Multiple systems estimation is a key approach for quantifying hidden populations such as the number of victims of modern slavery. The UK Government published an estimate of 10,000 to 13,000 victims, constructed by the present author, as part of the strategy leading to the Modern Slavery Act 2015. This estimate was obtained by a stepwise multiple systems method based on six lists. Further investigation shows that a small proportion of the possible models give rather different answers, and that other model fitting approaches may choose one of these. Three data sets collected in the field of modern slavery, together with a data set about the death toll in the Kosovo conflict, are used to investigate the stability and robustness of various multiple systems estimate methods. The crucial aspect is the way that interactions between lists are modelled, because these can substantially affect the results. Model selection and Bayesian approaches are considered in detail, in particular to assess their stability and robustness when applied to real modern slavery data. A new Markov Chain Monte Carlo Bayesian approach is developed; overall, this gives robust and stable results at least for the examples considered. The software and datasets are freely and publicly available to facilitate wider implementation and further research.
This article presents a cross-national comparative analysis of the relationship between different dimensions of globalization and modern slavery. It argues that both the economic and political dimensions of globalization are strongly associated with lower levels of slavery prevalence. Recent estimates suggest there are more than 40 million people in some form of slavery and the United Nations has committed the world to ending this problem by 2030. Some argue that a race to the bottom, and the structure of economic incentives associated with globalization have contributed to the problem of modern slavery. Others argue that increased openness and the diffusion of values, the spread of democratic forms of rule, and the advance of human rights that come with globalization limit modern slavery. This article presents a preliminary empirical analysis of these arguments using data on slavery prevalence across more than 60 countries and various measures of economic and political globalization. The analysis shows that economic measures of globalization and higher levels of democracy are significantly related to lower levels of slavery prevalence, even after controlling for armed conflict and regional differentiation. In order to support these findings, the article examines the international law on slavery, definitions and conceptions of modern slavery, and comparative data on slavery prevalence modeled across indicators of economic and political globalization. It concludes with a discussion of the implications of these findings for the trade-offs between globalization and modern slavery.
This article presents a cross-national comparative analysis of the relationship between different dimensions of globalization and modern slavery. It argues that both the economic and political dimensions of globalization are strongly associated with lower levels of slavery prevalence. Recent estimates suggest there are more than 40 million people in some form of slavery and the United Nations has committed the world to ending this problem by 2030. Some argue that a race to the bottom, and the structure of economic incentives associated with globalization have contributed to the problem of modern slavery. Others argue that increased openness and the diffusion of values, the spread of democratic forms of rule, and the advance of human rights that come with globalization limit modern slavery. This article presents a preliminary empirical analysis of these arguments using data on slavery prevalence across more than 60 countries and various measures of economic and political globalization. The analysis shows that economic measures of globalization and higher levels of democracy are significantly related to lower levels of slavery prevalence, even after controlling for armed conflict and regional differentiation. In order to support these findings, the article examines the international law on slavery, definitions and conceptions of modern slavery, and comparative data on slavery prevalence modeled across indicators of economic and political globalization. It concludes with a discussion of the implications of these findings for the trade-offs between globalization and modern slavery.
This article presents a cross-national comparative analysis of the relationship between different dimensions of globalization and modern slavery. It argues that both the economic and political dimensions of globalization are strongly associated with lower levels of slavery prevalence. Recent estimates suggest there are more than 40 million people in some form of slavery and the United Nations has committed the world to ending this problem by 2030. Some argue that a race to the bottom, and the structure of economic incentives associated with globalization have contributed to the problem of modern slavery. Others argue that increased openness and the diffusion of values, the spread of democratic forms of rule, and the advance of human rights that come with globalization limit modern slavery. This article presents a preliminary empirical analysis of these arguments using data on slavery prevalence across more than 60 countries and various measures of economic and political globalization. The analysis shows that economic measures of globalization and higher levels of democracy are significantly related to lower levels of slavery prevalence, even after controlling for armed conflict and regional differentiation. In order to support these findings, the article examines the international law on slavery, definitions and conceptions of modern slavery, and comparative data on slavery prevalence modeled across indicators of economic and political globalization. It concludes with a discussion of the implications of these findings for the trade-offs between globalization and modern slavery.
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARSCoV- 2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11–15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-tomiddle-income countries. This will provide important information for planning exit strategies that balance socioeconomic benefits with public health.
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.
In: Thompson , R N , Hollingsworth , T D , Isham , V , Arribas-Bel , D , Ashby , B , Britton , T , Challenor , P , Chappell , L H K , Clapham , H , Cunniffe , N J , Dawid , A P , Donnelly , C A , Eggo , R M , Funk , S , Gilbert , N , Glendinning , P , Gog , J R , Hart , W S , Heesterbeek , H , House , T , Keeling , M , Kiss , I Z , Kretzschmar , M E , Lloyd , A L , McBryde , E S , McCaw , J M , McKinley , T J , Miller , J C , Morris , M , O'Neill , P D , Parag , K V , Pearson , C A B , Pellis , L , Pulliam , J R C , Ross , J V , Tomba , G S , Silverman , B W , Struchiner , C J , Tildesley , M J , Trapman , P , Webb , C R , Mollison , D & Restif , O 2020 , ' Key questions for modelling COVID-19 exit strategies ' , Proceedings of the Royal Society B , vol. 287 , no. 1932 , pp. 20201405 . https://doi.org/10.1098/rspb.2020.1405
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11–15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.