Publications
301.
Tatem, Andrew J.
Mapping population and pathogen movements Journal Article
In: International Health, vol. 6, no. 1, pp. 5-11, 2014, ISSN: 1876-3413.
Abstract | Links | BibTeX | Tags:
@article{10.1093/inthealth/ihu006,
title = {Mapping population and pathogen movements},
author = {Andrew J. Tatem},
url = {https://doi.org/10.1093/inthealth/ihu006},
doi = {10.1093/inthealth/ihu006},
issn = {1876-3413},
year = {2014},
date = {2014-01-01},
journal = {International Health},
volume = {6},
number = {1},
pages = {5-11},
abstract = {For most of human history, populations have been relatively isolated from each other, and only recently has there been extensive contact between peoples, flora and fauna from both old and new worlds. The reach, volume and speed of modern travel are unprecedented, with human mobility increasing in high income countries by over 1000-fold since 1800. This growth is putting people at risk from the emergence of new strains of familiar diseases, and from completely new diseases, while ever more cases of the movement of both disease vectors and the diseases they carry are being seen. Pathogens and their vectors can now move further, faster and in greater numbers than ever before. Equally however, we now have access to the most detailed and comprehensive datasets on human mobility and pathogen distributions ever assembled, in order to combat these threats. This short review paper provides an overview of these datasets, with a particular focus on low income regions, and covers briefly approaches used to combine them to help us understand and control some of the negative effects of population and pathogen movements.},
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pubstate = {published},
tppubtype = {article}
}
For most of human history, populations have been relatively isolated from each other, and only recently has there been extensive contact between peoples, flora and fauna from both old and new worlds. The reach, volume and speed of modern travel are unprecedented, with human mobility increasing in high income countries by over 1000-fold since 1800. This growth is putting people at risk from the emergence of new strains of familiar diseases, and from completely new diseases, while ever more cases of the movement of both disease vectors and the diseases they carry are being seen. Pathogens and their vectors can now move further, faster and in greater numbers than ever before. Equally however, we now have access to the most detailed and comprehensive datasets on human mobility and pathogen distributions ever assembled, in order to combat these threats. This short review paper provides an overview of these datasets, with a particular focus on low income regions, and covers briefly approaches used to combine them to help us understand and control some of the negative effects of population and pathogen movements.
302.
Garcia, Andres J.; Pindolia, Deepa K.; Lopiano, Kenneth K.; Tatem, Andrew J.
Modeling internal migration flows in sub-Saharan Africa using census microdata Journal Article
In: Migration Studies, vol. 3, no. 1, pp. 89-110, 2014, ISSN: 2049-5838.
Abstract | Links | BibTeX | Tags:
@article{10.1093/migration/mnu036,
title = {Modeling internal migration flows in sub-Saharan Africa using census microdata},
author = {Andres J. Garcia and Deepa K. Pindolia and Kenneth K. Lopiano and Andrew J. Tatem},
url = {https://doi.org/10.1093/migration/mnu036},
doi = {10.1093/migration/mnu036},
issn = {2049-5838},
year = {2014},
date = {2014-01-01},
journal = {Migration Studies},
volume = {3},
number = {1},
pages = {89-110},
abstract = {Globalization and the expansion of transport networks has transformed migration into a major policy issue because of its effects on a range of phenomena, including resource flows in economics, urbanization, as well as the epidemiology of infectious diseases. Quantifying and modeling human migration can contribute towards a better understanding of the nature of migration and help develop evidence-based interventions for disease control policy, economic development, and resource allocation. In this study we paired census microdata from 10 countries in sub-Saharan Africa with additional spatial datasets to develop models for the internal migration flows in each country, including key drivers that reflect the changing social, demographic, economic, and environmental landscapes. We assessed how well these gravity-type spatial interaction models can both explain and predict migration. Results show that the models can explain up to 87 percent of internal migration, can predict future within-country migration with correlations of up to 0.91, and can also predict migration in other countries with correlations of up to 0.72. Findings show that such models are useful tools for understanding migration as well as predicting flows in regions where data are sparse, and can contribute towards strategic economic development, planning, and disease control targeting.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Globalization and the expansion of transport networks has transformed migration into a major policy issue because of its effects on a range of phenomena, including resource flows in economics, urbanization, as well as the epidemiology of infectious diseases. Quantifying and modeling human migration can contribute towards a better understanding of the nature of migration and help develop evidence-based interventions for disease control policy, economic development, and resource allocation. In this study we paired census microdata from 10 countries in sub-Saharan Africa with additional spatial datasets to develop models for the internal migration flows in each country, including key drivers that reflect the changing social, demographic, economic, and environmental landscapes. We assessed how well these gravity-type spatial interaction models can both explain and predict migration. Results show that the models can explain up to 87 percent of internal migration, can predict future within-country migration with correlations of up to 0.91, and can also predict migration in other countries with correlations of up to 0.72. Findings show that such models are useful tools for understanding migration as well as predicting flows in regions where data are sparse, and can contribute towards strategic economic development, planning, and disease control targeting.
303.
Perkins, T. Alex; Garcia, Andres J.; Paz-Soldán, Valerie A.; Stoddard, Steven T.; Reiner, Robert C.; Vazquez-Prokopec, Gonzalo; Bisanzio, Donal; Morrison, Amy C.; Halsey, Eric S.; Kochel, Tadeusz J.; Smith, David L.; Kitron, Uriel; Scott, Thomas W.; Tatem, Andrew J.
