Mixed-effects Negative Binomial Models Research Articles

Impact of four years of annually repeated indoor residual spraying (IRS) with Actellic 300CS on routinely reported malaria cases in an agricultural setting in Malawi.

Indoor residual spraying (IRS) is one of the main vector control tools used in malaria prevention. This study evaluates IRS in the context of a privately run campaign conducted across a low-lying, irrigated, sugarcane estate from Illovo Sugar, in the Chikwawa district of Malawi. The effect of Actellic 300CS annual spraying over four years (2015-2018) was assessed using a negative binomial mixed effects model, in an area where pyrethroid resistance has previously been identified. With an unadjusted incidence rate ratio (IRR) of 0.38 (95% CI: 0.32-0.45) and an adjusted IRR of 0.50 (95% CI: 0.42-0.59), IRS has significantly contributed to a reduction in case incidence rates at Illovo, as compared to control clinics and time points outside of the six month protective period. This study shows how the consistency of a privately run IRS campaign can improve the health of employees. More research is needed on the duration of protection and optimal timing of IRS programmes.

How turtles keep their cool: Seasonal and diel basking patterns in a tropical turtle

Behavioural thermoregulation by ectotherms is an important mechanism for maintaining body temperatures to optimise physiological performance. Experimental studies suggest that nocturnal basking by Krefft's river turtles (Emydura macquarii krefftii) in the tropics may allow them to avoid high water temperatures, however, this hypothesis has yet to be tested in the field. In this study, we examined the influence of environmental temperature on seasonal and diel patterns of basking in E. m. krefftii in tropical north Queensland, Australia. Wildlife cameras were used to document turtle basking events for seven consecutive days and nights for each month over a year (April 2020–March 2021). Air and water temperatures were recorded simultaneously using temperature loggers. We used a negative binomial mixed effects model to compare mean basking durations (min) occurring among four environmental temperature categories based on population thermal preference (26 °C): 1) air temperature above and water temperature below preferred temperature; 2) air temperature below and water temperature above preferred temperature; 3) air and water temperatures both above preferred temperature; and 4) air and water temperatures both below preferred temperature. Basking behaviour was influenced significantly by the relationship between air and water temperature. During the day, turtles spent significantly less time basking when both air and water temperatures were above their preferred temperatures. Conversely, at night, turtles spent significantly more time basking when water temperatures were warm and air temperatures were cool relative to their preferred temperature. This study adds to the growing body of work indicating pronounced heat avoidance as a thermoregulatory strategy among tropical reptile populations.

Impact of pneumococcal conjugate vaccine 13 introduction on severe lower respiratory tract infections associated with respiratory syncytial virus or influenza virus in hospitalized children in Ulaanbaatar, Mongolia

ObjectivesLimited data indicate a beneficial effect of pneumococcal conjugate vaccines (PCVs) on respiratory syncytial virus (RSV) and influenza infections in young children. We evaluated the impact of 13-valent PCV (PCV13) introduction on the incidence of severe lower respiratory tract infections (LRTIs) associated with RSV or influenza in hospitalized children. MethodsOur study was restricted to children aged <2 years with arterial oxygen saturation <93% and children with radiologically confirmed pneumonia nested in a pneumonia surveillance project in four districts of Ulaanbaatar city, Mongolia. We tested nasopharyngeal swabs collected on admission for RSV and influenza using quantitative reverse transcription-polymerase chain reaction. The impact of PCV13 on the incidence of LRTI outcomes associated with RSV or with influenza for the period April 2015-March 2020 was estimated. Incidence rate ratios comparing pre- and post-vaccine periods were estimated for each outcome for each district using negative binomial models and for all districts combined with a mixed-effects negative binomial model. Adjusted models accounted for seasonality. Sensitivity analyses were conducted to assess the robustness of our findings. ResultsAmong 5577 tested cases, the adjusted incidence rate ratios showed a trend toward a reduction in RSV-associated outcomes: all LRTIs (0.77, 95% confidence interval [CI] 0.44-1.36), severe LRTIs (0.88, 95% CI 0.48-1.62), very severe LRTIs (0.76, 95% CI 0.42-1.38), and radiologically confirmed pneumonia (0.66, 95% CI 0.32-1.38) but inconsistent trends in outcomes associated with influenza. ConclusionsNo significant reductions were observed in any outcomes associated with RSV and influenza after PCV introduction.

