Population size, prevalence, and incidence are essential metrics that influence public health programming and policy. However, stakeholders are frequently tasked with setting performance targets, ...reporting global indicators, and designing policies based on multiple (often incongruous) estimates of these variables, and they often do so in the absence of a formal, transparent framework for reaching a consensus estimate.
This study aims to describe a model to synthesize multiple study estimates while incorporating stakeholder knowledge, introduce an R Shiny app to implement the model, and demonstrate the model and app using real data.
In this study, we developed a Bayesian hierarchical model to synthesize multiple study estimates that allow the user to incorporate the quality of each estimate as a confidence score. The model was implemented as a user-friendly R Shiny app aimed at practitioners of population size estimation. The underlying Bayesian model was programmed in Stan for efficient sampling and computation.
The app was demonstrated using biobehavioral survey-based population size estimates (and accompanying confidence scores) of female sex workers and men who have sex with men from 3 survey locations in a country in sub-Saharan Africa. The consensus results incorporating confidence scores are compared with the case where they are absent, and the results with confidence scores are shown to perform better according to an app-supplied metric for unaccounted-for variation.
The utility of the triangulator model, including the incorporation of confidence scores, as a user-friendly app is demonstrated using a use case example. Our results offer empirical evidence of the model's effectiveness in producing an accurate consensus estimate and emphasize the significant impact that the accessible model and app offer for public health. It offers a solution to the long-standing problem of synthesizing multiple estimates, potentially leading to more informed and evidence-based decision-making processes. The Triangulator has broad utility and flexibility to be adapted and used in various other contexts and regions to address similar challenges.
Falls are highly prevalent amongst older people and have substantial financial and social costs for health services and the community. Prevention of falls is the key to managing this threat to older ...people. General practitioners can identify older people at risk of falls on their caseloads. Once identified, actions can be taken to reduce the risk of falls by referring to appropriate services available in the community, such as allied health practitioners. However, the level of engagement in evidence based falls prevention by GPs is unknown. This study aimed to explore how British general practitioners (GPs) address falls prevention with older people, and to determine if there are any gaps in practice. As a pilot study, another aim was to test the feasibility of methods to survey GPs, if a larger survey was warranted from the findings. An on-line cross-sectional survey was distributed by email to all the Clinical Commissioning Groups in NHS England (
= 213) and individual general practices listed on the NHS Choices website, supplemented by invitations distributed to CCGs through Twitter and LinkedIn sites. Thirty-seven responses were received. Most GPs were unfamiliar with the 2013 NICE guidelines on assessment and prevention of falls in older people (51.4%,
= 19), and only 29.7% (
= 11) asked older people if they had fallen during consultations. If falls risk was identified, 81.1% (
= 30) frequently made referrals to physiotherapy (PT) and 56.8% (
= 21) to occupational therapy (OT). Most GPs did not identify older people on their caseloads as being at risk of falls unless they presented with a fall, and referral rates to relevant AHPs or falls prevention programs were low. Barriers to implementation of falls prevention best practice were identified. Alternative methods are needed to capture the falls prevention practice of a wider sample of GPs.
This research project aimed at obtaining an in-depth analysis of the experiences of self-identified co-dependents, who chose twelve-steps groups as a way for dealing with difficulties identified as ...co-dependency. Interpretative phenomenological analysis (IPA) was used as the methodology for the research. Eight participants volunteered from local support groups for co-dependency in the UK. Data were collected through 3 in-depth interviews with each participant over a period of 3–6 months. A visual method was used to gain a more in-depth phenomenological perspective. It included photographs, drawings and images chosen by the participants to describe their experiences. The analysis revealed 2 contradicting and complementary themes: (1) representations of the twelve-step group as a helpful tool and (2) representations of the twelve-step group as no longer meaningful. It demonstrated that the participants found their groups useful as an initial pathway for recovery; however, it did not feature as a central aspect in their recovery, as different levels of engagement were described. The results of this study provide a base for developing a more empathic and contextualised understanding of the experience of individuals who attend twelve-step groups for co-dependency, which in turn will enable health professionals to offer support which is relevant to these individuals’ experiences.
