Integrated quantitative evaluation framework of sustainable development – The complex case of the Yangtze River Delta

Sustainable development is central to the current societal functioning, whose complexity demands consideration on a regional scale. However, there are disparate methods to express sustainable development, many of which use qualitative analysis cumbersome for policy-makers. Previous studies focused on environmental, economic, and social impacts without fully considering the regulation mechanisms of the plethora of administrative bodies. To fill this research gap, this research establishes an integrated assessment framework involving four pillars: environment and ecology, society and culture, economics, and governance and policy. Further, indicator systems and quantitative analysis give comparable and objective results. The current study applied them to one of the most economically significant and developed Chinese regions, the Yangtze River Delta. The result shows a dynamic variation in regional sustainability from 2010 to 2019, indicating an annual increase. Although economic and societal development has been increasing steadily, environmental development has stagnated in the past two years, and the influencing policy has fluctuated dramatically. Our analysis was done in Shanghai, Jiangsu, Zhejiang, and Anhui. Even though all regions showed increasing sustainability, we observed an imbalance in regional sustainable development. Achieving a regional approach and enhanced regional coordination in the Yangtze River Delta is imperative and cannot be ignored by local, regional, and national policy-makers. More importantly, this study created a model capable of predicting the impact of the COVID-19 epidemic on regional sustainable development. The model showed that, compared with predicted values, a 6.65% decrease in the integrated sustainability index ensued, attributed to the pandemic in Zhejiang province. © 2022 Elsevier Ltd

A study on the changes in the ICT industry after the COVID-19 pandemic

Purpose: The aim of this paper is to explore the changes in the ICT and global value chains (GVCs) after the COVID-19 pandemic. Design/methodology/approach: This study compared the difference between Korea' domestic ICT industries, ICT imports and ICT exports before and after the COVID-19 outbreak by using trade data of ICT products and national economic indicators, and presents growth strategy for the ICT industry in the post-COVID 19 era. For this purpose, this study determined the causalities between Korea's imports/exports of ICT products and composite Indexes before and after COVID-19, and derived implications in the ICT industry environment after the COVID-19 pandemic. Findings: Analysis results showed the following changes in Korea's ICT industry in the post-COVID-19 world. (1) Non-face-to-face and contact-free technologies related sectors in the ICT industry, such as the semiconductor sector, have grown exponentially;(2) as the USA has grown as the new key player, the causal relationship with China, a key player of the GVC in the pre-COVID-19 era, disappeared;and (3) the GVC of the ICT industry is not a rigid one-way vertical structure, but is changing to a flexible structure influenced by cooperation and competition between countries. Originality/value: The results indicate that it is essential to constantly develop new ICT sectors that make use of non-face-to-face and contact-free technologies in the post-COVID-19 era, and the main strategies in response to the changed GVC would be taking the initiative by securing source technologies and expanding through cooperation with other GVCs and resource sharing. © 2022, Emerald Publishing Limited.

Organizational preparedness domains and indicators of educational organizations for students with disabilities in pandemic times: A scoping review

Background: The impact of the COVID-19 pandemic on educational systems has caused a profound shift in the organization and delivery of education worldwide. The effects of the pandemic crisis on educational systems proved to be detrimental for students with disabilities, highlighting not only the looming social and educational inequalities but also the huge gap in organizational preparedness for education, including identifying the main areas (domains) of preparedness that guide the process of organizational preparedness and the sub-themes (indicators) per domain that help educational organizations to evaluate their level of preparedness and to identify potential gaps and set priorities for preparedness planning. Methods: Scoping review with thematic analysis was performed on literature published from 2010 to 2022. Six scientific databases (PsycInfo, Web of Science, Eric, Scopus, Proquest, JSTOR) and one academic search engine (Google Scholar) were examined in order to identify publications (peer-reviewed and preprint) in English. The search strategy and robust eligibility criteria were defined by the authors, who also performed screening of the papers, eligibility decisions, and key data extractions. A thematic analysis was applied to define the organizational preparedness domains and indicators per domain, informed by a system thinking approach for educational organizations. Conflicts were collaboratively resolved after each step. All members of the research team were involved in the data synthesis. Results: From 1,564 publications identified, 216 were included in the final analysis. Six domains and 14 indicators were identified. Conclusion: The organizational preparedness in educational organizations in pandemic crisis times needs to be prioritized in the educational policy agenda, drawing special attention on students with disabilities. The identified preparedness domains and indicators may guide the policy dialogue and inform accordingly a system thinking change approach in education and disability. Copyright © 2023 Vlachou, Kalaitzi, Tsermidou, Toulia, Papazoglou, Fyssa and Papazis.

