Household Pulse Survey (HPS): HPS is a rapid-response survey of adults ages ≥18 years led by the U.S. Census Bureau, in partnership with seven other federal statistical agencies, to measure household experiences during the COVID-19 pandemic. Detailed information on probability sampling using the U.S. Census Bureau’s Master Address File, questionnaires, response rates, and bias assessment is available on the Census Bureau website (https://www.census.gov/data/experimental-data-products/household-pulse-survey.html). Data from adults ages ≥18 years and older are collected by a 20-minute online survey from randomly sampled households stratified by state and the top 15 metropolitan statistical areas (MSAs). Data are weighted to represent total persons ages 18 and older living within households and to mitigate possible bias that can result from non-responses and incomplete survey frame. Data from adults ages ≥18 years and older are collected by 20-minute online survey from randomly sampled households stratified by state and the top 15 metropolitan statistical areas (MSAs). For more information on this survey, see https://www.census.gov/programs-surveys/household-pulse-survey.html. Data are weighted to represent total persons ages 18 and older living within households and to mitigate possible bias that can result from non-responses and incomplete survey frame. Responses in the Household Pulse Survey (https://www.census.gov/programs-surveys/household-pulse-survey.html) are self-reported. Estimates of vaccination coverage may differ from vaccine administration data reported at COVID-19 Vaccinations in the United States (https://covid.cdc.gov/covid-data-tracker/#vaccinations).

US Census Household Pulse Survey (HPS) Indicators by State

This dataset provides comprehensive, time-series data on key indicators derived from the US Census Bureau's Household Pulse Survey (HPS). It offers a granular view of economic conditions and experiences at the state level over time.

The dataset includes a rich array of variables such as:

• Demographic information: State and population.
• Survey metadata: Data collection start and end dates, survey cycle, phase.
• Key indicators: Employment status, income, housing, food security, healthcare access, public opinions on various topics, and more!
• Estimates and margins of error: Both point estimates and associated margins of error are provided.

This dataset can be used for trend analysis, impact assessments, and developing targeted interventions, as a standalone EDA project, or in conjunction with other datasets.

Potential Use Cases:

• Analyze economic recovery patterns across different states
• Identify disparities in household experiences by state
• Track changes in employment and unemployment rates over time
• Assess the impact of government policies on various populations

Due to the change in the survey instrument regarding intention to vaccinate, our estimates for “hesitant or unsure” or “hesitant” derived from April 14-26, 2021, are not directly comparable with prior Household Pulse Survey data and should not be used to examine trends in hesitancy.

To support state and local communication and outreach efforts, ASPE developed state, county, and sub-state level predictions of hesitancy rates(https://aspe.hhs.gov/pdf-report/vaccine-hesitancy) using the most recently available federal survey data.

We estimate hesitancy rates at the state level using the U.S. Census Bureau’s Household Pulse Survey (HPS)(https://www.census.gov/programs-surveys/household-pulse-survey.html) data and utilize the estimated values to predict hesitancy rates in more granular areas using the Census Bureau’s 2019 American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS)(https://www.census.gov/programs-surveys/acs/microdata.html). Public Use Microdata Areas (PUMA) level – PUMAs are geographic areas within each state that contain no fewer than 100,000 people. PUMAs can consist of part of a single densely populated county or can combine parts or all of multiple counties that are less densely populated.

The HPS is nationally representative and includes information on U.S. residents’ intentions to receive the COVID-19 vaccine when available, as well as other sociodemographic and geographic (state, region and metropolitan statistical areas) information. The ACS is a nationally representative survey, and it provides key sociodemographic and geographic (state, region, PUMAs, county) information. We utilized data for the survey collection period May 26, 2021 – June 7, 2021, which the HPS refers to as Week 31.

County and State Hesitancy Data - https://data.cdc.gov/Vaccinations/Vaccine-Hesitancy-for-COVID-19-County-and-local-es/q9mh-h2tw

Due to the change in the survey instrument regarding intention to vaccinate, our estimates for “hesitant or unsure” or “hesitant” derived from April 14-26, 2021, are not directly comparable with prior Household Pulse Survey data and should not be used to examine trends in hesitancy.

