Rice Crisis Forensics: How Asian Governments Carelessly Set the World Rice Market on Fire

The world rice market was aflame last spring and for several months it looked as if the trading edifice that had exhibited such resilience over the last two decades was going to burn to the ground. World prices trebled within less than four months and reached a 30-year inflation-adjusted high. Many market observers thought the previous record set in 1974 would soon be toast. The fire was man-made, not the result of natural developments. While the governments in India, Vietnam, and the Philippines did not to set the world market on fire, that was the unintended result of their actions which threatened both innocent bystanders (low-income rice importers as far away as Africa and Latin America) and, ultimately, poor rice consumers at home. This paper describes what sparked the fire and the accelerants that made a bad situation nearly catastrophic. Fortuitously, when the flames were raging at peak intensity, rain clouds appeared, the winds [market psychology] shifted, and conditions on the ground improved, allowing the fire to die down. It remains to be seen, however, if the trading edifice has been seriously undermined by the actions of decision makers in several key Asian rice exporting and importing countries. In describing the cascading negative effects of these seemingly rational domestic policies, this paper aims to help policy makers in the rice exporting and importing nations to avoid a repeat of the disastrous price spike of 2008.rice, inflation, prices

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Consortium-based genome-wide meta-analysis for childhood dental caries traits

Prior studies suggest dental caries traits in children and adolescents are partially heritable, but there has been no large-scale consortium genome-wide association study (GWAS) to date. We therefore performed GWAS for caries in participants aged 2.5-18.0 years from nine contributing centres. Phenotype definitions were created for the presence or absence of treated or untreated caries, stratified by primary and permanent dentition. All studies tested for association between caries and genotype dosage and the results were combined using fixed-effects meta-analysis. Analysis included up to 19 003 individuals (7530 affected) for primary teeth and 13 353 individuals (5875 affected) for permanent teeth. Evidence for association with caries status was observed at rs1594318-C for primary teeth [intronic within ALLC, odds ratio (OR) 0.85, effect allele frequency (EAF) 0.60, P 4.13e-8] and rs7738851-A (intronic within NEDD9, OR 1.28, EAF 0.85, P 1.63e-8) for permanent teeth. Consortium-wide estimated heritability of caries was low [h(2) of 1% (95% CI: 0%: 7%) and 6% (95% CI 0%: 13%) for primary and permanent dentitions, respectively] compared with corresponding within-study estimates [h(2) of 28% (95% CI: 9%: 48%) and 17% (95% CI: 2%: 31%)] or previously published estimates. This study was designed to identify common genetic variants with modest effects which are consistent across different populations. We found few single variants associated with caries status under these assumptions. Phenotypic heterogeneity between cohorts and limited statistical power will have contributed; these findings could also reflect complexity not captured by our study design, such as genetic effects which are conditional on environmental exposure

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Consortium-based genome-wide meta-analysis for childhood dental caries traits

Prior studies suggest dental caries traits in children and adolescents are partially heritable, but there has been no large-scale consortium genome-wide association study (GWAS) to date. We therefore performed GWAS for caries in participants aged 2.5–18.0 years from nine contributing centres. Phenotype definitions were created for the presence or absence of treated or untreated caries, stratified by primary and permanent dentition. All studies tested for association between caries and genotype dosage and the results were combined using fixed-effects meta-analysis. Analysis included up to 19 003 individuals (7530 affected) for primary teeth and 13 353 individuals (5875 affected) for permanent teeth. Evidence for association with caries status was observed at rs1594318-C for primary teeth [intronic within ALLC, odds ratio (OR) 0.85, effect allele frequency (EAF) 0.60, P 4.13e-8] and rs7738851-A (intronic within NEDD9, OR 1.28, EAF 0.85, P 1.63e-8) for permanent teeth. Consortium-wide estimated heritability of caries was low [h2 of 1% (95% CI: 0%: 7%) and 6% (95% CI 0%: 13%) for primary and permanent dentitions, respectively] compared with corresponding within-study estimates [h2 of 28% (95% CI: 9%: 48%) and 17% (95% CI: 2%: 31%)] or previously published estimates. This study was designed to identify common genetic variants with modest effects which are consistent across different populations. We found few single variants associated with caries status under these assumptions. Phenotypic heterogeneity between cohorts and limited statistical power will have contributed; these findings could also reflect complexity not captured by our study design, such as genetic effects which are conditional on environmental exposure

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

The Role of Biofuel Policies on Grain and Oilseed Prices

<br/><br/><br/><br/><br/><br/> Based on forecasts of global population growth, food security will remain an important economic development issue over the next several decades. In addition, real food prices have risen in recent years after decades of decline, bringing the issue of food security even further into the public spotlight. However, there is no global food shortage: the problem is one of moving food, often across borders, from surplus production areas to deficit ones at prices that low-income consumers in developing countries can afford. Trade can be an excellent buffer for domestic fluctuations in food supply. World output of a given food commodity is far less variable than output in individual countries so increased trade integration holds considerable potential to stabilize food prices, boost returns to farmers and reduce the prices faced by consumers. Trade liberalization protects national food markets against domestic shocks by allowing more food to be imported in times of shortage and exported in periods of plenty. Historically, however, most countries have chosen to take the opposite approach by restricting imports of food and discouraging exports to keep domestic markets isolated from international shocks. Food commodity markets, therefore, remain highly distorted despite the wave of liberalization that has swept world trade since the 1980s. In addition to examining the determinants of recent food price spikes, Trade Policy and Food Security explores the impact of food prices on economic welfare, and how the effect of price changes on food security and economic welfare in developing countries can be mitigated through appropriate national policies at the border. It highlights the importance of both the extension and continued application of existing WTO disciplines on trade-distorting agricultural trade policies as a key resolution to the collective action problem witnessed during the recent food price spikes, whereby unilateral border policies—especially export controls—simply exacerbated the initial price increases.<br/