Last data update: May 13, 2024. (Total: 46773 publications since 2009)
Records 1-30 (of 41 Records) |
Query Trace: Rivadeneira E [original query] |
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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. |
A model for accelerating access to care and treatment for children and adolescents living with HIV in Nigeria, Tanzania, Uganda, and Zambia: The Faith-Based Action for Scaling-Up Testing and Treatment for the Epidemic Response (FASTER) Initiative
Oliver D , Mabirizi D , Hast M , Alwano MG , Chungu C , Kelemani A , Mbanefo C , Gross J , Parris K , Dowling S , Clark A , Williams A , Simao L , Amole C , Suggu K , Kama J , Mpasela F , Mtui L , Nabitaka V , Saunders R , Williamson D , Rivadeneira ED , Hrapcak S , Nantume S , Nazziwa E , Itoh M , Machage E , Onyenuobi C , Munthali G , Rwebembera A , Mwiya M , Katureebe C , Ikpeazu A , Fenn T . J Int Assoc Provid AIDS Care 2023 22 23259582231186701 The number of children newly infected with HIV dropped by 50%, from 320 000 in 2010 to 160 000 in 2021. Despite progress, ongoing gaps persist in diagnosis, continuity of care, and treatment optimization. In response, the United States President's Emergency Plan for AIDS Relief created the Faith-based Action for Scaling-Up Testing and Treatment for Epidemic Response (FASTER). Faith-based Action for Scaling-Up Testing and Treatment for Epidemic Response addressed gaps in countries with the highest unmet need by working with government to operationalize innovative interventions and ensure alignment with national priorities and with communities living with HIV to ensure the change was community-led. Between 2019 and 2021, FASTER's interventions were incorporated into national policies, absorbed by Ministries of Health, and taken up in subsequent awards and country operating plans. Continued effort is needed to sustain gains made during the FASTER initiative and to continue scaling evidence-based interventions to ensure that children and adolescents are not left behind in the global HIV response. |
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 |
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. |
Implementation and uptake of raltegravir granules in newborns diagnosed with HIV through birth testing in maternity settings in Zimbabwe during the COVID-19 pandemic
Denoeud-Ndam L , Stecker C , Andifasi P , Mushavi A , Maphosa T , Zondo M , Murandu M , Gombakomba G , Katirayi L , Mungati M , Bailey R , Weber R , Rivadeneira E , Hrapcak S . Pediatr Infect Dis J 2023 42 (7) 573-575 Zimbabwe introduced raltegravir (RAL) granules at 14 facilities providing point-of-care HIV birth testing, aiming to initiate all newborns with HIV on a RAL-based regimen. From June 2020 to July 2021, we tested 3172 of the 6989 (45%) newborns exposed to HIV; we diagnosed 59(2%) with HIV infection, of whom 27 (46%) initiated RAL. The SARS-CoV-2 coronavirus disease pandemic exacerbated supply chain and trained provider shortages, contributing to low birth testing, RAL uptake and 6-month viral load testing. |
HIV viral load scale-up among children and adolescents: Trends in viral load suppression, sample type and processing in 7 PEPFAR countries, 2015-2018
Hrapcak S , Pals S , Itoh M , Peters N , Carpenter D , Hackett S , Prao AK , Adje-Toure C , Eboi E , Mutisya I , Nyabiage Omoto L , Ondondo RO , Bowen N , Nyanya W , Kayira D , Kaba MD , Mwenda R , Deus MI , Almeida J , Cuco RMM , Boylan A , Beard S , Ashikoto S , van Rooyen G , Kindra G , Diallo K , Carmona S , Nazziwa E , Mwangi C , Ntale J , Ssewanyana I , Nabadda SN , Nabukenya M , Ellenberger D , Rivadeneira E . Pediatr Infect Dis J 2023 42 (4) e102-e104 HIV-positive children and adolescents face gaps in viral load (VL) testing. To understand trends in pediatric/adolescent VL testing, 7 countries collected data from Laboratory Information Management Systems. Results showed increasing proportion of VL tests done through dried blood spot (DBS) and decreased sample rejection rates for DBS compared with plasma, supporting use of DBS VL when skilled phlebotomy is unavailable. |
The status of adolescent testing and treatment in PEPFAR-supported programs, October 2017-September 2020
Hrapcak S , Hast M , Okegbe T , Gross J , Williams J , Patel M , Wolf H , Siberry G , Lee L , Wiersma S , Agaba P , Carpenter D , Rivadeneira E . J Acquir Immune Defic Syndr 2023 93 (1) 15-24 BACKGROUND: Adolescents have poorer outcomes across the HIV cascade compared to adults. We aimed to assess progress in HIV case-finding, antiretroviral treatment (ART), viral load coverage (VLC), and viral load suppression (VLS) among adolescents enrolled in the U.S. President's Emergency Plan for AIDS Relief (PEPFAR)-supported programs over a three-year period that included the beginning of the COVID-19 pandemic. METHODS: We analyzed PEPFAR program data in 28 countries/regions for adolescents 10-19 years between year 1 (October 2017-September 2018), year 2 (October 2018-September 2019), and year 3 (October 2019-September 2020). We calculated the number and percent change for HIV tests, HIV-positive tests, and total number on ART. Calculated indicators included positivity, percent of positives newly initiated on ART (ART linkage), VLC (percent of ART patients on ART for ≥6 months with a documented viral load result within the past 12 months), and VLS (percent of viral load tests with <1000 copies/mL). RESULTS: Between Years 1 and 3, the number of HIV tests conducted decreased by 44.2%, with a 29.1% decrease in the number of positive tests. Positivity increased from 1.3% to 1.6%. The number of adolescents receiving ART increased by 10.4%. Additionally, ART linkage increased (77.8% to 86.7%) as did VLC (69.4% to 79.4%) and VLS (72.8% to 81.5%). CONCLUSIONS: Our findings demonstrate PEPFAR's success in increasing the adolescent treatment cohort. We identified ongoing gaps in adolescent case-finding, linkage, VLC, and VLS that could be addressed with a strategic mix of testing strategies, optimal ART regimens, and adolescent-focused service delivery models. |
