Ecosistema de plataformas y modelos que soportan el desarrollo de servicios digitales para toma de decisiones en el sector agropecuario en Latinoamérica

Centroamérica es una de las regiones más vulnerables a los efectos de la variabilidad climática, eventos extremos, y el cambio climático. Los servicios de información y sistemas de apoyo a la toma de decisiones son herramientas claves para adaptarse a la variabilidad climática, y anticipar y responder a eventos extremos. Esta nota describe de manera general el ecosistema de plataformas y modelos que soportan el desarrollo de servicios digitales para la toma de decisiones en el sector agropecuario de Honduras y Guatemala. Los hallazgos que se resumen aquí hacen parte de la iniciativa AgriLAC Resiliente del CGIAR. Como primera medida, se realizó un diagnóstico general de herramientas digitales y sistemas de apoyo a la toma de decisiones, que brinda un panorama general del ecosistema. Para cada herramienta, se realizó una evaluación de su proceso de desarrollo, ciclos de aprendizaje, y proceso de diseño centrado en el usuario. De igual manera, como parte de la fase de evaluación llevada a cabo en 2022, se llevaron a cabo reuniones y entrevistas con con la partes interesadas con el fin de recopilar información, identificar fortalezas y desafíos actuales, lo cual permitió identificar algunas de las principales necesidades existentes en los servicios meteorológicos en cuanto a la generación de información e implementación de plataformas de difusión de servicios de información que permitan proveer a los usuarios de servicios de monitoreo meteorológico y climático regional y de pronóstico a diferentes escalas

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Pooled analysis of WHO Surgical Safety Checklist use and mortality after emergency laparotomy

Background The World Health Organization (WHO) Surgical Safety Checklist has fostered safe practice for 10 years, yet its place in emergency surgery has not been assessed on a global scale. The aim of this study was to evaluate reported checklist use in emergency settings and examine the relationship with perioperative mortality in patients who had emergency laparotomy. Methods In two multinational cohort studies, adults undergoing emergency laparotomy were compared with those having elective gastrointestinal surgery. Relationships between reported checklist use and mortality were determined using multivariable logistic regression and bootstrapped simulation. Results Of 12 296 patients included from 76 countries, 4843 underwent emergency laparotomy. After adjusting for patient and disease factors, checklist use before emergency laparotomy was more common in countries with a high Human Development Index (HDI) (2455 of 2741, 89.6 per cent) compared with that in countries with a middle (753 of 1242, 60.6 per cent; odds ratio (OR) 0.17, 95 per cent c.i. 0.14 to 0.21, P <0001) or low (363 of 860, 422 per cent; OR 008, 007 to 010, P <0.001) HDI. Checklist use was less common in elective surgery than for emergency laparotomy in high-HDI countries (risk difference -94 (95 per cent c.i. -11.9 to -6.9) per cent; P <0001), but the relationship was reversed in low-HDI countries (+121 (+7.0 to +173) per cent; P <0001). In multivariable models, checklist use was associated with a lower 30-day perioperative mortality (OR 0.60, 0.50 to 073; P <0.001). The greatest absolute benefit was seen for emergency surgery in low- and middle-HDI countries. Conclusion Checklist use in emergency laparotomy was associated with a significantly lower perioperative mortality rate. Checklist use in low-HDI countries was half that in high-HDI countries.Peer reviewe

Zonificación agroecológica para el cultivo de arroz de riego (Oryza Sativa L.) en Colombia