Theory and data for simulating fine-scale human movement in an urban environment Journal Article
In: Journal of The Royal Society Interface, vol. 11, no. 99, pp. 20140642, 2014.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1098/rsif.2014.0642,
title = {Theory and data for simulating fine-scale human movement in an urban environment},
author = {T. Alex Perkins and Andres J. Garcia and Valerie A. Paz-Soldán and Steven T. Stoddard and Robert C. Reiner and Gonzalo Vazquez-Prokopec and Donal Bisanzio and Amy C. Morrison and Eric S. Halsey and Tadeusz J. Kochel and David L. Smith and Uriel Kitron and Thomas W. Scott and Andrew J. Tatem},
url = {https://royalsocietypublishing.org/doi/abs/10.1098/rsif.2014.0642},
doi = {10.1098/rsif.2014.0642},
year = {2014},
date = {2014-01-01},
journal = {Journal of The Royal Society Interface},
volume = {11},
number = {99},
pages = {20140642},
abstract = {Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it.},
keywords = {},
pubstate = {published},
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Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it.
304.
Deville, Pierre; Linard, Catherine; Martin, Samuel; Gilbert, Marius; Stevens, Forrest R.; Gaughan, Andrea E.; Blondel, Vincent D.; Tatem, Andrew J.
Dynamic population mapping using mobile phone data Journal Article
In: Proceedings of the National Academy of Sciences, vol. 111, no. 45, pp. 15888-15893, 2014.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1073/pnas.1408439111,
title = {Dynamic population mapping using mobile phone data},
author = {Pierre Deville and Catherine Linard and Samuel Martin and Marius Gilbert and Forrest R. Stevens and Andrea E. Gaughan and Vincent D. Blondel and Andrew J. Tatem},
url = {https://www.pnas.org/doi/abs/10.1073/pnas.1408439111},
doi = {10.1073/pnas.1408439111},
year = {2014},
date = {2014-01-01},
journal = {Proceedings of the National Academy of Sciences},
volume = {111},
number = {45},
pages = {15888-15893},
abstract = {Knowing where people are is critical for accurate impact assessments and intervention planning, particularly those focused on population health, food security, climate change, conflicts, and natural disasters. This study demonstrates how data collected by mobile phone network operators can cost-effectively provide accurate and detailed maps of population distribution over national scales and any time period while guaranteeing phone users’ privacy. The methods outlined may be applied to estimate human population densities in low-income countries where data on population distributions may be scarce, outdated, and unreliable, or to estimate temporal variations in population density. The work highlights how facilitating access to anonymized mobile phone data might enable fast and cheap production of population maps in emergency and data-scarce situations. During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.},
keywords = {},
pubstate = {published},
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Knowing where people are is critical for accurate impact assessments and intervention planning, particularly those focused on population health, food security, climate change, conflicts, and natural disasters. This study demonstrates how data collected by mobile phone network operators can cost-effectively provide accurate and detailed maps of population distribution over national scales and any time period while guaranteeing phone users’ privacy. The methods outlined may be applied to estimate human population densities in low-income countries where data on population distributions may be scarce, outdated, and unreliable, or to estimate temporal variations in population density. The work highlights how facilitating access to anonymized mobile phone data might enable fast and cheap production of population maps in emergency and data-scarce situations. During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.
305.
Piel, Frédéric B; Tatem, Andrew J; Huang, Zhuojie; Gupta, Sunetra; Williams, Thomas N; Weatherall, David J
Global migration and the changing distribution of sickle haemoglobin: a quantitative study of temporal trends between 1960 and 2000 Journal Article
In: The Lancet Global Health, vol. 2, no. 2, pp. e80-e89, 2014, ISSN: 2214-109X.
Abstract | Links | BibTeX | Tags:
@article{PIEL2014e80,
title = {Global migration and the changing distribution of sickle haemoglobin: a quantitative study of temporal trends between 1960 and 2000},
author = {Frédéric B Piel and Andrew J Tatem and Zhuojie Huang and Sunetra Gupta and Thomas N Williams and David J Weatherall},
url = {https://www.sciencedirect.com/science/article/pii/S2214109X13701505},
doi = {https://doi.org/10.1016/S2214-109X(13)70150-5},
issn = {2214-109X},
year = {2014},
date = {2014-01-01},
journal = {The Lancet Global Health},
volume = {2},
number = {2},
pages = {e80-e89},
abstract = {Summary
Background
Changes in the geographical distribution of genetic disorders are often thought to happen slowly, especially when compared with infectious diseases. Whereas mutations, genetic drift, and natural selection take place over many generations, epidemics can spread through large populations within a few days or weeks. Nevertheless, population movements can interfere with these processes, and few studies have been done of their effect on genetic disorders. We aimed to investigate the effect of global migration on the distribution of the sickle-cell gene—the most common and clinically significant haemoglobin structural variant.
Methods
For each country, we extracted data from the World Bank's Global Bilateral Migration Database about international human migrations between 1960 and 2000. We combined this information with evidence-based estimates of national HbS allele frequencies, generated within a Bayesian geostatistical framework, to analyse temporal changes in the net numbers of migrants, and classified countries with an index summarising these temporal trends.
Findings
The number of international migrants increased from 92·6 million in 1960, to 165·2 million in 2000. The estimated global number of migrants with HbS increased from about 1·6 million in 1960, to 3·6 million in 2000. This increase was largely due to an increase in the number of migrants from countries with HbS allele frequencies higher than 10%, from 3·1 million in 1960, to 14·2 million in 2000. Additionally, the mean number of countries of origin for each destination country increased from 70 (SE 46) in 1960, to 98 (48) in 2000, showing an increasing diversity in the network of international migrations between countries. Our index of change map shows a patchy distribution of the magnitude of temporal changes, with the highest positive and negative values scattered across all continents.
Interpretation
Global human population movements have had a substantial effect on the distribution of the HbS gene. Population movements can create a long-term burden on health-care systems. Our findings, which emphasise countries in which migration fluxes are changing the most, should increase awareness about the global burden of haemoglobinopathies and encourage policy makers to implement specific public health interventions, such as screening programmes and genetic counselling.