To support state and local communication and outreach efforts, ASPE developed state, county, and sub-state level predictions of hesitancy rates (https://aspe.hhs.gov/pdf-report/vaccine-hesitancy) using the most recently available federal survey data.

We estimate hesitancy rates at the state level using the U.S. Census Bureau’s Household Pulse Survey (HPS) (https://www.census.gov/programs-surveys/household-pulse-survey.html) data and utilize the estimated values to predict hesitancy rates at the Public Use Microdata Areas (PUMA) level using the Census Bureau’s 2019 American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS)(https://www.census.gov/programs-surveys/acs/microdata.html). To create county-level estimates, we used a PUMA-to-county crosswalk from the Missouri Census Data Center(https://mcdc.missouri.edu/applications/geocorr2014.html). PUMAs spanning multiple counties had their estimates apportioned across those counties based on overall 2010 Census populations.

The HPS is nationally representative and includes information on U.S. residents’ intentions to receive the COVID-19 vaccine when available, as well as other sociodemographic and geographic (state, region and metropolitan statistical areas) information. The ACS is a nationally representative survey, and it provides key sociodemographic and geographic (state, region, PUMAs, county) information. We utilized data for the survey collection period May 26, 2021 – June 7, 2021, which the HPS refers to as Week 31..

PUMA COVID-19 Hesitancy Data - https://data.cdc.gov/Vaccinations/Vaccine-Hesitancy-for-COVID-19-Public-Use-Microdat/djj9-kh3p

Abstract

Abstract Background: Sparse evidence is available to support improved programming and reporting on SRHR in refugee settings in the east and horn of Africa, where unsafe abortion is one of the major causes of maternal mortality and morbidity. It is important to design studies that explicitly investigate the sexual and reproductive health needs and outcomes of refugee populations, as it is likely that these factors differ among refugee populations as opposed to the general population. Understanding the state of abortion in a given context, including abortion incidence, safety, and outcomes, is challenging due to the limitations of currently available methodologies. Objectives: To determine the incidence of induced abortions and the severity of abortion-related complications in refugee settings in Uganda. Methods: The study employed a quantitative cross-sectional design. The study components included three separate surveys though the study was not nationally representative, but efforts were made to ensure representativeness at the refugee settlement/camp level : i) representative Health Facility Survey (HFS) to estimate the number of women who receive post-abortion care (PAC) following abortion complications, ii) a Knowledgeable Informants Survey (KIS) to captured information on the proportion of all women having abortions who receive facility-based treatment for abortion-related complications, and iv) a Prospective Morbidity Survey (PMS) to provide the data necessary to describe characteristics of women receiving treatment for abortion complications, the severity of complications, the type of treatment received, and the delays in access to PAC. The PMS also included clinical data abstraction from the medical records. Potential Impact: This will help host governments, humanitarian partners, and donors to seek long-term, innovative, cost-effective SRHR development solutions to bring about change in the health and lives of refugee women and girls.

Geographic coverage

refugee settlements in Uganda

Analysis unit

Abortion Incidence, Severity of Complications, and Health Facilities’ Capacity to offer Post Abortion Care for people living in refugee settings in Uganda.

Individual - PAC patients, Knowlegeble Informants Institutional (Health Facility) - PAC is providers

Universe

The components of the survey covered refugee settlements in Uganda, women aged 15-49 residents of the setttlement, health facilities located within or just outside the refugee settlements and individuals who were knowledgeable about induced abortion among refugee populations.

Sampling procedure

Sampling took place at different levels of the study since it had different components: Health Facility Survey

It was administered to all health facilities located within the 13 refugee settlements in Uganda. However, due to the integration of social services, including healthcare, some women from the host community had accessed services (or even reside) within the refugee settlements, and refugee women could choose to visit health facilities located outside the settlements. Therefore, we did not limit the HFS to facilities located within the 13 refugee settlements in Uganda. To construct the census, UNHCR provided a list of facilities (n=110) capable of providing PAC located within or just outside all 13 refugee settlements that were in operation at the time of data collection. However, upon further investigation, we excluded 17 of these facilities, either because they had health posts that do not provide PAC (n=8), do not serve refugees (n=3), or because they had recently closed (n=6). In addition, we identified additional eligible facilities during the fielding process that were not included in the UNHCR list (n=9). As such, our final HFS sample consisted of 102 facilities. At each facility, a senior staff member who was knowledgeable about the provision of PAC and had been working at their facility for at least 6 months was interviewed. Facility types included Health Center II (typically small health clinics), Health Center III (larger health centers with maternity wards), and Health Center IV and above (hospitals with maternity wards and inpatient services). Overall, 89.2% of facilities (n=91) were located within the borders of a refugee settlement.