Retention and predictors of attrition among HIV-infected children on antiretroviral therapy in Cte d'Ivoire between 2012 and 2016
Touré F , Etheredge GD , Brennan C , Parris K , Diallo MO , Ouffoue AF , Ekra A , Prao H , Assamoua NV , Gnongoue C , Kone F , Koffi C , Kamagaté F , Rivadeneira E , Carpenter D . Pediatr Infect Dis J 2023 42 (4) 299-304 BACKGROUND: An estimated 21,000 children aged 0-14 years were living with HIV in Côte d'Ivoire in 2020, of whom only 49% have been diagnosed and are receiving antiretroviral therapy (ART). Retention in HIV care and treatment is key to optimize clinical outcomes. We evaluated pediatric retention in select care and treatment centers (CTCs) in Côte d'Ivoire. METHODS: We retrospectively reviewed medical records using 2-stage cluster sampling for children under 15 years initiated on ART between 2012 and 2016. Kaplan-Meier time-to-event analysis was done to estimate cumulative attrition rates per total person-years of observation. Cox proportional hazard regression was performed to identify factors associated with attrition. RESULTS: A total of 1198 patient records from 33 CTCs were reviewed. Retention at 12, 24, 36, 48 and 60 months after ART initiation was 91%, 84%, 74%, 72% and 70%, respectively. A total of 309 attrition events occurred over 3169 person-years of follow-up [266 children were lost to follow-up (LTFU), 29 transferred to another facility and 14 died]. LTFU determinants included attending a "public-private" CTC [adjusted hazard ratio (aHR) 6.05; 95% confidence interval (CI): 4.23-8.65], receiving care at a CTC without an on-site laboratory (aHR: 4.01; 95% CI: 1.70-9.46) or attending a CTC without an electronic medical record (EMR) system (aHR: 2.22; 95% CI: 1.59-3.12). CONCLUSIONS: In Cote d'Ivoire, patients attending a CTC that is public-private, does not have on-site laboratory or EMR system were likely to be LTFU. Decentralization of laboratory services and scaling use of EMR systems could help to improve pediatric retention. |
Considerations to improve pediatric HIV testing and close the treatment gap in 16 African countries
Gross J , Medley A , Rivadeneira E , Battey K , Srivastava M , Grillo M , Wolf H , Simmons P , Hast M , Patel M . Pediatr Infect Dis J 2023 42 (2) 110-118 BACKGROUND: In 2019, South Africa, Nigeria, Tanzania, Democratic Republic of Congo, Uganda, Mozambique, Zambia, Angola, Cameroon, Zimbabwe, Ghana, Ethiopia, Malawi, Kenya, South Sudan and Côte d'Ivoire accounted for 80% of children living with HIV (CLHIV) not receiving HIV treatment. This manuscript describes pediatric HIV testing to inform case-finding strategies. METHODS: We analyzed US President's Emergency Plan for AIDS Relief monitoring, evaluation, and reporting data (October 1, 2018 to September 30, 2019) for these 16 countries. Number of HIV tests and positive results were reported by age band, country, treatment coverage and testing modality. The number needed to test (NNT) to identify 1 new CLHIV 1-14 years was measured by testing modality and country. The pediatric testing gap was estimated by multiplying the estimated number of CLHIV unaware of their status by NNT per country. RESULTS: Among children, 6,961,225 HIV tests were conducted, and 101,762 CLHIV were identified (NNT 68), meeting 17.6% of the pediatric testing need. Index testing accounted for 13.0% of HIV tests (29.7% of positive results, NNT 30), provider-initiated testing and counseling 65.9% of tests (43.6% of positives, NNT 103), and universal testing at sick entry points 5.3% of tests (6.5% of positives, NNT 58). CONCLUSIONS: As countries near HIV epidemic control for adults, the need to increase pediatric testing continues. Each testing modality - PITC, universal testing at sick entry points, and index testing - offers unique benefits. These results illustrate the comparative advantages of including a strategic mix of testing modalities in national programs to increase pediatric HIV case finding. |
Tuberculosis prevalence, incidence and prevention in a South African cohort of children living with HIV
Anyalechi GE , Bain R , Kindra G , Mogashoa M , Sogaula N , Mutiti A , Arpadi S , Rivadeneira E , Abrams EJ , Teasdale CA . J Trop Pediatr 2022 68 (6) BACKGROUND: We describe tuberculosis (TB) disease among antiretroviral treatment (ART) eligible children living with HIV (CLHIV) in South Africa to highlight TB prevention opportunities. METHODS: In our secondary analysis among 0- to 12-year-old ART-eligible CLHIV in five Eastern Cape Province health facilities from 2012 to 2015, prevalent TB occurred 90 days before or after enrollment; incident TB occurred >90 days after enrollment. Characteristics associated with TB were assessed using logistic and Cox proportional hazards regression with generalized estimating equations. RESULTS: Of 397 enrolled children, 114 (28.7%) had prevalent TB. Higher-income proxy [adjusted odds ratio (aOR) 1.8 [95% confidence interval (CI) 1.3-2.6] for the highest, 1.6 (95% CI 1.6-1.7) for intermediate]; CD4+ cell count <350 cells/µl [aOR 1.6 (95% CI 1.1-2.2)]; and malnutrition [aOR 1.6 (95% CI 1.1-2.6)] were associated with prevalent TB. Incident TB was 5.2 per 100 person-years and was associated with delayed ART initiation [hazard ratio (HR) 4.7 (95% CI 2.3-9.4)], malnutrition [HR 1.8 (95% CI 1.1-2.7)] and absence of cotrimoxazole [HR 2.3 (95% CI 1.0-4.9)]. Among 362 children with data, 8.6% received TB preventive treatment. CONCLUSIONS: Among these CLHIV, prevalent and incident TB were common. Early ART, cotrimoxazole and