Diagnostic test property of transcription-reverse transcription concerted reaction reagent TRCReady® SARS-CoV-2 i using nasopharyngeal swab samples

TRCReady® SARS-CoV-2 i is a reagent for transcription-reverse transcription concerted reaction (TRC) to detect SARS-CoV-2 N2 gene, used with the automated rapid isothermal nucleic acid amplification test (NAAT) analyzer TRCReady®-80. Sensitivity and specificity of TRCReady® SARS-CoV-2 i was assessed by comparison with the results of real-time reverse transcription-polymerase chain reaction (RT-PCR) using nasopharyngeal swab samples. From November 2020 to March 2021, a total of 441 nasopharyngeal swabs were obtained and analyzed both with TRCReady® SARS-CoV-2 i and RT-PCR. Sensitivity and specificity of TRCReady® SARS-CoV-2 i were 94.6% (53/56) and 99.2% (382/385), respectively. Reaction time to positivity of TRCReady® SARS-CoV-2 i ranged from 1.166 to 9.805 (median: 2.887) min, and minimum detection sensitivity of TRCReady® SARS-CoV-2 i was 9 copies per test, with reaction time as 5.014 min. Detection of SARS-CoV-2 gene from nasopharyngeal swab sample using TRCReady® SARS-CoV-2 i shows comparative diagnostic test accuracy with RT-PCR, and can be used as a useful test to diagnose SARS-CoV-2 infection. © 2022 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases

Social vulnerability and COVID-19 in Maringá, Brazil

This research explores the relationship between COVID-19 and social vulnerability on an intra-urban scale. For this, two composite indicators of social vulnerability have been constructed. The composite indicator constructed by the Benefit-of-the-Doubt considers spatial heterogeneity. It weakly captures the conceptually most significant individual indicator of social vulnerability (R=-0.39), as it overestimates the above-average performance sub-indicators. The composite indicator constructed by the Principal Component Analysis considers that the sub-indicators have the same weights in different census tracts, resulting in a highly consistent composite indicator as a multidimensional phenomenon concept (R=-0.93). These findings allow reaching four conclusions. First, the direction and strength of correlations associated with COVID-19 are sensitive to the method employed to construct the composite indicator and not just the geographic scale and space. Second, Medium and High social vulnerability census tracts concentrate 97% of the population but only 93% of COVID-19 cases and deaths. Third, people living in census tracts of None and Low social vulnerability are 3.87 and 2.13 times more likely to be infected or die from COVID-19. Fourth, policies to combat COVID-19 in the study area should prioritize older populations regardless of their social conditions. © 2022, The Author(s), under exclusive licence to Korean Spatial Information Society.

Arrival flight efficiency in pre- and post-Covid-19 pandemics

Covid-19 pandemic affected aviation severely, resulting in unprecedented reduction of air traffic. While aviation is slowly re-gaining traffic volumes, we use the opportunity to study the arrival performance in the Terminal Maneuvering Area (TMA) in non-congested scenarios. Applying flight efficiency and environmental performance indicators (PIs) to the historical data of arrivals to Stockholm Arlanda and Gothenburg Landvetter airports, we discover noticeable inefficiencies, despite significant reduction of traffic intensity. We analyze the impact of such factors as weather and traffic intensity on arrival efficiency in isolated scenarios when only one factor dominates: isolated scenario with low traffic and isolated scenario with good weather conditions. Our analysis uncovers that weather has a stronger influence than traffic intensity on the vertical efficiency, while traffic intensity has stronger effect on the lateral efficiency. Impact of traffic intensity on the lateral efficiency might be explained by frequent hold-on patterns and flight trajectory extensions due to vectoring in high traffic conditions. Further investigation is needed to explain weather and vertical/lateral efficiency correlations, the conclusions might be country-specific.

Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics

This paper investigates the impact of COVID-19 on financial markets. It focuses on the evolution of the market efficiency, using two efficiency indicators: the Hurst exponent and the memory parameter of a fractional Lévy-stable motion. The second approach combines, in the same model of dynamic, an alpha-stable distribution and a dependence structure between price returns. We provide a dynamic estimation method for the two efficiency indicators. This method introduces a free parameter, the discount factor, which we select so as to get the best alpha-stable density forecasts for observed price returns. The application to stock indices during the COVID-19 crisis shows a strong loss of efficiency for US indices. On the opposite, Asian and Australian indices seem less affected and the inefficiency of these markets during the COVID-19 crisis is even questionable. © 2022 Elsevier B.V.

The Impact of the COVID-19 Pandemic on Makkah City's Health Programs Performance

Background: Coronavirus (Covid-19) is a viral illness caused by a recently discovered coronavirus that began in the Chinese city of Wuhan in December 2019.(1). The impact of this global pandemic affects all social, psychological, and economic aspects of society, and health(1,2). The aim of the Saudi preventive health programs for Community health services was to increase awareness and decrease preventable diseases. This study aimed to assess the impact of the COVID-19 pandemic on key performance indicators of health programs at Makkah Al-Mukarramah City. Material and Methods: This comparative descriptive study was conducted to assess health programs' key performance indicators and statistics before COVID19 in 2019, in comparison with 2020 and 2021. KPI and statistics of health programs collected the data including that on chronic diseases Preventive programs, age categories and healthy life programs.

Associations between anthropometric indicators and refraction in school-age children during the post-COVID-19 era.

Purpose: To explore the associations between anthropometric indicators and refraction in school-aged children in the post-COVID-19 era. Methods: Data were collected from 25,644 children aged 7 to 12 years in 48 elementary schools in Tianjin. The comprehensive examination included height, weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), refraction, and calculation of BMI, with a follow-up visit after 6 months. Myopia was defined as spherical equivalent refraction (SER) ≤-0.50 diopter (D). Bivariate correlation coefficients and multiple linear regression models were used to explore the cross-sectional and longitudinal associations between anthropometric indicators (height, weight, BMI, SBP, and DBP) and refraction. Results: The mean changes in height, weight, BMI, SBP, DBP, and SER of the participants were 4.03 ± 2.18 cm, 3.10 ± 2.39 kg, 0.45 ± 1.16 kg/m2, 2.26 ± 14.74 mmHg, 2.18 ± 11.79 mmHg and -0.17 ± 0.51 D, respectively. Overall, height, weight, BMI, SBP, and DBP were all correlated with SER (r = -0.324, r = -0.234, r = -0.121, r = -0.112, r = -0.066, both p < 0.001), and changes in height and weight were correlated with changes in SER (r = -0.034, -0.031, both p < 0.001). Furthermore, multiple linear regression analysis revealed that the association of BMI, SBP, and DBP with SER was significant in myopic children but not in non-myopic children. The association between changes in weight and changes in SER was only present in non-myopic children but not in myopic children. Conclusion: Height and weight were negatively correlated with SER in both cross-sectional analysis and longitudinal changes, indicating that children's height, weight and growth rate may be used as a reference indicator for myopia risk prediction and myopia progression monitoring.

Vaccination coverage in children in the period before and during the COVID-19 pandemic in Brazil: a time series analysis and literature review.

OBJECTIVE: To evaluate the behavior of VCR and VCH, per municipality and per vaccines offered at the NVC, to identify priority areas for intervention. METHODS: Descriptive study of a time series, using secondary data and accompanied by a narrative review of the literature evaluating VCR and VCH. Vaccines offered to children under one year and to those aged one year in the pre-pandemic period of COVID-19 (2015 to 2019) were selected and compared to those offered during the pandemic period (2020 and 2021). RESULTS AND DISCUSSIONS: The decrease in VCR and VCH is a process that precedes the COVID-19 pandemic but was intensified during this period. In 2021, the VCR was around 70% for most vaccines. This phenomenon encompasses the entire country; however, it is more intense in the states/municipalities located in the north and northeast regions, suggesting greater difficulty in accessing health services. CONCLUSIONS: Low and heterogeneous VCR requires the adoption of practices that were previously implemented, establishing partnerships with governmental and non-governmental institutions, with adequate communication, active search for non-compliance and non-adherence to the regular vaccination program, adopting intra- and extramural vaccination strategies, to reverse the current situation and reduce the risk of recurrence of diseases that have been already controlled and eliminated.

Modeling local coronavirus outbreaks.

