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Simultaneously tracking the global COVID-19 impact across multiple populations is challenging due to regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network has the potential to provide reliable and standardized data streams to support monitoring and decision-making world-wide, in real time, and with limited local resources. The University of Maryland Global COVID Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, invites daily cross-sectional samples from the social media platforms active users to participate in the survey since launch April 23, 2020. COVID-19 indicators through December 20, 2020, from N=31,142,582 responses representing N=114 countries, weighted for nonresponse and adjusted to basic demographics, were benchmarked with government data. COVID-19-related signals showed similar concordance with reported benchmark case and test positivity. Bonferroni significance and minimal Spearman correlation strength thresholds were met in the majority. Light Gradient Boost machine learning trained on national and pooled global data verified known symptom indicators, and predicted COVID-19 trends similar to other signals. Risk mitigation behavior trends are correlated with, but sometimes lag, risk perception trends. In regions with strained health infrastructure, but active social media users, we show it is possible to define suitable COVID-19 impact trajectories. This syndromic surveillance public health tool is the largest global health survey to date, and, with brief participant engagement, can provide meaningful, timely insights into the COVID-19 pandemic and response in regions under-represented in epidemiological analyses. Significance StatementThe University of Maryland Global COVID Trends and Impact Survey (UMD-CTIS), launched April 23, 2020, is the largest remote global health monitoring system. This study includes about 30 million UMD-CTIS responses over 34 weeks (through December 2020) from N=114 countries with survey-weights to adjust for nonresponse and demographics. Using limited self-reported data, sampled daily from an international cohort of Facebook users, we demonstrate validity and utility for COVID-19 impacts trends, even in regions with scant or delayed government data. We predict COVID-19 cases in the absence of testing, and characterize perceived COVID-19 risk versus risk-lowering measures. The UMD-CTIS has the potential to support existing monitoring systems for the COVID-19 pandemic, as well as other new, as-yet-undefined global health threats.
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Objective To determine the spectrum of mutations responsible for Phenylalanine hydroxylase (PAH) deficiency on phenylketonuria (PKU) patients of Han Chinese people in the Huaihai region of central China.Methods One hundred and one patients diagnosed with PKU were referred to Xuzhou Maternity and Child Health Care Hospital for genetic counseling/analysis from January 2003 to December 2013.Thirteen exons of PAH gene mutations,as well as their flanking introns,were identified in 202 of chromosomes using polymerase chain reaction-single strand conformation polymorphism(PCR-SSCP) and sequencing.Results (1) The spectrum was composed of 24 different mutation types,which had been submitted to the National Center for Biotechnology Information(NCBI) dbSNP databases under accession number SS#2137543837_SS#C2137543860.(2)The most commonly affected region was exon 7 and its flanking introns.The most prevalent mutations were c.728G ＞ A (p.R243Q),followed by c.721C ＞ T (p.R241C),c.1155G ＞ C(p.L385L),c.1068C ＞ A(p.Y356X),c.-71A ＞ C(-71A ＞ C) and c.60 + 62C ＞ T (IVS1 +62C ＞T),accounting for 18.317％,8.416％,4.950％,3.960％,3.465％ and 2.970％ of the mutant chromosomes,respectively.(3)Two novel mutations were identified in PAH gene in PKU patients of Han Chinese people:c.60+62C＞T(IVS1 +62C ＞T) and c.782G ＞T(p.R261L).Conclusions The vast majority of PAH mutations identified corresponded to those observed for the PKU populations in the other regions in China,whereas a few are considerably different from others.The mutational spectrum of PAH gene found in patients with PKU in the Huaihai region exhibit regional association.