addressing malnutrition may prevent TB in these children. | BACKGROUND: We describe tuberculosis (TB) in children living with HIV (CLHIV) eligible for HIV treatment in South Africa to highlight opportunities to prevent TB. METHODS: We analyzed additional data from our original study of CLHIV who were 0–12 years old and due to start HIV treatment in five health facilities in Eastern Cape Province from 2012 to 2015 and assessed characteristics associated with existing and new TB. RESULTS: Of 397 enrolled children, 114 (28.7%) had existing TB. Children with a higher measure of household income had higher odds of existing TB. CD4+ cell count <350 cells/µl and malnutrition were also associated with existing TB. There were 5.2 new cases of TB for every 100 child-years. New TB was 4.7 times more likely for children with delayed HIV treatment start, 1.8 times more likely for children with malnutrition and 2.3 times more likely for children who did not get cotrimoxazole. Among 362 children with data, 8.6% received treatment to prevent TB. CONCLUSIONS: Among these CLHIV, existing and new TB were common. Early HIV treatment, cotrimoxazole and addressing malnutrition may prevent TB in these children. | eng |
Optimising neonatal antiretroviral therapy using raltegravir: a qualitative analysis of healthcare workers' and caregivers' perspectives
Katirayi L , Stecker C , Andifasi P , Mushavi A , Tiwari P , Jakazi C , Maphosa T , Thorsen V , Murandu M , Gombakomba G , Mungati M , Denoeud-Ndam L , Rivadeneira E , Weber R , Hrapcak S . BMJ Paediatr Open 2022 6 (1) Background In 2020, Zimbabwe adopted the WHO's recommendation to use raltegravir (RAL) granule-based regimens for treatment of neonates identified with HIV at the time of birth testing. This study explores the acceptability of RAL granules by caregivers and healthcare workers (HCWs). Methods Interviews were conducted with 15 caregivers and 12 HCWs from 8 health facilities in Zimbabwe participating in the introductory pilot of RAL granules treatment for newborns. Eligible caregivers included those who had administered RAL to their infant and attended either 8th or 28th day of life appointments. Caregivers of neonates recently initiated on RAL were selected through convenience sampling. Eligible HCWs who provided RAL preparation, administration instructions and support to caregivers of neonates on RAL for at least 3 months were recruited from the same facilities as the caregivers. Interview transcripts were coded and thematically analysed. Results Caregivers reported that their babies looked healthier after RAL initiation, with improved skin appearance and weight gain. Some caregivers wanted their child to remain on RAL beyond 28 days instead of switching regimens, as recommended by national guidelines. HCWs observed that RAL granules improved health outcomes compared with other regimens. HCWs reported challenges with caregivers understanding dosing instructions, measuring with a syringe, swirling and not shaking the medicine, discarding unused medication and following the changes in the dosing schedule and amount when RAL was initiated a few days after birth. HCWs stated that adequate counselling and repeat demonstrations were crucial to ensure that caregivers clearly understood RAL dosing and administration instructions. HCWs requested more standardised training targeting nurses with guidance on handling missed doses and clarification on mixing RAL granules with water and not breastmilk. Conclusion While feedback from caregivers and HCWs on RAL implementation was positive, barriers were also noted. Adequate training and sufficient instruction and support for caregivers would help to ensure that RAL granules are prepared, dosed and administered correctly. © Author(s) (or their employer(s)) 2022. |
Outcomes of HIV positive children and adolescents initiated on antiretroviral treatment in Nigeria (2007-2016)
Anukam O , Blanco N , Jumare J , Lo J , Babatunde E , Odafe S , Onotu D , Ene U , Fagbamigbe J , Carpenter D , Rivadeneira ED , Omoigberale AI , Charurat M , Swaminathan M , Stafford KA . J Int Assoc Provid AIDS Care 2022 21 23259582221117009 Background: This manuscript aimed to examine treatment outcomes of HIV-positive children and adolescents. Methods: We retrospectively analyzed data of a sample of patients aged 0-19 years who initiated ART (October 2007-September 2016) in participating sites in 30 states and the Federal Capital Territory in Nigeria. Results: Among 4006 patients alive at the end of the follow up period, 138 (3.4%) were LTFU. Adolescents had a significantly higher risk of being LTFU than children aged 3-5 years (HR 2.47 [95% CI 1.40-4.34]). Patients with advanced disease had a significantly higher risk of being LTFU (Stage IV HR, 3.66 [95% CI: 2.00-6.68]). On average, optimal ART refill adherence was met by 67.3% of patients. Conclusion: Our findings suggest that focusing on preventing and managing advanced disease and interventions supporting adolescents when transferring to adult care is warranted. |
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. |
Developing and Validating an Effective Pediatric and Adolescent HIV Testing Eligibility Screening Tool for High-Volume Entry Points in Uganda
