Are we prepared for the next influenza pandemic? Lessons from modelling different preparedness policies against four pandemic scenarios

Genomic Surveillance for Monitoring Variants of Concern: SARS-CoV-2 Delta, Omicron, and Beyond

The continuing emergence of new SARS-CoV-2 variants has perpetuated the current pandemic far beyond initial expectations. It is now likely that this virus is here to stay. Thus, a new infrastructure is required for monitoring and tracking of viral outbreaks which includes epidemiological and genomic surveillance. More effective monitoring will support rapid response times required for development of new treatments and vaccines to help manage the spread of the current virus and prepare the platforms required for future pandemics.

Sanitary Aspects of Countering the Spread of COVID-19 in Russia

Due to the conditions that cause the spread of COVID-19, national health systems worldwide are under severe strain. Most countries face similar difficulties such as a lack of medical personnel and equipment and tools for diagnosis and treatment, overrun hospitals, and forced restriction of planned medical care. Public authorities in healthcare take the following measures due to increased pressure: limiting the transmission and spread of the virus (social distancing and quarantine), mobilizing medical personnel, ensuring the availability of diagnostic and treatment tools, and providing a sufficient number of premises, which are not always suitable for the provision of medical care (buildings and structures). To date, the stages of management decision-making to counter coronavirus infection and the risk of COVID-19 transmission at various facilities have not been analyzed. The authors propose a methodology for assessing the COVID-19 transmission risk at various social and transport facilities. A survey of 1325 respondents from Moscow demonstrated the most significant risk factors, such as visitation avoidance, infection risk, and facemask wearing. Risk categories were determined and objects classified according to high, medium, and low-risk levels.

Short-hairpin RNAs delivered by recombinant adeno-associated virus inhibited the replication of influenza A viruses in vitro

Antiviral short-hairpin RNAs (shRNAs) delivered by recombinant adeno-associated virus (rAAV) were investigated for their potential prophylactic and therapeutic applications related to the influenza A virus (IAV). To express shRNAs efficiently, an H1 promoter was inserted into the commercial rAAV2 system. The modified rAAV2 system could express shRNAs, and the purified rAAV was obtained at levels over 10¹³ viral genomes/ml and 10¹⁰ viral infection units/ml. The shNP-1496-n and shM2-925 delivered by rAAV could inhibit the replication of the H1N1 and H5N1 virus by targeting the conserved regions of the IAV nucleoprotein and matrix 2 genes in MDCK cells. The shNP-1496-n and shM2-925 expressed by rAAV could provide potent and long-term anti-H5N1 virus effects in rAAV-shRNA-enriched MDCK cells. Our findings provide a rational basis for developing RNA interference for the prevention and therapy of IAV infection.

A Review of Research on Tourism Industry, Economic Crisis and Mitigation Process of the Loss: Analysis on Pre, During and Post Pandemic Situation

Throughout time, the global tourism industry and economy have been significantly affected by disasters and crises. At present, COVID-19 represents one of these disasters as it has been causing a serious economic downturn with huge implications in tourism. In this review paper, we have analysed more than 100 papers regarding the effect and consequences of a pandemic on tourism and related industries, the economic situation in countries and areas, and mitigation of the loss incurred due to pandemic situations. The article (1) is based on past research on tourism and economy, (2) examines the effects of a pandemic on listed sectors and mitigation processes, and (3) suggests future research and approaches to help progress the field. We have gathered and categorised the literature reviews into several parts. In addition, we have listed the name of authors, journal names, books, websites, and relevant data.

Mathematical model of the feedback between global supply chain disruption and COVID-19 dynamics

The pandemic of COVID-19 has become one of the greatest threats to human health, causing severe disruptions in the global supply chain, and compromising health care delivery worldwide. Although government authorities sought to contain the spread of SARS-CoV-2, by restricting travel and in-person activities, failure to deploy time-sensitive strategies in ramping-up of critical resource production exacerbated the outbreak. Here, we developed a mathematical model to analyze the effects of the interaction between supply chain disruption and infectious disease dynamics using coupled production and disease networks built on global data. Analysis of the supply chain model suggests that time-sensitive containment strategies could be created to balance objectives in pandemic control and economic losses, leading to a spatiotemporal separation of infection peaks that alleviates the societal impact of the disease. A lean resource allocation strategy can reduce the impact of supply chain shortages from 11.91 to 1.11% in North America. Our model highlights the importance of cross-sectoral coordination and region-wise collaboration to optimally contain a pandemic and provides a framework that could advance the containment and model-based decision making for future pandemics.

Artificial Intelligence-Empowered Mobilization of Assessments in COVID-19-like Pandemics: A Case Study for Early Flattening of the Curve

The global outbreak of the Coronavirus Disease 2019 (COVID-19) pandemic has uncovered the fragility of healthcare and public health preparedness and planning against epidemics/pandemics. In addition to the medical practice for treatment and immunization, it is vital to have a thorough understanding of community spread phenomena as related research reports 17.9–30.8% confirmed cases to remain asymptomatic. Therefore, an effective assessment strategy is vital to maximize tested population in a short amount of time. This article proposes an Artificial Intelligence (AI)-driven mobilization strategy for mobile assessment agents for epidemics/pandemics. To this end, a self-organizing feature map (SOFM) is trained by using data acquired from past mobile crowdsensing (MCS) campaigns to model mobility patterns of individuals in multiple districts of a city so to maximize the assessed population with minimum agents in the shortest possible time. Through simulation results for a real street map on a mobile crowdsensing simulator and considering the worst case analysis, it is shown that on the 15th day following the first confirmed case in the city under the risk of community spread, AI-enabled mobilization of assessment centers can reduce the unassessed population size down to one fourth of the unassessed population under the case when assessment agents are randomly deployed over the entire city.

Can mathematical modelling solve the current Covid-19 crisis?

Since COVID-19 transmission started in late January, mathematical modelling has been at the forefront of shaping the decisions around different non-pharmaceutical interventions to confine its' spread in the UK and worldwide. This Editorial discusses the importance of modelling in understanding Covid-19 spread, highlights different modelling approaches and suggests that while modelling is important, no one model can give all the answers.

A method for evaluating the cost-benefit of different preparedness planning policies against pandemic influenza

•Our work presents a unifying method to calculate the net-benefit of different preparedness policies against different pandemic influeunza strains. Unlike previous methods, which have focused on evaluating specific strategies against specific pandemics, our method allows assessment of mass immunisation strategies in presence and absence of antiviral drugs for a large range of pandemic influenza strain characteristics and programme features. Overall, the model described here combines two parts to evaluate different preparedness planning policies against pandemic influenza.•The first part is adaptation of an existing transmission model for seasonal influenza to include generalisation across large number of pandemic influenza scenarios.•The second part is development of a tailor-made health economic model devised in collaboration with colleagues at the UK Department of Health and Social Care.