Context-specific Data Research Articles

Cause-Specific Mortality Fraction (CSMF) of adult mortality in Butajira, South Central Ethiopia.

Cause- and context-specific mortality data are imperative to understand the extent of health problems in low-income settings, where national death registration and cause of death identification systems are at a rudimentary stage. Aiming to estimate cause-specific mortality fractions, adult (15+ years) deaths between January 2008 and April 2020 were extracted from the Butajira health and demographic surveillance system electronic database. The physician review and a computerized algorithm, InterVA (Interpreting Verbal Autopsy), methods were used to assign the likely causes of death from January 2008 to April 2017 (the first) and May 2017 to April 2020 (the second) phase of the surveillance period, respectively. Initially, adult mortality rates per 1000py across sex and age were summarized. A total of 1,625 deaths were captured in 280, 461 person-years, with an overall mortality rate of 5.8 (95%CI: 5.5, 6.0) per 1000py. Principally, mortality fractions for each specific cause of death were estimated, and for 1,571 deaths, specific causes were determined. During the first phase, the leading cause of death was tuberculosis (13.6%), followed by hypertension (6.6%) and chronic liver disease (5.9%). During the second phase, digestive neoplasms (17.3%), tuberculosis (12.1%), and stroke (9.4%) were the leading causes of death, respectively. Moreover, tuberculosis was higher among persons aged 50+ (15.0%), males (13.8%), and in rural areas (14.1%) during the first phase. Hypertensive diseases were higher among females (7.9%) and in urbanities. In the second phase, digestive neoplasms were higher in the age group of 50-64 years (25.4%) and females (19.0%), and stroke was higher in older adults (65+) (10%) and marginally higher among males (9.7%). Our results showed that tuberculosis and digestive neoplasms were the most common causes of death. Hence, prevention, early detection, and management of cases at all levels of the existing healthcare system should be prioritized to avert premature mortality.

Evaluating Collective Impact Initiatives: A Systematic Scoping Review

Collective impact (CI) is a structured approach that helps drive multi-sector collaborations to address social problems through systems changes. While the CI approach is gaining popularity, practitioners experience challenges in evaluating its implementation and intended outcomes. We conducted a systematic scoping review to understand evaluation methods specific to CI initiatives, identify challenges or limitations with these evaluations, and provide recommendations for the design of CI evaluations. Eighteen studies met the inclusion criteria. Process evaluations were the most frequently used evaluation design. Most studies collected cross-sectional data to evaluate their efforts. The complexity of CI was most frequently cited as the greatest evaluation challenge. Study recommendations primarily focused on improvements during the evaluation planning phase. Taking careful consideration in the planning of CI evaluations, developing context-specific data collection methods, and communicating results intentionally and effectively could prove useful to sufficiently capture and assess this systems-level approach to address social problems.

Pharmaceutical industry relationships with oncologists in sub-Saharan Africa.

Health-care systems in sub-Saharan Africa are considered to be new markets for pharmaceutical companies. This perception is particularly relevant within oncology, as the pharmaceutical industry has changed strategic priorities in the past 10 years to focus on cancer. Since the 1930s, pharmaceutical companies have used advertisements, sample drugs, gifts, paid speaking engagements, advisory boards, and trips to conferences to influence clinical practice and policy. A large amount of literature describes the commonness of these practices and their effects on the behaviour of doctors. However, these data come almost exclusively from high-income countries. Industry-doctor relationships are increasingly common in sub-Saharan Africa and other low-income and middle-income countries. Although there are undoubtedly risks of industry engagement in low-income and middle-income countries, many programmes with educational, research, and clinical value would not occur in these countries without industry support. Thus, what is known about these relationships in high-income countries will not necessarily apply in low-income and middle-income countries. There is a need for widespread discussion about industry-oncologist interactions across the African continent and context-specific data to understand the potential risks and benefits of these relationships.