Katureebe C , Ashburn K , Machekano R , Gill MM , Gross J , Kazooba P , Kiyonga A , Taasi G , Adler M , Nazziwa E , Rivadeneira ED , Kekitiinwa A , Magongo E , Matovu JB , Nantume S , Bitarakwate E . J Acquir Immune Defic Syndr 2021 88 (3) 290-298 INTRODUCTION: Because of low pediatric HIV prevalence, more tests are needed to find 1 HIV-positive child compared with adults. In Uganda, the number needed to test (NNT) to find 1 new HIV-positive child was 64 in outpatient departments (OPDs) and 31 through index testing. We aimed to develop and validate a pediatric (1.5-14 years) screening tool to optimize testing approaches. METHODS: Phase 1 evaluated the performance of 10 screening questions in 14 OPDs using a variable selection algorithm to evaluate combinations of screening questions. Using logistic regression, we identified the number of screening questions with the best predictive accuracy using the receiver operation characteristic curve. Phase 2 validated the proposed tool in 15 OPDs and 7 orphan and vulnerable children programs. We estimated sensitivity, specificity, and NNT accounting for intercluster correlations. RESULTS: A total of 3482 children were enrolled. The optimal model included reported HIV-positive maternal status or 2/5 symptoms (sickly in the last 3 months, recurring skin problems, weight loss, not growing well, and history of tuberculosis). The proposed tool had sensitivity of 83.6% [95% confidence interval (CI): 68.1 to 92.4] and specificity of 62.5% (95% CI: 55.0 to 69.4). The tool was validated in a sample of 11,342 children; sensitivity was 87.8% (95% CI: 80.9 to 92.5) and specificity 62.6% (95% CI: 54.8 to 69.7) across OPDs and community sites. In OPDs, sensitivity was 88.1% (95% CI: 80.8 to 92.8) and specificity 69.0% (95% CI: 61.9 to 75.3). The NNT was 43 (95% CI: 28 to 67) across settings and 28 (95% CI: 20 to 38) for OPD. CONCLUSIONS: This HIV screening tool has high sensitivity and reasonable specificity, increasing testing efficiency and yield for children and adolescents. |
Growth and Metabolic Changes After Antiretroviral Initiation in South African Children
Masi-Leone M , Arpadi S , Teasdale C , Yuengling KA , Mutiti A , Mogashoa M , Rivadeneira ED , Abrams EJ , Jao J . Pediatr Infect Dis J 2021 40 (11) 1004-1010 BACKGROUND: Poor growth and metabolic disturbances remain concerns for children living with HIV (CLHIV). We describe the impact of viral load (VL) on growth and lipid outcomes in South African CLHIV <12 years initiating World Health Organization recommended first-line antiretroviral therapy (ART) from 2012 to 2015. METHODS: Z scores for length-for-age (LAZ), weight-for-age (WAZ) and body mass index-for-age were calculated. Lipids (total cholesterol, low-density lipoprotein and high-density lipoprotein) were measured. Hemoglobin A1C ≥5.8 was defined as at risk for type 2 diabetes. Mixed effects models were used to assess the association of VL at ART initiation with Z scores and lipids over time. RESULTS: Of 241 CLHIV, 151 (63%) were <3 years initiating LPV/r-based ART and 90 (37%) were ≥3 years initiating EFV-based ART. Among CLHIV <3 years, higher VL at ART initiation was associated with lower mean LAZ (ß: -0.30, P=0.03), WAZ (ß: -0.32, P=0.01) and low-density lipoprotein (ß: -6.45, P=0.03) over time. Among CLHIV ≥3, a log 10 increase in pretreatment VL was associated with lower mean LAZ (ß: -0.29, P=0.07) trending towards significance and lower WAZ (ß: -0.32, P=0.05) as well as with more rapid increases in LAZ (ß: 0.14 per year, P=0.01) and WAZ (ß: 0.19 per year, P=0.04). Thirty percent of CLHIV were at risk for type 2 diabetes at ART initiation. CONCLUSIONS: CLHIV initiating ART <3 years exhibited positive gains in growth and lipids, though high viremia at ART initiation was associated with persistently low growth and lipids, underscoring the need for early diagnosis and rapid treatment initiation. Future studies assessing the long-term cardiometabolic impact of these findings are warranted. |
Human immunodeficiency virus prevention for people who use drugs: Overview of reviews and the ICOS of PICOS
Johnson WD , Rivadeneira N , Adegbite AH , Neumann MS , Mullins MM , Rooks-Peck C , Wichser ME , McDonald CM , Higa DH , Sipe TA . J Infect Dis 2020 222 S278-s300 BACKGROUND: This article summarizes the results from systematic reviews of human immunodeficiency virus (HIV) prevention interventions for people who use drugs (PWUD). We performed an overview of reviews, meta-analysis, meta-epidemiology, and PROSPERO Registration CRD42017070117. METHODS: We conducted a comprehensive systematic literature search using the Centers for Disease Control and Prevention HIV/AIDS Prevention Research Synthesis Project database to identify quantitative systematic reviews of HIV public heath interventions with PWUD published during 2002-2017. We recombined results of US studies across reviews to quantify effects on HIV infections, continuum of HIV care, sexual risk, and 5 drug-related outcomes (sharing injection equipment, injection frequency, opioid use, general drug use, and participation in drug treatment). We conducted summary meta-analyses separately for reviews of randomized controlled trials (RCTs) and quasi-experiments. We stratified effects by 5 intervention types: behavioral-psychosocial (BPS), syringe service programs (SSP), opioid agonist therapy (OAT), financial and scheduling incentives (FSI), and case management (CM). RESULTS: We identified 16 eligible reviews including >140 US studies with >55 000 participants. Summary effects among US studies were significant and favorable for 4 of 5 outcomes measured under RCT (eg, reduced opioid use; odds ratio [OR] = 0.70, confidence interval [CI] = 0.56-0.89) and all 6 outcomes under quasi-experiments (eg, reduced HIV infection [OR = 0.42, CI = 0.27-0.63]; favorable continuum of HIV care [OR = 0.68, CI = 0.53-0.88]). Each intervention type showed effectiveness on 1-6 outcomes. Heterogeneity was moderate to none for RCT but moderate to high for quasi-experiments. CONCLUSIONS: Behavioral-psychosocial, SSP, OAT, FSI, and CM interventions are effective in reducing risk of HIV and sequelae of injection and other drug use, and they have a continuing role in addressing the opioid crisis and Ending the HIV Epidemic. |
Drug resistance mutations among South African children living with HIV on WHO-recommended ART regimens.
