NEW METHOD: To overcome these limitations, we propose a new statistical model that smooths out the noise by exploiting the geometric structure of correlation matrices. The dynamic correlation matrix is modeled as a linear combination of symmetric positive-definite matrices combined with cosine series representation. The resulting smoothed dynamic correlation matrices are clustered into disjoint brain connectivity states using the k-means clustering algorithm.
RESULTS: The proposed model preserves the geometric structure of underlying physiological dynamic correlation, eliminates unwanted noise in connectivity and obtains more accurate state spaces. The difference in the estimated dynamic connectivity states between males and females is identified.
COMPARISON WITH EXISTING METHODS: We demonstrate that the proposed statistical model has less rapid state changes caused by noise and improves the accuracy in identifying and discriminating different states.
CONCLUSIONS: We propose a new regression model on dynamically changing correlation matrices that provides better performance over existing windowed correlation and is more reliable for the modeling of dynamic connectivity.
METHODS: The study was undertaken in five Latin American (Brazil, Colombia, Dominican Republic, Mexico, Peru) and five in Asian countries (Indonesia, Malaysia, Maldives, Sri Lanka, Vietnam). A mixed-methods approach was used which included document analysis, key informant interviews, focus-group discussions, secondary data analysis and consensus building by an international dengue expert meeting organised by the World Health Organization, Special Program for Research and Training in Tropical Diseases (WHO-TDR).
RESULTS: Country information on dengue is based on compulsory notification and reporting ("passive surveillance"), with laboratory confirmation (in all participating Latin American countries and some Asian countries) or by using a clinical syndromic definition. Seven countries additionally had sentinel sites with active dengue reporting, some also had virological surveillance. Six had agreed a formal definition of a dengue outbreak separate to seasonal variation in case numbers. Countries collected data on a range of warning signs that may identify outbreaks early, but none had developed a systematic approach to identifying and responding to the early stages of an outbreak. Outbreak response plans varied in quality, particularly regarding the early response. The surge capacity of hospitals with recent dengue outbreaks varied; those that could mobilise additional staff, beds, laboratory support and resources coped best in comparison to those improvising a coping strategy during the outbreak. Hospital outbreak management plans were present in 9/22 participating hospitals in Latin-America and 8/20 participating hospitals in Asia.
CONCLUSIONS: Considerable variation between countries was observed with regard to surveillance, outbreak detection, and response. Through discussion at the expert meeting, suggestions were made for the development of a more standardised approach in the form of a model contingency plan, with agreed outbreak definitions and country-specific risk assessment schemes to initiate early response activities according to the outbreak phase. This would also allow greater cross-country sharing of ideas.