Shengjie Lai

Biographic Data

ID	3635948
NAME	Shengjie Lai
GIVEN NAMES	Shengjie
FAMILY NAME	Lai
SIGNATURE	LAI S
AFFILIATIONS	University of Southampton
ORCID	0000-0001-9781-8148
VERIFIED	Yes
TOTAL WORKS	18
TOTAL CITATIONS	7
AUTHOR COUNT	18
EDITOR COUNT	0
FIRST PUBLICATION YEAR	2018
LATEST PUBLICATION YEAR	2026
H-INDEX	2

Spatio-temporal modelling of Covid-19 infection and associated risk factors in Dakar, Senegal
Open AccessAssane Niang Gadiaga, Mame Wodji Tine et al.ARTICLEPLOS Global Public Health2026
Infectious diseases are a major threat to global health and economy and the recent COVID-19 pandemic is a perfect example of this. Appropriate modelling and accurate prediction of the outcome of disease spread over time and across space are critical steps towards informed development of effective strategies for public health interventions. In low and middle-income countries, however, the scarcity of spatially disaggregated time-series infectious …
Assessing context-dependent effectiveness of heat adaptation through human mobility under different heatwave regimes
Open AccessHaiyan Liu, Siqin Wang et al.ARTICLESustainable Cities and Society2026
Combined benefits of multi-hazard early warnings on human mobility resilience to tropical cyclones
Open AccessHaiyan Liu, Jianghao Wang et al.ARTICLEGlobal Environmental Change2026References: 1
Comparing and integrating human mobility data sources for measles transmission modeling in Zambia
Open AccessNatalya Kostandova, Christine Prosperi et al.ARTICLEPLOS Global Public Health2025
Quantifying population mobility is crucial in developing accurate models of infectious disease dynamics. Increasingly, multiple data sources are available to describe individual and population mobility in a single location; however, there are no methods to systematically integrate these data. Combining information from these data sets may be valuable and help mitigate inherent biases in each data set due to sampling, censoring, and recall. We exa…
Comparing lagged impacts of mobility changes and environmental factors on Covid-19 waves in rural and urban India: A Bayesian spatiotemporal modelling study
Open AccessEimear Cleary, Fatumah Atuhaire et al.ARTICLEPLOS Global Public Health2025
Previous research in India has identified urbanisation, human mobility and population demographics as key variables associated with higher district level COVID-19 incidence. However, the spatiotemporal dynamics of mobility patterns in rural and urban areas in India, in conjunction with other drivers of COVID-19 transmission, have not been fully investigated. We explored travel networks within India during two pandemic waves using aggregated and a…
Improving mobility data for infectious disease research
Open AccessNatalya Kostandova, Ronan Corgel et al.ARTICLENature Human Behaviour2025References: 10
Identifying counter-urbanisation using Facebook's user count data
Open AccessQianwen Duan, Jessica Steele et al.ARTICLEHabitat International2024References: 67
Identifying the growing widespread phenomenon of counter-urbanisation, where people relocate from urban centres to rural areas, is essential for understanding the social and ecological consequences of the associated changes. However, its nuanced dynamics and complex characteristics pose challenges for quantitative analysis. Here, we used near real-time Facebook user count data for Belgium and Thailand, with missing data imputed, and applied the S…
Scaling Geospatial Data from the Perspective of Complexity: Exploring the Scaling Behavior of the Entropogram
Wei-Bin Zhang, Yong Ge et al.ARTICLEAnnals of the American…2024Cited by: 1References: 31
A fundamental challenge in geospatial data science is to determine how a property, or its characterization, changes with a change in the scale of measurement. Except for geostatistical regularization of the variogram, which is theoretically well established, the scaling behaviors of a wide range of alternative measures of spatial association remain unclear. This limits the ability to make inferences at scales beyond the scale of measurement. The …
Prior water availability modifies the effect of heavy rainfall on dengue transmission: A time series analysis of passive surveillance data from southern China
Open AccessQu Cheng, Qinlong Jing et al.ARTICLEFrontiers in Public Health2023
Introduction: Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions, potentially due to the neglect of prior water availability in mosquito breeding…
Data-Driven Models Informed by Spatiotemporal Mobility Patterns for Understanding Infectious Disease Dynamics
Open AccessDie Zhang, Yong Ge et al.ARTICLEISPRS International Journal of…2023
Data-driven approaches predict infectious disease dynamics by considering various factors that influence severity and transmission rates. However, these factors may not fully capture the dynamic nature of disease transmission, limiting prediction accuracy and consistency. Our proposed data-driven approach integrates spatiotemporal human mobility patterns from detailed point-of-interest clustering and population flow data. These patterns inform th…
Combined and delayed impacts of epidemics and extreme weather on urban mobility recovery
Open AccessHaiyan Liu, Jianghao Wang et al.ARTICLESustainable Cities and Society2023
The ever-increasing pandemic and natural disasters might spatial-temporal overlap to trigger compound disasters that disrupt urban life, including human movements. In this study, we proposed a framework for data-driven analyses on mobility resilience to uncover the compound effects of COVID-19 and extreme weather events on mobility recovery across cities with varied socioeconomic contexts. The concept of suppression risk (SR) is introduced to qua…
Spatiotemporal variations of “triple-demic” outbreaks of respiratory infections in the United States in the post-Covid-19 era
