Publications
101.
Lai, Shengjie; Ruktanonchai, Nick W.; Zhou, Liangcai; Prosper, Olivia; Luo, Wei; Floyd, Jessica R.; Wesolowski, Amy; Santillana, Mauricio; Zhang, Chi; Du, Xiangjun; Yu, Hongjie; Tatem, Andrew J.
Effect of non-pharmaceutical interventions to contain COVID-19 in China Journal Article
In: Nature, vol. 585, no. 7825, pp. 410-413, 2020, ISSN: 1476-4687.
Abstract | Links | BibTeX | Tags:
@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}
}
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.
102.
Nieves, Jeremiah J.; Bondarenko, Maksym; Kerr, David; Ves, Nikolas; Yetman, Greg; Sinha, Parmanand; Clarke, Donna J.; Sorichetta, Alessandro; Stevens, Forrest; Gaughan, Andrea E.; Tatem, Andrew J.
Measuring the Contribution of Built-Settlement Data to Global Population Mapping Journal Article
In: Social Sciences & Humanities Open, 2020.
Abstract | Links | BibTeX | Tags:
@article{nokey,
title = {Measuring the Contribution of Built-Settlement Data to Global Population Mapping},
author = {Nieves, Jeremiah J. and Bondarenko, Maksym and Kerr, David and Ves, Nikolas and Yetman, Greg and Sinha, Parmanand and Clarke, Donna J. and Sorichetta, Alessandro and Stevens, Forrest and Gaughan, Andrea E. and Tatem, Andrew J.},
url = {https://ssrn.com/abstract=3599775},
doi = {10.2139/ssrn.3599775},
year = {2020},
date = {2020-05-20},
journal = {Social Sciences & Humanities Open},
abstract = {Top-down population modelling has gained applied prominence in public health, planning, and sustainability applications at the global scale. These top-down population modelling methods often rely on remote-sensing (RS) derived representation of the built-environment and settlements as key predictive covariates. While these RS-derived data, which are global in extent, have become more advanced and more available, gaps in spatial and temporal coverage remain. Here we have modelled built-settlement extents between 2000 and 2012 and demonstrate the applied utility and information provided by these annually modelled data for the application of annually modelling population across 172 countries. We demonstrate that the modelled built-settlement data are consistently the 2nd most important covariate in predicting population density, behind annual lights at night, across the globe and across the study period. Further, we demonstrate that this modelled built-settlement data often provides more information than current annually available RS-derived data and last observed built-settlement extents.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Top-down population modelling has gained applied prominence in public health, planning, and sustainability applications at the global scale. These top-down population modelling methods often rely on remote-sensing (RS) derived representation of the built-environment and settlements as key predictive covariates. While these RS-derived data, which are global in extent, have become more advanced and more available, gaps in spatial and temporal coverage remain. Here we have modelled built-settlement extents between 2000 and 2012 and demonstrate the applied utility and information provided by these annually modelled data for the application of annually modelling population across 172 countries. We demonstrate that the modelled built-settlement data are consistently the 2nd most important covariate in predicting population density, behind annual lights at night, across the globe and across the study period. Further, we demonstrate that this modelled built-settlement data often provides more information than current annually available RS-derived data and last observed built-settlement extents.
103.
Dunnett, Sebastian; Sorichetta, Alessandro; Taylor, Gail; Eigenbrod, Felix
Harmonised global datasets of wind and solar farm locations and power Journal Article
In: Scientific Data, vol. 7, no. 1, pp. 130, 2020, ISSN: 2052-4463.
Abstract | Links | BibTeX | Tags:
@article{Dunnett2020,
title = {Harmonised global datasets of wind and solar farm locations and power},
author = {Sebastian Dunnett and Alessandro Sorichetta and Gail Taylor and Felix Eigenbrod},
url = {https://doi.org/10.1038/s41597-020-0469-8},
doi = {10.1038/s41597-020-0469-8},
issn = {2052-4463},
year = {2020},
date = {2020-04-29},
journal = {Scientific Data},
volume = {7},
number = {1},
pages = {130},
abstract = {Energy systems need decarbonisation in order to limit global warming to within safe limits. While global land planners are promising more of the planet's limited space to wind and solar photovoltaic, there is little information on where current infrastructure is located. The majority of recent studies use land suitability for wind and solar, coupled with technical and socioeconomic constraints, as a proxy for actual location data. Here, we address this shortcoming. Using readily accessible OpenStreetMap data we present, to our knowledge, the first global, open-access, harmonised spatial datasets of wind and solar installations. We also include user friendly code to enable users to easily create newer versions of the dataset. Finally, we include first order estimates of power capacities of installations. We anticipate these data will be of widespread interest within global studies of the future potential and trade-offs associated with the global decarbonisation of energy systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Energy systems need decarbonisation in order to limit global warming to within safe limits. While global land planners are promising more of the planet's limited space to wind and solar photovoltaic, there is little information on where current infrastructure is located. The majority of recent studies use land suitability for wind and solar, coupled with technical and socioeconomic constraints, as a proxy for actual location data. Here, we address this shortcoming. Using readily accessible OpenStreetMap data we present, to our knowledge, the first global, open-access, harmonised spatial datasets of wind and solar installations. We also include user friendly code to enable users to easily create newer versions of the dataset. Finally, we include first order estimates of power capacities of installations. We anticipate these data will be of widespread interest within global studies of the future potential and trade-offs associated with the global decarbonisation of energy systems.
104.
Floyd, Jessica R.; Ogola, Joseph; Fèvre, Eric M.; Wardrop, Nicola; Tatem, Andrew J.; Ruktanonchai, Nick W.
Activity-specific mobility of adults in a rural region of western Kenya Journal Article
In: PeerJ, vol. 8, pp. e8798, 2020, ISSN: 2167-8359.
