BACKGROUND: The COVID-19 pandemic is still a public health concern in South Sudan having caused suffering since the first case of COVID-19 was introduced on 28th February 2020. COVAX vaccines have since been introduced using a number of strategies including fixed site, temporary mobile, hit and run in flooded and conflict affected areas. We aim to describe the 2 ICVOPT campaigns that were conducted to improve the uptake and document lessons learnt during the initial rollout of the COVID-19 vaccination programin South Sudan between February 2022 and June 2022 each lasting for 7-days.
METHODS: We conducted an operational cross-sectional descriptive epidemiological study of a series of the intensified COVID-19 vaccination Optimization (ICVOPT) campaigns from February 2022 to June 2022. Before the campaign, a bottom up micro-planning was conducted, validated by the County Health Departments (CHDs) and national MOH team. Each of the 2 campaigns lasted for 7 days targeting 30% of the eligible unvaccinated target population who were18 years and above. Each team consisted of 2 vaccinators, 2 recorders and 1 mobilizer. The teams employed both fixed site, temporary mobile, hit and run in flooded and conflict affected areas. The number of teams were calculated based on the daily workload per day (80 persons per team/day) for the duration of the campaigns.
RESULTS: A total of 444,030 individuals were vaccinated with primary series COVID-19 vaccine (J&J) out of the targeted 635,030 persons. This represented 69.9% of target population in the selected 28 counties and 10 states of South Sudan in 7 days\' ICVOPT campaigns. More eligible persons were reached in 7 days campaigns than the 9 months of rollout of the COVID-19 vaccine prior to ICVOPT campaigns using the fixed site strategy at the health facility posts.
CONCLUSIONS: Intensified COVID-19 vaccination Optimization (ICVOPT) campaigns were vital and fast in scaling up vaccination coverages as compared to the fixed site vaccination strategies (2022 progress report on the Global Action Plan for Healthy Lives and Well-being for All Stronger collaboration for an equitable and resilient recovery towards the health-related Sustainable Development Goals, incentivizing collaboration, 2022) in complex humanitarian emergency settings and hard-to-reach areas of South Sudan.

The COVID-19 pandemic has had serious adverse impacts on public transport service providers. Most public transport lines exhibit reduced ridership levels while, at the same time, some of them may exhibit passenger demand levels beyond the pandemic-imposed capacity limitations. This study models the problem of bus dispatching time optimization within a periodic rolling horizon optimization framework that reacts to travel time and passenger demand variations. This model allows public transport service providers to adjust their bus schedules periodically to avoid in-vehicle crowding beyond the pandemic-imposed capacity limit. The proposed model is a mixed-integer linear program that considers the possible changes to vehicle schedules and tries to minimize the number of vehicles required to perform the service while adhering to the COVID-19 capacity restrictions. Case study results from the implementation of our model on bus Line 2 in the Twente region in the Netherlands are provided demonstrating the potential gains when rescheduling the trip dispatching times and vehicle schedules.

Urban greenhouse gas emissions monitoring is essential to assessing the impact of climate mitigation actions. Using atmospheric continuous measurements of air quality and carbon dioxide (CO2), we developed a gradient-descent optimization system to estimate emissions of the city of Paris. We evaluated our joint CO2-CO-NOx optimization over the first SARS-CoV-2 related lockdown period, resulting in a decrease in emissions by 40% for NOx and 30% for CO2, in agreement with preliminary estimates using bottom-up activity data yet lower than the decrease estimates from Bayesian atmospheric inversions (50%). Before evaluating the model, we first provide an in-depth analysis of three emission data sets. A general agreement in the totals is observed over the region surrounding Paris (known as Île-de-France) since all the data sets are constrained by the reported national and regional totals. However, the data sets show disagreements in their sector distributions as well as in the interspecies ratios. The seasonality also shows disagreements among emission products related to nonindustrial stationary combustion (residential and tertiary combustion). The results presented in this paper show that a multispecies approach has the potential to provide sectoral information to monitor CO2 emissions over urban areas enabled by the deployment of collocated atmospheric greenhouse gases and air quality monitoring stations.

