Tanzania's first Marburg Viral Disease outbreak response: Describing the roles of FELTP graduates and residents.

Viral Haemorrhagic Fever Outbreak presents a significant public health threat, requiring a timely, robust, and well-coordinated response. This paper aims to describe the roles of the Tanzania Field Epidemiology and Laboratory Training Program (TFELTP) graduates and residents in responding to Tanzania's first Marburg Viral Disease (MVD) outbreak. We performed a secondary data analysis using a range of documents, such as rosters of deployed responders and the TFELTP graduate and resident database, to count and describe them. Additionally, we conducted an exploratory textual analysis of field deployment reports and outbreak situational reports to delineate the roles played by the residents and graduates within each response pillar. A total of 70 TFELTP graduates and residents from different regions were involved in supporting the response efforts. TFELTP graduates and residents actively participated in several interventions, including contact tracing and follow up, sensitising clinicians on surveillance tools such as standard case definitions, alert management, supporting the National and Kagera Regional Public Health Emergency Operations Centres, active case search, risk communication, and community engagement, coordination of logistics, passenger screening at points of entry, and conducting Infection Prevention and Control (IPC) assessments and orientations in 144 Health Facilities. The successes achieved and lessons learned from the MVD response lay a foundation for sustained investment in skilled workforce development. FELTP Training is a key strategy for enhancing global health security and strengthening outbreak response capabilities in Tanzania and beyond

Etiologies of influenza-like illness and severe acute respiratory infections in Tanzania, 2017-2019.

In 2016, Tanzania expanded sentinel surveillance for influenza-like illness (ILI) and severe acute respiratory infection (SARI) to include testing for non-influenza respiratory viruses (NIRVs) and additional respiratory pathogens at 9 sentinel sites. During 2017-2019, respiratory specimens from 2730 cases underwent expanded testing: 2475 specimens (90.7%) were tested using a U.S. Centers for Disease Control and Prevention (CDC)-developed assay covering 7 NIRVs (respiratory syncytial virus [RSV], rhinovirus, adenovirus, human metapneumovirus, parainfluenza virus 1, 2, and 3) and influenza A and B viruses. Additionally, 255 specimens (9.3%) were tested using the Fast-Track Diagnostics Respiratory Pathogens 33 (FTD-33) kit which covered the mentioned viruses and additional viral, bacterial, and fungal pathogens. Influenza viruses were identified in 7.5% of all specimens; however, use of the CDC assay and FTD-33 kit increased the number of specimens with a pathogen identified to 61.8% and 91.5%, respectively. Among the 9 common viruses between the CDC assay and FTD-33 kit, the most identified pathogens were RSV (22.9%), rhinovirus (21.8%), and adenovirus (14.0%); multi-pathogen co-detections were common. Odds of hospitalization (SARI vs. ILI) varied by sex, age, geographic zone, year of diagnosis, and pathogen identified; hospitalized illnesses were most common among children under the age of 5 years. The greatest number of specimens were submitted for testing during December-April, coinciding with rainy seasons in Tanzania, and several viral pathogens demonstrated seasonal variation (RSV, human metapneumovirus, influenza A and B, and parainfluenza viruses). This study demonstrates that expanding an existing influenza platform to include additional respiratory pathogens can provide valuable insight into the etiology, incidence, severity, and geographic/temporal patterns of respiratory illness. Continued respiratory surveillance in Tanzania, and globally, can provide valuable data, particularly in the context of emerging respiratory pathogens such as SARS-CoV-2, and guide public health interventions to reduce the burden of respiratory illnesses

List of DENV-1 Tanzania sequences names, 2017–2019.

List of DENV-1 Tanzania sequences names, 2017–2019.</p

List of DENV-3 Tanzania sequences names, 2017–2019.

List of DENV-3 Tanzania sequences names, 2017–2019.</p

Distribution of dengue fever cases in Tanzania from 2017 to 2019.