Funding
Wellcome Trust, European Research Council, Bill & Melinda Gates Foundation, National Institute of Allergy and Infectious Diseases–National Institutes of Health, the Research and Policy for Infectious Disease Dynamics program, Fogarty International Center.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Summary
Background
Changes in the geographical distribution of genetic disorders are often thought to happen slowly, especially when compared with infectious diseases. Whereas mutations, genetic drift, and natural selection take place over many generations, epidemics can spread through large populations within a few days or weeks. Nevertheless, population movements can interfere with these processes, and few studies have been done of their effect on genetic disorders. We aimed to investigate the effect of global migration on the distribution of the sickle-cell gene—the most common and clinically significant haemoglobin structural variant.
Methods
For each country, we extracted data from the World Bank's Global Bilateral Migration Database about international human migrations between 1960 and 2000. We combined this information with evidence-based estimates of national HbS allele frequencies, generated within a Bayesian geostatistical framework, to analyse temporal changes in the net numbers of migrants, and classified countries with an index summarising these temporal trends.
Findings
The number of international migrants increased from 92·6 million in 1960, to 165·2 million in 2000. The estimated global number of migrants with HbS increased from about 1·6 million in 1960, to 3·6 million in 2000. This increase was largely due to an increase in the number of migrants from countries with HbS allele frequencies higher than 10%, from 3·1 million in 1960, to 14·2 million in 2000. Additionally, the mean number of countries of origin for each destination country increased from 70 (SE 46) in 1960, to 98 (48) in 2000, showing an increasing diversity in the network of international migrations between countries. Our index of change map shows a patchy distribution of the magnitude of temporal changes, with the highest positive and negative values scattered across all continents.
Interpretation
Global human population movements have had a substantial effect on the distribution of the HbS gene. Population movements can create a long-term burden on health-care systems. Our findings, which emphasise countries in which migration fluxes are changing the most, should increase awareness about the global burden of haemoglobinopathies and encourage policy makers to implement specific public health interventions, such as screening programmes and genetic counselling.
Funding
Wellcome Trust, European Research Council, Bill & Melinda Gates Foundation, National Institute of Allergy and Infectious Diseases–National Institutes of Health, the Research and Policy for Infectious Disease Dynamics program, Fogarty International Center.
Background
Changes in the geographical distribution of genetic disorders are often thought to happen slowly, especially when compared with infectious diseases. Whereas mutations, genetic drift, and natural selection take place over many generations, epidemics can spread through large populations within a few days or weeks. Nevertheless, population movements can interfere with these processes, and few studies have been done of their effect on genetic disorders. We aimed to investigate the effect of global migration on the distribution of the sickle-cell gene—the most common and clinically significant haemoglobin structural variant.
Methods
For each country, we extracted data from the World Bank's Global Bilateral Migration Database about international human migrations between 1960 and 2000. We combined this information with evidence-based estimates of national HbS allele frequencies, generated within a Bayesian geostatistical framework, to analyse temporal changes in the net numbers of migrants, and classified countries with an index summarising these temporal trends.
Findings
The number of international migrants increased from 92·6 million in 1960, to 165·2 million in 2000. The estimated global number of migrants with HbS increased from about 1·6 million in 1960, to 3·6 million in 2000. This increase was largely due to an increase in the number of migrants from countries with HbS allele frequencies higher than 10%, from 3·1 million in 1960, to 14·2 million in 2000. Additionally, the mean number of countries of origin for each destination country increased from 70 (SE 46) in 1960, to 98 (48) in 2000, showing an increasing diversity in the network of international migrations between countries. Our index of change map shows a patchy distribution of the magnitude of temporal changes, with the highest positive and negative values scattered across all continents.
Interpretation
Global human population movements have had a substantial effect on the distribution of the HbS gene. Population movements can create a long-term burden on health-care systems. Our findings, which emphasise countries in which migration fluxes are changing the most, should increase awareness about the global burden of haemoglobinopathies and encourage policy makers to implement specific public health interventions, such as screening programmes and genetic counselling.
Funding
Wellcome Trust, European Research Council, Bill & Melinda Gates Foundation, National Institute of Allergy and Infectious Diseases–National Institutes of Health, the Research and Policy for Infectious Disease Dynamics program, Fogarty International Center.
306.
Tatem, Andrew J.
Mapping the denominator: spatial demography in the measurement of progress Journal Article
In: International Health, vol. 6, no. 3, pp. 153-155, 2014, ISSN: 1876-3413.
Abstract | Links | BibTeX | Tags:
@article{,
title = {Mapping the denominator: spatial demography in the measurement of progress},
author = {Andrew J. Tatem},
url = {https://academic.oup.com/inthealth/article/6/3/153/2964850},
issn = {1876-3413},
year = {2014},
date = {2014-01-01},
urldate = {2014-01-01},
journal = {International Health},
volume = {6},
number = {3},
pages = {153-155},
abstract = {Measuring progress towards international health goals requires a reliable baseline from which to measure change and recent methodological advancements have advanced our abilities to measure, model and map the prevalence of health issues using sophisticated tools. The provision of burden estimates generally requires linking these estimates with spatial demographic data, but for many resource-poor countries data on total population sizes, distributions, compositions and temporal trends are lacking, prompting a reliance on uncertain estimates. Modern technologies and data archives are offering solutions, but the huge range of uncertainties that exist today in spatial denominator datasets will still be around for many years to come.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Measuring progress towards international health goals requires a reliable baseline from which to measure change and recent methodological advancements have advanced our abilities to measure, model and map the prevalence of health issues using sophisticated tools. The provision of burden estimates generally requires linking these estimates with spatial demographic data, but for many resource-poor countries data on total population sizes, distributions, compositions and temporal trends are lacking, prompting a reliance on uncertain estimates. Modern technologies and data archives are offering solutions, but the huge range of uncertainties that exist today in spatial denominator datasets will still be around for many years to come.
