@article{nokey,

title = {Practical geospatial and sociodemographic predictors of human mobility},

author = {Ruktanonchai, Corrine W and Lai, Shengjie and Utazi, Chigozie E and Cunningham, Alex D and Koper, Patrycja and Rogers, Grant E and Ruktanonchai, Nick W and Sadilek, Adam and Woods, Dorothea and Tatem, Andrew J and Steele, Jessica E. and Sorichetta, Alessandro},

doi = {https://doi.org/10.1038/s41598-021-94683-7},

year  = {2021},

date = {2021-07-28},

journal = {Scientific Reports},

volume = {11},

number = {15389},

abstract = {Understanding seasonal human mobility at subnational scales has important implications across sciences, from urban planning efforts to disease modelling and control. Assessing how, when, and where populations move over the course of the year, however, requires spatially and temporally resolved datasets spanning large periods of time, which can be rare, contain sensitive information, or may be proprietary. Here, we aim to explore how a set of broadly available covariates can describe typical seasonal subnational mobility in Kenya pre-COVID-19, therefore enabling better modelling of seasonal mobility across low- and middle-income country (LMIC) settings in non-pandemic settings. To do this, we used the Google Aggregated Mobility Research Dataset, containing anonymized mobility flows aggregated over users who have turned on the Location History setting, which is off by default. We combined this with socioeconomic and geospatial covariates from 2018 to 2019 to quantify seasonal changes in domestic and international mobility patterns across years. We undertook a spatiotemporal analysis within a Bayesian framework to identify relevant geospatial and socioeconomic covariates explaining human movement patterns, while accounting for spatial and temporal autocorrelations. Typical pre-pandemic mobility patterns in Kenya mostly consisted of shorter, within-county trips, followed by longer domestic travel between counties and international travel, which is important in establishing how mobility patterns changed post-pandemic. Mobility peaked in August and December, closely corresponding to school holiday seasons, which was found to be an important predictor in our model. We further found that socioeconomic variables including urbanicity, poverty, and female education strongly explained mobility patterns, in addition to geospatial covariates such as accessibility to major population centres and temperature. These findings derived from novel data sources elucidate broad spatiotemporal patterns of how populations move within and beyond Kenya, and can be easily generalized to other LMIC settings before the COVID-19 pandemic. Understanding such pre-pandemic mobility patterns provides a crucial baseline to interpret both how these patterns have changed as a result of the pandemic, as well as whether human mobility patterns have been permanently altered once the pandemic subsides. Our findings outline key correlates of mobility using broadly available covariates, alleviating the data bottlenecks of highly sensitive and proprietary mobile phone datasets, which many researchers do not have access to. These results further provide novel insight on monitoring mobility proxies in the context of disease surveillance and control efforts through LMIC settings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Untangling introductions and persistence in COVID-19 resurgence in Europe},

author = {Lemey, Philippe and Ruktanonchai, Nick and Hong, Samuel L and Colizza, Vittoria and Poletto, Chiara and Van den Broeck, Frederik and Gill, Mandev S and Ji, Xiang and Levasseur, Anthony and Oude Munnink, Bas B and Koopmans, Marion and Sadilek, Adam and Lai, Shengjie and Tatem, Andrew J. and Baele, Guy and Suchard, Marc A. and Dellicour, Simon},

doi = {https://doi.org/10.1038/s41586-021-03754-2},

year  = {2021},

date = {2021-06-30},

journal = {Nature},

volume = {595},

number = {713–717},

abstract = {After the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting in late summer 2020 that was deadlier and more difficult to contain1. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave2. Here we build a phylogeographical model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the resurgence of COVID-19 in Europe. We inform this model using genomic, mobility and epidemiological data from 10 European countries and estimate that in many countries more than half of the lineages circulating in late summer resulted from new introductions since 15 June 2020. The success in onward transmission of newly introduced lineages was negatively associated with the local incidence of COVID-19 during this period. The pervasive spread of variants in summer 2020 highlights the threat of viral dissemination when restrictions are lifted, and this needs to be carefully considered in strategies to control the current spread of variants that are more transmissible and/or evade immunity. Our findings indicate that more effective and coordinated measures are required to contain the spread through cross-border travel even as vaccination is reducing disease burden.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Impact of COVID-19 outbreaks and interventions on influenza in China and the United States},

author = {Feng, Luzhao and Zhang, Ting and Wang, Qing and Xie, Yiran and Peng, Zhibin and Zheng, Jiandong and Qin, Ying and Zhang, Muli and Lai, Shengjie and Wang, Dayan and Feng, Zijian and Li, Zhongjie and and Gao, George F.},

