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Abstract Background There are limited data from sub-Saharan Africa describing the demographic characteristics, clinical features and outcome of patients admitted to public hospitals with severe acute respiratory infections during the COVID-19 pandemic. Methods We conducted a prospective longitudinal hospital-based sentinel surveillance between May 2020 and December 2022 at 16 public hospitals in Kenya. All patients aged above 18 years admitted to adult medical wards in the participating hospitals were included. We collected data on demographic and clinical characteristics, SARS-CoV-2 infection and COVID-19 vaccination status and, admission episode outcomes. We determined COVID-19 vaccine effectiveness (VE) against admission with SARS-CoV-2 positive severe acute respiratory illness (SARI) (i.e., COVID-19) and progression to inpatient mortality among patients admitted with SARI, using a test-negative case control design. Results Of the 52,636 patients included in the study, 17,950 (34.1%) were admitted with SARI. The median age was 50 years. Patients were equally distributed across sexes. Pneumonia was the most common diagnosis at discharge. Hypertension, Human Immunodeficiency Virus (HIV) infection and Diabetes Mellitus were the most common chronic comorbidities. SARS-CoV-2 test results were positive in 2,364 (27.9%) of the 8,471 patients that underwent testing. After adjusting for age, sex and presence of a chronic comorbidity, SARI patients were more likely to progress to inpatient mortality compared to non-SARI patients regardless of their SARS-CoV-2 infection status (adjusted odds ratio (aOR) for SARI and SARS-CoV-2 negative patients 1.22, 95% CI 1.10–1.37; and aOR for SARI and SARS-CoV-2 positive patients 1.32, 95% CI 1.24–1.40). After adjusting for age, sex and presence of a chronic comorbidity, COVID-19 VE against progression to inpatient mortality following admission with SARI for those with a confirmed vaccination status was 0.59 (95% CI 0.27–0.77). Conclusion We have provided a comprehensive description of the demographic and clinical pattern of admissions with SARI in Kenyan hospitals during the COVID-19 pandemic period as well as the COVID-19 VE for these patients. These data were useful in providing situational awareness during the first three years of the pandemic in Kenya and informing national response measures.

Abstract In southwestern Uganda, a custom of health and social support has been managed through collective organizations known as engozi for centuries. Subscribers advanced help for those who were not able to provide for themselves and their households. Participants pooled financial and food resources, offered emotional assistance, and aided in transporting patients to hospitals. The institution of “free government health amenities” caused the decline of the engozi custom. However, with an insufficient annual health sector budget allocation, the state health services cannot satisfactorily meet the needs. The Kisiizi neighborhood, while depending on the engozi practice, arrived at a CHI system in 1996 as a self-help innovation to eliminate financial obstacles and enhance access to quality health amenities. Numerous studies on CHI have examined the structure, registration and memberships, health-related advantages, and monetary-related benefits, but little has been documented on how cultural beliefs and customs have affected its application. This study aimed to identify the role of culture and customs in tackling healthcare disparities via a CHI strategy. This study adopted a case study methodology and qualitative methods. The study utilizes Woolcock’s social capital theory and Cultural competence theory as the analytical framework. It identifies Brotherhood, Solidarity, Belonging, Cooperation, Volunteering, Reciprocity, and Respect for Authority and Leaders as key values upheld by the engozi tradition, strengthening social capital and laying a solid foundation for successful CHI. This study also identified that societal values and traditions have significantly impacted the implementation of the Kisiizi CHI scheme, as evidenced by the influence on CHI leadership and governance, collecting premium fees from subscribers, mobilization and registration of participants, and information dissemination. Lastly, the study identified that CHI has positively affected healthcare challenges within the community, evidenced by increased utilization of healthcare services, improved access to antenatal care, health promotion and disease prevention initiatives, and improved quality of services due to user feedback.

Abstract Background In low- and middle-income countries (LMICs), such as Tanzania, the competency of healthcare providers critically influences the quality of pediatric care. To address this issue, we introduced Pediatric Acute Care Education (PACE), an adaptive learning program to enhance provider competency in Tanzania’s guidelines for managing seriously ill children. Adaptive learning is a promising alternative to current in-service education, yet optimal implementation strategies in LMIC settings are unknown. Objectives (1) To evaluate the initial PACE implementation in Mwanza, Tanzania, using the construct of normalization process theory (NPT); (2) To provide insights into its feasibility, acceptability, and scalability potential. Methods Mixed-methods study involving healthcare providers at three facilities. Quantitative data was collected using the Normalization MeAsure Development (NoMAD) questionnaire, while qualitative data was gathered through in-depth interviews (IDIs) and focus groups discussions (FGDs). Results Eighty-two healthcare providers completed the NoMAD survey. Additionally, 24 senior providers participated in IDIs, and 79 junior providers participated in FGDs. Coherence and cognitive participation were high, demonstrating that PACE is well understood and resonates with existing healthcare goals. Providers expressed a willingness to integrate PACE into their practices, distinguishing it from existing educational methods. However, challenges related to resources and infrastructure, particularly those affecting collective action, were noted. Early indicators point toward the potential for long-term sustainability of the PACE, but assessment of reflexive monitoring was limited due to the study’s focus on PACE’s initial implementation. Conclusion This study offers vital insights into the feasibility and acceptability of implementing PACE in a Tanzanian context. While PACE aligns well with healthcare objectives, addressing resource and infrastructure challenges as well as conducting a longer-term study to assess reflexive monitoring is crucial for its successful implementation. Furthermore, the study underscores the value of the NPT as a framework for guiding implementation processes, with broader implications for implementation science and pediatric acute care in LMICs.

Aim This study presents a cutting-edge survey on privacy issues, security attacks, countermeasures and open problems in FL.Methodology The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was used to determine the research domain, establish a search query, and analyze all retrieved articles from the selected scientific databases (i.e. ACM, ArXiv, Google Scholar, IEEE, Scopus, ScienceDirect, and Springer) to meet eligibility criteria and select relevant articles. A total of 1783 articles were retrieved, and 112 articles were deemed eligible for the study.Result This study identified five categories and eleven types of attacks, as well as six types of security attack countermeasures in FL. The results show that privacy and heterogeneity issues are the most common open problems in FL, comprising 38% of the selected articles, while data poisoning emerges as the most common attack, constituting 25% of all attacks identified in the study. The results also show that differential privacy can be used to combat six types of attacks, while anomaly detection can be utilized to combat four types of attacks.Conclusion This study reveals that If researchers and industry experts fail to solve the additional security concerns that occur from transferring training to personal devices and private enterprises, FL adoption may come to a standstill.

