Older Adult Engagement With Symptom Reporting in a COVID-19 Citizen Science Application.

The current study examined the frequency and predictors of older adults' engagement with symptom reporting in COVIDWATCHER, a mobile health (mHealth) citizen science application. Citizen science is a type of participatory research that leverages information provided by community members. There were 1,028 COVIDWATCHER participants who engaged with symptom reporting between April 2020 and January 2021. Approximately 13.5% (n = 139) were adults aged ≥65 years. We used a Wilcoxon test to compare the mean frequency of engagement with symptom reporting by older adults (i.e., aged ≥65 years) to younger adults (i.e., aged ≤64 years) and multivariable linear regression to explore the predictors of engagement with symptom reporting. There was a significant difference in engagement with symptom reporting between adults aged ≥65 years compared to those aged ≤64 years (p < 0.001). In our final model, age (ß = 26.0; 95% confidence interval [14.8, 34.2]) was a significant predictor for engagement with symptom reporting. These results help further our understanding of older adult engagement with mHealth-enabled citizen science for symptom reporting. [Journal of Gerontological Nursing, 49(4), 6-11.].

Analysis and Acoustic Event Classification of Environmental Data Collected in a Citizen Science Project.

Citizen science can serve as a tool to obtain information about changes in the soundscape. One of the challenges of citizen science projects is the processing of data gathered by the citizens, to obtain conclusions. As part of the project Sons al Balcó, authors aim to study the soundscape in Catalonia during the lockdown due to the COVID-19 pandemic and afterwards and design a tool to automatically detect sound events as a first step to assess the quality of the soundscape. This paper details and compares the acoustic samples of the two collecting campaigns of the Sons al Balcó project. While the 2020 campaign obtained 365 videos, the 2021 campaign obtained 237. Later, a convolutional neural network is trained to automatically detect and classify acoustic events even if they occur simultaneously. Event based macro F1-score tops 50% for both campaigns for the most prevalent noise sources. However, results suggest that not all the categories are equally detected: the percentage of prevalence of an event in the dataset and its foregound-to-background ratio play a decisive role.

Active and healthy ageing in urban environments: laying the groundwork for solution-building through citizen science.

Urban age-friendly initiatives strive to promote active and healthy ageing by addressing urban influences that impact individuals as they age. Collaborative community partnerships with multi-level stakeholders are crucial for fostering age-friendly initiatives that can transform urban community health. Employing a citizen social science (CSS) approach, this study aimed to engage older adults and stakeholders in Birmingham, UK, to (i) identify key urban barriers and facilitators to active and healthy ageing, and (ii) facilitate collaboration and knowledge production to lay the groundwork for a citizen science project. Older adults (n = 16; mean age = 72(7.5 SD); 11 female) and community stakeholders (n = 11; 7 female) were engaged in six online group discussions, with audio recordings transcribed and thematically analysed to present key urban barrier and facilitator themes. Ageism, winter, technology and safety were barriers identified by both groups. Outdoor spaces and infrastructure, transportation, community facilities, and Covid-19 pandemic were identified as barriers and/or facilitators. Older adults identified the ageing process as a barrier and diversity of the city, health and mobility and technology as facilitators. For stakeholders, barriers were deprivation and poverty, gender differences, and ethnicity, whereas age-inclusive activities were a facilitator. Organic and active opportunities for older adults and stakeholders to connect, co-produce knowledge on urban environments and share resources presented foundations of solution-building and future collaboration. CSS effectively facilitated a range of stakeholders across local urban spaces to collaborate and co-produce ideas and solutions for enhancing local urban environments to promote active and healthy ageing.

Planning urban age-friendly environments requires engagement with local residents, service providers and decision-makers. This is important for developing joint actions, urban initiatives and allowing these individuals to share their experiences, needs and resources. Citizen social science (CSS) can engage residents and stakeholders to directly shape social research aiming to improve urban environments. This study engaged 16 older adults over the age of 60 and 11 stakeholders to identify urban features that influence active and healthy ageing in Birmingham, UK. Using six online discussion groups, the key urban barriers and facilitators were identified by older adults and stakeholders, who also checked the findings to confirm they represent the discussions accurately. Urban barriers and facilitators included health and mobility, ageism, outdoor spaces and infrastructure, transportation, technology, Covid-19, and the lack or presence of community facilities and activities. During discussion groups, both older adults and stakeholders connected to share information about local organizations, resources, websites for free activities or research, and provide solutions for each other's barriers. CSS effectively engaged older adults and stakeholders to collaborate and create knowledge together for improving local urban environments in Birmingham.