doi = {https://doi.org/10.1038/s41467-021-23440-1},

year  = {2021},

date = {2021-05-31},

journal = {Nature Communications},

volume = {12},

number = {3249},

issue = {1},

abstract = {Coronavirus disease 2019 (COVID-19) was detected in China during the 2019–2020 seasonal influenza epidemic. Non-pharmaceutical interventions (NPIs) and behavioral changes to mitigate COVID-19 could have affected transmission dynamics of influenza and other respiratory diseases. By comparing 2019–2020 seasonal influenza activity through March 29, 2020 with the 2011–2019 seasons, we found that COVID-19 outbreaks and related NPIs may have reduced influenza in Southern and Northern China and the United States by 79.2% (lower and upper bounds: 48.8%–87.2%), 79.4% (44.9%–87.4%) and 67.2% (11.5%–80.5%). Decreases in influenza virus infection were also associated with the timing of NPIs. Without COVID-19 NPIs, influenza activity in China and the United States would likely have remained high during the 2019–2020 season. Our findings provide evidence that NPIs can partially mitigate seasonal and, potentially, pandemic influenza.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Global COVID-19 lockdown highlights humans as both threats and custodians of the environment},

author = {Amanda E. Bates and Richard B. Primack and Brandy S. Biggar and Tomas J. Bird and Mary E. Clinton and Rylan J. Command and Cerren Richards and Marc Shellard and Nathan R. Geraldi and ... Shengjie Lai and and others.},

doi = {https://doi.org/10.1016/j.biocon.2021.109175},

issn = {0006-3207},

year  = {2021},

date = {2021-05-21},

urldate = {2021-05-21},

journal = {Biological Conservation},

volume = {263},

abstract = {The global lockdown to mitigate COVID-19 pandemic health risks has altered human interactions with nature. Here, we report immediate impacts of changes in human activities on wildlife and environmental threats during the early lockdown months of 2020, based on 877 qualitative reports and 332 quantitative assessments from 89 different studies. Hundreds of reports of unusual species observations from around the world suggest that animals quickly responded to the reductions in human presence. However, negative effects of lockdown on conservation also emerged, as confinement resulted in some park officials being unable to perform conservation, restoration and enforcement tasks, resulting in local increases in illegal activities such as hunting. Overall, there is a complex mixture of positive and negative effects of the pandemic lockdown on nature, all of which have the potential to lead to cascading responses which in turn impact wildlife and nature conservation. While the net effect of the lockdown will need to be assessed over years as data becomes available and persistent effects emerge, immediate responses were detected across the world. Thus, initial qualitative and quantitative data arising from this serendipitous global quasi-experimental perturbation highlights the dual role that humans play in threatening and protecting species and ecosystems. Pathways to favorably tilt this delicate balance include reducing impacts and increasing conservation effectiveness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Assessing the Effect of Global Travel and Contact Restrictions on Mitigating the COVID-19 Pandemic},

author = {Shengjie Lai and Nick W. Ruktanonchai and Alessandra Carioli and Corrine W. Ruktanonchai and Jessica R. Floyd and Olivia Prosper and Chi Zhang and Xiangjun Du and Weizhong Yang and Andrew J. Tatem},

doi = {https://doi.org/10.1016/j.eng.2021.03.017},

year  = {2021},

date = {2021-05-07},

journal = {Engineering},

volume = {7},

number = {7},

pages = {914-923},

abstract = {Travel restrictions and physical distancing have been implemented across the world to mitigate the coronavirus disease 2019 (COVID-19) pandemic, but studies are needed to understand their effectiveness across regions and time. Based on the population mobility metrics derived from mobile phone geolocation data across 135 countries or territories during the first wave of the pandemic in 2020, we built a metapopulation epidemiological model to measure the effect of travel and contact restrictions on containing COVID-19 outbreaks across regions. We found that if these interventions had not been deployed, the cumulative number of cases could have shown a 97-fold (interquartile range 79–116) increase, as of May 31, 2020. However, their effectiveness depended upon the timing, duration, and intensity of the interventions, with variations in case severity seen across populations, regions, and seasons. Additionally, before effective vaccines are widely available and herd immunity is achieved, our results emphasize that a certain degree of physical distancing at the relaxation of the intervention stage will likely be needed to avoid rapid resurgences and subsequent lockdowns.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Seasonal association between viral causes of hospitalised acute lower respiratory infections and meteorological factors in China: a retrospective study},

author = {Xu, Bing and Wang, Jinfeng and Li, Zhongjie and Xu, Chengdong and Liao, Yilan and Hu, Maogui and Yang, Jing and Lai, Shengjie and Wang, Liping and Yang, Weizhong },