The role of artificial intelligence (AI) in education has been extensively studied, focusing on its ability to enhance learning and teaching processes. However, the precise impact of AI adoption on academic performance in open and distance learning (ODL) remains largely unexplored. This systematic literature review critically evaluates AI's impact on academic performance within ODL environments. Drawing from a curated selection of 64 papers from an initial pool of 700, spanning from 2017 to 2023 and sourced from Scopus, Google Scholar, and Web of Science, this study delves into the multifaceted role of AI in enhancing learning outcomes. The meta-analysis reveals a diverse methodological landscape: machine learning methods, employed in 29.69 % of the studies, stand out for their ability to predict academic achievement, which is matched in prevalence by classical statistical methods. Although less common at 3.13 %, hybrid methods are a burgeoning area of research, while a significant 40.63 % of works prioritise nonempirical methods, focusing on theoretical analysis and literature reviews. This investigation highlights the critical factors driving AI adoption in education and its tangible benefits for student performance. It identifies a crucial literature gap: the absence of a process-based framework designed to forecast AI's educational impacts with greater precision, especially across gender and regional lines. By proposing this framework, this study contributes to the academic discourse on AI in education. It underscores the urgent need for structured methodologies to navigate the challenges and opportunities of AI integration. This framework, aligned with UNESCO's 2030 educational objectives, promises to bridge educational divides, ensuring equitable access to quality education across diverse demographics. The findings advocate for future research to design, refine, and test such a framework, paving the way for more inclusive and effective educational technologies in ODL settings.

Abstract Background The prevalence of type 2 diabetes is currently high and still rising, predominantly in developing countries including Ghana. Type 2 diabetes patients’ adherence to recommended diet is shown to improve their health outcomes. This study investigated dietary compliance and its determinants among type 2 diabetes patients in Tamale Metropolis, Ghana. Methods This study employed analytical cross-sectional study design and involved 343 participants selected through systematic random sampling from the outpatient diabetes clinics of Tamale Teaching Hospital, Tamale West Hospital and Tamale Central Hospital. A semi-structured questionnaire was used to document participants’ socio-demographic, lifestyle and clinical characteristics. The modified Morisky dietary adherence scale was used to assess dietary compliance. Bivariate and multivariate analyses were performed to determine the predictors of dietary compliance. Results The mean age of participants was 56.4 ± 15.7 years. More than half of the participants (62.4%) were females. The participants had a higher compliance status (70.6%). The study also revealed that, as a patient’s age increases, compliance decreases [Adjusted odd ratio (AOR): 0.96, 95%, Confidence interval (CI) 0.94–0.99, P = 0.002]. Regarding educational status, patients who completed JHS/Middle School [AOR: 2.458, 95% CI 1.019–5.928, P = 0.045] and SHS/Vocational School [AOR: 2.73, 95% CI 1.08–6.91, P = 0.035] were more likely to comply with dietary recommendations compared to those with no formal education. Conclusion The rate of dietary compliance was high among the study participants. Age and educational status of participants significantly influenced their dietary compliance, suggesting that these factors should be taken into account when developing strategies to enhance dietary adherence.

Much work has been done to understand and improve soil and water conservation where agriculture has driven land use intensification. Less is known about soil- and water-related impacts from intensification driven by solar farming, especially at watershed-scales. Here we employed Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) to model Pond Creek, a rural watershed in Texas, USA. Land use is primarily crop cultivation and secondarily pasture for cattle grazing. Presently, several industrial-scale projects are planned to convert ≈15–30% of Pond Creek from agriculture to solar farms. The model was parameterized using public data sources and information from local stakeholders, then calibrated to several historical precipitation events. Experiments were conducted by varying precipitation depth, duration, and land uses: native vegetation pre-cultivation (control), cultivation (current), current conditions with 15% solar farm conversion (solar), and current conditions with 30% solar farm conversion (solar x2). Shifting to solar farming led to significant increases in cumulative sediment load (+12%–30%), with no significant differences in peak discharge rate changes (+0.38%–4%). Comparison to soil loss tolerance values showed current and solar treatment erosion rates exceeded tolerance values between 0.17 and 2.29 tons per hectare and all treatments were significantly different than the native treatment. We discuss high leverage strategies applicable to solar farm development sites as well as watersheds where they reside. Accelerating demand for land for renewable energy such as solar farming warrants greater attention from the soil and water conservation community to anticipate and mitigate impacts across landscapes.

Abstract Background Pneumonia is a leading cause of childhood morbidity and mortality. Hospital re-admission may signify missed opportunities for care or undiagnosed comorbidities. Methods We conducted a retrospective cohort study including children aged $$\ge$$ ≥ 2 months-14 years hospitalised with severe pneumonia between 2013 and 2021 in a network of 20 primary referral hospitals in Kenya. Severe pneumonia was defined using the 2013 World Health Organization criteria, and re-admission was based on clinical documentation from individual patient case notes. We estimated the prevalence of re-admission, described clinical management practices, and modelled risk factors for re-admission and inpatient mortality. Results Among 20,603 children diagnosed with severe pneumonia, 2,274 (11.0%, 95% CI 10.6–11.5) were readmitted. Re-admission was independently associated with age (12–59 months vs. 2–11 months: adjusted odds ratio (aOR) 1.70, 1.54–1.87; >5 years vs. 2–11 months: aOR 1.85, 1.55–2.22), malnutrition (weight-for-age-z-score (WAZ) -2SD: aOR 2.05, 1.84–2.29); WAZ − 2 to -3 SD vs. WAZ> -2SD: aOR 1.37, 1.20–1.57), wheeze (aOR 1.17, 1.03–1.33) and presence of a concurrent neurological disorder (aOR 4.42, 1.70-11.48). Chest radiography was ordered more frequently among those readmitted (540/2,274 [23.7%] vs. 3,102/18,329 [16.9%], p -2SD: aHR 1.87, 1.71–2.05); WAZ − 2 to -3 SD vs. WAZ >-2SD: aHR 1.46, 1.31–1.63), complete vaccination (aHR 0.74, 0.60–0.91), wheeze (aHR 0.87, 0.78–0.98) and anaemia (aHR 2.14, 1.89–2.43) were independently associated with mortality. Conclusions Children readmitted with severe pneumonia account for a substantial proportion of pneumonia hospitalisations and deaths. Further research is required to develop evidence-based approaches to screening, case management, and follow-up of children with severe pneumonia, prioritising those with underlying risk factors for readmission and mortality.

