Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-13 (of 13 Records) |
Query Trace: McIntyre AF[original query] |
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Triangulating truth and reaching consensus on population size, prevalence, and more: Modeling study
Fellows IE , Corcoran C , McIntyre AF . JMIR Public Health Surveill 2024 10 e48738 BACKGROUND: Population size, prevalence, and incidence are essential metrics that influence public health programming and policy. However, stakeholders are frequently tasked with setting performance targets, reporting global indicators, and designing policies based on multiple (often incongruous) estimates of these variables, and they often do so in the absence of a formal, transparent framework for reaching a consensus estimate. OBJECTIVE: This study aims to describe a model to synthesize multiple study estimates while incorporating stakeholder knowledge, introduce an R Shiny app to implement the model, and demonstrate the model and app using real data. METHODS: In this study, we developed a Bayesian hierarchical model to synthesize multiple study estimates that allow the user to incorporate the quality of each estimate as a confidence score. The model was implemented as a user-friendly R Shiny app aimed at practitioners of population size estimation. The underlying Bayesian model was programmed in Stan for efficient sampling and computation. RESULTS: The app was demonstrated using biobehavioral survey-based population size estimates (and accompanying confidence scores) of female sex workers and men who have sex with men from 3 survey locations in a country in sub-Saharan Africa. The consensus results incorporating confidence scores are compared with the case where they are absent, and the results with confidence scores are shown to perform better according to an app-supplied metric for unaccounted-for variation. CONCLUSIONS: The utility of the triangulator model, including the incorporation of confidence scores, as a user-friendly app is demonstrated using a use case example. Our results offer empirical evidence of the model's effectiveness in producing an accurate consensus estimate and emphasize the significant impact that the accessible model and app offer for public health. It offers a solution to the long-standing problem of synthesizing multiple estimates, potentially leading to more informed and evidence-based decision-making processes. The Triangulator has broad utility and flexibility to be adapted and used in various other contexts and regions to address similar challenges. |
Development of a standards-based city-wide health information exchange for public health in response to COVID-19 (preprint)
Hota B , Casey P , McIntyre AF , Khan J , Rab S , Chopra A , Lateef O , Layden JE . medRxiv 2020 2020.08.12.20173559 Background Disease surveillance is a critical function of public health, provides essential information about disease burden, clinical and epidemiologic parameters of disease, and is an important element to effective and timely case and contact tracing. The COVID-19 pandemic has demonstrated the essential role these functions have to preserve public health. Syndromic surveillance, electronic laboratory reporting in the meaningful use program, and the growth of the National Healthcare Safety Network (NHSN) have created linkages between hospitals, commercial labs, and public health that can collect and organize data, often through EHR and order workflows, to improve the timeliness and completeness of reporting. In theory, the standard data formats and exchange methods provided by meaningful use should enable rapid healthcare data exchange in the setting of disruptive healthcare events like a pandemic. In reality, access to data remains challenging, and even if available, often lack conformity to regulated standards.Objective We sought to use regulated interoperability standards already in production to generate regional bed capacity awareness, enhance the capture of epidemiological risk factors and clinical variables among COVID-19 tested patients, and reduce the administrative burden of reporting for stakeholders in a manner that could be replicated by other public health agencies.Methods Following a public health order mandating data submission, we developed technical infrastructure to combine multiple data feeds from electronic health record systems. We measured the completeness of each feed, and the match rate between feeds.Results A cloud-based environment was created that received data from electronic lab reporting, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project beginning to aid in consensus and principles for data use. 88,906 total persons from CCDA data among 14 facilities, and 408,741 persons from ELR records among 88 facilities, were submitted. Fields routinely absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. CCDA data provided an improvement in the quality of data available for surveillance and was highly complete with <5% for all records types with the exception of patient cell phone. 