Public health engagement in alcohol licensing in England and Scotland: the ExILEnS mixed-method, natural experiment evaluation.

International systematic reviews suggest an association between alcohol availability and increased alcohol-related harms. Alcohol availability is regulated through separate locally administered licensing systems in England and Scotland, in which local public health teams have a statutory role. The system in Scotland includes a public health objective for licensing. Public health teams engage to varying degrees in licensing matters but no previous study has sought to objectively characterise and measure their activity, examine their effectiveness, or compare practices between Scotland and England. To critically assess the impact and mechanisms of impact of public health team engagement in alcohol premises licensing on alcohol-related harms in England and Scotland. We recruited 39 diverse public health teams in England (n = 27) and Scotland (n = 12). Public health teams more active in licensing were recruited first and then matched to lower-activity public health teams. Using structured interviews (n = 66), documentation analysis, and expert consultation, we developed and applied the Public Health Engagement In Alcohol Licensing (PHIAL) measure to quantify six-monthly activity levels from 2012 to 2019. Time series of PHIAL scores, and health and crime outcomes for each area, were analysed using multivariable negative binomial mixed-effects models to assess correlations between outcome and exposure, with 18-month average PHIAL score as the primary exposure metric. In-depth interviews (n = 53) and a workshop (n = 10) explored public health team approaches and potential mechanisms of impact of alcohol availability interventions with public health team members and licensing stakeholders (local authority licensing officers, managers and lawyers/clerks, police staff with a licensing remit, local elected representatives). Nineteen public health team activity types were assessed in six categories: (1) staffing; (2) reviewing and (3) responding to licence applications; (4) data usage; (5) influencing licensing stakeholders/policy; and (6) public involvement. Usage and intensity of activities and overall approaches varied within and between areas over time, including between Scotland and England. The latter variation could be explained by legal, structural and philosophical differences, including Scotland's public health objective. This objective was felt to legitimise public health considerations and the use of public health data within licensing. Quantitative analysis showed no clear evidence of association between level of public health team activity and the health or crime outcomes examined, using the primary exposure or other metrics (neither change in, nor cumulative, PHIAL scores). Qualitative data suggested that public health team input was valued by many licensing stakeholders, and that alcohol availability may lead to harms by affecting the accessibility, visibility and norms of alcohol consumption, but that the licensing systems have limited power to act in the interests of public health. This study provides no evidence that public health team engagement in local licensing matters was associated with measurable downstream reductions in crime or health harms, in the short term, or over a 7-year follow-up period. The extensive qualitative data suggest that public health team engagement is valued and appears to be slowly reorienting the licensing system to better address health (and other) harms, especially in Scotland, but this will take time. A rise in home drinking, alcohol deliveries, and the inherent inability of the licensing system to reduce - or in the case of online sales, to contain - availability, may explain the null findings and will continue to limit the potential of these licensing systems to address alcohol-related harms. Further analysis could consider the relative success of different public health team approaches in terms of changing alcohol availability and retailing. A key gap relates to the nature and impact of online availability on alcohol consumption, harms and inequalities, alongside development and study of relevant policy options. A national approach to licensing data and oversight would greatly facilitate future studies and public health input to licensing. Our interview data and therefore PHIAL scores may be limited by recall bias where documentary evidence of public health activity was not available, and by possible variability in grading of such activity, though steps were taken to minimise both. The analyses would have benefited from additional data on licensing policies and environmental changes that might have affected availability or harms in the study areas. The study was registered with the Research Registry (researchregistry6162) on 26 October 2020. The study protocol was published in BMC Medical Research Methodology on 6 November 2018. This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme as award number 15/129/11.

Exploring the link between the increase in high-rise buildings and youth jumping suicide in Taiwan: A longitudinal study.

From 2010 to 2021, suicide rates in 15-24 age group in Taiwan increased by 70%, with jumping being the most common method in 2021. We examined the link between the rise in youth suicides and the increase in high-rise buildings during this period. Spearman's correlation coefficients and negative binomial mixed-effects models were employed to assess the association between the increase in high-rise buildings and jumping suicides over time. Spearman's correlation coefficients of high-rise buildings and jumping suicide rates in youth decreased from 0.692 (p < 0.001) in 2010 to 0.354 (p = 0.11) in 2021. Negative binomial mixed-effects models showed that although jumping suicide rates in youths increased over time, the increase in numbers of high-rise buildings was not related to rates of youth suicide by jumping. Conversely, in older age groups, the correlations were still prominent. Despite the rising trend in youth suicides by jumping over the past 11 years, our study refutes the intuitive notion that the increase in high-rise buildings contributes to this trend. It is imperative to identify and address other potential factors, such as academic stress and/or family disruptions, for effective prevention of youth suicide.

