Examining County-Level Associations between Federally Qualified Health Centers and Sexually Transmitted Infections: A Political Ecology of Health Framework.

Federally Qualified Health Centers (FQHCs) are the largest providers of healthcare for sexually transmitted infections (STIs) in medically underserved communities in the United States (US). Through the Affordable Care Act (ACA), FQHCs have grown in number, but the impact of this growth on STIs is poorly understood. This ecological study seeks to quantify the association between FQHCs and STI prevalence in all US counties. Variables were described utilizing medians and interquartile ranges, and distributions were compared using Kruskal-Wallis tests. Median rates of chlamydia in counties with high, low, and no FQHCs were 370.3, 422.6, and 242.1 cases per 100,000 population, respectively. Gonorrhea rates were 101.9, 119.7, and 49.9 cases per 100,000 population, respectively. Multivariable linear regression models, adjusted for structural and place-based characteristics (i.e., Medicaid expansion, social vulnerability, metropolitan status, and region), were used to examine county-level associations between FQHCs and STIs. Compared to counties with no FQHCs, counties with a high number of FQHCs had chlamydia rates that were an average of 68.6 per 100,000 population higher (ß = 68.6, 95% CI: 45.0, 92.3) and gonorrhea rates that were an average of 25.2 per 100,000 population higher (ß = 25.2, 95% CI: 13.2, 37.2). When controlled for salient factors associated with STI risks, greater FQHC availability was associated with greater diagnosis and treatment of STIs. These findings provide empirical support for the utility of a political ecology of health framework and the critical role of FQHCs in confronting the STI epidemic in the US.

Barriers to conducting independent quantitative research in low-income countries: A cross-sectional study of public health graduate students in Liberia.

INTRODUCTION: During recent disease outbreaks, quantitative research has been used to investigate intervention scenarios while accounting for local epidemiological, social, and clinical context. Despite the value of such work, few documented research efforts have been observed to originate from low-income countries. This study aimed to assess barriers that may be limiting the awareness and conduct of quantitative research among Liberian public health graduate students. METHODS: A semi-structured questionnaire was administered September-November 2021 to Master's in Public Health (MPH) students in Liberia. Potential barriers around technology access, understanding of quantitative science, and availability of mentorship were interrogated. Associations between barriers and self-reported likelihood of conducting quantitative research within six months of the investigation period were evaluated using ordinal logistic regression. RESULTS: Among 120 participating MPH students, 86% reported owning a personal computer, but 18.4% and 39.4% had machines with malfunctioning hardware and/or with battery power lasting ≤2 hours, respectively. On average, students reported having poor internet network 3.4 days weekly. 47% reported never using any computer software for analysis, and 46% reported no specific knowledge on statistical analysis. Students indicated spending a median 30 minutes per week reading scientific articles. Moreover, 50% had no access to quantitative research mentors. Despite barriers, 59% indicated they were very likely to undertake quantitative research in the next 6 months; only 7% indicated they were not at all likely. Computer ownership was found to be statistically significantly associated with higher likelihood of conducting quantitative research in the multivariable analysis (aOR: 4.90,95% CI: 1.54-16.3). CONCLUSION: The high likelihood of conducting quantitative research among MPH students contrasts with limitations around computing capacity, awareness of research tools/methods, and access to mentorship. To promote rigorous analytical research in Liberia, there is a need for systematic measures to enhance capacity for diverse quantitative methods through efforts sensitive to the local research environment.

Potential Impacts of Mass Nutritional Supplementation on Measles Dynamics: A Simulation Study.