This article presents an overview of methods developed for the modeling and control of local coronavirus outbreaks. The article reviews early transmission dynamics featuring exponential growth in infections, and links this to a renewal epidemic model where the current incidence of infection depends upon the expected value of incidence randomly lagged into the past. This leads directly to simple formulas for the fraction of the population infected in an unmitigated outbreak, and reveals herd immunity as the solution to an optimization problem. The model also leads to direct and easy-to-understand formulas for aligning observable epidemic indicators such as cases, hospitalizations and deaths with the unobservable incidence of infection, and as a byproduct leads to a simple first-order approach for estimating the effective reproduction number R t . The model also leads naturally to direct assessments of the effectiveness of isolation in preventing the spread of infection. This is illustrated with application to repeat asymptomatic screening programs of the sort utilized by universities, sports teams and businesses to prevent the spread of infection.

[Quality analysis of a combined domestic vaccine for the prevention of measles, rubella and mumps].

INTRODUCTION: The need to maintain a high level of vaccination coverage against measles, rubella and mumps in conditions of an increased risk of outbreaks of infections due to violations of vaccination tactics associated with the pandemic of coronavirus infection and due to the unfavorable epidemic situation in neighboring countries determines the advisability of using a combined vaccine for the simultaneous prevention of these three socially significant infections. THE AIM OF THE STUDY: to analyze the quality of commercial series of a new domestic combined cultured live vaccine against measles, rubella and mumps (MRM) throughout the entire time of its manufacturing according to all specification indicators in regulatory documentation (RD). MATERIALS AND METHODS: The object of the study was the combined cultured live vaccine against measles, rubella and mumps. The analysis of the quality of the drug was carried out according to 86 consolidated production protocols of manufactured series, as well as according to the results of control of these series in the Testing Center for Quality Expertise of the Federal State Budgetary Institution NCESMP of the Ministry of Health of the Russian Federation. RESULTS: It is shown that the quality of the combined drug for the prevention of measles, rubella and mumps corresponds to the RD in all studied indicators. The drug does not contain an antibiotic. Bovine serum albumin, which is a technological impurity, is detected in quantities more than 5 times lower than the established norm. A comparison of the specific activity of the viral components of new combined domestic vaccine and the components of the bivalent vaccine against measles and mumps produced by the company in 20192021 showed that the spread of the activity values of the viral components in the new drug and in the series of mumps-measles vaccine was minimal, which allowed us to make a conclusion about the stability of the production technology. CONCLUSION: The quality of the new domestic combined vaccine for the prevention of measles, rubella and mumps meets WHO requirements. The results of the conducted studies indicate the stability of production and the standard quality of the drug. The use of a combined vaccine against three significant infections will ensure the necessary level of vaccination coverage in the population. Information about the results of studies can help reduce the number of vaccination refusal.

Selection of Pediatric Mental Health Quality Measures for Health System Improvement in British Columbia Based on a Modified Delphi Approach.

Background: The COVID-19 pandemic has highlighted the importance of mental wellbeing. The identification and implementation of quality measures can improve health outcomes and patient experience. The objective was to identify and define a core set of valid and relevant pediatric mental health quality measures that will support health system evaluation and quality improvement in British Columbia, Canada. Methods: The study consisted of four phases. First, a comprehensive database search identified valid pediatric quality measures focused on mental health and substance use (MH/SU). Second, the identified quality measures were mapped to focus areas, which were then prioritized by two stakeholder groups consisting of 26 members. Third, up to two representative measures for each prioritized focus area were pre-selected by an expert panel (n = 9). And fourth, a three-step modified Delphi approach was employed to (1) assess each quality measure on a 7-point Likert scale against three relevance criteria (representative of a quality problem, value to intended audience and actionable), (2) discuss the results, and (3) select and rank the most relevant measures. Forty-eight stakeholders were invited to participate; of those 24 completed the round 1 survey, 21 participated in the round 2 discussion and 18 voted in the round 3 selection and ranking survey. For round 1, consensus was determined when at least 70% of the response rates were within the range of five to seven. For round 3, Kendall's coefficient of concordance W was used as an estimator of inter-rater reliability. Results: One-hundred pediatric mental health quality measures were identified in the database search. Of those, 37 were mapped to ten focus areas. Pre-selection resulted in 19 representative measures moving forward to the Delphi study. Eleven measures met the consensus thresholds and were brought forward to the round 2 discussion. Round 3 ranking showed moderate to strong raters' agreement (Kendall's W = 0.595; p < 0.01) and resulted in the following five highest-ranked measures: level of satisfaction after discharge from inpatient admission due to MH/SU, number of patients experiencing seclusion or restraint, length of time from eating disorder referral to assessment, number of ED visits due to MH/SU, and number of readmissions to ED. Conclusion: The selected core set of valid and relevant pediatric quality measures will support sustainable system change in British Columbia. The five top-ranked measures will be refined and tested for data collection feasibility before being implemented in the province.

