A repeated cross-sectional study of the association of community health worker intervention with the maternal continuum of care in rural Liberian communities.

BACKGROUND: The maternal continuum of care (CoC) (antenatal care, facility-based delivery, postnatal care) is critical to maternal and neonatal health and reducing mortality, but completion in rural areas of low- and middle-income countries is often limited. We used repeated cross-sectional household surveys from a rural Liberian county to explore changes in rates of completion of all steps and no steps in the maternal CoC after implementation of the National Community Health Assistant Program (NCHAP), a community health worker (CHW) intervention designed to increase care uptake for families over five kilometers from a facility. METHODS: We analyzed repeated cross-sectional household surveys of women aged 18-49 served by NCHAP in Rivercess County, Liberia. We measured survey-weighted, before-to-after implementation difference in completion of all steps and no steps in the maternal CoC. We used multivariable regression to explore covariates associated with completion rates before and after NCHAP implementation. RESULTS: Data from surveys conducted at three timepoints (2015, n = 354; 2018, n = 312; 2021, n = 302) were analyzed. A significant increase in completing the full maternal CoC (2015:23.6%, 2018:53.4%, change:29.7% points (pp), 95% confidence interval (CI) [21.0,38.4]) and a decrease in completing no steps in the CoC (2015:17.6%, 2018:4.0%, change: -12.4pp [-17.6, -7.2]) after implementation of NCHAP were observed from 2015 to 2018, with rates maintained from 2018 to 2021. Living farther from a facility was consistently associated with less care across the continuum. Following implementation, living in a motorbike accessible community was associated with completing the CoC while living in a mining community was negatively associated with omitting the CoC. Household wealth was associated with differences in rates pre-NCHAP but not post-NCHAP. CONCLUSIONS: Following NCHAP implementation, completion rate of the full maternal CoC in Rivercess County more than doubled while the rate of completing no steps in the continuum fell below 5%. These rates were sustained over time including during COVID-19 with reduced differences across wealth groups, although far distances remained a risk for less care. CHW programs providing active outreach to remote communities can be important tools for improving uptake of interventions and reducing risk of no formal care during and after pregnancy.

Does it matter that standard preparedness indices did not predict COVID-19 outcomes?

A number of scientific publications and commentaries have suggested that standard preparedness indices such as the Global Health Security Index (GHSI) and Joint External Evaluation (JEE) scores did not predict COVID-19 outcomes. To some, the failure of these metrics to be predictive demonstrates the need for a fundamental reassessment which better aligns preparedness measurement with operational capacities in real-world stress situations, including the points at which coordination structures and decision-making may fail. There are, however, several reasons why these instruments should not be so easily rejected as preparedness measures.From a methodological point of view, these studies use relatively simple outcome measures, mostly based on cumulative numbers of cases and deaths at a fixed point of time. A country's "success" in dealing with the pandemic is highly multidimensional - both in the health outcomes and type and timing of interventions and policies - is too complex to represent with a single number. In addition, the comparability of mortality data over time and among jurisdictions is questionable due to highly variable completeness and representativeness. Furthermore, the analyses use a cross-sectional design, which is poorly suited for evaluating the impact of interventions, especially for COVID-19.Conceptually, a major reason that current preparedness measures fail to predict pandemic outcomes is that they do not adequately capture variations in the presence of effective political leadership needed to activate and implement existing system, instill confidence in the government's response; or background levels of interpersonal trust and trust in government institutions and country ability needed to mount fast and adaptable responses. These factors are crucial; capacity alone is insufficient if that capacity is not effectively leveraged. However, preparedness metrics are intended to identify gaps that countries must fill. As important as effective political leadership and trust in institutions, countries cannot be held accountable to one another for having good political leadership or trust in institutions. Therefore, JEE scores, the GHSI, and similar metrics can be useful tools for identifying critical gaps in capacities and capabilities that are necessary but not sufficient for an effective pandemic response.

Measuring health system responsiveness in a national community health worker primary care programme in rural Liberia.