doi = {https://doi.org/10.1016/S2542-5196(20)30297-7},

year  = {2021},

date = {2021-03-11},

urldate = {2021-03-11},

journal = {The Lancet Planetary Health},

volume = {5},

issue = {3},

pages = {e154-e163},

abstract = {Acute lower respiratory infections (ALRIs) caused by respiratory viruses are common and persistent infectious diseases worldwide and in China, which have pronounced seasonal patterns. Meteorological factors have important roles in the seasonality of some major viruses, especially respiratory syncytial virus (RSV) and influenza virus. Our aim was to identify the dominant meteorological factors and to model their effects on common respiratory viruses in different regions of China. We analysed monthly virus data on patients hospitalised with ALRI from 81 sentinel hospitals in 22 provinces in mainland China from Jan 1, 2009, to Sept 30, 2013. We considered seven common respiratory viruses: RSV, influenza virus, human parainfluenza virus, adenovirus, human metapneumovirus, human bocavirus, and human coronavirus. Meteorological data of the same period were used to analyse relationships between virus seasonality and seven meteorological factors according to region (southern vs northern China). The geographical detector method was used to quantify the explanatory power of each meteorological factor, individually and interacting in pairs, on the respiratory viruses. 28,369 hospitalised patients with ALRI were tested, 10,387 (36·6%) of whom were positive for at least one virus, including RSV (4091 [32·0%] patients), influenza virus (2665 [20·8%]), human parainfluenza virus (2185 [17·1%]), adenovirus (1478 [11·6%]), human bocavirus (1120 [8·8%]), human coronavirus (637 [5·0%]), and human metapneumovirus (615 [4·8%]). RSV and influenza virus had annual peaks in the north and biannual peaks in the south. Human parainfluenza virus and human bocavirus had higher positive rates in the spring–summer months. Human metapneumovirus had an annual peak in winter–spring, especially in the north. Adenovirus and human coronavirus exhibited no clear annual seasonality. Temperature, atmospheric pressure, vapour pressure, and rainfall had most explanatory power on most respiratory viruses in each region. Relative humidity was only dominant in the north, but had no significant explanatory power for most viruses in the south. Hours of sunlight had significant explanatory power for RSV and influenza virus in the north, and for most viruses in the south. Wind speed was the only factor with significant explanatory power for human coronavirus in the south. For all viruses, interactions between any two of the paired factors resulted in enhanced explanatory power, either bivariately or non-linearly. Spatiotemporal heterogeneity was detected for most viruses in this study, and interactions between pairs of meteorological factors were found to enhance their influence on virus variation. These findings might be helpful to guide government planning, such as public health interventions, infection control practice, and timing of passive immunoprophylaxis, and might facilitate the development of future vaccine strategies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities},

author = {Huang, Bo and Wang, Jionghua and Cai, Jixuan and Yao, Shiqi and Chan, Paul Kay Sheung and Tam, Tony Hong-wing and Hong, Ying-Yi and Ruktanonchai, Corrine W. and Carioli, Alessandra and Floyd, Jessica R. and Ruktanonchai, Nick W. and Yang, Weizhong and Li, Zhongjie and Tatem, Andrew J. and Lai, Shengjie},

doi = {https://doi.org/10.1038/s41562-021-01063-2},

year  = {2021},

date = {2021-02-18},

urldate = {2021-02-18},

journal = {Nature Human Behaviour},

volume = {5},

pages = {695–705},

abstract = {The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to the formulation of preventive interventions, particularly since the effects of physical distancing measures and upcoming vaccines on reducing susceptible social contacts and eventually halting transmission remain unclear. Here, using anonymized mobile geolocation data in China, we devise a mobility-associated social contact index to quantify the impact of both physical distancing and vaccination measures in a unified way. Building on this index, our epidemiological model reveals that vaccination combined with physical distancing can contain resurgences without relying on stay-at-home restrictions, whereas a gradual vaccination process alone cannot achieve this. Further, for cities with medium population density, vaccination can reduce the duration of physical distancing by 36% to 78%, whereas for cities with high population density, infection numbers can be well-controlled through moderate physical distancing. These findings improve our understanding of the joint effects of vaccination and physical distancing with respect to a city’s population density and social contact patterns.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lai2020,

title = {Effect of non-pharmaceutical interventions to contain COVID-19 in China},

author = {Shengjie Lai and Nick W. Ruktanonchai and Liangcai Zhou and Olivia Prosper and Wei Luo and Jessica R. Floyd and Amy Wesolowski and Mauricio Santillana and Chi Zhang and Xiangjun Du and Hongjie Yu and Andrew J. Tatem},

