BackgroundDengue dynamics are driven by complex interactions between human-hosts, mosquito-vectors and viruses that are influenced by environmental and climatic factors. The objectives of this study were to analyze and model the relationships between climate, Aedes aegypti vectors and dengue outbreaks in Noumea (New Caledonia), and to provide an early warning system.Methodology/Principal FindingsEpidemiological and meteorological data were analyzed from 1971 to 2010 in Noumea. Entomological surveillance indices were available from March 2000 to December 2009. During epidemic years, the distribution of dengue cases was highly seasonal. The epidemic peak (March–April) lagged the warmest temperature by 1–2 months and was in phase with maximum precipitations, relative humidity and entomological indices. Significant inter-annual correlations were observed between the risk of outbreak and summertime temperature, precipitations or relative humidity but not ENSO. Climate-based multivariate non-linear models were developed to estimate the yearly risk of dengue outbreak in Noumea. The best explicative meteorological variables were the number of days with maximal temperature exceeding 32°C during January–February–March and the number of days with maximal relative humidity exceeding 95% during January. The best predictive variables were the maximal temperature in December and maximal relative humidity during October–November–December of the previous year. For a probability of dengue outbreak above 65% in leave-one-out cross validation, the explicative model predicted 94% of the epidemic years and 79% of the non epidemic years, and the predictive model 79% and 65%, respectively.Conclusions/SignificanceThe epidemic dynamics of dengue in Noumea were essentially driven by climate during the last forty years. Specific conditions based on maximal temperature and relative humidity thresholds were determinant in outbreaks occurrence. Their persistence was also crucial. An operational model that will enable health authorities to anticipate the outbreak risk was successfully developed. Similar models may be developed to improve dengue management in other countries.

BackgroundMethicillin-resistant Staphylococcus aureus (MRSA) may cause prolonged outbreaks of infections in neonatal intensive care units (NICUs). While the specific factors favouring MRSA spread on neonatal wards are not well understood, colonized infants, their relatives, or health-care workers may all be sources for MRSA transmission. Whole-genome sequencing may provide a new tool for elucidating transmission pathways of MRSA at a local scale.Methods and FindingsWe applied whole-genome sequencing to trace MRSA spread in a NICU and performed a case-control study to identify risk factors for MRSA transmission. MRSA genomes had accumulated sequence variation sufficiently fast to reflect epidemiological linkage among individual patients, between infants and their mothers, and between infants and staff members, such that the relevance of individual nurses’ nasal MRSA colonization for prolonged transmission could be evaluated. In addition to confirming previously reported risk factors, we identified an increased risk of transmission from infants with as yet unknown MRSA colonisation, in contrast to known MRSA-positive infants.ConclusionsThe integration of epidemiological (temporal, spatial) and genomic data enabled the phylogenetic testing of several hypotheses on specific MRSA transmission routes within a neonatal intensive-care unit. The pronounced risk of transmission emanating from undetected MRSA carriers suggested that increasing the frequency or speed of microbiological diagnostics could help to reduce transmission of MRSA.

virus with the highest similarity to adenovirus type 11a.3

Electronic Surveillance System for Infectious Disease Outbreaks, GermanyThis system has managed detailed information on 30,578 disease outbreaks.

In 2001 Germany implemented a new electronic reporting system for surveillance of notifiable infectious diseases (SurvNet@RKI). The system is currently being used in all 431 local health departments (LHD), the 16 state health departments (SHD) and the Robert Koch-Institut (RKI), the national agency for infectious disease epidemiology. The SurvNet@RKI software is written in MS Access 97 and Visual Basic and it supports MS Access as well as MS SQL Server database management systems as a back-end. The database is designed as a distributed, dynamic database for 73 reporting categories with more than 600 fields and about 7000 predefined entry values. An integrated version management system documents deletion, undeletion, completion and correction of cases at any time and entry level and allows reproduction of previously conducted queries. Integrated algorithms and help functions support data quality and the application of case definitions. RKI makes the system available to all LHDs and SHDs free of charge. RKI receives an average of 300 000 case reports and 6240 outbreak reports per year through this system. A public web-based query interface, SurvStat@RKI, assures extensive and timely publication of the data. During the 5 years that SurvNet@RKI has been running in all LHDs and SHDs in Germany it has coped well with a complex federal structure which makes this system particularly attractive to multinational surveillance networks. The system is currently being migrated to Microsoft C#/.NET and transport formats in XML. Based on our experiences, we provide recommendations for the design and implementation of national or international electronic surveillance systems.