The bidirectional interaction between undernutrition and infection can be devastating to child health. Nutritional deficiencies impair immunity and increase susceptibility to infection. Simultaneously, infections compound undernutrition by increasing metabolic demand and impairing nutrient absorption. Treatment of acute malnutrition (wasting) can reverse some of its deleterious effects and reduce susceptibility to infectious diseases. Nutrition-specific approaches may be packaged with other interventions, including immunization, to support overall child health. To understand how mass nutritional supplementation, treatment of wasting, and vaccination affect the dynamics of a vaccine-preventable infection, we developed a population-level, compartmental model of measles transmission stratified by age and nutrition status. We simulated a range of scenarios to assess the potential reductions in measles infection and mortality associated with targeted therapeutic feeding for children who are wasted and with a mass supplementation intervention. Nutrition interventions were assumed to increase engagement with the health sector, leading to increased vaccination rates. We found that the combination of wasting treatment and mass supplementation coverage followed by an increase in vaccination coverage of non-wasted children from a baseline of 75% to 85%, leads to 34% to 57% and 65% to 77% reduction in measles infection and mortality and 56% to 60% reduction in overall mortality among wasted children, compared with the wasting treatment alone. Our work highlights the synergistic benefits that may be achieved by leveraging mass nutritional supplementation as a touch point with the health system to increase rates of vaccination and improve child survival beyond what would be expected from the additive benefits of each intervention.

Liberia adherence and loss-to-follow-up in HIV and AIDS care and treatment: A retrospective cohort of adolescents and adults from 2016-2019.

Antiretroviral therapy (ART) is a lifesaving intervention for people living with HIV infection, reducing morbidity and mortality; it is likewise essential to reducing transmission. The "Treat all" strategy recommended by the World Health Organization has dramatically increased ART eligibility and improved access. However, retaining patients on ART has been a major challenge for many national programs in low- and middle-income settings, despite actionable local policies and ambitious targets. To estimate retention of patients along the HIV care cascade in Liberia, and identify factors associated with loss-to-follow-up (LTFU), death, and suboptimal treatment adherence, we conducted a nationwide retrospective cohort study utilizing facility and patient-level records. Patients aged ≥15 years, from 28 facilities who were first registered in HIV care from January 2016 -December 2017 were included. We used Cox proportional hazard models to explore associations between demographic and clinical factors and the outcomes of LTFU and death, and a multinomial logistic regression model to investigate factors associated with suboptimal treatment adherence. Among the 4185 records assessed, 27.4% (n = 1145) were males and the median age of the cohort was 37 (IQR: 30-45) years. At 24 months of follow-up, 41.8% (n = 1751) of patients were LTFU, 6.6% (n = 278) died, 0.5% (n = 21) stopped treatment, 3% (n = 127) transferred to another facility and 47.9% (n = 2008) were retained in care and treatment. The incidence of LTFU was 46.0 (95% CI: 40.8-51.6) per 100 person-years. Relative to patients at WHO clinical stage I at first treatment visit, patients at WHO clinical stage III [adjusted hazard ratio (aHR) 1.59, 95%CI: 1.21-2.09; p <0.001] or IV (aHR 2.41, 95%CI: 1.51-3.84; p <0.001) had increased risk of LTFU; whereas at registration, age category 35-44 (aHR 0.65, 95%CI: 0.44-0.98, p = 0.038) and 45 years and older (aHR 0.60, 95%CI: 0.39-0.93, p = 0.021) had a decreased risk. For death, patients assessed with WHO clinical stage II (aHR 2.35, 95%CI: 1.53-3.61, p<0.001), III (aHR 2.55, 95%CI: 1.75-3.71, p<0.001), and IV (aHR 4.21, 95%CI: 2.57-6.89, p<0.001) had an increased risk, while non-pregnant females (aHR 0.68, 95%CI: 0.51-0.92, p = 0.011) and pregnant females (aHR 0.42, 95%CI: 0.20-0.90, p = 0.026) had a decreased risk when compared to males. Suboptimal adherence was strongly associated with the experience of drug side effects-average adherence [adjusted odds ratio (aOR) 1.45, 95% CI: 1.06-1.99, p = 0.02) and poor adherence (aOR 1.75, 95%CI: 1.11-2.76, p = 0.016), and attending rural facility decreased the odds of average adherence (aOR 0.01, 95%CI: 0.01-0.03, p<0.001) and poor adherence (aOR 0.001, 95%CI: 0.0004-0.003, p<0.001). Loss-to-follow-up and poor adherence remain major challenges to achieving viral suppression targets in Liberia. Over two-fifths of patients engaged with the national HIV program are being lost to follow-up within 2 years of beginning care and treatment. WHO clinical stage III and IV were associated with LTFU while WHO clinical stage II, III and IV were associated with death. Suboptimal adherence was further associated with experience of drug side effects. Active support and close monitoring of patients who have signs of clinical progression and/or drug side effects could improve patient outcomes.

