Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19·1 million participants by NCD Risk Factor Collaboration, Zhou, B, Bentham, J, Di Cesare, M, Chen, Z, Key, T, Smith, M, Woodward, M

“…<strong>Methods:</strong> We pooled 1,479 population-based studies that had measured blood pressure on 19.1 million adults aged 18 years and older. We used a Bayesian hierarchical model to estimate trends from 1975 to 2015 in mean SBP and DBP, and prevalence of raised blood pressure for 200 countries. …”

National and Subnational Trend of Dental Caries of Permanent Teeth in Iran, 1990–2017 by Shervan Shoaee, Masoud Masinaei, Sahar Saeedi Moghaddam, Ahmad Sofi-Mahmudi, Hossein Hessari, Erfan Shamsoddin, Mohammad-Hossein Heydari, Bagher Larijani, Hossein Fakhrzadeh, Farshad Farzadfar

“…The data for missing spots were estimated using the spatiotemporal Bayesian hierarchical model. We used the bootstrap method in multilevel models to predict the uncertainty interval (UI) of the modelled results. …”
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Environmental risk factors and exposure to the zoonotic malaria parasite Plasmodium knowlesi across northern Sabah, Malaysia: a population-based cross-sectional survey by Fornace, Kimberly M, Brock, Paddy M, Tommy R Abidin, Grignard, Lynn, Herman, Lou S, Chua, Tock Hing, Sylvia Daim, William, Timothy, Patterson, Catriona L E B, Hall, Tom, Grigg, Matthew J, Anstey, Nicholas M, Tetteh, Kevin K A, Cox, Jonathan, Drakeley, Chris J

“…Proportions and configurations of land types were extracted from maps derived from satellite images; a data-mining approach was used to select variables. A Bayesian hierarchical model for P knowlesi seropositivity was developed, incorporating questionnaire data about individual and household-level risk factors with selected landscape factors. …”
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Spatial pattern of isoniazid-resistant tuberculosis and its associated factors among a population with migrants in China: a retrospective population-based study by Hongyin Zhang, Ruoyao Sun, Zheyuan Wu, Zheyuan Wu, Yueting Liu, Meiru Chen, Jinrong Huang, Yixiao Lv, Fei Zhao, Fei Zhao, Fei Zhao, Yangyi Zhang, Yangyi Zhang, Yangyi Zhang, Minjuan Li, Hongbing Jiang, Yiqiang Zhan, Jimin Xu, Yanzi Xu, Jianhui Yuan, Yang Zhao, Xin Shen, Xin Shen, Chongguang Yang, Chongguang Yang, Chongguang Yang

“…Spatial autocorrelation was explored using Global Moran’s I and Getis-Ord Gi∗ statistics. A Bayesian hierarchical model with spatial effects was developed using the INLA package in R software to identify potential factors associated with Hr-TB at the county level.ResultsA total of 8,865 TB patients with DST were included in this analysis. …”
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Worldwide trends in diabetes since 1980: a pooled analysis of 751 population - based studies with 4.4 million participants by Gyanchand Rampal, Lekhraj Rampal

“…Methods: We pooled data from population-based studies that had collected data on diabetes through measurement of its biomarkers. We used a Bayesian hierarchical model to estimate trends in diabetes prevalence—defined as fasting plasma glucose of 7·0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs—in 200 countries and territories in 21 regions, by sex and from 1980 to 2014. …”
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Stroke care trends during COVID-19 pandemic in Zanjan Province, Iran from the CASCADE initiative: statistical analysis plan and preliminary results by Ghoreishi, Abdoreza, Arsang-Jang, Shahram, Sabaa-Ayoun, Ziad, Yassi, Nawaf, Sylaja, P. N., Akbari, Yama, Divani, Afshin A., Biller, Jose, Phan, Thanh, Steinwender, Sandy, Silver, Brian, Zand, Ramin, Basri, Hamidon, Iqbal, Omer M., Ranta, Annemarei, Ruland, Sean, Macri, Elizabeth, Ma, Henry, Nguyen, Thanh N., Abootalebi, Shahram, Azarpazhooh, M. Reza

“…From February 18, 2019, to July 18, 2020, we followed ischemic and hemorrhagic stroke hospitalization rates and outcomes in Valiasr Hospital, Zanjan, Iran. We used a Bayesian hierarchical model and an interrupted time series analysis (ITS) to identify changes in stroke hospitalization rate, baseline stroke severity [measured by the National Institutes of Health Stroke Scale (NIHSS)], disability [measured by the modified Rankin Scale (mRS)], presentation time (last seen normal to hospital presentation), thrombolytic therapy rate, median door-to-needle time, length of hospital stay, and in-hospital mortality. …”