307.
Pindolia, Deepa K.; Garcia, Andres J.; Huang, Zhuojie; Smith, David L.; Alegana, Victor A.; Noor, Abdisalan M.; Snow, Robert W.; Tatem, Andrew J.
The demographics of human and malaria movement and migration patterns in East Africa Journal Article
In: Malaria Journal, vol. 12, no. 1, pp. 397, 2013, ISSN: 1475-2875.
Abstract | Links | BibTeX | Tags:
@article{Pindolia2013,
title = {The demographics of human and malaria movement and migration patterns in East Africa},
author = {Deepa K. Pindolia and Andres J. Garcia and Zhuojie Huang and David L. Smith and Victor A. Alegana and Abdisalan M. Noor and Robert W. Snow and Andrew J. Tatem},
url = {https://doi.org/10.1186/1475-2875-12-397},
doi = {10.1186/1475-2875-12-397},
issn = {1475-2875},
year = {2013},
date = {2013-11-05},
journal = {Malaria Journal},
volume = {12},
number = {1},
pages = {397},
abstract = {The quantification of parasite movements can provide valuable information for control strategy planning across all transmission intensities. Mobile parasite carrying individuals can instigate transmission in receptive areas, spread drug resistant strains and reduce the effectiveness of control strategies. The identification of mobile demographic groups, their routes of travel and how these movements connect differing transmission zones, potentially enables limited resources for interventions to be efficiently targeted over space, time and populations.},
keywords = {},
pubstate = {published},
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The quantification of parasite movements can provide valuable information for control strategy planning across all transmission intensities. Mobile parasite carrying individuals can instigate transmission in receptive areas, spread drug resistant strains and reduce the effectiveness of control strategies. The identification of mobile demographic groups, their routes of travel and how these movements connect differing transmission zones, potentially enables limited resources for interventions to be efficiently targeted over space, time and populations.
308.
Lu, Xin; Wetter, Erik; Bharti, Nita; Tatem, Andrew J.; Bengtsson, Linus
Approaching the Limit of Predictability in Human Mobility Journal Article
In: Scientific Reports, vol. 3, no. 1, pp. 2923, 2013, ISSN: 2045-2322.
Abstract | Links | BibTeX | Tags:
@article{Lu2013,
title = {Approaching the Limit of Predictability in Human Mobility},
author = {Xin Lu and Erik Wetter and Nita Bharti and Andrew J. Tatem and Linus Bengtsson},
url = {https://doi.org/10.1038/srep02923},
doi = {10.1038/srep02923},
issn = {2045-2322},
year = {2013},
date = {2013-10-11},
journal = {Scientific Reports},
volume = {3},
number = {1},
pages = {2923},
abstract = {In this study we analyze the travel patterns of 500,000 individuals in Cote d'Ivoire using mobile phone call data records. By measuring the uncertainties of movements using entropy, considering both the frequencies and temporal correlations of individual trajectories, we find that the theoretical maximum predictability is as high as 88%. To verify whether such a theoretical limit can be approached, we implement a series of Markov chain (MC) based models to predict the actual locations visited by each user. Results show that MC models can produce a prediction accuracy of 87% for stationary trajectories and 95% for non-stationary trajectories. Our findings indicate that human mobility is highly dependent on historical behaviors and that the maximum predictability is not only a fundamental theoretical limit for potential predictive power, but also an approachable target for actual prediction accuracy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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In this study we analyze the travel patterns of 500,000 individuals in Cote d'Ivoire using mobile phone call data records. By measuring the uncertainties of movements using entropy, considering both the frequencies and temporal correlations of individual trajectories, we find that the theoretical maximum predictability is as high as 88%. To verify whether such a theoretical limit can be approached, we implement a series of Markov chain (MC) based models to predict the actual locations visited by each user. Results show that MC models can produce a prediction accuracy of 87% for stationary trajectories and 95% for non-stationary trajectories. Our findings indicate that human mobility is highly dependent on historical behaviors and that the maximum predictability is not only a fundamental theoretical limit for potential predictive power, but also an approachable target for actual prediction accuracy.
309.
Tatem, Andrew J.; Garcia, Andres J.; Snow, Robert W.; Noor, Abdisalan M.; Gaughan, Andrea E.; Gilbert, Marius; Linard, Catherine
Millennium development health metrics: where do Africa's children and women of childbearing age live? Journal Article
In: Population Health Metrics, vol. 11, no. 1, pp. 11, 2013, ISSN: 1478-7954.
Abstract | Links | BibTeX | Tags:
@article{Tatem2013,
title = {Millennium development health metrics: where do Africa's children and women of childbearing age live?},
author = {Andrew J. Tatem and Andres J. Garcia and Robert W. Snow and Abdisalan M. Noor and Andrea E. Gaughan and Marius Gilbert and Catherine Linard},
url = {https://doi.org/10.1186/1478-7954-11-11},
doi = {10.1186/1478-7954-11-11},
issn = {1478-7954},
year = {2013},
date = {2013-07-23},
journal = {Population Health Metrics},
volume = {11},
number = {1},
pages = {11},
abstract = {The Millennium Development Goals (MDGs) have prompted an expansion in approaches to deriving health metrics to measure progress toward their achievement. Accurate measurements should take into account the high degrees of spatial heterogeneity in health risks across countries, and this has prompted the development of sophisticated cartographic techniques for mapping and modeling risks. Conversion of these risks to relevant population-based metrics requires equally detailed information on the spatial distribution and attributes of the denominator populations. However, spatial information on age and sex composition over large areas is lacking, prompting many influential studies that have rigorously accounted for health risk heterogeneities to overlook the substantial demographic variations that exist subnationally and merely apply national-level adjustments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Millennium Development Goals (MDGs) have prompted an expansion in approaches to deriving health metrics to measure progress toward their achievement. Accurate measurements should take into account the high degrees of spatial heterogeneity in health risks across countries, and this has prompted the development of sophisticated cartographic techniques for mapping and modeling risks. Conversion of these risks to relevant population-based metrics requires equally detailed information on the spatial distribution and attributes of the denominator populations. However, spatial information on age and sex composition over large areas is lacking, prompting many influential studies that have rigorously accounted for health risk heterogeneities to overlook the substantial demographic variations that exist subnationally and merely apply national-level adjustments.