Open AccessWei Luo, Qianhuang Liu et al.ARTICLEBMC Public Health2023
Our study offers a novel spatiotemporal approach that combines both univariate and multivariate surveillance, as well as retrospective and prospective analyses. This approach offers a more comprehensive and timely understanding of how the co-occurrence of COVID-19, influenza, and RSV impacts various regions within the United States. Our findings assist in tailor-made strategies to mitigate the effects of these respiratory infections
Who and which regions are at high risk of returning to poverty during the Covid-19 pandemic
Open AccessYong Ge, Mengxiao Liu et al.ARTICLEHumanities and Social Sciences…2022
Pandemics such as COVID-19 and their induced lockdowns/travel restrictions have a significant impact on people’s lives, especially for lower-income groups who lack savings and rely heavily on mobility to fulfill their daily needs. Taking the COVID-19 pandemic as an example, this study analysed the risk of returning to poverty for low-income households in Hubei Province in China as a result of the COVID-19 lockdown. Employing a dataset including i…
Exploring methods for mapping seasonal population changes using mobile phone data
Open AccessD R Woods, A CUNNINGHAM et al.ARTICLEHumanities and Social Sciences…2022
Data accurately representing the population distribution at the subnational level within countries is critical to policy and decision makers for many applications. Call data records (CDRs) have shown great promise for this, providing much higher temporal and spatial resolutions compared to traditional data sources. For CDRs to be integrated with other data and in order to effectively inform and support policy and decision making, mobile phone use…
Integrated vaccination and physical distancing interventions to prevent future Covid-19 waves in Chinese cities
Open AccessBo Huang, Jionghua Wang et al.ARTICLENature Human Behaviour2021Cited by: 4References: 52
Effect of non-pharmaceutical interventions to contain Covid-19 in China
Open AccessShengjie Lai, Nick Ruktanonchai et al.ARTICLENature2020
Spatial Lifecourse Epidemiology Reporting Standards (Isle-ReSt) statement
Open AccessPeng Jia, Chao Yu et al.ARTICLEHealth & Place2019Cited by: 2References: 1
Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psychosocial, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the critical need for public health and policy decisi…
Modeling the Heterogeneity of Dengue Transmission in a City
Open AccessLingcai Kong, Jinfeng Wang et al.ARTICLEInternational Journal of…2018
Dengue fever is one of the most important vector-borne diseases in the world, and modeling its transmission dynamics allows for determining the key influence factors and helps to perform interventions. The heterogeneity of mosquito bites of humans during the spread of dengue virus is an important factor that should be considered when modeling the dynamics. However, traditional models generally assumed homogeneous mixing between humans and vectors…

Modeling the Heterogeneity of Dengue Transmission in a City
Open AccessLingcai Kong, Jinfeng Wang et al.ARTICLEInternational Journal of…2018
Dengue fever is one of the most important vector-borne diseases in the world, and modeling its transmission dynamics allows for determining the key influence factors and helps to perform interventions. The heterogeneity of mosquito bites of humans during the spread of dengue virus is an important factor that should be considered when modeling the dynamics. However, traditional models generally assumed homogeneous mixing between humans and vectors…
Spatial Lifecourse Epidemiology Reporting Standards (Isle-ReSt) statement
Open AccessPeng Jia, Chao Yu et al.ARTICLEHealth & Place2019Cited by: 2References: 1
Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psychosocial, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the critical need for public health and policy decisi…
Effect of non-pharmaceutical interventions to contain Covid-19 in China
Open AccessShengjie Lai, Nick Ruktanonchai et al.ARTICLENature2020
Integrated vaccination and physical distancing interventions to prevent future Covid-19 waves in Chinese cities
Open AccessBo Huang, Jionghua Wang et al.ARTICLENature Human Behaviour2021Cited by: 4References: 52
Who and which regions are at high risk of returning to poverty during the Covid-19 pandemic
Open AccessYong Ge, Mengxiao Liu et al.ARTICLEHumanities and Social Sciences…2022
Pandemics such as COVID-19 and their induced lockdowns/travel restrictions have a significant impact on people’s lives, especially for lower-income groups who lack savings and rely heavily on mobility to fulfill their daily needs. Taking the COVID-19 pandemic as an example, this study analysed the risk of returning to poverty for low-income households in Hubei Province in China as a result of the COVID-19 lockdown. Employing a dataset including i…
Exploring methods for mapping seasonal population changes using mobile phone data
Open AccessD R Woods, A CUNNINGHAM et al.ARTICLEHumanities and Social Sciences…2022
Data accurately representing the population distribution at the subnational level within countries is critical to policy and decision makers for many applications. Call data records (CDRs) have shown great promise for this, providing much higher temporal and spatial resolutions compared to traditional data sources. For CDRs to be integrated with other data and in order to effectively inform and support policy and decision making, mobile phone use…
Prior water availability modifies the effect of heavy rainfall on dengue transmission: A time series analysis of passive surveillance data from southern China
Open AccessQu Cheng, Qinlong Jing et al.ARTICLEFrontiers in Public Health2023