As many low- and middle-income countries scale up community health worker (CHW) programmes to achieve universal health coverage, ensuring quality as well as access is critical. Health system responsiveness (HSR) is a core domain of quality patient-centred care but has not been widely measured in CHW-delivered care. We report results from a household survey measuring HSR and health systems' quality of CHW-delivered care in two Liberian counties where the national CHW programme of Community Health Assistants (CHAs) for communities ≥5 km from a health centre has been implemented. We conducted a cross-sectional population-based household survey in 2019 in Rivercess (RC) and Grand Gedeh (GG) counties, using a two-stage cross-sectional cluster sampling approach. We included validated HSR questions on six responsiveness domains and patient-reported health system outcomes, such as satisfaction and trust in the CHA's skills and abilities. The HSR questions were administered to women aged 18-49 years who reported seeking care from a CHA in the 3 months prior to the survey. A composite responsiveness score was calculated and divided into tertiles. Multivariable analysis using Poisson regression with log link and adjusting for respondent characteristics was used to determine the association between responsiveness and patient-reported health system outcomes. The proportion of individuals rating responsiveness as very good or excellent was similar across all domains within a district, with ratings being lower in RC (23-29%) than in GG (52-59%). High ratings in both counties were seen for high trust in the CHA's skills and abilities (GG 84%, RC 75%) and high confidence in the CHA (GG 58%, RC 60%). Compared with women in the lowest responsiveness tertile (score ≤3), women in the highest tertile (score $ \ge $4.25) were significantly more likely to report high quality of CHA-delivered care (prevalence ratio, PR = 14.1), very good/excellent at meeting health needs (PR = 8.0), high confidence in the CHA to provide future care (PR = 2.4), and a high level of trust in CHA's skills and abilities (PR = 1.4). Controlling for respondent characteristics, the composite responsiveness score was significantly associated with all patient-reported health system outcomes (P < 0.001). We found that HSR was associated with important patient-reported health system quality outcomes, including satisfaction, trust, and confidence in the CHA. Measuring patients' experience and outcomes of care is important to complement more common measures of technical quality for CHW-delivered care to ensure that this domain of quality is central to the community health programme design and delivery.

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.

Complex relationship between household wealth, location of residence, road crash injury incidence and injury severity in Uganda.

BACKGROUND: Limited evidence exists about associations between road crash injury and economic status in sub-Saharan Africa from large, population-based data sets. Existing studies generally do not incorporate fatal crashes. This study aims to understand the relationship between relative wealth and road crash injury and severity using population-representative cross-sectional data from Uganda's 2016 Demographic and Health Survey . METHODS: One-year road crash risk was flexibly modelled as a function of wealth using fractional polynomial models, stratified by sex and rural/urban residence. Wealth was operationalised as 1/20th quantiles of the first principal component from a polychoric principal component analysis. Injury severity was coded as a three-level ordinal variable; associations with wealth were modelled with ordinal logistic regression on quintiles of relative wealth, stratified by residence. RESULTS: Overall, injury risk peaked in the upper middle of the wealth distribution. Rural resident injury risk increased monotonically with wealth. Urban resident risk had an upside-down U shape. Risk peaked in the distribution's middle at about double the lowest levels. Only urban men had higher risk among the least wealthy than most wealthy (3.2% vs 1.7%; difference=1.5 percentage points, 95% CI 0.2 to 2.7). Among those with road crash injuries, greater relative wealth was associated with decreased likelihood of more severe injury (33.2 percentage points lower in the highest category than lowest, 95% CI 18.4 to 48.1) or death (5.9 percentage points, 95% CI -0.1 to 11.8) for urban residents but not rural residents. CONCLUSION: Relationships between relative wealth and injury risk and severity are complex and different for urban and rural Ugandans.

Female sex and cardiovascular disease risk in rural Uganda: a cross-sectional, population-based study.