310.
Tatem, Andrew J.; Gething, Peter W.; Smith, David L.; Hay, Simon I.
Urbanization and the global malaria recession Journal Article
In: Malaria Journal, vol. 12, no. 1, pp. 133, 2013, ISSN: 1475-2875.
Abstract | Links | BibTeX | Tags:
@article{Tatem2013b,
title = {Urbanization and the global malaria recession},
author = {Andrew J. Tatem and Peter W. Gething and David L. Smith and Simon I. Hay},
url = {https://doi.org/10.1186/1475-2875-12-133},
doi = {10.1186/1475-2875-12-133},
issn = {1475-2875},
year = {2013},
date = {2013-04-17},
journal = {Malaria Journal},
volume = {12},
number = {1},
pages = {133},
abstract = {The past century has seen a significant contraction in the global extent of malaria transmission, resulting in over 50 countries being declared malaria free, and many regions of currently endemic countries eliminating the disease. Moreover, substantial reductions in transmission have been seen since 1900 in those areas that remain endemic today. Recent work showed that this malaria recession was unlikely to have been driven by climatic factors, and that control measures likely played a significant role. It has long been considered, however, that economic development, and particularly urbanization, has also been a causal factor. The urbanization process results in profound socio-economic and landscape changes that reduce malaria transmission, but the magnitude and extent of these effects on global endemicity reductions are poorly understood.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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The past century has seen a significant contraction in the global extent of malaria transmission, resulting in over 50 countries being declared malaria free, and many regions of currently endemic countries eliminating the disease. Moreover, substantial reductions in transmission have been seen since 1900 in those areas that remain endemic today. Recent work showed that this malaria recession was unlikely to have been driven by climatic factors, and that control measures likely played a significant role. It has long been considered, however, that economic development, and particularly urbanization, has also been a causal factor. The urbanization process results in profound socio-economic and landscape changes that reduce malaria transmission, but the magnitude and extent of these effects on global endemicity reductions are poorly understood.
311.
Cohen, Justin M.; Dlamini, Sabelo; Novotny, Joseph M.; Kandula, Deepika; Kunene, Simon; Tatem, Andrew J.
Rapid case-based mapping of seasonal malaria transmission risk for strategic elimination planning in Swaziland Journal Article
In: Malaria Journal, vol. 12, no. 1, pp. 61, 2013, ISSN: 1475-2875.
Abstract | Links | BibTeX | Tags:
@article{Cohen2013,
title = {Rapid case-based mapping of seasonal malaria transmission risk for strategic elimination planning in Swaziland},
author = {Justin M. Cohen and Sabelo Dlamini and Joseph M. Novotny and Deepika Kandula and Simon Kunene and Andrew J. Tatem},
url = {https://doi.org/10.1186/1475-2875-12-61},
doi = {10.1186/1475-2875-12-61},
issn = {1475-2875},
year = {2013},
date = {2013-02-11},
journal = {Malaria Journal},
volume = {12},
number = {1},
pages = {61},
abstract = {As successful malaria control programmes move towards elimination, they must identify residual transmission foci, target vector control to high-risk areas, focus on both asymptomatic and symptomatic infections, and manage importation risk. High spatial and temporal resolution maps of malaria risk can support all of these activities, but commonly available malaria maps are based on parasite rate, a poor metric for measuring malaria at extremely low prevalence. New approaches are required to provide case-based risk maps to countries seeking to identify remaining hotspots of transmission while managing the risk of transmission from imported cases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As successful malaria control programmes move towards elimination, they must identify residual transmission foci, target vector control to high-risk areas, focus on both asymptomatic and symptomatic infections, and manage importation risk. High spatial and temporal resolution maps of malaria risk can support all of these activities, but commonly available malaria maps are based on parasite rate, a poor metric for measuring malaria at extremely low prevalence. New approaches are required to provide case-based risk maps to countries seeking to identify remaining hotspots of transmission while managing the risk of transmission from imported cases.
312.
Gaughan, Andrea E.; Stevens, Forrest R.; Linard, Catherine; Jia, Peng; Tatem, Andrew J.
High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015 Journal Article
In: PLOS ONE, vol. 8, no. 2, pp. 1-11, 2013.
Abstract | Links | BibTeX | Tags:
@article{10.1371/journal.pone.0055882,
title = {High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015},
author = {Andrea E. Gaughan and Forrest R. Stevens and Catherine Linard and Peng Jia and Andrew J. Tatem},
url = {https://doi.org/10.1371/journal.pone.0055882},
doi = {10.1371/journal.pone.0055882},
year = {2013},
date = {2013-01-01},
journal = {PLOS ONE},
volume = {8},
number = {2},
pages = {1-11},
publisher = {Public Library of Science},
abstract = {Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.
313.
Caughlin, T. Trevor; Ruktanonchai, Nick; Acevedo, Miguel A.; Lopiano, Kenneth K.; Prosper, Olivia; Eagle, Nathan; Tatem, Andrew J.
