Prioritization Of Resources Research Articles

Integration of social, economic and environmental factors in GIS for land degradation vulnerability assessment in the Pir Panjal Himalaya, Kashmir, India

Land degradation assessment is imperative for developing a mitigation plan to minimize the adverse impacts associated with land degradation. The study involves the integration of various social, economic and environmental indices for identifying the land degradation vulnerable areas in the Pir Panjal Himalaya, Kashmir, India. Analysis of the land use and land cover from the satellite data revealed that ~47% of the area is devoid of any vegetal cover. Slope index revealed that ~40% of the study area is precipitous with slope >30%. The land utilization index indicated that ~51% of the area is over-utilized. Integration of all the environmental indices in GIS environment yielded the Natural Resource Prioritization Index which revealed that ~41% of the area needs attention for land degradation mitigation on top priority. Integration of all the socioeconomic indices yielded the Socio-Economic Priority Zones which revealed that ~35% of the area needs attention for the socio-economic upliftment on priority for combating the land degradation in the study area. Land Degradation Vulnerability Index (LDVI) model was developed in GIS environment based on the unique combination of various natural resource and socioeconomic priority zones using the weighted index approach to assess the cumulative impact of social, economic and environmental factors on land degradation. The model analyses revealed that ~48% of the study area (~603 Km2) shows high to very high LDVI values alluding to its high vulnerability to different forms of land degradation. The approach developed in this research for the integration of various causal factors to identify the lands vulnerable to varying degree and intensity of degradation will go a long way in developing appropriate mitigation strategies for combating land degradation at village level in the Himalaya.

Evidencing value of public health programmes to enable sustainable investment for health & wellbeing

Abstract Issue Global sustainability challenges related to health, inequity, the environment and the economy require urgent innovative action and focus on prevention. Fair evidence-informed prioritisation of scarce resources is pivotal to ensure sustainable investment policies and practices. It is key to capture the value and return on investment of public health (prevention) programmes in order to show their wider benefit to people, communities, society, economy and our planet. Description The Evidencing Value project builds on a global and national drive towards measuring the value of health services and interventions. The World Health Organization Collaborating Centre for Investment in Health and Well-being (WHO CC) is developing an innovative approach and digital solution to assess the holistic (economic, social and environmental) value and return on investment of public health programmes. It uses a Social Return on Investment (SROI) approach, which involves key stakeholders from the beginning and measures what matters most. This helps to identify the wider impact and outcomes of different health protection, disease prevention and health promotion programmes. The evidence is embedded in an interactive digital database to inform investment prioritisation and quality improvement. Results Project outputs include: (i) structured evidence repository detailing the value of public health services and interventions; (ii) interactive digital database for storage, manipulation and presentation of data; (iii) SROI pilots; and (iv) generalised framework for investing in public health/prevention to be used by other public bodies and countries. Lessons It is essential to understand the wider impact and value of public health programmes to facilitate Universal Health Coverage and sustainable investment for health and wellbeing. This project uses an innovative approach and digital solution to enable evidence informed resource allocation and decision-making focused on prevention. Key messages Evidencing value of public health supports the case for investing in prevention. Using innovative methods and digital solutions is essential to inform sustainable investment for health.

Mental health implications of COVID-19 pandemic and its response in India.

Introduction:Mental health concerns and treatment usually take a backseat when the limited resources are geared for pandemic containment. In this global humanitarian crisis of the COVID-19 pandemic, mental health issues have been reported from all over the world.Objectives:In this study, we attempt to review the prevailing mental health issues during the COVID-19 pandemic through global experiences, and reactive strategies established in mental health care with special reference to the Indian context. By performing a rapid synthesis of available evidence, we aim to propose a conceptual and recommendation framework for mental health issues during the COVID-19 pandemic.Methods:A search of the PubMed electronic database and google scholar were undertaken using the search terms ‘novel coronavirus’, ‘COVID-19’, ‘nCoV’, SARS-CoV-2, ‘mental health’, ‘psychiatry’, ‘psychology’, ‘anxiety’, ‘depression’ and ‘stress’ in various permutations and combinations. Published journals, magazines and newspaper articles, official webpages and independent websites of various institutions and non-government organizations, verified social media portals were compiled.Results:The major mental health issues reported were stress, anxiety, depression, insomnia, denial, anger and fear. Children and older people, frontline workers, people with existing mental health illnesses were among the vulnerable in this context. COVID-19 related suicides have also been increasingly common. Globally, measures have been taken to address mental health issues through the use of guidelines and intervention strategies. The role of social media has also been immense in this context. State-specific intervention strategies, telepsychiatry consultations, toll free number specific for psychological and behavioral issues have been issued by the Government of India.Conclusion:Keeping a positive approach, developing vulnerable-group-specific need-based interventions with proper risk communication strategies and keeping at par with the evolving epidemiology of COVID-19 would be instrumental in guiding the planning and prioritization of mental health care resources to serve the most vulnerable.