Coordinated support for local action: Modeling strategies to facilitate behavior adoption in urban-poor communities of Liberia for sustained COVID-19 suppression.

BACKGROUND: Long-term suppression of SARS-CoV-2 transmission will involve strategies that recognize the heterogeneous capacity of communities to undertake public health recommendations. We highlight the epidemiological impact of barriers to adoption and the potential role of community-led coordination of support for cases and high-risk contacts in urban slums. METHODS: A compartmental model representing transmission of SARS-CoV-2 in urban poor versus less socioeconomically vulnerable subpopulations was developed for Montserrado County, Liberia. Adoption of home-isolation behavior was assumed to be related to the proportion of each subpopulation residing in housing units with multiple rooms and with access to sanitation, water, and food. We evaluated the potential impact of increasing the maximum attainable proportion of adoption among urban poor following the scheduled lifting of the state of emergency. RESULTS: Without intervention, the model estimated higher overall infection burden but fewer severe cases among urban poor versus the less socioeconomically vulnerable population. With self-isolation by mildly symptomatic individuals, median reductions in cumulative infections, severe cases, and maximum daily incidence were 7.6% (IQR: 2.2%-20.9%), 7.0% (2.0%-18.5%), and 9.9% (2.5%-31.4%), respectively, in the urban poor subpopulation and 16.8% (5.5%-29.3%), 15.0% (5.0%-26.4%), and 28.1% (9.3%-47.8%) in the less socioeconomically vulnerable population. An increase in the maximum attainable percentage of behavior adoption by the urban slum subpopulation was associated with median reductions of 19.2% (10.1%-34.0%), 21.1% (13.3%-34.2%), and 26.0% (11.5%-48.9%) relative to the status quo scenario. CONCLUSIONS: Post-lockdown recommendations that prioritize home-isolation by confirmed cases are limited by resource constraints. Investing in community-based initiatives that coordinate support for self-identified cases and their contacts could more effectively suppress COVID-19 in settings with socioeconomic vulnerabilities.

Interruption of tuberculosis detection and care during the Ebola virus disease epidemic (2014-2015) in Liberia: time-series analyses for 2013-2017.

OBJECTIVE: Interrupted time-series analyses, using 5 years of routinely collected health information system data, were conducted to estimate the magnitude of impact of the 2014-2015 Ebola virus disease (EVD) epidemic and determine trends in tuberculosis (TB) care services in Liberia. METHODS: A segmented linear regression model was used to generate estimates and predictions for trends for three TB service indicators before, during, and after EVD, from January 2013 to December 2017. RESULTS: It was found that the number of presumptive TB cases declined significantly at the start of the EVD outbreak, with an estimated loss of 3222 cases (95% confidence interval (CI) -5691 to -752; P = 0.014). There was also an estimated loss of 709 cases per quarter post-EVD (95% CI -1346 to -71; P = 0.032). However, over the post-EVD period, quarterly increases were observed in the proportion of smear-positive to presumptive cases (1.45%, 95% CI 0.38% to 2.5%; P = 0.011) and the proportion of treatment success to TB cases evaluated (3.3%, 95% CI 0.82% to 5.79%; P = 0.013). CONCLUSIONS: These findings suggest that the EVD outbreak (2014-2015) negatively affected TB care services. Rigorous quantitative analyses can be used to assess the magnitude of interruption and advocate for preparedness in settings with limited healthcare capacity.

A review and agenda for integrated disease models including social and behavioural factors.