90.1% of records could be matched between CCDA and ELR feeds.Conclusions We describe the development of a city-wide public health data hub for the surveillance of COVID-19 infection. We were able to assess the completeness of existing ELR feeds, augment these feeds with CCDA documents, establish secure transfer methods for data exchange, develop cloud-based architecture to enable secure data storage and analytics, and produced meaningful dashboards for the monitoring of capacity and disease burden. We see this public health and clinical data registry as an informative example of the power of common standards across electronic records, and a potential template for future extension of the use of standards to improve public health surveillance.Competing Interest StatementThe authors have declared no competing interest.Funding StatementNo external funding was received for this work.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:This work was conducted under a public health exemption through the Chicago Department of Public HealthAll 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 retrospectiv ly, 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.YesThe data used for this study was reported to the health department and is not publicly available at this time. |
Key population size estimation to guide HIV epidemic responses in Nigeria: Bayesian analysis of 3-source capture-recapture data
McIntyre AF , Mitchell A , Stafford KA , Nwafor SU , Lo J , Sebastian V , Schwitters A , Swaminathan M , Dalhatu I , Charurat M . JMIR Public Health Surveill 2022 8 (10) e34555 BACKGROUND: Nigeria has the fourth largest burden of HIV globally. Key populations, including female sex workers, men who have sex with men, and people who inject drugs, are more vulnerable to HIV than the general population due to stigmatized and criminalized behaviors. Reliable key population size estimates are needed to guide HIV epidemic response efforts. OBJECTIVE: The objective of our study was to use empirical methods for sampling and analysis to improve the quality of population size estimates of female sex workers, men who have sex with men, and people who inject drugs in 7 states (Akwa Ibom, Benue, Cross River, Lagos, Nasarawa, Rivers, and the Federal Capital Territory) of Nigeria for program planning and to demonstrate improved statistical estimation methods. METHODS: From October to December 2018, we used 3-source capture-recapture to produce population size estimates in 7 states in Nigeria. Hotspots were mapped before 3-source capture-recapture started. We sampled female sex workers, men who have sex with men, and people who inject drugs during 3 independent captures about one week apart. During hotspot encounters, key population members were offered inexpensive, memorable objects unique to each capture round. In subsequent rounds, key population members were offered an object and asked to identify objects received during previous rounds (if any). Correct responses were tallied and recorded on tablets. Data were aggregated by key population and state for analysis. Median population size estimates were derived using Bayesian nonparametric latent-class models with 80% highest density intervals. RESULTS: Overall, we sampled approximately 310,000 persons at 9015 hotspots during 3 independent captures. Population size estimates for female sex workers ranged from 14,500 to 64,300; population size estimates for men who have sex with men ranged from 3200 to 41,400; and population size estimates for people who inject drugs ranged from 3400 to 30,400. CONCLUSIONS: This was the first implementation of these 3-source capture-recapture methods in Nigeria. Our population size estimates were larger than previously documented for each key population in all states. The Bayesian models account for factors, such as social visibility, that influence heterogeneous capture probabilities, resulting in more reliable population size estimates. The larger population size estimates suggest a need for programmatic scale-up to reach these populations, which are at highest risk for HIV. |
Development of a standards-based city-wide health information exchange for public health in response to COVID-19.