A New Dimension of Health Sustainability Model after Pandemic Crisis Using Structural Equation Model

Since the coronavirus (COVID-19) pandemic, it has been clear that the health dimension (HEDm) has a severe impact on sustainability, which was originally considered from the pillars of society, environment and economy. Hence, the integration of the health dimension into the other three pillars is plausible to define guidelines and criteria for progress monitoring and policy assessment towards a health-sustainable city. The objective of this study aims to present The Health Sustainability Model (HSM), a four-dimensional model for health sustainability (health, economy, environment, and society), using the Del-phi method to determine potential indicators agreed by eighteen experts, including physicians who deeply understand issues on health sustainability, and assess complex dimensions of health in the context of sustainability. The researchers have found that 45 indicators, later grouped into 15 elements and 4 dimensions, have a high level of agreement with Kendall's W (KW) at 0.36. The HSM was then examined by the structural equation model (SEM) with reliability and validity shown as follows: the absolute fit with CMIN/DF = 1.44, RMSEA = 0.033, GFI = 0.96, AGFI = 0.94, RMR = 0.025, and the incremental fit with NFI = 0.94, CFI = 0.98, TLI = 0.97, and IFI = 0.98. Based on the results, the model is valid, in line with the empirical data. For further application, the HSM is expected to support city planners and decision makers by identifying room for improvement in each dimension through the indicators employed in the model. In contrast to existing studies that mainly use qualitative data, by conducting quantitative assessment, the model enables policy makers to objectively evaluate conditions and appropriately design policies to improve residents' well-being.

Forecasting Spanish economic activity in times of COVID-19 by means of the RT-LEI and machine learning techniques

The main aim of this paper is to analyse and estimate the behaviour of the Spanish economic activity in the next 12 months, by means of a Real-Time Leading Economic Indicator (RT-LEI), based on Google Trends, and the real GDP. We apply methodologies based on fractional integration and cointegration to measure the degree of persistence and to examine the long-term relationship. Finally, we carry out a forecast using a Machine Learning model based on an Artificial Neural Network. Our results indicate that the Spanish economy will experience a contraction in 1Q-21 and will require strong measures to reverse the situation and recover the original trend.

Driving Financial Inclusion: Technology as an Indicator of Financial Ecosystem Development During the COVID-19 Pandemic in India

This paper examines India's level of digital access to financial services as compared to other Asian countries. The study also intends to analyse whether COVID-19 has influenced the usage trend of the selected digital payment indicators in India. Data has been collected from the World Bank Global Findex Database and RBI bulletins. Cross country descriptive analysis was used for studying India's digital financial access against the other Asian countries. Event study methodology followed by trend analysis was employed to examine whether COVID-19 has impacted the digital payment indicators' usage in India. The findings of the study indicated that India's position in digital financial access needs to be improved. It was further identified that COVID-19 has increased the usage of digital modes for financial transactions in India. There has been a significant increase in the usage volume of mobile banking after the declaration of the pandemic. Govt. can frame its action plans to make use of the opportunity created through the pandemic to improve digital financial access in India.

Before and after COVID-19: An examination of social indicators of mental health in early childhood education teachers