The cost of implementing the Systems Analysis and Improvement Approach for a cluster randomized trial integrating HIV testing into family planning services in Mombasa County, Kenya

BackgroundAlthough HIV testing in family planning (FP) clinics is a promising approach for engaging women in HIV treatment and prevention services, HIV testing rates are low in FP clinics in Kenya. In 2018, a cluster randomized trial was implemented in Mombasa, Kenya applying the Systems Analysis and Improvement Approach (SAIA) to integrate HIV testing into FP services (1K24HD088229-01). We estimated the incremental costs and explored cost drivers of the FP HIV SAIA implementation in Mombasa, Kenya.MethodsWe conducted a costing evaluation from the payer perspective for the FP HIV SAIA randomized control trial. We identified relevant activities for the intervention including start-up, training, research and FP HIV SAIA. We estimated activity time burden using a time-and motion study. We derived unit costs through staff interviews and programmatic budgets. We present cost estimates for two different scenarios: as-implemented including research and projected costs for a Ministry of Health-supported intervention. All costs are reported in 2018 USD.ResultsFor an annual program output of 36,086 HIV tests administered to new FP clients, we estimated the total annual program cost to be $91,994 with an average cost per new FP client served of $2.55. Personnel and HIV rapid testing kits comprised 55% and 21% of programmatic costs, respectively. Assuming no changes to program outputs and with efficiency gains under the MOH scenario, the estimated cost per new FP client served decreased to $1.30 with a programmatic cost reduction of 49%.ConclusionFP HIV SAIA is a low-cost and flexible implementation strategy for facilitating integrated delivery of HIV testing alongside FP services. Although cost implications of the FP HIV SAIA intervention must continue to be evaluated over time, these findings provide context-specific cost data useful for budget planning and decision-making regarding intervention delivery and expansion.Trial registrationThe trial was registeredon December 15, 2016, with clinicaltrials.gov (NCT02994355).

Cost-Effectiveness of Respiratory Syncytial Virus Preventive Interventions in Children: A Model Comparison Study

ObjectivesModel-based cost-effectiveness analyses on maternal vaccine (MV) and monoclonal antibody (mAb) interventions against respiratory syncytial virus (RSV) use context-specific data and produce varied results. Through model comparison, we aim to characterize RSV cost-effectiveness models and examine drivers for their outputs. MethodsWe compared 3 static and 2 dynamic models using a common input parameter set for a hypothetical birth cohort of 100 000 infants. Year-round and seasonal programs were evaluated for MV and mAb interventions, using available evidence during the study period (eg, phase III MV and phase IIb mAb efficacy). ResultsThree static models estimated comparable medically attended (MA) cases averted versus no intervention (MV, 1019-1073; mAb, 5075-5487), with the year-round MV directly saving ∼€1 million medical and €0.3 million nonmedical costs, while gaining 4 to 5 discounted quality-adjusted life years (QALYs) annually in <1-year-olds, and mAb resulting in €4 million medical and €1.5 million nonmedical cost savings, and 21 to 25 discounted QALYs gained. In contrast, both dynamic models estimated fewer MA cases averted (MV, 402-752; mAb, 3362-4622); one showed an age shift of RSV cases, whereas the other one reported many non-MA symptomatic cases averted, especially by MV (2014). These differences can be explained by model types, assumptions on non-MA burden, and interventions’ effectiveness over time. ConclusionsOur static and dynamic models produced overall similar hospitalization and death estimates, but also important differences, especially in non-MA cases averted. Despite the small QALY decrement per non-MA case, their larger number makes them influential for the costs per QALY gained of RSV interventions.

Justifying the More Restrictive Alternative: Ethical Justifications for One Health AMR Policies Rely on Empirical Evidence.

Global consumption of antibiotics has accelerated the evolution of bacterial antimicrobial resistance. Yet, the risks from increasing bacterial antimicrobial resistance are not restricted to human populations: transmission of antimicrobial resistant bacteria occurs between humans, farms, the environment and other reservoirs. Policies that take a 'One Health' approach deal with this cross-reservoir spread, but are often more restrictive concerning human actions than policies that focus on a single reservoir. As such, the burden of justification lies with these more restrictive policies. We argue that an ethical justification for preferring One Health policies over less restrictive alternatives relies on empirical evidence as well as theory. The ethical justification for these policies is based on two arguments: (i) comparatively greater effectiveness, and (ii) comparatively better tracking of moral responsibility. Yet the empirical assumptions on which these claims rest are limited by existing empirical knowledge. Using livestock farming as an example, we suggest that scientific research into characterising antimicrobial resistance and linking practices to outcomes ought to be guided (at least in part) by the imperative to supply the context-specific data needed to ethically justify preferring a One Health policy over less restrictive alternatives.

Effect of hybrid immunity, school reopening, and the Omicron variant on the trajectory of the COVID-19 epidemic in India: amodelling study.