Does a blended learning implementation package enhance HIV index case testing in Malawi? A protocol for a cluster randomised controlled trial

IntroductionIndex case testing (ICT) is an evidence-based approach that efficiently identifies persons in need of HIV treatment and prevention services. In Malawi, delivery of ICT has faced challenges due to...

Impact of childhood 13-valent pneumococcal conjugate vaccine introduction on adult pneumonia hospitalisations in Mongolia: a time series analysis

IntroductionFew studies have assessed the potential indirect effects of childhood pneumococcal conjugate vaccine (PCV) programs on the adult pneumonia burden in resource-limited settings. We evaluated the impact of childhood PCV13 immunisation on adult all-cause pneumonia following a phased program introduction from 2016. MethodsWe conducted a time-series analysis to assess changes in pneumonia hospitalisation incidence at four district hospitals in Mongolia. Adults (≥18 years) that met the clinical case definition for all-cause pneumonia were enrolled. A negative binomial mixed-effects model was used to assess the impact of PCV13 introduction on monthly counts of pneumonia admissions from January 2015—February 2022. We also performed a restricted analysis excluding the COVID-19 pandemic period. All models were stratified by age and assessed separately. Additional analyses assessed the robustness of our findings. FindingsThe average annual incidence of all-cause pneumonia hospitalisation was highest in adults 65+ years (62·81 per 10,000 population) and declined with decreasing age. After adjusting for the COVID-19 pandemic period, we found that rates of pneumonia hospitalisation remained largely unchanged over time. We did not observe a reduction in pneumonia hospitalisations in any age group. Results from restricted and sensitivity analyses were comparable to the primary results, finding limited evidence of a reduced pneumonia burden. InterpretationWe did not find evidence of indirect protection against all-cause pneumonia in adults following childhood PCV13 introduction. Direct pneumococcal vaccination and other interventions should be considered to reduce burden of pneumonia among older adults. FundingPfizer clinical research collaboration agreement (contract number: WI236621).

Subthreshold opioid use disorder prevention (STOP) trial: a cluster randomized clinical trial: study design and methods

BackgroundPreventing progression to moderate or severe opioid use disorder (OUD) among people who exhibit risky opioid use behavior that does not meet criteria for treatment with opioid agonists or antagonists (subthreshold OUD) is poorly understood. The Subthreshold Opioid Use Disorder Prevention (STOP) Trial is designed to study the efficacy of a collaborative care intervention to reduce risky opioid use and to prevent progression to moderate or severe OUD in adult primary care patients with subthreshold OUD.MethodsThe STOP trial is a cluster randomized controlled trial, randomized at the PCP level, conducted in 5 distinct geographic sites. STOP tests the efficacy of the STOP intervention in comparison to enhanced usual care (EUC) in adult primary care patients with risky opioid use that does not meet criteria for moderate-severe OUD. The STOP intervention consists of (1) a practice-embedded nurse care manager (NCM) who provides patient participant education and supports primary care providers (PCPs) in engaging and monitoring patient-participants; (2) brief advice, delivered to patient participants by their PCP and/or prerecorded video message, about health risks of opioid misuse; and (3) up to 6 sessions of telephone health coaching to motivate and support behavior change. EUC consists of primary care treatment as usual, plus printed overdose prevention educational materials and an educational video on cancer screening. The primary outcome measure is self-reported number of days of risky (illicit or nonmedical) opioid use over 180 days, assessed monthly via text message using items from the Addiction Severity Index and the Current Opioid Misuse Measure. Secondary outcomes assess other substance use, mental health, quality of life, and healthcare utilization as well as PCP prescribing and monitoring behaviors. A mixed effects negative binomial model with a log link will be fit to estimate the difference in means between treatment and control groups using an intent-to-treat population.DiscussionGiven a growing interest in interventions for the management of patients with risky opioid use, and the need for primary care-based interventions, this study potentially offers a blueprint for a feasible and effective approach to improving outcomes in this population.Trial Registration: Clinicaltrials.gov, identifier NCT04218201, January 6, 2020.