Evaluating the equity impact and cost-effectiveness of digital adherence technologies with differentiated care to support tuberculosis treatment adherence in Ethiopia: protocol and... by Nicola Foster, Amare W. Tadesse, Christopher Finn McQuaid, Lara Gosce, Tofik Abdurhman, Demelash Assefa, Ahmed Bedru, Rein M. G. J. Houben, Kristian van Kalmthout, Taye Letta, Zemedu Mohammed, Job van Rest, Demekech G. Umeta, Gedion T. Weldemichael, Hiwot Yazew, Degu Jerene, Matthew Quaife, Katherine L. Fielding

“…We will conduct a societal cost-effectiveness analysis using Bayesian hierarchical models that account for the individual-level correlation between costs and outcomes as well as intra-cluster correlation. …”
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A national survey of anthelmintic resistance in ascarid and strongylid nematodes in Australian Thoroughbred horses by Ghazanfar Abbas, Abdul Ghafar, Emma McConnell, Anne Beasley, Jenni Bauquier, Edwina J.A. Wilkes, Charles El-Hage, Peter Carrigan, Lucy Cudmore, John Hurley, Charles G. Gauci, Ian Beveridge, Elysia Ling, Caroline Jacobson, Mark A. Stevenson, Martin K. Nielsen, Kristopher J. Hughes, Abdul Jabbar

“…Faecal egg counts (FECs) were determined using the modified McMaster technique, and percent faecal egg count reduction (%FECR) was calculated using the Bayesian hierarchical model and hybrid Frequentist/Bayesian analysis method. …”
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Estimates of the global, regional, and national morbidity, mortality, and aetiologies of diarrhoea in 195 countries: a systematic analysis for the Global Burden of Disease Study 20... by Troeger, C, Blacker, BF, Khalil, IA, Rao, PC, Cao, S, Zimsen, SRM, Albertson, SB, Stanaway, JD, Deshpande, A, Abebe, Z, Alvis-Guzman, N, Amare, AT, Asgedom, SW, Anteneh, ZA, Antonio, CAT, Aremu, O, Asfaw, ET, Atey, TM, Atique, S, Avokpaho, EFGA, Awasthi, A, Ayele, HT, Barac, A, Barreto, ML, Bassat, Q, Belay, SA, Bensenor, IM, Bhutta, ZA, Bijani, A, Bizuneh, H, Castañeda-Orjuela, CA, Dadi, AF, Dandona, L, Dandona, R, Do, HP, Dubey, M, Dubljanin, E, Edessa, D, Endries, AY, Eshrati, B, Farag, T, Feyissa, GT, Foreman, KJ, Forouzanfar, MH, Fullman, N, Gething, PW, Gishu, MD, Godwin, WW, Gugnani, HC, Gupta, R, Hailu, GB, Hassen, HY, Hibstu, DT, Ilesanmi, OS, Jonas, JB, Kahsay, A, Kang, G, Kasaeian, A, Khader, YS, Khalil, IA, Khan, EA, Khan, MA, Khang, Y-H, Kissoon, N, Kochhar, S, Kotloff, KL, Kumar, GA, Razek, H, Malekzadeh, R, Malta, DC, Mehata, S, Mendoza, W, Mengistu, DT, Menota, BG, Mezgebe, HB, Mlashu, FW, Murthy, S, Naik, GA, Nguyen, CT, Nguyen, TH, Ningrum, DNA, Ogbo, FA, Olagunju, AT, Paudel, D, Platts-Mills, JA, Qorbani, M, Rafay, A, Rai, RK, Rana, SM, Ranabhat, CL, Rasella, D, Ray, SE, Reis, C, Renzaho, AMN, Rezai, MS, Ruhago, GM, Safiri, S, Salomon, JA, Sanabria, JR, Sartorius, B, Sawhney, M, Sepanlou, SG, Shigematsu, M, Sisay, M, Somayaji, R, Sreeramareddy, CT, Sykes, BL, Taffere, GR, Topor-Madry, R, Tran, BX, Tuem, KB, Ukwaja, KN, Vollset, SE, Walson, JL, Weaver, MR, Weldegwergs, KG, Werdecker, A, Workicho, A, Yenesew, M, Yirsaw, BD, Yonemoto, N, Zaki, M, Vos, T, Lim, SS, Naghavi, M, Murray, CJL, Mokdad, AH, Hay, SI, Reiner, RC, Hay, S

“…This study assesses cases, deaths, and aetiologies in 1990–2016 and assesses how the burden of diarrhoea has changed in people of all ages</p> <h4>Methods</h4> <p>We modelled diarrhoea mortality with a Bayesian hierarchical modelling platform that evaluates a wide range of covariates and model types on the basis of vital registration and verbal autopsy data. …”

