Modelling of seasonal influenza and estimation of the burden in Tunisia.

The burden of influenza was estimated from surveillance data in Tunisia using epidemiological parameters of transmission with WHO classical tools and mathematical modelling. The incidence rates of influenza-associated influenza-like illness (ILI) per 100 000 were 18 735 in 2012/2013 season; 5536 in 2013/14 and 12 602 in 2014/15. The estimated proportions of influenza-associated ILI in the total outpatient load were 3.16%; 0.86% and 1.98% in the 3 seasons respectively. Distribution of influenza viruses among positive patients was: A(H3N2) 15.5%; A(H1N1)pdm2009 39.2%; and B virus 45.3% in 2014/2015 season. From the estimated numbers of symptomatic cases, we estimated that the critical proportions of the population that should be vaccinated were 15%, 4% and 10% respectively. Running the model for the different values of R0, we quantified the number of symptomatic clinical cases, the clinical attack rates, the symptomatic clinical attack rates and the number of deaths. More realistic versions of this model and improved estimates of parameters from surveillance data will strengthen the estimation of the burden of influenza.

Modelling of seasonal influenza and estimation of the burden in Tunisia

The burden of influenza was estimated from surveillance data in Tunisia using epidemiological parameters of transmission with WHO classical tools and mathematical modelling. The incidence rates of influenza-associated influenza-like illness [ILI] per 100 000 were 18 735 in 2012/2013 season; 5536 in 2013/14 and 12 602 in 2014/15. The estimated proportions of influenza-associated ILI in the total outpatient load were 3.16%; 0.86% and 1.98% in the 3 seasons respectively. Distribution of influenza viruses among positive patients was: A[H3N2] 15.5%; A[H1N1] pdm2009 39.2%; and B virus 45.3% in 2014/2015 season. From the estimated numbers of symptomatic cases, we estimated that the critical proportions of the population that should be vaccinated were 15%, 4% and 10% respectively. Running the model for the different values of R0, we quantified the number of symptomatic clinical cases, the clinical attack rates, the symptomatic clinical attack rates and the number of deaths. More realistic versions of this model and improved estimates of parameters from surveillance data will strengthen the estimation of the burden of influenza

En Tunisie, la charge de la grippe a été estimée à partir des données de surveillance, en utilisant les paramètres épidémiologiques de la transmission avec les outils classiques de l'OMS et la modélisation mathématique. Les taux d'incidence des syndromes de type grippal [STG] associés à la grippe étaient 18 735 pour 100 000 pour la saison 2012-2013 ; 5 536 pour 2013-2014 et 12 602 pour 2014-2015. La part estimée de STG associés à la grippe pour la charge totale de patients externes était respectivement de 3,16%, 0,86% et 1,98% pour les trois saisons. Parmi les patients positifs au virus de la grippe, la répartition était la suivante pour la saison 2014-2015 : 15,5% pour le virus A[H3N2] ; 39,2% pour le virus A[H1N1]pdm2009 ; et 45,3% pour le virus B. A partir du nombre estimé de cas symptomatiques, nous avons calculé que la proportion critique de la population devant être vaccinée était respectivement de 15%, 4% et 10%. L'exécution du modèle avec les différentes valeurs de R0 nous a permis de déterminer le nombre de cas cliniques symptomatiques, les taux d'attaque clinique, les taux d'attaque clinique pour les cas symptomatiques et le nombre de décès. Des versions plus réalistes de ce modèle ainsi que des estimations améliorées des paramètres issus des données de surveillance permettront d'accroître l'utilité des modèles mathématiques

Hybrid segmentation of fluorescent Leschmania-infected images using a watersched and combined region merging based method.

Automatic parasite segmentation in fluorescent images is of high importance as it serves as an easier and faster tool for detecting and counting parasites in each focus. In this paper we present a hybrid segmentation for the Promastigote form of Leishmania parasites in Indirect Immunofluorescence (IIF) images, combining edge and region-based techniques through the morphological algorithm of watershed. The proposed approach deals first with a pre-processing step to correct illumination non-uniformities in the fluorescence Leishmania-infected images before performing the initial segmentation by means of the watershed algorithm. A merging step using joint region homogeneity and edge integrity criteria is then applied to improve the segmentation results. Segmentation tests of 1438 parasites from 40 collected IIF images illustrate the efficiency of our approach.

Adaptive automatic segmentation of Leishmaniasis parasite in Indirect Immunofluorescence images.

This paper describes the first steps for the automation of the serum titration process. In fact, this process requires an Indirect Immunofluorescence (IIF) diagnosis automation. We deal with the initial phase that represents the fluorescence images segmentation. Our approach consists of three principle stages: (1) a color based segmentation which aims at extracting the fluorescent foreground based on k-means clustering, (2) the segmentation of the fluorescent clustered image, and (3) a region-based feature segmentation, intended to remove the fluorescent noisy regions and to locate fluorescent parasites. We evaluated the proposed method on 40 IIF images. Experimental results show that such a method provides reliable and robust automatic segmentation of fluorescent Promastigote parasite.