Air pollution, mortality, and hospital admissions in Scotland: A 16 years register-based study

Abstract Background Air pollution is associated with poor health and higher mortality. However, studies that link high spatial resolution air pollution data for several pollutants to individual-level data over prolonged period (&amp;gt;10 years) and assess multiple health outcomes are limited. In this study, we investigated the association between 16-years exposure to air pollution and all-cause and cause-specific (cardiovascular, respiratory, cancer, infectious, and mental/behavioural disorders) mortality and hospital admissions in Scotland. Methods Individual-level data from the “Scottish Longitudinal Study” for 202,237 individuals (2002-2017) were linked to yearly concentrations of NO2, SO2, PM10, and PM2.5 pollutants at 1-Km2 spatial resolution using the individual's residential postcode. The association between air pollution and mortality and hospital admissions was examined using Cox Proportional-Hazards and multilevel mixed-effects negative binomial models, respectively. Results Increasing concentrations of PM2.5, PM10, and NO2 pollutants were associated with higher rates of all-cause, cardiovascular, respiratory, cancer, and infectious mortality and hospital admissions. Mortality from respiratory diseases increased by 6.2% (95%CI=2.8%−9.6%), 2.5% (95%CI=0.5%−4.5%), and 1.2% (95%CI=0.5%−1.9%) per 1 µg/m3 increase in PM2.5, PM10 and NO2 pollutants, respectively. Exposure to SO2 was mainly linked to mental/behavioural disorders mortality (HR = 1.05; 95%CI=1.02-1.07) and respiratory hospital admissions (IRR=1.02; 95%CI=1.01-1.03). Conclusions This study revealed a positive association between air pollution and mortality and hospital admissions in Scotland. Interventions on air pollution through stricter environmental regulations could help ease the mortality and hospital admission burden, for both physical and mental illness. Key messages • Air pollution is associated with a higher risk of mortality and hospital admissions for both physical and mental health-related outcomes. • Policymakers are urged to provide incentives for the usage of greener energy sources to reduce air pollution emissions.

The implementation of infection prevention and control measures and health care utilisation in ACF-supported health facilities during the COVID-19 pandemic in Kinshasa, Democratic Republic of the Congo, 2020

ABSTRACT Background Infection prevention and control (IPC) was a central component of the Democratic Republic of the Congo’s COVID-19 response in 2020, aiming to prevent infections and ensure safe health service provision. Objectives We aimed to assess the evolution of IPC capacity in 65 health facilities supported by Action Contre la Faim in three health zones in Kinshasa (Binza Meteo (BM), Binza Ozone (BO), and Gombe), investigate how triage and alert validation were implemented, and estimate how health service utilisation changed in these facilities (April–December 2020). Methods We used three datasets: IPC Scorecard data assessing health facilities’ IPC capacity at baseline, monthly and weekly triage data, and monthly routine data on eight health services. We examined factors associated with triage and isolation capacity with a mixed-effects negative binomial model and estimated changes in health service utilisation with a mixed-model with random intercept and long-term trend for each health facility. We reported incidence rate ratios (IRRs) for level change when the pandemic began, for trend change, and for lockdown and post-lockdown periods (Gombe). We estimated cumulative and monthly percent differences with expected consultations. Results IPC capacity reached an average score of 90% by the end of the programme. A one-point increase in the IPC score was associated with +6% and +5% increases in triage capacity in BO and Gombe, respectively, and with +21% and +10% increases in isolation capacity in the same zones. When the pandemic began, decreases were seen in outpatient consultations (IRR: 0.67, 95% confidence interval (CI) [0.48–0.95] BM&BO-combined; IRR: 0.29, 95%CI [0.16–0.53] Gombe), consultations for respiratory tract infections (IRR: 0.48, 95%CI [0.28–0.87] BM&BO-combined), malaria (IRR: 0.60, 95%CI [0.43–0.84] BM&BO-combined, IRR: 0.33, 95%CI [0.18–0.58] Gombe), and vaccinations (IRR: 0.27, 95%CI [0.10–0.71] Gombe). Maternal health services decreased in Gombe (ANC1: IRR: 0.42, 95%CI [0.21–0.85]). Conclusions The effectiveness of the triage and alert validation process was affected by the complexity of implementing a broad clinical definition in limited-resource settings with a pre-pandemic epidemiological profile characterised by infectious diseases with symptoms like COVID-19. Readily available testing capacity remains key for future pandemic response to improve the disease understanding and maintain health services.