Social and behavioural factors are critical to the emergence, spread and containment of human disease, and are key determinants of the course, duration and outcomes of disease outbreaks. Recent epidemics of Ebola in West Africa and coronavirus disease 2019 (COVID-19) globally have reinforced the importance of developing infectious disease models that better integrate social and behavioural dynamics and theories. Meanwhile, the growth in capacity, coordination and prioritization of social science research and of risk communication and community engagement (RCCE) practice within the current pandemic response provides an opportunity for collaboration among epidemiological modellers, social scientists and RCCE practitioners towards a mutually beneficial research and practice agenda. Here, we provide a review of the current modelling methodologies and describe the challenges and opportunities for integrating them with social science research and RCCE practice. Finally, we set out an agenda for advancing transdisciplinary collaboration for integrated disease modelling and for more robust policy and practice for reducing disease transmission.

Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa.

BACKGROUND: The multi-host taeniosis/cysticercosis disease system is associated with significant neurological morbidity, as well as economic burden, globally. We investigated whether lower cost behavioral interventions are sufficient for local elimination of human cysticercosis in Boulkiemdé, Sanguié, and Nayala provinces of Burkina Faso. METHODOLOGY/PRINCIPAL FINDINGS: Province-specific data on human behaviors (i.e., latrine use and pork consumption) and serological prevalence of human and pig disease were used to inform a deterministic, compartmental model of the taeniosis/cysticercosis disease system. Parameters estimated via Bayesian melding provided posterior distributions for comparing transmission rates associated with human ingestion of Taenia solium cysticerci due to undercooking and human exposure to T. solium eggs in the environment. Reductions in transmission via these pathways were modeled to determine required effectiveness of a market-focused cooking behavior intervention and a community-led sanitation and hygiene program, independently and in combination, for eliminating human cysticercosis as a public health problem (<1 case per 1000 population). Transmission of cysticerci due to consumption of undercooked pork was found to vary significantly across transmission settings. In Sanguié, the rate of transmission due to undercooking was 6% higher than that in Boulkiemdé (95% CI: 1.03, 1.09; p-value < 0.001) and 35% lower than that in Nayala (95% CI: 0.64, 0.66; p-value < 0.001). We found that 67% and 62% reductions in undercooking of pork consumed in markets were associated with elimination of cysticercosis in Nayala and Sanguié, respectively. Elimination of active cysticercosis in Boulkiemdé required a 73% reduction. Less aggressive reductions of 25% to 30% in human exposure to Taenia solium eggs through sanitation and hygiene programs were associated with elimination in the provinces. CONCLUSIONS/SIGNIFICANCE: Despite heterogeneity in effectiveness due to local transmission dynamics and behaviors, education on the importance of proper cooking, in combination with community-led sanitation and hygiene efforts, has implications for reducing morbidity due to cysticercosis and neurocysticercosis.

Seeding COVID-19 across Sub-Saharan Africa: An Analysis of Reported Importation Events across 49 Countries.

The first case of COVID-19 in sub-Saharan Africa (SSA) was reported by Nigeria on February 27, 2020. Whereas case counts in the entire region remain considerably less than those being reported by individual countries in Europe, Asia, and the Americas, variation in preparedness and response capacity as well as in data availability has raised concerns about undetected transmission events in the SSA region. To capture epidemiological details related to early transmission events into and within countries, a line list was developed from publicly available data on institutional websites, situation reports, press releases, and social media accounts. The availability of indicators-gender, age, travel history, date of arrival in country, reporting date of confirmation, and how detected-for each imported case was assessed. We evaluated the relationship between the time to first reported importation and the Global Health Security Index (GHSI) overall score; 13,201 confirmed cases of COVID-19 were reported by 48 countries in SSA during the 54 days following the first known introduction to the region. Of the 2,516 cases for which travel history information was publicly available, 1,129 (44.9%) were considered importation events. Imported cases tended to be male (65.0%), with a median age of 41.0 years (range: 6 weeks-88 years; IQR: 31-54 years). A country's time to report its first importation was not related to the GHSI overall score, after controlling for air traffic. Countries in SSA generally reported with less publicly available detail over time and tended to have greater information on imported than local cases.

Participatory Design and Process Testing to Optimize Utility, Usability, and Acceptability of a Mobile Game for Promoting Evidence-Driven Public Health Decision-Making in Resource-Constrained Settings.