Resumen: El presente estudio se llevó a cabo con el objetivo principal de realizar una zonificación y caracterización ambiental del sistema de arroz de riego en los departamentos de Tolima, Huila y Córdoba en Colombia, aplicando un enfoque de simulación espacial a través del modelo de cultivo ORYZA2000. Además, se buscó identificar el estrés abiótico más relevante que limita el rendimiento del cultivo en la región de estudio. Se evaluaron cuatro variedades de arroz (Fedearroz 2000, Fedearroz 60, Fedearroz 733 y CT21375) en 38 localidades con información climática histórica entre 1984 a 2012, se consideraron 18 fechas de siembra y seis diferentes tipos de suelos, en las regiones Centro y Bajo Cauca de Colombia. Sobre los rendimientos simulados, se implementó un método de agrupamiento jerárquico aglomerativo, con el fin de identificar los grupos ambientales. Para determinar el número óptimo de grupos se utilizaron indicadores de eficiencia y estabilidad de agrupamiento. Posteriormente, se produjeron mapas de distribución y frecuencia de ocurrencia de los ambientes. Para identificar el principal factor de estrés que afectó el rendimiento del cultivo, se desarrolló un modelo de Red Neural Artificial supervisada en cada ambiente, el cual relacionó 16 variables ambientales explicativas con una variable de respuesta (rendimiento de cultivo). Finalmente, para identificar la importancia relativa (positiva o negativa) de cada variable predictora sobre la variable de respuesta, se aplicó el algoritmo de Garson a cada modelo de red neuronal. Los resultados mostraron que el modelo ORYZA2000 pudo predecir la duración de cada uno de los estados fenológicos de los diferentes cultivares, en ambientes contrastantes, con un error no superior a 4 días. De igual manera fue lo suficientemente preciso para simular el rendimiento, el índice de área foliar (LAI) y biomasa de los órganos de los cultivares considerados. En promedio, los valores de RMSEn variaron entre 22% - 32% para la biomasa total, 27% - 37% para la biomasa de hoja verde, 27% - 40% para la biomasa de tallo, 30% - 40% para la biomasa de panícula y 30% - 35% para el LAI, y Los 11% - 15% para el rendimiento. Los resultados obtenidos revelaron que el modelo ORYZA2000 puede aplicarse como una herramienta valiosa para evaluar el desempeño del arroz bajo diferentes condiciones ambientales, y estrategias de manejo en las regiones del Centro y Bajo Cauca de Colombia. Con base en los rendimientos simulados de cada grupo ambiental, estos se clasificaron de la siguiente manera: Altamente favorables (HFE), Favorables (FE) y Menos favorable (LFE). El HFE se caracterizó por tener los mayores rendimientos promedios (9.140 kg ha-1), y representó el 18,5% del total del área de estudio. Por su parte, el FE tuvo un rendimiento promedio de 7.578 kg ha-1, y ocupó el 50,2% de toda la zona de producción; Mientras que el LFE se caracterizó por ser el ambiente de menor rendimiento (6.000 kg ha-1), y por ser el segundo ambiente con la mayor probabilidad de ocurrencia (31.3%). Espacialmente, el HFE se distribuyó en dos pequeñas regiones ubicadas en el centro norte del departamento de Tolima y al sur del Huila. Este ambiente se caracterizó por tener una alta estabilidad ambiental (87% - 100%). Por otra parte, el FE ocupó una gran región que comprende los municipios del centro y norte de los departamentos de Tolima y Huila, dicha región se caracterizó por tener una mediana estabilidad ambiental (54% - 86%). En cuanto al ambiente LFE, este se distribuyó en el departamento de Córdoba, y presentó una mediana estabilidad ambiental (54% -86%). Con base en el Análisis de Modelos de Redes Neuronales y la relevancia métrica, se identificó la temperatura mínima como el principal factor abiótico limitante que tiene un efecto negativo en el rendimiento del arroz. La fase comprendida entre la iniciación panicular y el final de la floración, fue la etapa más sensible al aumento de las temperaturas nocturnas. La temperatura mínima en el peor ambiente (LFE) osciló entre 23°C - 25°C, afectando el rendimiento, el número de espiguillas y la producción total de biomasa de los cuatro cultivares considerados en el estudio.//Abstract: The aim of this study was carry out an environmental zonation and characterization of irrigated rice system across Tolima, Huila and Cordoba departments in Colombia, applying a spatial simulation approach through the ORYZA2000 crop model, as well as, identify the most relevant abiotic stress that limit the crop yield over the study region. Under this research, we seek to generate information that can support the new breeding programs strategies, in their effort to develop new germplasms with good yield stability, tolerant to certain abiotic stresses and resistant to interannual climate variability. Four rice Colombian varieties (Fedearroz 2000, Fedearroz 60, Fedearroz 733 and CT21375) were evaluated across 38 locations with historical climate information from 1984 to 2012, considering 18 planting dates and six different soil types, in the Central and Bajo Cauca regions. An agglomerative hierarchical clustering method was employed on modeled attainable rice yields, in order to identify the environmental groups. Clustering efficiency and stability indicators were used to determine the optimal number of environments for the study region. Using the clustering results, maps of environments distribution and frequency were produced. To identify the main stress factor that affected crop yield, a supervised Artificial Neural Network model was developed in each environment, which related 16 explicative environmental variables with one response variable (crop yield). Finally, to identify the relative importance (positive or negative) of each explicative variable on the response variable, the Garson algorithm was applicate to each Neural Network Model. The results showed that ORYZA2000 model could predict well the duration of each phenological stage, however, consistently underestimated the length of growing period from 2 to 4 days. The range in normalized root mean square error (RMSEn) values for each phenological stage was between 3% and 6%. From the evaluation, was concluded that ORYZA2000 was sufficiently accurate in simulation of yield for each cultivar, leaf area index (LAI) and biomass of crop organs over time and across the regions. On average, RMSEn values were 22%−32% for total biomass, 27% − 37% for green leaf biomass, 27% − 40% for stem biomass, 30 % − 40 % for panicle biomass and 30% − 35% for LAI. The RMSEn values for final yield were 11.0 % − 15.0 %. The results obtained revealed that ORYZA2000 model can be applicate as a valuable tool to support the research oriented to assess the rice performance under different environmental conditions, and management strategies developed across the Centro and Bajo Cauca regions in Colombia. According to the yields obtained in each environmental group, the production environments were classified as follows: Highly Favorable (HFE), Favorable (FE) and Less Favorable (LFE). The HFE was the environment with the highest average yields (9,140 kg ha-1) and represented 18.5% of the total study area. For its part, the FE, had an average yield of 7,578 kg ha-1, occupying 50.2% of the entire production area; while the LFE was characterized by the lowest yielding environment (6,000 kg ha-1), and it was the second environment with the highest probability of occurrence (31.3%) within the study region. Spatially, the HFE was distributed in two small regions located at north center Tolima department and to the southern Huila. This environment was distinguished to have a high environmental stability (87.0 % - 100.0 %). On the other hand, the FE occupied a large region comprising the municipalities across the central and northern Tolima and Huila, this region was distinguished by its medium environmental stability (54% - 86%). Regarding the LFE environment, it was distributed in Cordoba department, which presented a medium-environmental stability (54% - 86%). Based on the Neural Network Model Analysis and the metric relevance, the minimum temperature was identified as the main limiting abiotic factor that has a negative effect on the rice yield. From the panicle initiation to the end of the flowering stage, was the most sensitive stage to the increase of the night temperatures. The minimum temperature in worst environment was between 23°C – 25°C, which reduced the yield, spikelet number and total biomass production of the four cultivars considered in the study.Maestrí