Comparison of different statistical models for the analysis of fracture events: findings from the Prevention of Falls Injury Trial (PreFIT)

BackgroundFractures are rare events and can occur because of a fall. Fracture counts are distinct from other count data in that these data are positively skewed, inflated by excess zero counts, and events can recur over time. Analytical methods used to assess fracture data and account for these characteristics are limited in the literature.MethodsCommonly used models for count data include Poisson regression, negative binomial regression, hurdle regression, and zero-inflated regression models. In this paper, we compare four alternative statistical models to fit fracture counts using data from a large UK based clinical trial evaluating the clinical and cost-effectiveness of alternative falls prevention interventions in older people (Prevention of Falls Injury Trial; PreFIT).ResultsThe values of Akaike information criterion and Bayesian information criterion, the goodness-of-fit statistics, were the lowest for negative binomial model. The likelihood ratio test of no dispersion in the data showed strong evidence of dispersion (chi-square = 225.68, p-value < 0.001). This indicates that the negative binomial model fits the data better compared to the Poisson regression model. We also compared the standard negative binomial regression and mixed effects negative binomial models. The LR test showed no gain in fitting the data using mixed effects negative binomial model (chi-square = 1.67, p-value = 0.098) compared to standard negative binomial model.ConclusionsThe negative binomial regression model was the most appropriate and optimal fit model for fracture count analyses.Trial registrationThe PreFIT trial was registered as ISRCTN71002650.

Air pollution, mortality, and hospital admissions in Scotland: A 16 years register-based study

BackgroundAir pollution is associated with poor health and higher mortality. However, studies that link high spatial resolution air pollution data for several pollutants to individual-level data over prolonged period (&gt;10 years) and assess multiple health outcomes are limited. In this study, we investigated the association between 16-years exposure to air pollution and all-cause and cause-specific (cardiovascular, respiratory, cancer, infectious, and mental/behavioural disorders) mortality and hospital admissions in Scotland.&#x0D; MethodsIndividual-level data from the “Scottish Longitudinal Study” for 202,237 individuals (2002-2017) were linked to yearly concentrations of NO2, SO2, PM10, and PM2.5 pollutants at 1-Km2 spatial resolution using the individual’s residential postcode. The association between air pollution and mortality and hospital admissions was examined using Cox Proportional-Hazards and multilevel mixed-effects negative binomial models, respectively.&#x0D; ResultsIncreasing concentrations of PM2.5, PM10, and NO2 pollutants were associated with higher rates of all-cause, cardiovascular, respiratory, cancer, and infectious mortality and hospital admissions. Mortality from respiratory diseases increased by 6.2% (95%CI=2.8%-9.6%), 2.5% (95%CI=0.5%-4.5%), and 1.2% (95%CI=0.5%-1.9%) per 1 µg/m3 increase in PM2.5, PM10 and NO2 pollutants, respectively. Exposure to SO2 was mainly linked to mental/behavioural disorders mortality (HR=1.05; 95%CI=1.02-1.07) and respiratory hospital admissions (IRR=1.02; 95%CI=1.01-1.03).&#x0D; ConclusionsThis study revealed a positive association between air pollution and mortality and hospital admissions in Scotland. Interventions on air pollution through stricter environmental regulations could help ease the mortality and hospital admission burden, for both physical and mental illness.

Nursing 12-Hour Shifts and Patient Incidents in Mental Health and Community Hospitals: A Longitudinal Study Using Routinely Collected Data

Shifts of 12 hours or longer are common in nursing services within general hospital wards. Concerns have been raised about their safety, but previous research has mostly used staff-reported measures of quality and safety and has occurred in general hospital settings only. This study aims to measure the association between the use of 12+ hour shifts in nursing staff (including registered nurses, healthcare support workers or nursing assistants, and nursing associates) and the rate of patient incidents in mental health and community hospitals. This is a longitudinal study using routinely collected data from two mental health and community NHS trusts in the South of England. We accessed rosters of nursing staff and patient incident data from April 2018 to March 2021. We extracted 1,018,971 shifts and excluded those not worked by nursing staff, with a final sample of 898,143 shifts. We extracted 53,078 incidents. We only included incidents that involved patients and that occurred in wards. Our final sample consisted of 38,373 patient incidents. We linked all patient incidents and nurses’ worked shifts at the ward-day level. Depending on the distribution of incident rates, we used either negative binomial mixed-effects models or Poisson mixed-effect models to investigate the association between the proportion of 12+ hour shifts and all patient incidents, violence against staff, falls, self-injury, disruptive behaviour, and medication management incidents at the ward-day level. We found a relationship between 12+ hour shifts and the incident rate. Compared to days in wards with no long shifts, increasing the proportion of long shifts was initially associated with a small increase in the overall rate of incidents, but the rate increased sharply as the proportion of long shifts was above 70%. Rates of self-injury increased more steadily as the proportion of long shifts increased. The mandatory implementation of long shifts should be discouraged.