Hota B , Casey P , McIntyre AF , Khan J , Rab S , Chopra A , Lateef O , Layden JE . JMIR Public Health Surveill 2022 8 (9) e35973 BACKGROUND: Disease surveillance is a critical function of public health, provides essential information about disease burden, clinical and epidemiologic parameters of disease, and is an important element of effective and timely case and contact tracing. The COVID-19 pandemic demonstrates the essential role of disease surveillance in preserving public health. In theory, the standard data formats and exchange methods provided by EHR meaningful use should enable rapid healthcare data exchange in the setting of disruptive healthcare events like a pandemic. In reality, access to data remains challenging, and, even if available, often lacks conformity to regulated standards. As a result of the COVID-19 pandemic, we developed a regional data hub to enhance public health surveillance. OBJECTIVE: We sought to use regulated interoperability standards already in production to generate awareness of regional bed capacity and enhance the capture of epidemiological risk factors and clinical variables among patients tested for SARS-CoV-2. We describe the technical and operational components, governance model, and timelines required to implement the public health order which mandated electronic reporting of data from EHRs among hospitals in the Chicago jurisdiction. We also evaluate the data sources, infrastructure requirements and the completeness of data supplied to the platform and the capacity to link these sources. METHODS: Following a public health order mandating data submission by all acute care hospitals in Chicago, we developed the technical infrastructure to combine multiple data feeds from those EHR systems. We measured the completeness of each feed and the match rate between feeds. RESULTS: A cloud-based environment was created that received ELR, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project initiation to aid in consensus and principles for data use. Data from 88,906 persons from consolidated clinical data architecture (CCDA) records among 14 facilities, and 408,741 persons from ELR records among 88 facilities, were submitted. Most (90.1%) records could be matched between CCDA and ELR feeds. Data fields absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. Less than 5% of CCDA data fields were empty. Merging CCDA with ELR data improved race, ethnicity, comorbidity, and hospitalization information data availability. CONCLUSIONS: We describe the development of a city-wide public health data hub for the surveillance of SARS-CoV-2 infection. We were able to assess the completeness of existing ELR feeds, augment these feeds with CCDA documents, establish secure transfer methods for data exchange, develop cloud-based architecture to enable secure data storage and analytics, and produce dashboards for monitoring of capacity and disease burden. We consider this public health and clinical data registry as an informative example of the power of common standards across EHR and a potential template for future use of standards to improve public health surveillance. |
Population Size Estimation From Capture-Recapture Studies Using shinyrecap: Design and Implementation of a Web-Based Graphical User Interface.
McIntyre AF , Fellows IE , Gutreuter S , Hladik W . JMIR Public Health Surveill 2022 8 (4) e32645 BACKGROUND: Population size estimates (PSE) provide critical information in determining resource allocation for HIV services geared toward those at high risk of HIV, including female sex workers, men who have sex with men, and people who inject drugs. Capture-recapture (CRC) is often used to estimate the size of these often-hidden populations. Compared with the commonly used 2-source CRC, CRC relying on 3 (or more) samples (3S-CRC) can provide more robust PSE but involve far more complex statistical analysis. OBJECTIVE: This study aims to design and describe the Shiny application (shinyrecap), a user-friendly interface that can be used by field epidemiologists to produce PSE. METHODS: shinyrecap is built on the Shiny web application framework for R. This allows it to seamlessly integrate with the sophisticated CRC statistical packages (eg, Rcapture, dga, LCMCR). Additionally, the application may be accessed online or run locally on the user's machine. RESULTS: The application enables users to engage in sample size calculation based on a simulation framework. It assists in the proper formatting of collected data by providing a tool to convert commonly used formats to that used by the analysis software. A wide variety of methodologies are supported by the analysis tool, including log-linear, Bayesian model averaging, and Bayesian latent class models. For each methodology, diagnostics and model checking interfaces are provided. CONCLUSIONS: Through a use case, we demonstrated the broad utility of this powerful tool with 3S-CRC data to produce PSE for female sex workers in a subnational unit of a country in sub-Saharan Africa. |