The current study aimed to identify individual- and environmental-level social indicators of mental health for Washington State early childhood education (ECE) teachers before and at the onset of the COVID-19 pandemic. Using survey data collected in Fall 2019 and April 2020 from the Washington State ECE Workforce Survey Study (N = 1156), I examined whether ECE teachers' socio-demographic, professional, and work environment characteristics were predictive of ECE teachers' depression scores before the pandemic in Fall 2019. In addition, I also examined whether COVID-19 stressors were predictive of change in depression scores in ECE teachers at the onset of the pandemic, after controlling for pre-pandemic depression levels and other individual- and work environment-level characteristics. When looking at social indicators of mental health before the pandemic, regression model results showed that ECE teachers' age, self-identification as Latinx, weekly work hours, teachers' students' age group, job demands, and job support were each uniquely predictive of depression scores. Specifically, weekly work hours, working with infants and toddlers, and job demands were predictive of increased depression, and teachers' age, self-identification as Latinx, and job support were predictive of decreased depression. In the second regression model, results showed a significant mean increase in depression scores from Fall 2019 to onset of the pandemic in April 2020, indicating a change from mild to more pervasive symptoms of depression in ECE teachers. Further, the model results revealed that ECE teachers' pre-COVID depression scores, age, self-identification as Asian, and other minority racial groups, such as Native American, Middle Eastern, Pacific Islander, and biracial, and job demands, and income worry were predictive of change in depression scores, with income worry being one of the strongest predictors. Specifically, job demands before COVID and income worry were predictive of more change in depression scores (indicating more depression symptoms), and pre-COVID depression scores, self-identification as Asian, Native American, Middle Eastern, Pacific Islander, and biracial were predictive of less change in depression scores, indicating a little less increase in depression scores compared to teachers with higher depression scores before the pandemic and White teachers. Implications of these findings on the ECE teacher workforce, as well as recommendations for policy and practice, are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Overview of the current situation relating to chemical engineering degree courses

In 2020, the Conference of Chemical Engineering Directors and Deans (CODDIQ) proposed the creation of an observatory to monitor chemical engineering degrees in Spain. This representative radiography of Chemical Engineering studies offers an initial point to observe the future changes when Royal Decree 822/2021 and proposed challenges in the last Ministerial Conference on the European Higher Education Area (EHEA) will be implanted. The survey data from CODDIQ partners allow us to know important data such as (i) the 24 international quality accreditations at Spanish universities, (ii) the high demand and the required marks, an average of 7.25, for the Chemical Engineering Bachelor's degree, (iii) 9560 undergraduate students in this degree in Spain and their gender profile which is around 43% of women, similar than women lectures, (iv) the difficulty of this Bachelor's degree through some indicators like duration of studies (5.25 years), graduation rate (41%) and drop-out rate (26%), (v) the employability after obtaining the Bachelor's degree is very high (>70%). In addition, Chemical engineering undergraduate and graduate students indicate their expectations are covered. In this paper, some consequences of the pandemic on students' performance (lower than before COVID-19) are analyzed, despite lectures tried to innovate in their classes and the university provided adequate tools for online teaching.

The Effect of the Coronavirus Pandemic on the Prediction Accuracy of Stock Price

In late 2019, the coronavirus began to spread around the world and impact international politics and economies significantly. In the face of the pandemic, stock markets around the world fluctuated sharply. The study aims to investigate the impact of the pandemic on the predictive variables of a stock prediction model, formed using chip-based variables and sentiment variables derived from comments posted on a social media platform. This study first performs feature engineering analysis to identify the indicators suitable for constructing the prediction model. The analysis then establishes a set of phrase rules to assign sentiment scores to the opinions expressed in replies and evaluates the effect on the accuracy of predictions. The results show that the major chip-based indicators affecting changes in the stock market differ before and after the pandemic. Hence, prediction models should be established separately for analysis in either period. In addition, the results indicate that the model relying on reply-based sentiment scores as a predictive variable provides more accurate predictions of stock price change.

An Iterative, Participatory Approach to Developing a Neighborhood-Level Indicator System of Health and Wellbeing.

Despite increased awareness of the essential role of neighborhood characteristics for residents' health and wellbeing, the development of neighborhood-level indicator systems has received relatively little attention to date. To address this gap, we describe the participatory development process of a small-area indicator system that includes information on local health needs in a pilot neighborhood in the German city of Mannheim. To identify relevant indicators, we partnered with representatives of the city's public health department and used an iterative approach that included multiple Plan-Do-Check-Act cycles with ongoing feedback from local key stakeholders. The described process resulted in a web-based indicator system with a total of 86 indicators. Additionally, 123 indicators were perceived as relevant by stakeholders but could not be included due to data unavailability. Overall, stakeholders evaluated the participatory approach as useful. Even though the onset of the COVID-19 pandemic and the lack of some data elements hindered instrument development, close collaboration with public health partners facilitated the process. To identify and target sub-national health inequalities, we encourage local public health stakeholders to develop meaningful and useful neighborhood-level indicator systems, building on our experiences from the applied development process and considering identified barriers and facilitators.