Impact of COVID-19 epidemic on temporal pattern of new HIV diagnoses in Italy, 2021 database.

New HIV diagnoses in Italy decreased drastically in 2020 due to COVID-19 related effects: 50% fewer diagnoses were reported by the National HIV Surveillance System. COVID-19 pandemic impact on HIV surveillance is unclear. We estimated the expected number of new HIV diagnoses in 2020 in order to isolate the impact of the COVID-19 pandemic. We analyzed 29697 new HIV infections diagnosed from 2012 to 2020, reported to the National HIV Surveillance System. We assessed temporal trends of new HIV diagnoses applying negative binomial mixed effects models. We estimated the COVID-19 impact as the difference between the model-estimated slopes from 2012 to 2019 and the change reported in the diagnoses. The expected number of new HIV diagnoses in 2020 was also estimated and compared with the reported count. Based on the historical trend, we expected a 15% (95% CI: 5-25%) decline of new HIV diagnoses in 2020. We reported, however, a 49% decrease, yielding to a 34% net decrease in the number of new diagnoses. The strongest impact was estimated in northern regions (-40%) and MSM (-38%). We estimated 761 (95% prediction interval: 350-1277) missed diagnoses during 2020, the majority of them occurring in the North (465 cases), among MSM (416) and heterosexual males (217). In 2020, when excluding 15% decrease of new diagnoses attributable to the expected reduction, an additional 34% decrease was observed, representing a large decline in new HIV diagnoses associated with the COVID-19 pandemic.

Mixed-Effects Zero-Inflated Negative Binomial Crash Predictive Models for Unsignalized Intersections along Two-Lane Highways with Minor Roads Operating with Very Low Traffic Volumes

Current and past investigations into road accidents have mainly focused on high-volume roads which have experienced a significant number of collisions. However, low-volume roads also record crash data which merit analysis to understand the causes of accidents and find potential countermeasures. This study focuses on unsignalized intersections linking major highways and minor stop-controlled local roads that operate with very low traffic volumes. In this scenario, an over-abundance of zero observations has to be accounted for. To address this issue, zero-inflated Poisson and negative binomial regression models have been calibrated and analyzed to find the geometric and operational factors which contribute most to the crash rate. Random effects have also been considered to account for unobserved heterogeneity inherent in the grouping of intersections within the database. The results indicate that the mixed-effect negative binomial model had the best prediction performance. Developing models for subgroups of crashes, for example, failure-to-yield and other types of crash, resulted in better prediction performance. The major road’s average annual daily traffic and the surface type (i.e., paved or unpaved) of minor road approaches had a significant effect on the frequency of all crash types. The type of intersection (three- or four-legs), the skew angle of intersection, deviation angle of near curves, and operating speed differences also had statistically significant effects on the frequency of crashes that do not include the failure-to-yield.

Associations Between Sexual History Documentation in Electronic Health Records and Referral to Pre-Exposure Prophylaxis Navigator on Prescription of Pre-Exposure Prophylaxis at a Multi-Site Federally Qualified Health Center.

