Innovating at the human-technology interface in disasters and disease outbreaks.

Disasters and disease outbreaks have long been a catalyst for innovative applications of emerging technologies. The urgent need to respond to an emergency leads to resourceful uses of the technologies at hand. However, the best and most cost-effective use of new technologies is to prevent disease and improve resilience. In this paper, the authors present a range of approaches through which both opportunities can be grasped. Global connectedness enables more data to be collected and processed in emergencies, especially with the rise of open-source data, including social media. In general, the poorest and most remote populations are most vulnerable to disaster. However, with smaller, faster, smarter, cheaper and more connected technology, reliable, efficient, and targeted response and recovery can be provided. Initially, crowdsourcing was used to find people, map affected areas, and determine resource allocation. This led to the generation of an overwhelming amount of data, and the need to extract valuable information from that data in a timely manner. As technology evolved, organisations started outsourcing many tasks, first to other people, then to machines. Since the volume of data generated outpaces human capacity, data analysis is being automated using artificial intelligence and machine learning, which furthers our abilities in predictive analytics. As we move towards prevention rather than remediation, information collection and processing must become faster and more efficient while maintaining accuracy. Moreover, these new strategies and technologies can help us to move forwards, by integrating layers of human, veterinary, public, and environmental health data for a One Health approach.

Les catastrophes et les foyers de maladies font depuis longtemps office de catalyseurs pour l'émergence d'applications technologiques innovantes. Le besoin impérieux de répondre à une urgence encourage les utilisations ingénieuses des technologies disponibles. Cependant, la meilleure utilisation des nouvelles technologies, et la plus rentable, consiste à prévenir les maladies et à améliorer la résilience. Les auteurs présentent une gamme d'approches permettant de tirer le meilleur parti de ces deux possibilités. La connectivité mondiale permet de recueillir et de traiter davantage de données lors des situations d'urgence, en particulier grâce à l'essor des données de sources ouvertes, y compris dans les réseaux sociaux. De manière générale, les populations les plus pauvres et les plus isolées sont aussi les plus vulnérables aux catastrophes. Cependant, en recourant à des technologies plus compactes, plus rapides, plus intelligentes, plus abordables et plus connectées, il est possible de proposer des interventions d'urgence et de redressement fiables, efficaces et ciblées. À l'origine, on a fait appel à la production ouverte et participative (crowdsourcing) pour la recherche de personnes, la cartographie des zones affectées et les décisions d'allocation des ressources. Cela a engendré un volume exorbitant de données, d'où la nécessité de parvenir à extraire l'information utile de cet ensemble de données et ce, en temps opportun. À mesure de l'évolution de la technologie, les organisations ont commencé à externaliser davantage de tâches, en les confiant d'abord à des tiers, puis à des machines. Étant donné que le volume des données générées dépasse les capacités humaines, l'analyse des données a été progressivement automatisée en recourant à l'intelligence artificielle et à l'apprentissage automatique, ce qui a amélioré nos capacités en matière d'analyse prédictive. Lorsqu'il s'agit de passer de la réhabilitation à la prévention, les informations doivent être recueillies et traitées de manière plus rapide et plus efficace, tout en maintenant leur exactitude. En outre, ces nouvelles stratégies et technologies peuvent nous aider à progresser en intégrant différentes strates de données provenant des secteurs de la santé humaine, vétérinaire, publique et environnementale, conformément à l'approche Une seule santé.