Key population hotspots in Nigeria for targeted HIV program planning: Mapping, validation, and reconciliation
Lo J , Nwafor SU , Schwitters AM , Mitchell A , Sebastian V , Stafford KA , Ezirim I , Charurat M , McIntyre AF . JMIR Public Health Surveill 2021 7 (2) e25623 BACKGROUND: With the fourth highest HIV burden globally, Nigeria is characterized as having a mixed HIV epidemic with high HIV prevalence among key populations, including female sex workers, men who have sex with men, and people who inject drugs. Reliable and accurate mapping of key population hotspots is necessary for strategic placement of services and allocation of limited resources for targeted interventions. OBJECTIVE: We aimed to map and develop a profile for the hotspots of female sex workers, men who have sex with men, and people who inject drugs in 7 states of Nigeria to inform HIV prevention and service programs and in preparation for a multiple-source capture-recapture population size estimation effort. METHODS: In August 2018, 261 trained data collectors from 36 key population-led community-based organizations mapped, validated, and profiled hotspots identified during the formative assessment in 7 priority states in Nigeria designated by the United States President's Emergency Plan for AIDS Relief. Hotspots were defined as physical venues wherein key population members frequent to socialize, seek clients, or engage in key population-defining behaviors. Hotspots were visited by data collectors, and each hotspot's name, local government area, address, type, geographic coordinates, peak times of activity, and estimated number of key population members was recorded. The number of key population hotspots per local government area was tabulated from the final list of hotspots. RESULTS: A total of 13,899 key population hotspots were identified and mapped in the 7 states, that is, 1297 in Akwa Ibom, 1714 in Benue, 2666 in Cross River, 2974 in Lagos, 1550 in Nasarawa, 2494 in Rivers, and 1204 in Federal Capital Territory. The most common hotspots were those frequented by female sex workers (9593/13,899, 69.0%), followed by people who inject drugs (2729/13,899, 19.6%) and men who have sex with men (1577/13,899, 11.3%). Although hotspots were identified in all local government areas visited, more hotspots were found in metropolitan local government areas and state capitals. CONCLUSIONS: The number of key population hotspots identified in this study is more than that previously reported in similar studies in Nigeria. Close collaboration with key population-led community-based organizations facilitated identification of many new and previously undocumented key population hotspots in the 7 states. The smaller number of hotspots of men who have sex with men than that of female sex workers and that of people who inject drugs may reflect the social pressure and stigma faced by this population since the enforcement of the 2014 Same Sex Marriage (Prohibition) Act, which prohibits engaging in intimate same-sex relationships, organizing meetings of gays, or patronizing gay businesses. |
Identification of presymptomatic and asymptomatic cases using cohort-based testing approaches at a large correctional facility - Chicago, Illinois, USA, May 2020.
Wadhwa A , Fisher KA , Silver R , Koh M , Arons MM , Miller DA , McIntyre AF , Vuong JT , Kim K , Takamiya M , Binder AM , Tate JE , Armstrong PA , Black SR , Mennella CC , Levin R , Gubser J , Jones B , Welbel SF , Moonan PK , Curran K , Ghinai I , Doshi R , Zawitz CJ . Clin Infect Dis 2020 72 (5) e128-e135 BACKGROUND: COVID-19 continues to cause significant morbidity and mortality worldwide. Correctional and detention facilities are at high risk of experiencing outbreaks. We aimed to evaluate cohort-based testing among detained persons exposed to laboratory-confirmed cases of SARS-CoV-2 in order to identify presymptomatic and asymptomatic cases. METHODS: During May 1-19, 2020, two testing strategies were implemented in 12 tiers or housing units of the Cook County Jail in Chicago, Illinois. Detained persons were approached to participate in serial testing (n=137) tests at 3 time points over 14 days (day 1, day 3-5, and day 13-14). The second group was offered a single test and interview at the end of a 14-day quarantine period (day 14 group) (n=87). RESULTS: A total of 224 detained persons were approached for participation and of these 194 (87%) participated in at least one interview, and 172 (77%) had at least one test. Of the 172 tested, 19 were positive for SARS-CoV-2. In the serial testing group, 17 (89%) new cases were detected, sixteen (84%) on day 1, one (5%) on days 3-5, and none on days 13-14; and, in day 14 group, two (11%) cases were identified. More than half (12/19; 63%) of the newly identified cases were pre-symptomatic or asymptomatic. CONCLUSION: Our findings highlight the utility of cohort-based testing promptly after initiating quarantine within a housing tier. Cohort-based testing efforts identified new SARS-CoV-2 asymptomatic and presymptomatic infections that may have been missed by symptom screening alone. |