Knowledgeable Informant Survey For the KIS, we purposely identified and sampled individuals who were knowledgeable about induced abortion among refugee populations in Uganda. These individuals included providers who serve refugee women, including nurses, midwives, clinical officers, doctors, social workers, traditional birth attendants, and community health providers, as well as district-level health officers and coordinators and staff at NGOs that provide services to refugee women within the settlements. The final sample consisted of 59 of these knowledgeable informants.

Prospective Morbidity Survey To select facilities for the PMS, we asked HFS Research Assistants to collect contact information of facility leadership for potential PMS participation. We contacted and invited all facilities to participate in the PMS. We excluded Health Posts (HPs) from the sample, which typically do not provide PAC. However, given that facility levels can often change, there were some discrepancy between levels identified in our original HFS universe, and the level the facility was later identified as when in the field. For example, despite excluding HPs from our sampling frame, one HP was included as it was erroneously classified as a level 3 facility in our HFS sample and was dropped from analysis. In addition, some facilities were unable to send health facility staff to the PMS training. As such, the final PMS sample consisted of 65 health facilities.

Sampling deviation

PMS: A sample was randomly drawn from the original list of facilities provided to us by UNHCR Uganda. The original sampling design was based on facility level, drawing 0% of HPs, 40% of HC IIs, and all HC IIIs and HC IVs. Some facilities in the UNHCR master list were found in the HFS to not provide PAC, and were purposively replaced by facilities that did provide PAC. One HP was mistakenly included in PMS fielding, but was dropped from analysis.

KIS: N/A

HFS: N/A

Mode of data collection

Face-to-face [f2f]

Research instrument

The study used four questionnaires during data collection with different target population. The questionnaires were written in english. The HFS questionnaire captured information to estimate the number of women receiving treatment in facilities for complications from unsafe abortions, the KIS questionnaire was used to collect information on the proportion of all refugee women having abortions who received facility-based treatment for abortion-related complications and the PMS provided data necessary to describe characteristics of women living in refugee settings and receiving treatment for abortion complications, the type of treatment received for complications, uptake of post-abortion family planning, and the delays in access to post-abortion care. The PMS also included charts review to abstract data on laboratory measurements, procedures and management of complications for PAC patients.

Cleaning operations

Interviews for all surveys was conducted face-to-face, using Open Data Kit (ODK) software on Android smartphones. Completed ODK forms were submitted to a secure cloud server using Wi-Fi or mobile data networks accessible only to the study team. The data was later uploaded to Stata to be cleaned and analyzed.

Response rate

KIS: N/A

HFS: 100% (census survey)

PMS, Uganda: Of the 78 facilities sampled for participation in the PMS, a total of 65 participated (response rate: 67.9%). Due to the sampling deviation described above (the PMS sample being drawn from the original UNHCR facility list during HFS fielding), 15 facilities were purposively replaced by those deemed to be ineligible due to non-provision of PAC. Regarding the individual-level response rate, all patients treated at the sampled facilities during the study period were eligible to participate in the study. The participation rate of patients was 89% overall, 85.7% at HC IIs, 88.6% at HC IIIs, and 94.9% at HC IVs.

Sampling error estimates

Analyses were performed in Stata 19. The dataset was weighted using the following command: svyset [pweight=wgt_pmsind].

The need to develop the UK supply for domestic heat pumps (HPs) and to evaluate the empirical performance of HP systems in the field has led to the establishment of two major UK field trials of HPs (the first one took place between 2008 and 2012). These data were generated from the second field trial, established by the Department for Energy and Climate Change (DECC) in conjunction with the Renewable Heat Premium Payment (RHPP) grant scheme, which ran from 2011-2014 (note that the data included here cover the period October 2013-March 2015). Please note that this study contains the cleaned data - a raw version is available under SN 7955. See the RAPID-HPC statement below for information on data quality.