BACKGROUND: Sex-based differences in cardiovascular disease (CVD) burden are widely acknowledged, with male sex considered a risk factor in high-income settings. However, these relationships have not been examined in sub-Saharan Africa (SSA). We aimed to apply the American Heart Association (AHA) ideal cardiovascular health (CVH) tool modified by the addition of C-reactive protein (CRP) to examine potential sex-based differences in the prevalence of CVD risk in rural Uganda. METHODS: In a cross-sectional study nested within a population-wide census, 857 community-living adults completed physical and laboratory-based assessments to calculate individual ideal CVH metrics including an eight category for CRP levels. We summarized sex-specific ideal CVH indices, fitting ordinal logistic regression models to identify correlates of improving CVH. As secondary outcomes, we assessed subscales of ideal CVH behaviours and factors. Models included inverse probability of sampling weights to determine population-level estimates. RESULTS: The weighted-population mean age was 39.2 (1.2) years with 52.0 (3.7) % females. Women had ideal scores in smoking (80.4% vs. 68.0%; p < 0.001) and dietary intake (26.7% vs. 16.8%; p = 0.037) versus men, but the opposite in body mass index (47.3% vs. 84.4%; p < 0.001), glycated hemoglobin (87.4% vs. 95.2%; p = 0.001), total cholesterol (80.2% vs. 85.0%; p = 0.039) and CRP (30.8% vs. 49.7%; p = 0.009). Overall, significantly more men than women were classified as having optimal cardiovascular health (6-8 metrics attaining ideal level) (39.7% vs. 29.0%; p = 0.025). In adjusted models, female sex was correlated with lower CVH health factors sub-scales but higher ideal CVH behaviors. CONCLUSIONS: Contrary to findings in much of the world, female sex in rural SSA is associated with worse ideal CVH profiles, despite women having better indices for ideal CVH behaviors. Future work should assess the potential role of socio-behavioural sex-specific risk factors for ideal CVH in SSA, and better define the downstream consequences of these differences.

A Community Health Worker Intervention to Increase Childhood Disease Treatment Coverage in Rural Liberia: A Controlled Before-and-After Evaluation.

OBJECTIVES: To assess a community health worker (CHW) program's impact on childhood illness treatment in rural Liberia. METHODS: We deployed CHWs in half of Rivercess County in August 2015 with the other half constituting a comparison group until July 2016. All CHWs were provided cash incentives, supply chain support, and monthly clinical supervision. We conducted stratified cluster-sample population-based surveys at baseline (March-April 2015) and follow-up (April-June 2016) and performed a difference-in-differences analysis, adjusted by inverse probability of treatment weighting, to assess changes in treatment of fever, diarrhea, and acute respiratory infection by a qualified provider. RESULTS: We estimated a childhood treatment difference-in-differences of 56.4 percentage points (95% confidence interval [CI] = 36.4, 76.3). At follow-up, CHWs provided 57.6% (95% CI = 42.8, 71.2) of treatment in the intervention group. The difference-in-differences diarrhea oral rehydration therapy was 22.4 percentage points (95% CI = -0.7, 45.5). CONCLUSIONS: Implementation of a CHW program in Rivercess County, Liberia, was associated with large, statistically significant improvements treatment by a qualified provider; however, improvements in correct diarrhea treatment were lower than improvements in coverage. Findings from this study offer support for expansion of Liberia's new National Community Health Assistant Program.

Relative household wealth and non-fatal road crashes: analysis of population-representative data of Kenyan adults.

Background: This study aims to examine potential road crash disparities across relative wealth and location of residence in Kenya by analyzing population-representative Demographic and Health Survey data. Methods: Relative wealth was measured by household assets, converted into an index by polychoric principal components analysis. Location and sex-stratified associations between wealth quantiles and crashes were flexibly estimated using fractional polynomial models. Structural equation models were fit to examine whether observed differences may operate through previously identified determinants. Results: In rural areas, crashes were least common for both the poorest men (-5.2 percentage points, 95% CI: -7.3 to -3.2) and women (-1.6 percentage points, 95% CI: -2.9 to -0.4). In urban areas, male crashes were lowest (-3.0 percentage points, 95% CI: -5.2 to -0.8) among the wealthiest, while they peaked in the middle of the female wealth distribution (2.0 percentage points, 95% CI: 0.3-3.8). Male differences operate partially though occupational driving and vehicle ownership. Urban female differences operate partially through household vehicle ownership, but differences for rural women were not explained by modeled determinants. Conclusions: Relative wealth and road crash have opposite associations in rural and urban areas. Especially in rural areas, it is important to mitigate potential unintended effects of economic development.

Implementation research on community health workers' provision of maternal and child health services in rural Liberia.

