program and/or Temporary Assistance for Needy Families in 17 (33.3%) states. Nine (17.6%) states prohibit criminal history questions on job applications. Criminal convictions limit eligibility for various professional licences in all states. State chlamydia, gonorrhoea and syphilis rates were positively associated with the percentage of the state population convicted of a felony (p < 0.05). Conclusion: While associations between crime, poverty, stigma and health have been investigated, our findings could be used to investigate the relationship between the likelihood of criminal justice system interactions, their consequences and public health outcomes including sexually transmitted disease risk. |
Systematic identification of facility-based stillbirths and neonatal deaths through the piloted use of an adapted RAPID tool in Liberia and Nepal
Greene-Cramer B , Boyd AT , Russell S , Hulland E , Tromble E , Widiati Y , Sharma S , Pun A , Roth Allen D , Dokubo EK , Handzel E . PLoS One 2019 14 (9) e0222583 Maternal, fetal, and neonatal health outcomes are interdependent. Designing public health strategies that link fetal and neonatal outcomes with maternal outcomes is necessary in order to successfully reduce perinatal and neonatal mortality, particularly in low- and middle- income countries. However, to date, there has been no standardized method for documenting, reporting, and reviewing facility-based stillbirths and neonatal deaths that links to maternal health outcomes would enable a more comprehensive understanding of the burden and determinants of poor fetal and neonatal outcomes. We developed and pilot-tested an adapted RAPID tool, Perinatal-Neonatal Rapid Ascertainment Process for Institutional Deaths (PN RAPID), to systematically identify and quantify facility-based stillbirths and neonatal deaths and link them to maternal health factors in two countries: Liberia and Nepal. This study found an absence of stillbirth timing documented in records, a high proportion of neonatal deaths occurring within the first 24 hours, and an absence of documentation of pregnancy-related and maternal factors that might be associated with fetal and neonatal outcomes. The use of an adapted RAPID methodology and tools was limited by these data gaps, highlighting the need for concurrent strengthening of death documentation through training and standardized record templates. |
Medicaid coverage of sexually transmitted disease service visits
Pearson WS , Spicknall IH , Cramer R , Jenkins WD . Am J Prev Med 2019 57 (1) 51-56 INTRODUCTION: Chlamydia and gonorrhea are the most commonly reported notifiable infections in the U.S., with direct medical costs for the treatment of these infections exceeding $700 million annually. Medicaid currently covers approximately 80 million low-income Americans, including a high percentage of racial and ethnic minorities. Studies have shown that racial and ethnic minority populations, particularly those with low SES, are at an increased risk of acquiring a sexually transmitted disease. Therefore, as Medicaid expands, there will likely be a greater demand for sexually transmitted disease services in community-based physician offices. To determine demand for these services among Medicaid enrollees, this study examined how often Medicaid was used to pay for sexually transmitted disease services received in this setting. METHODS: This study combined 2014 and 2015 data from the National Ambulatory Medical Care Survey and tested for differences in the proportion of visits with an expected payment source of Medicaid when sexually transmitted disease services were and were not provided. All analyses were conducted in October 2018. RESULTS: During 2014-2015, an estimated 25 million visits received a sexually transmitted disease service. Medicaid paid for a greater percentage of sexually transmitted disease visits (35.5%, 95% CI=22.5%, 51.1%) compared with non-sexually transmitted disease visits (12.1%, 95% CI=10.8%, 13.6%). Logistic regression modeling, controlling for age, sex, and race of the patient, showed that visits covered by Medicaid had increased odds of paying for a sexually transmitted disease service visit (OR=1.97, 95% CI=1.12, 3.46), compared with other expected payment sources. CONCLUSIONS: Focusing sexually transmitted disease prevention in Medicaid populations could reduce sexually transmitted disease incidence and resulting morbidity and costs. |
Geographic correlates of primary and secondary syphilis among men who have sex with men in the United States
Leichliter JS , Grey JA , Cuffe KM , de Voux A , Cramer R , Hexem S , Chesson HW , Bernstein KT . Ann Epidemiol 2019 32 14-19 e1 PURPOSE: Primary and secondary (P&S) syphilis in men who have sex with men (MSM) has been increasing; however, there is a lack of research on geographic factors associated with MSM P&S syphilis. METHODS: We used multiple data sources to examine associations between social and environmental factors and MSM P&S syphilis rates at the state- and county-level in 2014 and 2015, separately. General linear models were used for state-level analyses, and hurdle models were used for county-level models. Bivariate analyses (P < .25) were used to select variables for adjusted models. RESULTS: In 2014 and 2015 state models, a higher percentage of impoverished persons (2014 beta = 1.24, 95% confidence interval, 0.28-2.20; 2015 beta = 1.19; 95% confidence interval, 0.42-1.97) was significantly associated with higher MSM P&S syphilis rates. In the 2015 county model, policies related to sexual orientation (marriage, housing, hate crimes) were significant correlates of MSM P&S syphilis rates (P < .05). CONCLUSIONS: Our state-level findings that poverty is associated with MSM P&S syphilis are consistent with research at the individual level across different subpopulations and various sexually transmitted diseases. Our findings also suggest that more research is needed to further evaluate potential associations between policies and sexually transmitted diseases. Geographic-level interventions to address these determinants may help curtail the rising syphilis rates and their sequelae in MSM. |