Association between hypertension and pneumonia caused by SARS-CoV-2 in Mexican population.

We have read with great interest the published article by Tapia-Orihuela [1], in which it is stated that hypertension is one of the most frequent comorbidities observed in severe cases of coronavirus disease 2019 (COVID-19) and deaths. In favor of what the author mentioned, COVID-19 has become a pandemic in recent months due to its high transmissibility and mortality. These characteristics cause sanitary systems to collapse, and COVID-19 is not optimally controlled. For this reason, for some months, several investigations have served to understand the behavior of COVID-19 and its risk factors, with hypertension being one of the most studied [2]. Case reports from China describe a higher frequency of COVID-19 cases in patients with hypertension [3–5]. SARS-CoV-2 uses the angiotensin-converting enzyme 2 (ACE2) to bind to the target cell [6]. Based on the increase in the expression of ACE2 in patients treated with ACE inhibitors and AT1 blockers, it is postulated that patients with hypertension and treated with those antihypertensive drugs could be susceptible to an increased susceptibility to SARS-CoV-2 infection and increased risk of severity of the disease [7,8]. However, the association between the presence of hypertension or an increased ACE2 expression and the susceptibility and severity of SARS-CoV-2 infection has not been established in the population affected with COVID-19, including COVID-19 patients in the Americas region. Therefore, we sought to estimate the association between the presence of hypertension and severe COVID-19 disease (defined by the diagnosis of SARS-CoV-2 pneumonia) in the Mexican population. A cross-sectional study was performed analyzing the data of patients diagnosed with COVID-19 in Mexico. The data were collected by the Secretaría de Salud de México and is available at https://coronavirus.gob.mx. The independent variable was the presence of hypertension. A logistic regression model was performed to assess the association between the presence of hypertension and severe COVID-19 disease, adjusting this association for sex, age, smoking, and comorbidities. The analysis was performed using Stata 14 software (Stata Corp, College Station, Texas, USA). A total of 4992 SARS-CoV-2 positive cases were included, being 2902 (58.1%) males. The average age was 45.7, and the median was 45 (interquartile range: 34–57). Of the total patients, 1247 (25.0%) had a diagnosis of SARS-CoV-2 pneumonia [434 (34.8%) of these patients had hypertension]. A statistically significant association was found between hypertension and SARS-CoV-2 pneumonia both in the crude model [odds ratio (OR) = 3.27, 95% confidence interval (CI): 2.82–3.79] and in the adjusted model (adjusted OR = 1.50, 95% CI: 1.26–1.79) (Table 1). The study findings suggest that hypertension in Mexican patients would be associated with a greater probability of developing SARS-CoV-2 pneumonia.TABLE 1: Unadjusted and adjusted logistic regression analysis of the association between hypertension and pneumonia caused by SARS-CoV-2Chronic diseases, such as hypertension, affect a significant percentage of the world population vulnerable to COVID-19. In Mexico, 25.5% of the population has hypertension [9]. In a pandemic context, the identification of groups at higher risk to present COVID-19 facilitates the prioritization of resources, especially in countries with health systems with limited capacity to respond to global crises, such as those in the Latin American region. It is necessary to deepen the investigation on the pathophysiological mechanisms that would have a role in the association between hypertension and COVID-19, for the development of recommendations for the management of patients with SARS-CoV-2 and this comorbidity. ACKNOWLEDGEMENTS Author contributions: A.H.V. conceived the study. Data were interpreted by A.H.V. All authors drafted the article, and critically reviewed, and approved the final article. All authors assume responsibility for the content of the article. Conflicts of interest There are no conflicts of interest.

A Comparison of Attribute-Focused and Harm-Focused Methods for Assessing the Risk of Organized Crime Groups: Are They in Agreement?