Abstract | Links | BibTeX | Tags: Activity, GPS, Mobility, Resource access
@article{10.7717/peerj.8798,
title = {Activity-specific mobility of adults in a rural region of western Kenya},
author = {Jessica R. Floyd and Joseph Ogola and Eric M. Fèvre and Nicola Wardrop and Andrew J. Tatem and Nick W. Ruktanonchai},
url = {https://doi.org/10.7717/peerj.8798},
doi = {10.7717/peerj.8798},
issn = {2167-8359},
year = {2020},
date = {2020-04-01},
journal = {PeerJ},
volume = {8},
pages = {e8798},
abstract = {Improving rural household access to resources such as markets, schools and healthcare can help alleviate poverty in low-income settings. Current models of geographic accessibility to various resources rarely take individual variation into account due to a lack of appropriate data, yet understanding mobility at an individual level is key to knowing how people access their local resources. Our study used both an activity-specific survey and GPS trackers to evaluate how adults in a rural area of western Kenya accessed local resources. We calculated the travel time and time spent at six different types of resource and compared the GPS and survey data to see how well they matched. We found links between several demographic characteristics and the time spent at different resources, and that the GPS data reflected the survey data well for time spent at some types of resource, but poorly for others. We conclude that demography and activity are important drivers of mobility, and a better understanding of individual variation in mobility could be obtained through the use of GPS trackers on a wider scale.},
keywords = {Activity, GPS, Mobility, Resource access},
pubstate = {published},
tppubtype = {article}
}
Improving rural household access to resources such as markets, schools and healthcare can help alleviate poverty in low-income settings. Current models of geographic accessibility to various resources rarely take individual variation into account due to a lack of appropriate data, yet understanding mobility at an individual level is key to knowing how people access their local resources. Our study used both an activity-specific survey and GPS trackers to evaluate how adults in a rural area of western Kenya accessed local resources. We calculated the travel time and time spent at six different types of resource and compared the GPS and survey data to see how well they matched. We found links between several demographic characteristics and the time spent at different resources, and that the GPS data reflected the survey data well for time spent at some types of resource, but poorly for others. We conclude that demography and activity are important drivers of mobility, and a better understanding of individual variation in mobility could be obtained through the use of GPS trackers on a wider scale.
105.
Qader, Sarchil Hama; Lefebvre, Veronique; Tatem, Andrew J.; Pape, Utz; Jochem, Warren; Himelein, Kristen; Ninneman, Amy; Wolburg, Philip; Nunez-Chaim, Gonzalo; Bengtsson, Linus; Bird, Tomas
Using gridded population and quadtree sampling units to support survey sample design in low-income settings Journal Article
In: International Journal of Health Geographics, vol. 19, no. 1, pp. 10, 2020, ISSN: 1476-072X.
Abstract | Links | BibTeX | Tags:
@article{Qader2020,
title = {Using gridded population and quadtree sampling units to support survey sample design in low-income settings},
author = {Sarchil Hama Qader and Veronique Lefebvre and Andrew J. Tatem and Utz Pape and Warren Jochem and Kristen Himelein and Amy Ninneman and Philip Wolburg and Gonzalo Nunez-Chaim and Linus Bengtsson and Tomas Bird},
url = {https://doi.org/10.1186/s12942-020-00205-5},
doi = {10.1186/s12942-020-00205-5},
issn = {1476-072X},
year = {2020},
date = {2020-03-26},
journal = {International Journal of Health Geographics},
volume = {19},
number = {1},
pages = {10},
abstract = {Household surveys are the main source of demographic, health and socio-economic data in low- and middle-income countries (LMICs). To conduct such a survey, census population information mapped into enumeration areas (EAs) typically serves a sampling frame from which to generate a random sample. However, the use of census information to generate this sample frame can be problematic as in many LMIC contexts, such data are often outdated or incomplete, potentially introducing coverage issues into the sample frame. Increasingly, where census data are outdated or unavailable, modelled population datasets in the gridded form are being used to create household survey sampling frames.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Household surveys are the main source of demographic, health and socio-economic data in low- and middle-income countries (LMICs). To conduct such a survey, census population information mapped into enumeration areas (EAs) typically serves a sampling frame from which to generate a random sample. However, the use of census information to generate this sample frame can be problematic as in many LMIC contexts, such data are often outdated or incomplete, potentially introducing coverage issues into the sample frame. Increasingly, where census data are outdated or unavailable, modelled population datasets in the gridded form are being used to create household survey sampling frames.
106.
Sorichetta, Alessandro; Nghiem, Son V.; Masetti, Marco; Linard, Catherine; Richter, Andreas
Transformative Urban Changes of Beijing in the Decade of the 2000s Journal Article
In: Remote Sensing, vol. 12, no. 4, 2020, ISSN: 2072-4292.
Abstract | Links | BibTeX | Tags:
@article{rs12040652,
title = {Transformative Urban Changes of Beijing in the Decade of the 2000s},
author = {Alessandro Sorichetta and Son V. Nghiem and Marco Masetti and Catherine Linard and Andreas Richter},
url = {https://www.mdpi.com/2072-4292/12/4/652},
doi = {10.3390/rs12040652},
issn = {2072-4292},
year = {2020},
date = {2020-01-01},
journal = {Remote Sensing},
volume = {12},
number = {4},
abstract = {The rapid economic growth, the exodus from rural to urban areas, and the associated extreme urban development that occurred in China in the decade of the 2000s have severely impacted the environment in Beijing, its vicinity, and beyond. This article presents an innovative approach for assessing mega-urban changes and their impact on the environment based on the use of decadal QuikSCAT (QSCAT) satellite data, acquired globally by the SeaWinds scatterometer over that period. The Dense Sampling Method (DSM) is applied to QSCAT data to obtain reliable annual infrastructure-based urban observations at a posting of ~1 km. The DSM-QSCAT data, along with different DSM-based change indices, were used to delineate the extent of the Beijing infrastructure-based urban area in each year between 2000 and 2009, and assess its development over time, enabling a physical quantification of its urbanization which reflects the implementation of various development policies during the same time period. Eventually, as a proxy for the impact of Beijing urbanization on the environment, the decadal trend of its infrastructure-based urbanization is compared with that of the corresponding tropospheric nitrogen dioxide (NO2) column densities as observed from the Global Ozone Monitoring Experiment (GOME) instrument aboard the second European Remote Sensing satellite (ERS-2) between 2000 and 2002, and from the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY aboard of the ESA’s ENVIronmental SATellite (SCIAMACHY /ENVISAT) between 2003 and 2009. Results reveal a threefold increase of the yearly tropospheric NO2 column density within the Beijing infrastructure-based urban area extent in 2009, which had quadrupled since 2000.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The rapid economic growth, the exodus from rural to urban areas, and the associated extreme urban development that occurred in China in the decade of the 2000s have severely impacted the environment in Beijing, its vicinity, and beyond. This article presents an innovative approach for assessing mega-urban changes and their impact on the environment based on the use of decadal QuikSCAT (QSCAT) satellite data, acquired globally by the SeaWinds scatterometer over that period. The Dense Sampling Method (DSM) is applied to QSCAT data to obtain reliable annual infrastructure-based urban observations at a posting of ~1 km. The DSM-QSCAT data, along with different DSM-based change indices, were used to delineate the extent of the Beijing infrastructure-based urban area in each year between 2000 and 2009, and assess its development over time, enabling a physical quantification of its urbanization which reflects the implementation of various development policies during the same time period. Eventually, as a proxy for the impact of Beijing urbanization on the environment, the decadal trend of its infrastructure-based urbanization is compared with that of the corresponding tropospheric nitrogen dioxide (NO2) column densities as observed from the Global Ozone Monitoring Experiment (GOME) instrument aboard the second European Remote Sensing satellite (ERS-2) between 2000 and 2002, and from the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY aboard of the ESA’s ENVIronmental SATellite (SCIAMACHY /ENVISAT) between 2003 and 2009. Results reveal a threefold increase of the yearly tropospheric NO2 column density within the Beijing infrastructure-based urban area extent in 2009, which had quadrupled since 2000.