Estimating the size of key populations in Kampala, Uganda: 3-source capture-recapture study
Doshi RH , Apodaca K , Ogwal M , Bain R , Amene E , Kiyingi H , Aluzimbi G , Musinguzi G , Serwadda D , McIntyre AF , Hladik W . JMIR Public Health Surveill 2019 5 (3) e12118 BACKGROUND: Key populations, including people who inject drugs (PWID), men who have sex with men (MSM), and female sex workers (FSW), are disproportionately affected by the HIV epidemic. Understanding the magnitude of, and informing the public health response to, the HIV epidemic among these populations requires accurate size estimates. However, low social visibility poses challenges to these efforts. OBJECTIVE: The objective of this study was to derive population size estimates of PWID, MSM, and FSW in Kampala using capture-recapture. METHODS: Between June and October 2017, unique objects were distributed to the PWID, MSM, and FSW populations in Kampala. PWID, MSM, and FSW were each sampled during 3 independent captures; unique objects were offered in captures 1 and 2. PWID, MSM, and FSW sampled during captures 2 and 3 were asked if they had received either or both of the distributed objects. All captures were completed 1 week apart. The numbers of PWID, MSM, and FSW receiving one or both objects were determined. Population size estimates were derived using the Lincoln-Petersen method for 2-source capture-recapture (PWID) and Bayesian nonparametric latent-class model for 3-source capture-recapture (MSM and FSW). RESULTS: We sampled 467 PWID in capture 1 and 450 in capture 2; a total of 54 PWID were captured in both. We sampled 542, 574, and 598 MSM in captures 1, 2, and 3, respectively. There were 70 recaptures between captures 1 and 2, 103 recaptures between captures 2 and 3, and 155 recaptures between captures 1 and 3. There were 57 MSM captured in all 3 captures. We sampled 962, 965, and 1417 FSW in captures 1, 2, and 3, respectively. There were 316 recaptures between captures 1 and 2, 214 recaptures between captures 2 and 3, and 235 recaptures between captures 1 and 3. There were 109 FSW captured in all 3 rounds. The estimated number of PWID was 3892 (3090-5126), the estimated number of MSM was 14,019 (95% credible interval (CI) 4995-40,949), and the estimated number of FSW was 8848 (95% CI 6337-17,470). CONCLUSIONS: Our population size estimates for PWID, MSM, and FSW in Kampala provide critical population denominator data to inform HIV prevention and treatment programs. The 3-source capture-recapture is a feasible method to advance key population size estimation. |
Outcomes of infants born to women with influenza A(H1N1)pdm09
Newsome K , Alverson CJ , Williams J , McIntyre AF , Fine AD , Wasserman C , Lofy KH , Acosta M , Louie JK , Jones-Vessey K , Stanfield V , Yeung A , Rasmussen SA . Birth Defects Res 2019 111 (2) 88-95 BACKGROUND: Pregnant women with influenza are more likely to have complications, but information on infant outcomes is limited. METHODS: Five state/local health departments collected data on outcomes of infants born to pregnant women with 2009 H1N1 influenza reported to the Centers for Disease Control and Prevention from April to December 2009. Collaborating sites linked information on pregnant women with confirmed 2009 H1N1 influenza, many who were severely ill, to their infants' birth certificates. Collaborators also collected birth certificate data from two comparison groups that were matched with H1N1-affected pregnancies on month of conception, sex, and county of residence. RESULTS: 490 pregnant women with influenza, 1,451 women without reported influenza with pregnancies in the same year, and 1,446 pregnant women without reported influenza with prior year pregnancies were included. Women with 2009 H1N1 influenza admitted to an intensive care unit (ICU; n = 64) were more likely to deliver preterm infants (<37 weeks), low birth weight infants, and infants with Apgar scores <=6 at 5 min than women in comparison groups (adjusted relative risk, aRR = 3.9 [2.7, 5.6], aRR = 4.6 [2.9, 7.5], and aRR = 8.7 [3.6, 21.2], for same year comparisons, respectively). Women with influenza who were not hospitalized and hospitalized women not admitted to the ICU did not have significantly elevated risks for adverse infant outcomes. CONCLUSIONS: Severely ill women with 2009 H1N1 influenza during pregnancy were more likely to have adverse birth outcomes than women without influenza, providing more support for influenza vaccination during pregnancy. |
