Outbreak Conditions Research Articles

“I get amazing strength when conditions are overcrowded” nurses experience in handling covid-19 patients during outbreaks in emergency rooms

This study explores the experience of nurses dealing with COVID-19 patients in the ER during an outbreak. Using a qualitative design, phenomenological approach. Using a qualitative design with a phenomenological approach. Data collection was carried out using semi-structured interviews with 7 participants who cared for COVID-19 patients during the outbreak. Data analysis This research uses the Colaizzi method analysis technique (Cresswell). Data collection was carried out by semi structure interviews with 7 participants who handled COVID-19 patients during the outbreak. The results of the interviews were transcribed, analysed and classified. Next, determine the meaningful statement from the transcript. Data analysis using collaizi. This study shows the identified themes based on the experience of nurses in dealing with COVID-19 patients in the ER during outbreak conditions, namely: Feeling the crisis and outbreak of COVID-19; fear of contracting and transmitting in epidemic conditions; attitude of family rejection related to COVID-19; grateful for health; share feelings to strengthen; and better prepared for the next COVID-19 outbreak. Participants as emergency room nurses experienced a crisis and COVID-19 outbreak in June-July 2021, felt afraid of contracting and transmitting the COVID-19 virus. Emergency room nurses experience family rejection related to COVID-19, but after being infected with COVID-19, they are very grateful for the gift of health, share feelings to encourage one another, and are better prepared for the next COVID-19 outbreak. The hospital needs to provide training to nurses regarding SPGDT-B RS due to the COVID-19 pandemic, and training to deal effectively with psychological problems routine and consistent.

Epidemiological characteristics of infectious disease outbreaks in schools in Zhejiang province, China, from 2013 to 2021

BackgroundSchools are special and important places where susceptible groups of infectious diseases congregate, providing conditions for infectious disease outbreaks. A retrospective analysis of school outbreaks was conducted to explore the epidemiological characteristics of school outbreaks in Zhejiang Province, China.MethodsData on school infectious disease outbreaks reported in Zhejiang Province from 2013 to 2021 were collected. The characteristics of the temporal and spatial distributions, attack rates, identification durations, outbreak durations and influencing factors were studied using descriptive epidemiological methods.ResultsA total of 1248 school outbreaks of 20 infectious causes were reported, for an overall attack rate of 2.97%. Among intestinal and respiratory infections, norovirus acute gastroenteritis and varicella, respectively, were the most common causes. May and December presented the greatest number of causes of school outbreaks, whereas November to January presented the peak number of school outbreaks. The three causes of outbreaks with the highest attack rates were herpeticangina (7.76%), influenza-like illness (7.48%), and influenza (6.37%) outbreaks. The three most common causes with the longest median identification duration and median outbreak duration were tuberculosis, Mycoplasma pneumoniae, and mumps. Kindergartens (5.54%), by school closures (3.44%), and rural schools (4.02%) presented higher attack rates, whereas reporting outbreaks within two days yielded a lower attack rate (2.09%). The median duration of outbreaks in kindergartens (4.00 days), by school closures (7.00 days), and reporting outbreaks within two days (3.00 days) was shorter, whereas that in rural schools was longer (10.50 days).ConclusionKindergartens and rural schools are the key units for preventing and controlling school outbreaks. May and November–January should receive more attention. Timely reporting and school closures could be implemented to reduce the attack rate, outbreak duration, and impact of infectious diseases on students’ health.

Towards transient space-use dynamics: re-envisioning models of utilization distribution and their applications