The RHPP policy provided subsidies for private householders, Registered Social Landlords and communities to install renewable heat measures in residential properties. Eligible measures included air and ground-source heat pumps, biomass boilers and solar thermal panels. Around 14,000 heat pumps were installed via this scheme. DECC (now BEIS) funded a detailed monitoring campaign, which covered 700 heat pumps (around 5% of the total). The aim of this monitoring campaign was to provide data to enable an assessment of the efficiencies of the heat pumps and to gain greater insight into their performance. The RHPP scheme was administered by the Energy Savings Trust (EST) who engaged the Buildings Research Establishment (BRE) to run the meter installation and data collection phases of the monitoring program. They collected data from 31 October 2013 to 31 March 2015. RHPP heat pumps were installed between 2009 and 2014. Since the start of the RHPP Scheme, the installation requirements set by MCS standards and processes have been updated. Further information about the RHPP scheme (which has now closed), including statistics, can be found on the Gov.uk Renewable Heat Premium Payment scheme statistics webpage.

DECC contracted the RAPID-HPC to analyse these data. The data provided to RAPID-HPC included physical monitoring data, and metadata describing the features of the heat pump installations and the dwellings in which they were installed. As the analysis has progressed, limitations with the underlying data have been identified. See RAPID-HPC's statement (below). (See also SN 7955 for a raw version of the data.)

RAPID-HPC's Statement on Data Anomalies and Interpretation, February 2016 (covered in the Detailed Analysis of Data Report and the spreadsheets included with this study)
The work of the RAPID-HPC consisted of cleaning the data, selection of sites and data for analysis, analysis, and the development of conclusions and interpretations. The monitoring data and contextual information are imperfect. Discussion of the data limitations are provided in the DECC Detailed analysis of data from heat pumps installed via the Renewable Heat Premium Payment Scheme report on the gov.uk website which is essential to the understanding of this data. RAPID-HPC has used a top-down rules-based approach to identifying data anomalies to clean the data. The advantages of this approach are that it is transparent and replicable and enables analysis of the very large (over 0.5 billion data points) dataset as a whole. It is important to note that the data was collected from domestic heat pumps installed via the RHPP policy. [RAPID-HPC] have not assessed the degree to which the heat pumps assessed are representative of the general sample of domestic heat pumps in the UK. Therefore, results from any analysis undertaken using these data should not be assumed to be representative of any other sample of heat pumps.

Downloading the data - using suitable zip software
Users should note that the download zip file for this study is over 1GB in size. The standard Windows system zip compression software is not able to unzip a file of this size completely and may mean that problems are encountered with some of the data or documentation files. Therefore, it is recommended that users install one of the following software packages in order to unzip the file:

• 7zip (free open source software for Windows, check 7zip website for Linux/Unix);
• WinZip (free to try for Windows and Mac);
• iZip (free software for Mac).

Hydroxypropyl starch ether (HPS) market size research report, identifies new revenue opportunity in hydroxypropyl starch ether (HPS) driver industry. The report aims at estimating the market size and future growth of the hydroxypropyl starch ether based on type, end-use industry & region.

Human pluripotent stem (hPS) cells are capable of differentiation into derivatives of all three primary embryonic germ layers and can self-renew indefinitely. They therefore offer a potentially scalable source of replacement cells to treat a variety of degenerative diseases. The ability to reprogram adult cells to induced pluripotent stem (iPS) cells has now enabled the possibility of patient-specific hPS cells as a source of cells for disease modeling, drug discovery, and potentially, cell replacement therapies. While reprogramming technology has dramatically increased the availability of normal and diseased hPS cell lines for basic research, a major bottleneck is the critical unmet need for more efficient methods of deriving well-defined cell populations from hPS cells. Phage display is a powerful method for selecting affinity ligands that could be used for identifying and potentially purifying a variety of cell types derived from hPS cells. However, identification of specific progenitor cell-binding peptides using phage display may be hindered by the large cellular heterogeneity present in differentiating hPS cell populations. We therefore tested the hypothesis that peptides selected for their ability to bind a clonal cell line derived from hPS cells would bind early progenitor cell types emerging from differentiating hPS cells. The human embryonic stem (hES) cell-derived embryonic progenitor cell line, W10, was used and cell-targeting peptides were identified. Competition studies demonstrated specificity of peptide binding to the target cell surface. Efficient peptide targeted cell labeling was accomplished using multivalent peptide-quantum dot complexes as detected by fluorescence microscopy and flow cytometry. The cell-binding peptides were selective for differentiated hPS cells, had little or no binding on pluripotent cells, but preferential binding to certain embryonic progenitor cell lines and early endodermal hPS cell derivatives. Taken together these data suggest that selection of phage display libraries against a clonal progenitor stem cell population can be used to identify progenitor stem cell targeting peptides. The peptides may be useful for monitoring hPS cell differentiation and for the development of cell enrichment procedures to improve the efficiency of directed differentiation toward clinically relevant human cell types.