The map shows 26 Tanzania mainland administrative regions. The five color-coded regions show dengue fever cases distribution between 2017–2019. Map created with QGIS 3.24.1 All shape files are openly available sources (https://www.nbs.go.tz/index.php/en/census-surveys/gis/385-2012-phc-shapefiles-level-one-and-two). The shapefiles were made based on the 2012 population and housing census, but in this study, the shapefile has been modified to capture all the regions and district information.</p

Distribution of dengue samples per region from 2017–2019.

Distribution of dengue samples per region from 2017–2019.</p

Genotyping of DENV-1 circulating in Tanzania in 2019.

Maximum likelihood phylogenetic tree reconstructed with the 341 sequences generated by this study and 69 additional sequences from GenBank to provide genotype reference and geographic-temporal context. The tree was rooted at midpoint. Genotype I was only detected from one sample in 2019, while genotype V was found widely circulated in the 2019 epidemic. The Tanzanian sequences (OM920075—OM920415) in red. Genotypes are presented with colored highlighted branches; Genotypes IV, III, V, II, and I are highlighted in pink, blue, green, gold, and purple, respectively. Contextual sequences are labeled with GenBank accession number, country of origin, and year of isolation.</p

Genotyping of DENV-3 circulating in Tanzania 2017–2018.

Maximum likelihood phylogenetic tree reconstructed with the 32 DENV-3 sequence generated by this study and 40 additional sequences from GenBank to provide genotype reference and geographic-temporal context. The tree was rooted at midpoint. pink, blue, green, gold and purple represents genotypes V, II, III, I, and IV, respectively. Tanzanian sequences (OM920035—OM920066) are in red. Contextual sequences are labeled with GenBank accession number, country of origin, and year of isolation.</p

Socio-demographic characteristics of patients with dengue infection in Tanzania from 2017 to 2019.

Socio-demographic characteristics of patients with dengue infection in Tanzania from 2017 to 2019.</p

The East African Community (EAC) mobile laboratory networks in Kenya, Burundi, Tanzania, Rwanda, Uganda, and South Sudan—from project implementation to outbreak response against Dengue, Ebola, COVID-19, and epidemic-prone diseases

Background!#!East Africa is home to 170 million people and prone to frequent outbreaks of viral haemorrhagic fevers and various bacterial diseases. A major challenge is that epidemics mostly happen in remote areas, where infrastructure for Biosecurity Level (BSL) 3/4 laboratory capacity is not available. As samples have to be transported from the outbreak area to the National Public Health Laboratories (NPHL) in the capitals or even flown to international reference centres, diagnosis is significantly delayed and epidemics emerge.!##!Main text!#!The East African Community (EAC), an intergovernmental body of Burundi, Rwanda, Tanzania, Kenya, Uganda, and South Sudan, received 10 million € funding from the German Development Bank (KfW) to establish BSL3/4 capacity in the region. Between 2017 and 2020, the EAC in collaboration with the Bernhard-Nocht-Institute for Tropical Medicine (Germany) and the Partner Countries' Ministries of Health and their respective NPHLs, established a regional network of nine mobile BSL3/4 laboratories. These rapidly deployable laboratories allowed the region to reduce sample turn-around-time (from days to an average of 8h) at the centre of the outbreak and rapidly respond to epidemics. In the present article, the approach for implementing such a regional project is outlined and five major aspects (including recommendations) are described: (i) the overall project coordination activities through the EAC Secretariat and the Partner States, (ii) procurement of equipment, (iii) the established laboratory setup and diagnostic panels, (iv) regional training activities and capacity building of various stakeholders and (v) completed and ongoing field missions. The latter includes an EAC/WHO field simulation exercise that was conducted on the border between Tanzania and Kenya in June 2019, the support in molecular diagnosis during the Tanzanian Dengue outbreak in 2019, the participation in the Ugandan National Ebola response activities in Kisoro district along the Uganda/DRC border in Oct/Nov 2019 and the deployments of the laboratories to assist in SARS-CoV-2 diagnostics throughout the region since early 2020.!##!Conclusions!#!The established EAC mobile laboratory network allows accurate and timely diagnosis of BSL3/4 pathogens in all East African countries, important for individual patient management and to effectively contain the spread of epidemic-prone diseases