Longitudinal cohort studies are critical for understanding the evolution of health-influencing behaviors, such as e-cigarette use, over time. Optimizing follow-up rates in longitudinal studies is necessary for ensuring high-quality data with sufficient power for analyses. However, achieving high rates of follow-up in web-based longitudinal studies can be challenging, even when monetary incentives are provided.
This study compares participant progress through a survey and demographics for 2 incentive structures (conditional and hybrid unconditional-conditional) among US adults using e-cigarettes to understand the optimal incentive structure.
The data used in this study are from a web-based longitudinal cohort study (wave 4; July to September 2022) of US adults (aged 21 years or older) who use e-cigarettes ≥5 days per week. Participants (N=1804) invited to the follow-up survey (median completion time=16 minutes) were randomly assigned into 1 of 2 incentive structure groups (n=902 each): (1) conditional (US $30 gift code upon survey completion) and (2) hybrid unconditional-conditional (US $15 gift code prior to survey completion and US $15 gift code upon survey completion). Chi-square tests assessed group differences in participant progress through 5 sequential stages of the survey (started survey, completed screener, deemed eligible, completed survey, and deemed valid) and demographics.
Of the 902 participants invited to the follow-up survey in each group, a higher proportion of those in the conditional (662/902, 73.4%) than the hybrid (565/902, 62.6%) group started the survey (P<.001). Of those who started the survey, 643 (97.1%) participants in the conditional group and 548 (97%) participants in the hybrid group completed the screener (P=.89), which was used each wave to ensure participants remained eligible. Of those who completed the screener, 555 (86.3%) participants in the conditional group and 446 (81.4%) participants in the hybrid group were deemed eligible for the survey (P=.02). Of those eligible, 514 (92.6%) participants from the conditional group and 401 (89.9%) participants from the hybrid group completed the survey and were deemed valid after data review (P=.14). Overall, more valid completions were yielded from the conditional (514/902, 57%) than the hybrid group (401/902, 44.5%; P<.001). Among those who validly completed the survey, no significant differences were found by group for gender, income, race, ethnicity, region, e-cigarette use frequency, past 30-day cigarette use, or number of waves previously completed.
Providing a US $30 gift code upon survey completion yielded higher rates of survey starts and completions than providing a US $15 gift code both before and after survey completion. These 2 methods yielded participants with similar demographics, suggesting that one approach is not superior in obtaining a balanced sample. Based on this case study, future web-based surveys examining US adults using e-cigarettes could consider providing the full incentive upon completion of the survey.
RR2-10.2196/38732.

Protecting and increasing linear landscape elements (LLEs) in agricultural lands is regarded as a possible solution for a transition to a more biodiverse agricultural system. However, optimizing the spatial configuration of LLEs protected areas is challenging, especially given the demand for land for food production. Systematic Conservation Planning (SCP) can address this challenge, by prioritizing cost-efficient protection areas. We used a SCP approach to look at the LLEs network in the Province of Noord-Brabant in the Netherlands, identifying the possible trade-off between optimizing species conservation, costs and the monetary values of ecosystem services (ES). For this we defined two scenarios. One scenario focuses on achieving species conservation targets at the minimum cost, and the other focuses on achieving targets while maximizing the benefits provided by ES. For each scenario, we further developed two land-management options, namely land-sharing and land-sparing. For each solution, we tested their cost-effectiveness by calculating implementation costs, economic benefits provided by ES, and cost/benefit ratios. First, our scenario analysis indicates that the economic benefits provided by ES always outweigh the implementation costs. Second, it shows that including ES as co-benefits in SCP (Maximize ES Scenario) yields more cost-efficient conservation solutions. Third, both land-sharing and land-sparing are possible cost-efficient approaches to achieve conservation targets. Our results are spatially explicit and identify crucial habitat areas for the conservation of the selected species, which represent 12-20% of the current unprotected network of LLEs. Our findings showcase net economic benefit of conserving species and LLEs, thus representing an additional reason for biodiversity conservation.

Waste facilities siting is one of the complex problems encountered by decision makers of waste management in urban developing areas. Waste to Energy (WtE) facilities siting alongside transfer stations involves a Multi-Criteria Decision Analysis (MCDA) and has leveraged waste value chain. However, the process requires to consider the interlinked fields of environment, socio-cultural and economic/technical factors as Geographical Information Systems (GIS) in a context of lack of knowledge and expertise. This study aims to propose a framework of WtE facilities siting through a GIS-based Fuzzy Analytical Hierarchy Process (FAHP) and location-allocation method in Lomé\'s case study in Togo. This method was applied with boolean logic and fuzzy overlay operators, to assess the potential sites and optimize their selection through a location-allocation solver considering transfer stations and road networks under ArcGIS. Moreover, WtE technologies were attributed to sites based on the territorial aspect. As result, 30.70% of the study area was excluded and three potential areas with a minimum value of 3.47 km2 comprised between 0.81% and 1.01% of the study area, and have been obtained with an acceptable consistency ratio of 0.09. The potential sites are more influenced by slope and residence criteria under economic/technical and socio-cultural factors, with 29.13% and 19.84% of weight respectively. Therefore, through the location-allocation method two optimized sites are obtained and assigned to transfer stations; the first suitable site close to industrial area is appropriate for the gasifier which consequently classified ahead of the anaerobic digester that is suitable for the second suitable site close to agricultural area. As result, prioritizing WtE technologies and site selection should take into account territory aspect, waste sources as well other environmental, socio-cultural and economic/technical factors. This approach has demonstrated its robustness and serves as a stepwise tool for decision makers in WtE facilities siting in developing urban areas.