Hackett S , Teasdale CA , Pals S , Muttiti A , Mogashoa M , Chang J , Zeh C , Ramos A , Rivadeneira ED , DeVos J , Sleeman K , Abrams EJ . Clin Infect Dis 2020 73 (7) e2217-e2225 BACKGROUND: Children living with HIV (CLHIV) receiving antiretroviral treatment (ART) in resource limited settings are susceptible to high rates of acquired HIV drug resistance (HIVDR), but few studies include children initiating age-appropriate WHO-recommended first-line regimens. We report data from a cohort of ART-naïve South African children who initiated first-line ART. METHODS: ART-eligible CLHIV aged 0-12 years were enrolled from 2012 to 2014 at five public South African facilities and followed for up to 24 months. Enrolled CLHIV received standard of care WHO-recommended first-line ART. At the final study visit, a dried blood spot sample was obtained for viral load and genotypic resistance testing. RESULTS: Among 72 successfully genotyped CLHIV, 49 (68.1%) received ABC/3TC/LPV/r, and 23 (31.9%) received ABC/3TC/EFV. All but 2 children on ABC/3TC/LPV/r were <3 years and all CLHIV on ABC/3TC/EFV were ≥3 years. Overall, 80.6% (58/72) had at least one drug resistance mutation (DRM). DRMs to NNRTIs and NRTIs were found among 65% and 51% of all CLHIV, respectively, with no statistical difference by ART regimen. More CLHIV on ABC/3TC/EFV, 47.8% (11/23), were found to have 0 or only 1 effective antiretroviral drug remaining in their current regimen compared to 8.2% (4/49) on ABC/3TC/LPV/r. CONCLUSIONS: High levels of NNRTI and NRTI DRMs among CLHIV receiving ABC/3TC/LPV/r suggests a lasting impact of failed PMTCT interventions on DRMs. However, drug susceptibility analysis, reveals that CLHIV with detectable viremia on ABC/3TC/LPV/r are more likely to have maintained at least two effective agents on their current HIV regimen than those on ABC/3TC/EFV. |
HIV-exposed uninfected infant morbidity and mortality within a nationally representative prospective cohort of mother-infant pairs in Zimbabwe
Patel MR , Mushavi A , Balachandra S , Shambira G , Nyakura J , Mugurungi O , Kilmarx PH , Rivadeneira E , Dinh TH . AIDS 2020 34 (9) 1339-1346 OBJECTIVE: To examine morbidity and mortality risk among HIV-exposed uninfected (HEU) infants. DESIGN: Secondary data analysis of HEU infants in a prospective cohort study of mother-infant pairs. METHODS: Infants were recruited from immunization clinics (n = 151) in Zimbabwe from February to August 2013, enrolled at 4-12 weeks age, and followed every 3 months until incident HIV-infection, death, or 18-month follow-up. We estimated cumulative mortality probability and hazard ratios with 95% confidence intervals (CIs) using Kaplan-Meier curves and Cox regression, respectively. We also described reported reasons for infant hospitalization and symptoms preceding death. Median weight-for-age z-scores (WAZ) and median age were calculated and analyzed across study visits. RESULTS: Of 1188 HIV-exposed infants, 73 (6.1%) contracted HIV; we analyzed the remaining 1115 HEU infants. In total, 54 (4.8%) infants died, with median time to death of 5.5 months since birth (interquartile range: 3.6-9.8 months). Diarrhea, difficulty breathing, not eating, fever, and cough were commonly reported (range: 7.4-22.2%) as symptoms preceding infant death. Low birth weight was associated with higher mortality (adjusted hazard ratio 2.66, CI: 1.35-5.25), whereas maternal antiretroviral therapy predelivery (adjusted hazard ratio 0.34, CI: 0.18-0.64) and exclusive breastfeeding (adjusted hazard ratio 0.50, CI: 0.28-0.91) were associated with lower mortality. Overall, 9.6% of infants were hospitalized. Infant median WAZ declined after 3 months of age, reaching a minimum at 14.5 months of age, at which 50% of infants were underweight (WAZ below -2.0). CONCLUSION: Clinical interventions including maternal antiretroviral therapy; breastfeeding and infant feeding counseling and support; and early prevention, identification, and management of childhood illness; are needed to reduce HEU infant morbidity and mortality. |
Increasing pediatric HIV testing positivity rates through focused testing in high-yield points of service in health facilities-Nigeria, 2016-2017
Odafe S , Onotu D , Fagbamigbe JO , Ene U , Rivadeneira E , Carpenter D , Omoigberale AI , Adamu Y , Lawal I , James E , Boyd AT , Dirlikov E , Swaminathan M . PLoS One 2020 15 (6) e0234717 BACKGROUND: In 2017, UNAIDS estimated that 140,000 children aged 0-14 years are living with HIV in Nigeria, but only 35% have been diagnosed and are receiving antiretroviral therapy. Children are tested primarily in outpatient clinics, which show low HIV-positive rates. To demonstrate efficient facility-based HIV testing among children aged 0-14 years, we evaluated pediatric HIV-positivity rates in points of service in select health facilities in Nigeria. METHODS: We conducted a retrospective analysis of HIV testing and case identification among children aged 0-14 years at all points of service at nine purposively sampled hospitals (November 2016-March 2017). Points of service included family index testing, pediatric outpatient department (POPD), tuberculosis (TB) clinics, immunization clinics, and pediatric inpatient ward. Eligibility for testing at POPD was done using a screening tool while all children with unknown status were eligible for HIV test at other points of service. The main outcome was HIV positivity rates stratified by the testing point of service and by age group. Predictors of an HIV-positive result were assessed using logistic regression. All analyses were done using Stata 15 statistical software. RESULTS: Of 2,180 children seen at all facility points of service with unknown HIV status, 1,822 (83.6%) were tested for HIV, of whom 43 (2.4%) tested HIV positive. The numbers of children tested by age group were <1 years = 230 (12.6%); 1-4 years = 752 (41.3%); 5-9 years = 520 (28.5%); and 10-14 years = 320 (17.6%). The number of children tested