Halide perovskites (HPs) are widely viewed as promising photovoltaic and light-emitting materials for their suitable band gaps in the visible spectrum. Density functional theory (DFT) calculations employing (semi)local exchange-correlation functionals usually underestimate the band gaps for these systems. Accurate descriptions of the electronic structures of HPs often demand higher-order levels of theory such as the Heyd-Scuseria-Ernzerhof (HSE) hybrid density functional and GW approximations that are much more computationally expensive than standard DFT. Here, we investigate three representative types of HPs, ABX3 halide perovskites, vacancy-ordered double perovskites (VODPs), and bond disproportionated halide perovskites (BDHPs), using DFT+U+V with onsite U and intersite V Hubbard parameters computed self-consistently without a priori assumption. The inclusion of Hubbard corrections improves the band gap prediction accuracy for all three types of HPs to a similar level of advanced methods. Moreover, the self-consistent Hubbard U is a meaningful indicator of the true local charge state of multivalence metal atoms in HPs. The inclusion of the intersite Hubbard V is crucial to properly capture the hybridization between valence electrons on neighboring atoms in BDHPs that have breathing-mode distortions of halide octahedra. In particular, the simultaneous convergence of both Hubbard parameters and crystal geometry enables a band gap prediction accuracy superior to HSE for BDHPs but at a fraction of the cost. Our work highlights the importance of using self-consistent Hubbard parameters when dealing with HPs that often possess intricate competitions between onsite localization and intersite hybridization.

BackgroundKnowledge and attitudes are among the key drivers of social behavioral change. We assessed employed health professionals' (HPs) knowledge, attitude, and practice regarding COVID-19 in Dessie city, northeast Ethiopia.MethodsA facility-based cross-sectional study was conducted among 419 HPs working at Dessie city from 17 to 21 May 2020. The data were collected using a self-administered structured questionnaire. Knowledge, attitude, and practice are measured using 19, 16, and 8 questions, respectively. Knowledge and attitude scores are dichotomized at the 3rd quartile, while practice is using the mean value. Data entry and analysis were conducted using EpiData Manager 4.2 and SPSS 25, respectively. Three independent logistic regression analyses were carried out to determine the associated factors. We defined significant association at a p-value of < 0.05.ResultsOut of 419 participants, 369 (88.1%) have sufficient knowledge regarding COVID-19 (95% CI: 85–91). The mean knowledge score is 16.8 with a ± 2.1 SD. Similarly, 355 (84.7%) of the HPs have a favorable attitude toward COVID-19 (95% CI: 81–87.9). The mean attitude score is 14 with ± 2.1 SD. However, practice regarding COVID-19 is adequate only in 69.7% (292) of the HPs (95% CI: 65.2–94). The mean practice score is 5.1 with a ± 1.3 SD. Sufficient knowledge is significantly associated with the type of health facility (AOR: 4.4, 95% CI: 1.4–13.3), degree and above education (AOR: 2.6, 95% Cl: 1.4–4.9), radio availability (AOR: 2.4, 95% CI: 1.3–4.7), and social media utilization (AOR: 2.3, 95% CI: 1.1–5.1). The predictors of favorable attitude are training (AOR: 3.1, 95% CI: 1.6–6.1), sufficient knowledge (AOR: 5.2, 95% Cl: 2.6–10.4), and type of health facility (AOR: 2.3, 95% CI: 1.1–5.2).ConclusionMost HPs have sufficient knowledge and a favorable attitude regarding COVID-19. However, practice is relatively low and there remains plenty to build assertive preventive behaviors. The gap between knowledge and practice should be narrowed through an appropriate social and behavioral change communication strategy.