url = {https://doi.org/10.1038/s41586-020-2293-x},

doi = {10.1038/s41586-020-2293-x},

issn = {1476-4687},

year  = {2020},

date = {2020-09-01},

journal = {Nature},

volume = {585},

number = {7825},

pages = {410-413},

abstract = {On 11 March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a pandemic1. The strategies based on non-pharmaceutical interventions that were used to contain the outbreak in China appear to be effective2, but quantitative research is still needed to assess the efficacy of non-pharmaceutical interventions and their timings3. Here, using epidemiological data on COVID-19 and anonymized data on human movement4,5, we develop a modelling framework that uses daily travel networks to simulate different outbreak and intervention scenarios across China. We estimate that there were a total of 114,325 cases of COVID-19 (interquartile range 76,776--164,576) in mainland China as of 29 February 2020. Without non-pharmaceutical interventions, we predict that the number of cases would have been 67-fold higher (interquartile range 44--94-fold) by 29 February 2020, and we find that the effectiveness of different interventions varied. We estimate that early detection and isolation of cases prevented more infections than did travel restrictions and contact reductions, but that a combination of non-pharmaceutical interventions achieved the strongest and most rapid effect. According to our model, the lifting of travel restrictions from 17 February 2020 does not lead to an increase in cases across China if social distancing interventions can be maintained, even at a limited level of an on average 25% reduction in contact between individuals that continues until late April. These findings improve our understanding of the effects of non-pharmaceutical interventions on COVID-19, and will inform response efforts across the world.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1371/journal.pntd.0008757,

title = {Risk mapping of scrub typhus infections in Qingdao city, China},

author = {Hualei Xin and Peng Fu and Junling Sun and Shengjie Lai and Wenbiao Hu and Archie C. A. Clements and Jianping Sun and Jing Cui and Simon I. Hay and Xiaojing Li and Zhongjie Li},

url = {https://doi.org/10.1371/journal.pntd.0008757},

doi = {10.1371/journal.pntd.0008757},

year  = {2020},

date = {2020-01-01},

journal = {PLOS Neglected Tropical Diseases},

volume = {14},

number = {12},

pages = {1-14},

publisher = {Public Library of Science},

abstract = {Background The emergence and re-emergence of scrub typhus has been reported in the past decade in many global regions. In this study, we aim to identify potential scrub typhus infection risk zones with high spatial resolution in Qingdao city, in which scrub typhus is endemic, to guide local prevention and control strategies. Methodology/Principal findings Scrub typhus cases in Qingdao city during 2006–2018 were retrieved from the Chinese National Infectious Diseases Reporting System. We divided Qingdao city into 1,101 gridded squares and classified them into two categories: areas with and without recorded scrub typhus cases. A boosted regression tree model was used to explore environmental and socioeconomic covariates associated with scrub typhus occurrence and predict the risk of scrub typhus infection across the whole area of Qingdao city. A total of 989 scrub typhus cases were reported in Qingdao from 2006–2018, with most cases located in rural and suburban areas. The predicted risk map generated by the boosted regression tree models indicated that the highest infection risk areas were mainly concentrated in the mid-east and northeast regions of Qingdao, with gross domestic product (20.9%±1.8% standard error) and annual cumulative precipitation (20.3%±1.1%) contributing the most to the variation in the models. By using a threshold environmental suitability value of 0.26, we identified 757 squares (68.7% of the total) with a favourable environment for scrub typhus infection; 66.2% (501/757) of the squares had not yet recorded cases. It is estimated that 6.32 million people (72.5% of the total population) reside in areas with a high risk of scrub typhus infection. Conclusions/Significance Many locations in Qingdao city with no recorded scrub typhus cases were identified as being at risk for scrub typhus occurrence. In these at-risk areas, awareness and capacity for case diagnosis and treatment should be enhanced in the local medical service institutes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1093/jtm/taaa200,

title = {Uncovering two phases of early intercontinental COVID-19 transmission dynamics},

author = {Jing Yang and Juan Li and Shengjie Lai and Corrine W Ruktanonchai and Weijia Xing and Alessandra Carioli and Peihan Wang and Nick W Ruktanonchai and Ruiyun Li and Jessica R Floyd and Liang Wang and Yuhai Bi and Weifeng Shi and Andrew J Tatem},

url = {https://doi.org/10.1093/jtm/taaa200},

doi = {10.1093/jtm/taaa200},

issn = {1708-8305},

year  = {2020},

date = {2020-01-01},

journal = {Journal of Travel Medicine},

volume = {27},

number = {8},

abstract = {The COVID-19 pandemic has posed an ongoing global crisis, but how the virus spread across the world remains poorly understood. This is of vital importance for informing current and future pandemic response strategies.We performed two independent analyses, travel network-based epidemiological modelling and Bayesian phylogeographic inference, to investigate the intercontinental spread of COVID-19.Both approaches revealed two distinct phases of COVID-19 spread by the end of March 2020. In the first phase, COVID-19 largely circulated in China during mid-to-late January 2020 and was interrupted by containment measures in China. In the second and predominant phase extending from late February to mid-March, unrestricted movements between countries outside of China facilitated intercontinental spread, with Europe as a major source. Phylogenetic analyses also revealed that the dominant strains circulating in the USA were introduced from Europe. However, stringent restrictions on international travel across the world since late March have substantially reduced intercontinental transmission.Our analyses highlight that heterogeneities in international travel have shaped the spatiotemporal characteristics of the pandemic. Unrestricted travel caused a large number of COVID-19 exportations from Europe to other continents between late February and mid-March, which facilitated the COVID-19 pandemic. Targeted restrictions on international travel from countries with widespread community transmission, together with improved capacity in testing, genetic sequencing and contact tracing, can inform timely strategies for mitigating and containing ongoing and future waves of COVID-19 pandemic.},