CDC Pregnancy Flu Line: monitoring severe illness among pregnant women with influenza
Ailes EC , Newsome K , Williams JL , McIntyre AF , Jamieson DJ , Finelli L , Honein MA . Matern Child Health J 2013 18 (7) 1578-82 The Centers for Disease Control and Prevention implemented the Pregnancy Flu Line (PFL) during the influenza A(H1N1)pdm09 (pH1N1) pandemic and continued operation through the 2010-2011 influenza season to collect reports of intensive care unit (ICU) admissions and deaths among pregnant women with influenza. The system documented the severe impact of influenza on pregnant women during both seasons with 181 ICU/survivals and 37 deaths reported during the 2009 fall pandemic wave and 69 ICU/survivals and ten deaths reported in the subsequent influenza season (2010-2011). A health department survey suggests PFL participants perceived public health benefits and minimum time burdens. |
Seasonal influenza vaccination coverage - United States, 2009-10 and 2010-11
McIntyre AF , Gonzalez-Feliciano AG , Bryan LN , Santibanez TA , Williams WW , Singleton JA . MMWR Suppl 2013 62 (3) 65-8 Infection with influenza viruses can cause severe morbidity and mortality among all age groups. Children, particularly those aged <5 years, have the highest incidence of infection during epidemic periods; however, the highest rates of influenza-associated hospitalizations and deaths are among the elderly (aged ≥65 years), children aged <2 years, and those of any age with underlying medical conditions. Each year, influenza-related complications are estimated to result in more than 226,000 hospitalizations. During 1976-2006, estimates of influenza-associated deaths in the United States ranged from approximately 3,000 to an estimated 49,000 persons. Annual vaccination is the most effective strategy for preventing influenza virus infection and its complications. |
Potential influence of seasonal influenza vaccination requirement versus traditional vaccine promotion strategies on unvaccinated healthcare personnel
Thompson MG , McIntyre AF , Naleway AL , Black C , Kennedy ED , Ball S , Walker DK , Henkle EM , Gaglani MJ . Vaccine 2013 31 (37) 3915-21 In a prospective cohort study of 1670 healthcare personnel (HCP) providing direct patient care at Scott & White Healthcare in Texas and Kaiser Permanente Northwest in Oregon and Washington, we examined the potential impact of twelve vaccine promotion strategies on the likelihood of being vaccinated. Internet-based surveys were conducted at enrollment (Fall, 2010) and at post-season (Spring, 2011), which asked HCP whether twelve vaccination promotion strategies would make them "much less" to "much more" likely to be vaccinated next season (on a 5-point Likert scale). Overall, 366 of 1670 HCP (22%) were unvaccinated. Half (50%) of unvaccinated HCP self-reported that a vaccination requirement would make them more likely to be vaccinated and most (62%) identified at least one strategy other than a vaccination requirement that would make them more likely to be vaccinated. In sub-groups of unvaccinated HCPs with specific barriers to vaccination, about one in three (range=27-35%) indicated that interventions targeting specific vaccination barrier would increase the likelihood they would be vaccinated. However, in all cases, significantly more unvaccinated HCP reported that a vaccination requirement would increase the likelihood of vaccination than reported a targeted intervention would have this effect (range in difference scores=+11-23%). |
Pneumonia in US hospitalized patients with influenza-like illness: BioSense, 2007-2010
Benoit SR , Burkom H , McIntyre AF , Kniss K , Brammer L , Finelli L , Jain S . Epidemiol Infect 2012 141 (4) 1-11 SUMMARY: We used data from BioSense, a national electronic surveillance system, to describe pneumonia in hospitalized patients with influenza-like illness (ILI). Ninety-five hospitals from 20 states reported ICD-9-CM-coded inpatient final diagnosis data during the study period of September 2007 to February 2010. We compared the characteristics of persons with and without pneumonia among those with ILI-related hospitalizations. BioSense captured 26,987 ILI-related inpatient hospitalizations; 8979 (33%) had a diagnosis of pneumonia. Analysis of trends showed highest counts of pneumonia during the 2007-2008 season and the second 2009 pandemic wave. Pneumonia was more common with increasing age. Microbiology and pharmacy data were available for a subset of patients; 107 (5%) with pneumonia had a bloodstream infection and 17% of patients were prescribed antiviral treatment. Our findings demonstrate the potential utility of electronic healthcare data to track trends in ILI and pneumonia, identify risk factors for disease, identify bacteraemia in patients with pneumonia, and monitor antiviral use. |
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