Hermansky-Pudlak Syndrome type-1 (HPS-1) is an autosomal recessive disorder caused by mutations in HPS1 which result in reduced expression of the HPS-1 protein, defective lysosome-related organelle (LRO) transport and absence of platelet delta granules. Patients with HPS-1 exhibit oculocutaneous albinism, colitis, bleeding and pulmonary fibrosis postulated to result from a dysregulated immune response. The effect of the HPS1 mutation on human mast cells (HuMCs) is unknown. Since HuMC granules classify as LROs along with platelet granules and melanosomes, we set out to determine if HPS-1 cutaneous and CD34+ culture-derived HuMCs have distinct granular and cellular characteristics. Cutaneous and cultured CD34+-derived HuMCs from HPS-1 patients were compared with normal cutaneous and control HuMCs, respectively, for any morphological and functional differences. One cytokine-independent HPS-1 culture was expanded, cloned, designated the HP proMastocyte (HPM) cell line and characterized. HPS-1 and idiopathic pulmonary fibrosis (IPF) alveolar interstitium showed numerous HuMCs; HPS-1 dermal mast cells exhibited abnormal granules when compared to healthy controls. HPS-1 HuMCs showed increased CD63, CD203c and reduced mediator release following FcɛRI aggregation when compared with normal HuMCs. HPM cells also had the duplication defect, expressed FcɛRI and intracytoplasmic proteases and exhibited less mediator release following FcɛRI aggregation. HPM cells constitutively released IL-6, which was elevated in patients’ serum, in addition to IL-8, fibronectin-1 (FN-1) and galectin-3 (LGALS3). Transduction with HPS1 rescued the abnormal HPM morphology, cytokine and matrix secretion. Microarray analysis of HPS-1 HuMCs and non-transduced HPM cells confirmed upregulation of differentially expressed genes involved in fibrogenesis and degranulation. Cultured HPS-1 HuMCs appear activated as evidenced by surface activation marker expression, a decrease in mediator content and impaired releasibility. The near-normalization of constitutive cytokine and matrix release following rescue by HPS1 transduction of HPM cells suggests that HPS-1 HuMCs may contribute to pulmonary fibrosis and constitute a target for therapeutic intervention.

BackgroundThe communication of prognosis represents an ethical and clinical challenge in medical practice due to the inherent uncertain character of prognostic projections. The literature has stressed that the mode of communicating prognoses has an impact on patients’ hope, which is considered to play a major role in adapting to illness and disability. In light of this, this study aims to explore health professionals’ (HPs) perceptions of the role of hope in rehabilitation and to examine if and how they use strategies to maintain hope when discussing prognostic information with patients.MethodsEleven qualitative semi-structured interviews with a purposive sample of HPs were conducted at two rehabilitation clinics in the Canton of Ticino, Switzerland. The interviews were analyzed using thematic analysis.ResultsThe HPs perceive hope in rehabilitation as a double-edged sword. Three main strategies were identified to maintain hope while avoiding false hope: 1) giving space for self-evaluation; 2) tailoring the communication of prognostic information; and 3) supporting the patient in dealing with the prognosis. These strategies are particularly suitable when HPs consider that patients might not be ready to accept the prognosis, due to their expectations for recovery.ConclusionsThe strategies identified here support a person-centered approach to the communication of prognosis and are in line with existing protocols for the communication of unfavorable medical information. The findings emphasize the need for strengthening communication and inter-professional collaboration skills of rehabilitation HPs.

These simulations describe the dynamic changes (5 minute intervals) of the indoor climate (temperature, humidity, CO2 concentration) and energy consumption (lighting and heating) of a simulated greenhouse season in a typical meteorological year (350 days starting September 27). A modern, Venlo type, 4 hectare greenhouse with a tomato crop is simulated, with either HPS or LED lamps. 15 different weather scenarios from around the world are included, as well as various settings for design and climate control. The GreenLight model, https://github.com/davkat1/GreenLight, was used for this purpose.