Abstract Risk assessment methods are used to map the threat posed by organized crime and assist in the prioritization of policing resources. Within policing, risk assessment methods are currently in use that either focus on the attributes of organized crime groups or the types of harm posed. Statistical analysis was undertaken of risk assessment data produced using one attribute-focused and one harm-focused method. The study was based on a non-random sample of 113 attribute-focused and 77 harm-focused risk assessments of the same 17 OCGs, and a sub-sample of 36 pairs of risk assessments of 16 of the OCGs. A moderate correlation was found between the two methods, despite differences in their risk assessment processes. Lower levels of agreement tended to be associated with OCGs posing high levels of harm, particularly financial and psychological. Using the two risk assessment methods in combination is proposed as a way of building consensus that draws on their alternative perspectives. The techniques applied in this analysis could be used to inform revisions to the methods and their supporting materials, identify outlying risk assessments, and potentially incorporate other information sources such as harm indices.

The use of resources for legal terminological decision-making: patterns and profile variations among institutional translators

ABSTRACT Effective information mining for legal terminological research in translation is largely determined by the ability to contextualize concepts in their legal framework and to resort to relevant legal sources. Specialized knowledge of these sources thus emerges as a competence marker that is expected to converge with that of comparative law practitioners. Against this background, a survey was conducted in order to examine institutional translators’ use of resources for translation in general and their perceptions of sources for legal translation in particular. The data provided by 234 respondents from 12 international organizations offer a comprehensive portrait of translation professionals and information-mining practices in these settings. Profile features in terms of legal translation frequency, main translation specializations and academic backgrounds were correlated to relevance and reliability scores assigned to the sources used for legal terminological research. The results confirm several hypotheses based on generally accepted indicators of specialization in this field, including the prioritization of monolingual lexicographical resources over bilingual ones and the higher reliability of primary legal sources over institutional terminological databases and previous translations. Common patterns and variations between institutions and profiles, as well as their implications for institutional terminology management and translation quality, are briefly discussed.

Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential for effective patient allocation and management. To predict patient risk for critical COVID-19 based on status at admission using machine-learning models. Retrospective study based on a database of tertiary medical center with designated departments for patients with COVID-19. Patients with severe COVID-19 at admission, based on low oxygen saturation, low partial arterial oxygen pressure, were excluded. The primary outcome was risk for critical disease, defined as mechanical ventilation, multi-organ failure, admission to the ICU, and/or death. Three different machine-learning models were used to predict patient deterioration and compared to currently suggested predictors and to the APACHEII risk-prediction score. Among 6995 patients evaluated, 162 were hospitalized with non-severe COVID-19, of them, 25 (15.4%) patients deteriorated to critical COVID-19. Machine-learning models outperformed the all other parameters, including the APACHE II score (ROC AUC of 0.92 vs. 0.79, respectively), reaching 88.0% sensitivity, 92.7% specificity and 92.0% accuracy in predicting critical COVID-19. The most contributory variables to the models were APACHE II score, white blood cell count, time from symptoms to admission, oxygen saturation and blood lymphocytes count. Machine-learning models demonstrated high efficacy in predicting critical COVID-19 compared to the most efficacious tools available. Hence, artificial intelligence may be applied for accurate risk prediction of patients with COVID-19, to optimize patients triage and in-hospital allocation, better prioritization of medical resources and improved overall management of the COVID-19 pandemic.

Management of Acute Appendicitis in Covid Pandemic- A Prospective Study of 25 Cases

Acute Appendicitis is a surgical emergency. Patients present with pain in right lower abdomen, with other symptoms like nausea/vomiting, fever, diarrhoea, urinary symptoms. Diagnosis is based on a multimodality approach that includes, clinical, radiological and pathological findings. Alvarado Score helps determine the severity of infection, confirm diagnosis and guide further management. Management is either conservative with antibiotics or surgical depending on severity. However approach to surgical management has changed with the ongoing Covid-19 pandemic. It has necessitated categorisation of surgical procedures into essential and non essential to limit risk to both patient and surgical team and also for prioritization of resources to the rising, continued spread of Covid-19. We present a prospective study of 25 cases of appendicitis presenting during the Covid Pandemic between 15th March and 30th May to our hospital, with an intent to try conservative management for all patients except in the presentations with complications like perforation, abscess or the presence of fecolith or poor response to conservative management.Patients not amenable to conservative management were treated by Open appendicectomy.