Los desastres y los brotes infecciosos vienen catalizando desde hace tiempo aplicaciones innovadoras de las nuevas tecnologías. La acuciante necesidad de responder a una emergencia obliga a aguzar el ingenio con las tecnologías que se tienen a mano. Con todo, el uso idóneo de las nuevas tecnologías, y el más efectivo en relación con el costo, pasa por prevenir las enfermedades y mejorar la resiliencia. Los autores presentan aquí diversos métodos que posibilitan ambas cosas. La interconexión planetaria hace posible que en el curso de las emergencias se reúnan y traten cada vez más datos, sobre todo con el auge de los datos de código abierto (incluidas las redes sociales). Por regla general, las poblaciones más pobres y aisladas son las más vulnerables a los desastres. Sin embargo, la existencia de tecnología cada vez más pequeña, rápida, inteligente, barata e interconectada hace posible una labor fiable, eficiente y selectiva de respuesta y recuperación. En un primer momento, los dispositivos de colaboración abierta (crowdsourcing) fueron utilizados para encontrar a personas, cartografiar áreas afectadas y determinar la asignación de recursos, todo lo cual generaba una ingente cantidad de datos y, a la vez, la necesidad de extraer de ellos información útil sin tardanza. A medida que la tecnología evolucionaba las organizaciones empezaron a externalizar muchas tareas, delegándolas primero en terceras personas y después en máquinas. Dado que el volumen de datos generados supera la capacidad humana, se tiende a automatizar el análisis de datos recurriendo a la inteligencia artificial y el aprendizaje automático, lo que potencia aún más nuestra capacidad de análisis predictivo. Cuanto más avanzamos hacia una lógica de prevención, dejando atrás la de mera reparación, más necesitamos procesos de recogida y tratamiento de datos cada vez más rápidos y eficientes, sin perder por ello en precisión. Por añadidura, estas nuevas estrategias y tecnologías pueden ayudarnos a avanzar gracias a la combinación de acervos de datos de salud humana, veterinaria, pública y ambiental, integrados todos ellos en clave de Una sola salud.

Detection of linezolid resistance due to the optrA gene in Enterococcus faecalis from poultry meat from the American continent (Colombia).

Background: Three Enterococcus isolates obtained from retail chicken collected in 2010-11 as part of the Colombian Integrated Program for Antimicrobial Resistance Surveillance (COIPARS) showed reduced susceptibility towards linezolid (MIC 8 mg/L). Objectives: This study aimed at characterizing the isolates resistant to linezolid and detecting the resistance mechanism. Methods: Strains were analysed in 2011-12 without successful detection of the resistance mechanism. All isolates were found negative for the cfr gene and no 23S rRNA mutations were detected. In 2016, with the novel resistance gene optrA being described, the WGS data were re-analysed using in silico genomic tools for confirmation of species, detection of virulence and resistance genes, MLST and SNP analyses and comparison of the genetic environment with the previously published plasmid pE349. Results: : Three Enterococcus faecalis isolates were found positive for the optrA gene encoding resistance to linezolid and phenicols. Additional screening of 37 enterococci strains from the same study did not detect any further positives. Typing showed that two of the isolates belong to ST59, while the last belongs to ST489. All isolates carry genes encoding resistance to macrolide-lincosamide-streptogramin B, tetracycline and phenicols. In addition, the ST489 isolate also carries genes conferring aminoglycoside resistance and is resistant to quinolones, but no plasmid-mediated gene was detected. The optrA gene regions of the three plasmids showed high similarity to the originally reported optrA -carrying plasmid pE349. Conclusions: To the best of our knowledge, this is the first description of the optrA gene in E. faecalis isolated from poultry meat in the Americas.

The Establishment of the Colombian Integrated Program for Antimicrobial Resistance Surveillance (COIPARS): A Pilot Project on Poultry Farms, Slaughterhouses and Retail Market.

The development of antimicrobial resistance among bacteria (AMR) is currently one of the world's most pressing public health problems. The use of antimicrobial agents in humans and animals has resulted in AMR which has narrowed the potential use of antibiotics for the treatment of infections in humans. To monitor AMR and to develop control measures, some countries, such as the USA, Canada and Denmark, have established national integrated surveillance systems (FDA, , CIPARS, 2007, DANMAP,2002). The components of these programs monitor changes in susceptibility/resistance to antimicrobial agents of selected zoonotic pathogens and commensal organisms recovered from animals, retail meats and humans. The rapid development of Colombia's animal production industry has raised food safety issues including the emergence of antibiotic resistance. The Colombian Integrated Surveillance Program for Antimicrobial Resistance (COIPARS) was established as a pilot project to monitor AMR on poultry farms, slaughter houses and retail markets.