by point of service were POPD = 906 (49.7%); family index testing = 693 (38.0%); pediatric inpatient ward = 192 (10.5%); immunization clinic = 16 (0.9%); and TB clinic = 15 (0.8%). HIV positivity rates by point of service were TB clinic = 6.7% (95% Confidence Interval (CI): 0.9-35.2%); pediatric inpatient ward = 4.7% (95%CI: 2.5-8.8%); family index testing = 3.5% (95%CI: 2.3-5.1%); POPD = 1.0% (95%CI: 0.5-1.9%); and immunization clinic = 0%. The percentage contribution to total HIV positive children found by point of services was: family index testing = 55.8% (95%CI: 40.9-69.8%); POPD = 20.9% (95%CI: 11.3-35.6%); inpatient ward = 20.9 (95%CI: 11.3-35.6%) and TB Clinic = 2.3% (95%CI: 0.3-14.8%). Compared with the POPD, the adjusted odds ratio (95% CI) for finding an HIV positive child by point of service were TB clinic = 7.2 (95% CI: 0.9-60.9); pediatric inpatient ward = 4.9 (95% CI: 1.9-12.8); and family index testing = 3.7 (95% CI: 1.5-8.8). HIV-positivity rates did not significantly differ by age group. CONCLUSION: In Nigeria, to improve facility-based HIV positivity rates among children aged 0-14 years, an increased focus on HIV testing among children seeking care in pediatric inpatient wards, through family index testing, and perhaps TB clinics is appropriate. |
Birth testing for infant HIV diagnosis in Eswatini: Implementation experience and uptake among women living with HIV in Manzini Region
Teasdale CA , Tsiouris F , Mafukidze A , Shongwe S , Choy M , Nhlengetfwa H , Simelane S , Mthethwa S , Ao T , Ryan C , Dale H , Rivadeneira E , Abrams EJ . Pediatr Infect Dis J 2020 39 (9) e235-e241 INTRODUCTION: HIV testing at birth of HIV-exposed infants (HEIs) may improve the identification of infants infected with HIV in utero and accelerate antiretroviral treatment (ART) initiation. METHODS: ICAP at Columbia University supported implementation of a national pilot of HIV testing at birth (0-7 days) in Eswatini at 2 maternity facilities. Dried blood spot (DBS) samples from neonates of women living with HIV (WLHIV) were collected and processed at the National Molecular Reference Laboratory using polymerase chain reaction (PCR). Mothers received birth test results at community health clinics. We report data on HIV birth testing uptake and outcomes for HIV-positive infants from the initial intensive phase (October 2017-March 2018) and routine support phase (April-December 2018). RESULTS: During the initial intensive pilot phase, 1669 WLHIV delivered 1697 live-born HEI at 2 health facilities and 1480 (90.3%) HEI received birth testing. During the routine support phase, 2546 WLHIV delivered and 2277 (93.5%) HEI received birth testing. Overall October 2017-December 2018, 22 (0.6%) infants of 3757 receiving birth testing had a positive PCR test, 15 (68.2%) of whom were successfully traced and linked for confirmatory testing (2 infants were reported by caregivers to have negative follow-up HIV tests). Median time from birth test to receipt of results by the caregiver was 13 days (range: 8-23). Twelve (60.0%) of 20 infants confirmed to be HIV-positive started ART at median age of 17.5 days (12-43). One mother of an HIV-positive infant who was successfully traced refused ART following linkage to care and another child died after ART initiation. Three infants (15.0%) had died by the time their mothers were reached and 4 (15.0%) infants were never located. CONCLUSION: This pilot of universal birth testing in Eswatini demonstrates the feasibility of using a standard of care approach in a low resource and high burden setting. We document high uptake of testing for newborns among HIV-positive mothers and very few infants were found to be infected through birth testing. |
Spatio-temporal dynamics of Plasmodium falciparum transmission within a spatial unit on the Colombian Pacific Coast.
Knudson A , Gonzalez-Casabianca F , Feged-Rivadeneira A , Pedreros MF , Aponte S , Olaya A , Castillo CF , Mancilla E , Piamba-Dorado A , Sanchez-Pedraza R , Salazar-Terreros MJ , Lucchi N , Udhayakumar V , Jacob C , Pance A , Carrasquilla M , Apraez G , Angel JA , Rayner JC , Corredor V . Sci Rep 2020 10 (1) 3756 As malaria control programmes concentrate their efforts towards malaria elimination a better understanding of malaria transmission patterns at fine spatial resolution units becomes necessary. Defining spatial units that consider transmission heterogeneity, human movement and migration will help to set up achievable malaria elimination milestones and guide the creation of efficient operational administrative control units. Using a combination of genetic and epidemiological data we defined a malaria transmission unit as the area contributing 95% of malaria cases diagnosed at the catchment facility located in the town of Guapi in the South Pacific Coast of Colombia. We provide data showing that P. falciparum malaria transmission is heterogeneous in time and space and analysed, using topological data analysis, the spatial connectivity, at the micro epidemiological level, between parasite populations circulating within the unit. To illustrate the necessity to evaluate the efficacy of malaria control measures within the transmission unit in order to increase the efficiency of the malaria control effort, we provide information on the size of the asymptomatic reservoir, the nature of parasite genotypes associated with drug resistance as well as the frequency of the Pfhrp2/3 deletion associated with false negatives when using Rapid Diagnostic Tests. |
Better outcomes among HIV-infected Rwandan children 18-60 months of age after the implementation of "Treat All"