Innovative game-based training methods that leverage the ubiquity of cellphones and familiarity with phone-based interfaces have the potential to transform the training of public health practitioners in low-income countries such as Liberia. This article describes the design, development, and testing of a prototype of the Figure It Out mobile game. The prototype game uses a disease outbreak scenario to promote evidence-based decision-making in determining the causative agent and prescribing intervention measures to minimize epidemiological and logistical burdens in resource-limited settings. An initial prototype of the game developed by the US team was playtested and evaluated by focus groups with 20 University of Liberia Masters of Public Health (UL MPH) students. Results demonstrate that the learning objectives-improving search skills for identifying scientific evidence and considering evidence before decision-making during a public health emergency-were considered relevant and important in a setting that has repeatedly and recently experienced severe threats to public health. However, some of the game mechanics that were thought to enhance engagement such as trial-and-error and choose-your-own-path gameplay, were perceived by the target audience as distracting or too time-consuming, particularly in the context of a realistic emergency scenario. Gameplay metrics that mimicked real-world situations around lives lost, money spent, and time constraints during public health outbreaks were identified as relatable and necessary considerations. Our findings reflect cultural differences between the game development team and end users that have emphasized the need for end users to have an integral part of the design team; this formative evaluation has critically informed next steps in the iterative development process. Our multidisciplinary, cross-cultural and cross-national design team will be guided by Liberia-based public health students and faculty, as well as community members who represent our end user population in terms of experience and needs. These stakeholders will make key decisions regarding game objectives and mechanics, to be vetted and implemented by game design experts, epidemiologists, and software developers.

Unmet needs and behaviour during the Ebola response in Sierra Leone: a retrospective, mixed-methods analysis of community feedback from the Social Mobilization Action Consortium.

BACKGROUND: The west African Ebola epidemic (2014-15) necessitated behaviour change in settings with prevalent and pre-existing unmet needs as well as extensive mechanisms for local community action. We aimed to assess spatial and temporal trends in community-reported needs and associations with behaviour change, community engagement, and the overall outbreak situation in Sierra Leone. METHODS: We did a retrospective, mixed-methods study. Post-hoc analyses of data from 12 096 mobiliser visits as part of the Social Mobilization Action Consortium were used to describe the evolution of satisfied and unsatisfied needs (basic, security, autonomy, respect, and social support) between Nov 12, 2014, and Dec 18, 2015, and across 14 districts. Via Bayesian hierarchical regression modelling, we investigated associations between needs categories and behaviours (numbers of individuals referred to treatment within 24 h of symptom onset or deaths responded to with safe and dignified burials) and the role of community engagement programme status (initial vs follow-up visit) in the association between satisfied versus unsatisfied needs and behaviours. FINDINGS: In general, significant associations were observed between unsatisfied needs categories and both prompt referrals to treatment and safe burials. Most notably, communities expressing unsatisfied capacity needs reported fewer safe burials (relative risk [RR] 0·86, 95% credible interval [CrI] 0·82-0·91) and fewer prompt referrals to treatment (RR 0·76, 0·70-0·83) than did those without unsatisfied capacity needs. The exception was expression of unsatisfied basic needs, which was associated with significantly fewer prompt referrals only (RR 0·86, 95% CrI 0·79-0·93). Compared with triggering visits by community mobilisers, follow-up visits were associated with higher numbers of prompt referrals (RR 1·40, 95% CrI 1·30-1·50) and safe burials (RR 1·08, 1·02-1·14). INTERPRETATION: Community-based development of locally feasible, locally owned action plans, with the support of community mobilisers, has potential to address unmet needs for more sustained behaviour change in outbreak settings. FUNDING: Bill & Melinda Gates, Bill & Melinda Gates Foundation, and National Institutes of Health.

Spatio-temporal dynamics of measles outbreaks in Cameroon.

