INTRODUCTION: HIV replication leads to a change in lymphocyte phenotypes that impairs immune protection against opportunistic infections. We examined current HIV replication as an independent risk factor for tuberculosis (TB). METHODS: We included people living with HIV from 25 European cohorts 1983-2015. Individuals <16 years or with previous TB were excluded. Person-time was calculated from enrolment (baseline) to the date of TB diagnosis or last follow-up information. We used adjusted Poisson regression and general additive regression models. RESULTS: We included 272,548 people with a median follow-up of 5.9 years (interquartile range [IQR] 2.3-10.9). At baseline, the median CD4 cell count was 355 cells/μL (IQR 193-540) and the median HIV-RNA level 22,000 copies/mL (IQR 1,300-103,000). During 1,923,441 person-years of follow-up, 5,956 (2.2%) people developed TB. Overall, TB incidence was 3.1 per 1,000 person-years (95% confidence interval [CI] 3.02-3.18) and was four times higher in patients with HIV-RNA levels of 10,000 compared with levels <400 copies/mL in any CD4 stratum. CD4 and HIV-RNA time-updated analyses showed that the association between HIV-RNA and TB incidence was independent of CD4. The TB incidence rate ratio for people born in TB-endemic countries compared with those born in Europe was 1.8 (95% CI 1.5-2.2). CONCLUSIONS: Our results indicate that ongoing HIV replication (suboptimal HIV control) is an important risk factor for TB, independent of CD4 count. Those at highest risk of TB are people from TB-endemic countries. Close monitoring and TB preventive therapy for people with suboptimal HIV control is important.
- MeSH
- dospělí MeSH
- HIV infekce * epidemiologie imunologie komplikace MeSH
- incidence MeSH
- kohortové studie MeSH
- lidé středního věku MeSH
- lidé MeSH
- počet CD4 lymfocytů MeSH
- replikace viru MeSH
- rizikové faktory MeSH
- RNA virová MeSH
- tuberkulóza * epidemiologie imunologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa MeSH
BACKGROUND: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. METHODS: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1-4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models' predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models' forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models' past predictive performance. RESULTS: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models' forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models' forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models' forecasts of deaths (N=763 predictions from 20 models). Across a 1-4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. CONCLUSIONS: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. FUNDING: AA, BH, BL, LWa, MMa, PP, SV funded by 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 respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by 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 NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (https://www.nfdi4health.de/task-force-covid-19-2) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).
- MeSH
- COVID-19 * diagnóza epidemiologie MeSH
- epidemie * MeSH
- infekční nemoci * MeSH
- lidé MeSH
- předpověď MeSH
- retrospektivní studie MeSH
- statistické modely MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- Research Support, U.S. Gov't, P.H.S. MeSH
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. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk 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.
- MeSH
- COVID-19 * mortalita MeSH
- lidé MeSH
- pandemie MeSH
- pravděpodobnost MeSH
- předpověď MeSH
- správnost dat MeSH
- veřejné zdravotnictví trendy MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Spojené státy americké MeSH
- Publikační typ
- abstrakt z konference MeSH
INTRODUCTION: Since the beginning of the HIV epidemic in resource-rich countries, Pneumocystis jirovecii pneumonia (PjP) is one of the most frequent opportunistic AIDS-defining infections. The Collaboration of Observational HIV Epidemiological Research Europe (COHERE) has shown that primary Pneumocystis jirovecii Pneumonia (PjP) prophylaxis can be safely withdrawn in patients with CD4 counts of 100 to 200 cells/µL if plasma HIV-RNA is suppressed on combination antiretroviral therapy. Whether this holds true for secondary prophylaxis is not known, and this has proved difficult to determine due to the much lower population at risk. METHODS: We estimated the incidence of secondary PjP by including patient data collected from 1998 to 2015 from the COHERE cohort collaboration according to time-updated CD4 counts, HIV-RNA and use of PjP prophylaxis in persons >16 years of age. We fitted a Poisson generalized additive model in which the smoothed effect of CD4 was modelled by a restricted cubic spline, and HIV-RNA was stratified as low (<400), medium (400 to 10,000) or high (>10,000copies/mL). RESULTS: There were 373 recurrences of PjP during 74,295 person-years (py) in 10,476 patients. The PjP incidence in the different plasma HIV-RNA strata differed significantly and was lowest in the low stratum. For patients off prophylaxis with CD4 counts between 100 and 200 cells/µL and HIV-RNA below 400 copies/mL, the incidence of recurrent PjP was 3.9 (95% CI: 2.0 to 5.8) per 1000 py, not significantly different from patients on prophylaxis in the same stratum (1.9, 95% CI: 0.1 to 3.7). CONCLUSIONS: HIV viraemia importantly affects the risk of recurrent PjP. In virologically suppressed patients on ART with CD4 counts of 100 to 200/µL, the incidence of PjP off prophylaxis is below 10/1000 py. Secondary PjP prophylaxis may be safely withheld in such patients. While European guidelines recommend discontinuing secondary PjP prophylaxis only if CD4 counts rise above 200 cells/mL, the latest US Guidelines consider secondary prophylaxis discontinuation even in patients with a CD4 count above 100 cells/µL and suppressed viral load. Our results strengthen and support this US recommendation.