Perceptions and acceptability of an experimental Ebola vaccine among health care workers, frontline staff, and the general public during the 2014-2015 Ebola outbreak in Sierra Leone
Jalloh MF , Jalloh MB , Albert A , Wolff B , Callis A , Ramakrishnan A , Cramer E , Sengeh P , Pratt SA , Conteh L , Hajjeh R , Bunnell R , Redd JT , Ekstrom AM , Nordenstedt H . Vaccine 2019 37 (11) 1495-1502 INTRODUCTION: Experimental Ebola vaccines were introduced during the 2014-2015 Ebola outbreak in West Africa. Planning for the Sierra Leone Trial to Introduce a Vaccine against Ebola (STRIVE) was underway in late 2014. We examined hypothetical acceptability and perceptions of experimental Ebola vaccines among health care workers (HCWs), frontline workers, and the general public to guide ethical communication of risks and benefits of any experimental Ebola vaccine. METHODS: Between December 2014 and January 2015, we conducted in-depth interviews with public health leaders (N=31), focus groups with HCWs and frontline workers (N=20), and focus groups with members of the general public (N=15) in Western Area Urban, Western Area Rural, Port Loko, Bombali, and Tonkolili districts. Themes were identified using qualitative content analysis. RESULTS: Across all participant groups, not knowing the immediate and long-term effects of an experimental Ebola vaccine was the most serious concern. Some respondents feared that experimental vaccines may cause Ebola, lead to death, or result in other adverse events. Among HCWs, not knowing the level of protection provided by experimental Ebola vaccines was another concern. HCWs and frontline workers were motivated to help find a vaccine for Ebola to help end the outbreak. General public participants cited positive experiences with routine childhood immunization in Sierra Leone. DISCUSSION: Our formative assessment prior to STRIVE's implementation in Sierra Leone helped identify concerns, motivations, and information gaps among potential participants of an experimental Ebola vaccine trial, at the time when an unprecedented outbreak was occurring in the country. The findings from this assessment were incorporated early in the process to guide ethical communication of risks and benefits when discussing informed consent for possible participation in the vaccine trial that was launched later in 2015. |
Young adults' access to insurance through parents: Relationship to receipt of reproductive health services and chlamydia testing, 2007-2014
Loosier PS , Hsieh H , Cramer R , Tao G . J Adolesc Health 2018 63 (5) 575-581 PURPOSE: Adolescents' concerns about confidential service receipt have been linked to avoidance of sexual and reproductive healthcare. Healthcare system changes allowing young adults to remain on a parent's health insurance plan up to age 26 may have extended these concerns to young adults. This study examines: (1) The association between the relationship of young women to primary health plan policy holder (parent or self) on receipt of reproductive health services and chlamydia screening. (2) Changes, over time, in the proportion of young women who are parentally- versus self-insured. METHODS: Cross-sectional analysis of commercially insured young women (18-25) enrolled >/=330 days in health plans included in the Truven Health MarketScan commercial claims and encounters database (2007-2014). RESULTS: Between 2010 and 2014, the proportion of parentally-insured young women increased significantly across all age groups (AOR=4.32, CI=4.29, 4.33). Compared to self-insured young women, parentally-insured young women were less likely to receive a reproductive health service (AOR=.66, CI=.66, .67) and sexually active parentally-insured young women were less likely to receive chlamydia testing (AOR=.75, CI=.75, .76) using their parent's insurance. CONCLUSIONS: Young women who are insured through a parent are less likely to receive reproductive health services or chlamydia testing using their parent's insurance, which could suggest that concerns about confidential receipt of health services may result in missed care. Various policies, including those related to explanation of benefits sent to a plan policy holder outlining services received, may affect the receipt of confidential healthcare by young adults. |
State laws related to billing third parties for health care services at public sexually transmitted disease clinics in the United States