107.
Ruktanonchai, Corrine Warren; Nieves, Jeremiah J; Ruktanonchai, Nick W; Nilsen, Kristine; Steele, Jessica E; Matthews, Zoe; Tatem, Andrew J
Estimating uncertainty in geospatial modelling at multiple spatial resolutions: the pattern of delivery via caesarean section in Tanzania Journal Article
In: BMJ Global Health, vol. 4, no. Suppl 5, 2020.
Abstract | Links | BibTeX | Tags:
@article{Ruktanonchaie002092,
title = {Estimating uncertainty in geospatial modelling at multiple spatial resolutions: the pattern of delivery via caesarean section in Tanzania},
author = {Corrine Warren Ruktanonchai and Jeremiah J Nieves and Nick W Ruktanonchai and Kristine Nilsen and Jessica E Steele and Zoe Matthews and Andrew J Tatem},
url = {https://gh.bmj.com/content/4/Suppl_5/e002092},
doi = {10.1136/bmjgh-2019-002092},
year = {2020},
date = {2020-01-01},
journal = {BMJ Global Health},
volume = {4},
number = {Suppl 5},
publisher = {BMJ Specialist Journals},
abstract = {Visualising maternal and newborn health (MNH) outcomes at fine spatial resolutions is crucial to ensuring the most vulnerable women and children are not left behind in improving health. Disaggregated data on life-saving MNH interventions remain difficult to obtain, however, necessitating the use of Bayesian geostatistical models to map outcomes at small geographical areas. While these methods have improved model parameter estimates and precision among spatially correlated health outcomes and allowed for the quantification of uncertainty, few studies have examined the trade-off between higher spatial resolution modelling and how associated uncertainty propagates. Here, we explored the trade-off between model outcomes and associated uncertainty at increasing spatial resolutions by quantifying the posterior distribution of delivery via caesarean section (c-section) in Tanzania. Overall, in modelling delivery via c-section at multiple spatial resolutions, we demonstrated poverty to be negatively correlated across spatial resolutions, suggesting important disparities in obtaining life-saving obstetric surgery persist across sociodemographic factors. Lastly, we found that while uncertainty increased with higher spatial resolution input, model precision was best approximated at the highest spatial resolution, suggesting an important policy trade-off between identifying concealed spatial heterogeneities in health indicators.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Visualising maternal and newborn health (MNH) outcomes at fine spatial resolutions is crucial to ensuring the most vulnerable women and children are not left behind in improving health. Disaggregated data on life-saving MNH interventions remain difficult to obtain, however, necessitating the use of Bayesian geostatistical models to map outcomes at small geographical areas. While these methods have improved model parameter estimates and precision among spatially correlated health outcomes and allowed for the quantification of uncertainty, few studies have examined the trade-off between higher spatial resolution modelling and how associated uncertainty propagates. Here, we explored the trade-off between model outcomes and associated uncertainty at increasing spatial resolutions by quantifying the posterior distribution of delivery via caesarean section (c-section) in Tanzania. Overall, in modelling delivery via c-section at multiple spatial resolutions, we demonstrated poverty to be negatively correlated across spatial resolutions, suggesting important disparities in obtaining life-saving obstetric surgery persist across sociodemographic factors. Lastly, we found that while uncertainty increased with higher spatial resolution input, model precision was best approximated at the highest spatial resolution, suggesting an important policy trade-off between identifying concealed spatial heterogeneities in health indicators.
108.
Dotse-Gborgbortsi, Winfred; Dwomoh, Duah; Alegana, Victor; Hill, Allan; Tatem, Andrew J; Wright, Jim
The influence of distance and quality on utilisation of birthing services at health facilities in Eastern Region, Ghana Journal Article
In: BMJ Global Health, vol. 4, no. Suppl 5, 2020.
