COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery

Introduction: Over the past two decades, vaccination programmes for vaccine-preventable diseases (VPDs) have expanded across low- and middle-income countries (LMICs). However, the rise of COVID-19 resulted in global disruption to routine immunisation (RI) activities. Such disruptions could have a detrimental effect on public health, leading to more deaths from VPDs, particularly without mitigation efforts. Hence, as RIs resume, it is important to estimate the effectiveness of different approaches for recovery. Methods: We apply an impact extrapolation method developed by the Vaccine Impact Modelling Consortium to estimate the impact of COVID-19-related disruptions with different recovery scenarios for ten VPDs across 112 LMICs. We focus on deaths averted due to RIs occurring in the years 2020- 2030 and investigate two recovery scenarios relative to a no-COVID-19 scenario. In the recovery scenarios, we assume a 10% COVID-19-related drop in RI coverage in the year 2020. We then linearly interpolate coverage to the year 2030 to investigate two routes to recovery, whereby the immunization agenda (IA2030) targets are reached by 2030 or fall short by 10%. Results: We estimate that falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths over the years 2020-2030 relative to the noCOVID-19 scenario, whereas, reaching the IA2030 targets reduces these proportions to 5% fewer FVPs and 5.22% more deaths. The impact of the disruption varies across the VPDs with diseases where coverage expands drastically in future years facing a smaller detrimental effect. Conclusion: Overall, our results show that drops in RI coverage could result in more deaths due to VPDs. As the impact of COVID-19-related disruptions is dependent on the vaccination coverage that is achieved over the coming years, the continued efforts of building up coverage and addressing gaps in immunity are vital in the road to recovery.

Globally consistent assessment of economic impacts of wildfires in CLIMADA v2.2

In light of the dramatic increase in economic impacts due to wildfires over recent years, the need for globally consistent impact modelling of wildfire damages is ever increasing. Insurance companies, individual households, humanitarian organizations, governmental authorities, and investors and portfolio owners are increasingly required to account for climate-related physical risks. In response to these societal challenges, we present an extension to the open-source and open-access risk modelling platform CLIMADA (CLImate ADAptation) for modelling economic impacts of wildfires in a globally consistent and spatially explicit approach. All input data are free, public and globally available, ensuring applicability in data-scarce regions of the Global South. The model was calibrated at resolutions of 1, 4 and 10 km using information on past wildfire damage reported by the disaster database EM-DAT. Despite the large remaining uncertainties, the model yields sound damage estimates with a model performance well in line with the results of other natural catastrophe impact models, such as for tropical cyclones. To complement the global perspective of this study, we conducted two case studies on the recent megafires in Chile (2017) and Australia (2020). The model is made available online as part of a Python package, ready for application in practical contexts such as disaster risk assessment, near-real-time impact estimates or physical climate risk disclosure.

How can the public health impact of vaccination be estimated?

Background Deaths due to vaccine preventable diseases cause a notable proportion of mortality worldwide. To quantify the importance of vaccination, it is necessary to estimate the burden averted through vaccination. The Vaccine Impact Modelling Consortium (VIMC) was established to estimate the health impact of vaccination. Methods We describe the methods implemented by the VIMC to estimate impact by calendar year, birth year and year of vaccination (YoV). The calendar and birth year methods estimate impact in a particular year and over the lifetime of a particular birth cohort, respectively. The YoV method estimates the impact of a particular year’s vaccination activities through the use of impact ratios which have no stratification and stratification by activity type and/or birth cohort. Furthermore, we detail an impact extrapolation (IE) method for use between coverage scenarios. We compare the methods, focusing on YoV for hepatitis B, measles and yellow fever. Results We find that the YoV methods estimate similar impact with routine vaccinations but have greater yearly variation when campaigns occur with the birth cohort stratification. The IE performs well for the YoV methods, providing a time-efficient mechanism for updates to impact estimates. Conclusions These methods provide a robust set of approaches to quantify vaccination impact; however it is vital that the area of impact estimation continues to develop in order to capture the full effect of immunisation.