note = {taaa200},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1093/cid/ciaa1057,

title = {Risk of Coronavirus Disease 2019 Transmission in Train Passengers: an Epidemiological and Modeling Study},

author = {Maogui Hu and Hui Lin and Jinfeng Wang and Chengdong Xu and Andrew J Tatem and Bin Meng and Xin Zhang and Yifeng Liu and Pengda Wang and Guizhen Wu and Haiyong Xie and Shengjie Lai},

url = {https://doi.org/10.1093/cid/ciaa1057},

doi = {10.1093/cid/ciaa1057},

issn = {1058-4838},

year  = {2020},

date = {2020-01-01},

journal = {Clinical Infectious Diseases},

volume = {72},

number = {4},

pages = {604-610},

abstract = {Train travel is a common mode of public transport across the globe; however, the risk of coronavirus disease 2019 (COVID-19) transmission among individual train passengers remains unclear.We quantified the transmission risk of COVID-19 on high-speed train passengers using data from 2334 index patients and 72 093 close contacts who had co-travel times of 0–8 hours from 19 December 2019 through 6 March 2020 in China. We analyzed the spatial and temporal distribution of COVID-19 transmission among train passengers to elucidate the associations between infection, spatial distance, and co-travel time.The attack rate in train passengers on seats within a distance of 3 rows and 5 columns of the index patient varied from 0 to 10.3% (95% confidence interval [CI], 5.3%–19.0%), with a mean of 0.32% (95% CI, .29%–.37%). Passengers in seats on the same row (including the adjacent passengers to the index patient) as the index patient had an average attack rate of 1.5% (95% CI, 1.3%–1.8%), higher than that in other rows (0.14% [95% CI, .11%–.17%]), with a relative risk (RR) of 11.2 (95% CI, 8.6–14.6). Travelers adjacent to the index patient had the highest attack rate (3.5% [95% CI, 2.9%–4.3%]) of COVID-19 infection (RR, 18.0 [95% CI, 13.9–23.4]) among all seats. The attack rate decreased with increasing distance, but increased with increasing co-travel time. The attack rate increased on average by 0.15% (P = .005) per hour of co-travel; for passengers in adjacent seats, this increase was 1.3% (P = .008), the highest among all seats considered.COVID-19 has a high transmission risk among train passengers, but this risk shows significant differences with co-travel time and seat location. During disease outbreaks, when traveling on public transportation in confined spaces such as trains, measures should be taken to reduce the risk of transmission, including increasing seat distance, reducing passenger density, and use of personal hygiene protection.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lai2020.06.17.20133843,

title = {Assessing the effect of global travel and contact reductions to mitigate the COVID-19 pandemic and resurgence},

author = {Shengjie Lai and Nick W Ruktanonchai and Alessandra Carioli and Corrine W Ruktanonchai and Jessica R Floyd and Olivia Prosper and Chi Zhang and Xiangjun Du and Weizhong Yang and Andrew J Tatem},

url = {https://www.medrxiv.org/content/early/2020/06/19/2020.06.17.20133843},

doi = {10.1101/2020.06.17.20133843},

year  = {2020},

date = {2020-01-01},

journal = {medRxiv},

publisher = {Cold Spring Harbor Laboratory Press},

abstract = {Travel and physical distancing interventions have been implemented across the World to mitigate the COVID-19 pandemic, but studies are needed to quantify the effectiveness of these measures across regions and time. Timely population mobility data were obtained to measure travel and contact reductions in 135 countries or territories. During the 10 weeks of March 22 – May 30, 2020, domestic travel in study regions has dramatically reduced to a median of 59% (interquartile range [IQR] 43% - 73%) of normal levels seen before the outbreak, with international travel down to 26% (IQR 12% - 35%). If these travel and physical distancing interventions had not been deployed across the World, the cumulative number of cases might have shown a 97-fold (IQR 79 – 116) increase, as of May 31, 2020. However, effectiveness differed by the duration and intensity of interventions and relaxation scenarios, with variations in case severity seen across populations, regions, and seasons.One Sentence Summary Travel and physical distancing interventions across the World are key to mitigate the COVID-19 pandemic and resurgence.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis study was supported by the grants from the Bill & Melinda Gates Foundation (OPP1134076); the European Union Horizon 2020 (MOOD 874850). N.R. is supported by funding from the Bill & Melinda Gates Foundation (OPP1170969). O.P. is supported by the National Science Foundation (1816075). A.J.T. is supported by funding from the Bill & Melinda Gates Foundation (OPP1106427, OPP1032350, OPP1134076, OPP1094793), the Clinton Health Access Initiative, the UK Department for International Development (DFID) and the Wellcome Trust (106866/Z/15/Z, 204613/Z/16/Z).Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Ethical clearance for collecting and using secondary population mobility data was granted by the institutional review board of the University of Southampton (No. 48002). All data were supplied and analyzed in an anonymous format, without access to personal identifying information.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesCode for the model simulations is available at the following GitHub repository: https://github.com/wpgp/BEARmod. The data on COVID-19 cases and interventions reported by country are available from the data sources listed in Supplementary Materials. The parameters and population data for running simulations and estimating the severity are listed in Supplementary Data S1 to S2. The population movement data obtained from Baidu are available at: https://qianxi.baidu.com/. The Google COVID-19 Aggregated Mobility Research Dataset used for this study is available with permission of Google, LLC.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{JIA2020235,