Abstract | Links | BibTeX | Tags:
@article{Dotse-Gborgbortsie002020,
title = {The influence of distance and quality on utilisation of birthing services at health facilities in Eastern Region, Ghana},
author = {Winfred Dotse-Gborgbortsi and Duah Dwomoh and Victor Alegana and Allan Hill and Andrew J Tatem and Jim Wright},
url = {https://gh.bmj.com/content/4/Suppl_5/e002020},
doi = {10.1136/bmjgh-2019-002020},
year = {2020},
date = {2020-01-01},
journal = {BMJ Global Health},
volume = {4},
number = {Suppl 5},
publisher = {BMJ Specialist Journals},
abstract = {Objectives Skilled birth attendance is the single most important intervention to reduce maternal mortality. However, studies have not used routinely collected health service birth data at named health facilities to understand the influence of distance and quality of care on childbirth service utilisation. Thus, this paper aims to quantify the influence of distance and quality of healthcare on utilisation of birthing services using routine health data in Eastern Region, Ghana.Methods We used a spatial interaction model (a model that predicts movement from one place to another) drawing on routine birth data, emergency obstetric care surveys, gridded estimates of number of pregnancies and health facility location. We compared travel distances by sociodemographic characteristics and mapped movement patterns.Results A kilometre increase in distance significantly reduced the prevalence rate of the number of women giving birth in health facilities by 6.7%. Although quality care increased the number of women giving birth in health facilities, its association was insignificant. Women travelled further than expected to give birth at facilities, on average journeying 4.7 km beyond the nearest facility with a recorded birth. Women in rural areas travelled 4 km more than urban women to reach a hospital. We also observed that 56% of women bypassed the nearest hospital to their community.Conclusion This analysis provides substantial opportunities for health planners and managers to understand further patterns of skilled birth service utilisation, and demonstrates the value of routine health data. Also, it provides evidence-based information for improving maternal health service provision by targeting specific communities and health facilities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Objectives Skilled birth attendance is the single most important intervention to reduce maternal mortality. However, studies have not used routinely collected health service birth data at named health facilities to understand the influence of distance and quality of care on childbirth service utilisation. Thus, this paper aims to quantify the influence of distance and quality of healthcare on utilisation of birthing services using routine health data in Eastern Region, Ghana.Methods We used a spatial interaction model (a model that predicts movement from one place to another) drawing on routine birth data, emergency obstetric care surveys, gridded estimates of number of pregnancies and health facility location. We compared travel distances by sociodemographic characteristics and mapped movement patterns.Results A kilometre increase in distance significantly reduced the prevalence rate of the number of women giving birth in health facilities by 6.7%. Although quality care increased the number of women giving birth in health facilities, its association was insignificant. Women travelled further than expected to give birth at facilities, on average journeying 4.7 km beyond the nearest facility with a recorded birth. Women in rural areas travelled 4 km more than urban women to reach a hospital. We also observed that 56% of women bypassed the nearest hospital to their community.Conclusion This analysis provides substantial opportunities for health planners and managers to understand further patterns of skilled birth service utilisation, and demonstrates the value of routine health data. Also, it provides evidence-based information for improving maternal health service provision by targeting specific communities and health facilities.
109.
Lai, Shengjie; Bogoch, Isaac I.; Ruktanonchai, Nick W; Watts, Alexander; Lu, Xin; Yang, Weizhong; Yu, Hongjie; Khan, Kamran; Tatem, Andrew J
Assessing spread risk of Wuhan novel coronavirus within and beyond China, January-April 2020: a travel network-based modelling study Journal Article
In: medRxiv, 2020.
Abstract | Links | BibTeX | Tags:
@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).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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).
110.
Boo, G; Darin, E; Thomson, DR; Tatem, AJ
A grid-based sample design framework for household surveys [version 1; peer review: 2 approved, 1 approved with reservations] Journal Article
In: Gates Open Research, vol. 4, no. 13, 2020.
@article{10.12688/gatesopenres.13107.1,
title = {A grid-based sample design framework for household surveys [version 1; peer review: 2 approved, 1 approved with reservations]},
author = {G Boo and E Darin and DR Thomson and AJ Tatem},
doi = {10.12688/gatesopenres.13107.1},
year = {2020},
date = {2020-01-01},
journal = {Gates Open Research},
volume = {4},
number = {13},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
111.
Dujardin, Sébastien; Jacques, Damien; Steele, Jessica; Linard, Catherine
Mobile Phone Data for Urban Climate Change Adaptation: Reviewing Applications, Opportunities and Key Challenges Journal Article
In: Sustainability, vol. 12, no. 4, 2020, ISSN: 2071-1050.
Abstract | Links | BibTeX | Tags:
@article{su12041501,
title = {Mobile Phone Data for Urban Climate Change Adaptation: Reviewing Applications, Opportunities and Key Challenges},
author = {Sébastien Dujardin and Damien Jacques and Jessica Steele and Catherine Linard},
url = {https://www.mdpi.com/2071-1050/12/4/1501},
doi = {10.3390/su12041501},
issn = {2071-1050},
year = {2020},
date = {2020-01-01},
journal = {Sustainability},
volume = {12},
number = {4},
abstract = {Climate change places cities at increasing risk and poses a serious challenge for adaptation. As a response, novel sources of data combined with data-driven logics and advanced spatial modelling techniques have the potential for transformative change in the role of information in urban planning. However, little practical guidance exists on the potential opportunities offered by mobile phone data for enhancing adaptive capacities in urban areas. Building upon a review of spatial studies mobilizing mobile phone data, this paper explores the opportunities offered by such digital information for providing spatially-explicit assessments of urban vulnerability, and shows the ways these can help developing more dynamic strategies and tools for urban planning and disaster risk management. Finally, building upon the limitations of mobile phone data analysis, it discusses the key urban governance challenges that need to be addressed for supporting the emergence of transformative change in current planning frameworks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Climate change places cities at increasing risk and poses a serious challenge for adaptation. As a response, novel sources of data combined with data-driven logics and advanced spatial modelling techniques have the potential for transformative change in the role of information in urban planning. However, little practical guidance exists on the potential opportunities offered by mobile phone data for enhancing adaptive capacities in urban areas. Building upon a review of spatial studies mobilizing mobile phone data, this paper explores the opportunities offered by such digital information for providing spatially-explicit assessments of urban vulnerability, and shows the ways these can help developing more dynamic strategies and tools for urban planning and disaster risk management. Finally, building upon the limitations of mobile phone data analysis, it discusses the key urban governance challenges that need to be addressed for supporting the emergence of transformative change in current planning frameworks.
112.
Utazi, C. Edson; Wagai, John; Pannell, Oliver; Cutts, Felicity T.; Rhoda, Dale A.; Ferrari, Matthew J.; Dieng, Boubacar; Oteri, Joseph; Danovaro-Holliday, M. Carolina; Adeniran, Adeyemi; Tatem, Andrew J.
Geospatial variation in measles vaccine coverage through routine and campaign strategies in Nigeria: Analysis of recent household surveys Journal Article
In: Vaccine, vol. 38, no. 14, pp. 3062-3071, 2020, ISSN: 0264-410X.