Improving Water Quality in the Short Beach Neighborhood of Branford, Connecticut, 2019-A Citizen Science Project.

We initiated a collaboration between local government, academia, and citizen scientists to investigate high frequencies of elevated Escherichia coli bacteria levels in the coastal Short Beach neighborhood of Branford, Connecticut. Citizen scientist involvement enabled collection of short-duration postprecipitation outfall flow water samples (mean E. coli level = 4930 most probable number per 100 mL) and yielded insights into scientific collaboration with local residents. A records review and sanitary questionnaire identified aging properties with septic systems (3.3%) and holding tanks (0.6%) as potential sources of the E. coli contamination. (Am J Public Health. 2022;112(9):1261-1264. https://doi.org/10.2105/AJPH.2022.306943).

The process evaluation of a citizen science approach to design and implement workplace health promotion programs.

BACKGROUND: Many workplace health promotion programs (WHPPs) do not reach blue-collar workers. To enhance the fit and reach, a Citizen Science (CS) approach was applied to co-create and implement WHPPs. This study aims to evaluate i) the process of this CS approach and ii) the resulting WHPPs. METHODS: The study was performed in two companies: a construction company and a container terminal company. Data were collected by questionnaires, interviews and logbooks. Using the framework of Nielsen and Randall, process measures were categorized in the intervention, context and mental models. Interviews were transcribed and thematically coded using MaxQDA software. RESULTS: The involvement in the CS approach and co-creating the WHPPs was positively experienced. Information provision, sustained engagement over time and alignment with the workplace's culture resulted in barriers in the CS process. As to the resulting WHPPs, involvement and interaction during the intervention sessions were particularly experienced in small groups. The reach was affected by the unfavorable planning off the WHPPs and external events of re-originations and the covid-19 pandemic. DISCUSSION: Continuous information provision and engagement over time, better alignment with the workplace's culture and favorable planning are considered to be important factors for facilitating involvement, reach and satisfaction of the workers in a Citizen science approach to design and implement a WHPP. Further studies continuously monitoring the process of WHPPs using the CS approach could be helpful to anticipate on external factors and increase the adaptability. CONCLUSIONS: Workers were satisfied with the involvement in WHPPs. Organizational and social cultural factors were barriers for the CS approach and its reach. Involvement and interaction in WHPPs were particularly experienced in small grouped sessions. Consequently, contextual and personal factors need be considered in the design and implementation of WHPPs with CS approach among blue-collar workers.

A call for citizen science in pandemic preparedness and response: beyond data collection.

The COVID-19 pandemic has underlined the need to partner with the community in pandemic preparedness and response in order to enable trust-building among stakeholders, which is key in pandemic management. Citizen science, defined here as a practice of public participation and collaboration in all aspects of scientific research to increase knowledge and build trust with governments and researchers, is a crucial approach to promoting community engagement. By harnessing the potential of digitally enabled citizen science, one could translate data into accessible, comprehensible and actionable outputs at the population level. The application of citizen science in health has grown over the years, but most of these approaches remain at the level of participatory data collection. This narrative review examines citizen science approaches in participatory data generation, modelling and visualisation, and calls for truly participatory and co-creation approaches across all domains of pandemic preparedness and response. Further research is needed to identify approaches that optimally generate short-term and long-term value for communities participating in population health. Feasible, sustainable and contextualised citizen science approaches that meaningfully engage affected communities for the long-term will need to be inclusive of all populations and their cultures, comprehensive of all domains, digitally enabled and viewed as a key component to allow trust-building among the stakeholders. The impact of COVID-19 on people's lives has created an opportune time to advance people's agency in science, particularly in pandemic preparedness and response.