Abstract Background Intake of a diversified diet is key to the prevention of malnutrition among children as it results in improved intake of energy and micronutrients, which are deemed critical for better nutritional status of children. This study assessed minimum dietary diversity (MDD) and its determinants among children aged 6–23 months in the Sagnarigu Municipality of Ghana. Methods This was an analytical cross-sectional study, carried out in the Sagnarigu Municipality, Ghana and involved 369 mother-child pairs selected through a systematic random sampling. A semi-structured questionnaire was used to obtain respondents’ socio-demographic characteristics, feeding practices, nutritional knowledge and anthropometry. MDD was assessed using a repeated 24-hour dietary recall method. Chi-square/Fisher exact test and binary logistic regression analysis were used to determine the factors associated with MDD. Results The study found that 24.9% of the children were between the ages of 6–8 months and 75.1% were between the ages of 9–23 months. About 64.2% of the children met the MDD. Children of mothers who were self-employed were approximately 2 times more likely to meet the MDD as compared to children of mothers who were unemployed [Adjusted Odd Ratio (AOR): 1.93, 95% CI (1.13–3.31), P = 0.017]. Also, children aged 9–23 months were approximately 14 times more likely to meet MDD as compared to younger children aged 6–8 months [AOR: 13.98, 95% CI (7.54–25.91), P

Urban climatologist particularly those interested in Urban Heat Island (UHI), require some form of explanations to UHI variations at both spatial and temporal scales in cities. Temperature cooling and warming rate can be use as a form of explanations for spatial and temporal variations for UHI intensity characteristics of an area. This study therefore, assessed variations in temperature warming and cooling rates in Jalingo. The study used temperature data collected at six locations representing six different thermal climate zones in the study area. Temperature data were collected for the period of 90 days thirty days in each of rainy season, dry season, and hamattan period. Simple statistical analysis was performed to determine the warming and cooling rates. The results indicate that temperature warm and cool differently in the study area. The results also revealed that general warming in the area within the study period begins at 8:00 h local time (GMT +1) with warming rate ranging from 0.94°C to 1.75°C across locations with a mean of 1.30°C. Cooling starts at 15:00 h ranging from -0.88°C to -1.84°C with an average of -1.48°C. It is recommended that environmental planners particularly the urban planners and Architectures should take into considerations the warming and cooling rates in their building design and also embrace appropriate landscaping to improve thermal comfort.

The Northern Gulf of Mexico hosts a severe dead zone, an oxygen-depleted area spanning 1,618,000 hectares, threatening over 40% of the U.S. fishing industry and causing annual losses of USD 82 million. Using a System Dynamics (SD) approach, this study examined the Mississippi–Atchafalaya River Basin (MARB), a major contributor to hypoxia in the Gulf. A dynamic model, developed with Vensim software version 10.2.1 andexisting data, represented the physical, biological, and chemical processes leading to eutrophication and simulated dead zone formation over time. Various policies were assessed, considering natural system variability. The findings showed that focusing solely on nitrogen control reduced the dead zone but required greater intensity or managing other inputs to meet environmental goals. Runoff control policies delayed nutrient discharge but did not significantly alter long-term outcomes. Extreme condition tests highlighted the critical role of runoff dynamics, dependent on nitrogen load relative to flow volume from upstream. The model suggests interventions should not just reduce eutrophication inputs but enhance factors slowing down the process, allowing natural denitrification to override anthropogenic nitrification.

Introduction To improve healthcare provider knowledge of Tanzanian newborn care guidelines, we developed adaptive Essential and Sick Newborn Care (aESNC), an adaptive e-learning environment. The objectives of this study were to (1) assess implementation success with use of in-person support and nudging strategy and (2) describe baseline provider knowledge and metacognition.Methods 6-month observational study at one zonal hospital and three health centres in Mwanza, Tanzania. To assess implementation success, we used the Reach, Efficacy, Adoption, Implementation and Maintenance framework and to describe baseline provider knowledge and metacognition we used Howell’s conscious-competence model. Additionally, we explored provider characteristics associated with initial learning completion or persistent activity.Results aESNC reached 85% (195/231) of providers: 75 medical, 53 nursing and 21 clinical officers; 110 (56%) were at the zonal hospital and 85 (44%) at health centres. Median clinical experience was 4 years (IQR 1–9) and 45 (23%) had previous in-service training for both newborn essential and sick newborn care. Efficacy was 42% (SD ±17%). Providers averaged 78% (SD ±31%) completion of initial learning and 7% (SD ±11%) of refresher assignments. 130 (67%) providers had ≥1 episode of inactivity >30 day, no episodes were due to lack of internet access. Baseline conscious-competence was 53% (IQR: 38%–63%), unconscious-incompetence 32% (IQR: 23%–42%), conscious-incompetence 7% (IQR: 2%–15%), and unconscious-competence 2% (IQR: 0%–3%). Higher baseline conscious-competence (OR 31.6 (95% CI 5.8 to 183.5)) and being a nursing officer (aOR: 5.6 (95% CI 1.8 to 18.1)), compared with medical officer, were associated with initial learning completion or persistent activity.Conclusion aESNC reach was high in a population of frontline providers across diverse levels of care in Tanzania. Use of in-person support and nudging increased reach, initial learning and refresher assignment completion, but refresher assignment completion remains low. Providers were often unaware of knowledge gaps, and lower baseline knowledge may decrease initial learning completion or activity. Further study to identify barriers to adaptive e-learning normalisation is needed.

[This corrects the article DOI: 10.1371/journal.pone.0258040.].