title = {Spatial Lifecourse Epidemiology and Infectious Disease Research},

author = {Peng Jia and Weihua Dong and Shujuan Yang and Zhicheng Zhan and La Tu and Shengjie Lai},

url = {https://www.sciencedirect.com/science/article/pii/S1471492220300052},

doi = {https://doi.org/10.1016/j.pt.2019.12.012},

issn = {1471-4922},

year  = {2020},

date = {2020-01-01},

journal = {Trends in Parasitology},

volume = {36},

number = {3},

pages = {235-238},

abstract = {Spatial lifecourse epidemiology aims to utilize advanced spatial, location-aware, and artificial intelligence technologies to investigate long-term effects of measurable biological, environmental, behavioral, and psychosocial factors on individual risk for chronic diseases. It could also further the research on infectious disease dynamics, risks, and consequences across the life course.},

keywords = {infectious disease, spatial analysis, spatial lifecourse epidemiology},

pubstate = {published},

tppubtype = {article}

}

@article{Lai2020.02.04.20020479,

title = {Assessing spread risk of Wuhan novel coronavirus within and beyond China, January-April 2020: a travel network-based modelling study},

author = {Shengjie Lai and Isaac I. Bogoch and Nick W Ruktanonchai and Alexander Watts and Xin Lu and Weizhong Yang and Hongjie Yu and Kamran Khan and Andrew J Tatem},

url = {https://www.medrxiv.org/content/early/2020/03/09/2020.02.04.20020479},

doi = {10.1101/2020.02.04.20020479},

year  = {2020},

date = {2020-01-01},

journal = {medRxiv},

publisher = {Cold Spring Harbor Laboratory Press},

abstract = {Background A novel coronavirus (2019-nCoV) emerged in Wuhan City, China, at the end of 2019 and has caused an outbreak of human-to-human transmission with a Public Health Emergency of International Concern declared by the World Health Organization on January 30, 2020.Aim We aimed to estimate the potential risk and geographic range of Wuhan novel coronavirus (2019-nCoV) spread within and beyond China from January through to April, 2020.Methods A series of domestic and international travel network-based connectivity and risk analyses were performed, by using de-identified and aggregated mobile phone data, air passenger itinerary data, and case reports.Results The cordon sanitaire of Wuhan is likely to have occurred during the latter stages of peak population numbers leaving the city before Lunar New Year (LNY), with travellers departing into neighbouring cities and other megacities in China. We estimated that 59,912 air passengers, of which 834 (95% UI: 478 - 1349) had 2019-nCoV infection, travelled from Wuhan to 382 cities outside of mainland China during the two weeks prior to Wuhan’s lockdown. The majority of these cities were in Asia, but major hubs in Europe, the US and Australia were also prominent, with strong correlation seen between predicted importation risks and reported cases. Because significant spread has already occurred, a large number of airline travellers (3.3 million under the scenario of 75% travel reduction from normal volumes) may be required to be screened at origin high-risk cities in China and destinations across the globe for the following three months of February to April, 2020 to effectively limit spread beyond its current extent.Conclusion Further spread of 2019-nCoV within China and international exportation is likely to occur. All countries, especially vulnerable regions, should be prepared for efforts to contain the 2019-nCoV infection.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis study was supported by the grants from the Bill & Melinda Gates Foundation (OPP1134076); the European Union Horizon 2020 (MOOD 874850); the National Natural Science Fund of China (81773498, 71771213, 91846301); National Science and Technology Major Project of China (2016ZX10004222-009); Program of Shanghai Academic/Technology Research Leader (18XD1400300); Hunan Science and Technology Plan Project (2017RS3040, 2018JJ1034). AJT is supported by funding from the Bill & Melinda Gates Foundation (OPP1106427, OPP1032350, OPP1134076, OPP1094793), the Clinton Health Access Initiative, the UK Department for International Development (DFID) and the Wellcome Trust (106866/Z/15/Z, 204613/Z/16/Z). HY is supported by funding from the National Natural Science Fund for Distinguished Young Scholars of China (No. 81525023); Program of Shanghai Academic/Technology Research Leader (No. 18XD1400300); and the United States National Institutes of Health (Comprehensive International Program for Research on AIDS grant U19 AI51915). The research team members were independent from the funding agencies. The funders had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; and the preparation, review, or approval of the manuscript.Author DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe datasets on monthly air passenger data in February – April, 2018 used in this study are available from Dr. Kamran Khan (Kamranatbluedot.global). The case data are available from Dr. Shengjie Lai (Shengjie.Laiatsoton.ac.uk). The datasets on holidays and air travel statistics from 2010 through 2018 used for validation are available on the WorldPop website (www.worldpop.org). The mobile phone datasets analysed during the current study are not publicly available since this would compromise the agreement with the data provider, but information on the process of requesting access to the data that support the findings of this study are available from Dr. Shengjie Lai (Shengjie.Laiatsoton.ac.uk).},