In the pursuit of sustainability, managing agro-industrial and food processing residues (AFR) efficiently is crucial. This study proposes a systematic approach to convert AFR into valuable products via solid-state fermentation (SSF). Using fungal enzyme production as a case study, this adaptable methodology suits any SSF bioprocess. Initially, AFR\'s physicochemical properties were evaluated to assess their feasible use as carbon sources and solid matrices for SSF. Then, five strains were screened for their capability to produce enzymes (Xylanase, X; pectinase, P; cellulase, C). Apple pomace (AP) and brewery spent grain (BSG) with Aspergillus sp. (strain G5) were selected. Subsequent steps involved a two-phase statistical approach, identifying critical factors and optimizing them. Process conditions were screened using a Plackett-Burman design, narrowing critical variables to three (BSG/AP, pH, humidity). Response Surface Methodology (Central Composite Design) further optimized these factors for co-synthesis of X, P, and C. The humidity had the most significant effect on the three responses. The optimum conditions depended on each enzyme and were further validated to maximize either X, P or C. The obtained extracts were used for pectin extraction from orange peels. The extract containing primarily xylanase (X = 582.39, P = 22.86, C = 26.10 U mL-1) showed major pectin yield recovery (12.33 ± 0.53%) and it was obtained using the optimal settings of BSG/AP (81/19), humidity (50.40%), and pH (4.58). The findings will enable adjusting process conditions to obtain enzymatic cocktails with a tailored composition for specific applications.

：Land management strategies often prioritize agricultural supply services at the expense of other ecosystem services. To achieve a high and steady supply of multiple ecosystem services, it is essential to optimize land management practices in areas suitable for agriculture. However, many studies on land management tend to focus on their benefits to ecosystem service delivery without adequately considering the potential risks to other services that might be involved. Here we use modern portfolio theory to quantitatively measure benefits and risks from land management strategies to enhance ecosystem services. We create seven land management scenarios that balance different kinds of ecosystem services in different ways in the agricultural production area of Maoming, Guangdong Province, China. The method yielded optimal portfolios of land management patterns that enhanced ecosystem services while reducing risk as much as possible. This includes a scenario delivering a 22% increase in agricultural production service, while simultaneously increasing the provision of nature-related ecosystem services by 2%. However, no optimization scenario was perfect, and there was always a trade-off between gaining certain ecosystem service benefits and creating a risk of losing others. Our portfolio theory approach reveals that it is essential to consider both the benefits and risks of land management strategies.

Flooding is the leading natural hazard in Iowa and has resulted in billions of dollars of damage to properties and critical infrastructure over the past couple of decades. Land alterations, urbanization, and changing precipitation regimes increase the magnitude and frequency of flood events. Considering the increasing risk, flood mitigation efforts are significant to reduce future losses. In this study, we present a comprehensive flood mitigation assessment for the cities of Cedar Falls, Cedar Rapids, and Waterloo in Iowa, utilizing various datasets such as property information, flood inundation maps, mitigation costs, and depth-damage functions. The research revealed that flooding has a minimal impact on Waterloo below the 200-year return period flood scenario, but Cedar Falls and Cedar Rapids are significantly vulnerable, requiring more mitigation investments and planning. The study conducted a benefit-cost analysis, indicating that dry floodproofing is the most feasible option to reduce flood impacts in all studied communities. Moreover, the research conducted a climate data-driven analysis, which found that elevating structures significantly increases the number of feasible mitigation options, regardless of various long-term climate projections. The study also analyzed predetermined mitigation budgets, revealing potential avoided losses and benefit-cost ratios for properties with the highest BCRs and prioritizing them to maximize the total benefit to the communities. The study findings offer crucial insights and recommendations to guide decision-makers in the community on prioritizing cost-effective flood mitigation strategies and minimizing flood impact in the studied regions.

Groundwater vulnerability assessment has nowadays evolved into an essential tool towards proper groundwater protection and management, while the DRASTIC method is included among the most widely applied vulnerability assessment methods. However, the high uncertainty of the DRASTIC method mainly associated with the subjectivity in assigning parameters ratings and weights has driven many researchers to apply various methods for improving its efficiency. In this context, in the present study, different techniques were implemented with the aim of modifying the DRASTIC framework and thus enhancing its performance for groundwater vulnerability assessment in the Bouficha aquifer, Tunisia. In a first stage, the land use type (L) was incorporated as an additional parameter in the typical DRASTIC framework, thus taking into consideration the impact of anthropogenic activities on groundwater vulnerability. Subsequently, the rating and weighting systems of the developed DRASTIC-L framework were modified through the application of statistical methods (DRASTIC-L-SA) and genetic algorithms (GA) (DRASTIC-L-GA) in an attempt to investigate and compare both linear and nonlinear modifications. To evaluate the various vulnerability frameworks, correlation between vulnerability values and nitrate concentrations, expressed as Spearman\'s rank correlation coefficient (ρ) and Correlation Index (CI), was examined. The results revealed that the DRASTIC-L-GA framework developed by applying a fully GA-based optimization procedure provided the highest values in terms of the performance metrics used, making it the most suitable for the study area. In addition, the aquifer under study was found to be less vulnerable to pollution when employing the typical DRASTIC framework instead of the modified ones, leading to the conclusion that the former substantially underestimates pollution potential in the study area.