Place-Based Attributes Predict Community Membership in a Mobile Phone Communication Network Journal Article
In: PLOS ONE, vol. 8, no. 2, pp. 1-9, 2013.
Abstract | Links | BibTeX | Tags:
@article{10.1371/journal.pone.0056057,
title = {Place-Based Attributes Predict Community Membership in a Mobile Phone Communication Network},
author = {T. Trevor Caughlin and Nick Ruktanonchai and Miguel A. Acevedo and Kenneth K. Lopiano and Olivia Prosper and Nathan Eagle and Andrew J. Tatem},
url = {https://doi.org/10.1371/journal.pone.0056057},
doi = {10.1371/journal.pone.0056057},
year = {2013},
date = {2013-01-01},
journal = {PLOS ONE},
volume = {8},
number = {2},
pages = {1-9},
publisher = {Public Library of Science},
abstract = {Social networks can be organized into communities of closely connected nodes, a property known as modularity. Because diseases, information, and behaviors spread faster within communities than between communities, understanding modularity has broad implications for public policy, epidemiology and the social sciences. Explanations for community formation in social networks often incorporate the attributes of individual people, such as gender, ethnicity or shared activities. High modularity is also a property of large-scale social networks, where each node represents a population of individuals at a location, such as call flow between mobile phone towers. However, whether or not place-based attributes, including land cover and economic activity, can predict community membership for network nodes in large-scale networks remains unknown. We describe the pattern of modularity in a mobile phone communication network in the Dominican Republic, and use a linear discriminant analysis (LDA) to determine whether geographic context can explain community membership. Our results demonstrate that place-based attributes, including sugar cane production, urbanization, distance to the nearest airport, and wealth, correctly predicted community membership for over 70% of mobile phone towers. We observed a strongly positive correlation (r = 0.97) between the modularity score and the predictive ability of the LDA, suggesting that place-based attributes can accurately represent the processes driving modularity. In the absence of social network data, the methods we present can be used to predict community membership over large scales using solely place-based attributes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Social networks can be organized into communities of closely connected nodes, a property known as modularity. Because diseases, information, and behaviors spread faster within communities than between communities, understanding modularity has broad implications for public policy, epidemiology and the social sciences. Explanations for community formation in social networks often incorporate the attributes of individual people, such as gender, ethnicity or shared activities. High modularity is also a property of large-scale social networks, where each node represents a population of individuals at a location, such as call flow between mobile phone towers. However, whether or not place-based attributes, including land cover and economic activity, can predict community membership for network nodes in large-scale networks remains unknown. We describe the pattern of modularity in a mobile phone communication network in the Dominican Republic, and use a linear discriminant analysis (LDA) to determine whether geographic context can explain community membership. Our results demonstrate that place-based attributes, including sugar cane production, urbanization, distance to the nearest airport, and wealth, correctly predicted community membership for over 70% of mobile phone towers. We observed a strongly positive correlation (r = 0.97) between the modularity score and the predictive ability of the LDA, suggesting that place-based attributes can accurately represent the processes driving modularity. In the absence of social network data, the methods we present can be used to predict community membership over large scales using solely place-based attributes.
314.
Wesolowski, Amy; Buckee, Caroline O.; Pindolia, Deepa K.; Eagle, Nathan; Smith, David L.; Garcia, Andres J.; Tatem, Andrew J.
The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales Journal Article
In: PLOS ONE, vol. 8, no. 1, pp. 1-8, 2013.
Abstract | Links | BibTeX | Tags:
@article{10.1371/journal.pone.0052971,
title = {The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales},
author = {Amy Wesolowski and Caroline O. Buckee and Deepa K. Pindolia and Nathan Eagle and David L. Smith and Andres J. Garcia and Andrew J. Tatem},
url = {https://doi.org/10.1371/journal.pone.0052971},
doi = {10.1371/journal.pone.0052971},
year = {2013},
date = {2013-01-01},
journal = {PLOS ONE},
volume = {8},
number = {1},
pages = {1-8},
publisher = {Public Library of Science},
abstract = {Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data.
315.
Linard, Catherine; Tatem, Andrew J.; Gilbert, Marius
Modelling spatial patterns of urban growth in Africa Journal Article
In: Applied Geography, vol. 44, pp. 23-32, 2013, ISSN: 0143-6228.
Abstract | Links | BibTeX | Tags: Africa, Boosted regression trees, Modelling, Spatial pattern, Urban growth
@article{LINARD201323,
title = {Modelling spatial patterns of urban growth in Africa},
author = {Catherine Linard and Andrew J. Tatem and Marius Gilbert},
url = {https://www.sciencedirect.com/science/article/pii/S0143622813001707},
doi = {https://doi.org/10.1016/j.apgeog.2013.07.009},
issn = {0143-6228},
year = {2013},
date = {2013-01-01},
journal = {Applied Geography},
volume = {44},
pages = {23-32},
abstract = {The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.},
keywords = {Africa, Boosted regression trees, Modelling, Spatial pattern, Urban growth},
pubstate = {published},
tppubtype = {article}
}
The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.
316.
Metcalf, C. J. E.; Cohen, C.; Lessler, J.; McAnerney, J. M.; Ntshoe, G. M.; Puren, A.; Klepac, P.; Tatem, A.; Grenfell, B. T.; Bjørnstad, O. N.