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pubstate = {published},

tppubtype = {article}

}

@article{Zhang2019,

title = {Patterns of human social contact and contact with animals in Shanghai, China},

author = {Juanjuan Zhang and Petra Klepac and Jonathan M. Read and Alicia Rosello and Xiling Wang and Shengjie Lai and Meng Li and Yujian Song and Qingzhen Wei and Hao Jiang and Juan Yang and Henry Lynn and Stefan Flasche and Mark Jit and Hongjie Yu},

url = {https://doi.org/10.1038/s41598-019-51609-8},

doi = {10.1038/s41598-019-51609-8},

issn = {2045-2322},

year  = {2019},

date = {2019-10-22},

journal = {Scientific Reports},

volume = {9},

number = {1},

pages = {15141},

abstract = {East Asia is as a principal hotspot for emerging zoonotic infections. Understanding the likely pathways for their emergence and spread requires knowledge on human-human and human-animal contacts, but such studies are rare. We used self-completed and interviewer-completed contact diaries to quantify patterns of these contacts for 965 individuals in 2017/2018 in a high-income densely-populated area of China, Shanghai City. Interviewer-completed diaries recorded more social contacts (19.3 vs. 18.0) and longer social contact duration (35.0 vs. 29.1thinspacehours) than self-reporting. Strong age-assortativity was observed in all age groups especially among young participants (aged 7--20) and middle aged participants (25--55 years). 17.7% of participants reported touching animals (15.3% (pets), 0.0% (poultry) and 0.1% (livestock)). Human-human contact was very frequent but contact with animals (especially poultry) was rare although associated with frequent human-human contact. Hence, this densely populated area is more likely to act as an accelerator for human-human spread but less likely to be at the source of a zoonosis outbreak. We also propose that telephone interview at the end of reporting day is a potential improvement of the design of future contact surveys.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kraemer2019,

title = {Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus},

author = {Moritz U. G. Kraemer and Robert C. Reiner and Oliver J. Brady and Jane P. Messina and Marius Gilbert and David M. Pigott and Dingdong Yi and Kimberly Johnson and Lucas Earl and Laurie B. Marczak and Shreya Shirude and Nicole Davis Weaver and Donal Bisanzio and T. Alex Perkins and Shengjie Lai and Xin Lu and Peter Jones and Giovanini E. Coelho and Roberta G. Carvalho and Wim Van Bortel and Cedric Marsboom and Guy Hendrickx and Francis Schaffner and Chester G. Moore and Heinrich H. Nax and Linus Bengtsson and Erik Wetter and Andrew J. Tatem and John S. Brownstein and David L. Smith and Louis Lambrechts and Simon Cauchemez and Catherine Linard and Nuno R. Faria and Oliver G. Pybus and Thomas W. Scott and Qiyong Liu and Hongjie Yu and G. R. William Wint and Simon I. Hay and Nick Golding},

url = {https://doi.org/10.1038/s41564-019-0376-y},

doi = {10.1038/s41564-019-0376-y},

issn = {2058-5276},

year  = {2019},

date = {2019-05-01},

journal = {Nature Microbiology},

volume = {4},

number = {5},

pages = {854-863},

abstract = {The global population at risk from mosquito-borne diseases---including dengue, yellow fever, chikungunya and Zika---is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lai2019b,

title = {Changing epidemiology and challenges of malaria in China towards elimination},

author = {Shengjie Lai and Junling Sun and Nick W. Ruktanonchai and Sheng Zhou and Jianxing Yu and Isobel Routledge and Liping Wang and Yaming Zheng and Andrew J. Tatem and Zhongjie Li},

url = {https://doi.org/10.1186/s12936-019-2736-8},

doi = {10.1186/s12936-019-2736-8},

issn = {1475-2875},

year  = {2019},

date = {2019-03-29},

journal = {Malaria Journal},

volume = {18},

number = {1},

pages = {107},

abstract = {Historically, malaria had been a widespread disease in China. A national plan was launched in China in 2010, aiming to eliminate malaria by 2020. In 2017, no indigenous cases of malaria were detected in China for the first time. To provide evidence for precise surveillance and response to achieve elimination goal, a comprehensive study is needed to determine the changing epidemiology of malaria and the challenges towards elimination.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lai2019,