Abstract | Links | BibTeX | Tags: Geospatial analysis, Measles vaccine, Post-campaign coverage survey, Routine immunization, Supplementary immunization activities
@article{UTAZI20203062,
title = {Geospatial variation in measles vaccine coverage through routine and campaign strategies in Nigeria: Analysis of recent household surveys},
author = {C. Edson Utazi and John Wagai and Oliver Pannell and Felicity T. Cutts and Dale A. Rhoda and Matthew J. Ferrari and Boubacar Dieng and Joseph Oteri and M. Carolina Danovaro-Holliday and Adeyemi Adeniran and Andrew J. Tatem},
url = {https://www.sciencedirect.com/science/article/pii/S0264410X20303017},
doi = {https://doi.org/10.1016/j.vaccine.2020.02.070},
issn = {0264-410X},
year = {2020},
date = {2020-01-01},
journal = {Vaccine},
volume = {38},
number = {14},
pages = {3062-3071},
abstract = {Measles vaccination campaigns are conducted regularly in many low- and middle-income countries to boost measles control efforts and accelerate progress towards elimination. National and sometimes first-level administrative division campaign coverage may be estimated through post-campaign coverage surveys (PCCS). However, these large-area estimates mask significant geographic inequities in coverage at more granular levels. Here, we undertake a geospatial analysis of the Nigeria 2017–18 PCCS data to produce coverage estimates at 1 × 1 km resolution and the district level using binomial spatial regression models built on a suite of geospatial covariates and implemented in a Bayesian framework via the INLA-SPDE approach. We investigate the individual and combined performance of the campaign and routine immunization (RI) by mapping various indicators of coverage for children aged 9–59 months. Additionally, we compare estimated coverage before the campaign at 1 × 1 km and the district level with predicted coverage maps produced using other surveys conducted in 2013 and 2016–17. Coverage during the campaign was generally higher and more homogeneous than RI coverage but geospatial differences in the campaign’s reach of previously unvaccinated children are shown. Persistent areas of low coverage highlight the need for improved RI performance. The results can help to guide the conduct of future campaigns, improve vaccination monitoring and measles elimination efforts. Moreover, the approaches used here can be readily extended to other countries.},
keywords = {Geospatial analysis, Measles vaccine, Post-campaign coverage survey, Routine immunization, Supplementary immunization activities},
pubstate = {published},
tppubtype = {article}
}
Measles vaccination campaigns are conducted regularly in many low- and middle-income countries to boost measles control efforts and accelerate progress towards elimination. National and sometimes first-level administrative division campaign coverage may be estimated through post-campaign coverage surveys (PCCS). However, these large-area estimates mask significant geographic inequities in coverage at more granular levels. Here, we undertake a geospatial analysis of the Nigeria 2017–18 PCCS data to produce coverage estimates at 1 × 1 km resolution and the district level using binomial spatial regression models built on a suite of geospatial covariates and implemented in a Bayesian framework via the INLA-SPDE approach. We investigate the individual and combined performance of the campaign and routine immunization (RI) by mapping various indicators of coverage for children aged 9–59 months. Additionally, we compare estimated coverage before the campaign at 1 × 1 km and the district level with predicted coverage maps produced using other surveys conducted in 2013 and 2016–17. Coverage during the campaign was generally higher and more homogeneous than RI coverage but geospatial differences in the campaign’s reach of previously unvaccinated children are shown. Persistent areas of low coverage highlight the need for improved RI performance. The results can help to guide the conduct of future campaigns, improve vaccination monitoring and measles elimination efforts. Moreover, the approaches used here can be readily extended to other countries.
113.
Jia, Peng; Dong, Weihua; Yang, Shujuan; Zhan, Zhicheng; Tu, La; Lai, Shengjie
Spatial Lifecourse Epidemiology and Infectious Disease Research Journal Article
In: Trends in Parasitology, vol. 36, no. 3, pp. 235-238, 2020, ISSN: 1471-4922.
Abstract | Links | BibTeX | Tags: infectious disease, spatial analysis, spatial lifecourse epidemiology
@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}
}
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.
114.
Dujardin, Sébastien; Jacques, Damien; Steele, Jessica; Linard, Catherine
Mobile Phone Data for Urban Climate Change Adaptation: Reviewing Applications, Opportunities and Key Challenges Journal Article
In: Sustainability, vol. 12, no. 4, 2020, ISSN: 2071-1050.
Abstract | Links | BibTeX | Tags:
@article{su12041501b,
title = {Mobile Phone Data for Urban Climate Change Adaptation: Reviewing Applications, Opportunities and Key Challenges},
author = {Sébastien Dujardin and Damien Jacques and Jessica Steele and Catherine Linard},
url = {https://www.mdpi.com/2071-1050/12/4/1501},
doi = {10.3390/su12041501},
issn = {2071-1050},
year = {2020},
date = {2020-01-01},
journal = {Sustainability},
volume = {12},
number = {4},
abstract = {Climate change places cities at increasing risk and poses a serious challenge for adaptation. As a response, novel sources of data combined with data-driven logics and advanced spatial modelling techniques have the potential for transformative change in the role of information in urban planning. However, little practical guidance exists on the potential opportunities offered by mobile phone data for enhancing adaptive capacities in urban areas. Building upon a review of spatial studies mobilizing mobile phone data, this paper explores the opportunities offered by such digital information for providing spatially-explicit assessments of urban vulnerability, and shows the ways these can help developing more dynamic strategies and tools for urban planning and disaster risk management. Finally, building upon the limitations of mobile phone data analysis, it discusses the key urban governance challenges that need to be addressed for supporting the emergence of transformative change in current planning frameworks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Climate change places cities at increasing risk and poses a serious challenge for adaptation. As a response, novel sources of data combined with data-driven logics and advanced spatial modelling techniques have the potential for transformative change in the role of information in urban planning. However, little practical guidance exists on the potential opportunities offered by mobile phone data for enhancing adaptive capacities in urban areas. Building upon a review of spatial studies mobilizing mobile phone data, this paper explores the opportunities offered by such digital information for providing spatially-explicit assessments of urban vulnerability, and shows the ways these can help developing more dynamic strategies and tools for urban planning and disaster risk management. Finally, building upon the limitations of mobile phone data analysis, it discusses the key urban governance challenges that need to be addressed for supporting the emergence of transformative change in current planning frameworks.
115.
Nieves, Jeremiah J.; Bondarenko, Maksym; Sorichetta, Alessandro; Steele, Jessica E.; Kerr, David; Carioli, Alessandra; Stevens, Forrest R.; Gaughan, Andrea E.; Tatem, Andrew J.
