Epidemiology and burden of Severe Acute Respiratory Infections (SARI) in the aftermath of COVID-19 pandemic: A prospective sentinel surveillance study in a Tunisian Medical ICU, 2022/2023.

BACKGROUND: Severe Acute Respiratory Infections (SARI) caused by influenza and other respiratory viruses pose significant global health challenges, and the COVID-19 pandemic has further strained healthcare systems. As the focus shifts from the pandemic to other respiratory infections, assessing the epidemiology and burden of SARI is crucial for healthcare planning and resource allocation. Aim: to understand the impact of the post-pandemic period on the epidemiology of SARI cases, clinical outcomes, and healthcare resource utilization in Tunisia. METHODS: This is a prospective study conducted in a Tunisian MICU part of a national sentinel surveillance system, focusing on enhanced SARI surveillance. SARI cases from week 39/2022, 26 September to week 19/2023, 13 May were included, according to a standardized case definition. Samples were collected for virological RT-PCR testing, and an electronic system ensured standardized and accurate data collection. Descriptive statistics were performed to assess epidemiology, trends, and outcomes of SARI cases, and univariate/multivariate analyses to assess factors associated with mortality. RESULTS: Among 312 MICU patients, 164 SARI cases were identified during the study period. 64(39%) RT-PCR were returned positive for at least one pathogen, with influenza A and B strains accounting for 20.7% of cases at the early stages of the influenza season. The MICU experienced a significant peak in admissions during weeks 1-11/2023, leading to resource mobilization and the creation of a surge unit. SARI cases utilized 1664/3120 of the MICU-stay days and required 1157 mechanical ventilation days. The overall mortality rate among SARI cases was 22.6%. Age, non-COPD, and ARDS were identified as independent predictors of mortality. CONCLUSIONS: The present study identified a relatively high rate of SARI cases, with 39% positivity for at least one respiratory virus, with influenza A and B strains occurring predominantly during the early stages of the influenza season. The findings shed light on the considerable resource utilization and mortality associated with these infections, underscoring the urgency for proactive management and efficient resource allocation strategies.

Full Genome Characterization of Respiratory Syncytial Virus Causing a Fatal Infection in an Immunocompromised Patient in Tunisia.

Human orthopneumovirus (HRSV) is a virus belonging to the Pneumovirus genus that causes lower respiratory tract infections (LRTI) in infants worldwide. In Tunisia, thousands of infants hospitalized for LRTI are found to be positive for HRSV but no whole genome sequences of HRSV strains circulating in this country are available thus far. In this study, five nasal swab samples collected at different time points from a three-month-old female baby with severe immunodeficiency that was hospitalized for acute bronchiolitis were investigated by next generation sequencing. The Tunisian sequences from this study originated from samples collected in 2021, belong to the ON1 genotype of HRSV-A, and are clustered with European sequences from 2019 and not from 2020 or 2021. This is most likely related to local region-specific transmission of different HRSV-A variants due to the COVID-19 related travel restrictions. Overall, this is the first report describing the whole genome sequence of HRSV from Tunisia. However, more sequence data is needed to better understand the genetic diversity and transmission dynamic of HRSV.

Applying the moving epidemic method to determine influenza epidemic and intensity thresholds using influenza-like illness surveillance data 2009-2018 in Tunisia.