Arpadi S , Lamb M , Nzeyimana IN , Vandebriel G , Anyalechi G , Wong M , Smith R , Rivadeneira ED , Kayirangwa E , Malamba SS , Musoni C , Koumans EH , Braaten M , Nsanzimana S . J Acquir Immune Defic Syndr 2019 80 (3) e74-e83 BACKGROUND: In 2012, Rwanda introduced a Treat All approach for HIV-infected children younger than 5 years. We compared antiretroviral therapy (ART) initiation, outcomes, and retention, before and after this change. METHODS: We conducted a retrospective study of children enrolled into care between June 2009 and December 2011 [Before Treat All (BTA) cohort] and between July 2012 and April 2015 [Treat All (TA) cohort]. SETTING: Medical records of a nationally representative sample were abstracted for all eligible aged 18-60 months from 100 Rwandan public health facilities. RESULTS: We abstracted 374 medical records: 227 in the BTA and 147 in the TA cohorts. Mean (SD) age at enrollment was [3 years (1.1)]. Among BTA, 59% initiated ART within 1 year, vs. 89% in the TA cohort. Median time to ART initiation was 68 days (interquartile range 14-494) for BTA and 9 days (interquartile range 0-28) for TA (P < 0.0001), with 9 (5%) undergoing same-day initiation in BTA compared with 50 (37%) in TA (P < 0.0001). Before ART initiation, 59% in the BTA reported at least one health condition compared with 35% in the TA cohort (P < 0.0001). Although overall loss to follow-up was similar between cohorts (BTA: 13%, TA: 8%, P = 0.18), loss to follow-up before ART was significantly higher in the BTA (8%) compared with the TA cohort (2%) (P = 0.02). CONCLUSIONS: Nearly 90% of Rwandan children started on ART within 1 year of enrollment, most within 1 month, with greater than 90% retention after implementation of TA. TA was also associated with fewer morbidities. |
Delays in fast track ART initiation and reasons for not starting treatment among eligible children in Eastern Cape, South Africa
Teasdale CA , Yuengling KA , Mutiti A , Arpadi S , Nxele M , Pepeta L , Mogashoa M , Rivadeneira ED , Abrams EJ . AIDS 2019 33 (13) 2099-2101 We report data from an observational cohort of South African children living with HIV <12 years of age eligible for fast track ART (rapid) initiation. We found that less than half those eligible for rapid ART initiation based on immunologic and disease status started treatment within one week. |
Delays in fast track ART initiation and reasons for not starting treatment among eligible children in Eastern Cape, South Africa
Teasdale CA , Yuengling KA , Mutiti A , Arpadi S , Nxele M , Pepeta L , Mogashoa M , Rivadeneira ED , Abrams EJ . AIDS 2019 33 (13) 2099-2101 We report data from an observational cohort of South African children living with HIV <12 years of age eligible for fast track ART (rapid) initiation. We found that less than half those eligible for rapid ART initiation based on immunologic and disease status started treatment within one week. |
HIV viral suppression and longevity among a cohort of children initiating antiretroviral therapy in Eastern Cape, South Africa
Teasdale CA , Sogaula N , Yuengling KA , Wang C , Mutiti A , Arpadi S , Nxele M , Pepeta L , Mogashoa M , Rivadeneira ED , Abrams EJ . J Int AIDS Soc 2018 21 (8) e25168 INTRODUCTION: There are limited data on viral suppression (VS) in children with HIV receiving antiretroviral therapy (ART) in routine care in low-resource settings. We examined VS in a cohort of children initiating ART in routine HIV care in Eastern Cape Province, South Africa. METHODS: The Pediatric Enhanced Surveillance Study enrolled HIV-infected ART eligibility children zero to twelve years at five health facilities from 2012 to 2014. All children received routine HIV care and treatment services and attended quarterly study visits for up to 24 months. Time to VS among those starting treatment was measured from ART start date to first viral load (VL) result <1000 and VL <50 copies/mL using competing risk estimators (death as competing risk). Multivariable sub-distributional hazards models examined characteristics associated with VS and VL rebound following suppression among those with a VL >30 days after the VS date. RESULTS: Of 397 children enrolled, 349 (87.9%) started ART: 118 (33.8%) children age <12 months, 122 (35.0%) one to five years and 109 (31.2%) six to twelve years. At study enrolment, median weight-for-age z-score (WAZ) was -1.7 (interquartile range (IQR):-3.1 to -0.4) and median log VL was 5.6 (IQR: 5.0 to 6.2). Cumulative incidence of VS <1000 copies/mL at six, twelve and twenty-four months was 57.6% (95% CI 52.1 to 62.7), 78.7% (95% CI 73.7 to 82.9) and 84.0% (95% CI 78.9 to 87.9); for VS <50 copies/mL: 40.3% (95% CI 35.0 to 45.5), 63.9% (95% CI 58.2 to 69.0) and 72.9% (95% CI 66.9 to 78.0). At 12 months only 46.6% (95% CI 36.6 to 56.0) of children <12 months had achieved VS <50 copies/mL compared to 76.9% (95% CI 67.9 to 83.7) of children six to twelve years (p < 0.001). In multivariable models, children with VL >1 million copies/mL at ART initiation were half as likely to achieve VS <50 copies/mL (adjusted sub-distributional hazards 0.50; 95% CI 0.36 to 0.71). Among children achieving VS <50 copies/mL, 37 (19.7%) had VL 50 to 1000 copies/mL and 31 (16.5%) had a VL >1000 copies/mL. Children <12 months had twofold increased risk of VL rebound to VL >1000 copies/mL (adjusted relative risk 2.03, 95% CI: 1.10 to 3.74) compared with six to twelve year olds. CONCLUSIONS: We found suboptimal VS among South African children initiating treatment and high proportions experiencing VL rebound, particularly among younger children. Greater efforts are needed to ensure that all children achieve optimal outcomes. |
Strategies for identifying and linking HIV-infected infants, children, and adolescents to HIV treatment services in resource limited settings