Background. Although vaccination with trivalent inactivated influenza vaccine (TIV) is recommended for all pregnant women, no vaccine effectiveness (VE) studies of TIV in pregnant women have assessed ...laboratory-confirmed influenza outcomes. Methods. We conducted a case-control study over 2 influenza seasons (2010–2011 and 2011–2012) among Kaiser Permanente health plan members in 2 metropolitan areas in California and Oregon. We compared the proportion vaccinated among 100 influenza cases (confirmed by reverse transcription polymerase chain reaction) with the proportions vaccinated among 192 controls with acute respiratory illness (ARI) who tested negative for influenza and 200 controls without ARI (matched by season, site, and trimester). Results. Among influenza cases, 42% were vaccinated during the study season compared to 58% and 63% vaccinated among influenza-negative controls and matched ARI-negative controls, respectively. The adjusted VE of the current season vaccine against influenza A and B was 44% (95% confidence interval CI, 5%–67%) using the influenza-negative controls and 53% (95% CI, 24%–72%) using the ARI-negative controls. Receipt of the prior season's vaccine, however, had an effect similar to receipt of the current season's vaccine. As such, vaccination in either or both seasons had statistically similar adjusted VE using influenza-negative controls (VE point estimates range = 51%–76%) and ARI-negative controls (48%–76%). Conclusions. Influenza vaccination reduced the risk of ARI associated with laboratory-confirmed influenza among pregnant women by about one-half, similar to VE observed among all adults during these seasons.
Abstract
Background
Coronavirus disease 2019 (COVID-19) continues to cause significant morbidity and mortality worldwide. Correctional and detention facilities are at high risk of experiencing ...outbreaks. We aimed to evaluate cohort-based testing among detained persons exposed to laboratory-confirmed cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in order to identify presymptomatic and asymptomatic cases.
Methods
During 1–19 May 2020, 2 testing strategies were implemented in 12 tiers or housing units of the Cook County Jail, Chicago, Illinois. Detained persons were approached to participate in serial testing (n = 137) and offered tests at 3 time points over 14 days (day 1, days 3–5, and days 13–14). The second group was offered a single test and interview at the end of a 14-day quarantine period (day 14 group) (n = 87).
Results
224 detained persons were approached for participation and, of these, 194 (87%) participated in ≥1 interview and 172 (77%) had ≥1 test. Of the 172 tested, 19 were positive for SARS-CoV-2. In the serial testing group, 17 (89%) new cases were detected, 16 (84%) on day 1, 1 (5%) on days 3–5, and none on days 13–14; in the day 14 group, 2 (11%) cases were identified. More than half (12/19; 63%) of the newly identified cases were presymptomatic or asymptomatic.
Conclusions
Our findings highlight the utility of cohort-based testing promptly after initiating quarantine within a housing tier. Cohort-based testing efforts identified new SARS-CoV-2 asymptomatic and presymptomatic infections that may have been missed by symptom screening alone.
Our findings suggest that early cohort-based testing in detained persons helped identify new SARS-CoV-2 asymptomatic and presymptomatic infections that may have been missed by symptom screening alone. Frequency of testing may be dependent on status of outbreak in the facility.
Population size estimates (PSE) provide critical information in determining resource allocation for HIV services geared toward those at high risk of HIV, including female sex workers, men who have ...sex with men, and people who inject drugs. Capture-recapture (CRC) is often used to estimate the size of these often-hidden populations. Compared with the commonly used 2-source CRC, CRC relying on 3 (or more) samples (3S-CRC) can provide more robust PSE but involve far more complex statistical analysis.
This study aims to design and describe the Shiny application (shinyrecap), a user-friendly interface that can be used by field epidemiologists to produce PSE.
shinyrecap is built on the Shiny web application framework for R. This allows it to seamlessly integrate with the sophisticated CRC statistical packages (eg, Rcapture, dga, LCMCR). Additionally, the application may be accessed online or run locally on the user's machine.
The application enables users to engage in sample size calculation based on a simulation framework. It assists in the proper formatting of collected data by providing a tool to convert commonly used formats to that used by the analysis software. A wide variety of methodologies are supported by the analysis tool, including log-linear, Bayesian model averaging, and Bayesian latent class models. For each methodology, diagnostics and model checking interfaces are provided.
Through a use case, we demonstrated the broad utility of this powerful tool with 3S-CRC data to produce PSE for female sex workers in a subnational unit of a country in sub-Saharan Africa.
Highlights • Most vaccinated children receive their influenza vaccination at a doctor's office. • Place of vaccination has changed very little over four influenza seasons. • There is large ...variability in vaccination setting by age, race/ethnicity, income, and MSA.