- MeSH
- dospělí MeSH
- HIV infekce * komplikace farmakoterapie MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- Pneumocystis carinii * MeSH
- pneumocystová pneumonie * epidemiologie prevence a kontrola MeSH
- počet CD4 lymfocytů MeSH
- viremie epidemiologie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- Publikační typ
- časopisecké články MeSH
- pozorovací studie MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Evropa MeSH
BACKGROUND & AIMS: Robust data on hepatocellular carcinoma (HCC) incidence among HIV/hepatitis B virus (HBV)-coinfected individuals on antiretroviral therapy (ART) are needed to inform HCC screening strategies. We aimed to evaluate the incidence and risk factors of HCC among HIV/HBV-coinfected individuals on tenofovir disoproxil fumarate (TDF)-containing ART in a large multi-cohort study. METHODS: We included all HIV-infected adults with a positive hepatitis B surface antigen test followed in 4 prospective European cohorts. The primary outcome was the occurrence of HCC. Demographic and clinical information was retrieved from routinely collected data, and liver cirrhosis was defined according to results from liver biopsy or non-invasive measurements. Multivariable Poisson regression was used to assess HCC risk factors. RESULTS: A total of 3,625 HIV/HBV-coinfected patients were included, of whom 72% had started TDF-containing ART. Over 32,673 patient-years (py), 60 individuals (1.7%) developed an HCC. The incidence of HCC remained stable over time among individuals on TDF, whereas it increased steadily among those not on TDF. Among individuals on TDF, the incidence of HCC was 5.9 per 1,000 py (95% CI 3.60-9.10) in cirrhotics and 1.17 per 1,000 py (0.56-2.14) among non-cirrhotics. Age at initiation of TDF (adjusted incidence rate ratio per 10-year increase: 2.2, 95% CI 1.6-3.0) and the presence of liver cirrhosis (4.5, 2.3-8.9) were predictors of HCC. Among non-cirrhotic individuals, the incidence of HCC was only above the commonly used screening threshold of 2 cases per 1,000 py in patients aged >45 years old at TDF initiation. CONCLUSIONS: Whereas the incidence of HCC was high in cirrhotic HIV/HBV-coinfected individuals, it remained below the HCC screening threshold in patients without cirrhosis who started TDF aged <46 years old. LAY SUMMARY: We investigated the incidence of hepatocellular carcinoma in HIV/hepatitis B virus-coinfected individuals from a large multi-cohort study in Europe. Over 32,673 patient-years, 60 individuals (1.7%) developed hepatocellular carcinoma. The incidence of hepatocellular carcinoma remained low in patients without cirrhosis, who started on tenofovir disoproxil fumarate when aged <46 years old.
- MeSH
- dospělí MeSH
- hepatitida B - antigeny povrchové analýza MeSH
- hepatitida B farmakoterapie virologie MeSH
- hepatocelulární karcinom epidemiologie MeSH
- HIV * MeSH
- incidence MeSH
- koinfekce farmakoterapie virologie MeSH
- látky proti HIV terapeutické užití MeSH
- lidé středního věku MeSH
- lidé MeSH
- nádory jater epidemiologie MeSH
- následné studie MeSH
- oportunní infekce doprovázející AIDS farmakoterapie virologie MeSH
- prospektivní studie MeSH
- tenofovir terapeutické užití MeSH
- virus hepatitidy B imunologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Fire is a major factor controlling global carbon (C) and nitrogen (N) cycling. While direct C and N losses caused by combustion have been comparably well established, important knowledge gaps remain on postfire N losses. Here, we quantified both direct C and N combustion losses as well as postfire gaseous losses (N2 O, NO and N2 ) and N leaching after a high-intensity experimental fire in an old shrubland in central Spain. Combustion losses of C and N were 9.4 Mg C/ha and 129 kg N/ha, respectively, representing 66% and 58% of initial aboveground vegetation and litter stocks. Moreover, fire strongly increased soil mineral N concentrations by several magnitudes to a maximum of 44 kg N/ha 2 months after the fire, with N largely originating from dead soil microbes. Postfire soil emissions increased from 5.4 to 10.1 kg N ha-1 year-1 for N2 , from 1.1 to 1.9 kg N ha-1 year-1 for NO and from 0.05 to 0.2 kg N ha-1 year-1 for N2 O. Maximal leaching losses occurred 2 months after peak soil mineral N concentrations, but remained with 0.1 kg N ha-1 year-1 of minor importance for the postfire N mass balance. 15 N stable isotope labelling revealed that 33% of the mineral N produced by fire was incorporated in stable soil N pools, while the remainder was lost. Overall, our work reveals significant postfire N losses dominated by emissions of N2 that need to be considered when assessing fire effects on ecosystem N cycling and mass balance. We propose indirect N gas emissions factors for the first postfire year, equalling to 7.7% (N2 -N), 2.7% (NO-N) and 5.0% (N2 O-N) of the direct fire combustion losses of the respective N gas species.
A new test of the proportional hazards assumption in the Cox model is proposed. The idea is based on Neyman's smooth tests. The Cox model with proportional hazards (i.e. time-constant covariate effects) is embedded in a model with a smoothly time-varying covariate effect that is expressed as a combination of some basis functions (e.g., Legendre polynomials, cosines). Then the smooth test is the score test for significance of these artificial covariates. Furthermore, we apply a modification of Schwarz's selection rule to choosing the dimension of the smooth model (the number of the basis functions). The score test is then used in the selected model. In a simulation study, we compare the proposed tests with standard tests based on the score process.