BackgroundThe course of the COVID-19 pandemic has been driven by several dynamic behavioral, immunological, and viral factors. We used mathematical modeling to explore how the concurrent reopening of schools, increasing levels of hybrid immunity, and the emergence of the Omicron variant affected the trajectory of the pandemic in India, using Andhra Pradesh (pop: 53 million) as an exemplar Indian state.MethodsWe constructed an age- and contact-structured compartmental model that allows for individuals to proceed through various states depending on whether they have received zero, one, or two doses of the COVID-19 vaccine. We calibrated our model using results from another model (ie, INDSCI-SIM) as well as available context-specific serosurvey data. The introduction of the Omicron variant is modelled alongside protection gained from hybrid immunity. We predict disease dynamics in the background of hybrid immunity coming from infections and an ongoing vaccination program, given prior levels of seropositivity from earlier waves of infection. We describe the consequences of school reopening on cases across different age-bands, as well as the impact of the Omicron (BA.2) variant.FindingsWe show the existence of an epidemic peak in India that is strongly related to the value of background seroprevalence. As expected, because children were not vaccinated in India, re-opening schools increases the number of cases in children more than in adults, although in all scenarios, the peak number of active hospitalizations was never greater than 0.45 times the corresponding peak in the Delta wave before schools were reopened. We varied the level of infection induced seropositivity in our model and found the height of the peak associated with schools reopening reduced as background infection-induced seropositivity increased from 20% to 40%. At reported values of seropositivity of 64% from representative surveys done in India, no discernable peak was observed. We also explored counterfactual scenarios regarding the effect of vaccination on hybrid immunity. We found that in the absence of vaccination, even at high levels of seroprevalence (>60%), the emergence of the Omicron variant would have resulted in a large rise in cases across all age bands by as much as 1.8 times. We conclude that the presence of high levels of hybrid immunity resulted in fewer cases in the Omicron wave than in the Delta wave.InterpretationIn India, decreasing prevalence of immunologically naïve individuals of all ages was associated with fewer cases reported once schools were reopened. In addition, hybrid immunity, together with the lower intrinsic severity of disease associated with the Omicron variant, contributed to low reported COVID-19 hospitalizations and deaths.FundingWorld Health Organization, Mphasis

Relevance of sludge management practices and substance modeling in LCA for decision-making: A case study in Chile

Reducing the costs and environmental impacts of sludge management is currently one of the main challenges faced by the wastewater treatment sector. Anaerobic digestion followed by land application has been widely endorsed as a low-impact approach to sludge management, mainly due to the recovery of biogas and the valorization of digestate. However, the influence that the operational conditions of digestion and the management practices of land application can have over the environmental performance of this strategy has been scarcely studied. Furthermore, most of the previous studies dealing with the environmental assessment of this strategy use simplified methods for estimating emissions after land application of sludge, and the lack of systematic accounting of these environmental flows might significantly affect the validity and comparability of the results. Therefore, this work performed an assessment of the influence that 4 relevant practices can have over the environmental impacts of this approach in the context of south-central Chile, providing a mass-balanced inventory for nitrogen, phosphorus and heavy metals in soil based on the ad hoc implementation of models developed for agricultural Life Cycle Assessment (LCA). A total of 16 scenarios were defined and 10 impact categories were evaluated, with the results showing that the environmental impacts were greatly influenced by the variables under study. Overall, solids retention time and the inclusion of pre-treatment mainly influenced climate change, fossil resource depletion and terrestrial ecotoxicity potential, while sludge application rate influenced the eutrophication, water ecotoxicity and human toxicity categories. The type of crop in the receiving soil was a significant driver behind the differences observed in the human toxicity category, which showed the highest variation and relevance in the final weighted result. The results clearly highlight the relevance of using context specific data as well as of quantifying the fate of nutrients, metals and heavy metals during LCA of sludge management. Based on the results, some policy and decision-making recommendations are formulated to optimize the environmental performance of sludge digestion and land application.

A Mixed-Methods Participatory Intervention Design Process to Develop Intervention Options in Immediate Food and Built Environments to Support Healthy Eating and Active Living among Children and Adolescents in Cameroon and South Africa.