BackgroundStunting and wasting are key public health problems in Ghana that are significantly linked with mortality and morbidity risk among children. However, information on their associated factors using nationally representative data is scanty in Ghana. This study investigated the influence of Infant and Young Child Feeding (IYCF) indicators, socio-demographic and economic related factors, and water and sanitation on stunting and wasting, using nationally representative data in Ghana.MethodsThis is a secondary data analysis of the most recent (2017/2018) Ghana Multi-Indicator Cluster Survey (MICS) datasets. The multi-indicator cluster survey is a national cross-sectional household survey with rich data on women of reproductive age and children under the age of five. The survey used a two-stage sampling method in the selection of respondents and a computer-assisted personal interviewing technique to administer structured questionnaires from October 2017 to January 2018. The present study involved 2529 mother-child pairs, with their children aged 6 to 23 months. We used the Complex Sample procedures in SPSS, adjusting for clustering and stratification effects. In a bivariate logistic regression, variables with P-values ≤ 0.05 were included in a backward multivariate logistic regression to identify the significant factors associated with stunting and wasting.ResultsThe mean age of children was 14.32 ± 0.14 months, with slightly more being males (50.4%). About 12% and 16% of the children were wasted and stunted, respectively. There were 39.4%, 25.9%, and 13.7% of children who, respectively, satisfied the minimum meal frequency (MMF), minimum dietary diversity (MDD), and minimum acceptable diet (MAD). None of the IYCF indicators was significantly associated with stunting or wasting in the multivariate analysis but low socio-economic status, low birth weight, being a male child and unimproved toilet facilities were significantly associated with both wasting and stunting.ConclusionOur findings suggest that aside from the pre-natal period, in certain contexts, household factors such as low socio-economic status and poor water and sanitation, may be stronger predictors of undernutrition. A combination of nutrition-specific and nutrition-sensitive interventions including the pre-natal period to simultaneously address the multiple determinants of undernutrition need strengthening.

Abstract Biohybrid robots have been developed for biomedical applications and industrial robotics. However, the biohybrid robots have limitations to be applied in neurodegenerative disease research due to the absence of a central nervous system. In addition, the organoids‐on‐a‐chip has not yet been able to replicate the physiological function of muscle movement in the human motor system, which is essential for evaluating the accuracy of the drugs used for treating neurodegenerative diseases. Here, a human motor system‐based biohybrid robot‐on‐a‐chip composed of a brain organoid, multi‐motor neuron spheroids, and muscle bundle on solid substrateis proposed to evaluate the drug effect on neurodegenerative diseases for the first time. The electrophysiological signals from the cerebral organoid induced the muscle bundle movement through motor neuron spheroids. To evaluate the drug effect on Parkinson's disease (PD), a patient‐derived midbrain organoid is generated and incorporated into a biohybrid robot‐on‐a‐chip. The drug effect on PD is successfully evaluated by measuring muscle bundle movement. The muscle bundle movement of PD patient‐derived midbrain organoid‐based biohybrid robot‐on‐a‐chip is increased from 4.5 ± 0.99 µm to 18.67 ± 2.25 µm in response to levodopa. The proposed human motor system‐based biohybrid robot‐on‐a‐chip can serve as a standard biohybrid robot model for drug evaluation.

The paper presents the results of studying the spatial and seasonal atmospheric temperature characteristics of Jalingo metropolis, Nigeria, with the aim of assessing seasonal temperature variations for thermal comfort planning. Temperature data for this study was collected across the local climate zones, otherwise known as thermal climate zones (TCZ), following the TZC classification of the area. Temperature data was collected for 30 days continuously and simultaneously across the TCZ. The collection of temperature data was done in the months of April and August 2021, and January 2022 – representing the dry season, the rainy season and the Harmattan period respectively. A Thermochron Ibutton sensor by Maxim Incorporation was used to collect temperature data, while the specific series used was DS1921. An improvised automated weather station was constructed to house the sensor. The result of the study indicates that air temperature varies considerably within Jalingo metropolis, as well as throughout the seasons, thus affecting human thermal comfort in the study area, as temperature is found to correlate well with both human morbidity and mortality, especially regarding cardiovascular diseases. The paper recommends increasing ventilation and nature-based solution to reduce high temperatures through tree planting in order to improve human thermal comfort in Jalingo metropolis area.

Abstract Several in-situ electrochemical approaches have been developed for performing a localized photoelectrochemical investigation of the photoanode. One of the techniques is scanning electrochemical microscopy (SECM), which probes local heterogeneous reaction kinetics and fluxes of generated species. In traditional SECM analysis of photocatalysts, evaluation of the influence of radiation on the rate of studied reaction requires an additional dark background experiment. Here, using SECM and an inverted optical microscope, we demonstrate the determination of O2 flux caused by light-driven photoelectrocatalytic water splitting. Photocatalytic signal and dark background are recorded in a single SECM image. We used an indium tin oxide electrode modified with hematite (α-Fe2O3) by electrodeposition as a model sample. The light-driven flux of oxygen is calculated by analysis of SECM image recorded in substrate generation/tip collection mode. In photoelectrochemistry, the qualitative and quantitative knowledge of oxygen evolution will open new doors for understanding the local effects of dopants and hole scavengers in a straightforward and conventional manner.

Background:Throat infections are one of the commonest causes for visits to health care physicians. It was hypothesized that some rare Gram negative bacteria could be implicated in respiratory infections. The molecular dynamics of clinically-significant Gram negative bacteria associated with lower respiratory tract infections was also ascertained. This study investigated the prevalence and antibiotic susceptibility pattern of bacteria associated with throat infections in a hospital setting. Methods: Two hundred and five (205) throat swabs were collected from patients at the study area. Bacterial isolates were identified based on their morphological and biochemical profile. The molecular identity of selected multidrug resistant bacterial isolates was conducted via DNA extraction, polymerase chain reaction (PCR) amplification, sequencing and genome blasting. Antibiotic susceptibility of the test bacterial isolates was evaluated using Kirby-Bauer disc diffusion method. Results: The highest frequency of carriers of throat pathogens was obtained among male patients between ages 31 and 40 years. Streptococcus pneumoniae (28%)had the highest prevalence while Escherichia coli (4%) had the least. One of the enumerated Enterobacter species from the samples was further identified via 16S ribosomal ribose-nucleic acid (rRNA) as Enterobacter bugandensis MH712497.1. Staphylococcus aureus and Streptococcus pyogenes were resistant to gentamicin whilst both Gram-negative bacteria were susceptible to ciprofloxacin at 21.00±0.58mm and 20.00±0.58 mm respectively.Conclusion: This study deduced that Streptococcus species is most implicated bacteria responsible for throat infections in clinical setting. Molecularly-identified Enterobacter bugandensis from throat infections in this study has recently being implicated as a fresh enterobacteria associated with severe clinically-significant infection.