Cramer R , Loosier PS , Krasner A , Kawatu J . Sex Transm Dis 2018 45 (8) 549-553 BACKGROUND: Health departments (HDs) cite state laws as barriers to billing third parties for sexually transmitted disease (STD) services, but the association between legal/policy barriers and third-party HD billing has not been examined. This study investigates the relationship between laws that may limit HDs' ability to bill, clinic perceptions of billing barriers, and billing practices. METHODS: Two surveys, (1) clinic managers (n = 246), (2) STD program managers (n = 63), conducted via a multiregional needs assessment of federally funded HD clinics' capacity to bill for STD services, billing/reimbursement practices, and perceived barriers were combined with an analysis of state laws regarding third-party billing for STD services. Statistical analyses examined relationships between laws that may limit HDs' ability to bill, clinic perceptions, and billing practices. RESULTS: Clinic managers reported clinics were less likely to bill Medicaid and other third parties in jurisdictions with a state law limiting their ability to bill compared with respondents who billed neither or 1 payer (odds ratio [OR], 0.31; 95% confidence interval [CI], 0.10-0.97) and cited practical concerns as a primary barrier to billing (OR, 2.83; 95% CI, 1.50-5.37). The STD program managers report that the staff believed that STD services should be free (OR, 0.34; 95% CI, 0.13-0.90) was associated with not billing (not sure versus no resistance to billing); confidentiality concerns was not a reported barrier to billing among either sample. CONCLUSIONS: Practical concerns and clinic staff beliefs that STD services should be free emerged as possible barriers to billing, as were laws to a lesser extent. Attempts to initiate HD billing for STD services may benefit from staff education as well as addressing perceived legal barriers and staff concerns. |
State requirements for prenatal syphilis screening in the United States, 2016
Warren HP , Cramer R , Kidd S , Leichliter JS . Matern Child Health J 2018 22 (9) 1227-1232 Objectives This study assesses U.S. state laws related to prenatal syphilis screening, including whether these laws align with CDC screening recommendations and include legal penalties for failing to screen. Methods Statutes and regulations regarding syphilis screening during pregnancy and at delivery effective in 2016 were examined for all 50 U.S. states and the District of Columbia (DC). Targeted search terms were used to identify laws in legal research databases. The timing of the screening mandates for each state law was coded for: (1) first visit, (2) third trimester, and (3) delivery. Descriptive statistics were calculated to examine the number of states with each type of requirement and whether requirements adhered to the CDC STD treatment guidelines. Results Only six states (11.8%) do not require prenatal syphilis screening. Of states with screening requirements (n = 45), the majority (84.3%) require testing at first prenatal visit or soon after. 17 states (33.3%) require screening during the third trimester with five requiring screening only if the patient is considered at high risk. 8 (15.7%) states require screening at delivery with five requiring testing only if the woman is at high risk. 14 (27.5%) states include punishments for failing to screen (civil penalties, criminal penalties and license revocation). Conclusions for Practice Most states had prenatal syphilis screening requirements; a minority corresponded to or extended CDC recommendations. States vary in when they require testing, who must be tested, and whether a failure to screen could result in a punishment for the provider. |
Notes from the Field: Diarrhea and acute respiratory infection, oral cholera vaccination coverage, and care-seeking behaviors of Rohingya refugees - Cox's Bazar, Bangladesh, October-November 2017
Summers A , Humphreys A , Leidman E , Van Mil LT , Wilkinson C , Narayan A , Miah ML , Cramer BG , Bilukha O . MMWR Morb Mortal Wkly Rep 2018 67 (18) 533-535 Violence in the Rakhine State of Myanmar, which began on August 25, 2017, prompted mass displacement of Rohingya to the bordering district of Cox’s Bazar, Bangladesh. Joining the nearly 213,000 Rohingya already in the region, an estimated 45,000 persons settled in two preexisting refugee camps, Nayapara and Kutupalong, and nearly 550,000 into new makeshift settlements (1). Mass violence and displacement, accompanied by malnutrition, overcrowding, poor hygiene, and lack of access to safe water and health care increase the vulnerability of children to infectious diseases, including pneumonia and diarrhea (2). |
Notes from the field: Increase in hepatitis A virus infections - Marshall Islands, 2016-2017
Hofmeister MG , McCready JA , Link-Gelles R , Cramer BG , Nolen LD , Garstang H , Foster MA . MMWR Morb Mortal Wkly Rep 2018 67 (17) 504-505 In mid-September 2016, a case of hepatitis A virus (HAV) infection was reported to the Marshall Islands Ministry of Health and Human Services (MOHHS). On November 4, MOHHS received laboratory confirmation of four additional cases, prompting activation of an outbreak investigation by the MOHHS Exposure Prevention Information Network (EPINet) team and solicitation of technical assistance from the Pacific Island Health Officers’ Association, the World Health Organization, and CDC. CDC began participating in the investigation by providing technical assistance remotely at that time. CDC provided remote assistance throughout the course of the investigation. In April 2017, the CDC-affiliated coauthors traveled to the Marshall Islands to provide in-person technical assistance. |
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