PURPOSE: In 2012, Cameroon experienced a large measles outbreak of over 14,000 cases. To determine the spatio-temporal dynamics of measles transmission in Cameroon, we analyzed weekly case data collected by the Ministry of Health. METHODS: We compared several multivariate time-series models of population movement to characterize the spatial spread of measles in Cameroon. Using the best model, we evaluated the contribution of population mobility to disease transmission at increasing geographic resolutions: region, department, and health district. RESULTS: Our spatio-temporal analysis showed that the power law model, which accounts for long-distance population movement, best represents the spatial spread of measles in Cameroon. Population movement between health districts within departments contributed to 7.6% (range: 0.4%-13.4%) of cases at the district level, whereas movement between departments within regions contributed to 16.0% (range: 1.3%-23.2%) of cases. Long-distance movement between regions contributed to 16.7% (range: 0.1%-59.0%) of cases at the region level, 20.1% (range: 7.1%-30.0%) at the department level, and 29.7% (range: 15.3%-47.6%) at the health district level. CONCLUSIONS: Population long-distance mobility is an important driver of measles dynamics in Cameroon. These findings demonstrate the need to improve our understanding of the roles of population mobility and local heterogeneity of vaccination coverage in the spread and control of measles in Cameroon.

Missing data treatments matter: an analysis of multiple imputation for anterior cervical discectomy and fusion procedures.

BACKGROUND CONTEXT: The presence of missing data is a limitation of large datasets, including the National Surgical Quality Improvement Program (NSQIP). In addressing this issue, most studies use complete case analysis, which excludes cases with missing data, thus potentially introducing selection bias. Multiple imputation, a statistically rigorous approach that approximates missing data and preserves sample size, may be an improvement over complete case analysis. PURPOSE: The present study aims to evaluate the impact of using multiple imputation in comparison with complete case analysis for assessing the associations between preoperative laboratory values and adverse outcomes following anterior cervical discectomy and fusion (ACDF) procedures. STUDY DESIGN/SETTING: This is a retrospective review of prospectively collected data. PATIENT SAMPLE: Patients undergoing one-level ACDF were identified in NSQIP 2012-2015. OUTCOME MEASURES: Perioperative adverse outcome variables assessed included the occurrence of any adverse event, severe adverse events, and hospital readmission. METHODS: Missing preoperative albumin and hematocrit values were handled using complete case analysis and multiple imputation. These preoperative laboratory levels were then tested for associations with 30-day postoperative outcomes using logistic regression. RESULTS: A total of 11,999 patients were included. Of this cohort, 63.5% of patients had missing preoperative albumin and 9.9% had missing preoperative hematocrit. When using complete case analysis, only 4,311 patients were studied. The removed patients were significantly younger, healthier, of a common body mass index, and male. Logistic regression analysis failed to identify either preoperative hypoalbuminemia or preoperative anemia as significantly associated with adverse outcomes. When employing multiple imputation, all 11,999 patients were included. Preoperative hypoalbuminemia was significantly associated with the occurrence of any adverse event and severe adverse events. Preoperative anemia was significantly associated with the occurrence of any adverse event, severe adverse events, and hospital readmission. CONCLUSIONS: Multiple imputation is a rigorous statistical procedure that is being increasingly used to address missing values in large datasets. Using this technique for ACDF avoided the loss of cases that may have affected the representativeness and power of the study and led to different results than complete case analysis. Multiple imputation should be considered for future spine studies.

Dynamic Models of Infectious Disease Transmission in Prisons and the General Population.

Incarcerated populations experience elevated burdens of infectious diseases, which are exacerbated by limited access to prevention measures. Dynamic models are used to assess the spread and control of diseases within correctional facilities and repercussions on the general population. Our systematic review of dynamic models of infectious diseases within correctional settings identified 34 studies published between 1996 and 2017. Of these, 23 focused on disease dynamics and intervention in prison without accounting for subsequent spread to the community. The main diseases modeled in these studies were human immunodeficiency virus (HIV; n = 14, 41%), tuberculosis (TB; n = 10, 29%), and hepatitis C virus (HCV; n = 7, 21%). Models were fitted to epidemiologic data in 14 studies; uncertainty and sensitivity analyses were conducted in 8, and validation of model projection against empirical data was done in 1 study. According to the models, prison-based screening and treatment may be highly effective strategies for reducing the burden of HIV, TB, HCV, and other sexually transmissible infections among prisoners and the general community. Decreasing incarceration rates were projected to reduce HIV and HCV infections among people who inject drugs and TB infections among all prisoners. Limitations of the modeling studies and opportunities for using dynamic models to develop quantitative evidence for informing prison infection control measures are discussed.