Importations of COVID-19 into African countries and risk of onward spread

BackgroundThe emergence of a novel coronavirus (SARS-CoV-2) in Wuhan, China, at the end of 2019 has caused widespread transmission around the world. As new epicentres in Europe and America have arisen, of particular concern is the increased number of imported coronavirus disease 2019 (COVID-19) cases in Africa, where the impact of the pandemic could be more severe. We aim to estimate the number of COVID-19 cases imported from 12 major epicentres in Europe and America to each African country, as well as the probability of reaching 10,000 cases in total by the end of March, April, May, and June following viral introduction.MethodsWe used the reported number of cases imported from the 12 major epicentres in Europe and America to Singapore, as well as flight data, to estimate the number of imported cases in each African country. Under the assumption that Singapore has detected all the imported cases, the estimates for Africa were thus conservative. We then propagated the uncertainty in the imported case count estimates to simulate the onward spread of the virus, until 10,000 cases are reached or the end of June, whichever is earlier. Specifically, 1,000 simulations were run separately under four different combinations of parameter values to test the sensitivity of our results.ResultsWe estimated Morocco, Algeria, South Africa, Egypt, Tunisia, and Nigeria as having the largest number of COVID-19 cases imported from the 12 major epicentres. Based on our 1,000 simulation runs, Morocco and Algeria’s estimated probability of reaching 10,000 cases by end of March was close to 100% under all scenarios. In particular, we identified countries with less than 1,000 cases in total reported by end of June whilst the estimated probability of reaching 10,000 cases by then was higher than 50% even under the most optimistic scenario.ConclusionsOur study highlights particular countries that are likely to reach (or have reached) 10,000 cases far earlier than the reported data suggest, calling for the prioritization of resources to mitigate the further spread of the epidemic.

An e-registry for household contacts exposed to multidrug resistant TB in Mongolia

BackgroundThe WHO recommends that individuals exposed to persons with multidrug resistant tuberculosis (MDRTB) should be screened for active TB and followed up for 2 years to detect and treat secondary cases early. Resource prioritisation means this is rarely undertaken and where it is performed it’s usually using a paper-based record, without collation of data. Electronic data collection into a web-based registry offers the opportunity for simplified and systematic TB contact surveillance with automatic synthesis of data at local, regional and national level. This pilot study was designed to explore the feasibility of usage of a novel e-registry tool and explore obstacles and facilitating factors to implementation.MethodsIn parallel with their paper records, seven dispensaries in Ulaanbaatar, Mongolia collected standardized data electronically using Open Data Kit (ODK). Patients with MDRTB and their contacts were recruited during a single clinic visit. Staff and patients were interviewed to gain insights into acceptability and to identify areas for improvement.ResultsSeventy household contacts of 32 MDR-TB index patients were recruited. 7/70 contacts (10%) traced had active TB at the time they were recruited to the e-registry.Paper registry satisfaction was low; 88% of staff preferred the e-registry as it was perceived as faster and more secure. Patients and their contacts were generally supportive of the e-registry; however, a significant minority 10/42 (24%) of index cases who were invited, declined to participate in the e-registry, with data security cited as their top concern.ConclusionE-registries are a promising tool for MDRTB contact tracing, but their acceptability amongst patients should not be taken for granted.

Towards precision public health: Geospatial analytics and sensitivity/specificity assessments to inform liver cancer prevention.

ObjectivesLiver cancer (LC) continues to rise, partially due to limited resources for prevention. To test the precision public health (PPH) hypothesis that fewer areas in need of LC prevention could be identified by combining existing surveillance data, we compared the sensitivity/specificity of standard recommendations to target geographic areas using U.S. Census demographic data only (percent (%) Hispanic, Black, and those born 1950–1959) to an alternative approach that couples additional geospatial data, including neighborhood socioeconomic status (nSES), with LC disease statistics.MethodsPennsylvania Cancer Registry data from 2007-2014 were linked to 2010 U.S. Census data at the Census tract (CT) level. CTs in the top 80th percentile for 3 standard demographic variables, %Hispanic, %Black, %born 1950–1959, were identified. Spatial scan statistics (SatScan) identified CTs with significantly elevated incident LC rates (p-value<0.05), adjusting for age, gender, diagnosis year. Sensitivity, specificity, and positive predictive value (PPV) of a CT being located in an elevated risk cluster and/or testing positive/negative for at least one standard variable were calculated. nSES variables (deprivation, stability, segregation) significantly associated with LC in regression models (p < 0.05) were systematically evaluated for improvements in sensitivity/specificity.Results9,460 LC cases were diagnosed across 3,217 CTs. 1,596 CTs were positive for at least one of 3 standard variables. 5 significant elevated risk clusters (CTs = 402) were identified. 324 CTs were positive for a high risk cluster AND standard variable (sensitivity = 92%; specificity = 37%; PPV = 17.4%). Incorporation of 3 new nSES variables with one standard variable (%Black) further improved sensitivity (93%), specificity (62.9%), and PPV (26.3%).ConclusionsWe introduce a quantitative assessment of PPH by applying established sensitivity/specificity assessments to geospatial data. Coupling existing disease cluster and nSES data can more precisely identify intervention targets with a liver cancer burden than standard demographic variables. Thus, this approach may inform prioritization of limited resources for liver cancer prevention.