Predicting Near-Future Built-Settlement Expansion Using Relative Changes in Small Area Populations Journal Article
In: Remote Sensing, vol. 12, no. 10, 2020, ISSN: 2072-4292.
Abstract | Links | BibTeX | Tags:
@article{rs12101545,
title = {Predicting Near-Future Built-Settlement Expansion Using Relative Changes in Small Area Populations},
author = {Jeremiah J. Nieves and Maksym Bondarenko and Alessandro Sorichetta and Jessica E. Steele and David Kerr and Alessandra Carioli and Forrest R. Stevens and Andrea E. Gaughan and Andrew J. Tatem},
url = {https://www.mdpi.com/2072-4292/12/10/1545},
doi = {10.3390/rs12101545},
issn = {2072-4292},
year = {2020},
date = {2020-01-01},
journal = {Remote Sensing},
volume = {12},
number = {10},
abstract = {Advances in the availability of multi-temporal, remote sensing-derived global built-/human-settlements datasets can now provide globally consistent definitions of “human-settlement” at unprecedented spatial fineness. Yet, these data only provide a time-series of past extents and urban growth/expansion models have not had parallel advances at high-spatial resolution. Here our goal was to present a globally applicable predictive modelling framework, as informed by a short, preceding time-series of built-settlement extents, capable of producing annual, near-future built-settlement extents. To do so, we integrated a random forest, dasymetric redistribution, and autoregressive temporal models with open and globally available subnational data, estimates of built-settlement population, and environmental covariates. Using this approach, we trained the model on a 11 year time-series (2000-2010) of European Space Agency (ESA) Climate Change Initiative (CCI) Land Cover “Urban Areas” class and predicted annual, 100m resolution, binary settlement extents five years beyond the last observations (2011-2015) within varying environmental, urban morphological, and data quality contexts. We found that our model framework performed consistently across all sampled countries and, when compared to time-specific imagery, demonstrated the capacity to capture human-settlement missed by the input time-series and the withheld validation settlement extents. When comparing manually delineated building footprints of small settlements to the modelled extents, we saw that the modelling framework had a 12 percent increase in accuracy compared to withheld validation settlement extents. However, how this framework performs when using different input definitions of “urban” or settlement remains unknown. While this model framework is predictive and not explanatory in nature, it shows that globally available “off-the-shelf” datasets and relative changes in subnational population can be sufficient for accurate prediction of future settlement expansion. Further, this framework shows promise for predicting near-future settlement extents and provides a foundation for forecasts further into the future.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Advances in the availability of multi-temporal, remote sensing-derived global built-/human-settlements datasets can now provide globally consistent definitions of “human-settlement” at unprecedented spatial fineness. Yet, these data only provide a time-series of past extents and urban growth/expansion models have not had parallel advances at high-spatial resolution. Here our goal was to present a globally applicable predictive modelling framework, as informed by a short, preceding time-series of built-settlement extents, capable of producing annual, near-future built-settlement extents. To do so, we integrated a random forest, dasymetric redistribution, and autoregressive temporal models with open and globally available subnational data, estimates of built-settlement population, and environmental covariates. Using this approach, we trained the model on a 11 year time-series (2000–2010) of European Space Agency (ESA) Climate Change Initiative (CCI) Land Cover “Urban Areas” class and predicted annual, 100m resolution, binary settlement extents five years beyond the last observations (2011–2015) within varying environmental, urban morphological, and data quality contexts. We found that our model framework performed consistently across all sampled countries and, when compared to time-specific imagery, demonstrated the capacity to capture human-settlement missed by the input time-series and the withheld validation settlement extents. When comparing manually delineated building footprints of small settlements to the modelled extents, we saw that the modelling framework had a 12 percent increase in accuracy compared to withheld validation settlement extents. However, how this framework performs when using different input definitions of “urban” or settlement remains unknown. While this model framework is predictive and not explanatory in nature, it shows that globally available “off-the-shelf” datasets and relative changes in subnational population can be sufficient for accurate prediction of future settlement expansion. Further, this framework shows promise for predicting near-future settlement extents and provides a foundation for forecasts further into the future.
116.
Lai, Shengjie; Ruktanonchai, Nick W; Carioli, Alessandra; Ruktanonchai, Corrine W; Floyd, Jessica R; Prosper, Olivia; Zhang, Chi; Du, Xiangjun; Yang, Weizhong; Tatem, Andrew J
Assessing the effect of global travel and contact reductions to mitigate the COVID-19 pandemic and resurgence Journal Article
In: medRxiv, 2020.
Abstract | Links | BibTeX | Tags:
@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}
}
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.
117.
Rice, Benjamin L.; Annapragada, Akshaya; Baker, Rachel E.; Bruijning, Marjolein; Dotse-Gborgbortsi, Winfred; Mensah, Keitly; Miller, Ian F.; Motaze, Nkengafac Villyen; Raherinandrasana, Antso; Rajeev, Malavika; Rakotonirina, Julio; Ramiadantsoa, Tanjona; Rasambainarivo, Fidisoa; Yu, Weiyu; Grenfell, Bryan T.; Tatem, Andrew J.; Metcalf, C. Jessica E.
High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa Journal Article
In: medRxiv, 2020.