Objectives: Many regions of Africa have experienced lower COVID-19 morbidity and mortality than Europe. Pre-existing humoral responses to endemic human coronaviruses (HCoV) may cross-protect against SARS-CoV-2. We investigated the neutralizing capacity of SARS-CoV-2 spike reactive and nonreactive immunoglobulin (Ig)G and IgA antibodies in prepandemic samples. Methods: To investigate the presence of pre-existing immunity, we performed enzyme-linked immunosorbent assay using spike antigens from reference SARS-CoV-2, HCoV HKU1, OC43, NL63, and 229E using prepandemic samples from Kilifi in coastal Kenya. In addition, we performed neutralization assays using pseudotyped reference SARS-CoV-2 to determine the functionality of the identified reactive antibodies. Results: We demonstrate the presence of HCoV serum IgG and mucosal IgA antibodies, which cross-react with the SARS-CoV-2 spike. We show pseudotyped reference SARS-CoV-2 neutralization by prepandemic serum, with a mean infective dose 50 of 1: 251, which is 10-fold less than that of the pooled convalescent sera from patients with COVID-19 but still within predicted protection levels. The prepandemic naso-oropharyngeal fluid neutralized pseudo-SARS-CoV-2 at a mean infective dose 50 of 1: 5.9 in the neutralization assay. Conclusion: Our data provide evidence for pre-existing functional humoral responses to SARS-CoV-2 in Kilifi, coastal Kenya and adds to data showing pre-existing immunity for COVID-19 from other regions.

Globally, inadequate healthcare provider (HCP) proficiency with evidence-based guidelines contributes to millions of newborn, infant, and child deaths each year. HCP guideline proficiency would improve patient outcomes. Conventional (in person) HCP in-service education is limited in 4 ways: reach, scalability, adaptability, and the ability to contextualize. Adaptive e-learning environments (AEE), a subdomain of e-learning, incorporate artificial intelligence technology to create a unique cognitive model of each HCP to improve education effectiveness. AEEs that use existing internet access and personal mobile devices may overcome limits of conventional education. This paper provides an overview of the development of our AEE HCP in-service education, Pediatric Acute Care Education (PACE). PACE uses an innovative approach to address HCPs’ proficiency in evidence-based guidelines for care of newborns, infants, and children. PACE is novel in 2 ways: 1) its patient-centric approach using clinical audit data or frontline provider input to determine content and 2) its ability to incorporate refresher learning over time to solidify knowledge gains. We describe PACE's integration into the Pediatric Association of Tanzania's (PAT) Clinical Learning Network (CLN), a multifaceted intervention to improve facility-based care along a single referral chain. Using principles of co-design, stakeholder meetings modified PACE's characteristics and optimized integration with CLN. We plan to use three-phase, mixed-methods, implementation process. Phase I will examine the feasibility of PACE and refine its components and protocol. Lessons gained from this initial phase will guide the design of Phase II proof of concept studies which will generate insights into the appropriate empirical framework for (Phase III) implementation at scale to examine effectiveness.

Abstract Background Understanding the age patterns of disease is necessary to target interventions to maximise cost-effective impact. New malaria chemoprevention and vaccine initiatives target young children attending routine immunisation services. Here we explore the relationships between age and severity of malaria hospitalisation versus malaria transmission intensity. Methods Clinical data from 21 surveillance hospitals in East Africa were reviewed. Malaria admissions aged 1 month to 14 years from discrete administrative areas since 2006 were identified. Each site-time period was matched to a model estimated community-based age-corrected parasite prevalence to provide predictions of prevalence in childhood (PfPR2–10). Admission with all-cause malaria, severe malaria anaemia (SMA), respiratory distress (RD) and cerebral malaria (CM) were analysed as means and predicted probabilities from Bayesian generalised mixed models. Results 52,684 malaria admissions aged 1 month to 14 years were described at 21 hospitals from 49 site-time locations where PfPR2–10 varied from

Background: The Kilifi Health and Demographic Surveillance System (KHDSS) was established in 2000 to define the incidence and prevalence of local diseases and evaluate the impact of community-based interventions. KHDSS morbidity data have been reported comprehensively but mortality has not been described. This analysis describes mortality in the KHDSS over 16 years. Methods: We calculated mortality rates from 2003–2018 in four intervals of equal duration and assessed differences in mortality across these intervals by age and sex. We calculated the period survival function and median survival using the Kaplan–Meier method and mean life expectancies using abridged life tables. We estimated trend and seasonality by decomposing a time series of monthly mortality rates. We used choropleth maps and random-effects Poisson regression to investigate geographical heterogeneity. Results: Mortality declined by 36% overall between 2003–2018 and by 59% in children aged

The epidemiology of pediatric COVID-19 in sub-Saharan Africa and the role of fecal-oral transmission in SARS-CoV-2 are poorly understood. Among children and adolescents in Kenya, we identify correlates of COVID-19 infection, document the clinical outcomes of infection, and evaluate the prevalence and viability of SARS-CoV-2 in stool. We recruited a prospective cohort of hospitalized children aged two months to 15 years in western Kenya between March 1 and June 30 2021. Children with SARS-CoV-2 were followed monthly for 180-days after hospital discharge. Bivariable logistic regression analysis was used to identify the clinical and sociodemographics correlates of SARS-CoV-2 infection. We also calculated the prevalence of SARS-CoV-2 detection in stool of confirmed cases. Of 355 systematically tested children, 55 (15.5%) were positive and were included in the cohort. The commonest clinical features among COVID-19 cases were fever (42/55, 76%), cough (19/55, 35%), nausea and vomiting (19/55, 35%), and lethargy (19/55, 35%). There were no statistically significant difference in baseline sociodemographic and clinical characteristics between SARS-CoV-2 positive and negative participants. Among positive participants, 8/55 (14.5%, 95%CI: 5.3%-23.9%) died; seven during the inpatient period. Forty-nine children with COVID-19 had stool samples or rectal swabs available at baseline, 9 (17%) had PCR-positive stool or rectal swabs, but none had SARS-CoV-2 detected by culture. Syndromic identification of COVID-19 is particularly challenging among children as the presenting symptoms and signs mirror other common pediatric diseases. Mortality among children hospitalized with COVID-19 was high in this cohort but was comparable to mortality seen with other common illnesses in this setting. Among this small set of children with COVID-19 we detected SARS-CoV-2 DNA, but were not able to culture viable SARs-CoV-2 virus, in stool. This suggests that fecal transmission may not be a substantial risk in children recently diagnosed and hospitalized with COVID-19 infection.