Implications of spatially heterogeneous vaccination coverage for the risk of congenital rubella syndrome in South Africa Journal Article
In: Journal of The Royal Society Interface, vol. 10, no. 78, pp. 20120756, 2013.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1098/rsif.2012.0756,
title = {Implications of spatially heterogeneous vaccination coverage for the risk of congenital rubella syndrome in South Africa},
author = {C. J. E. Metcalf and C. Cohen and J. Lessler and J. M. McAnerney and G. M. Ntshoe and A. Puren and P. Klepac and A. Tatem and B. T. Grenfell and O. N. Bjørnstad},
url = {https://royalsocietypublishing.org/doi/abs/10.1098/rsif.2012.0756},
doi = {10.1098/rsif.2012.0756},
year = {2013},
date = {2013-01-01},
journal = {Journal of The Royal Society Interface},
volume = {10},
number = {78},
pages = {20120756},
abstract = {Rubella is generally a mild childhood disease, but infection during early pregnancy may cause spontaneous abortion or congenital rubella syndrome (CRS), which may entail a variety of birth defects. Since vaccination at levels short of those necessary to achieve eradication may increase the average age of infection, and thus potentially the CRS burden, introduction of the vaccine has been limited to contexts where coverage is high. Recent work suggests that spatial heterogeneity in coverage should also be a focus of concern. Here, we use a detailed dataset from South Africa to explore the implications of heterogeneous vaccination for the burden of CRS, introducing realistic vaccination scenarios based on reported levels of measles vaccine coverage. Our results highlight the potential impact of country-wide reductions of incidence of rubella on the local CRS burdens in districts with small population sizes. However, simulations indicate that if rubella vaccination is introduced with coverage reflecting current estimates for measles coverage in South Africa, the burden of CRS is likely to be reduced overall over a 30 year time horizon by a factor of 3, despite the fact that this coverage is lower than the traditional 80 per cent rule of thumb for vaccine introduction, probably owing to a combination of relatively low birth and transmission rates. We conclude by discussing the likely impact of private-sector vaccination.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rubella is generally a mild childhood disease, but infection during early pregnancy may cause spontaneous abortion or congenital rubella syndrome (CRS), which may entail a variety of birth defects. Since vaccination at levels short of those necessary to achieve eradication may increase the average age of infection, and thus potentially the CRS burden, introduction of the vaccine has been limited to contexts where coverage is high. Recent work suggests that spatial heterogeneity in coverage should also be a focus of concern. Here, we use a detailed dataset from South Africa to explore the implications of heterogeneous vaccination for the burden of CRS, introducing realistic vaccination scenarios based on reported levels of measles vaccine coverage. Our results highlight the potential impact of country-wide reductions of incidence of rubella on the local CRS burdens in districts with small population sizes. However, simulations indicate that if rubella vaccination is introduced with coverage reflecting current estimates for measles coverage in South Africa, the burden of CRS is likely to be reduced overall over a 30 year time horizon by a factor of 3, despite the fact that this coverage is lower than the traditional 80 per cent rule of thumb for vaccine introduction, probably owing to a combination of relatively low birth and transmission rates. We conclude by discussing the likely impact of private-sector vaccination.
317.
Smith, David L.; Cohen, Justin M.; Chiyaka, Christinah; Johnston, Geoffrey; Gething, Peter W.; Gosling, Roly; Buckee, Caroline O.; Laxminarayan, Ramanan; Hay, Simon I.; Tatem, Andrew J.
A sticky situation: the unexpected stability of malaria elimination Journal Article
In: Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 368, no. 1623, pp. 20120145, 2013.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1098/rstb.2012.0145,
title = {A sticky situation: the unexpected stability of malaria elimination},
author = {David L. Smith and Justin M. Cohen and Christinah Chiyaka and Geoffrey Johnston and Peter W. Gething and Roly Gosling and Caroline O. Buckee and Ramanan Laxminarayan and Simon I. Hay and Andrew J. Tatem},
url = {https://royalsocietypublishing.org/doi/abs/10.1098/rstb.2012.0145},
doi = {10.1098/rstb.2012.0145},
year = {2013},
date = {2013-01-01},
journal = {Philosophical Transactions of the Royal Society B: Biological Sciences},
volume = {368},
number = {1623},
pages = {20120145},
abstract = {Malaria eradication involves eliminating malaria from every country where transmission occurs. Current theory suggests that the post-elimination challenges of remaining malaria-free by stopping transmission from imported malaria will have onerous operational and financial requirements. Although resurgent malaria has occurred in a majority of countries that tried but failed to eliminate malaria, a review of resurgence in countries that successfully eliminated finds only four such failures out of 50 successful programmes. Data documenting malaria importation and onwards transmission in these countries suggests malaria transmission potential has declined by more than 50-fold (i.e. more than 98%) since before elimination. These outcomes suggest that elimination is a surprisingly stable state. Elimination's ‘stickiness’ must be explained either by eliminating countries starting off qualitatively different from non-eliminating countries or becoming different once elimination was achieved. Countries that successfully eliminated were wealthier and had lower baseline endemicity than those that were unsuccessful, but our analysis shows that those same variables were at best incomplete predictors of the patterns of resurgence. Stability is reinforced by the loss of immunity to disease and by the health system's increasing capacity to control malaria transmission after elimination through routine treatment of cases with antimalarial drugs supplemented by malaria outbreak control. Human travel patterns reinforce these patterns; as malaria recedes, fewer people carry malaria from remote endemic areas to remote areas where transmission potential remains high. Establishment of an international resource with backup capacity to control large outbreaks can make elimination stickier, increase the incentives for countries to eliminate, and ensure steady progress towards global eradication. Although available evidence supports malaria elimination's stickiness at moderate-to-low transmission in areas with well-developed health systems, it is not yet clear if such patterns will hold in all areas. The sticky endpoint changes the projected costs of maintaining elimination and makes it substantially more attractive for countries acting alone, and it makes spatially progressive elimination a sensible strategy for a malaria eradication endgame.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Malaria eradication involves eliminating malaria from every country where transmission occurs. Current theory suggests that the post-elimination challenges of remaining malaria-free by stopping transmission from imported malaria will have onerous operational and financial requirements. Although resurgent malaria has occurred in a majority of countries that tried but failed to eliminate malaria, a review of resurgence in countries that successfully eliminated finds only four such failures out of 50 successful programmes. Data documenting malaria importation and onwards transmission in these countries suggests malaria transmission potential has declined by more than 50-fold (i.e. more than 98%) since before elimination. These outcomes suggest that elimination is a surprisingly stable state. Elimination's ‘stickiness’ must be explained either by eliminating countries starting off qualitatively different from non-eliminating countries or becoming different once elimination was achieved. Countries that successfully eliminated were wealthier and had lower baseline endemicity than those that were unsuccessful, but our analysis shows that those same variables were at best incomplete predictors of the patterns of resurgence. Stability is reinforced by the loss of immunity to disease and by the health system's increasing capacity to control malaria transmission after elimination through routine treatment of cases with antimalarial drugs supplemented by malaria outbreak control. Human travel patterns reinforce these patterns; as malaria recedes, fewer people carry malaria from remote endemic areas to remote areas where transmission potential remains high. Establishment of an international resource with backup capacity to control large outbreaks can make elimination stickier, increase the incentives for countries to eliminate, and ensure steady progress towards global eradication. Although available evidence supports malaria elimination's stickiness at moderate-to-low transmission in areas with well-developed health systems, it is not yet clear if such patterns will hold in all areas. The sticky endpoint changes the projected costs of maintaining elimination and makes it substantially more attractive for countries acting alone, and it makes spatially progressive elimination a sensible strategy for a malaria eradication endgame.