Abstract | Links | BibTeX | Tags:
@article{Rice2020.07.23.20161208,
title = {High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa},
author = {Benjamin L. Rice and Akshaya Annapragada and Rachel E. Baker and Marjolein Bruijning and Winfred Dotse-Gborgbortsi and Keitly Mensah and Ian F. Miller and Nkengafac Villyen Motaze and Antso Raherinandrasana and Malavika Rajeev and Julio Rakotonirina and Tanjona Ramiadantsoa and Fidisoa Rasambainarivo and Weiyu Yu and Bryan T. Grenfell and Andrew J. Tatem and C. Jessica E. Metcalf},
url = {https://www.medrxiv.org/content/early/2020/07/29/2020.07.23.20161208},
doi = {10.1101/2020.07.23.20161208},
year = {2020},
date = {2020-01-01},
journal = {medRxiv},
publisher = {Cold Spring Harbor Laboratory Press},
abstract = {A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (e.g., warmer environments1, younger populations2–4) have yet to be framed within a comprehensive analysis accounting for factors that may offset the effects of climate and demography. Here, we synthesize factors hypothesized to shape the pace of this pandemic and its burden as it moves across SSA, encompassing demographic, comorbidity, climatic, healthcare and intervention capacity, and human mobility dimensions of risk. We find large scale diversity in probable drivers, such that outcomes are likely to be highly variable among SSA countries. While simulation shows that extensive climatic variation among SSA population centers has little effect on early outbreak trajectories, heterogeneity in connectivity is likely to play a large role in shaping the pace of viral spread. The prolonged, asynchronous outbreaks expected in weakly connected settings may result in extended stress to health systems. In addition, the observed variability in comorbidities and access to care will likely modulate the severity of infection: We show that even small shifts in the infection fatality ratio towards younger ages, which are likely in high risk settings, can eliminate the protective effect of younger populations. We highlight countries with elevated risk of ‘slow pace’, high burden outbreaks. Empirical data on the spatial extent of outbreaks within SSA countries, their patterns in severity over age, and the relationship between epidemic pace and health system disruptions are urgently needed to guide efforts to mitigate the high burden scenarios explored here.Competing Interest StatementThe authors have declared no competing interest.Funding StatementREB is supported by the Cooperative Institute for Modeling the Earth System (CIMES). AA acknowledges support from the NIH Medical Scientist Training Program 1T32GM136577. AJT is funded by the BMGF (OPP1182425, OPP1134076 and INV-002697). MB is funded by NWO Rubicon grant 019.192EN.017.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:NAAll 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.YesData and code have been deposited into a publicly available GitHub repository: https://github.com/labmetcalf/SSA-SARS-CoV-2 High resolution maps and further visualizations of the risk indicators and simulations studied here can be accessed online through an interactive tool: https://labmetcalf.shinyapps.io/covid19-burden-africa/ https://labmetcalf.shinyapps.io/covid19-burden-africa/},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (e.g., warmer environments1, younger populations2–4) have yet to be framed within a comprehensive analysis accounting for factors that may offset the effects of climate and demography. Here, we synthesize factors hypothesized to shape the pace of this pandemic and its burden as it moves across SSA, encompassing demographic, comorbidity, climatic, healthcare and intervention capacity, and human mobility dimensions of risk. We find large scale diversity in probable drivers, such that outcomes are likely to be highly variable among SSA countries. While simulation shows that extensive climatic variation among SSA population centers has little effect on early outbreak trajectories, heterogeneity in connectivity is likely to play a large role in shaping the pace of viral spread. The prolonged, asynchronous outbreaks expected in weakly connected settings may result in extended stress to health systems. In addition, the observed variability in comorbidities and access to care will likely modulate the severity of infection: We show that even small shifts in the infection fatality ratio towards younger ages, which are likely in high risk settings, can eliminate the protective effect of younger populations. We highlight countries with elevated risk of ‘slow pace’, high burden outbreaks. Empirical data on the spatial extent of outbreaks within SSA countries, their patterns in severity over age, and the relationship between epidemic pace and health system disruptions are urgently needed to guide efforts to mitigate the high burden scenarios explored here.Competing Interest StatementThe authors have declared no competing interest.Funding StatementREB is supported by the Cooperative Institute for Modeling the Earth System (CIMES). AA acknowledges support from the NIH Medical Scientist Training Program 1T32GM136577. AJT is funded by the BMGF (OPP1182425, OPP1134076 and INV-002697). MB is funded by NWO Rubicon grant 019.192EN.017.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:NAAll 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.YesData and code have been deposited into a publicly available GitHub repository: https://github.com/labmetcalf/SSA-SARS-CoV-2 High resolution maps and further visualizations of the risk indicators and simulations studied here can be accessed online through an interactive tool: https://labmetcalf.shinyapps.io/covid19-burden-africa/ https://labmetcalf.shinyapps.io/covid19-burden-africa/
118.
Dotse-Gborgbortsi, Winfred; Tatem, Andrew J.; Alegana, Victor; Utazi, C. Edson; Ruktanonchai, Corrine Warren; Wright, Jim
In: Tropical Medicine & International Health, vol. 25, no. 9, pp. 1044-1054, 2020.
Abstract | Links | BibTeX | Tags: accouchement qualifié, EmONC, financement EmONC, GIS, maternal health, quality care, santé maternelle, skilled birth attendance, soins de qualité, temps de trajet, travel time
@article{https://doi.org/10.1111/tmi.13460,
title = {Spatial inequalities in skilled attendance at birth in Ghana: a multilevel analysis integrating health facility databases with household survey data},
author = {Winfred Dotse-Gborgbortsi and Andrew J. Tatem and Victor Alegana and C. Edson Utazi and Corrine Warren Ruktanonchai and Jim Wright},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/tmi.13460},
doi = {https://doi.org/10.1111/tmi.13460},
year = {2020},
date = {2020-01-01},
journal = {Tropical Medicine & International Health},
volume = {25},
number = {9},
pages = {1044-1054},
abstract = {Abstract Objective This study aimed at using survey data to predict skilled attendance at birth (SBA) across Ghana from healthcare quality and health facility accessibility. Methods Through a cross-sectional, observational study, we used a random intercept mixed effects multilevel logistic modelling approach to estimate the odds of having SBA and then applied model estimates to spatial layers to assess the probability of SBA at high-spatial resolution across Ghana. We combined data from the Demographic and Health Survey (DHS), routine birth registers, a service provision assessment of emergency obstetric care services, gridded population estimates and modelled travel time to health facilities. Results Within an hour's travel, 97.1% of women sampled in the DHS could access any health facility, 96.6% could reach a facility providing birthing services, and 86.2% could reach a secondary hospital. After controlling for characteristics of individual women, living in an urban area and close proximity to a health facility with high-quality services were significant positive determinants of SBA uptake. The estimated variance suggests significant effects of cluster and region on SBA as 7.1% of the residual variation in the propensity to use SBA is attributed to unobserved regional characteristics and 16.5% between clusters within regions. Conclusion Given the expansion of primary care facilities in Ghana, this study suggests that higher quality healthcare services, as opposed to closer proximity of facilities to women, is needed to widen SBA uptake and improve maternal health.},
keywords = {accouchement qualifié, EmONC, financement EmONC, GIS, maternal health, quality care, santé maternelle, skilled birth attendance, soins de qualité, temps de trajet, travel time},
pubstate = {published},
tppubtype = {article}
}
Abstract Objective This study aimed at using survey data to predict skilled attendance at birth (SBA) across Ghana from healthcare quality and health facility accessibility. Methods Through a cross-sectional, observational study, we used a random intercept mixed effects multilevel logistic modelling approach to estimate the odds of having SBA and then applied model estimates to spatial layers to assess the probability of SBA at high-spatial resolution across Ghana. We combined data from the Demographic and Health Survey (DHS), routine birth registers, a service provision assessment of emergency obstetric care services, gridded population estimates and modelled travel time to health facilities. Results Within an hour's travel, 97.1% of women sampled in the DHS could access any health facility, 96.6% could reach a facility providing birthing services, and 86.2% could reach a secondary hospital. After controlling for characteristics of individual women, living in an urban area and close proximity to a health facility with high-quality services were significant positive determinants of SBA uptake. The estimated variance suggests significant effects of cluster and region on SBA as 7.1% of the residual variation in the propensity to use SBA is attributed to unobserved regional characteristics and 16.5% between clusters within regions. Conclusion Given the expansion of primary care facilities in Ghana, this study suggests that higher quality healthcare services, as opposed to closer proximity of facilities to women, is needed to widen SBA uptake and improve maternal health.