Treatments of Missing Values in Large National Data Affect Conclusions: The Impact of Multiple Imputation on Arthroplasty Research.

BACKGROUND: Despite the advantages of large, national datasets, one continuing concern is missing data values. Complete case analysis, where only cases with complete data are analyzed, is commonly used rather than more statistically rigorous approaches such as multiple imputation. This study characterizes the potential selection bias introduced using complete case analysis and compares the results of common regressions using both techniques following unicompartmental knee arthroplasty. METHODS: Patients undergoing unicompartmental knee arthroplasty were extracted from the 2005 to 2015 National Surgical Quality Improvement Program. As examples, the demographics of patients with and without missing preoperative albumin and hematocrit values were compared. Missing data were then treated with both complete case analysis and multiple imputation (an approach that reproduces the variation and associations that would have been present in a full dataset) and the conclusions of common regressions for adverse outcomes were compared. RESULTS: A total of 6117 patients were included, of which 56.7% were missing at least one value. Younger, female, and healthier patients were more likely to have missing preoperative albumin and hematocrit values. The use of complete case analysis removed 3467 patients from the study in comparison with multiple imputation which included all 6117 patients. The 2 methods of handling missing values led to differing associations of low preoperative laboratory values with commonly studied adverse outcomes. CONCLUSION: The use of complete case analysis can introduce selection bias and may lead to different conclusions in comparison with the statistically rigorous multiple imputation approach. Joint surgeons should consider the methods of handling missing values when interpreting arthroplasty research.

Characterizing risk of Ebola transmission based on frequency and type of case-contact exposures.

During the initial months of the 2013-2016 Ebola epidemic, rapid geographical dissemination and intense transmission challenged response efforts across West Africa. Contextual behaviours associated with increased risk of exposure included travel to high-transmission settings, caring for sick and preparing the deceased for traditional funerals. Although such behaviours are widespread in West Africa, high-transmission pockets were observed. Superspreading and clustering are typical phenomena in infectious disease outbreaks, as a relatively small number of transmission chains are often responsible for the majority of events. Determining the characteristics of contacts at greatest risk of developing disease and of cases with greatest transmission potential could therefore help curb propagation of infection. Our analysis of contact tracing data from Montserrado County, Liberia, suggested that the probability of transmission was 4.5 times higher for individuals who were reported as having contact with multiple cases. The probability of individuals developing disease was not significantly associated with age or sex of their source case but was higher when they were in the same household as the infectious case. Surveillance efforts for rapidly identifying symptomatic individuals and effectively messaged campaigns encouraging household members to bring the sick to designated treatment centres without administration of home care could mitigate transmission.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

Effectiveness of UNAIDS targets and HIV vaccination across 127 countries.

The HIV pandemic continues to impose enormous morbidity, mortality, and economic burdens across the globe. Simultaneously, innovations in antiretroviral therapy, diagnostic approaches, and vaccine development are providing novel tools for treatment-as-prevention and prophylaxis. We developed a mathematical model to evaluate the added benefit of an HIV vaccine in the context of goals to increase rates of diagnosis, treatment, and viral suppression in 127 countries. Under status quo interventions, we predict a median of 49 million [first and third quartiles 44M, 58M] incident cases globally from 2015 to 2035. Achieving the Joint United Nations Program on HIV/AIDS 95-95-95 target was estimated to avert 25 million [20M, 33M] of these new infections, and an additional 6.3 million [4.8M, 8.7M] reduction was projected with the 2020 introduction of a 50%-efficacy vaccine gradually scaled up to 70% coverage. This added benefit of prevention through vaccination motivates imminent and ongoing clinical trials of viable candidates to realize the goal of HIV control.