This cross-sectional study examined the relationships between sexual history screening (SHS) and referrals to a pre-exposure prophylaxis (PrEP) navigator (non-clinical staff member who assists patients in overcoming structural barriers to PrEP) on the proportion of days covered by PrEP for adult patients at a federally qualified health center. Patients' sociodemographics, PrEP prescriptions, referral to a PrEP navigator, and SHS data were extracted from the electronic health record (EHR). The analytic sample was 214 adult patients who were human immunodeficiency virus (HIV) negative and taking PrEP to prevent infection from January 2016 to December 2019. Mixed-effects negative binomial models were conducted accounting for clustering by patients' primary care providers. Documentation of SHS was associated with a higher proportion of days covered by PrEP (incidence rate ratio = 1.44, 95% confidence interval: 1.17-1.77). There was no significant effect of having a referral to the PrEP navigator on the proportion of days covered by PrEP, nor did having a referral to the PrEP navigator moderate the relationship between having SHS documented in the EHR and the proportion of days covered by PrEP. This study is the first to investigate the relationship between having sexual history documented in the EHR, referrals to a PrEP navigator, and their combined effect on the proportion of days covered by PrEP. Results of this study provide foundational evidence for future studies examining SHS as an opportunity to improve PrEP access and adherence and indicate the need for additional research exploring the value of PrEP navigators as an implementation strategy to overcome social and structural barriers to care.

Association of Hospital Procedural Volume With Outcomes of Left Ventricular Assist Device Placement

With the advancement in device technology, the use of durable left ventricular assist devices (LVADs) has increased significantly in recent years. However, there is a dearth of evidence to conclude whether patients who undergo LVAD implantation at high-volume centers have better clinical outcomes than those receiving care at low- or medium-volume centers. We analyzed the hospitalizations using the Nationwide Readmission Database for the year 2019 for new LVAD implantation. Baseline comorbidities and hospital characteristics were compared among low- (1-5 procedures/year), medium- (6-16 procedures/year) and high-volume (17-72 procedures/year) hospitals. The volume/outcome relationship was analyzed using the annualized hospital volume as a categorical variable (tertiles) as well as a continuous variable. Multilevel mixed-effect logistic regression and negative binomial regression models were used to determine the association of hospital volume and outcomes, with tertile 1 (low-volume hospitals) as the reference category. A total of 1533 new LVAD procedures were included in the analysis. The inpatient mortality rate was lower in the high-volume centers compared with the low-volume centers (9.04% vs 18.49%, aOR 0.41, CI0.21-0.80; P = 0.009). There was a trend toward lower mortality rates in medium-volume centers compared with low-volume centers; however, it did not reach statistical significance (13.27% vs 18.49%, aOR 0.57, CI0.27-1.23; P = 0.153). Similar results were seen for major adverse events (composite of stroke/transient ischemic attack and in-hospital mortality). There was no significant difference in bleeding/transfusion, acute kidney injury, vascular complications, pericardial effusion/hemopericardium/tamponade, length of stay, cost, or 30-day readmission rates between medium- and high-volume centers compared to low-volume centers. Our findings indicate lower inpatient mortality rates in high-volume LVAD implantation centers and a trend toward lower mortality rates in medium-volume LVAD implantation centers compared to lower-volume centers.

Determinants of worldwide antibiotic resistance dynamics across drug-bacterium pairs: a multivariable spatial-temporal analysis using ATLAS

Antibiotic resistance (ABR) is a major concern for global health. However, factors driving its emergence and dissemination are not fully understood. Identification of such factors is crucial to explain heterogeneity in ABR rates observed across space, time, and species and antibiotics. We analysed count data of clinical isolates from 51 countries over 2006-19 for thirteen drug-bacterium pairs taken from the ATLAS database. We characterised ABR spatial and temporal patterns and used a mixed-effect negative binomial model, accounting for country-year dependences with random effects, to investigate associations with potential drivers, including antibiotic sales, economic and health indicators, meteorological data, population density, and tourism. ABR patterns were strongly country and drug-bacterium pair dependent. In 2019, median ABR rates ranged from 6·3% (IQR 19·7% [0·5-20·2]) for carbapenem-resistant Klebsiella pneumoniae to 80·7% (41·8% [50·4-92·2]) for fluoroquinolone-resistant Acinetobacter baumannii, with heterogeneity across countries. From 2006 to 2019, carbapenem resistance increased in more than 60% of investigated countries; no global trend was observed for other resistances. Multivariable analyses identified significant associations of ABR with country-level selecting antibiotic sales, but only in fluoroquinolone-resistant-Escherichia coli, fluoroquinolone-resistant-Pseudomonas aeruginosa, and carbapenem-resistant-A baumannii. We also found a correlation between temperature and resistance in Enterobacteriaceae and with the health system quality for all drug-bacterium pairs except Enterococci and Streptococcus pneumoniae pairs. Despite wide consideration of possible explanatory variables, drug-bacterium pair ABR rates still showed unexplained spatial random effects variance. Our findings reflect the diversity of mechanisms driving global antibiotic resistance across pathogens and stress the need for tailored interventions to tackle bacterial resistance. Independent research Pfizer Global Medical Grant and ANR Labex IBEID.