Dramatic Lockdown Fossil Fuel CO2 Decrease Detected by Citizen Science-Supported Atmospheric Radiocarbon Observations.

COVID-19 lockdowns resulted in dramatic changes to fossil fuel CO2 emissions around the world, most prominently in the transportation sector. Yet travel restrictions also hampered observational data collection, making it difficult to evaluate emission changes as they occurred. To overcome this, we used a novel citizen science campaign to detect emission changes during lockdown and engage youth in climate science. Citizen scientists collected grass samples from their garden or local park, from which we analyzed the radiocarbon content to infer the recently added atmospheric fossil fuel CO2 mole fraction at each sampling location. The local fossil fuel CO2 mole fractions during lockdown were compared with a "normal" nonlockdown period. Our results from 17 sites in five cities around New Zealand demonstrate dramatic reductions in traffic emissions of 75 ± 3% during the most severe lockdown restriction period. This is consistent with sparse local traffic count information and a much larger decrease in traffic emissions than reported in global aggregate estimates of emission changes. Our results demonstrate that despite nationally consistent rules on travel during lockdown, emission changes varied by location, with inner-city sites typically dominated by bus traffic showing smaller decreases in emissions than elsewhere.

Citizen science reveals unexpected solute patterns in semiarid river networks.

Human modification of water and nutrient flows has resulted in widespread degradation of aquatic ecosystems. The resulting global water crisis causes millions of deaths and trillions of USD in economic damages annually. Semiarid regions have been disproportionately affected because of high relative water demand and pollution. Many proven water management strategies are not fully implemented, partially because of a lack of public engagement with freshwater ecosystems. In this context, we organized a large citizen science initiative to quantify nutrient status and cultivate connection in the semiarid watershed of Utah Lake (USA). Working with community members, we collected samples from ~200 locations throughout the 7,640 km2 watershed on a single day in the spring, summer, and fall of 2018. We calculated ecohydrological metrics for nutrients, major ions, and carbon. For most solutes, concentration and leverage (influence on flux) were highest in lowland reaches draining directly to the lake, coincident with urban and agricultural sources. Solute sources were relatively persistent through time for most parameters despite substantial hydrological variation. Carbon, nitrogen, and phosphorus species showed critical source area behavior, with 10-17% of the sites accounting for most of the flux. Unlike temperate watersheds, where spatial variability often decreases with watershed size, longitudinal variability showed an hourglass shape: high variability among headwaters, low variability in mid-order reaches, and high variability in tailwaters. This unexpected pattern was attributable to the distribution of human activity and hydrological complexity associated with return flows, losing river reaches, and diversions in the tailwaters. We conclude that participatory science has great potential to reveal ecohydrological patterns and rehabilitate individual and community relationships with local ecosystems. In this way, such projects represent an opportunity to both understand and improve water quality in diverse socioecological contexts.

Virtual Methodology for Household Waste Characterization During The Pandemic in An Urban District of Peru: Citizen Science for Waste Management.

The Covid-19 pandemic has caused the alteration of many aspects of the solid waste management chain, such as variations in the waste composition, generation and disposal. Various studies have examined these changes with analysis of integrated waste management strategies; qualitative studies on perceived variations and statistical evaluations based on waste collected or disposed in landfills. Despite this information there is a need for updated data on waste generation and composition, especially in developing countries. The objective of this article is to develop a data sampling and analytical approach for the collection of data on household waste generation and composition during the pandemic; and, in addition, estimate the daily generation of masks in the study area. The proposed methodology is based on the principles of citizen science and utilizes virtual tools to contact participants, and for the training and collection of information. The study participants collected the information, installed segregation bins in their homes and trained their relatives in waste segregation. The article presents the results of the application of the methodology in an urban district of Lima (Peru) in August 2020. The results suggest an apparent decrease in household waste per capita and a slight increase in plastics composition in the study area. It is estimated that each participant generates 0.124 masks per day and 0.085 pairs of gloves per day. The method developed and results presented can be used as a tool for public awareness and training on household waste characterization and segregation. Furthermore it can provide the necessary evidence to inform policy directives in response household waste issues and Covid-19 restrictions.

