Assessing the impact of regional laboratory networks in East and West Africa on national health security capacities.

National laboratories are a fundamental capacity for public health, contributing to disease surveillance and outbreak response. The establishment of regional laboratory networks has been posited as a means of improving health security across multiple countries. Our study objective was to assess whether membership in regional laboratory networks in Africa has an effect on national health security capacities and outbreak response. We conducted a literature review to select regional laboratory networks in the Eastern and Western African regions. We examined data from the World Health Organization Joint External Evaluation (JEE) mission reports, the 2018 WHO States Parties Annual Report (SPAR), and the 2019 Global Health Security Index (GHS). We compared the average scores of countries that are members of a regional laboratory network to those that are not. We also assessed country-level diagnostic and testing indicators during the COVID-19 pandemic. We found no significant differences in any of the selected health security metrics for member versus non-member countries of the either the East Africa Public Health Laboratory Networking Project (EAPHLNP) in the Eastern Africa region, nor for the West African Network of Clinical Laboratories (RESAOLAB) in the Western Africa region. No statistically significant differences were observed in COVID-19 testing rates in either region. Small sample sizes and the inherent heterogeneities in governance, health, and other factors between countries within and between regions limited all analyses. These results suggest potential benefit in setting baseline capacity for network inclusion and developing regional metrics for measuring network impact, but also beyond national health security capacities, other effects that may be required to justify continued support for regional laboratory networks.

Impact of simulated flight conditions on supraventricular and ventricular ectopy.

Though billions of passengers and crew travel by air each year and are exposed to altitude equivalents of 7000-8000 feet, the health impact of cabin oxygenation levels has not been well studied. The hypoxic environment may produce ectopic heartbeats that may increase the risk of acute in-flight cardiac events. We enrolled forty older and at-risk participants under a block-randomized crossover design in a hypobaric chamber study to examine associations between flight oxygenation and both ventricular (VE) and supraventricular ectopy (SVE). We monitored participant VE and SVE every 5 min under both flight and control conditions to investigate the presence and rate of VE and SVE. While the presence of VE did not differ according to condition, the presence of SVE was higher during flight conditions (e.g. OR ratio = 1.77, 95% CI: 1.21, 2.59 for SVE couplets). Rates of VE and SVE were higher during flight conditions (e.g. RR ratio = 1.25, 95% CI: 1.03, 1.52 for VE couplets, RR ratio = 1.76, 95% CI: 1.39, 2.22 for SVE couplets). The observed higher presence and rate of ectopy tended to increase with duration of the flight condition. Further study of susceptible passengers and crew may elucidate the specific associations between intermittent or sustained ectopic heartbeats and hypoxic pathways.

The effect of interviewer-respondent age difference on the reporting of sexual activity in the Demographic and Health Surveys: Analysis of data from 21 countries.

Background: Interviewer effects can have consequential impacts on survey data, particularly for reporting sensitive attitudes and behaviours such as sexual activity and drug use, yet these effects remain understudied in low- and middle-income countries. The Demographic and Health Surveys (DHS) present a unique opportunity to study interviewer effects on the self-report of sensitive topics in low- and middle-income countries by including interviewer characteristics data. This paper aims to narrow the gap in research on interviewer effects by studying the effects that age difference between interviewer and respondent and interviewer survey experience have on the reporting of ever having sexual intercourse. Methods: We used DHS data from 91 066 women and 56 336 men in 21 countries where the standard DHS was implemented among all women of reproductive age, and interviewer characteristics were included in the data set. Using a Bayesian cross-classified model with random intercepts for interviewer and cluster, we assessed whether the effect of an age difference of 10 years or greater was associated with a difference in self-report of ever having sexual intercourse, adjusting for respondent demographics. Results: There was a meaningful association between an age difference of greater than ten years and reporting of ever having had sexual intercourse in most countries for both genders after adjusting for interviewer age and experience, rural or urban cluster, and individual-level characteristics. Among women, the marginal posterior probability of reporting ever having sexual intercourse if the interviewer was ten years or more years older was lower for 17 of 19 countries (countries ranged from -12.50 to 3.90 percentage points). Among men, the marginal posterior probability was lower for 16 of 20 countries, ranging from -18.30 to 17.10 percentage points. Conclusions: In most countries, women and men were less likely to report ever having sexual activity if the interviewer was ten or more years older than them, adjusting for potential confounders. These findings have important implications for interpreting numerous sexual health indicators, such as unmet family planning needs and human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) risk. Survey administrators may consider more careful interviewer-respondent characteristic matching or novel approaches like Audio Computer Assisted Self Interview to minimize interviewer-induced variance.

