Guangquan Li

• PhD in Medical Statistics
• Lecturer at Northumbria University

During the COVID-19 pandemic, studies in a number of countries have shown how wastewater can be used as an efficient surveillance tool to detect outbreaks at much lower cost than traditional prevalence surveys. In this study, we consider the utilisation of wastewater data in the post-pandemic setting, in which collection of health data via national...

The evident shedding of the SARS-CoV-2 RNA particles from infected individuals into the wastewater opened up a tantalizing array of possibilities for prediction of COVID-19 prevalence prior to symptomatic case identification through community testing. Many countries have therefore explored the use of wastewater metrics as a surveillance tool, repla...

During the COVID-19 pandemic, studies in a number of countries have shown how wastewater can be used as an efficient surveillance tool to detect outbreaks at much lower cost than traditional prevalence surveys. However, all of these studies have been set in a specific city or region; none have attempted to embed wastewater in a country-level survei...

Purpose: We examine how various PrEP accessibility measures impact the detection of PrEP shortage areas and the relation of shortage areas to social determinants of health (SDOH). Methods: Using ZIP Code Tabulation Areas (ZCTAs) in New York City as a case study, we compared 25 measures of spatial PrEP accessibility across four categories, includ...

Background: London has outperformed smaller towns and rural areas in terms of life expectancy increase. Our aim was to investigate life expectancy change at very-small-area level, and its relationship with house prices and their change. Methods: We performed a hyper-resolution spatiotemporal analysis from 2002 to 2019 for 4835 London Lower-layer...

The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentr...

The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentr...

Background The evidence is sparse regarding the associations between serious mental illnesses (SMIs) prevalence and environmental factors in adulthood as well as the geographic distribution and variability of these associations. In this study, we evaluated the association between availability and proximity of green and blue space with SMI prevalenc...

Background High-resolution data for how mortality and longevity have changed in England, UK are scarce. We aimed to estimate trends from 2002 to 2019 in life expectancy and probabilities of death at different ages for all 6791 middle-layer super output areas (MSOAs) in England. Methods We performed a high-resolution spatiotemporal analysis of civi...

The Observatory for Monitoring Data-Driven Approaches to Covid-19 (OMDDAC) is an Arts and Humanities Research Council funded research project investigating data-driven approaches to Covid-19, focused upon legal, ethical, policy and operational challenges. The project is a collaboration between Northumbria University (Law School, Department of Compu...

There is strong evidence that low birth weight (LBW) has a negative impact on infants' health. Children with LBW are more vulnerable to having disabilities. There has been a considerable amount of research on LBW, but only a small proportion of this research has examined local geographical patterns in LBW and its determinants. LBW is a particular h...

A review of the state of the art in spatial statistics for regional scientists, but relevant to social scientists generally, covering spatial econometric modelling and Hierarchical modelling with spatial dependence from a Bayesian perspective.

Empirical research has repeatedly focused on the potential existence of sentencing disparities. In particular, a growing number of studies have used multilevel models to quantify the extent that ‘similar’ offences are treated alike in different courts. This reliance on multilevel models has resulted in a natural focus on differences in the mean sen...

This research applies a Bayesian multivariate modeling approach to analyze the spatiotemporal patterns of physical disorder, social disorder, property crime, and violent crime at the small‐area scale. Despite crime and disorder exhibiting similar spatiotemporal patterns, as hypothesized by broken windows and collective efficacy theories, past studi...

The ‘England and Wales Sentencing Guidelines’ aim to promote consistency by organising the sentencing process as a sequence of steps, with initial judicial assessments subsequently adjusted to reflect relevant case characteristics. Yet, existing evaluations of the guidelines have failed to incorporate this structure adequately, instead concentratin...

The objective of this article is to report the results of an ecological study into the geography of rape in Stockholm, Sweden using small area data. In order to test the importance of factors indicating opportunity, accessibility and anonymity to the understanding of the geography of rape, a two-stage modelling approach is implemented. First, the o...

Purpose To examine if, and how, spatial crime patterns are explained by one or more underlying crime-general patterns. Methods A set of Bayesian multivariate spatial models are applied to analyze burglary, robbery, vehicle crime, and violent crime at the small-area scale. The residual variability of each crime type is partitioned into shared and t...

The objective of this article is to report the results of an ecological study into the geography of rape in Stockholm, Sweden, using small area data. In order to test the importance of factors indicating opportunity, accessibility and anonymity to the understanding of the geography of rape, a two-stage modelling approach is implemented. First, the...

Neighborhood land use composition influences the geographical patterns of property crime. Few studies, however, have investigated if, and how, the relationships between land use and crime change over time. This research applies a Bayesian spatio-temporal regression model to analyze 12 seasons of property crime at the small-area scale. Time-varying...