BackgroundModels of utilization distribution in the form of partial differential equations have long contributed to our understanding of organismal space use patterns. In studies of infectious diseases, they are also being increasingly adopted in support of epidemic forecasting and scenario planning. However, as movement research shifts its focus towards large data collection and statistical modeling of movement trajectories, the development of such models has notably slowed.MethodsHere, we demonstrate the continued importance of modeling utilization distribution to predict variation in space-use patterns over time. We highlight the considerable, yet largely untapped, potential of such models, which have historically been limited by the steady-state assumption due to longstanding technical constraints. Now, by adapting existing computational tools primarily developed for material science and engineering, we can probe beyond the steady states and unlock from them a broad spectrum of complex, transient space-use dynamics. Our approach requires little experience in numerical analysis and is readily accessible to model practitioners in ecology and epidemiology across diverse systems where movement is a critical feature.ResultsWe illustrated our approach using a mix of canonical and novel case studies, covering topics from wildlife translocation to vaccine deployment. First, we revisited a classical model of canid territorial formation driven by scent-mediated conspecific avoidance. Transient space-use analysis uncovered previously hidden spatial dynamics that are ecologically informative. Next, we applied our approach to long-distance movement on realistic landscapes. Habitat and land-use heterogeneities markedly affected the transient space-use dynamics and short-term forecasts, even when the steady state remained unchanged, with direct implications for conservation management. Finally, we modeled transient space-use dynamics as both a response to and a driver of transient population dynamics. The importance of this interdependence was shown in the context of epidemiology, in a scenario where the movement of healthcare personnel is influenced by local outbreak conditions that are stochastically evolving.ConclusionsBy facilitating transient space-use analysis, our approach could lead to reevaluations of foundational ecological concepts such as home range and territory, replacing static with dynamic definitions that more accurately reflect biological realities. Furthermore, we contend that a growing interest in transient space-use dynamics, spurred by this work, could have transformative effects, stimulating new research avenues in ecology and epidemiology.

Multispectral drone images for the early detection of bark beetle infestations: assessment over large forest areas in the Italian South-Eastern Alps

IntroductionEuropean forests face increasing threats from climate change-induced stressors, which create favorable conditions for bark beetle outbreaks. The most critical spruce forest pest in Europe is the European Spruce Bark Beetle (Ips typographus L.). Effective forest management of this beetles’ outbreaks necessitates timely detection of recently attacked spruce trees, which is challenging given the difficulty in identifying symptoms on infested tree crowns, especially over large areas. This study assessed the detectability of infested trees over large spruce dominated areas (20–60 ha) using high-resolution drone multispectral imagery.MethodsA multispectral sensor mounted on an Unmanned Aerial Vehicle (UAV) was used to capture images of the investigated spruce stands weekly during June 2023. These were used to compute the reflectance of all single trees, derive vegetation indices, and then compare these between bark beetle infested trees and healthy ones.ResultsThe results showed that it was possible to separate the spectral features of recently infested trees from the healthy trees during the final developmental stage of the first beetles’ generation, despite the limitations due to difficulties in image processing over large areas. The best performing vegetation indices included NDRE (Normalized Difference Red Edge index) and GNDVI (Green Normalized Difference Vegetation Index), which allowed the earlier separation between infested and healthy trees.DiscussionThe study shows that the use of UAV high-resolution imagery can present some limitations when performing early detection over larger areas. The integration of sensors focused on narrower spectral windows around the Red-Edge and Green bands and other remote sensing methods (e.g., satellite imagery) could help overcome these limitations and improve early-detection over large forest areas. The proposed early-detection approach will increase the understanding of which factors to consider when performing early detection with remote sensing techniques. In particular, it will add insights when upscaling to larger spatial scales, providing useful guidance for the management of areas suffering pest outbreaks.

Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria

Cholera continues to pose a significant public health challenge in Nigeria, driven by poor sanitation, inadequate water quality, and climatic factors that create favorable conditions for outbreaks. Since the first epidemic in 1972, Nigeria has experienced recurrent outbreaks, with the most severe in 1991, resulting in over 7,000 deaths. Current surveillance systems and diagnostic methods are limited by infrastructural gaps, insufficient skilled personnel, and inadequate reporting, leading to delays in outbreak detection and response. These limitations exacerbate the public health burden, increasing mortality and the economic impact of cholera epidemics. This paper explores the potential of artificial intelligence (AI) and machine learning (ML) to address these challenges. AI technologies, including predictive modeling and ML algorithms such as random forests and convolutional neural networks (CNNs), can analyze diverse data sources—such as meteorological, environmental, and health records—to detect patterns and predict outbreaks. Case studies from other cholera-endemic regions, where AI achieved high predictive accuracy, demonstrate its transformative potential. By integrating AI into Nigeria’s public health infrastructure, early detection and response can be improved, resource allocation optimized, and disease transmission minimized. However, challenges such as data quality, standardization, and infrastructural deficits must be addressed. Multi-sectoral collaboration involving public health authorities, AI specialists, and policymakers is essential for the successful deployment of these technologies. This article concludes that AI-powered cholera surveillance systems have the potential to revolutionize public health outcomes, reducing cholera-related morbidity and mortality in resource-limited settings like Nigeria.