ORDINAL PROBIT FUNCTIONAL OUTCOME REGRESSION WITH APPLICATION TO COMPUTER-USE BEHAVIOR IN RHESUS MONKEYS.

Research in functional regression has made great strides in expanding to non-Gaussian functional outcomes, but exploration of ordinal functional outcomes remains limited. Motivated by a study of computer-use behavior in rhesus macaques (Macaca mulatta), we introduce the Ordinal Probit Functional Outcome Regression model (OPFOR). OPFOR models can be fit using one of several basis functions including penalized B-splines, wavelets, and O'Sullivan splines-the last of which typically performs best. Simulation using a variety of underlying covariance patterns shows that the model performs reasonably well in estimation under multiple basis functions with near nominal coverage for joint credible intervals. Finally, in application, we use Bayesian model selection criteria adapted to functional outcome regression to best characterize the relation between several demographic factors of interest and the monkeys' computer use over the course of a year. In comparison with a standard ordinal longitudinal analysis, OPFOR outperforms a cumulative-link mixed-effects model in simulation and provides additional and more nuanced information on the nature of the monkeys' computer-use behavior.

Financial Assistance for Health Security: Effects of International Financial Assistance on Capacities for Preventing, Detecting, and Responding to Public Health Emergencies.

BACKGROUND: Health security funding is intended to improve capacities for preventing, detecting, and responding to public health emergencies. Recent years have witnessed substantial increases in the amounts of donor financial assistance to health security from countries, philanthropies, and other development partners. To date, no work has examined the effects of assistance on health security capacity development over time. This paper presents an analysis of the time-lagged effects of assistance for health security (AHS) on levels of capacity. METHODS: We collected publicly available health security assessment scores published between 2010 and 2019 and data relating to financial AHS. Using validated methods, we rescaled assessment scores on analogous scales to enable comparison and binned them in quartiles. We then used a distributed lag model (DLM) in a Bayesian ordinal regression framework to assess the effects of AHS on capacity development over time. RESULTS: Strong evidence exists for associations between financial assistance and select capacities on a variety of lagged time intervals. Financial assistance had positive effects on zoonotic disease capacities in the year it was disbursed, and positive effects on legislation, laboratory, workforce, and risk communication capacities one year after disbursal. Financial assistance had negative effects on laboratory and emergency response capacities two years after it was disbursed. Financial assistance did not have measurable effects on coordination, antimicrobial resistance (AMR), food safety, biosafety, surveillance, or response preparedness capacities over the timeframe considered. CONCLUSION: Financial AHS is associated with positive effects for several core health security capacities. However, for the majority of capacities, levels of funding were not significantly associated with capacity level, though we cannot fully exclude endogeneity. Future work should continue to investigate these relationships in different contexts and examine other factors that may contribute to capacity development.

Adjusting COVID-19 Seroprevalence Survey Results to Account for Test Sensitivity and Specificity.

Population-based seroprevalence surveys can provide useful estimates of the number of individuals previously infected with serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and still susceptible, as well as contribute to better estimates of the case-fatality rate and other measures of coronavirus disease 2019 (COVID-19) severity. No serological test is 100% accurate, however, and the standard correction that epidemiologists use to adjust estimates relies on estimates of the test sensitivity and specificity often based on small validation studies. We have developed a fully Bayesian approach to adjust observed prevalence estimates for sensitivity and specificity. Application to a seroprevalence survey conducted in New York State in 2020 demonstrates that this approach results in more realistic-and narrower-credible intervals than the standard sensitivity analysis using confidence interval endpoints. In addition, the model permits incorporating data on the geographical distribution of reported case counts to create informative priors on the cumulative incidence to produce estimates and credible intervals for smaller geographic areas than often can be precisely estimated with seroprevalence surveys.

FUNCTION-ON-FUNCTION REGRESSION FOR THE IDENTIFICATION OF EPIGENETIC REGIONS EXHIBITING WINDOWS OF SUSCEPTIBILITY TO ENVIRONMENTAL EXPOSURES.