Cyberattacks are becoming more sophisticated and ubiquitous. Cybercriminals are inevitably adopting Artificial Intelligence (AI) techniques to evade the cyberspace and cause greater damages without being noticed. Researchers in cybersecurity domain have not researched the concept behind AI-powered cyberattacks enough to understand the level of sophistication this type of attack possesses. This paper aims to investigate the emerging threat of AI-powered cyberattacks and provide insights into malicious used of AI in cyberattacks. The study was performed through a three-step process by selecting only articles based on quality, exclusion, and inclusion criteria that focus on AI-driven cyberattacks. Searches in ACM, arXiv Blackhat, Scopus, Springer, MDPI, IEEE Xplore and other sources were executed to retrieve relevant articles. Out of the 936 papers that met our search criteria, a total of 46 articles were finally selected for this study. The result shows that 56% of the AI-Driven cyberattack technique identified was demonstrated in the access and penetration phase, 12% was demonstrated in exploitation, and command and control phase, respectively; 11% was demonstrated in the reconnaissance phase; 9% was demonstrated in the delivery phase of the cybersecurity kill chain. The findings in this study shows that existing cyber defence infrastructures will become inadequate to address the increasing speed, and complex decision logic of AI-driven attacks. Hence, organizations need to invest in AI cybersecurity infrastructures to combat these emerging threats.

Electricity propels economic development through improvement in the quality of life. Even though government's strategy to increase power generation and supply exists, Uganda experiences regular power outages and has one of the lowest electrification rates in the world. This study employs a systematic review approach and extends securitisation theory to the electricity sector to characterise electricity security and assess its barriers in Uganda. In this context, five dimensions of electricity security are identified and compared. Based on this set of dimensions, results show that Uganda is electricity “insecure.” Further, six (6) barriers to electricity security in Uganda are identified, and each of them is assessed as either existential, potential, or both. Thus, interventions that alleviate or mitigate these barriers can improve Uganda's electricity security. A quantitative empirical analysis using longitudinal data could offer superior evidence and conclusion on electricity security in Uganda.

SARS-CoV-2 was first detected in Kenya in March 2020 and there was evidence of local transmission in the following months. Here, the authors characterise the early stages of the epidemic in coastal Kenya using phylogenetics and find evidence of multiple strain importations from international points of entry.

This interdisciplinary, conceptual analysis addresses the nature and benefits of artistic processes in learning and work. While recognizing various forms of artistry, the emphasis is on visual-spatial thinking. The benefits of this kind of thinking in academic and professional activities include the simplification of massively complex writing, improvement of psychological functioning, and the magnification of creative work in various professions, especially in science, technology, engineering, and mathematics (STEM) fields. Visual-spatial thinking also is a strength that often helps twice-exceptional individuals overcome their learning difficulties. Several thinking and learning strategies are explored, including visual data animation, concept cartooning, visual metaphor, and musical translation of written material. Some ways that visual-spatial thinking can help overcome the problems generated by dogmatic school reform also are scrutinized.

Policymakers in Africa need robust estimates of the current and future spread of SARS-CoV-2. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya up to the end of September 2020, which encompasses the first wave of SARS-CoV-2 transmission in the country. We estimate that the first wave of the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 30-50% of residents infected. Our analysis suggests, first, that the reported low COVID-19 disease burden in Kenya cannot be explained solely by limited spread of the virus, and second, that a 30-50% attack rate was not sufficient to avoid a further wave of transmission.

Background A few studies have assessed the epidemiological impact and the cost-effectiveness of COVID-19 vaccines in settings where most of the population had been exposed to SARS-CoV-2 infection.Methods We conducted a cost-effectiveness analysis of COVID-19 vaccine in Kenya from a societal perspective over a 1.5-year time frame. An age-structured transmission model assumed at least 80% of the population to have prior natural immunity when an immune escape variant was introduced. We examine the effect of slow (18 months) or rapid (6 months) vaccine roll-out with vaccine coverage of 30%, 50% or 70% of the adult (>18 years) population prioritising roll-out in those over 50-years (80% uptake in all scenarios). Cost data were obtained from primary analyses. We assumed vaccine procurement at US$7 per dose and vaccine delivery costs of US$3.90–US$6.11 per dose. The cost-effectiveness threshold was US$919.11.Findings Slow roll-out at 30% coverage largely targets those over 50 years and resulted in 54% fewer deaths (8132 (7914–8373)) than no vaccination and was cost saving (incremental cost-effectiveness ratio, ICER=US$−1343 (US$−1345 to US$−1341) per disability-adjusted life-year, DALY averted). Increasing coverage to 50% and 70%, further reduced deaths by 12% (810 (757–872) and 5% (282 (251–317) but was not cost-effective, using Kenya’s cost-effectiveness threshold (US$919.11). Rapid roll-out with 30% coverage averted 63% more deaths and was more cost-saving (ICER=US$−1607 (US$−1609 to US$−1604) per DALY averted) compared with slow roll-out at the same coverage level, but 50% and 70% coverage scenarios were not cost-effective.Interpretation With prior exposure partially protecting much of the Kenyan population, vaccination of young adults may no longer be cost-effective.

The fast and wireless estimation of moisture in sand and other bulk materials usually requires high-tech instrumentation and computation. To overcome the complexity of such systems, we have employed bipolar electrochemistry as a fast, straightforward, and cost-effective method to wirelessly produce an optical signal. An electric field generated across moist sand is used to polarize an immersed light-emitting diode (LED), triggering an electrochemical reaction and causing a current to flow. Therefore, the bipolar activation of the LED by a threshold electric field creates an optically readable moisture sensor. The light emission intensity depends on two factors: the amount of moisture and the salt concentration. As two stimuli control the light emission, the signal can be considered as an AND logic gate, which is expected to open possibilities in wireless and user-friendly moisture sensors.