Using citizen science to identify environmental correlates of bird-window collisions in Poland.

Bird collisions with windows are among the highest sources of human caused mortality to this group of animals. However, environmental correlates of spatial patterns in collision risk are poorly understood, thus making mitigation measures difficult to implement. We took advantage of Covid-19 lockdown in the spring of 2020, when people were obligated to stay mainly at home, and performed a memory-recall questionnaire survey concerning bird-window collisions in Poland. We received information on bird-window collisions with 1800 buildings across the whole country accompanied by characteristics of each building, its vicinity and resident's behavior (time spent home, window cleaning). We supplemented these data with landscape description and performed statistical models to estimate importance of 13 explanatory variables as predictors of number of bird-window collisions. Reported number of collisions increased with the share of forests and arable land within 2 km of the building, and with proximity to rivers. Number of collisions also increased when single trees were close to buildings. More collisions were reported for houses than for flats and for new buildings than for old ones. Reported number of collisions increased with window cleaning which might suggest that cleaning reduces glass visibility for birds. As bird-window collision risk is highly variable among buildings but can be reduced with several measures improving glass visibility for birds, we recommend to use predictive models to identify collision hotspots for applying these measures. New houses located near rivers, in forests or agricultural landscapes have highest collision risk, and trees near buildings, often planted to benefit birds, can additionally elevate collision rate, thus potentially creating ecological traps. In such collision hotspots, reduction of window cleaning frequency can be considered as a mitigation measure unless the visual markers improving glass visibility for birds are installed on the panels.

Accessible data curation and analytics for international-scale citizen science datasets.

The Covid Symptom Study, a smartphone-based surveillance study on COVID-19 symptoms in the population, is an exemplar of big data citizen science. As of May 23rd, 2021, over 5 million participants have collectively logged over 360 million self-assessment reports since its introduction in March 2020. The success of the Covid Symptom Study creates significant technical challenges around effective data curation. The primary issue is scale. The size of the dataset means that it can no longer be readily processed using standard Python-based data analytics software such as Pandas on commodity hardware. Alternative technologies exist but carry a higher technical complexity and are less accessible to many researchers. We present ExeTera, a Python-based open source software package designed to provide Pandas-like data analytics on datasets that approach terabyte scales. We present its design and capabilities, and show how it is a critical component of a data curation pipeline that enables reproducible research across an international research group for the Covid Symptom Study.

Citizen science initiative points at childhood BCG vaccination as a risk factor for COVID-19.

Current results do not provide conclusive evidence on the effect of BCG vaccination on COVID-19 alone or in combination with other factors. To address this limitation, in this study we used a citizen science initiative on the COVID-19 pandemic to collect data worldwide during 2 October 2020-30 October 2020 (1,233 individuals) in a structured way for analysing factors and characteristics of affected individuals in relation to BCG vaccination. For the first time, the results of our study suggested that vaccination with BCG may increase the risk for COVID-19 at certain age, particularly in individuals vaccinated at childhood. Childhood BCG vaccination increased the likelihood of being diagnosed with COVID-19 fivefold in COVID-19 low-incidence countries and threefold in high-incidence countries. A reasonable explanation for this effect is the activation of certain innate immunity mechanisms associated with inflammatory reactions. These factors should be considered when analysing the risks associated with this global pandemic.

Citizen science: A way forward in tackling the plastic pollution crisis during and beyond the COVID-19 pandemic.

The COVID-19 pandemic has resulted in an unprecedented surge of production, consumption, and disposal of single-use plastics (SUPs) and personal protective equipment (PPE) by the public. This widespread use of mostly plastic items like face masks and disposable gloves has led to global reports of improper disposal of potentially infectious PPE both in our urban and natural environments. Due to international travel restrictions during the pandemic, many research programs targeted at measuring plastic pollution were halted. These disruptions to research programs have stunted the ability to assess the true quantities of SUPs and PPE being mismanaged from the waste stream into the environment. This article calls for increased citizen science participation in collecting plastic pollution data both during and post pandemic. By initiating this dialogue and raising attention to the importance and potential of citizen science data collection, data can be used to develop globally informed plastic pollution mitigation strategies.

