Surveillance Metrics Research Articles

Research progress of lipid-derived parameters in atherosclerotic cardiovascular disease

Dyslipidemia stands as an autonomous peril in the realm of atherosclerotic cardiovascular maladies. Prompt identification and timely intervention in the case of dyslipidemia hold promise for substantially curbing the onset and fatality rates associated with coronary heart disease. Traditional lipid surveillance metrics employed in clinical settings, such as low-density lipoprotein cholesterol, exhibit notable limitations. Conversely, lipid-derived parameters emerge as formidable contenders, demonstrating a capacity to amalgamate and quantify disparate risk factors and multifactorial etiologies inherent in a given disease. By encompassing a broader spectrum of information than singular indices, these parameters offer a more profound insight into disease progression by virtue of their grounding in the physiological intricacies of lipid metabolism. Drawing upon extant domestic and international guidelines and research, this discourse delineates and synthesizes four lipid-derived parameters with promising clinical applications: atherogenic index of plasma, non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio, apolipoprotein B/A1 ratio, and lipoprotein combine index, and forwards a perspective grounded in current strides in clinical research.

Surveillance Metrics and History of the COVID-19 Pandemic in Central Asia: Updated Epidemiological Assessment.

This study updates the COVID-19 pandemic surveillance in Central Asia we conducted during the first year of the pandemic by providing 2 additional years of data for the region. The historical context provided through additional data can inform regional preparedness and early responses to infectious outbreaks of either the SARS-CoV-2 virus or future pathogens in Central Asia. First, we aim to measure whether there was an expansion or contraction in the pandemic in Central Asia when the World Health Organization (WHO) declared the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in Central Asia. Traditional surveillance metrics, including counts and rates of COVID-19 transmissions and deaths, and enhanced surveillance indicators, including speed, acceleration, jerk, and persistence, were used to measure shifts in the pandemic. To identify the appearance and duration of variants of concern, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t test to determine whether regional speed was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the sample period. Speed for the region had remained below the outbreak threshold for 7 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant, the coefficients were relatively small in magnitude (0.125 and 0.347, respectively). Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, were both significant and negative, meaning the clustering effect of new COVID-19 cases became even smaller in the 2 weeks around the WHO declaration. From December 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of speed equal to 10 became entirely insignificant for the first time in March 2023. Although COVID-19 continues to circulate in Central Asia, the rate of transmission remained well below the threshold of an outbreak for 7 months ahead of the WHO declaration. COVID-19 appeared to be endemic in the region and no longer reached the threshold of a pandemic. Both standard and enhanced surveillance metrics suggest the pandemic had ended by the time of the WHO declaration.

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in the Middle East and North Africa: Longitudinal Trend Analysis.

This study updates the COVID-19 pandemic surveillance in the Middle East and North Africa (MENA) we first conducted in 2020 with 2 additional years of data for the region. The objective of this study is to determine whether the MENA region meets the criteria for moving from a pandemic to endemic. In doing so, this study considers pandemic trends, dynamic and genomic surveillance methods, and region-specific historical context for the pandemic. These considerations continue through the World Health Organization (WHO) declaration of the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. In addition to updates to traditional surveillance data and dynamic panel estimates from the original study by Post et al, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t test to determine whether regional weekly speed of COVID-19 spread was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data from September 4, 2020, to May 12, 2023. The speed of COVID-19 spread for the region had remained below the outbreak threshold for 7 continuous months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant and positive, the weekly shift parameters suggested the coefficients had most recently turned negative, meaning the clustering effect of new COVID-19 cases became even smaller in the 2 weeks around the WHO declaration. From December 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of the speed of spread equal to 10 became entirely insignificant from October 2022 onward. The COVID-19 pandemic had far-reaching effects on MENA, impacting health care systems, economies, and social well-being. Although COVID-19 continues to circulate in the MENA region, the rate of transmission remained well below the threshold of an outbreak for over 1 year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had transitioned to endemic by the time of the WHO declaration.

Population Percentage and Population Size of Men Who Have Sex With Men in the United States, 2017-2021: Meta-Analysis of 5 Population-Based Surveys.