The spatio-temporal distribution of acute encephalitis syndrome and its association with climate and landcover in Vietnam

BackgroundAcute encephalitis syndrome (AES) differs in its spatio-temporal distribution in Vietnam with the highest incidence seen during the summer months in the northern provinces. AES has multiple aetiologies, and the cause remains unknown in many cases. While vector-borne disease such as Japanese encephalitis and dengue virus and non-vector-borne diseases such as influenza and enterovirus show evidence of seasonality, associations with climate variables and the spatio-temporal distribution in Vietnam differs between these. The aim of this study was therefore to understand the spatio-temporal distribution of, and risk factors for AES in Vietnam to help hypothesise the aetiology.MethodsThe number of monthly cases per province for AES, meningitis and diseases including dengue fever; influenza-like-illness (ILI); hand, foot, and mouth disease (HFMD); and Streptococcus suis were obtained from the General Department for Preventive Medicine (GDPM) from 1998–2016. Covariates including climate, normalized difference vegetation index (NDVI), elevation, the number of pigs, socio-demographics, JEV vaccination coverage and the number of hospitals were also collected. Spatio-temporal multivariable mixed-effects negative binomial Bayesian models with an outcome of the number of cases of AES, a combination of the covariates and harmonic terms to determine the magnitude of seasonality were developed.ResultsThe national monthly incidence of AES declined by 63.3% over the study period. However, incidence increased in some provinces, particularly in the Northwest region. In northern Vietnam, the incidence peaked in the summer months in contrast to the southern provinces where incidence remained relatively constant throughout the year. The incidence of meningitis, ILI and S. suis infection; temperature, relative humidity with no lag, NDVI at a lag of one month, and the number of pigs per 100,000 population were positively associated with the number of cases of AES in all models in which these covariates were included.ConclusionsThe positive correlation of AES with temperature and humidity suggest that a number of cases may be due to vector-borne diseases, suggesting a need to focus on vaccination campaigns. However, further surveillance and research are recommended to investigate other possible aetiologies such as S. suis or Orientia tsutsugamushi.

Social participation and tooth loss, vision, and hearing impairments among older Brazilian adults.

Vision and hearing impairments can reduce participation in social activities. Given the prominent role of the mouth in face-to-face interactions, this study evaluated the associations of tooth loss, vision, and hearing impairments with social participation among older adults. This analysis included 1947 participants, aged 60+ years, who participated in three waves (2006, 2010, and 2015) of the Health, Wellbeing and Aging Study (SABE) in Brazil. Social participation was measured by the number of formal and informal social activities (requiring face-to-face interaction) participants were regularly involved in. Teeth were counted during clinical examinations and categorized as 0, 1-19, and 20+ teeth. Reports on vision and hearing impairments were classified into three categories (good, regular, and poor). The associations of each impairment with the 9-year change in the social participation score were tested in negative binomial mixed-effects models adjusting for time-variant and time-invariant covariates. Each impairment was associated with the baseline social participation score and the annual rate of change in the social participation score. Participants with 1-19 (incidence rate ratio: 0.96, 95% CI: 0.91-1.01) and no teeth (0.92, 95% CI: 0.87-0.97), those with regular (0.98, 95% CI: 0.95-1.01) and poor vision (0.86, 95% CI: 0.81-0.90), and those with regular (0.94, 95% CI: 0.91-0.98) and poor hearing (0.91, 95% CI: 0.87-0.95) had lower baseline social participation scores than those with 20+ teeth, good vision, and good hearing, respectively. Furthermore, participants with 1-19 (0.996, 95% CI: 0.990-1.002) and no teeth (0.994, 95% CI: 0.987-0.999), those with regular (0.996, 95% CI: 0.992-0.999) and poor vision (0.997, 95% CI: 0.991-1.003), and those with regular (0.997, 95% CI: 0.992-1.001) and poor hearing (0.995, 95% CI: 0.990-0.999) had greater annual declines in the social participation score than those with 20+ teeth, good vision and good hearing, respectively. This 9-year longitudinal study shows that tooth loss, vision, and hearing impairments are associated with reduced social participation among older adults.