Anxiety is a common co-occurring condition for autistic students; however, little is known about how anxiety may affect their social or academic outcomes in an educational setting. Furthermore, the perspectives of students themselves have rarely been included in the literature. Using Q-sort method, 45 autistic participants aged 7 to 17 years identified the outcomes they perceived were most impacted by their anxiety in the educational setting. The three outcomes most highly rated as being impacted by anxiety overall were academic outcomes. Using by-person factor analysis, six distinct factors, or 'viewpoints', were identified. These viewpoints reflect different combinations of outcomes affected by anxiety, including missing school or activities, reduced interactions with friends, reduced classroom communication and finding it harder to complete schoolwork. This study adds to the literature by using Q-sort method to enable autistic children and adolescents to report the impacts of their anxiety. Anxiety has additional impacts on the social and academic outcomes of autistic students, highlighting the need for increased awareness and training for parents and professionals, an individualised approach to student support and further research regarding the relationship between anxiety and academic outcomes.

The reported burden of SARS-CoV-2 has been relatively low in tropical Africa compared to Europe and the Americas, but estimating true infection rates is challenging. Here, the authors screen blood donors in Kenya for SARS-CoV-2 antibodies and describe spatiotemporal seroprevalence dynamics.

Abstract Background Prominent activation of microglial immune/inflammatory processes is a characteristic feature of brains of patients with tauopathies including Alzheimer’s disease (AD), suggesting that neuroinflammation may be a critical factor in their pathogenesis. Strategies aimed at developing new therapeutics for tauopathies based on anti-inflammation or immunomodulation are likely to be promising avenues of research. We previously developed JM4—a 19’mer cyclic peptide derived from the first loop of human erythropoietin. This peptide possesses beneficial immune modulatory and tissue protective effects while lacking the undesirable side effects of full-length erythropoietin. In this preclinical study, we investigated the effect of chronic JM4 treatment on the PS19 mouse that carries the P301S mutant human tau gene, linked to a form of frontotemporal dementia. This transgenic mouse has been widely used as a model of tauopathies including AD and related dementias. Methods Daily subcutaneous treatment of female PS19 mice with JM4 was initiated before disease onset and continued on for the animals’ lifespan. The progression of neurological deficit and the lifespan of these mice were assessed. To evaluate the effect of JM4 treatment on cognition of these animals, the PS19 mice underwent Barnes maze test and elevated plus maze test. In addition, neuronal loss, phosphorylated tau aggregation, and microglial activation were assessed using immunohistochemistry of PS19 mouse brain sections. Results JM4 treatment of PS19 mice initiated before disease onset reduced neurological deficit, prolonged lifespan, and rescued memory impairment. The beneficial effects of JM4 were accompanied by reductions in neuronal loss, phosphorylated tau aggregation, and microglial activation in the PS19 mouse brain. Limitations Use of a single dose of JM4 and female mice only. Conclusion JM4 is a potential novel therapeutic agent for the treatment of tauopathies including AD and related dementias.

Background: Detailed understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) regional transmission networks within sub-Saharan Africa is key for guiding local public health interventions against the pandemic. Methods: Here, we analysed 1139 SARS-CoV-2 genomes from positive samples collected between March 2020 and February 2021 across six counties of Coastal Kenya (Mombasa, Kilifi, Taita Taveta, Kwale, Tana River, and Lamu) to infer virus introductions and local transmission patterns during the first two waves of infections. Virus importations were inferred using ancestral state reconstruction, and virus dispersal between counties was estimated using discrete phylogeographic analysis. Results: During Wave 1, 23 distinct Pango lineages were detected across the six counties, while during Wave 2, 29 lineages were detected; 9 of which occurred in both waves and 4 seemed to be Kenya specific (B.1.530, B.1.549, B.1.596.1, and N.8). Most of the sequenced infections belonged to lineage B.1 (n = 723, 63%), which predominated in both Wave 1 (73%, followed by lineages N.8 [6%] and B.1.1 [6%]) and Wave 2 (56%, followed by lineages B.1.549 [21%] and B.1.530 [5%]). Over the study period, we estimated 280 SARS-CoV-2 virus importations into Coastal Kenya. Mombasa City, a vital tourist and commercial centre for the region, was a major route for virus imports, most of which occurred during Wave 1, when many Coronavirus Disease 2019 (COVID-19) government restrictions were still in force. In Wave 2, inter-county transmission predominated, resulting in the emergence of local transmission chains and diversity. Conclusions: Our analysis supports moving COVID-19 control strategies in the region from a focus on international travel to strategies that will reduce local transmission. Funding: This work was funded by The Wellcome (grant numbers: 220985, 203077/Z/16/Z, 220977/Z/20/Z, and 222574/Z/21/Z) and the National Institute for Health and Care Research (NIHR), project references: 17/63/and 16/136/33 using UK Aid from the UK government to support global health research, The UK Foreign, Commonwealth and Development Office. The views expressed in this publication are those of the author(s) and not necessarily those of the funding agencies.

Urban landscapes homogenize our world at global scales, contributing to “extinction of experience”, a progressive decline in human interactions with native greenspace that can disconnect people from the services it provides. College age adults report feeling disconnected from nature more than other demographics, making universities a logical place to explore interventions intended to restore a connection with nature. This study surveyed 1088 students and staff across four university campus communities in Southern California, USA and used multicriteria decision analysis to explore their landscape preferences and the implications of those preferences for combatting extinction of experience. Our results suggest that perspectives of, and preferences for, different greenspace forms vary significantly (i.e., they are not perceived as substitutable). Support for native ecosystems, particularly coastal sage scrub (top ranked landscape) was generally high, suggesting that disaffection with wild nature is not particularly widespread. Programs for replacing turf grass lawns (lowest ranked landscape) with native plants were also well supported, but support for stormwater bioswales was more moderate (and variable). This may reflect their relative newness, both on university campuses and in urban spaces more generally. Not all members of campus communities preferred the same landscapes; preferences differed with degree of pro-environmentalism and university status (undergraduate student, graduate student, staff). Even so, all respondents exhibited landscape preferences consistent with at least one approach for combatting extinction of experience, suggesting that ecologists, engineers and urban planners have a viable set of generalizable tools for reconnecting people with nature.