Agroclimatic Indices Dataset for Characterizing Crop Water Requirements, Dry and Wet Spells, Heatwaves, and Water Balance in Agricultural Regions of Angola

This database contains spatial information with a 0.05° grid resolution of specific agroclimatic indices for maize, dry beans, soybeans, and coffee regions in Angola. In total, the database comprises 13 agroclimatic indices for each crop, grouped as follows: 1. Dry Conditions Indices: • Number of Dry Days • Number of Dry Spells • Average Length of Dry Spells 2. Wet Conditions Indices: • Number of Wet Days • Number of Wet Spells • Average Length of Wet Spells • Total Precipitation 3. Heatwave Indices: • Number of Hot Days • Number of Heatwaves • Maximum Length of Heatwaves 4. Crop Water Requirement Index: • Potential Evapotranspiration (ETo) 5. Water Balance Index: • Standardized Precipitation and Evapotranspiration Index (SPEI) These indices were calculated using historical climatic data for the period 1981 to 2020, considering the typical growth and development periods of each crop of interest, detailed as follows: • Maize: September - April • Beans: November – March • Soybeans: October – April • Coffee: September – August Additionally, six "El Niño" events (1982-1983, 1987-1988, 1991-1992, 1997-1998, 2009-2010, 2015-2016) and six "La Niña" events (1984-1985, 1988-1989, 1998-1999) were considered to characterize the behavior of each indicator under the influence of different phases of the ENSO phenomenon. Metodology:Regarding the climatic data used to calculate each of the indices, the following information is provided: 1. Dry and Wet Conditions Indices: Historical daily rainfall data from the Climate Hazards Group InfraRed Precipitation Measurement (CHIRPS) dataset (https://www.chc.ucsb.edu/data) were used. 2. Heatwave Indices: Historical daily maximum temperature data were obtained from the AgERA5 database (https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-agrometeorological-indicators?tab=overview), and a resampling process was applied to reduce the spatial scale of the original maps from 0.1° to 0.05°. 3. Crop Water Requirement Indices: The Priestley-Taylor equation was used to calculate Potential Evapotranspiration (ETo) due to its simplicity and suitability for tropical conditions. Daily maximum and minimum temperature data, as well as solar radiation, were obtained from the AgERA5 database. A resampling process was also applied to reduce the spatial scale of the original maps from 0.1° to 0.05°. 4. Water Balance Indices: The SPEI indicator calculation was based on daily precipitation data from CHIRPS and ETo calculated using daily maximum and minimum temperature data, as well as solar radiation, from the AgERA5 database. This database provides a valuable tool for understanding and managing agroclimatic aspects in key crop-producing regions in Angola, which can have a significant impact on the country's agriculture and food security. (2023-09

