RESUMEN
BackgroundThe Epidemic Intelligence from Open Sources (EIOS) system, jointly developed by the World Health Organisation (WHO), the Joint Research Centre (JRC) of the European Commission and various partners, is a web-based platform that facilitate the monitoring of information on public health threats in near real-time from thousands of online sources.AimsTo assess the capacity of the EIOS system to strengthen data collection for neglected diseases of public health importance, and to evaluate the use of EIOS data for improving the understanding of the geographic extents of diseases and their level of risk.MethodsA Bayesian additive regression trees (BART) model was implemented to map the risk of Crimean-Congo haemorrhagic fever (CCHF) occurrence in 52 countries and territories within the European Region between January 2012 and March 2022 using data on CCHF occurrence retrieved from the EIOS system.ResultsThe model found a positive association between all temperature-related variables and the probability of CCHF occurrence, with an increased risk in warmer and drier areas. The highest risk of CCHF was found in the Mediterranean basin and in areas bordering the Black Sea. There was a general decreasing risk trend from south to north across the entire European Region.ConclusionThe study highlights that the information gathered by public health intelligence can be used to build a disease risk map. Internet-based sources could aid in the assessment of new or changing risks and planning effective actions in target areas.
Asunto(s)
Epidemias , Virus de la Fiebre Hemorrágica de Crimea-Congo , Fiebre Hemorrágica de Crimea , Humanos , Fiebre Hemorrágica de Crimea/diagnóstico , Fiebre Hemorrágica de Crimea/epidemiología , Enfermedades Desatendidas/epidemiología , Teorema de BayesRESUMEN
From 1 January to 30 June 2018, 11 cases of Lymphogranuloma venereum (LGV; all preserved samples (n = 4) genovar L2b) were identified at the Genitourinary Clinic (GUC), Mater Dei Hospital, Msida, Malta. All cases were diagnosed in men who have sex with men (MSM); six participated in three group-sex parties. Here, we describe the outbreak and risk factors associated with LGV diagnoses in MSM in Malta in 2018.
Asunto(s)
Chlamydia trachomatis/aislamiento & purificación , Coinfección/diagnóstico , Brotes de Enfermedades , Homosexualidad Masculina , Linfogranuloma Venéreo/diagnóstico , Adulto , Chlamydia trachomatis/genética , Trazado de Contacto , Gonorrea/diagnóstico , Infecciones por VIH/diagnóstico , Humanos , Linfogranuloma Venéreo/epidemiología , Masculino , Malta/epidemiología , Técnicas de Amplificación de Ácido Nucleico , Factores de RiesgoRESUMEN
Between 1 June 2016 and 31 May 2017, 17 European Union (EU) and European Economic Area countries reported 4,096 cases associated with a multi-country hepatitis A (HA) outbreak. Molecular analysis identified three co-circulating hepatitis A virus (HAV) strains of genotype IA: VRD_521_2016, V16-25801 and RIVM-HAV16-090. We categorised cases as confirmed, probable or possible, according to the EU outbreak case definitions. Confirmed cases were infected with one of the three outbreak strains. We investigated case characteristics and strain-specific risk factors for transmission. A total of 1,400 (34%) cases were confirmed; VRD_521_2016 and RIVM-HAV16-090 accounted for 92% of these. Among confirmed cases with available epidemiological data, 92% (361/393) were unvaccinated, 43% (83/195) travelled to Spain during the incubation period and 84% (565/676) identified as men who have sex with men (MSM). Results depict an HA outbreak of multiple HAV strains, within a cross-European population, that was particularly driven by transmission between non-immune MSM engaging in high-risk sexual behaviour. The most effective preventive measure to curb this outbreak is HAV vaccination of MSM, supplemented by primary prevention campaigns that target the MSM population and promote protective sexual behaviour.
Asunto(s)
Brotes de Enfermedades , Virus de la Hepatitis A/aislamiento & purificación , Hepatitis A/epidemiología , Homosexualidad Masculina/estadística & datos numéricos , Hospitalización/estadística & datos numéricos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Preescolar , Europa (Continente)/epidemiología , Unión Europea , Genotipo , Hepatitis A/diagnóstico , Virus de la Hepatitis A/genética , Humanos , Lactante , Recién Nacido , Masculino , Persona de Mediana Edad , Factores de Riesgo , Conducta Sexual , España/epidemiología , Adulto JovenRESUMEN
The Early Alerting and Reporting (EAR) project, launched in 2008, is aimed at improving global early alerting and risk assessment and evaluating the feasibility and opportunity of integrating the analysis of biological, chemical, radionuclear (CBRN), and pandemic influenza threats. At a time when no international collaborations existed in the field of event-based surveillance, EAR's innovative approach involved both epidemic intelligence experts and internet-based biosurveillance system providers in the framework of an international collaboration called the Global Health Security Initiative, which involved the ministries of health of the G7 countries and Mexico, the World Health Organization, and the European Commission. The EAR project pooled data from 7 major internet-based biosurveillance systems onto a common portal that was progressively optimized for biological threat detection under the guidance of epidemic intelligence experts from public health institutions in Canada, the European Centre for Disease Prevention and Control, France, Germany, Italy, Japan, the United Kingdom, and the United States. The group became the first end users of the EAR portal, constituting a network of analysts working with a common standard operating procedure and risk assessment tools on a rotation basis to constantly screen and assess public information on the web for events that could suggest an intentional release of biological agents. Following the first 2-year pilot phase, the EAR project was tested in its capacity to monitor biological threats, proving that its working model was feasible and demonstrating the high commitment of the countries and international institutions involved. During the testing period, analysts using the EAR platform did not miss intentional events of a biological nature and did not issue false alarms. Through the findings of this initial assessment, this article provides insights into how the field of epidemic intelligence can advance through an international network and, more specifically, how it was further developed in the EAR project.