DESERTION AND THE FIGHT AGAINST IT IN THE TERRITORY OF THE MARI TERRITORY IN 1919–1920 (based on the materials of the State Archive of the Republic of Mari El)

Desertion, as an element of the Russian army’s disintegration at the beginning of the 20th century, was finally formed during the First World War. Lack of motivation, depressed morale and abandoned battlefield positions became the main reasons for Russia’s military and political failures at the final stage of the war. That is why, in the conditions of the Civil War outbreak in Russia, an important task for the new Soviet government was to strengthen discipline and revive the combat capability of the army. The fight against desertion was the key to preserve and establish the Soviet power on the ground, including in the Mari Territory. The purpose of the study is to study desertion as a phenomenon of the Civil War period in Russia in 1919–1920 in the Mari Territory, as well as to identify the main forms and methods of combating it. Materials and methods. The research used general scientific and special historical methods and approaches. When working with archival materials on the topic of desertion in the Mari Territory, a collection of documents that had not previously appeared in scientific circulation was formed. Research results. The authority responsible for the search and capture of deserters was the Central Commission for Combating Desertion. The Mari Territory in this matter fell under the jurisdiction of governorate commissions for combating desertion, located in the cities of Kazan and Vyatka. To carry out local tasks in each uyezd of the Mari Territory its own commission for combating desertion was formed under the uyezd military commissariat. They actively cooperated and carried out joint work with both the military commissariat and the uyezd commission for combating counterrevolution. Village councils were also supposed to provide active assistance.The Soviet government toughened penalties for desertion, but also used soft methods to combat this phenomenon. The study conclusions. During the Russian Civil War, six forms of combating desertion operated in the Mari Territory, all of them functioned together and formed a single integrated system to eradicate and prevent this kind of crime.

Disruptions to HIV Prevention During Armed Conflict in Ukraine and Other Settings.

This review evaluates recent literature to understand the ways in which war disrupts HIV prevention and creates conditions for HIV outbreaks, with a focus on Ukraine. We also examine potential responses that can be deployed to sustain HIV prevention services amid ongoing conflict. Recent studies and frameworks suggest that disruptions caused during war are comparable to other emergencies, like natural disasters. The most important disruptions included health system/infrastructure destabilization, displacement, and psychological and financial challenges for individuals in key populations. Wars in most settings, as exemplified by the recent war in Ukraine, demonstrate that these disruptions can be tempered through a coordinated, rapid response. Lesson learned from Ukraine show that adequate preparation and a rapid, collaborative response by providers is needed to ensure HIV prevention during war. Future research should develop comprehensive frameworks outlining how to facilitate this response.

Outbreak conditions and impacts of parasites in copepod populations

Abstract Although parasitism is vital for ecosystem dynamics and food webs, the population effects of parasitism in the marine pelagic have received little attention. Pelagic copepods link primary producers and higher consumers in marine food webs and host numerous parasites that may affect reproduction, behavior, and survival. We present a simple model consisting of uninfected hosts, infected hosts, and the free‐living parasite stage and use it to investigate population dynamics and outbreak conditions of this host–parasite system. The host population growth is limited by a carrying capacity determined by resource availability and stoichiometric constraints. We parameterized the model for 10 copepod species with different traits but with the same Blastodinium‐like parasite. We derived a threshold ratio for establishing infection, which showed that the parasite could invade and persist in all hosts. The ability of parasites to invade host populations largely depended on traits of free‐living spores and host density. From numerical analysis, we found that the parasite typically induced oscillations in the host population. Host traits were important for infection dynamics: High host growth rates mitigated some of the consequences of infection, and larger copepods were more susceptible to infection than smaller ones. The model implies that parasitism can impact the functional role of the copepod population in the ecosystem, and the system as a whole.

The Cumulative Effect of Wintertime Weather Systems on the Ocean Mixed‐Layer Stable Isotope Composition in the Iceland and Greenland Seas