Service Life Prediction of Polymers and Coatings : Enhanced Methods / by White, Christopher C., editor 650650, Nichols, Mark E., editor 650651, Pickett, James E., editor 650652, ScienceDirect (Online service) 7722

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Small area disease mapping of cancer incidence in British Columbia using Bayesian spatial models and the smallareamapp R Package by Jonathan Simkin, Jonathan Simkin, Trevor J. B. Dummer, Trevor J. B. Dummer, Anders C. Erickson, Michael C. Otterstatter, Michael C. Otterstatter, Ryan R. Woods, Ryan R. Woods, Gina Ogilvie, Gina Ogilvie, Gina Ogilvie

“…This study demonstrates an accessible approach for small area cancer risk estimation using Bayesian hierarchical models and data visualization through the smallareamapp R package.Materials and methodsIncident lung (N = 26,448), female breast (N = 28,466), cervical (N = 1,478), and colorectal (N = 25,457) cancers diagnosed among British Columbia (BC) residents between 2011 and 2018 were obtained from the BC Cancer Registry. …”
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Onset and window of SARS-CoV-2 infectiousness and temporal correlation with symptom onset: a prospective, longitudinal, community cohort study by Hakki, S, Zhou, J, Jonnerby, J, Singanayagam, A, Barnett, JL, Madon, KJ, Koycheva, A, Kelly, C, Houston, H, Nevin, S, Fenn, J, Kundu, R, Crone, MA, Ahmad, S, Derqui-Fernandez, N, Conibear, E, Freemont, PS, Taylor, GP, Ferguson, N, Zambon, M, Barclay, WS, Dunning, J, Lalvani, A, Badhan, A, Varro, R, Luca, C, Quinn, V, Cutajar, J, Nichols, N, Russell, J, Grey, H, Ketkar, A, Miserocchi, G, Tejpal, C, Catchpole, H, Nixon, K, Di Biase, B, Hopewell, T, Narean, JS, Samuel, J, Timcang, K, McDermott, E, Bremang, S, Hammett, S, Evetts, S, Kondratiuk, A

“…Outcomes were assessed with empirical data and a phenomenological Bayesian hierarchical model. <br><strong>Findings<br></strong> Between Sept 13, 2020, and March 31, 2021, we enrolled 393 contacts from 327 households (the SARS-CoV-2 pre-alpha and alpha variant waves); and between May 24, 2021, and Oct 28, 2021, we enrolled 345 contacts from 215 households (the delta variant wave). 173 of these 738 contacts were PCR positive for more than one timepoint, 57 of which were at the start of infection and comprised the final study population. …”

Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million childre... by NCD Risk Factor Collaboration (NCD-RisC), Key, T

“…</p><p> Methods: We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5–19 years. We used a Bayesian hierarchical model to estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories for children and adolescents aged 5–19 years: more than 2 SD below the median of the WHO growth reference for children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to 2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity).…”

Trends and mortality effects of vitamin A deficiency in children in 138 low-income and middle-income countries between 1991 and 2013: a pooled analysis of population-based surveys by Gretchen A Stevens, DSc, James E Bennett, PhD, Quentin Hennocq, MSc, Yuan Lu, DSc, Luz Maria De-Regil, DSc, Lisa Rogers, PhD, Goodarz Danaei, MD, Guangquan Li, PhD, Richard A White, PhD, Seth R Flaxman, BA, Sean-Patrick Oehrle, BA, Mariel M Finucane, PhD, Ramiro Guerrero, MSc, Prof. Zulfiqar A Bhutta, PhD, Amarilis Then-Paulino, MD, Prof. Wafaie Fawzi, MBBS, Prof. Robert E Black, MD, Prof. Majid Ezzati, FMedSci

“…Methods: We collated 134 population-representative data sources from 83 countries with measured serum retinol concentration data. We used a Bayesian hierarchical model to estimate the prevalence of vitamin A deficiency, defined as a serum retinol concentration lower than 0·70 μmol/L. …”
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Spatio-temporal pattern and associate factors of intestinal infectious diseases in Zhejiang Province, China, 2008–2021: a Bayesian modeling study by Zhixin Zhu, Yan Feng, Lanfang Gu, Xifei Guan, Nawen Liu, Xiaoxia Zhu, Hua Gu, Jian Cai, Xiuyang Li

“…Moran’s I index and the local indicators of spatial association (LISA) were calculated using Geoda software to identify the spatial autocorrelation and high-risk areas of IID incidence. Bayesian hierarchical model was used to explore socioeconomic and climate factors affecting IID incidence inequities from spatial and temporal perspectives. …”
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