Barriers to addressing mental health issues in childbearing women in Ghana.

AimThe aim of the study is to investigate factors hampering the provision of mental health services by nurses and midwives to childbearing women to assist in the prioritization and distribution of limited mental health resources.DesignThis is a cross‐sectional self‐report study.MethodsData collected from 309 nurses and midwives were analysed using descriptive and inferential statistic, namely chi‐square and analysis of variance (ANOVA).ResultsThe barriers reported by the participants include unavailability of mental health services (77%), lack of knowledge of mental health in women from different tribes (75.7%), lack of a clear mental healthcare pathway (75.1%), heavy workload (74.1%) and lack of knowledge of mental health issue (74.1%). These barriers are less likely to be reported by participants who are males, old and who have practiced for a long time.ConclusionsSystematic effort to restructure the healthcare delivery system, including equipping healthcare professionals with requisite knowledge, skills and competencies in maternal mental health, is highly recommended.

Optimization of an aperiodic sequential inspection and condition-based maintenance policy driven by value of information

The issue of the optimal planning of inspection and maintenance actions for a randomly deteriorating system constitutes a difficult sequential decision-making problem in which the objective is generally to achieve minimal life-cycle cost. For mathematical tractability, most approaches rely either on the consideration of specific maintenance strategies, e.g. Periodic Inspection and Replacement (PIR), whose defining parameters are optimized, or on time-and-space-state discretization using Markov Decision Process (MDP) models and resolution through policy iteration. In both cases, optimality may be hard to guarantee. In this paper, the decision-theoretic concept of Value of Information (VoI) is used as a metric to guide resource prioritization in time, that is, to schedule inspections in a piecewise optimal manner.An aperiodic sequential inspection policy is proposed, where the determination of the next best time for inspection, or replacement, is based on the current condition and on the computed expected gain from possible inspections, i.e. on a VoI metric. This policy can be implemented when the current condition is known from imperfect inspection or processing of condition-monitoring data. Also, more generally, a discussion is proposed on the use of VoI as a guide for information collection in life-cycle management.

Telemediated Training in the Home as a Part of the Everyday Life and Practice With Very Severe Chronic Obstructive Pulmonary Disease.

Patients with very severe chronic obstructive pulmonary disease (COPD) conduct their everyday lives under shortness of breath. The aim of this study was to explore telemediated exercise training to patients at home, with the conduct of everyday life as a theoretical framework. Based on ethnographic fieldwork involving a hospital, two municipalities, and homes of 11 patients from 2013 to 2017, this article shows how telemediated training became part of patients' and partners' everyday lives and the prioritization of time and resources for basic activities. Most of the patients found telemediated training meaningful, that it can work as an agent of hope in holding on to essential everyday life activities, but also that it may be experienced as burdensome and disciplining. The physiotherapists' understanding of the patients' circumstances and needs for rehabilitation changed. The article argues that telemediated training should be offered as part of a palliative approach for those severely affected by COPD.