Abstract The Iceland and Greenland Seas are characterized by strong heat fluxes from the ocean to the atmosphere during wintertime. Here we characterize the atmospheric signal of this strong evaporation in terms of water vapor isotopes and investigate if such a signal can have a cumulative imprint on the ocean mixed‐layer. Observations include continuous water vapor isotope measurements, event‐based precipitation samples, and sea‐water samples taken at various depths from the research vessel Alliance during the Iceland‐Greenland Seas Project cruise in February and March 2018. In conjunction with a simulation from a regional, isotope‐enabled atmospheric model, we find that the predominant atmospheric isotope signature during predominant marine cold‐air outbreak conditions is −129.8 ± 16.6‰ for δ2H and −18.10 ± 2.87‰ for δ18O, with a d‐excess of 15.1 ± 7.9‰, indicating enhanced non‐equilibrium fractionation compared to the global average. During events of warm‐air intrusion from mid‐latitudes, near‐surface vapor becomes saturated and the vapor d‐excess approaches equilibrium or becomes negative. Similarly, precipitation d‐excess is lower and thus closer to equilibrium conditions during warm‐air intrusions. There are indications that an evaporation signal of waters exiting the Nordic Seas through Denmark Strait could be locally enhanced over seasons to years, as supported by simple model calculations. Our findings thus suggest that evaporation signals could be transferred into the ocean isotope composition in this region, potentially enabling mass‐balance constraints in isotope‐enabled coupled ocean‐atmosphere models.

Dynamic spatial–temporal conflict quantification of construction machinery for pouring blocks in arch dams

PurposeThe spatial–temporal conflicts in the construction process of concrete arch dams are related to the construction quality and duration, especially for pouring blocks with a continuous high-strength and high-density construction process. Furthermore, the complicated construction technology and limited space resources aggravate the spatial–temporal conflicts in the process of space resource allocation and utilization, directly affecting the pouring quality and progress of concrete. To promote the high-strength, quality-preserving and rapid construction of dams and to clarify the explosion moment and influence degree of the spatial–temporal conflicts of construction machinery during the pouring process, a quantification method and algorithm for a “Conflict Bubble” (CB) between construction machines is proposed based on the “Time–Space Microelement” (TSM).Design/methodology/approachFirst, the concept of a CB is proposed, which is defined as the spatial overlap of different entities in the movement process. The subsidiary space of the entity is divided into three layered spaces: the physical space, safe space and efficiency space from the inside to the outside. Second, the processes of “creation,” “transition” and “disappearance” of the CB at different levels with the movement of the entity are defined as the evolution of the spatial–temporal state of the entity. The mapping relationship between the spatial variation and the running time of the layered space during the movement process is defined as “Time–Space” (TS), which is intended to be processed by a microelement.FindingsThe quantification method and algorithm of the CB between construction machinery are proposed based on the TSM, which realizes the quantification of the physical collision accident rate, security risk rate and efficiency loss rate of the construction machinery at any time point or time period. The risk rate of spatial–temporal conflicts in the construction process was calculated, and the outbreak condition of spatial–temporal conflict in the pouring process was simulated and rehearsed. The quantitative calculation results show that the physical collision accident rate, security risk rate and efficiency loss rate of construction machinery at any time point or time period can be quantified.Originality/valueThis study provides theoretical support for the quantitative evaluation and analysis of the spatial–temporal conflict risk in the pouring construction process. It also serves as a reference for the rational organization and scientific decision-making for pouring blocks and provides new ideas and methods for the safe and efficient construction and the scientific and refined management of dams.

The Legacy Effect of Mountain Pine Beetle Outbreaks on the Chemical and Anatomical Defences of Surviving Lodgepole Pine Trees.

The recent mountain pine beetle outbreaks have caused widespread mortality among lodgepole pine trees in western North America, resulting in a reduced population of surviving trees. While previous studies have focused on the cascading impacts of these outbreaks on the physiology and growth of the surviving trees, there remains a need for a comprehensive study into the interactions among various physiological traits and the growth in post-outbreak stands. Specifically, the relationship between chemical (primarily terpenes) and anatomical (mainly resin ducts) defences, as well as the allocation of non-structural carbohydrates (NSCs) to support these defence modalities, is poorly understood. To address these gaps, we conducted a field survey of surviving lodgepole pine trees in post-mountain pine beetle outbreak stands in western Canada. Our retrospective analysis aimed at determining correlations between the post-outbreak concentrations of monoterpenes, diterpenes, and NSCs in the phloem and the historical resin duct characteristics and growth traits before and after the outbreak. We detected strong correlations between the post-outbreak concentrations of monoterpenes and historical resin duct characteristics, suggesting a possible link between these two defence modalities. Additionally, we found a positive relationship between the NSCs and the total concentrations of monoterpenes and diterpenes, suggesting that NSCs likely influence the production of these terpenes in lodgepole pine. Furthermore, historical tree growth patterns showed strong positive correlations with many individual monoterpenes and diterpenes. Interestingly, while surviving trees had enhanced anatomical defences after the outbreak, their growth patterns did not vary before and after the outbreak conditions. The complexity of these relationships emphasizes the dynamics of post-outbreak stand dynamics and resource allocations in lodgepole pine forests, highlighting the need for further research. These findings contribute to a broader understanding of conifer defences and their coordinated responses to forest insect outbreaks, with implications for forest management and conservation strategies.