How does El Niño Southern Oscillation affect rice-producing environments in central Colombia?

International audienceThe rice industry plays an important role in the agricultural economy of Colombia and its success dependents largely on weather conditions. Rice farmers, policymakers and other stakeholders thus need to understand and manage the risks associated with climate variability, including those related to El Nino Southern Oscillation (ENSO) - the most important source of variability affecting Colombian climates. The objectives of this study were to (1) assess the ENSO influence on the spatio-temporal variability of agro-climatic conditions (crop water requirements, dry and wet spells, and heatwaves) and rice yield across the central producing region of Colombia; and (2) identify the main agro-climatic factors driving crop yield variability. Results showed that rice irrigation water requirements under positive ENSO phases (El Nino) increased by up to 14% compared to the long-term average. These increases were associated with less total precipitation, more dry days and longer dry spells, together with a greater number of day-and-night heatwave episodes. During negative phases (La Nina), on the other hand, irrigation requirements decreased by 16% with respect to the long-term average due to longer and more frequent wet spells, and more total precipitation. Analyses of simulated yields indicated that El Nino years reduce crop yield in about 86% of the study region, while La Nina affects 62% of the region positively. The number of heat nights (i.e. nights with minimum temperature > 23 degrees C) during the growing season was the most important agro-climatic factor causing yield losses during ENSO events. Our results represent an important step towards understanding the interaction between climate variability and rice production in Colombia, which is useful for improving climate risk management at local levels

Surgical site infection after gastrointestinal surgery in children : an international, multicentre, prospective cohort study

Introduction Surgical site infection (SSI) is one of the most common healthcare-associated infections (HAIs). However, there is a lack of data available about SSI in children worldwide, especially from low-income and middle-income countries. This study aimed to estimate the incidence of SSI in children and associations between SSI and morbidity across human development settings. Methods A multicentre, international, prospective, validated cohort study of children aged under 16 years undergoing clean-contaminated, contaminated or dirty gastrointestinal surgery. Any hospital in the world providing paediatric surgery was eligible to contribute data between January and July 2016. The primary outcome was the incidence of SSI by 30 days. Relationships between explanatory variables and SSI were examined using multilevel logistic regression. Countries were stratified into high development, middle development and low development groups using the United Nations Human Development Index (HDI). Results Of 1159 children across 181 hospitals in 51 countries, 523 (45 center dot 1%) children were from high HDI, 397 (34 center dot 2%) from middle HDI and 239 (20 center dot 6%) from low HDI countries. The 30-day SSI rate was 6.3% (33/523) in high HDI, 12 center dot 8% (51/397) in middle HDI and 24 center dot 7% (59/239) in low HDI countries. SSI was associated with higher incidence of 30-day mortality, intervention, organ-space infection and other HAIs, with the highest rates seen in low HDI countries. Median length of stay in patients who had an SSI was longer (7.0 days), compared with 3.0 days in patients who did not have an SSI. Use of laparoscopy was associated with significantly lower SSI rates, even after accounting for HDI. Conclusion The odds of SSI in children is nearly four times greater in low HDI compared with high HDI countries. Policies to reduce SSI should be prioritised as part of the wider global agenda.Peer reviewe