Reclassifying the Wildland–Urban Interface Using Fire Occurrences for the United States

The wildland–urban interface (WUI) occurs at the intersection of houses and undeveloped wildlands, where fire is a safety concern for communities, motivating investment in planning, protection, and risk mitigation. Because there is no operational definition of WUI based on where fires in fact have occurred, I used fire occurrences to objectively establish a definition of WUI, while examining spatiotemporal changes, for the conterminous United States. I applied four classifiers, but focused on C5.0, which produced equivalent sensitivity (0.87 to 0.91 at prevalence = 0.67) and generated a ruleset that indicated housing density was the preferable basis for definitions. Fire occurrences overall were predicted for housing densities &lt;100 houses/km2 with potentially low (≥10%) thresholds for percent vegetation cover, varying by housing densities and models. A generalized guideline according to classifications is continued use of existing definitions for wildlands of &lt;6.17 houses/km2 and a low-density intermix class of 6.17 to 50 houses/km2. Departing from other definitions, the medium-density class encompasses 50 to 100 houses/km2 and the high-density class is 100 to 200 houses/km2. Interface, or suburban, communities are 200 to 400 houses/km2. Implications of refining the definition include a larger critical area classified as greater fire risk (low and medium-density WUI below 100 houses/km2) at 855,000 km2 during 2010, and; therefore, incorporation of more communities and homeowners into a high-risk status. The low-density class had greatest risk of fire exposure, but the medium-density class contained a greater concentration of houses. Classification of the wildland–urban interface or intermix based on realized fire occurrences provides an objective foundation for identifying residential densities at risk of fire exposure, which permits disclosure of risk, prioritization of resources to communities and homeowners with greater wildfire exposure, development of strategies for communities to coexist with fire, and responses to reduce vulnerability.

Prioritization of Medicine Importation by the Private Sector in Sudan: Evidence from a Data Analysis, 2012-2015

ObjectivesThe objective of this study is to analyze the annual medicines imported by private sector for the period between 2012 and 2015 with the help of priority system based on ABC-VEN matrix analysis and therapeutic category analysis. MethodsA retrospective cross-sectional study was conducted. The Always, Better, and Control (ABC) analysis based on drug expenditure and Vital, Essential, and Nonessential (VEN) analysis based on the criticality of the drugs was performed for annual importation in 2015. ResultsUsing ABC analysis, we found that 47 items (9.2%) accounted for 70% of the budget (class A), whereas a larger numbers of items (344; 67.2%) accounted for only 10% of the importation costs (class C). A moderate number of items (120; 23.5%) comprised 20% of the annual medicine importation value (class B). VEN analysis revealed that 89 items (17.4%) in the vital category constituted 41.6% of the importation value, whereas 349 (68.3%) grouped as essential constituted 45.1% of the value, and 73 (14.2%) of the items considered as nonessential medicines consumed only 13.3% of the total medicines imported in 2015. From the resultant ABC-VEN coupled matrix, three categories were created I, II and III. ConclusionIn view of limited resources, it is important that the existing resources should be utilized appropriately. This study identified a range of suggestions for better medication importation. The ABC and VEN analyses along with the therapeutic category analysis technique are convenient, systematic, and replicable methods and should be adopted for optimization and prioritization of resources.

Initial and Repeated Point Prevalence Surveys to Inform SARS-CoV-2 Infection Prevention in 26 Skilled Nursing Facilities - Detroit, Michigan, March-May 2020.

Skilled nursing facilities (SNFs) are focal points of the coronavirus disease 2019 (COVID-19) pandemic, and asymptomatic infections with SARS-CoV-2, the virus that causes COVID-19, among SNF residents and health care personnel have been described (1-3). Repeated point prevalence surveys (serial testing of all residents and health care personnel at a health care facility irrespective of symptoms) have been used to identify asymptomatic infections and have reduced SARS-CoV-2 transmission during SNF outbreaks (1,3). During March 2020, the Detroit Health Department and area hospitals detected a sharp increase in COVID-19 diagnoses, hospitalizations, and associated deaths among SNF residents. The Detroit Health Department collaborated with local government, academic, and health care system partners and a CDC field team to rapidly expand SARS-CoV-2 testing and implement infection prevention and control (IPC) activities in all Detroit-area SNFs. During March 7-May 8, among 2,773 residents of 26 Detroit SNFs, 1,207 laboratory-confirmed cases of COVID-19 were identified during three periods: before (March 7-April 7) and after two point prevalence surveys (April 8-25 and April 30-May 8): the overall attack rate was 44%. Within 21 days of receiving their first positive test results, 446 (37%) of 1,207 COVID-19 patients were hospitalized, and 287 (24%) died. Among facilities participating in both surveys (n = 12), the percentage of positive test results declined from 35% to 18%. Repeated point prevalence surveys in SNFs identified asymptomatic COVID-19 cases, informed cohorting and IPC practices aimed at reducing transmission, and guided prioritization of health department resources for facilities experiencing high levels of SARS-CoV-2 transmission. With the increased availability of SARS-CoV-2 testing, repeated point prevalence surveys and enhanced and expanded IPC support should be standard tools for interrupting and preventing COVID-19 outbreaks in SNFs.

