Success and challenges of health systems resilience-enhancing strategies for managing Public Health Emergencies of International Concerns (PHEIC): A systematic review protocol.

INTRODUCTION: Health systems resilience is the ability to prepare, manage and learn from a sudden and unpredictable extreme change that impacts health systems. Health systems globally have recently been affected by a number of catastrophic events, including natural disasters and infectious disease epidemics. Understanding health systems resilience has never been more essential until emerging global pandemics. Therefore, the application of resilience-enhancing strategies needs to be assessed to identify the management gaps and give valuable recommendations from the lessons learnt from the global pandemic. METHODS: The systematic review will be reported using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA-P) protocols guideline. Reporting data on World Health Organization (WHO) health system building blocks and systematic searches on resilience enhancing strategies for the management of Public Health Emergencies of International Concerns (PHEIC) after the establishment of International Health Regulations (IHR) in 2007 will be included. The search will be conducted in PubMed, Scopus, Web of Science and Google Scholar ETHICS AND DISSEMINATION: Ethics approval and safety considerations are not applicable. Pre-print of the protocol is available online, and the screening of the articles will be done using Rayyan software in a transparent manner. The findings will be presented at conferences and the final review's findings will be published in a peer-reviewed international journal and will be disseminated to global communities for the application of successful management strategies for the management of future pandemics. PROSPERO REGISTRATION NUMBER: CRD42022352612; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022352612.

Predictive Analysis of COVID-19 Spread in Sri Lanka using an Adaptive Compartmental Model: Susceptible-Exposed-Infected-Recovered-Dead (SEIRD) Model

Novel Corona Virus (COVID-19) is still spreading throughout the world despite various degrees of movement restrictions and the availability of multiple safe and effective vaccines. Modelling in predicting the spread of an epidemic is important for health planning and policies. This study aimed to apply a dynamic Susceptible-Exposed-Infected-Recovered-Deaths (SEIRD) model and simulated it under a range of epidemic conditions using python programme language. The predictions were based on different scenarios from without any preventive measures to several different preventive measures under R0 of 4. The model shows that more weight to personal protection can halt the spread of transmission followed by the closure of public places and interprovincial movement restriction. Results after simulating various scenarios indicate that disregarding personal protective measures can have devastating effects on the local population. Strict adherence, maintaining and monitoring of self-preventive measures are vital towards minimizing the death toll from COVID-19.

An Extended Susceptible-Exposed-Infected-Recovered (SEIR) Model with Vaccination for Forecasting the COVID-19 Pandemic in Sri Lanka

The role of modelling in predicting the spread of an epidemic is important for health planning and policies. This study aimed to apply a compartmental model for predicting the variations of epidemiological parameters in Sri Lanka. We used a dynamic Susceptible-Exposed-Infected-Recovered-Vaccinated (SEIRV) model and simulated potential vaccine strategies under a range of epidemic conditions. The predictions were based on different vaccination coverages (5% to 90%), vaccination-rates (1%, 2%, 5%) and vaccine-efficacies (40%, 60%, 80%) under different R0 (2,4,6). We estimated the duration, exposed, and infected populations. When the R0 was increased, the days of reduction of susceptibility and the days to reach the peak of the infection were reduced gradually. At least 45% vaccine coverage is required for reducing the infected population to mitigate a disastrous situation in Sri Lanka. The results revealed that when R0 is increased in the SEIRV model along with the increase of vaccination efficacy and vaccination rate, the population to be vaccinated is reducing. Thus, the vaccination offers greater benefits to the local population by reducing the time to reach the peak, exposed and infected population through flattening the curves.

Analysis of scoring systems for primary immunodeficiency diagnosis in adult immunology clinics.

Failure to spot the signs of primary immunodeficiency (PID) often results in delayed diagnosis. Scoring systems to identify PID exist, such as the immunodeficiency disease-related (IDR) score. This research aims to analyse and improve the diagnostic sensitivity and specificity of the IDR scoring system in a small preselected group of adult patients referred to immunology with clinical suspicion of a PID. Records of all patients presenting for the first time to an adult immunology clinic in 2018 at Addenbrooke's Hospital, Cambridge, were scored using the unmodified IDR score and modified versions of it. Included records were searched for a subsequent diagnosis of PID, and the diagnostic sensitivity and specificity of the scoring systems were analysed. Of 400 patients, 213 were excluded: 141 due to secondary immunodeficiency, 69 due to no clinical suspicion of a PID, and hence no investigation for PID, and three due to ongoing diagnostic investigations. Of 187 included patients, 71 were found to have a clinically significant PID. The unmodified IDR score was useful in discriminating between those with and without PID. Modification of the scoring system with seven additional criteria improved the sensitivity and specificity for PID diagnosis to the greatest extent. A modified IDR score with seven additional criteria validated in adults referred to immunology with suspicion of a PID could be used clinically to aid PID diagnosis, although further validation in different patient cohorts is required before it is used in other contexts.