The ability to identify time periods when individuals are most susceptible to exposures as well as the biological mechanisms through which these exposures act is of great public health interest. Growing evidence supports an association between prenatal exposure to air pollution and epigenetic marks, such as DNA methylation, but the timing and gene-specific effects of these epigenetic changes are not well understood. Here, we present the first study that aims to identify prenatal windows of susceptibility to air pollution exposures in cord blood DNA methylation. In particular, we propose a function-on-function regression model that leverages data from nearby DNA methylation probes to identify epigenetic regions that exhibit windows of susceptibility to ambient particulate matter less than 2.5 microns (PM2.5). By incorporating the covariance structure among both the multivariate DNA methylation outcome and the time-varying exposure under study, this framework yields greater power to detect windows of susceptibility and greater control of false discoveries than methods that model probes independently. We compare our method to a distributed lag model approach that models DNA methylation in a probe-by-probe manner, both in simulation and by application to motivating data from the Project Viva birth cohort. We identify a window of susceptibility to PM2.5 exposure in the middle of the third trimester of pregnancy in an epigenetic region selected based on prior studies of air pollution effects on epigenome-wide methylation.

Bayesian Wavelet-packet Historical Functional Linear Models.

Historical Functional Linear Models (HFLM) quantify associations between a functional predictor and functional outcome where the predictor is an exposure variable that occurs before, or at least concurrently with, the outcome. Prior work on the HFLM has largely focused on estimation of a surface that represents a time-varying association between the functional outcome and the functional exposure. This existing work has employed frequentist and spline-based estimation methods, with little attention paid to formal inference or adjustment for multiple testing and no approaches that implement wavelet-bases. In this work, we propose a new functional regression model that estimates the time-varying, lagged association between a functional outcome and a functional exposure. Building off of recently developed function-on-function regression methods, the model employs a novel use the wavelet-packet decomposition of the exposure and outcome functions that allows us to strictly enforce the temporal ordering of exposure and outcome, which is not possible with existing wavelet-based functional models. Using a fully Bayesian approach, we conduct formal inference on the time-varying lagged association, while adjusting for multiple testing. We investigate the operating characteristics of our wavelet-packet HFLM and compare them to those of two existing estimation procedures in simulation. We also assess several inference techniques and use the model to analyze data on the impact of lagged exposure to particulate matter finer than 2.5µg, or PM2.5, on heart rate variability in a cohort of journeyman boilermakers during the morning of a typical day's shift.

Access to primary healthcare during lockdown measures for COVID-19 in rural South Africa: an interrupted time series analysis.

OBJECTIVES: We evaluated whether implementation of lockdown orders in South Africa affected ambulatory clinic visitation in rural Kwa-Zulu Natal (KZN). DESIGN: Observational cohort SETTING: Data were analysed from 11 primary healthcare clinics in northern KZN. PARTICIPANTS: A total of 46 523 individuals made 89 476 clinic visits during the observation period. EXPOSURE OF INTEREST: We conducted an interrupted time series analysis to estimate changes in clinic visitation with a focus on transitions from the prelockdown to the level 5, 4 and 3 lockdown periods. OUTCOME MEASURES: Daily clinic visitation at ambulatory clinics. In stratified analyses, we assessed visitation for the following subcategories: child health, perinatal care and family planning, HIV services, non-communicable diseases and by age and sex strata. RESULTS: We found no change in total clinic visits/clinic/day at the time of implementation of the level 5 lockdown (change from 90.3 to 84.6 mean visits/clinic/day, 95% CI -16.5 to 3.1), or at the transitions to less stringent level 4 and 3 lockdown levels. We did detect a >50% reduction in child healthcare visits at the start of the level 5 lockdown from 11.9 to 4.7 visits/day (-7.1 visits/clinic/day, 95% CI -8.9 to 5.3), both for children aged <1 year and 1-5 years, with a gradual return to prelockdown within 3 months after the first lockdown measure. In contrast, we found no drop in clinic visitation in adults at the start of the level 5 lockdown, or related to HIV care (from 37.5 to 45.6, 8.0 visits/clinic/day, 95% CI 2.1 to 13.8). CONCLUSIONS: In rural KZN, we identified a significant, although temporary, reduction in child healthcare visitation but general resilience of adult ambulatory care provision during the first 4 months of the lockdown. Future work should explore the impacts of the circulating epidemic on primary care provision and long-term impacts of reduced child visitation on outcomes in the region.

Access to primary healthcare during lockdown measures for COVID-19 in rural South Africa: a longitudinal cohort study.

