COVID-19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy.

OBJECTIVE: Mathematical models are vital tools to understand transmission dynamics and assess the impact of interventions to mitigate COVID-19. However, historically, their use in Africa has been limited. In this scoping review, we assess how mathematical models were used to study COVID-19 vaccination to potentially inform pandemic planning and response in Africa. METHODS: We searched six electronic databases: MEDLINE, Embase, Web of Science, Global Health, MathSciNet and Africa-Wide NiPAD, using keywords to identify articles focused on the use of mathematical modelling studies of COVID-19 vaccination in Africa that were published as of October 2022. We extracted the details on the country, author affiliation, characteristics of models, policy intent and heterogeneity factors. We assessed quality using 21-point scale criteria on model characteristics and content of the studies. RESULTS: The literature search yielded 462 articles, of which 32 were included based on the eligibility criteria. Nineteen (59%) studies had a first author affiliated with an African country. Of the 32 included studies, 30 (94%) were compartmental models. By country, most studies were about or included South Africa (n = 12, 37%), followed by Morocco (n = 6, 19%) and Ethiopia (n = 5, 16%). Most studies (n = 19, 59%) assessed the impact of increasing vaccination coverage on COVID-19 burden. Half (n = 16, 50%) had policy intent: prioritising or selecting interventions, pandemic planning and response, vaccine distribution and optimisation strategies and understanding transmission dynamics of COVID-19. Fourteen studies (44%) were of medium quality and eight (25%) were of high quality. CONCLUSIONS: While decision-makers could draw vital insights from the evidence generated from mathematical modelling to inform policy, we found that there was limited use of such models exploring vaccination impacts for COVID-19 in Africa. The disparity can be addressed by scaling up mathematical modelling training, increasing collaborative opportunities between modellers and policymakers, and increasing access to funding.

Patient-reported outcome measures for primary hyperparathyroidism: a systematic review of measurement properties.

BACKGROUND: The quality of patient-reported outcome measures (PROMs) used to assess the outcomes of primary hyperparathyroidism (PHPT), a common endocrine disorder that can negatively affect patients' health-related quality of life due to chronic symptoms, has not been rigorously examined. This systematic review aimed to summarize and evaluate evidence on the measurement properties of PROMs used in adult patients with PHPT, and to provide recommendations for appropriate measure selection. METHODS: After PROSPERO registration (CRD42023438287), Medline, EMBASE, CINAHL Complete, Web of Science, PsycINFO, and Cochrane Trials were searched for full-text articles in English investigating PROM development, pilot studies, or evaluation of at least one PROM measurement property in adult patients with any clinical form of PHPT. Two reviewers independently identified studies for inclusion and conducted the review following the Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) Methodology to assess risk of bias, evaluate the quality of measurement properties, and grade the certainty of evidence. RESULTS: From 4989 records, nine PROM development or validation studies were identified for three PROMs: the SF-36, PAS, and PHPQoL. Though the PAS demonstrated sufficient test-retest reliability and convergent validity, and the PHPQoL sufficient test-retest reliability, convergent validity, and responsiveness, the certainty of evidence was low-to-very low due to risk of bias. All three PROMs lacked sufficient evidence for content validity in patients with PHPT. CONCLUSIONS: Based upon the available evidence, the SF-36, PAS, and PHPQoL cannot currently be recommended for use in research or clinical care, raising important questions about the conclusions of studies using these PROMs. Further validation studies or the development of more relevant PROMs with strong measurement properties for this patient population are needed.

Anti-racism curricula in undergraduate medical education: A scoping review.