OBJECTIVE: To assess changes in the use of essential maternal and child health services in Konobo, Liberia, after implementation of an enhanced community health worker (CHW) programme. METHODS: The Liberian Ministry of Health partnered with Last Mile Health, a nongovernmental organization, to implement a pilot CHW programme with enhanced recruitment, training, supervision and compensation. To assess changes in maternal and child health-care use, we conducted repeated cross-sectional cluster surveys before (2012) and after (2015) programme implementation. FINDINGS: Between 2012 and 2015, 54 CHWs, seven peer supervisors and three clinical supervisors were trained to serve a population of 12 127 people in 44 communities. The regression-adjusted percentage of children receiving care from formal care providers increased by 60.1 (95% confidence interval, CI: 51.6 to 68.7) percentage points for diarrhoea, by 30.6 (95% CI: 20.5 to 40.7) for fever and by 51.2 (95% CI: 37.9 to 64.5) for acute respiratory infection. Facility-based delivery increased by 28.2 points (95% CI: 20.3 to 36.1). Facility-based delivery and formal sector care for acute respiratory infection and diarrhoea increased more in agricultural than gold-mining communities. Receipt of one-or-more antenatal care sessions at a health facility and postnatal care within 24 hours of delivery did not change significantly. CONCLUSION: We identified significant increases in uptake of child and maternal health-care services from formal providers during the pilot CHW programme in remote rural Liberia. Clinic-based services, such as postnatal care, and services in specific settings, such as mining areas, require additional interventions to achieve optimal outcomes.

Crowdsourced data collection for public health: A comparison with nationally representative, population tobacco use data.

INTRODUCTION: Internet-based crowdsourcing is increasingly used for social and behavioral research in public health, however the potential generalizability of crowdsourced data remains unclear. This study assessed the population representativeness of Internet-based crowdsourced data. METHODS: A total of 3999 U.S. young adults ages 18 to 30years were recruited in 2016 through Internet-based crowdsourcing to complete measures taken from the 2012-2013 National Adult Tobacco Survey (NATS). Post-hoc sampling weights were created using procedures similar to the NATS. Weighted analyses were conducted in 2016 to compare crowdsourced and publicly-available 2012-2013 NATS data on demographics, tobacco use, and measures of tobacco perceptions and product warning label exposure. RESULTS: Those in the crowdsourced sample were less likely to report an annual household income of $50,000 or greater, and e-cigarette, waterpipe, and cigar use were more prevalent in the crowdsourced sample. High proportions of both samples indicated cigarette smoking is very harmful and very addictive. Comparable proportions of non-smokers and smokers reported cigarette warning label exposure, however the likelihood of reporting that smoking is very harmful by frequency of warning label exposure was lower among smokers in the crowdsourced sample. CONCLUSIONS: Our findings indicate that crowdsourced samples may differ demographically and may not produce generalizable estimates of tobacco use prevalence relative to population data after post-hoc sample weighting. However, correlational analyses in crowdsourced samples may reasonably approximate population data. Future studies can build from this work by testing additional methodological strategies to improve crowdsourced sampling strategies.

Validation Relaxation: A Quality Assurance Strategy for Electronic Data Collection.

BACKGROUND: The use of mobile devices for data collection in developing world settings is becoming increasingly common and may offer advantages in data collection quality and efficiency relative to paper-based methods. However, mobile data collection systems can hamper many standard quality assurance techniques due to the lack of a hardcopy backup of data. Consequently, mobile health data collection platforms have the potential to generate datasets that appear valid, but are susceptible to unidentified database design flaws, areas of miscomprehension by enumerators, and data recording errors. OBJECTIVE: We describe the design and evaluation of a strategy for estimating data error rates and assessing enumerator performance during electronic data collection, which we term "validation relaxation." Validation relaxation involves the intentional omission of data validation features for select questions to allow for data recording errors to be committed, detected, and monitored. METHODS: We analyzed data collected during a cluster sample population survey in rural Liberia using an electronic data collection system (Open Data Kit). We first developed a classification scheme for types of detectable errors and validation alterations required to detect them. We then implemented the following validation relaxation techniques to enable data error conduct and detection: intentional redundancy, removal of "required" constraint, and illogical response combinations. This allowed for up to 11 identifiable errors to be made per survey. The error rate was defined as the total number of errors committed divided by the number of potential errors. We summarized crude error rates and estimated changes in error rates over time for both individuals and the entire program using logistic regression. RESULTS: The aggregate error rate was 1.60% (125/7817). Error rates did not differ significantly between enumerators (P=.51), but decreased for the cohort with increasing days of application use, from 2.3% at survey start (95% CI 1.8%-2.8%) to 0.6% at day 45 (95% CI 0.3%-0.9%; OR=0.969; P<.001). The highest error rate (84/618, 13.6%) occurred for an intentional redundancy question for a birthdate field, which was repeated in separate sections of the survey. We found low error rates (0.0% to 3.1%) for all other possible errors. CONCLUSIONS: A strategy of removing validation rules on electronic data capture platforms can be used to create a set of detectable data errors, which can subsequently be used to assess group and individual enumerator error rates, their trends over time, and categories of data collection that require further training or additional quality control measures. This strategy may be particularly useful for identifying individual enumerators or systematic data errors that are responsive to enumerator training and is best applied to questions for which errors cannot be prevented through training or software design alone. Validation relaxation should be considered as a component of a holistic data quality assurance strategy.

Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference.

Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales.

Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey.

BACKGROUND: The Ebola virus disease (EVD) epidemic has threatened access to basic health services through facility closures, resource diversion, and decreased demand due to community fear and distrust. While modeling studies have attempted to estimate the impact of these disruptions, no studies have yet utilized population-based survey data. METHODS AND FINDINGS: We conducted a two-stage, cluster-sample household survey in Rivercess County, Liberia, in March-April 2015, which included a maternal and reproductive health module. We constructed a retrospective cohort of births beginning 4 y before the first day of survey administration (beginning March 24, 2011). We then fit logistic regression models to estimate associations between our primary outcome, facility-based delivery (FBD), and time period, defined as the pre-EVD period (March 24, 2011-June 14, 2014) or EVD period (June 15, 2014-April 13, 2015). We fit both univariable and multivariable models, adjusted for known predictors of facility delivery, accounting for clustering using linearized standard errors. To strengthen causal inference, we also conducted stratified analyses to assess changes in FBD by whether respondents believed that health facility attendance was an EVD risk factor. A total of 1,298 women from 941 households completed the survey. Median age at the time of survey was 29 y, and over 80% had a primary education or less. There were 686 births reported in the pre-EVD period and 212 in the EVD period. The unadjusted odds ratio of facility-based delivery in the EVD period was 0.66 (95% confidence interval [CI] 0.48-0.90, p-value = 0.010). Adjustment for potential confounders did not change the observed association, either in the principal model (adjusted odds ratio [AOR] = 0.70, 95%CI 0.50-0.98, p = 0.037) or a fully adjusted model (AOR = 0.69, 95%CI 0.50-0.97, p = 0.033). The association was robust in sensitivity analyses. The reduction in FBD during the EVD period was observed among those reporting a belief that health facilities are or may be a source of Ebola transmission (AOR = 0.59, 95%CI 0.36-0.97, p = 0.038), but not those without such a belief (AOR = 0.90, 95%CI 0.59-1.37, p = 0.612). Limitations include the possibility of FBD secular trends coincident with the EVD period, recall errors, and social desirability bias. CONCLUSIONS: We detected a 30% decreased odds of FBD after the start of EVD in a rural Liberian county with relatively few cases. Because health facilities never closed in Rivercess County, this estimate may under-approximate the effect seen in the most heavily affected areas. These are the first population-based survey data to show collateral disruptions to facility-based delivery caused by the West African EVD epidemic, and they reinforce the need to consider the full spectrum of implications caused by public health emergencies.

Charting health system reconstruction in post-war Liberia: a comparison of rural vs. remote healthcare utilization.

BACKGROUND: Despite a growing global emphasis on universal healthcare, access to basic primary care for remote populations in post-conflict countries remains a challenge. To better understand health sector recovery in post-conflict Liberia, this paper seeks to evaluate changes in utilization of health services among rural populations across a 5-year time span. METHODS: We assessed trends in healthcare utilization among the national rural population using the Liberian Demographic and Health Survey (DHS) from 2007 and 2013. We compared these results to results obtained from a two-staged cluster survey in 2012 in the district of Konobo, Liberia, to assess for differential health utilization in an isolated, remote region. Our primary outcomes of interest were maternal and child health service care seeking and utilization. RESULTS: Most child and maternal health indicators improved in the DHS rural sub-sample from 2007 to 2013. However, this progress was not reflected in the remote Konobo population. A lower proportion of women received 4+ antenatal care visits (AOR 0.28, P < 0.001) or any postnatal care (AOR 0.25, P <0.001) in Konobo as compared to the 2013 DHS. Similarly, a lower proportion of children received professional care for common childhood illnesses, including acute respiratory infection (9 % vs. 52 %, P < 0.001) or diarrhea (11 % vs. 46 %, P < 0.001). CONCLUSIONS: Our data suggest that, despite the demonstrable success of post-war rehabilitation in rural regions, particularly remote populations in Liberia remain at disproportionate risk for limited access to basic health services. As a renewed effort is placed on health systems reconstruction in the wake of the Ebola-epidemic, a specific focus on solutions to reach isolated populations will be necessary in order to ensure extension of coverage to remote regions such as Konobo.