Biogeochemical conditions controlling the intensity of paralytic shellfish poisoning (PSP) outbreak caused by Alexandrium blooms: Results from 6-year field observations in Jinhae-Masan Bay, Korea

Biogeochemical conditions controlling the intensity of paralytic shellfish poisoning (PSP) outbreak caused by Alexandrium blooms: Results from 6-year field observations in Jinhae-Masan Bay, Korea

Multiple endemic equilibria in an environmentally-transmitted disease with three disease stages

Multiple endemic equilibria in an environmentally-transmitted disease with three disease stages

Drone-based early detection of bark beetle infested spruce trees differs in endemic and epidemic populations

IntroductionEuropean forests face increasing threats due to climate change-induced stressors, which create the perfect conditions for bark beetle outbreaks. The most important spruce forest pest in Europe is the European Spruce Bark Beetle (Ips typographus L.). Effective management of I. typographus outbreaks necessitates the timely detection of recently attacked spruce trees, which is challenging given the difficulty in spotting symptoms on infested tree crowns. Bark beetle population density is one of many factors that can affect infestation rate and symptoms development. This study compares the appearance of early symptoms in endemic and epidemic bark beetle populations using highresolution Unmanned Aerial Vehicles (UAV) multispectral imagery.MethodsIn spring of 2022, host colonization by bark beetles was induced on groups of spruce trees growing in 10 sites in the Southern Alps, characterized by different population density (5 epidemic and 5 endemic). A multispectral sensor mounted on a drone captured images once every 2 weeks, from May to August 2022. The analyses of a set of vegetational indices allowed the actual infested trees’ reflectance features and symptoms appearance to be observed at each site, comparing them with those of unattacked trees.ResultsResults show that high bark beetles population density triggers a more rapid and intense response regarding the emergence of symptoms. Infested trees were detected at least 1 month before symptoms became evident to the human eye (red phase) in epidemic sites, while this was not possible in endemic sites. Key performing vegetation indices included NDVI (Normalized Difference Vegetation Index), SAVI (Soil Adjust Vegetation Index, with a correction factor of 0.44), and NDRE (Normalized Difference Red Edge index).DiscussionThis early-detection approach could allow automatic diagnosis of bark beetles’ infestations and provide useful guidance for the management of areas suffering pest outbreaks.

Assessing dengue risk globally using non-Markovian models

Assessing dengue risk globally using non-Markovian models

Australian vertebrate hosts of Japanese encephalitis virus; a review of the evidence

Japanese Encephalitis Virus (JEV) transmission in temperate Australia has underscored a critical need to characterise transmission pathways and identify probable hosts of infection within the country. This systematic review consolidates existing research on the vertebrate hosts of JEV that are known to exist in Australia. Specifically, we aim to identify probable species for JEV transmission, their potential role as either a spillover or maintenance host and identify critical knowledge gaps. Data were extracted from studies involving experimental infection, seroprevalence, and virus isolation and were available for 22 vertebrate species known to reside in Australia. A host competence score was calculated to assess the potential for a given species to infect JEV vectors and to quantity their possible role in JEV transmission. Based on the host competence score and ecology of each species, we find ardeid birds, feral pigs, and flying foxes have potential as maintenance hosts for JEV in the Australian context. We also note that brushtail possums and domestic pigs have potential as spillover hosts under certain outbreak conditions. However, evidence to confirm these roles in localized transmission or outbreaks is sparse, emphasizing the need for further targeted research. This review provides a foundation for future investigations into JEV transmission in Australia, advocating for enhanced surveillance and standardized research methodologies to better understand and mitigate the virus’s impact.

Detecting changes in generation and serial intervals under varying pathogen biology, contact patterns and outbreak response.