PURPOSE: Medical educators have increasingly focused on the systemic effects of racism on health inequities in the United States (U.S.) and globally. There is a call for educators to teach students how to actively promote an anti-racist culture in healthcare. This scoping review assesses the existing undergraduate medical education (UME) literature of anti-racism curricula, implementation, and assessment. METHODS: The Ovid, Embase, ERIC, Web of Science, and MedEdPORTAL databases were queried on 7 April 2023. Keywords included anti-racism, medical education, and assessment. Inclusion criteria consisted of any UME anti-racism publication. Non-English articles with no UME anti-racism curriculum were excluded. Two independent reviewers screened the abstracts, followed by full-text appraisal. Data was extracted using a predetermined framework based on Kirkpatrick's educational outcomes model, Miller's pyramid for assessing clinical competence, and Sotto-Santiago's theoretical framework for anti-racism curricula. Study characteristics and anti-racism curriculum components (instructional design, assessment, outcomes) were collected and synthesized. RESULTS: In total, 1064 articles were screened. Of these, 20 met the inclusion criteria, with 90% (n = 18) published in the past five years. Learners ranged from first-year to fourth-year medical students. Study designs included pre- and post-test evaluations (n = 10; 50%), post-test evaluations only (n = 7; 35%), and qualitative assessments (n = 3; 15%). Educational interventions included lectures (n = 10, 50%), multimedia (n = 6, 30%), small-group case discussions (n = 15, 75%), large-group discussions (n = 5, 25%), and reflections (n = 5, 25%). Evaluation tools for these curricula included surveys (n = 18; 90%), focus groups (n = 4; 20%), and direct observations (n = 1; 5%). CONCLUSIONS: Our scoping review highlights the growing attention to anti-racism in UME curricula. We identified a gap in published assessments of behavior change in applying knowledge and skills to anti-racist action in UME training. We also provide considerations for developing UME anti-racism curricula. These include explicitly naming and defining anti-racism as well as incorporating longitudinal learning opportunities and assessments.

Efficacy of Antibiotic Regimens for Meningitis in Young Infants Aged 0-59 Days: A Systematic Review.

CONTEXT: Meningitis is associated with high mortality risk in young infants, yet the optimal treatment regimen is unclear. OBJECTIVES: To systematically evaluate the efficacy of antibiotic regimens to treat meningitis in young infants aged 0 to 59 days on critical clinical outcomes. DATA SOURCES: MEDLINE, Embase, CINAHL, WHO Global Index Medicus, and Cochrane Central Registry of Trials. STUDY SELECTION: We included randomized controlled trials (RCTs) of young infants with meningitis (population) comparing the efficacy of antibiotic regimens (interventions) with alternate regimens (control) on clinical outcomes. DATA EXTRACTION: We extracted data on study characteristics and assessed risk of bias in duplicate. Grading of Recommendations Assessment, Development, and Evaluation was used to assess certainty of evidence. RESULTS: Of 1088 studies screened, only 2 RCTs were identified. They included 168 infants from 5 countries and were conducted between 1976 and 2015. Neither study compared current World Health Organization-recommended regimens. One multisite trial from 4 countries compared intrathecal gentamicin plus systemic ampicillin/gentamicin to systemic ampicillin/gentamicin and found no difference in mortality (relative risk, 0.88; 95% confidence interval, 0.41-1.53; 1 trial, n = 98, very low certainty of evidence) or adverse events (no events in either trial arm). Another trial in India compared a 10-day versus 14-day course of antibiotics and found no difference in mortality (relative risk, 0.88; 95% confidence interval, 0.41-1.53; 1 trial, n = 98, very low certainty of evidence) or other outcomes. CONCLUSIONS: Trial data on the efficacy of antibiotic regimens in young infant meningitis are scarce. Rigorous RCTs are needed to inform recommendations for optimal antibiotic regimens for meningitis treatment in this vulnerable population, particularly within the context of changing epidemiology and increasing antimicrobial resistance.

Predictive Accuracy of Infant Clinical Sign Algorithms for Mortality in Young Infants Aged 0 to 59 Days: A Systematic Review.