Background: Projections of future mortality and life expectancy are needed to plan for health and social services and pensions. Our aim was to forecast national age-specific mortality and life expectancy using an approach that takes into account the uncertainty related to the choice of forecasting model. Methods: We developed an ensemble of 21 f...

Mortality forecasts are typically limited in that they pertain only to national death rates, predict only all-cause mortality or do not capture and utilize the correlation between diseases. We present a novel Bayesian hierarchical model that jointly forecasts cause-specific death rates for geographic subunits. We examine its effectiveness by applyi...

Vitamin A deficiency is a risk factor for blindness and for mortality from measles and diarrhoea in children aged 6-59 months. We aimed to estimate trends in the prevalence of vitamin A deficiency between 1991 and 2013 and its mortality burden in low-income and middle-income countries. We collated 134 population-representative data sources from 83...

Modelling spatio-temporal offence data contributes to our understanding of the spatio-temporal characteristics of the risk of becoming a victim of crime and has implications for policing. Space–time interactions are deeply embedded both empirically and theoretically into many areas of criminology. In this paper, we apply a familiar Bayesian spatio-...

Models for complex biological systems may involve a large number of parameters. It may well be that some of these parameters (in particular any value of those parameters) cannot be derived from observed data via regression techniques. Such parameters are said to be unidentifiable, the remaining parameters being identifiable. Closely related to this...

Some police forces in the UK institute ‘No Cold Calling’ (NCC) zones to reduce cold callings (unsolicited visits to sell products or services), which are often associated with rogue trading and distraction burglary. This paper evaluates the NCC-targeted areas chosen in 2005–06 in Peterborough and reports whether they experienced a measurable impact...

Space-time modeling of small area data is often used in epidemiology for mapping chronic disease rates and by government statistical agencies for producing local estimates of, for example, unemployment or crime rates. Although there is typically a general temporal trend, which affects all areas similarly, abrupt changes may occur in a particular ar...

Retinoblastoma (RB) is an important ocular malignancy of childhood. It has been commonly accepted for some time that knockout of the two alleles of the RB1 gene is the principal molecular target associated with the occurrence of RB. In this article, we examine the validity of the two-hit theory for RB by comparing the fit of a stochastic model with...

Space-time modelling of small area data is often used in epidemiology for mapping temporal trends in chronic disease rates. For rare diseases such as cancers, data are sparse, and a Bayesian hierarchical modelling approach is typically adopted in order to smooth the raw disease rates. Although there may be a general temporal trend which affect all...

Maheswaran et al. (2006) analysed the effect of outdoor modelled NO(x) levels, classified into quintiles, on stroke mortality using a Poisson Bayesian hierarchical model with spatial random effects. An association was observed between higher levels of NO(x) and stroke mortality at the small area (enumeration district) level. As this model is framed...

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Models for complex biological systems may involve a large number of parameters. It may well be that some of these parameters cannot be derived from observed data via regression techniques. Such parameters are said to be unidentifiable, the remaining parameters being identifiable. Closely related to this idea is that of redundancy, that a set of par...

National statistical offices are often required to provide statistical infor-mation about characteristics of the population, such as mean income or unem-ployment rate, at several administrative or small area levels. Having good area level estimates is important because policies will often be based on this type of information. In this paper we descr...

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Heidenreich et al. (Risk Anal 1997 17 391-399) considered parameter identifiability in the context of the two-mutation cancer model and demonstrated that combinations of all but two of the model parameters are identifiable. We consider the problem of identifiability in the recently developed carcinogenesis models of Little and Wright (Math Biosci 2...

In this paper we outline general considerations on parameter identifiability, and introduce the notion of weak local identifiability and gradient weak local identifiability. These are based on local properties of the likelihood, in particular the rank of the Hessian matrix. We relate these to the notions of parameter identifiability and redundancy...

A generalization of the two-mutation stochastic carcinogenesis model of Moolgavkar, Venzon and Knudson and certain models constructed by Little [Little, M.P. (1995). Are two mutations sufficient to cause cancer? Some generalizations of the two-mutation model of carcinogenesis of Moolgavkar, Venzon, and Knudson, and of the multistage model of Armita...

Three stochastic models of genomic instability recently developed by Little and Wright (Math. Biosci., (2003) 183, 111-34), with two, three and five stages, and the two-stage genomic instability model of Nowak et al. (Proc. Natl Acad. Sci. USA, (2002) 99, 16226-16231) are compared with the four-stage model proposed by Luebeck and Moolgavkar (Proc....