Violent conflict in the Middle East has forced millions to flee their homes and seek refuge in host nations around the globe. Across three studies, we asked American participants (N ∼ 1,500) to consider a refugee-resettlement policy that would bring displaced families from the Middle East into their communities, and tracked the items of information these Americans were interested in seeing during the consideration of their decision. Results suggest that participants who rejected the resettlement policy were especially concerned with security-related information and uninterested in humanitarian-related information, while participants who supported the policy expressed interest in a more balanced ratio of security and humanitarian-related information. We situate these findings within the broader literature on attitude-confirming behaviour (e.g. conformation bias, selective exposure) and discuss how information spotlighting might exacerbate polarization on politically charged issues like refugee policy.
The ongoing Russian aggression against Ukraine has forced over eight million people to migrate out of Ukraine. Understanding the dynamics of forced migration is essential for policy-making and for delivering humanitarian assistance. Existing work is hindered by a reliance on observational data which is only available well after the fact. In this work, we study the efficacy of a data-driven agent-based framework motivated by social and behavioral theory in predicting outflow of migrants as a result of conflict events during the initial phase of the Ukraine war. We discuss policy use cases for the proposed framework by demonstrating how it can leverage refugee demographic details to answer pressing policy questions. We also show how to incorporate conflict forecast scenarios to predict future conflict-induced migration flows. Detailed future migration estimates across various conflict scenarios can both help to reduce policymaker uncertainty and improve allocation and staging of limited humanitarian resources in crisis settings.
more » « less- NSF-PAR ID:
- 10496044
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- PNAS Nexus
- Volume:
- 3
- Issue:
- 3
- ISSN:
- 2752-6542
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Predicting where crop pests and diseases can occur, both now and in the future under different climate change scenarios, is a major challenge for crop management. One solution is to estimate the fundamental thermal niche of the pest/disease to indicate where establishment is possible. Here, we develop methods for estimating and displaying the fundamental thermal niche of pests and pathogens and apply these methods to Huanglongbing (HLB), a vector‐borne disease that is currently threatening the citrus industry worldwide.
We derive a suitability metric based on a mathematical model of HLB transmission between tree hosts and its vector
Diaphorina citri , and incorporate the effect of temperature on vector traits using data from laboratory experiments performed at different temperatures. We validate the model using data on the historical range of HLB.Our model predicts that transmission of HLB is possible between 16 and 33°C with peak transmission at ~25°C. The greatest uncertainty in our suitability metric is associated with the mortality of the vectors at peak transmission, and fecundity at the edges of the thermal range, indicating that these parameters need further experimental work.
We produce global thermal niche maps by plotting how many months each location is suitable for establishment of the pest/disease. This analysis reveals that the highest suitability for HLB occurs near the equator in large citrus‐producing regions, such as Brazil and South‐East Asia. Within the Northern Hemisphere, the Iberian peninsula and California are HLB suitable for up to 7 months of the year and are free of HLB currently.
Policy implications . We create a thermal niche map which indicates the places at greatest risk of establishment should a crop disease or pest enter these regions. This indicates where surveillance should be focused to prevent establishment. Our mechanistic method can be used to predict new areas for Huanglongbing transmission under different climate change scenarios and is easily adapted to other vector‐borne diseases and crop pests. -
The Russian invasion of Ukraine on February 24, 2022, has displaced more than a quarter of the population. Assessing disease burdens among displaced people is instrumental in informing global public health and humanitarian aid efforts. We estimated the disease burden in Ukrainians displaced both within Ukraine and to other countries by combining a spatiotemporal model of forcible displacement with age- and gender-specific estimates of cardiovascular disease (CVD), diabetes, cancer, HIV, and tuberculosis (TB) in each of Ukraine’s 629 raions (i.e., districts). Among displaced Ukrainians as of May 13, we estimated that more than 2.63 million have CVDs, at least 615,000 have diabetes, and over 98,500 have cancer. In addition, more than 86,000 forcibly displaced individuals are living with HIV, and approximately 13,500 have TB. We estimated that the disease prevalence among refugees was lower than the national disease prevalence before the invasion. Accounting for internal displacement and healthcare facilities impacted by the conflict, we estimated that the number of people per hospital has increased by more than two-fold in some areas. As regional healthcare systems come under increasing strain, these estimates can inform the allocation of critical resources under shifting disease burdens.more » « less
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The Russian invasion of Ukraine on February 24, 2022, has displaced more than a quarter of the population. Assessing disease burdens among displaced people is instrumental in informing global public health and humanitarian aid efforts. We estimated the disease burden in Ukrainians displaced both within Ukraine and to other countries by combining a spatiotemporal model of forcible displacement with age- and gender-specific estimates of cardiovascular disease (CVD), diabetes, cancer, HIV, and tuberculosis (TB) in each of Ukraine's 629 raions (i.e., districts). Among displaced Ukrainians as of May 13, we estimated that more than 2.63 million have CVDs, at least 615,000 have diabetes, and over 98,500 have cancer. In addition, more than 86,000 forcibly displaced individuals are living with HIV, and approximately 13,500 have TB. We estimated that the disease prevalence among refugees was lower than the national disease prevalence before the invasion. Accounting for internal displacement and healthcare facilities impacted by the conflict, we estimated that the number of people per hospital has increased by more than two-fold in some areas. As regional healthcare systems come under increasing strain, these estimates can inform the allocation of critical resources under shifting disease burdens.more » « less
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Abstract Background The development of public health policy is inextricably linked with governance structure. In our increasingly globalized world, human migration and infectious diseases often span multiple administrative jurisdictions that might have different systems of government and divergent management objectives. However, few studies have considered how the allocation of regulatory authority among jurisdictions can affect disease management outcomes.
Methods Here we evaluate the relative merits of decentralized and centralized management by developing and numerically analyzing a two-jurisdiction
SIRS model that explicitly incorporates migration. In our model, managers choose between vaccination, isolation, medication, border closure, and a travel ban on infected individuals while aiming to minimize either the number of cases or the number of deaths.Results We consider a variety of scenarios and show how optimal strategies differ for decentralized and centralized management levels. We demonstrate that policies formed in the best interest of individual jurisdictions may not achieve global objectives, and identify situations where locally applied interventions can lead to an overall increase in the numbers of cases and deaths.
Conclusions Our approach underscores the importance of tailoring disease management plans to existing regulatory structures as part of an evidence-based decision framework. Most importantly, we demonstrate that there needs to be a greater consideration of the degree to which governance structure impacts disease outcomes.