Introduction: Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions, potentially due to the neglect of prior water availability in mosquito breeding…
Data-Driven Models Informed by Spatiotemporal Mobility Patterns for Understanding Infectious Disease Dynamics
Open AccessDie Zhang, Yong Ge et al.ARTICLEISPRS International Journal of…2023
Data-driven approaches predict infectious disease dynamics by considering various factors that influence severity and transmission rates. However, these factors may not fully capture the dynamic nature of disease transmission, limiting prediction accuracy and consistency. Our proposed data-driven approach integrates spatiotemporal human mobility patterns from detailed point-of-interest clustering and population flow data. These patterns inform th…
Combined and delayed impacts of epidemics and extreme weather on urban mobility recovery
Open AccessHaiyan Liu, Jianghao Wang et al.ARTICLESustainable Cities and Society2023
The ever-increasing pandemic and natural disasters might spatial-temporal overlap to trigger compound disasters that disrupt urban life, including human movements. In this study, we proposed a framework for data-driven analyses on mobility resilience to uncover the compound effects of COVID-19 and extreme weather events on mobility recovery across cities with varied socioeconomic contexts. The concept of suppression risk (SR) is introduced to qua…
Spatiotemporal variations of “triple-demic” outbreaks of respiratory infections in the United States in the post-Covid-19 era
Open AccessWei Luo, Qianhuang Liu et al.ARTICLEBMC Public Health2023
Our study offers a novel spatiotemporal approach that combines both univariate and multivariate surveillance, as well as retrospective and prospective analyses. This approach offers a more comprehensive and timely understanding of how the co-occurrence of COVID-19, influenza, and RSV impacts various regions within the United States. Our findings assist in tailor-made strategies to mitigate the effects of these respiratory infections
Identifying counter-urbanisation using Facebook's user count data
Open AccessQianwen Duan, Jessica Steele et al.ARTICLEHabitat International2024References: 67
Identifying the growing widespread phenomenon of counter-urbanisation, where people relocate from urban centres to rural areas, is essential for understanding the social and ecological consequences of the associated changes. However, its nuanced dynamics and complex characteristics pose challenges for quantitative analysis. Here, we used near real-time Facebook user count data for Belgium and Thailand, with missing data imputed, and applied the S…
Scaling Geospatial Data from the Perspective of Complexity: Exploring the Scaling Behavior of the Entropogram
Wei-Bin Zhang, Yong Ge et al.ARTICLEAnnals of the American…2024Cited by: 1References: 31
A fundamental challenge in geospatial data science is to determine how a property, or its characterization, changes with a change in the scale of measurement. Except for geostatistical regularization of the variogram, which is theoretically well established, the scaling behaviors of a wide range of alternative measures of spatial association remain unclear. This limits the ability to make inferences at scales beyond the scale of measurement. The …
Comparing and integrating human mobility data sources for measles transmission modeling in Zambia
Open AccessNatalya Kostandova, Christine Prosperi et al.ARTICLEPLOS Global Public Health2025
Quantifying population mobility is crucial in developing accurate models of infectious disease dynamics. Increasingly, multiple data sources are available to describe individual and population mobility in a single location; however, there are no methods to systematically integrate these data. Combining information from these data sets may be valuable and help mitigate inherent biases in each data set due to sampling, censoring, and recall. We exa…
Comparing lagged impacts of mobility changes and environmental factors on Covid-19 waves in rural and urban India: A Bayesian spatiotemporal modelling study
Open AccessEimear Cleary, Fatumah Atuhaire et al.ARTICLEPLOS Global Public Health2025
Previous research in India has identified urbanisation, human mobility and population demographics as key variables associated with higher district level COVID-19 incidence. However, the spatiotemporal dynamics of mobility patterns in rural and urban areas in India, in conjunction with other drivers of COVID-19 transmission, have not been fully investigated. We explored travel networks within India during two pandemic waves using aggregated and a…
Improving mobility data for infectious disease research
Open AccessNatalya Kostandova, Ronan Corgel et al.ARTICLENature Human Behaviour2025References: 10
Spatio-temporal modelling of Covid-19 infection and associated risk factors in Dakar, Senegal
Open AccessAssane Niang Gadiaga, Mame Wodji Tine et al.ARTICLEPLOS Global Public Health2026
Infectious diseases are a major threat to global health and economy and the recent COVID-19 pandemic is a perfect example of this. Appropriate modelling and accurate prediction of the outcome of disease spread over time and across space are critical steps towards informed development of effective strategies for public health interventions. In low and middle-income countries, however, the scarcity of spatially disaggregated time-series infectious …
Assessing context-dependent effectiveness of heat adaptation through human mobility under different heatwave regimes
Open AccessHaiyan Liu, Siqin Wang et al.ARTICLESustainable Cities and Society2026
Combined benefits of multi-hazard early warnings on human mobility resilience to tropical cyclones
Open AccessHaiyan Liu, Jianghao Wang et al.ARTICLEGlobal Environmental Change2026References: 1