Illness duration and symptom profile in symptomatic UK school-aged children tested for SARS-CoV-2.

BACKGROUND: In children, SARS-CoV-2 infection is usually asymptomatic or causes a mild illness of short duration. Persistent illness has been reported; however, its prevalence and characteristics are unclear. We aimed to determine illness duration and characteristics in symptomatic UK school-aged children tested for SARS-CoV-2 using data from the COVID Symptom Study, one of the largest UK citizen participatory epidemiological studies to date. METHODS: In this prospective cohort study, data from UK school-aged children (age 5-17 years) were reported by an adult proxy. Participants were voluntary, and used a mobile application (app) launched jointly by Zoe Limited and King's College London. Illness duration and symptom prevalence, duration, and burden were analysed for children testing positive for SARS-CoV-2 for whom illness duration could be determined, and were assessed overall and for younger (age 5-11 years) and older (age 12-17 years) groups. Children with longer than 1 week between symptomatic reports on the app were excluded from analysis. Data from symptomatic children testing negative for SARS-CoV-2, matched 1:1 for age, gender, and week of testing, were also assessed. FINDINGS: 258 790 children aged 5-17 years were reported by an adult proxy between March 24, 2020, and Feb 22, 2021, of whom 75 529 had valid test results for SARS-CoV-2. 1734 children (588 younger and 1146 older children) had a positive SARS-CoV-2 test result and calculable illness duration within the study timeframe (illness onset between Sept 1, 2020, and Jan 24, 2021). The most common symptoms were headache (1079 [62·2%] of 1734 children), and fatigue (954 [55·0%] of 1734 children). Median illness duration was 6 days (IQR 3-11) versus 3 days (2-7) in children testing negative, and was positively associated with age (Spearman's rank-order rs 0·19, p<0·0001). Median illness duration was longer for older children (7 days, IQR 3-12) than younger children (5 days, 2-9). 77 (4·4%) of 1734 children had illness duration of at least 28 days, more commonly in older than younger children (59 [5·1%] of 1146 older children vs 18 [3·1%] of 588 younger children; p=0·046). The commonest symptoms experienced by these children during the first 4 weeks of illness were fatigue (65 [84·4%] of 77), headache (60 [77·9%] of 77), and anosmia (60 [77·9%] of 77); however, after day 28 the symptom burden was low (median 2 symptoms, IQR 1-4) compared with the first week of illness (median 6 symptoms, 4-8). Only 25 (1·8%) of 1379 children experienced symptoms for at least 56 days. Few children (15 children, 0·9%) in the negatively tested cohort had symptoms for at least 28 days; however, these children experienced greater symptom burden throughout their illness (9 symptoms, IQR 7·7-11·0 vs 8, 6-9) and after day 28 (5 symptoms, IQR 1·5-6·5 vs 2, 1-4) than did children who tested positive for SARS-CoV-2. INTERPRETATION: Although COVID-19 in children is usually of short duration with low symptom burden, some children with COVID-19 experience prolonged illness duration. Reassuringly, symptom burden in these children did not increase with time, and most recovered by day 56. Some children who tested negative for SARS-CoV-2 also had persistent and burdensome illness. A holistic approach for all children with persistent illness during the pandemic is appropriate. FUNDING: Zoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation, and Alzheimer's Society.

First landscape-scale survey of the background level of COVID-19 face mask litter: Exploring the potential for citizen science data collection during a 'pollution pilgrimage' of walking a 250-km roadside transect.