Inferring the historical and biophysical causes of diversity within protein families is a complex puzzle. A key to unraveling this problem is characterizing the rugged topography of sequence–function adaptive landscapes. Using biochemical data from a 29 = 512 combinatorial library of tobacco 5-epi-aristolochene synthase (TEAS) mutants engineered to make the native major product of Egyptian henbane premnaspirodiene synthase (HPS) and a complementary 512 mutant HPS library, we address the question of how product specificity is controlled. These data sets reveal that HPS is far more robust and resistant to mutations than TEAS, where most mutants are promiscuous. We also combine experimental data with a sequence Potts Hamiltonian model and direct coupling analysis to quantify mutant fitness. Our results demonstrate that the Hamiltonian captures variation in product outputs across both libraries, clusters native family members based on their substrate specificities, and exposes the divergent catalytic roles of couplings between the catalytic and noncatalytic domains of TEAS versus HPS. Specifically, we found that the role of the interdomain connectivities in specifying product output is more important in TEAS than connectivities within the catalytic domain. Despite being 75% identical, this property is not shared by HPS, where connectivities within the catalytic domain are more important for specificity. By solving the X-ray crystal structure of HPS, we assessed structural bases for their interdomain network differences. Last, we calculate the product profile Shannon entropies of the two libraries, which showcases that site–site connectivities also play divergent roles in catalytic accuracy.

There has been a sustained interest in transfer of care (ToC) services, from hospital to home, in the past twenty years. In England, an electronic referral (e-referral) service from hospital to community pharmacy has been provided since 2014. However, to date, there has been little information about service implementation and delivery. This study investigates the barriers to this referral process in hospital and community pharmacy settings, and barriers to providing subsequent community pharmacy interventions from the perspectives of the service leaders (SLs), hospital pharmacy staff (HPS) and community pharmacists (CPs). Semi-structured face-to-face or telephone interviews were conducted with the key informants from two tertiary hospitals and nine pharmacies. The Consolidated Framework for Implementation Research (CFIR) tool informed the data collection tools and data analysis. A total of three SLs, ten HPS and nine CPs were interviewed. Data analysis identified various barriers to the provision of the e-referral service. Some were related to (1) patient engagement, e.g., patients’ awareness/acceptance of the service, (2) the SLs and other National Health Service hospitals, e.g., lack of monitoring of the service progress, (3) the HPS, e.g., resource limitations, or (4) the CPs, e.g., lack of understanding/appreciation of the service. In-depth understanding of barriers related to the provision of e-referral service are essential to drive improvement and facilitate wider diffusion and adoption. The use of implementation science and behaviour change model as a lens to assess this service enables the identification of certain behaviours that can be modified to produce the required change to drive better implementation and delivery.

IntroductionMedical screening is a major driver of overdiagnosis, which should be considered when making an informed screening decision. Health professionals (HPs) often initiate screening and are therefore responsible for informing eligible screening participants about the benefits and harms of screening. However, little is known about HPs’ knowledge of overdiagnosis and whether they are prepared to inform screening candidates about this risk and enable people to make an informed screening decision.MethodsThis is a systematic review of studies examining HPs’ knowledge and perception of overdiagnosis, whether it affects their position on offering screening, and their willingness to inform screening candidates about overdiagnosis. We conducted systematic searches in MEDLINE, Embase, Web of Science, Scopus, CINAHL, and PsycArticles without language restrictions. Two authors analysed the qualitative and quantitative data separately. Confidence in the findings of the qualitative data was assessed using the GRADE-CERQual approach.ResultsWe included 23 publications after screening 9786 records. No studies directly examined HPs’ knowledge of overdiagnosis. HPs’ perceptions of overdiagnosis varied widely, from considering it a significant harm to seeing it as negligible. This seems linked to their overall beliefs about the benefits and harms of screening and to their position on offering screening, which varies from discouraging to actively promoting it. HPs also hold diverging approaches to informing screening candidates about overdiagnosis, from providing detailed explanations to limited or no information.ConclusionThere is a lack of research on HPs’ knowledge of overdiagnosis, however, HPs who do know about overdiagnosis attribute substantially different levels of harm to it. This seems intertwined with their overall beliefs about the benefits of screening, their position towards offering screening, and their willingness to inform screening candidates about overdiagnosis. This has important implications for the public’s right to evidence-based information and compromises an individual’s right to make an informed screening decision.