Objectives Public health interventions designed to interrupt COVID-19 transmission could have deleterious impacts on primary healthcare access. We sought to identify whether implementation of the nationwide lockdown (shelter-in-place) order in South Africa affected ambulatory clinic visitation in rural Kwa-Zulu Natal (KZN). Design Prospective, longitudinal cohort study Setting Data were analyzed from the Africa Health Research Institute Health and Demographic Surveillance System, which includes prospective data capture of clinic visits at eleven primary healthcare clinics in northern KwaZulu-Natal Participants A total of 36,291 individuals made 55,545 clinic visits during the observation period. Exposure of Interest We conducted an interrupted time series analysis with regression discontinuity methods to estimate changes in outpatient clinic visitation from 60 days before through 35 days after the lockdown period. Outcome Measures Daily clinic visitation at ambulatory clinics. In stratified analyses we assessed visitation for the following sub-categories: child health, perinatal care and family planning, HIV services, non-communicable diseases, and by age and sex strata. Results We found no change in total clinic visits/clinic/day from prior to and during the lockdown (-6.9 visits/clinic/day, 95%CI -17.4, 3.7) or trends in clinic visitation over time during the lockdown period (-0.2, 95%CI -3.4, 3.1). We did detect a reduction in child healthcare visits at the lockdown (-7.2 visits/clinic/day, 95%CI -9.2, -5.3), which was seen in both children <1 and children 1-5. In contrast, we found a significant increase in HIV visits immediately after the lockdown (8.4 visits/clinic/day, 95%CI 2.4, 14.4). No other differences in clinic visitation were found for perinatal care and family planning, non-communicable diseases, or among adult men and women. Conclusions In rural KZN, the ambulatory healthcare system was largely resilient during the national-wide lockdown order. A major exception was child healthcare visitation, which declined immediately after the lockdown but began to normalize in the weeks thereafter. Future work should explore efforts to decentralize chronic care for high-risk populations and whether catch-up vaccination programs might be required in the wake of these findings.

Changes in Heart Rate and Rhythm During a Crossover Study of Simulated Commercial Flight in Older and Vulnerable Participants.

Objectives: Elderly passengers and those with preexisting disease are flying with increasing frequency and in-flight cardiac emergencies are a more frequent occurrence. We conducted a study of the physiological effects of simulated cabin altitudes and resulting lower oxygen levels among such passengers. Methods: We monitored 41 participants in a hypobaric chamber for 2 days, one at an equivalent of 7,000 feet altitude (regulations limit pressurization to 8,000 feet) for a 4-5 h simulated flight and the other at ground level using generalized least squares models to account for repeated measures. We evaluated associations between simulated flight, heart rate (HR) and measures of heart rate variability(HRV) (root mean square of successive R-R interval differences [RMSSD], standard deviation of normal-to-normal intervals [SDNN], high-frequency power [HF], and low-frequency power [LF]). Results: Heart rate was 3.9% (95% CI: 2.1, 5.8) higher on simulated flight days compared with non-flight days. The RMSSD was 10.6% (95% CI: -21.3, 0.05) lower during simulated flight days, indicative of reduced HRV. The remaining HRV measures were also lower on simulated flight days, though associations were less precise. Conclusion: We report that typical simulated flight conditions elicit changes in cardiac autonomic control, suggesting sympathetic arousal or reductions in parasympathetic drive. Our findings, if confirmed, may suggest the need for guidelines to protect vulnerable passengers including prescreens, symptom evaluation after air travel, the use of oxygen concentrators, and education about healthy behaviors in flight.

Scope and nature of financial conflicts of interest between neurologists and industry: 2013-2016.

OBJECTIVE: To detail the scope and nature of financial conflicts of interest (COIs) between neurologists and the pharmaceutical and medical device industries (Industry) using the Centers for Medicare and Medicaid Services Open Payments (OP) database, with a focus on trends from 2013 to 2016. METHODS: Payments from Industry to US neurologists were categorized into research payments, general (nonresearch) payments, and value of ownership in Industry. We performed descriptive analyses to detail the scope and nature of these relationships and trends over time. RESULTS: At least 9,505 neurologists received at least one payment from Industry each year. From 2013 to 2016, 1.6 million payments totaled $354 million, of which 99.5% of payments and 85.6% of payment value were for general/nonresearch-related payments. Most neurologists (between 65% and 80%) received less than $1,000 per year, but over 200 neurologists each received more than $100,000 during some years. Several received over $1 million. General payments are increasing, research payments are steady, and neurologists' ownership and investments are decreasing. CONCLUSIONS: Neurologists have extensive financial relationships with Industry, though this is driven by a well-paid minority. As a profession, we must work to establish firm rules to manage these potential COIs, ensuring that relationships with Industry yield synergistic advances while minimizing bias and maintaining public trust.

Influences of demographic, seasonal, and social factors on automated touchscreen computer use by rhesus monkeys (Macaca mulatta) in a large naturalistic group.