Rates of obesity and related non-communicable diseases are on the rise in sub-Saharan Africa, associated with sub-optimal diet and physical inactivity. Implementing evidence-based interventions targeting determinants of unhealthy eating and physical inactivity in children and adolescents’ immediate environments is critical to the fight against obesity and related non-communicable diseases. Setting priorities requires a wide range of stakeholders, methods, and context-specific data. This paper reports on a novel participatory study design to identify and address contextual drivers of unhealthy eating and physical inactivity of children and adolescents in school and in their home neighborhood food and built environments. We developed a three-phase mixed-method study in Cameroon (Yaoundé) and South Africa (Johannesburg and Cape Town) from 2020–2021. Phase one focused on identifying contextual drivers of unhealthy eating and physical inactivity in children and adolescents in each setting using secondary analysis of qualitative data. Phase two matched identified drivers to evidence-based interventions. In phase three, we worked with stakeholders using the Delphi technique to prioritize interventions based on perceived importance and feasibility. This study design provides a rigorous method to identify and prioritize interventions that are tailored to local contexts, incorporating expertise of diverse local stakeholders.

A Pragmatic Approach to Qualitative Formative Evaluation of an Integrated Primary Care Program in Togo, West Africa

Despite the utility of formative evaluation in implementation research, few published projects in low- and middle-income countries have used this approach and incorporating qualitative data into implementation projects can be challenging. Implementation science and qualitative formative evaluation can help inform the delivery of evidence-based practices, specifically identifying gaps in service delivery and implementation fidelity. Including stakeholders in formative evaluation facilitates actionable feedback and practical problem-solving of real-time implementation challenges. This paper presents a real-world example of qualitative formative evaluation that was used to inform the implementation of an integrated healthcare intervention in Togo, West Africa. We organize our results around the five main advantages of implementation-focused formative evaluation that can provide context-specific data useful for implementation teams: (a) highlighting actual versus planned interventions; (b) enabling implementation through identification of modifiable barriers; (c) facilitating any needed refinements in the original implementation intervention; (d) enhancing interpretation of project results; and (e) identifying critical details and guidance necessary for replication of results in other clinical settings. We provide specific examples of how these qualitative findings provide context-specific data and result in actionable steps, with a specific focus on including program implementers and stakeholders in the process. This paper describes lessons learned from the implementation of qualitative implementation-focused formative evaluation.Clinical Trial Registration ClinicalTrials.gov, NCT03694366 (registered 10/03/2018).

Development of Client-Specific Web Service for Manipulating Real-Time Contextual Data

Abstract: The aim of this work was to create a fully functional client-specific solution for accessing real-time context specific data. These kinds of interfaces have been all the buzz in the domain of banking and can help in achieving a faster turn-aroundtime for the queries being asked by the internal users spread all over the globe. These kinds of interfaces provide an effective way to communicate with a user and offer helpful support in a more economical way- saving both time and efforts being spent on accessing real-time data. The application built aims to provide more space for decision making as real-time access is enabled. The study below mainly concentrates on the various techniques used in developing the system for accessing real-time context specific data.

Knowledge of diabetes and associated factors in rural Eastern Cape, South Africa: A cross sectional study.

Diabetes management is complex and requires several lifestyle modifications and engagement in self-management behaviours to prevent complications and to improve health outcomes. Adequate disease knowledge is required in order to engage in appropriate self-management behaviours. Yet, patients' knowledge of diabetes and associated factors are scarcely investigated. Context-specific data on diabetes knowledge are crucial for designing appropriate interventions for improving knowledge and treatment outcomes. This study examined the level of diabetes knowledge and its associated factors among persons with diabetes in Eastern Cape Province, South Africa. We conducted a cross-sectional study among 399 individuals attending diabetes care at six randomly selected primary healthcare facilities in Eastern Cape. Demographic data were obtained through questionnaire interviews while diabetes knowledge was assessed using the validated Michigan Diabetes Knowledge Test questionnaire. Descriptive and inferential statistics were used to assess the mean diabetes knowledge and its associated factors. Participants' median age was 63 (IQR: 54-70) years, and the median diabetes duration was 6 (IQR: 3-13) years. From a total score of 20, participants' knowledge of diabetes ranged from 0 to 17 with an average score of 7.5 (SD±2.2). After controlling for relevant covariates, being employed was positively associated with higher diabetes knowledge (p<0.001). However, health facility level was negatively associated with diabetes knowledge (p = 0.001). Participants receiving care at the community healthcare centres had a lower level of diabetes knowledge compared to those receiving care at the primary healthcare clinics. There was a low level of knowledge on the various components of diabetes management among individuals with diabetes in this setting. Therefore, context-specific interventions to improve the knowledge of diabetes is required and should target unemployed individuals and the community health centres in the region.