Abstract Ideal sillenite type Bi12FeO20 (BFO) micron sized single crystals have been successfully grown via inexpensive hydrothermal method. The refined single crystal X-ray diffraction data reveals cubic Bi12FeO20 structure with single crystal parameters. Occurrence of rare Fe4+ state is identified via X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS). The lattice parameter (a) and corresponding molar volume (V m ) of Bi12FeO20 have been measured in the temperature range of 30–700 °C by the X-ray diffraction method. The thermal expansion coefficient (α) 3.93 × 10–5 K−1 was calculated from the measured values of the parameters. Electronic structure and density of states are investigated by first principle calculations. Photoelectrochemical measurements on single crystals with bandgap of 2 eV reveal significant photo response. The photoactivity of as grown crystals were further investigated by degrading organic effluents such as Methylene blue (MB) and Congo red (CR) under natural sunlight. BFO showed photodegradation efficiency about 74.23% and 32.10% for degrading MB and CR respectively. Interesting morphology and microstructure of pointed spearhead like BFO crystals provide a new insight in designing and synthesizing multifunctional single crystals.

Abstract Objective This study sought to assess maternal growth monitoring knowledge and its effect on stunting, wasting and underweight among children 0–18 months in the Tamale Metropolis. An analytical cross-sectional study design, involving 340 mother–child pairs randomly selected from 4 health facilities in the Tamale Metropolis was used. A structured questionnaire was used to collect information on socio-demographic characteristics and maternal growth monitoring knowledge. Weight and length of children were taken to assess nutritional status (stunting, underweight and wasting). Chi square/Fisher’s exact test was used to determine the association between maternal growth monitoring knowledge level and child nutritional status. Results The study revealed that 87.6% of mothers had good knowledge on growth monitoring. The prevalence of stunting, underweight and wasting were 9.4%, 25.9% and 17.9% respectively. Bivariate analysis revealed that there is no association between maternal growth monitoring knowledge and stunting (p = 0.781), wasting (p = 0.743) and underweight (p = 0.529) among children 0–18 months in the Tamale Metropolis.

Policymakers in Africa need robust estimates of the current and future spread of SARS-CoV-2. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya up to the end of September 2020, which encompasses the first wave of SARS-CoV-2 transmission in the country. We estimate that the first wave of the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 30-50% of residents infected. Our analysis suggests, first, that the reported low COVID-19 disease burden in Kenya cannot be explained solely by limited spread of the virus, and second, that a 30-50% attack rate was not sufficient to avoid a further wave of transmission.

BackgroundMost of the studies that have informed the public health response to the COVID-19 pandemic in Kenya have relied on samples that are not representative of the general population. We conducted population-based serosurveys at three Health and Demographic Surveillance Systems (HDSSs) to determine the cumulative incidence of infection with SARS-CoV-2.MethodsWe selected random age-stratified population-based samples at HDSSs in Kisumu, Nairobi and Kilifi, in Kenya. Blood samples were collected from participants between 01 Dec 2020 and 27 May 2021. No participant had received a COVID-19 vaccine. We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Locally-validated assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. We adjusted prevalence estimates using classical methods and Bayesian modelling to account for the sampling scheme and assay performance.ResultsWe recruited 2,559 individuals from the three HDSS sites, median age (IQR) 27 (10-78) years and 52% were female. Seroprevalence at all three sites rose steadily during the study period. In Kisumu, Nairobi and Kilifi, seroprevalences (95% CI) at the beginning of the study were 36.0% (28.2-44.4%), 32.4% (23.1-42.4%), and 14.5% (9.1-21%), and respectively; at the end they were 42.0% (34.7-50.0%), 50.2% (39.7-61.1%), and 24.7% (17.5-32.6%), respectively. Seroprevalence was substantially lower among children (ConclusionBy May 2021 in three broadly representative populations of unvaccinated individuals in Kenya, seroprevalence of anti-SARS-CoV-2 IgG was 25-50%. There was wide variation in cumulative incidence by location and age.

Introduction The high proportion of SARS-CoV-2 infections that have remained undetected presents a challenge to tracking the progress of the pandemic and estimating the extent of population immunity. Methods We used residual blood samples from women attending antenatal care services at three hospitals in Kenya between August 2020 and October 2021and a validated IgG ELISA for SARS-Cov-2 spike protein and adjusted the results for assay sensitivity and specificity. We fitted a two-component mixture model as an alternative to the threshold analysis to estimate of the proportion of individuals with past SARS-CoV-2 infection. Results We estimated seroprevalence in 2,981 women; 706 in Nairobi, 567 in Busia and 1,708 in Kilifi. By October 2021, 13% of participants were vaccinated (at least one dose) in Nairobi, 2% in Busia. Adjusted seroprevalence rose in all sites; from 50% (95%CI 42–58) in August 2020, to 85% (95%CI 78–92) in October 2021 in Nairobi; from 31% (95%CI 25–37) in May 2021 to 71% (95%CI 64–77) in October 2021 in Busia; and from 1% (95% CI 0–3) in September 2020 to 63% (95% CI 56–69) in October 2021 in Kilifi. Mixture modelling, suggests adjusted cross-sectional prevalence estimates are underestimates; seroprevalence in October 2021 could be 74% in Busia and 72% in Kilifi. Conclusions There has been substantial, unobserved transmission of SARS-CoV-2 in Nairobi, Busia and Kilifi Counties. Due to the length of time since the beginning of the pandemic, repeated cross-sectional surveys are now difficult to interpret without the use of models to account for antibody waning.

Objectives To characterise adoption and explore specific clinical and patient factors that might influence pulse oximetry and oxygen use in low-income and middle-income countries (LMICs) over time; to highlight useful considerations for entities working on programmes to improve access to pulse oximetry and oxygen.Design A multihospital retrospective cohort study.Settings All admissions (n=132 737) to paediatric wards of 18 purposely selected public hospitals in Kenya that joined a Clinical Information Network (CIN) between March 2014 and December 2020.Outcomes Pulse oximetry use and oxygen prescription on admission; we performed growth-curve modelling to investigate the association of patient factors with study outcomes over time while adjusting for hospital factors.Results Overall, pulse oximetry was used in 48.8% (64 722/132 737) of all admission cases. Use rose on average with each month of participation in the CIN (OR: 1.11, 95% CI 1.05 to 1.18) but patterns of adoption were highly variable across hospitals suggesting important factors at hospital level influence use of pulse oximetry. Of those with pulse oximetry measurement, 7% (4510/64 722) had hypoxaemia (SpO2