Sensitivity of Estuaries to Compound Flooding

Fluvial and surge-tide extremes can occur synchronously resulting in compound flooding in estuaries, greatly intensifying the hazard. This flood risk has the potential to increase in the future as the frequency, phasing and/or intensity of these drivers change. Improved understanding of how extreme fluvial discharge and surge-tides interact will help inform future flood mitigation methodology. In this paper, therefore, we resolve for the first time intra-estuary sensitivities to fluvial and surge-tide extremes, for two contrasting UK estuaries (Humber and Dyfi). Model simulations at hyper-spatial resolution (< 50 m) using a 2D hydrodynamic model predicted compound flooding hazards based on: (1) present-day extreme events (worst on record); (2) present-day extreme events with shifted timings of the drivers to maximise flooding; and (3) modified drivers representing projected climate change. We found that in a small estuary with short-duration, high-intensity fluvial inputs (Dyfi), flood extent is sensitive to the relative timing of the fluvial and surge-tide drivers. In contrast, the relative timing of these drivers did not affect flooding in a larger estuary with a slower fluvial response to rainfall (Humber). In the Humber, extreme fluvial inputs during a compound hazard actually reduced maximum water depths in the outer estuary, compared with a surge-tide-only event. Projected future changes in these drivers by 2100 will increase compound flooding hazards: simulated sea-level rise scenarios predicted substantial and widespread flooding in both estuaries. However, projected increases in surge-tide behaved differently to sea-level rise of the same magnitude, resulting in a greater seawater influx and more flooding. Increased fluvial volumes were the weakest driver of estuarine flooding. In this paper we show how these interactions are complex and how the hydrodynamics vary considerably between different estuaries and sites within estuaries, making it difficult to generalise, use probabilistic or use 1D approaches for assessing compound flooding hazards. Hence, we contribute new knowledge and methods for catchment-to-coast impact modelling used for flood mitigation strategies.

Globally consistent assessment of economic impacts of wildfires in CLIMADA v2.2

In light of the dramatic increase in economic impacts due to wildfires over recent years, the need for globally consistent impact modelling of wildfire damages is ever increasing. Insurance companies, individual households, humanitarian organisations and governmental authorities, as well as investors and portfolio owners, are increasingly required to account for climate-related physical risks. In this study we present a globally consistent and spatially explicit approach to modelling wildfire impacts using the open-source and open-access risk modelling platform CLIMADA (CLImate ADAptation). All input data is free, public and globally available, ensuring applicability in data-scarce regions of the Global South. The model was calibrated at resolutions of 1, 4 and 10 kilometers using information on past wildfire damage reported by the disaster database EM-DAT. Despite the large remaining uncertainties, the model yields sound damage estimates with a model performance well in line with the results of other natural catastrophe impact models, such as for tropical cyclones. To complement the global 10 perspective of this study, we conducted two case studies on the recent mega fires in Chile (2017) and Australia (2020). The model is made available online as part of a Python package, ready for application in practical contexts such as disaster risk assessment or physical climate risk disclosure.

Experiences with virtual schools on “Climate data for impact assessments”

&lt;p&gt;The provision of climate services to users is a fast developing field. In support of this development, the IS-ENES3 project, funded within the EC Horizon2020 program, organized three schools on &amp;#8220;Climate data for impact assessments&amp;#8221; in 2020 and 2021. In an Autumn school, a Spring school and a Summer school, climate scientists and impact scientists were brought together. An important aim of the schools was&amp;#160;to enhance interaction between Vulnerability-Impact-Adaptation (VIA) researchers, climate services providers and climate researchers. Another aim was to provide an overview of information on climate modeling, climate data, impact modelling and climate services based on the work of the IS-ENE3 project.&lt;/p&gt;&lt;p&gt;In the first three weeks a series of lectures was given, covering topics such as climate data and modelling, impact models, portals for accessing and processing climate data, setting-up impact assessments, and communication of results to stakeholders. In the last three weeks the participants worked in small groups of one climate scientist with one impact scientist on a case study under the guidance of the course lecturers. Impact and climate researchers were combined on purpose to let them experience how they could help each other.&lt;/p&gt;&lt;p&gt;Originally the schools were planned to take place on-site (e.g. in Prague) during one week; however, due to COVID-19 the schools had to be transformed to virtual schools with two weekly sessions during six weeks. Although the virtual set-up had some disadvantages (e.g. less possibilities for networking), there were also some advantages (e.g. the possibility to record the lectures and make them available to a broader audience; more time to explore and work with climate data in between the sessions, no CO&lt;sub&gt;2&lt;/sub&gt; emissions for travelling). During this presentation we will present the set-up of the schools and the conversion to a virtual school. We will focus on the lessons learnt and the evaluation of the virtual schools by the participants and give some recommendations for similar schools and how to link the climate and VIA research communities .&lt;/p&gt;

Spatial Algorithms for Geometric Contact Detection in Multibody System Dynamics

In the present work, different algorithms for contact detection in multibody systems based on smooth contact modelling approaches are presented. Beginning with the simplest ones, some difficult interactions are subsequently introduced. In addition, a brief overview on the different kinds of contact/impact modelling is provided and an underlining of the advantages and the drawbacks of each of them is determined. Finally, some practical examples of each interaction are presented and analyzed and an outline of the issues arisen during the design process and how they have been solved in order to obtain stable and accurate results is given. The main goal of this paper is to provide a resource for the early-stage researchers in the field that serves as an introduction to the modelling of simple contact/impact events in the context of multibody system dynamics.