We investigated progress towards UNAIDS 90-90-90 targets among female sex workers in Kampala, Uganda, who bear a disproportionate burden of HIV.
Between April and December 2012, 1,487 female sex ...workers, defined as women, 15-49 years, residing in greater Kampala, and selling sex for money in the last 6 months, were recruited using respondent-driven sampling. Venous blood was collected for HIV and viral load testing viral load suppression (VLS) defined as <1,000 copies/mL. We collected data using audio computer-assisted self-interviews and calculated weighted population-level estimates.
The median age was 27 years (interquartile range: 23 to 32). HIV seroprevalence was 31.4% (95% confidence interval CI: 29.0, 33.7%). Among all female sex workers who tested HIV-positive in the survey (population-level targets), 45.5% (95% CI: 40.1, 51.0) had knowledge of their serostatus (population-level target: 90%), 37.8% (95% CI: 32.2, 42.8) self-reported to be on ART (population-level target: 81%), and 35.2% (95% CI: 20.7, 30.4) were virally suppressed (population-level target: 73%).
HIV prevalence among Kampala female sex workers is high, whereas serostatus knowledge and VLS are far below UNAIDS targets. Kampala female sex workers are in need of intensified and targeted HIV prevention and control efforts.
Purpose. The International Classification of Functioning, Disability and Health (ICF) is advocated as a tool to structure rehabilitation and a universal language to aid communication, within the ...multi-disciplinary team (MDT). The ICF may also facilitate clarification of team roles and clinical reasoning for intervention. This article aims to explore both factors in stroke rehabilitation.
Method. Following a review of the literature, a summary was presented and discussed with clinicians working within stroke rehabilitation, to gather expert opinions. The discussions were informal, being part of service development and on-going education. The clinicians summarised key themes for the potential use of the ICF within clinical practice.
Results. Two key themes emerged from the literature and expert opinion for the potential use of the ICF in stroke rehabilitation: (i) to aid communication and structure service provision, (ii) to clarify team roles and aid clinical reasoning. Expert opinion was that clarification of team roles needs to occur at a local level due to the skill mix, particular interests, setting and staffing levels within individual teams. The ICF has the potential to demonstrate/facilitate clinical reasoning, especially when different MDT members are working on the same intervention.
Conclusion. There is potential for the ICF to be used to clarify team roles and demonstrate clinical reasoning within stroke rehabilitation. Further experiential research is required to substantiate this view.
Nigeria has the fourth largest burden of HIV globally. Key populations, including female sex workers, men who have sex with men, and people who inject drugs, are more vulnerable to HIV than the ...general population due to stigmatized and criminalized behaviors. Reliable key population size estimates are needed to guide HIV epidemic response efforts.
The objective of our study was to use empirical methods for sampling and analysis to improve the quality of population size estimates of female sex workers, men who have sex with men, and people who inject drugs in 7 states (Akwa Ibom, Benue, Cross River, Lagos, Nasarawa, Rivers, and the Federal Capital Territory) of Nigeria for program planning and to demonstrate improved statistical estimation methods.
From October to December 2018, we used 3-source capture-recapture to produce population size estimates in 7 states in Nigeria. Hotspots were mapped before 3-source capture-recapture started. We sampled female sex workers, men who have sex with men, and people who inject drugs during 3 independent captures about one week apart. During hotspot encounters, key population members were offered inexpensive, memorable objects unique to each capture round. In subsequent rounds, key population members were offered an object and asked to identify objects received during previous rounds (if any). Correct responses were tallied and recorded on tablets. Data were aggregated by key population and state for analysis. Median population size estimates were derived using Bayesian nonparametric latent-class models with 80% highest density intervals.
Overall, we sampled approximately 310,000 persons at 9015 hotspots during 3 independent captures. Population size estimates for female sex workers ranged from 14,500 to 64,300; population size estimates for men who have sex with men ranged from 3200 to 41,400; and population size estimates for people who inject drugs ranged from 3400 to 30,400.
This was the first implementation of these 3-source capture-recapture methods in Nigeria. Our population size estimates were larger than previously documented for each key population in all states. The Bayesian models account for factors, such as social visibility, that influence heterogeneous capture probabilities, resulting in more reliable population size estimates. The larger population size estimates suggest a need for programmatic scale-up to reach these populations, which are at highest risk for HIV.
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