119.
Hu, Maogui; Lin, Hui; Wang, Jinfeng; Xu, Chengdong; Tatem, Andrew J; Meng, Bin; Zhang, Xin; Liu, Yifeng; Wang, Pengda; Wu, Guizhen; Xie, Haiyong; Lai, Shengjie
Risk of Coronavirus Disease 2019 Transmission in Train Passengers: an Epidemiological and Modeling Study Journal Article
In: Clinical Infectious Diseases, vol. 72, no. 4, pp. 604-610, 2020, ISSN: 1058-4838.
Abstract | Links | BibTeX | Tags:
@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}
}
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.
120.
Ruktanonchai, N. W.; Floyd, J. R.; Lai, S.; Ruktanonchai, C. W.; Sadilek, A.; Rente-Lourenco, P.; Ben, X.; Carioli, A.; Gwinn, J.; Steele, J. E.; Prosper, O.; Schneider, A.; Oplinger, A.; Eastham, P.; Tatem, A. J.
Assessing the impact of coordinated COVID-19 exit strategies across Europe Journal Article
In: Science, vol. 369, no. 6510, pp. 1465-1470, 2020.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1126/science.abc5096,
title = {Assessing the impact of coordinated COVID-19 exit strategies across Europe},
author = {N. W. Ruktanonchai and J. R. Floyd and S. Lai and C. W. Ruktanonchai and A. Sadilek and P. Rente-Lourenco and X. Ben and A. Carioli and J. Gwinn and J. E. Steele and O. Prosper and A. Schneider and A. Oplinger and P. Eastham and A. J. Tatem},
url = {https://www.science.org/doi/abs/10.1126/science.abc5096},
doi = {10.1126/science.abc5096},
year = {2020},
date = {2020-01-01},
journal = {Science},
volume = {369},
number = {6510},
pages = {1465-1470},
abstract = {Even during a pandemic, all countries—even islands—are dependent in one way or another on their neighbors. Without coordinated relaxation of nonpharmaceutical interventions (NPIs) among the most closely connected countries, it is difficult to envisage maintaining control of infectious viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Ruktanonchai et al. used mobility data from smartphones to estimate movements between administrative units across Europe before and after the implementation of NPIs for coronavirus disease 2019 (COVID-19). Modeling disease dynamics under alternative scenarios of countries releasing NPIs, in particular stay-at-home orders, showed that if countries do not coordinate their NPIs when they relax lockdown, resurgence of disease occurs sooner. Coordination of on-off NPIs would significantly increase their effectiveness at reducing transmission across Europe. Science, this issue p. 1465 Coordination among countries in easing restrictions is key to preventing resurgent COVID-19 outbreaks and stopping community transmission. As rates of new coronavirus disease 2019 (COVID-19) cases decline across Europe owing to nonpharmaceutical interventions such as social distancing policies and lockdown measures, countries require guidance on how to ease restrictions while minimizing the risk of resurgent outbreaks. We use mobility and case data to quantify how coordinated exit strategies could delay continental resurgence and limit community transmission of COVID-19. We find that a resurgent continental epidemic could occur as many as 5 weeks earlier when well-connected countries with stringent existing interventions end their interventions prematurely. Further, we find that appropriate coordination can greatly improve the likelihood of eliminating community transmission throughout Europe. In particular, synchronizing intermittent lockdowns across Europe means that half as many lockdown periods would be required to end continent-wide community transmission.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Even during a pandemic, all countries—even islands—are dependent in one way or another on their neighbors. Without coordinated relaxation of nonpharmaceutical interventions (NPIs) among the most closely connected countries, it is difficult to envisage maintaining control of infectious viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Ruktanonchai et al. used mobility data from smartphones to estimate movements between administrative units across Europe before and after the implementation of NPIs for coronavirus disease 2019 (COVID-19). Modeling disease dynamics under alternative scenarios of countries releasing NPIs, in particular stay-at-home orders, showed that if countries do not coordinate their NPIs when they relax lockdown, resurgence of disease occurs sooner. Coordination of on-off NPIs would significantly increase their effectiveness at reducing transmission across Europe. Science, this issue p. 1465 Coordination among countries in easing restrictions is key to preventing resurgent COVID-19 outbreaks and stopping community transmission. As rates of new coronavirus disease 2019 (COVID-19) cases decline across Europe owing to nonpharmaceutical interventions such as social distancing policies and lockdown measures, countries require guidance on how to ease restrictions while minimizing the risk of resurgent outbreaks. We use mobility and case data to quantify how coordinated exit strategies could delay continental resurgence and limit community transmission of COVID-19. We find that a resurgent continental epidemic could occur as many as 5 weeks earlier when well-connected countries with stringent existing interventions end their interventions prematurely. Further, we find that appropriate coordination can greatly improve the likelihood of eliminating community transmission throughout Europe. In particular, synchronizing intermittent lockdowns across Europe means that half as many lockdown periods would be required to end continent-wide community transmission.
