ObjectiveTo establish morbidity patterns of influenza A/H1N1 in Swaziland from 10th July to 15th August 2017.IntroductionInfluenza infection is caused by the influenza virus, a single-stranded RNA virus belonging to the Orthomyxoviridae family. Influenza viruses are classified as types A, B and C. Influenza A and B viruses can cause epidemic disease in humans and type C viruses usually cause a mild, cold-like illness. The influenza virus spreads rapidly around the world in seasonal epidemics, resulting in significant morbidity and mortality. On the 10th of July 2017, a case of confirmed Influenza A/H1N1 was reported through the immediate disease notification system from a private hospital in the Hhohho region. A 49 year old female was diagnosed of Influenza A/H1N1 after presenting with flu-like symptoms. Contacts of the index case were followed and further positive cases were identified.MethodsUpon identification of the index case, the rapid response teams conducted further investigations. Two nasal swaps from each sample were taken and sent to a private laboratory in South Africa for the detection of the virus RNA using RT-PCR to assess for the presence Influenza A, B and Influenza A/H1N1. Further laboratory results were sourced from a private laboratory to monitor trends of influenza. Data was captured and analyzed in STATA version 12 from STATA cooperation. Descriptive statistics were carried out using means and standard deviations. The Pearson Chi square test and student t test were used to test for any possible association between influenza A/H1N1 and the explanatory variables (age and sex).ResultsSurveillance data captured between 10th July 2017 and 15th August 2017 indicated that a total of 87 patients had their samples taken for laboratory confirmation. There were 45 females and 42 males and the mean age was 27 years (SD= 17). At least 25 of the 87 patients tested positive for influenza A while only 1 tested positive for influenza B. The prevalence of influenza A/H1N1 was 16%. The prevalence of influenza A/H1N1 among males was 19% compared to 13% in females; however the difference was not statistically significant (p=0.469). There was no association noted between age and influenza A/H1N1 (p=427). Upon further sub-typing results indicated that the circulating strain was influenza A/H1N1 pdm 09 strain which is a seasonal influenza. The epidemic task forces held weekly and ad-hoc meetings to provide feedback to principals and health messaging to the general population to allay anxiety.ConclusionsThough WHO has classified the influenza A/H1N1 strain pdm 0029 as a seasonal influenza, surveillance remains important for early detection and management. There is therefore an urgent need to set up sentinel sites to monitor and understand the circulating influenza strains. Health promotion remains crucial to dispel anxiety as the general public still link any influenza to the 2009 pandemic influenza. Finally the Ministry of Health should consider introducing influenza vaccines into the routine immunization schedule especially for children.References1. Global Epidemiological Surveillance Standards for Influenza. 2014 [cited 2015 15 April]; Available from: http://www.who.int/influenza/resources/documents/influenza_surveillance_manual/en/.2. Human cases of influenza at the human-animal interface, 2013. Wkly Epidemiol Rec, 2014.89(28): p. 309-20.3. WHO Global Influenza Surveillance Network. Manual for the laboratory diagnosis and virological surveillance of influenza. 2011 [cited 2015 April27]; Available from: http://www.who.int/influenza/gisrs_laboratory/manual_diagnosis_surveillance_influenza/en/.

ObjectiveTo enable coordination of Swaziland Ministry of Health units forpublic health surveillance (PHS).IntroductionIn the Kingdom of Swaziland, a baseline assessment found thatmultiple functional units within the Ministry of Health (MoH) performPHS activities. There is limited data sharing and coordination betweenunits; roles and responsibilities are unclear. The Epidemiology andDisease Control Unit (EDCU) is mandated to coordinate efforts andstrengthen PHS through implementing Integrated Disease Surveillanceand Response (IDSR) to fulfill requirements of International HealthRegulations (2005) (IHR[2005]), and the Global Health SecurityAgenda (GHSA).MethodsA baseline assessment that included key informant interviewsof unit representatives was conducted. Data flows were developed.Results were disseminated at a facilitated stakeholder workshop withunit representatives. A database was then built containing all distinctactivities found within the IDSR Technical Guidelines (2010), IHR[2005], GHSA Action Packages, the baseline assessment, a previousCDC IDSR assessment, and suggestions from the stakeholderworkshop. Activities were categorized by IDSR function (identify,report, analyze, investigate, prepare, respond, provide feedback,and evaluate) and designated as an ongoing “role” or a one-timeimplementation activity. A document containing all PHS roles waspresented at a facilitated consensus workshop; unit representativesdiscussed and designated a lead unit/agency for each role.One-time implementation activities were assigned a lead actor, targetcompletion date, and compiled into a 3-year IDSR Roadmap to guideimplementation.ResultsA Roles and Responsibilities Framework was developed thatpresents a consensus on lead units for all roles within an IDSR-basedPHS system that fulfills requirements of IHR [2005] and GHSA.This document enables coordination by EDCU. The IDSR Roadmapprovides time-bound activities with assigned actors to implementIDSR. EDCU is using these documents to guide coordination ofmultiple MOH units already performing PHS activities.ConclusionsCoordinating well-established programs that already collectepidemiological data increases efficiency and enables more completeepidemiologic analysis. Stakeholder engagement and clarity of rolesis critical for EDCU to coordinate PHS. Consolidating activitiesfor IDSR, IHR [2005], and GHSA in guiding documents enables astreamlined approach for public health surveillance strengthening.Future work aims to achieve data sharing through an electronicplatform and introduce data standards for interoperability among datasets.K