Estimating Crime Laboratory Efficiency in the Testing of Sexual Assault Kits.

Over the past decade, the large numbers of untested sexual assault kits (SAKs) have been highlighted as a systematic problem that jeopardizes or delays justice for victims. Considering the benefits of testing SAKs, researchers have worked to shed light on why sexual assault evidence has not been effectively submitted to and processed by crime laboratories. Missing from this discourse has been an understanding of the types of practices or qualities that encourage efficiency in the testing of SAKs in crime laboratories. We analyzed results of a national survey administered to all publicly funded state and local crime laboratories (N = 132 respondents) to provide critical information about (i) the extent to which laboratories are testing all of the SAKs possible given the resources they have available; and (ii) the impact that staffing, equipment, policies, and other practices have on SAK testing efficiency. We find that the average laboratory tests only about 69% of the SAKs possible given the resources available to them. However, although technical inefficiencies explain a large proportion of the number of untested SAKs, the accumulation of untested SAKs must also be attributed to laboratories having insufficient resources (e.g., too few forensic analysts). Moreover, results from stochastic frontier models show that doubling the number of forensic analysts in the typical laboratory would allow them to expand their SAK testing capacity by nearly 50%. Implications of these findings are discussed as they relate to the prioritization of resources for crime laboratories, which often operate under strict budgetary realities.

Pharmacists detecting atrial fibrillation in general practice: a qualitative focus group study.

BackgroundAtrial fibrillation (AF) affects up to 10% of people aged ≥65 years, yet a third of all cases remain undetected. Practice-based pharmacists are in an ideal position to facilitate opportunistic AF screening, while increasing general practice capacity at a time of workforce crisis.AimTo explore the perspectives of three stakeholder groups involved in the ‘Pharmacists Detecting Atrial Fibrillation’ (PDAF) study to elucidate the facilitators and barriers to pharmacist-led AF screening in general practice.Design & settingA qualitative study took place, comprising homogeneous focus groups with stakeholders in Kent, UK.MethodThe stakeholder groups — patients, general practice staff (GPS), and clinical pharmacists (CPs) — were recruited using convenience sampling. Audio-recordings were transcribed verbatim and analysed using a deductive Theoretical Domains Framework (TDF) approach.ResultsTwenty-five patients, four pharmacists, and nine practice staff participated in six focus groups. Three main themes were identified: knowledge and awareness; prioritisation of resources; and environmental considerations. The public’s lack of awareness of AF-related risks and pharmacist-led screening services was highlighted. Practice-based pharmacists were perceived as an underutilised educational resource which, together with novel electrocardiogram devices, enabled convenient access to screening while reducing GPs’ workload. Participants agreed that AF screening should be incorporated into personalised health checks and at-risk groups should be prioritised, such as care home residents. Patients favoured the general practice environment over the community pharmacy where concerns of privacy, staffing, and commercialisation were raised.ConclusionThe findings of this study support the introduction of pharmacist-led AF screening programmes in general practice surgeries. Commissioners should consider the added value of utilising CPs and focus on the delivery of AF screening within an integrated service.

Summary from Advanced Manufacturing Technology Workshop Held at 6th Accelerating Biopharmaceutical Development Meeting.

A workshop was held at the 6th Accelerating Biopharmaceutical Development meeting in Carlsbad, CA on February 18, 2019. An anonymous survey was sent to all industry participants before the meeting to identify their top technological barriers to achieving a future manufacturing state and a real-time polling tool was used to collect live feedback during the meeting. Senior leaders from across the biopharmaceutical industry discussed the top technology opportunities to enable high-throughput, flexible manufacturing capabilities and business drivers for the industry. New analytical technologies and upstream operations were identified to be opportunities that could have a profound effect on the shift toward flexible manufacturing. Further discussion at the workshop also identified key business drivers, such as speed, simplicity, and flexibility, as well as the global regulatory environment, to be factors that have a major impact on an organization's ability to implement flexible manufacturing. This workshop has identified industry-wide needs and concerns and can inform future industry-wide initiatives and prioritization of resources to achieve more flexible manufacturing.