Coastal vulnerability: Impact of port disruptions and the economic impacts of tropical cyclones

Coastal counties in the United States account for less than 10% of the nation’s land mass. Yet, approximately 40% of the country’s population, or over 127 million people, live in these areas. The population density of coastal counties is 461 people per square mile, much larger than the nation’s average population density of 87 people per square mile. Coasts also present the logistic benefit of allowing the transportation of goods between countries and continents through maritime ports. However, the increase in coastal population and economic activity means an increased exposure and vulnerability to potential natural hazards, such as hurricanes and tropical storms. These weather events are powerful, with the capacity to devastate coastal regions. Therefore, understanding these potentially catastrophic events is critical to assess vulnerability and support informed decision-making at local, state, and federal levels. This research provides valuable insights related to the characteristics of tropical cyclones and to their potential impacts to the coastal United States. First, an extensive review of the literature related to maritime supply chain resilience and the impacts of port disruptions to the maritime supply chain is performed. Ports are complex enterprises, comprised of a wide variety of stakeholders and subject to risks of many kinds, both man-made and natural hazards. This review allowed the identification of gaps of knowledge to be explored on the topic of maritime supply chain resilience. One of the gaps is the lack of a clearly quantifiable metric for the impacts of one of the most common sources of weather disruptions: hurricane and tropical storms. Albeit the immediate impacts are limited to areas prone to these events, tropical cyclones have been known to impact extensive areas and cause long lasting negative effects. Second, machine learning is used to rigorously explore and quantify the relationship of tropical cyclone characteristics and their destructive outcomes on the coast of the United States. Historical data on hurricanes and tropical storms is identified and curated to support supervised learning. A novel Storm Damage Ratio is introduced to address the inherent challenge of comparing damage to regions with distinct assets and population. Multiple mathematical models to predict economic impacts from tropical events are created using machine learning methods and the results are compared. Additionally, the storm features that most influence the accuracy of predictions are identified and ranked. The third research component consists in analyzing coastal vulnerability to tropical cyclones at the state-level by providing mechanisms to account for uncertainty in studying the destructive potential of storms, supporting the decision-making process to improve community resilience. The previously developed concept of Storm Damage Ratio is extended, creating the Local Storm Damage Ratio, which assess the destructive potential of storms with respect to intrinsic characteristics, regardless of the local economic characteristics. Multiple machine learning models are developed to predict the value of Local Storm Damage Ratio at a state-level. The most promising machine learning model is used to study the relationship between state and damage, as well as evaluate state preparedness. Finally, this work makes the innovative approach of building state-level empirical fragility curves to tropical storms. The novelty curves are built for three damage levels: minor, moderate, and major damage

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples.

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed.  Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination

Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network.  It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented.  For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations.  We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent.  We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines.  Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website

Genomic epidemiology of artemisinin resistant malaria

International audienceThe current epidemic of artemisinin resistant Plasmodium falciparum in Southeast Asia is the result of a soft selective sweep involving at least 20 independent kelch13 mutations. In a large global survey, we find that kelch13 mutations which cause resistance in Southeast Asia are present at low frequency in Africa. We show that African kelch13 mutations have originated locally, and that kelch13 shows a normal variation pattern relative to other genes in Africa, whereas in Southeast Asia there is a great excess of non-synonymous mutations, many of which cause radical amino-acid changes. Thus, kelch13 is not currently undergoing strong selection in Africa, despite a deep reservoir of variations that could potentially allow resistance to emerge rapidly. The practical implications are that public health surveillance for artemisinin resistance should not rely on kelch13 data alone, and interventions to prevent resistance must account for local evolutionary conditions, shown by genomic epidemiology to differ greatly between geographical regions

Genomic epidemiology of artemisinin resistant malaria

International audienceThe current epidemic of artemisinin resistant Plasmodium falciparum in Southeast Asia is the result of a soft selective sweep involving at least 20 independent kelch13 mutations. In a large global survey, we find that kelch13 mutations which cause resistance in Southeast Asia are present at low frequency in Africa. We show that African kelch13 mutations have originated locally, and that kelch13 shows a normal variation pattern relative to other genes in Africa, whereas in Southeast Asia there is a great excess of non-synonymous mutations, many of which cause radical amino-acid changes. Thus, kelch13 is not currently undergoing strong selection in Africa, despite a deep reservoir of variations that could potentially allow resistance to emerge rapidly. The practical implications are that public health surveillance for artemisinin resistance should not rely on kelch13 data alone, and interventions to prevent resistance must account for local evolutionary conditions, shown by genomic epidemiology to differ greatly between geographical regions

An open dataset of <i>Plasmodium falciparum</i> genome variation in 7,000 worldwide samples.

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed.  Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination

Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples.

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network.  It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented.  For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations.  We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent.  We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines.  Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website