title = {Exploring the use of mobile phone data for national migration statistics},

author = {Shengjie Lai and Elisabeth zu Erbach-Schoenberg and Carla Pezzulo and Nick W. Ruktanonchai and Alessandro Sorichetta and Jessica Steele and Tracey Li and Claire A. Dooley and Andrew J. Tatem},

url = {https://doi.org/10.1057/s41599-019-0242-9},

doi = {10.1057/s41599-019-0242-9},

issn = {2055-1045},

year  = {2019},

date = {2019-03-26},

journal = {Palgrave Communications},

volume = {5},

number = {1},

pages = {34},

abstract = {Statistics on internal migration are important for keeping estimates of subnational population numbers up-to-date, as well as urban planning, infrastructure development, and impact assessment, among other applications. However, migration flow statistics typically remain constrained by the logistics of infrequent censuses or surveys. The penetration rate of mobile phones is now high across the globe with rapid recent increases in ownership in low-income countries. Analyzing the changing spatiotemporal distribution of mobile phone users through anonymized call detail records (CDRs) offers the possibility to measure migration at multiple temporal and spatial scales. Based on a dataset of 72 billion anonymized CDRs in Namibia from October 2010 to April 2014, we explore how internal migration estimates can be derived and modeled from CDRs at subnational and annual scales, and how precision and accuracy of these estimates compare to census-derived migration statistics. We also demonstrate the use of CDRs to assess how migration patterns change over time, with a finer temporal resolution compared with censuses. Moreover, we show how gravity-type spatial interaction models built using CDRs can accurately capture migration flows. The results highlight that estimates of migration flows made using mobile phone data is a promising avenue for complementing more traditional national migration statistics and obtaining more timely and local data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Oidtman2019,

title = {Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China},

author = {Rachel J. Oidtman and Shengjie Lai and Zhoujie Huang and Juan Yang and Amir S. Siraj and Robert C. Reiner and Andrew J. Tatem and T. Alex Perkins and Hongjie Yu},

url = {https://doi.org/10.1038/s41467-019-09035-x},

doi = {10.1038/s41467-019-09035-x},

issn = {2041-1723},

year  = {2019},

date = {2019-03-08},

journal = {Nature Communications},

volume = {10},

number = {1},

pages = {1148},

abstract = {Vector-borne diseases display wide inter-annual variation in seasonal epidemic size due to their complex dependence on temporally variable environmental conditions and other factors. In 2014, Guangzhou, China experienced its worst dengue epidemic on record, with incidence exceeding the historical average by two orders of magnitude. To disentangle contributions from multiple factors to inter-annual variation in epidemic size, we fitted a semi-mechanistic model to time series data from 2005--2015 and performed a series of factorial simulation experiments in which seasonal epidemics were simulated under all combinations of year-specific patterns of four time-varying factors: imported cases, mosquito density, temperature, and residual variation in local conditions not explicitly represented in the model. Our results indicate that while epidemics in most years were limited by unfavorable conditions with respect to one or more factors, the epidemic in 2014 was made possible by the combination of favorable conditions for all factors considered in our analysis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Routledge628842,

title = {Tracking progress towards malaria elimination in China: estimates of reproduction numbers and their spatiotemporal variation},

author = {Isobel Routledge and Shengjie Lai and Katherine E Battle and Azra C Ghani and Manuel Gomez-Rodriguez and Kyle B Gustafson and Swapnil Mishra and Joshua L Proctor and Andrew J Tatem and Zhongjie Li and Samir Bhatt},

url = {https://www.biorxiv.org/content/early/2019/05/10/628842},

doi = {10.1101/628842},

year  = {2019},

date = {2019-01-01},

journal = {bioRxiv},

publisher = {Cold Spring Harbor Laboratory},

abstract = {China reported zero locally-acquired malaria cases in 2017 and 2018. Understanding the spatio-temporal pattern underlying this decline, especially the relationship between locally-acquired and imported cases, can inform efforts to maintain elimination and prevent re-emergence. This is particularly pertinent in Yunnan province, where the potential for local transmission is highest. Using a geo-located individual-level dataset of cases recorded in Yunnan province between 2011 and 2016, we jointly estimate the case reproduction number, Rc, and the number of unobserved sources of infection. We use these estimates within spatio-temporal geostatistical models to map how transmission varied over time and space, estimate the timeline to elimination and the risk of resurgence. Our estimates suggest that, maintaining current intervention efforts, Yunnan is unlikely to experience sustained local transmission up to 2020. However, even with a mean Rc of 0.005 projected for the year 2019, locally-acquired cases are possible due to high levels of importation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}