Short-term and long-term risk of mortality and neurodevelopmental impairments after bacterial meningitis during infancy in children in Denmark and the Netherlands: a nationwide matched cohort study

SummaryBackgroundFew studies have reported the long-term consequences of bacterial meningitis during infancy, and studies that have been done usually do not include a comparison cohort. We aimed to assess short-term and long-term risk of mortality, neurodevelopmental impairment (NDI), and health-care use and household income in cohorts of children with and without a history of bacterial meningitis during infancy in Denmark and the Netherlands.MethodsIn this nationwide cohort study, infants with a history of bacterial meningitis before age 1 year were identified through the Danish Medical Birth Registry and Danish National Patient Registry using International Classification of Diseases (ICD)-10 codes and through the Netherlands Reference Laboratory for Bacterial Meningitis. Infants were matched (1:10) by sex and birth month and year to a comparison cohort of the general population without a history of bacterial meningitis. We analysed mortality using Cox proportional hazards regression. In Denmark, diagnoses of NDIs were based on ICD-10 codes; in the Netherlands, special educational needs were used as a functional NDI outcome. Risk ratios (RRs) of NDIs were estimated using modified Poisson regression. We also analysed long-term health-care use in Denmark and household income in both countries. All regression analyses were adjusted for sex and year of birth, and stratified by pathogen whenever sample size allowed.FindingsWe included 2216 children with a history of bacterial meningitis (570 [25·7%] in Denmark between Jan 1, 1997, and Dec 31, 2018, and 1646 [74·3%] in the Netherlands between Jan 1, 1995, and Dec 31, 2018), matched to 22 127 comparison cohort members. Median age at diagnosis was 2·8 months (IQR 0·4–7·1) in Denmark and 4·3 months (0·7–7·4) in the Netherlands. Mortality risks within 3 months after disease onset were 3·9% (95% CI 2·6–5·8%) in Denmark and 5·9% (4·7–7·0) in the Netherlands, compared with 0·0% (p<0·0001) and 0·1% (p<0·0001) in the comparison cohorts. Survivors had an increased risk of moderate or severe NDIs at age 10 years (RR 5·0 [95% CI 3·5–7·1] in Denmark and 4·9 [4·0–6·2] in the Netherlands) compared to children in the comparison cohort, particularly after pneumococcal and group B streptococcal meningitis. In Denmark, a history of bacterial meningitis was associated with increased health-care use in the 10 years following diagnosis (rate ratio 4·5 [95% CI 3·9–5·2] for outpatient visits and 4·1 [3·6–4·7] for hospital admissions).InterpretationOur study shows increased risk of mortality in the short and long term, a five times increase in risk of NDIs, and increased health-care use after bacterial meningitis during infancy. Together with context-specific incidence data, our results can advance pathogen-specific estimation of the meningitis burden and inform service provision at the individual and population level.FundingBill & Melinda Gates Foundation, the Stichting Remmert Adriaan Laan Fonds, and the Netherlands Organisation for Health Research and Development.

Bayesian Optimization of Computer-Proposed Multistep Synthetic Routes on an Automated Robotic Flow Platform.

Computer-aided synthesis planning (CASP) tools can propose retrosynthetic pathways and forward reaction conditions for the synthesis of organic compounds, but the limited availability of context-specific data currently necessitates experimental development to fully specify process details. We plan and optimize a CASP-proposed and human-refined multistep synthesis route toward an exemplary small molecule, sonidegib, on a modular, robotic flow synthesis platform with integrated process analytical technology (PAT) for data-rich experimentation. Human insights address catalyst deactivation and improve yield by strategic choices of order of addition. Multi-objective Bayesian optimization identifies optimal values for categorical and continuous process variables in the multistep route involving 3 reactions (including heterogeneous hydrogenation) and 1 separation. The platform’s modularity, robotic reconfigurability, and flexibility for convergent synthesis are shown to be essential for allowing variation of downstream residence time in multistep flow processes and controlling the order of addition to minimize undesired reactivity. Overall, the work demonstrates how automation, machine learning, and robotics enhance manual experimentation through assistance with idea generation, experimental design, execution, and optimization.

A systematic review of methodological approaches for evaluating real-world effectiveness of COVID-19 vaccines: Advising resource-constrained settings.