318.
Qi, Qiuyin; Guerra, Carlos A.; Moyes, Catherine L.; Elyazar, Iqbal AR F.; Gething, Peter W.; Hay, Simon I.; Tatem, Andrew J.
The effects of urbanization on global Plasmodium vivax malaria transmission Journal Article
In: Malaria Journal, vol. 11, no. 1, pp. 403, 2012, ISSN: 1475-2875.
Abstract | Links | BibTeX | Tags:
@article{Qi2012,
title = {The effects of urbanization on global Plasmodium vivax malaria transmission},
author = {Qiuyin Qi and Carlos A. Guerra and Catherine L. Moyes and Iqbal AR F. Elyazar and Peter W. Gething and Simon I. Hay and Andrew J. Tatem},
url = {https://doi.org/10.1186/1475-2875-11-403},
doi = {10.1186/1475-2875-11-403},
issn = {1475-2875},
year = {2012},
date = {2012-12-05},
journal = {Malaria Journal},
volume = {11},
number = {1},
pages = {403},
abstract = {Many recent studies have examined the impact of urbanization on Plasmodium falciparum malaria endemicity and found a general trend of reduced transmission in urban areas. However, none has examined the effect of urbanization on Plasmodium vivax malaria, which is the most widely distributed malaria species and can also cause severe clinical syndromes in humans. In this study, a set of 10,003 community-based P. vivax parasite rate (Pv PR) surveys are used to explore the relationships between Pv PR in urban and rural settings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many recent studies have examined the impact of urbanization on Plasmodium falciparum malaria endemicity and found a general trend of reduced transmission in urban areas. However, none has examined the effect of urbanization on Plasmodium vivax malaria, which is the most widely distributed malaria species and can also cause severe clinical syndromes in humans. In this study, a set of 10,003 community-based P. vivax parasite rate (Pv PR) surveys are used to explore the relationships between Pv PR in urban and rural settings.
319.
Pindolia, Deepa K.; Garcia, Andres J.; Wesolowski, Amy; Smith, David L.; Buckee, Caroline O.; Noor, Abdisalan M.; Snow, Robert W.; Tatem, Andrew J.
Human movement data for malaria control and elimination strategic planning Journal Article
In: Malaria Journal, vol. 11, no. 1, pp. 205, 2012, ISSN: 1475-2875.
Abstract | Links | BibTeX | Tags:
@article{Pindolia2012,
title = {Human movement data for malaria control and elimination strategic planning},
author = {Deepa K. Pindolia and Andres J. Garcia and Amy Wesolowski and David L. Smith and Caroline O. Buckee and Abdisalan M. Noor and Robert W. Snow and Andrew J. Tatem},
url = {https://doi.org/10.1186/1475-2875-11-205},
doi = {10.1186/1475-2875-11-205},
issn = {1475-2875},
year = {2012},
date = {2012-06-18},
journal = {Malaria Journal},
volume = {11},
number = {1},
pages = {205},
abstract = {Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.
320.
Tatem, Andrew J.; Adamo, Susana; Bharti, Nita; Burgert, Clara R.; Castro, Marcia; Dorelien, Audrey; Fink, Gunter; Linard, Catherine; John, Mendelsohn; Montana, Livia; Montgomery, Mark R.; Nelson, Andrew; Noor, Abdisalan M.; Pindolia, Deepa; Yetman, Greg; Balk, Deborah
Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation Journal Article
In: Population Health Metrics, vol. 10, no. 1, pp. 8, 2012, ISSN: 1478-7954.
Abstract | Links | BibTeX | Tags:
@article{Tatem2012,
title = {Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation},
author = {Andrew J. Tatem and Susana Adamo and Nita Bharti and Clara R. Burgert and Marcia Castro and Audrey Dorelien and Gunter Fink and Catherine Linard and Mendelsohn John and Livia Montana and Mark R. Montgomery and Andrew Nelson and Abdisalan M. Noor and Deepa Pindolia and Greg Yetman and Deborah Balk},
url = {https://doi.org/10.1186/1478-7954-10-8},
doi = {10.1186/1478-7954-10-8},
issn = {1478-7954},
year = {2012},
date = {2012-05-16},
journal = {Population Health Metrics},
volume = {10},
number = {1},
pages = {8},
abstract = {The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models.