BACKGROUND: Defining the start and assessing the intensity of influenza seasons are essential to ensure timely preventive and control measures and to contribute to the pandemic preparedness. The present study aimed to determine the epidemic and intensity thresholds of influenza season in Tunisia using the moving epidemic method. METHODS: We applied the moving epidemic method (MEM) using the R Language implementation (package "mem"). We have calculated the epidemic and the different intensity thresholds from historical data of the past nine influenza seasons (2009-2010 to 2017-2018) and assessed the impact of the 2009-2010 pandemic year. Data used were the weekly influenza-like illness (ILI) proportions compared with all outpatient acute consultations. The goodness of the model was assessed using a cross validation procedure. RESULTS: The average duration of influenza epidemic during a typical season was 20 weeks and ranged from 11 weeks (2009-2010 season) to 23 weeks (2015-2016 season). The epidemic threshold with the exclusion of the pandemic season was 6.25%. It had a very high sensitivity of 85% and a high specificity of 69%. The different levels of intensity were established as follows: low, if ILI proportion is below 9.74%, medium below 12.05%; high below 13.27%; and very high above this last rate. CONCLUSIONS: This is the first mathematically based study of seasonal threshold of influenza in Tunisia. As in other studies in different countries, the model has shown both good specificity and sensitivity, which allows timely and accurate detection of the start of influenza seasons. The findings will contribute to the development of more efficient measures for influenza prevention and control.

Evaluation of the influenza-like illness surveillance system in Tunisia, 2012-2015.

BACKGROUND: This study was initiated to evaluate, for the first time, the performance and quality of the influenza-like illness (ILI) surveillance system in Tunisia. METHODS: The evaluation covered the period of 2012-2015 and used different data sources to measure indicators related to data quality and completeness, representativeness, timeliness, simplicity, acceptability, flexibility, stability and utility. RESULTS: During the evaluation period, 485.221 ILI cases were reported among 6.386.621 outpatients at 268 ILI sentinel sites. To conserve resources, cases were only enrolled and tested for influenza during times when the number of patients meeting the ILI case definition exceeded 7% (10% after 2014) of the total number of outpatients for the week. When this benchmark was met, five to 10 patients were enrolled and sampled by nasopharyngeal swabs the following week. In total, The National Influenza Center (NIC) received 2476 samples, of which 683 (27.6%) were positive for influenza. The greatest strength of the system was its representativeness and flexibility. The timeliness of the data and the acceptability of the surveillance system performed moderately well; however, the utility of the data and the stability and simplicity of the surveillance system need improvement. Overall, the performance of the Tunisian influenza surveillance system was evaluated as performing moderately well for situational awareness in the country and for collecting representative influenza virologic samples. CONCLUSIONS: The influenza surveillance system in Tunisia provided pertinent evidence for public health interventions related to influenza situational awareness. To better monitor influenza, we propose that ILI surveillance should be limited to sites that are currently performing well and the quality of data collected should be closely monitored and improved.

Implementation of the One Health approach to fight arbovirus infections in the Mediterranean and Black Sea Region: Assessing integrated surveillance in Serbia, Tunisia and Georgia.

BACKGROUND: In the Mediterranean and Black Sea Region, arbovirus infections are emerging infectious diseases. Their surveillance can benefit from one health inter-sectoral collaboration; however, no standardized methodology exists to study One Health surveillance. METHODS: We designed a situation analysis study to document how integration of laboratory/clinical human, animal and entomological surveillance of arboviruses was being implemented in the Region. We applied a framework designed to assess three levels of integration: policy/institutional, data collection/data analysis and dissemination. We tested the use of Business Process Modelling Notation (BPMN) to graphically present evidence of inter-sectoral integration. RESULTS: Serbia, Tunisia and Georgia participated in the study. West Nile Virus surveillance was analysed in Serbia and Tunisia, Crimea-Congo Haemorrhagic Fever surveillance in Georgia. Our framework enabled a standardized analysis of One Health surveillance integration, and BPMN was easily understandable and conducive to detailed discussions among different actors/institutions. In all countries, we observed integration across sectors and levels except in data collection and data analysis. Data collection was interoperable only in Georgia without integrated analysis. In all countries, surveillance was mainly oriented towards outbreak response, triggered by an index human case. DISCUSSION: The three surveillance systems we observed prove that integrated surveillance can be operationalized with a diverse spectrum of options. However, in all countries, the integrated use of data for early warning and inter-sectoral priority setting is pioneeristic. We also noted that early warning before human case occurrence is recurrently not operationally prioritized.