Real-world effectiveness studies are important for monitoring performance of COVID-19 vaccination programmes and informing COVID-19 prevention and control policies. We aimed to synthesise methodological approaches used in COVID-19 vaccine effectiveness studies, in order to evaluate which approaches are most appropriate to implement in low- and middle-income countries (LMICs). For this rapid systematic review, we searched PubMed and Scopus for articles published from inception to July 7, 2021, without language restrictions. We included any type of peer-reviewed observational study measuring COVID-19 vaccine effectiveness, for any population. We excluded randomised control trials and modelling studies. All data used in the analysis were extracted from included papers. We used a standardised data extraction form, modified from STrengthening the Reporting of OBservational studies in Epidemiology (STROBE). Study quality was assessed using the REal Life EVidence AssessmeNt Tool (RELEVANT) tool. This study is registered with PROSPERO, CRD42021264658. Our search identified 3,327 studies, of which 42 were eligible for analysis. Most studies (97.5%) were conducted in high-income countries and the majority assessed mRNA vaccines (78% mRNA only, 17% mRNA and viral vector, 2.5% viral vector, 2.5% inactivated vaccine). Thirty-five of the studies (83%) used a cohort study design. Across studies, short follow-up time and limited assessment and mitigation of potential confounders, including previous SARS-CoV-2 infection and healthcare seeking behaviour, were major limitations. This review summarises methodological approaches for evaluating real-world effectiveness of COVID-19 vaccines and highlights the lack of such studies in LMICs, as well as the importance of context-specific vaccine effectiveness data. Further research in LMICs will refine guidance for conducting real-world COVID-19 vaccine effectiveness studies in resource-constrained settings.

“Our mothers do not tell us”: a qualitative study of adolescent girls’ perspectives on sexual and reproductive health in rural Nepal

Adolescent girls in low- and middle-income countries continue to face poor sexual and reproductive health (SRH). In Nepal, early marriage and motherhood, gender-based violence, and unmet need for contraception remain pervasive. Adolescent girls in rural areas bear a disproportionate burden of poor reproductive health outcomes, but there are limited context-specific data. This is a qualitative study to identify factors that impact adolescent girls’ utilisation of and access to SRH services in a rural district of Nepal. We conducted 21 individual interviews with adolescent girls aged 15–19 years, and three focus group discussions with community health workers. We used an inductive analytic approach to identify emergent and recurrent themes and present the themes using the social ecological model. Individual-level factors that contribute to low uptake of services among adolescent girls include lack of knowledge, self-perceived lack of need, low decision-making autonomy, and shyness. Interpersonal factors that impact access include unsupportive family norms, absence of open communication, and need for permission from family members to access care. At the community level, disparate gender norms, son preference, and judgment by community members affect adolescent SRH. Inadequate sex education, far travel distance to facilities, lack of female healthcare providers and teachers, and inability to access abortion services were identified as organisational and systems barriers. Stigma was a factor cross-cutting several levels. Our findings suggest the need for multi-level strategies to address these factors to improve adolescent girls’ SRH.

Identification of the Challenges of Life Cycle Costing in Green Construction Projects in Malaysia

Concerns on the effect of construction industry to the environment has driven an increase in sustainable construction activities as well as green initiatives. Life cycle costing (LCC) which is a method of assessing the total cost of ownership of an asset or project has been commonly associated with sustainable-related studies and are used around the world for the last few decades. Even though many benefits have been associated with LCC, its implementation in construction industry is still limited, particularly in green construction projects. This paper aimed to identify the main challenges in implementing LCC in Malaysia’s green construction projects. A quantitative approach via questionnaires survey was conducted on 200 respondents from various backgrounds, namely architects, quantity surveyors, engineers and other professionals typically would be involved in LCC preparation for green construction projects in Malaysia. The questionnaires were distributed to the respondents via traditional mail followed by e-mail as well as online platforms in order to increase the response rate. A total of fifty (50) completed and usable questionnaires were collected and analysed based on mean scores and ranking method. It was discovered that the main challenges of LCC in green construction projects were insufficient project or context specific data and difficulties in carrying out LCC calculations due to absent of proper LCC guidelines or framework. The findings serve as a valid point of reference for industry participants concerned with green developments to improve the LCC process and its adoption in Malaysia’s green construction projects. Efforts must be taken to minimize or ease these challenges perhaps by formulating a framework or guideline specifically designed to address the challenges, thus improving the LCC process and encouraging its adoption in Malaysia which will ultimately contribute towards achieving the world’s green construction agenda.