The epidemiological characteristics of SARS-CoV-2 transmission have changed over the pandemic due to emergence of new variants. A decrease in the generation or serial intervals would imply a shortened transmission timescale and, hence, outbreak response measures would need to expand at a faster rate. However, there are challenges in measuring these intervals. Alongside epidemiological changes, factors like varying delays in outbreak response, social contact patterns, dependence on the growth phase of an outbreak, and effects of exposure to multiple infectors can also influence measured generation or serial intervals. To guide real-time interpretation of variant data, we simulated concurrent changes in the aforementioned factors and estimated the statistical power to detect a change in the generation and serial interval. We compared our findings to the reported decrease or lack thereof in the generation and serial intervals of different SARS-CoV-2 variants. Our study helps to clarify contradictory outbreak observations and informs the required sample sizes under certain outbreak conditions to ensure that future studies of generation and serial intervals are adequately powered.

A Two-Objective Model for the Multilevel Supply Chain of Blood Products with the Approach of Reducing the Rate of Contagion under the (COVID-19) Epidemic Outbreak Conditions

The conditions of the coronavirus epidemic have put much pressure on the healthcare system. This disease has hurt the blood supply through the reduction of blood donation and the reduction of access to suitable collection facilities due to dysfunction. Considering the importance of the subject, the purpose of this paper is to design a two-level supply chain network for blood products with the approach of reducing costs and the rate of contagion under the conditions of epidemic outbreaks (COVID-19). After examining the solution methods for multilevel supply chain networks of blood products under the conditions of the spread of the COVID-19 virus, three exact solution methods, including LP-metric, an improved version of the augmented ε-constraint (AUGMECON2), and an improved weighted Chebyshev, are proposed. They are used to solve the model in small dimensions. In order to compare the methods in the obtained solutions, several numerical examples of different sizes are generated and solved. Then, using the statistical assumption test, the obtained results are compared in all numerical examples by Tukey’s technique. Also, the TOPSIS is applied to select the best method. Finally, in order to investigate the reaction of the objectives to the changes in the contagion probability parameter, a sensitivity analysis has been performed. The results emphasize that improving the performance of the blood supply chain (BSC) can lead to a reduction in BSC costs and improved service to patients. Also, the adaptation of different components of the BSC and regular coordination between them play an efficient role in controlling and improving this disease and reducing the costs of the BSC. Also, receiving the plasma product of recovered people from type (II) donors can play a vital role in reducing the percentage of disease transmission.

Evidence of cross-channel dispersal into England of the forest pest Ips typographus

A breeding population of the tree-killing European spruce bark beetle Ips typographus was detected in England for the first time in 2018 and was initially assumed to have arrived with infested timber. To test the hypothesis that the beetles are dispersing naturally across the English channel, extensive trap networks were deployed in 2021 and 2022 to track the flight activity of the beetles from an outbreak hotspot in France and Belgium to southern England, including parallel ‘coastal’ traps on either side of the channel. Beetles were caught all along the transect, decreasing in abundance with distance from the outbreak area. Linear modelling indicates that beetles dispersed into England during 2021 and 2022, and that during a large-scale dispersal event in June 2021, beetles could have penetrated more than 160 km inland. The 2021 dispersal event initiated new incursions of the beetle in southeast England and demonstrates the extraordinary distance I. typographus may move under outbreak conditions. Our findings support the hypothesis of a damaging forest pest aerially dispersing across the barrier of the English channel and suggest that future incursions of this and other plant-associated pests may move via the same pathway.

Quantifying riming from airborne data during the HALO-(AC)3 campaign

Abstract. Riming is a key precipitation formation process in mixed-phase clouds which efficiently converts cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC)3 aircraft campaign, where two aircraft collected radar and in situ measurements that were closely spatially and temporally collocated over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse optimal estimation algorithm for the retrieval of the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments (combined method). The second method relies on in situ observations only, relating the normalized rime mass to optical particle shape measurements (in situ method). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.024 and 0.021 (mean values of 0.035 and 0.033) for the combined and in situ method, respectively. Assuming that particles with a normalized rime mass smaller than 0.01 are unrimed, we obtain average rimed fractions of 88 % and 87 % over all collocated flight segments. Although in situ measurement volumes are in the range of a few cubic centimeters and are therefore much smaller than the radar volume (about 45 m footprint diameter at an altitude of 500 m above ground, with a vertical resolution of 5 m), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We show the performance of the methods in a case study of a collocated segment of cold-air outbreak conditions and compare normalized rime mass results with meteorological and cloud parameters. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. The methods presented improve our ability to quantify riming from aircraft observations.