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Leveraging ancillary benefits from urban greenspace - a case study of St. Louis, Missouri.

ABSTRACT: Urban greenspace and green infrastructure are often cited for their many ecosystem services and benefits including stormwater management. However, the localized nature and limited range of effects of these benefits and the type of greenspace and green infrastructure, make planning and placement critical components to selecting for and maximizing desired benefits. Here, the authors test a framework to demonstrate a practical approach to simultaneously manage excess stormwater and maximize distribution of ecosystem services to underserved areas using spatial analysis. St. Louis was subdivided using census block polygons and polygons identified have combined sewer systems with high aggregate annual discharge. Additionally, indicators representing social, economic, and environmental characteristics, which have demonstrated effects from greenspace, were mapped to identify spatial distribution and overlap. The analysis identified one polygon that could promote multiple desired ecosystem services, while reducing annual discharge into combined sewers, and provide these services to an underserved demographic.

SUBMITTER: Jordan P

PROVIDER: S-EPMC9104785 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Leveraging ancillary benefits from urban greenspace - a case study of St. Louis, Missouri.

Jordan Page P Hoover Fushcia-Ann FA Hopton Matthew E ME

Urban water journal 20211101 3

Urban greenspace and green infrastructure are often cited for their many ecosystem services and benefits including stormwater management. However, the localized nature and limited range of effects of these benefits and the type of greenspace and green infrastructure, make planning and placement critical components to selecting for and maximizing desired benefits. Here, the authors test a framework to demonstrate a practical approach to simultaneously manage excess stormwater and maximize distrib ...[more]

PMID: 35573082

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Project description:BackgroundThe epidemiology of nasopharyngeal (NP) pneumococcal carriage varies with geography and has changed in response to pneumococcal conjugate vaccine (PCV): a low prevalence (3% or less of colonizing isolates) of colonization by vaccine-type (VT) pneumococcal serotypes after PCV introduction has been reported. The primary goal of this study was to determine the VT serotype prevalence of NP pneumococcal colonization of children residing in the St. Louis, MO, USA metropolitan area following introduction of the 13-valent PCV in 2010. The secondary goal of this study was to identify characteristics associated with NP pneumococcal carriage of any serotype.MethodsBetween July 2013 and April 2016, we enrolled 397 healthy children, aged 0-17years, who required sedation for procedures or minor surgeries at St. Louis Children's Hospital. NP swabs were collected after sedation or anesthesia and cultured for pneumococcus. Vaccine records were obtained from primary care providers or from state immunization databases. Parents/guardians completed a questionnaire to provide demographics, past medical history and household characteristics.ResultsOf the 88 pneumococcal isolates recovered from 84 colonized subjects (21.2% of all enrolled subjects; 95% CI 17.2-25.2%), 16 were VT. Eleven isolates were serotype 19F (12.5%), four (4.5%) were 6A and one (1.1%) was 19A. Prevalence of VT among colonizing isolates was thus 18.2% (CI 10.1-26.1%) in our cohort, despite complete PCV vaccination in 87% of colonized children. Factors associated with pneumococcal colonization by any serotype included younger age and daycare attendance.ConclusionChildren in St. Louis exhibit a higher prevalence of VT serotypes among pneumococcal carriage isolates than has been reported in other areas in the US, demonstrating the necessity of ongoing surveillance of local epidemiology and providing evidence that serotype 19F can remain prevalent in a pediatric population despite high vaccine uptake.