Prevalence, risk factors, and antimicrobial resistance profiles of Salmonella from commercial broiler farms in two important poultry-producing regions of Colombia.

Salmonella is one of the most common foodborne pathogens associated with diarrheal disease in humans. Food animals, especially poultry, are important direct and indirect sources of human salmonellosis, and antimicrobial resistance is an emerging problem of public health concern. The use of antimicrobials benefits producers but contributes to the emergence of antimicrobial resistant bacteria. As a step toward implementing the Colombian Integrated Program for Antimicrobial Resistance Surveillance, this study was conducted to establish the prevalence, distribution of serovars, antimicrobial resistance profiles, and risk factors for Salmonella on poultry farms in the two largest states of poultry production in Colombia. Salmonella was isolated from 41% of farms and 65% of the 315 chicken houses sampled. Salmonella Paratyphi B variant Java was the most prevalent serovar (76%), followed by Salmonella Heidelberg (23%). All Salmonella isolates were resistant to 2 to 15 of the antimicrobial drugs tested in this study. For Salmonella Paratyphi B variant Java, 34 drug resistance patterns were present. The predominant resistance pattern was ciprofloxacin, nitrofurantoin, tetracycline, trimethoprim-sulfamethoxazole, ceftiofur, streptomycin, enrofloxacin, and nalidixic acid; this pattern was detected in 15% of isolates. The resistance pattern of tetracycline, ceftiofur, and nalidixic acid was found in over 40% of the isolates of Salmonella Heidelberg. Of the biosecurity practices considered, two factors were significantly associated with reduction in Salmonella: cleaning of fixed equipment and composting of dead birds on the farm. Findings from the present study provide scientific evidence to inform implementation of official policies that support new biosecurity legislation in an effort to decrease the prevalence of Salmonella on Colombian poultry farms.

The effect of management factors on the seroprevalence of Anaplasma marginale in Bos indicus cattle in the Mexican tropics.

A cross-sectional study with a two-stage design and proportional distribution was carried out to determine the effect of management factors on the seroprevalence of Anaplasma marginale in Bos indicus cattle in the Mexican tropics. Serum was obtained from 384 cattle aged 1-2 years on 92 farms. The number of samples was proportionally distributed according to the number of farms in eastern Yucatan. Antibody activity against A. marginale was assessed using the card agglutination test. A primary screening using a 2 x K contingency table of the exposed variables with the outcomes was performed. All variables for which p < 0.20 were included in a fixed-effects log regression. The seroprevalence in the cattle was 69.75% (SE +/- 0.02). Sixty-four per cent of the farms had a seroprevalence > or = 75%. The risks related to managemental factors were stocking density ( > or = 1 animal/ha, OR = 10.94), type of acaricide (pyrethroids, OR = 3.8), dipping interval ( > 60 days, OR = 0.13) and type of veterinary instruments used (needles, scalpels, ear tattoos, and dehorners, OR = 0.17).

Management factors associated with Babesia bovis seroprevalence in cattle from eastern Yucatán, Mexico.

The effect of management on the seroprevalence of Babesia bovis was studied in 399 Bos indicus cattle 1-2 years old from 92 farms in the eastern Yucatán, México. The management factors studied were: farm-type, production system, herd size, farm size, stocking density, vector control, dipping interval, type of dipping, type of acaricide and cattle introduction to the farm. A cross-sectional study was carried out (2-stage cluster sampling). The number of serum samples was proportionally distributed according to the number of farms in the nine locations of eastern Yucatán, México (399 animals from 92 farms). Antibody activity to B. bovis was tested using an indirect ELISA. The farms with a seroprevalence < or = 75% were considered as cases and those with seroprevalence > 75% were considered as controls. The variables with p < or = 0.20 were included in fixed effects logistic regression. The seroprevalence of the zone was 73.8% (66.3-81.3%). The following risk factors were found: Stocking density (< 1 head/ha, OR = 4.04, CI (OR) = 1.20-13.62) and dipping interval (> 60 days, OR = 5.07 CI (OR) = 1.26-20.48).