The Human-Milk Oligosaccharide Profile of Lactating Women in Dhaka, Bangladesh.

ABSTRACTBackgroundHuman-milk oligosaccharides (HMOs) are an abundant component of human milk that have health-related effects on breastfeeding infants. Since variation in HMO composition can be explained by maternal and environmental factors, understanding the diversity in HMOs across settings and identifying context-specific factors associated with HMO abundances is important.ObjectivesThe aim was to describe the HMO profile of Bangladeshi women and to estimate the effect of maternal vitamin D supplementation on HMO composition.MethodsIn a cross-sectional analysis of data and samples from the Maternal Vitamin D for Infant Growth trial in Dhaka, Bangladesh (clinicaltrials.gov; NCT01924013), 192 participants were randomly selected including 96 from each of the placebo and highest-dose vitamin D supplementation groups. In mid-feed breast milk samples collected at a mean (±SD) postpartum age of 93 ± 7 d, absolute and relative abundances of 19 HMOs were analyzed by HPLC. “Secretors” were defined as participants with 2′fucosyllactose concentrations >350 nmol/mL. Associations between HMO concentrations and selected maternal or environmental factors were estimated by multivariable linear regression, adjusting for vitamin D group allocation and secretor status. HMO profiles of Bangladeshi women were compared with data from other international cohorts.ResultsOverall, 34% (65/192) of participants were nonsecretors. Secretor status was associated with the concentrations of total HMOs and 79% (15/19) of individual HMOs. Vitamin D supplementation did not affect the total or individual concentration of any measured HMO. 3-Fucosyllactose concentration was significantly higher in breast milk samples collected in December to February compared with samples collected in March to May. HMO composition was similar to other previously reported cohorts.ConclusionsThe HMO profile of Bangladeshi women is predominantly determined by secretor status. Context-specific HMO data may improve understanding of the effects of HMOs on the infant microbiome and health and guide the development of HMO-containing interventions.

COVID-19 and all-cause-mortality; differential trends between countries and selected states of India

By 22nd January 2021, the Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus had infected over 98 million and 10.6 million individuals globally and in India, with 1.7 million and 153, 067 deaths, respectively. Case Fatality rates (CFR) due to coronavirus disease 2019 (COVID 19) have varied significantly between countries. In order to understand the true impact of the pandemic, we should report coronavirus (COVID-19) mortality in the context of all-cause and non-COVID-19 mortality, and compare with previous years. The consequences of the pandemic have been, and will be, different in different settings within and across countries. To compare the all-cause mortality in the year 2020 with previous years in three selected states of India correlate it to the burden of COVID19 and compare all-cause mortality between three states of India to four high income countries. We provide quantitative data in three states across India (Himachal Pradesh, Kerala and Odisha) and compare with high-income countries to illustrate the importance of context-specific data monitoring and public health responses. There was a 1.9% increase in deaths, with 2.8% decrease in births in 2020, compared to 2019 in Himachal Pradesh, 13.3 and 9.2% decrease in Kerala and 16.7% and 21.4% decrease in Odisha. There was a direct correlation of all cause mortality to CFR on comparison between three states of India and despite the enormous burden of COVID19 in India all-cause mortality was lower compared to previous years in addition to the CFR due to COVID 19 being lower than in selected HICs.

A life cycle-based, sustainability-driven innovation approach in the minerals industry: Application to a large-scale granitic quarry in Rio de Janeiro

Sustainability in mining must be envisioned from a more comprehensive perspective that involves the management of primary and secondary resources and that prioritizes the adoption of innovation beyond a techno-economic mindset. The holistic Life Cycle Assessment (LCA) methodology is useful to diagnose the environmental profile of mining operations seeking a greater contribution to sustainability. This work proposes an enhanced life cycle-based approach for the minerals industry, which is supported by mine-to-product process simulation, scenario analysis, and a comprehensive and context-specific data collection involving the life cycles of the product and the mining project. The convenience of this approach in terms of reducing epistemic uncertainty is demonstrated with a Brazilian case study of a large-scale granitic quarry operation. It is shown that mining can contribute to sustainability by adopting sustainability-driven innovation and circularity principles. The proposed methodology can be applied to other mineral commodities and geographic contexts.