Project description:Background Evidence seems to suggest that the risk of Coronavirus Disease 2019 (COVID-19) might vary across communities due to differences in population characteristics and movement patterns. However, little is known about these differences in the greater St Louis Area of Missouri and yet this information is useful for targeting control efforts. Therefore, the objectives of this study were to investigate (a) geographic disparities of COVID-19 risk and (b) associations between COVID-19 risk and socioeconomic, demographic, movement and chronic disease factors in the Greater St. Louis Area of Missouri, USA. Methods Data on COVID-19 incidence and chronic disease hospitalizations were obtained from the Department of Health and Missouri Hospital Association, respectively. Socioeconomic and demographic data were obtained from the 2018 American Community Survey while population mobility data were obtained from the SafeGraph website. Choropleth maps were used to identify geographic disparities of COVID-19 risk and several sociodemographic and chronic disease factors at the ZIP Code Tabulation Area (ZCTA) spatial scale. Global negative binomial and local geographically weighted negative binomial models were used to investigate associations between ZCTA-level COVID-19 risk and socioeconomic, demographic and chronic disease factors. Results There were geographic disparities found in COVID-19 risk. Risks tended to be higher in ZCTAs with high percentages of the population with a bachelor’s degree (p<0.0001) and obesity hospitalizations (p<0.0001). Conversely, risks tended to be lower in ZCTAs with high percentages of the population working in agriculture (p<0.0001). However, the association between agricultural occupation and COVID-19 risk was modified by per capita between ZCTA visits. Areas that had both high per capita between ZCTA visits and high percentages of the population employed in agriculture had high COVID-19 risks. The strength of association between agricultural occupation and COVID-19 risk varied by geographic location. Conclusions Geographic disparities of COVID-19 risk exist in the St. Louis area and are associated with sociodemographic factors, population movements, and obesity hospitalization risks. The latter is particularly concerning due to the growing prevalence of obesity and the known immunological impairments among obese individuals. Therefore, future studies need to focus on improving our understanding of the relationships between COVID-19 vaccination efficacy, obesity and waning of immunity among obese individuals so as to better guide vaccination regimens and reduce disparities.

Project description:ImportanceIn the absence of a national strategy in response to the COVID-19 pandemic, many public health decisions fell to local elected officials and agencies. Outcomes of such policies depend on a complex combination of local epidemic conditions and demographic features as well as the intensity and timing of such policies and are therefore unclear.ObjectiveTo use a decision analytical model of the COVID-19 epidemic to investigate potential outcomes if actual policies enacted in March 2020 (during the first wave of the epidemic) in the St Louis region of Missouri had been delayed.Design, setting, and participantsA previously developed, publicly available, open-source modeling platform (Local Epidemic Modeling for Management & Action, version 2.1) designed to enable localized COVID-19 epidemic projections was used. The compartmental epidemic model is programmed in R and Stan, uses bayesian inference, and accepts user-supplied demographic, epidemiologic, and policy inputs. Hospital census data for 1.3 million people from St Louis City and County from March 14, 2020, through July 15, 2020, were used to calibrate the model.ExposuresHypothetical delays in actual social distancing policies (which began on March 13, 2020) by 1, 2, or 4 weeks. Sensitivity analyses were conducted that explored plausible spontaneous behavior change in the absence of social distancing policies.Main outcomes and measuresHospitalizations and deaths.ResultsA model of 1.3 million residents of the greater St Louis, Missouri, area found an initial reproductive number (indicating transmissibility of an infectious agent) of 3.9 (95% credible interval [CrI], 3.1-4.5) in the St Louis region before March 15, 2020, which fell to 0.93 (95% CrI, 0.88-0.98) after social distancing policies were implemented between March 15 and March 21, 2020. By June 15, a 1-week delay in policies would have increased cumulative hospitalizations from an observed actual number of 2246 hospitalizations to 8005 hospitalizations (75% CrI: 3973-15 236 hospitalizations) and increased deaths from an observed actual number of 482 deaths to a projected 1304 deaths (75% CrI, 656-2428 deaths). By June 15, a 2-week delay would have yielded 3292 deaths (75% CrI, 2104-4905 deaths)-an additional 2810 deaths or a 583% increase beyond what was actually observed. Sensitivity analyses incorporating a range of spontaneous behavior changes did not avert severe epidemic projections.Conclusions and relevanceThe results of this decision analytical model study suggest that, in the St Louis region, timely social distancing policies were associated with improved population health outcomes, and small delays may likely have led to a COVID-19 epidemic similar to the most heavily affected areas in the US. These findings indicate that an open-source modeling platform designed to accept user-supplied local and regional data may provide projections tailored to, and more relevant for, local settings.

Dataset Information

Leveraging ancillary benefits from urban greenspace - a case study of St. Louis, Missouri.

Publications

Leveraging ancillary benefits from urban greenspace - a case study of St. Louis, Missouri.

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