Strengthening the detection of and early response to public health emergencies: lessons from the West African Ebola epidemic.

Mark Siedner and colleagues reflect on the early response to the Ebola epidemic and lessons that can be learned for future epidemics.

Epidemiology of non-fatal US emergency room visits for road crashes involving pedestrians in wheelchairs.

This study aims to quantify and describe the risk of non-fatal pedestrian injury among persons who use wheelchairs in the US. Cases of pedestrian injury between 2002 and 2010 among persons using wheelchairs were identified in the National Electronic Injury Surveillance System to generate national injury estimates. Between 2002 and 2010, an estimated 9348 (95% CI 4912 to 13,784) people were treated in emergency departments for non-fatal pedestrian injuries sustained while using wheelchairs. Using wheelchair-use denominators calculated from the Survey of Income and Program Participation, this equates to an incidence rate of 31.3 (95% CI 16.4 to 46.1) per 100,000 person-years. Injury risk was 3.5 times higher for men than women (p<0.001). Contusions, abrasions, and lacerations (42.7%) and fractures (16.4%) were most common. The head and neck (24.7%) and lower extremities (28.4%) were most often injured. A fifth (21.4%) of injuries required hospitalisation, and 89.2% occurred in traffic on public roadways.

Assessing the reliability and validity of direct observation and traffic camera streams to measure helmet and motorcycle use.

There is a need to develop motorcycle helmet surveillance approaches that are less labour intensive than direct observation (DO), which is the commonly recommended but never formally validated approach, particularly in developing settings. This study sought to assess public traffic camera feeds as an alternative to DO, in addition to the reliability of DO under field conditions. DO had high inter-rater reliability, κ=0.88 and 0.84, respectively, for cycle type and helmet type, which reinforces its use as a gold standard. However, traffic camera-based data collection was found to be unreliable, with κ=0.46 and 0.53 for cycle type and helmet type. When bicycles, motorcycles and scooters were classified based on traffic camera streams, only 68.4% of classifications concurred with those made via DO. Given the current technology, helmet surveillance via traffic camera streams is infeasible, and there remains a need for innovative traffic safety surveillance approaches in low-income urban settings.

Assessing the potential for bias in direct observation of adult commuter cycling and helmet use.

OBJECTIVES: Bicycling and helmet surveillance, research, and programme evaluation depend on accurate measurement by direct observation, but it is unclear whether weather and other exogenous factors introduce bias into observed counts of cyclists and helmet use. METHODS: To address this issue, a time series was created of cyclists observed at two observation points in Washington, DC, at peak commuting times and locations between September 2012 and February 2013. Using multiple linear regression with Newey-West SEs to account for possible serial correlation, the association between various factors and cyclist counts and helmet use was investigated. RESULTS: The number of cyclists observed per 1 h session was significantly associated with predicted daily high temperature, chance of rain, and actual rain. Additionally, fewer cyclists were observed on Fridays. Helmet use was significantly lower during evening commutes than morning and also lower on Fridays. Helmet use was not associated with weather variables. Controlling for observable cyclists characteristics weakened the association between helmet use and the time of day and day of the week, but it did not eliminate that association. CONCLUSIONS: Direct observation to measure commuter cycling trends or evaluate interventions should control for weather and day of week. Measurement of helmet use is unlikely to be meaningfully biased by weather factors, but time of day and day of week should be taken into account. Failing to control for these factors could lead to significant bias in assessments of the level of, and trends in, commuter cycling and helmet use.

Synopsis of a public health emergency preparedness critical incident registry.

As called for in the National Health Security Strategy, health departments currently use a number of "after action report" formats to collect data from actual public health emergency responses. The 2009 H1N1 pandemic revealed significant weaknesses in the use of these approaches, especially the absence both of reflective root-cause analyses and of a framework to describe performance in terms of public health emergency preparedness capabilities. To address these deficiencies and to develop an effective approach to learning from actual public health emergencies, we sought to understand how the concept and operations of a "critical incident registry," common in health care and other industries, could be adapted to meet the National Health Security Strategy objectives.

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.