Medley AM , Hrapcak S , Golin RA , Dziuban EJ , Watts H , Siberry GK , Rivadeneira ED , Behel S . J Acquir Immune Defic Syndr 2018 78 Suppl 2 S98-s106 Many children living with HIV in resource-limited settings remain undiagnosed and at risk for HIV-related mortality and morbidity. This article describes 5 key strategies for strengthening HIV case finding and linkage to treatment for infants, children, and adolescents. These strategies result from lessons learned during the Accelerating Children's HIV/AIDS Treatment Initiative, a public-private partnership between the President's Emergency Plan for AIDS Relief (PEPFAR) and the Children's Investment Fund Foundation (CIFF). The 5 strategies include (1) implementing a targeted mix of HIV case finding approaches (eg, provider-initiated testing and counseling within health facilities, optimization of early infant diagnosis, index family testing, and integration of HIV testing within key population and orphan and vulnerable children programs); (2) addressing the unique needs of adolescents; (3) collecting and using data for program improvement; (4) fostering a supportive political and community environment; and (5) investing in health system-strengthening activities. Continued advocacy and global investments are required to eliminate AIDS-related deaths among children and adolescents. |
Trends in antiretroviral therapy eligibility and coverage among children aged <15 years with HIV infection - 20 PEPFAR-supported sub-Saharan African countries, 2012-2016
Burrage A , Patel M , Mirkovic K , Dziuban E , Teferi W , Broyles L , Rivadeneira E . MMWR Morb Mortal Wkly Rep 2018 67 (19) 552-555 Rapid disease progression and associated opportunistic infections contribute to high mortality rates among children aged <15 years with human immunodeficiency virus (HIV) infection (1). Antiretroviral therapy (ART) has decreased childhood HIV-associated morbidity and mortality rates over the past decade (2). As accumulating evidence revealed lower HIV-associated mortality with early ART initiation, the World Health Organization (WHO) guidelines broadened ART eligibility for children with HIV infection (2). Age at ART initiation for children with HIV infection expanded sequentially in the 2010, 2013, and 2016 WHO guidelines to include children aged <2, <5, and <15 years, respectively, regardless of clinical or immunologic status (3-5). The United States President's Emergency Plan for AIDS Relief (PEPFAR) has supported ART for children with HIV infection since 2003 and, informed by the WHO guidelines and a growing evidence base, PEPFAR-supported countries have adjusted their national pediatric guidelines. To understand the lag between guideline development and implementation, as well as the ART coverage gap, CDC assessed national pediatric HIV guidelines and analyzed Joint United Nations Programme on HIV and AIDS (acquired immunodeficiency syndrome; UNAIDS) data on children aged <15 years with HIV infection and the numbers of these children on ART. Timeliness of WHO pediatric ART guideline adoption varied by country; >50% of children with HIV infection are not receiving ART, underscoring the importance of strengthening case finding and linkage to HIV treatment in pediatric ART programs. |
Impact of human immunodeficiency virus drug resistance on treatment of human immunodeficiency virus infection in children in low- and middle-income countries
Siberry GK , Amzel A , Ramos A , Rivadeneira ED . J Infect Dis 2017 216 S838-S842 Children living with human immunodeficiency virus (HIV) in low- and middle-income countries (LMICs) experience higher rates of virologic failure than adults. Human immunodeficiency virus drug resistance (HIVDR) plays a major role in pediatric HIV treatment failure because nonsuppressive maternal antiretroviral therapy (ART) during pregnancy and breastfeeding as well as infant antiretroviral prophylaxis lead to high rates of pretreatment drug resistance to regimens most commonly used in children living with HIV. Lack of availability of durable, potent drugs in child-friendly formulations in LMICs and adherence difficulties contribute to acquired drug resistance during treatment. Optimizing drugs available for treating children living with HIV in LMICs, providing robust adherence support, and ensuring virologic monitoring for children receiving ART are essential for reducing HIVDR and improving treatment outcomes for children living with HIV in LMICs. |
Performance characteristics of finger-stick dried blood spots (DBS) on the determination of human immunodeficiency virus (HIV) treatment failure in a pediatric population in Mozambique
Chang J , de Sousa A , Sabatier J , Assane M , Zhang G , Bila D , Vaz P , Alfredo C , Cossa L , Bhatt N , Koumans EH , Yang C , Rivadeneira E , Jani I , Houston JC . PLoS One 2017 12 (7) e0181054 Quantitative plasma viral load (VL) at 1000 copies /mL was recommended as the threshold to confirm antiretroviral therapy (ART) failure by the World Health Organization (WHO). Because of ongoing challenges of using plasma for VL testing in resource-limited settings (RLS), especially for children, this study collected 717 DBS and paired plasma samples from children receiving ART ≥1 year in Mozambique and compared the performance of DBS using Abbott's VL test with a paired plasma sample using Roche's VL test. At a cut-off of 1000 copies/mL, sensitivity of DBS using Abbott DBS VL test was 79.9%, better than 71.0% and 63.9% at 3000 and 5000 copies/mL, respectively. Specificities were 97.6%, 98.8%, 99.3% at 1000, 3000, and 5000 copies/mL, respectively. The Kappa value at 1000 copies/mL, 0.80 (95% CI: 0.73, 0.87), was higher than 0.73 (95% CI: 0.66, 0.80) and 0.66 (95% CI: 0.59, 0.73) at 3000, 5000 copies/mL, respectively, also indicating better agreement. The mean difference between the DBS and plasma VL tests with 95% limits of agreement by Bland-Altman was 0.311 (-0.908, 1.530). Among 73 children with plasma VL between 1000 to 5000 copies/mL, the DBS results were undetectable in 53 at the 1000 copies/mL threshold. While one DBS sample in the Abbott DBS VL test may be an alternative method to confirm ART failure at 1000 copies/mL threshold when a plasma sample is not an option for treatment monitoring, because of sensitivity concerns between 1,000 and 5,000 copies/ml, two DBS samples may be preferred accompanied by careful patient monitoring and repeat testing. |
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