The COVID-19 pandemic has generated a global problem through the cavalier or deliberate disposal of personal protective equipment (PPE) by the general public. This has raised concerns that the billions of discarded face masks pose a threat to wildlife through entanglement or, when broken down, through ingestion of derived microplastics. Previous quantitative surveys of the magnitude of such litter have focused on areas where people congregate, such as tourist beaches and large cities. The present survey is the first to provide data on the background level of face mask litter through a landscape of variable land-use. A 250-km transect along an historic road between Montreal and Quebec City (Canada) was surveyed during a walking pilgrimage, revealing an overall density of 0.0001 ± 0.00006 face masks m-2. Average densities were significantly higher in areas of human occupation compared to agricultural and forested rural land. However, there was no significant correlation between population size of communities and the number of face masks encountered, nor in litter extent and proximity to municipalities. This may be due to the confounding influence of inter-community differences in scheduled street cleaning operations. Seventy-six percent of face masks were of the disposable surgical variety, with the remaining 24% being reusable cloth masks. This, and the fact that only 10% of the former and none of the latter exhibited broken ear straps, insinuates that the litter could be due to accidental loss rather than inappropriate discarding by individuals en route. Scaling-up these findings in relation to the global road network generates a preliminary background estimate for roadside litter of >17 million face masks. The present study endorses the call made by others to engage citizen scientists in surveying PPE litter, in particular, the thousands who each year walk the medieval pilgrimage routes through the landscape of Europe.

Empowering grassroots innovation to accelerate biomedical research.

The purpose of biomedicine is to serve society, yet its hierarchical and closed structure excludes many citizens from the process of innovation. We propose a collection of reforms to better integrate citizens within the research community, reimagining biomedicine as more participatory, inclusive, and responsive to societal needs.

Digital Citizen Science for Responding to COVID-19 Crisis: Experiences from Iran.

The Coronavirus Disease 2019 (COVID-19) pandemic has so far been the most severe global public health emergency in this century. Generally, citizen science can provide a complement to authoritative scientific practices for responding to this highly complex biological threat and its adverse consequences. Several citizen science projects have been designed and operationalized for responding to COVID-19 in Iran since the infection began. However, these projects have mostly been overlooked in the existing literature on citizen science. This research sheds light on the most significant online citizen science projects to respond to the COVID-19 crisis in Iran. Furthermore, it highlights some of the opportunities and challenges associated with the strengths and weaknesses of these projects. Moreover, this study captures and discusses some considerable insights and lessons learned from the failures and successes of these projects and provides solutions to overcome some recognized challenges and weaknesses of these projects. The outcomes of this synthesis provide potentially helpful directions for current and future citizen science projects-particularly those aiming to respond to biological disasters such as the COVID-19 pandemic.

COVID-19 related poor mental health and sleep disorders in rheumatic patients: a citizen science project.

BACKGROUND: Patients with chronic rheumatic diseases (RDs) are more vulnerable and the containment measures related to the COVID-19 pandemic might have severe psychological consequences. We investigated the presence of and risk factors associated with poor mental health, sleep disorders among RDs during the pandemic. METHODS: This cross-sectional Italian citizen science project evaluated the psychological impact of the COVID-19 pandemic in patients with RDs. Between May and September 2020, eleven RD patients' associations sent the survey by using their mailing list and the related webpage and social network. 507 RD patients completed an ad-hoc anonymous online survey including the Perceived Stress Scale (PSS) and Impact Event Scale-Revised (IES-R). RESULTS: The mean scores on the PSS-10 and the IES-R were 18.1 and 29.7, respectively. Higher PSS scores were associated with younger age (p <  0.01), female gender (p <  0.01), overweight/obesity (p = 0.01), psychiatric pharmacotherapy (p <  0.01), and anxiety for loss of income (p <  0.01). Higher IES-R scores were associated with female gender (p <  0.01), intestinal diseases (p = 0.03), anxiety (p <  0.01), and health concern (p <  0.01). Among 375 patients with inflammatory arthritis, 246 (65.6%) had trouble staying asleep, 238 (63.5%) falling asleep, and 112 (29.9%) had dreams about the pandemic. Older age (OR = 1.038, CI 1.002-1.076), psychiatric pharmacotherapy (OR = 25.819, CI 11.465-58.143), and COVID infection (OR = 2.783, CI 1.215-6.372) were predictive of insomnia during the pandemic. CONCLUSIONS: A considerable COVID-19 related psychosocial burden has been detected in RDs. Different factors were predictive of poor mental health and sleep disorders in these patients. Focused supportive strategies should be implemented to improve the psychological well-being of fragile patients during pandemics.