CONTEXT: Clinical sign algorithms are a key strategy to identify young infants at risk of mortality. OBJECTIVE: Synthesize the evidence on the accuracy of clinical sign algorithms to predict all-cause mortality in young infants 0-59 days. DATA SOURCES: MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL Registry of Trials. STUDY SELECTION: Studies evaluating the accuracy of infant clinical sign algorithms to predict mortality. DATA EXTRACTION: We used Cochrane methods for study screening, data extraction, and risk of bias assessment. We determined certainty of evidence using Grading of Recommendations Assessment Development and Evaluation. RESULTS: We included 11 studies examining 26 algorithms. Three studies from non-hospital/community settings examined sign-based checklists (n = 13). Eight hospital-based studies validated regression models (n = 13), which were administered as weighted scores (n = 8), regression formulas (n = 4), and a nomogram (n = 1). One checklist from India had a sensitivity of 98% (95% CI: 88%-100%) and specificity of 94% (93%-95%) for predicting sepsis-related deaths. However, external validation in Bangladesh showed very low sensitivity of 3% (0%-10%) with specificity of 99% (99%-99%) for all-cause mortality (ages 0-9 days). For hospital-based prediction models, area under the curve (AUC) ranged from 0.76-0.93 (n = 13). The Score for Essential Neonatal Symptoms and Signs had an AUC of 0.89 (0.84-0.93) in the derivation cohort for mortality, and external validation showed an AUC of 0.83 (0.83-0.84). LIMITATIONS: Heterogeneity of algorithms and lack of external validation limited the evidence. CONCLUSIONS: Clinical sign algorithms may help identify at-risk young infants, particularly in hospital settings; however, overall certainty of evidence is low with limited external validation.

Diagnostic Accuracy of Clinical Sign Algorithms to Identify Sepsis in Young Infants Aged 0 to 59 Days: A Systematic Review and Meta-analysis.

CONTEXT: Accurate identification of possible sepsis in young infants is needed to effectively manage and reduce sepsis-related morbidity and mortality. OBJECTIVE: Synthesize evidence on the diagnostic accuracy of clinical sign algorithms to identify young infants (aged 0-59 days) with suspected sepsis. DATA SOURCES: MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL Registry of Trials. STUDY SELECTION: Studies reporting diagnostic accuracy measures of algorithms including infant clinical signs to identify young infants with suspected sepsis. DATA EXTRACTION: We used Cochrane methods for study screening, data extraction, risk of bias assessment, and determining certainty of evidence using Grading of Recommendations Assessment Development and Evaluation. RESULTS: We included 19 studies (12 Integrated Management of Childhood Illness [IMCI] and 7 non-IMCI studies). The current World Health Organization (WHO) 7-sign IMCI algorithm had a sensitivity of 79% (95% CI 77%-82%) and specificity of 77% (95% CI 76%-78%) for identifying sick infants aged 0-59 days requiring hospitalization/antibiotics (1 study, N = 8889). Any IMCI algorithm had a pooled sensitivity of 84% (95% CI 75%-90%) and specificity of 80% (95% CI 64%-90%) for identifying suspected sepsis (11 studies, N = 15523). When restricting the reference standard to laboratory-supported sepsis, any IMCI algorithm had a pooled sensitivity of 86% (95% CI 82%-90%) and lower specificity of 61% (95% CI 49%-72%) (6 studies, N = 14278). LIMITATIONS: Heterogeneity of algorithms and reference standards limited the evidence. CONCLUSIONS: IMCI algorithms had acceptable sensitivity for identifying young infants with suspected sepsis. Specificity was lower using a reference standard of laboratory-supported sepsis diagnosis.

Communications for US Populations With Limited English Proficiency During Infectious Disease Outbreaks: A Scoping Review.

The COVID-19 pandemic has highlighted the need for research about communicating with populations who have limited English proficiency in the United States during infectious disease outbreaks. These populations have experienced significantly worse health outcomes during emergencies, including the COVID-19 pandemic, and evidence-based risk communications are critical to protecting their health. To support improved development of emergency communications for these communities, we conducted a scoping review that examined the extent of research available, with an intent to identify which communications topics are covered in the literature and where research gaps exist. Following the JBI framework, with reporting guided by the PRISMA extension for scoping reviews, 6 electronic databases were systematically searched in October 2022. The inclusion criteria for articles selected were: data collected between 2009 and 2022, published in English, and focused on communications pertaining to emergency infectious disease outbreaks (eg, H1N1 influenza, Zika virus, COVID-19) for populations with limited English proficiency. Of 2,049 articles identified through the search, 31 met the inclusion criteria and were selected for review. We identified major limitations in the evidence base: a majority of studies were conducted only among Spanish speakers or during the COVID-19 pandemic, and most used qualitative or nonrandom samples. Most studies documented basic language barriers in communications, but there was little exploration of more nuanced barriers, such as cultural relevance or social context. Ahead of future outbreaks, more research is urgently needed to examine the information landscapes of populations with limited English proficiency, to inform the development of more effective communications strategies from public health institutions and others.