Animals housed in naturalistic social groups with access to automated cognitive testing vary in whether and how much they participate in cognitive testing. Understanding how demographic, seasonal, and social factors relate to participation is essential to evaluating the usefulness of these systems for studying cognition and in assessing the data produced. We evaluated how sex, age, reproductive experience, seasonality, and rank related to patterns of participation in a naturalistic group of rhesus monkeys over a 4-year period. Females interacted with the touchscreen systems more than males and were more likely to complete initial training. Age was positively correlated with touchscreen activity through adolescence in females, at which point seasonality and reproductive experience were stronger associates of participation. While monkeys in different rank categories did not differ in how much they interacted with the touchscreen systems, monkeys of different ranks tended not to work at the same times, perhaps reflecting avoidance of high ranking animals by those of lower rank. Automated cognitive testing systems for naturalistic social groups of rhesus monkeys can yield quality cognitive data from individuals of all ages and ranks, but participation biases may make it difficult to study sex differences or seasonal variation in cognition.

Care Coordination for Youth With Mental Health Disorders in Primary Care.

Many children are treated for mental health disorders in primary care settings. The system of care (SOC) provides a framework for collaboration among pediatric mental health providers, but it is unclear if youth treated for mental health disorders in primary care receive such coordination. At the South Boston Community Health Center from September /2012 to August 2013 for 74 individuals ≤18 years, the odds of contact with SOC agencies (mental health, education, child protective services, juvenile justice and developmental disabilities) were compared for mental health treatment in primary versus specialty care. The odds of SOC contact within primary care were lower compared to specialty care (OR = 0.43, 95% CI = 0.29-0.66), specifically for mental health (OR = 0.54, 95% CI = 0.25-1.2), education (OR = 0.12, 95% CI = 0.050-0.28), and child protective services (OR = 0.64, 95% CI = 0.22-1.9). As care coordination may improve health outcomes, increased support and education for care coordination specific to youth treated for mental health disorders in primary care settings may be warranted.

Bayesian function-on-function regression for multilevel functional data.

Medical and public health research increasingly involves the collection of complex and high dimensional data. In particular, functional data-where the unit of observation is a curve or set of curves that are finely sampled over a grid-is frequently obtained. Moreover, researchers often sample multiple curves per person resulting in repeated functional measures. A common question is how to analyze the relationship between two functional variables. We propose a general function-on-function regression model for repeatedly sampled functional data on a fine grid, presenting a simple model as well as a more extensive mixed model framework, and introducing various functional Bayesian inferential procedures that account for multiple testing. We examine these models via simulation and a data analysis with data from a study that used event-related potentials to examine how the brain processes various types of images.

Risk predictors of opioid-induced critical respiratory events in children: naloxone use as a quality measure of opioid safety.

BACKGROUND: Opioid-induced respiratory depression (OIRD) is a life-threatening complication of opioid therapy in children. Naloxone administration triggered by OIRD has been used to monitor safety of opioid therapy in adults. We used this trigger as a quality measure of opioid safety in hospitalized children to identify risk predictors of OIRD. METHODS: We retrospectively reviewed medical records of 38 patients identified from the hospital risk management database as requiring naloxone for critical respiratory events between January 2010 and June 2012 for demographics, comorbidities, surgery, naloxone event details, and outcomes. These data were compared with baseline prevalence in contemporary patients followed by pain service, who did not receive naloxone, to calculate unadjusted odds ratios. Thematic classification of preventable events was undertaken based on analysis of each event. RESULTS: The incidence of naloxone use among hospital inpatients, who received opioids at-least once, was 0.06% compared with 0.23% for patients on the pain service. A majority of naloxone events occurred in postoperative patients (n = 27/38, 71.1%) within the first 24 hours of surgery (n = 20/27, 75.1%) and in the critical care unit (50%). Patients undergoing airway surgeries had higher risk for OIRD (P = 0.01). Patient risk factors for naloxone use included age <1 year (P < 0.001), obstructive sleep apnea (P < 0.001), obesity (P = 0.019), being underweight (P < 0.0001), prematurity (P < 0.001), and developmental delay (P < 0.001). Majority of events (87%) were found to be preventable, which were classified into six main themes based on type of event. CONCLUSION: OIRD is an important, albeit mostly preventable, complication of opioid therapy in children. Naloxone use can be used as a measure to track opioid safety in children, identify contributing factors, and formulate preventive strategies to reduce the risk for OIRD.

Case report: neurological complications associated with epidural analgesia in children: a report of 4 cases of ambiguous etiologies.

The safety and utility of pediatric epidural analgesia is well established, but the risk of permanent neurological injury is unknown and largely must be extrapolated from adult literature. In this article we present a series of 4 cases of longterm or permanent neurologic complications associated with epidural analgesia. Possible mechanisms of injury and implications for practice are discussed.