Male-to-male sexual transmission continues to account for the greatest proportion of new HIV diagnoses in the United States. However, calculating population-specific surveillance metrics for HIV and other sexually transmitted infections requires regularly updated estimates of the number and proportion of men who have sex with men (MSM) in the United States, which are not collected by census surveys. The purpose of this analysis was to estimate the number and percentage of MSM in the United States from population-based surveys. We used data from 5 population-based surveys to calculate weighted estimates of the proportion of MSM in the United States and pooled these estimates using meta-analytic procedures. We estimated the proportion of MSM using sexual behavior-based questions (encompassing anal or oral sex) for 3 recall periods-past 12 months, past 5 years, and lifetime. In addition, we estimated the proportion of MSM using self-reported identity and attraction survey responses. The total number of MSM and non-MSM in the United States were calculated from estimates of the percentage of MSM who reported sex with another man in the past 12 months. The percentage of MSM varied by recall period: 3.3% (95% CI 1.7%-4.9%) indicated sex with another male in the past 12 months, 4.7% (95% CI 0.0%-33.8%) in the past 5 years, and 6.2% (95% CI 2.9%-9.5%) in their lifetime. There were comparable percentages of men who identified as gay or bisexual (3.4%, 95% CI 2.2%-4.6%) or who indicated that they are attracted to other men (4.9%, 95% CI 3.1%-6.7%) based on pooled estimates. Our estimate of the total number of MSM in the United States is 4,230,000 (95% CI 2,179,000-6,281,000) based on the history of recent sexual behavior (sex with another man in the past 12 months). We calculated the pooled percentage and number of MSM in the United States from a meta-analysis of population-based surveys collected from 2017 to 2021. These estimates update and expand upon those derived from the Centers for Disease Control and Prevention in 2012 by including estimates of the percentage of MSM based on sexual identity and sexual attraction. The percentage and number of MSM in the United States is an important indicator for calculating population-specific disease rates and eligibility for preventive interventions such as pre-exposure prophylaxis.

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis.

In May 2020, the World Health Organization (WHO) declared Latin America and the Caribbean (LAC) the epicenter of the COVID-19 pandemic, with over 40% of worldwide COVID-19-related deaths at the time. This high disease burden was a result of the unique circumstances in LAC. This study aimed to (1) measure whether the pandemic was expanding or contracting in LAC when the WHO declared the end of COVID-19 as a public health emergency of international concern on May 5, 2023; (2) use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history; and (3) provide, with a focus on prevention policies, a historical context for the course of the pandemic in the region. In addition to updates of traditional surveillance data and dynamic panel estimates from the original study, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern (VOCs). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Additionally, we conducted a 1-sided t test for whether the regional weekly speed (rate of novel COVID-19 transmission) was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the period from August 2020 to May 2023. The speed of pandemic spread for the region had remained below the outbreak threshold for 6 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant for the 120-day period ending on the week of May 5, 2023, the coefficients were relatively modest in magnitude (0.457 and 0.491, respectively). Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any change in this clustering effect of cases on future cases. From December 2021 onward, Omicron was the predominant VOC in sequenced viral samples. The rolling t test of speed=10 became entirely insignificant from January 2023 onward. Although COVID-19 continues to circulate in LAC, surveillance data suggest COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. However, the region experienced a high COVID-19 burden in the early stages of the pandemic, and prevention policies should be an immediate focus in future pandemics. Ahead of vaccination development, these policies can include widespread testing of individuals and an epidemiological task force with a contact-tracing system.

The Development of the Municipal Registry of People with Diabetes in Porto Alegre, Brazil.

Background/Objective: Diabetes registries that enhance surveillance and improve medical care are uncommon in low- and middle-income countries, where most of the diabetes burden lies. We aimed to describe the methodological and technical aspects adopted in the development of a municipal registry of people with diabetes using local and national Brazilian National Health System databases. Methods: We obtained data between July 2018 and June 2021 based on eight databases covering primary care, specialty and emergency consultations, medication dispensing, outpatient exam management, hospitalizations, and deaths. We identified diabetes using the International Classification of Disease (ICD), International Classification of Primary Care (ICPC), medications for diabetes, hospital codes for the treatment of diabetes complications, and exams for diabetes management. Results: After data processing and database merging using deterministic and probabilistic linkage, we identified 73,185 people with diabetes. Considering that 1.33 million people live in Porto Alegre, the registry captured 5.5% of the population. Conclusions: With additional data processing, the registry can reveal information on the treatment and outcomes of people with diabetes who are receiving publicly financed care in Porto Alegre. It will provide metrics for epidemiologic surveillance, such as the incidence, prevalence, rates, and trends of complications and causes of mortality; identify inadequacies; and provide information. It will enable healthcare providers to monitor the quality of care, identify inadequacies, and provide feedback as needed.

The next frontier of healthcare-associated infection (HAI) surveillance metrics: Beyond device-associated infections.

In recent years, it has become increasingly evident that surveillance metrics for invasive device-associated infections (ie, central-line-associated bloodstream infections, ventilator-associated pneumonias, and catheter-associated urinary tract infections) do not capture all harms; they capture only a subset of healthcare-associated infections (HAIs). Although prevention of device-associated infections remains critical, we need to address the full spectrum of potential harms from device use and non-device-associated infections. These include complications associated with additional devices, such as peripheral venous and arterial catheters, non-device-associated infections such as nonventilator hospital-acquired pneumonia, and noninfectious device complications such as trauma, thrombosis, and acute lung injury. As authors of the device-associated infection sections in the SHEA/IDSA/APIC Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals, we highlight catheter-associated urinary tract infection as an example of the strengths and limitations of the current emphasis on device-associated infection surveillance, suggest performance metrics that present a more comprehensive picture of patient harm, and provide a high-level overview of similar issues with other infection surveillance measures.

Social Acceptability of Health Behavior Posts on Social Media: An Experiment

IntroductionSocial media sites like Twitter (now X) are increasingly used to create health behavior metrics for public health surveillance. Yet little is known about social norms that may bias the content of posts about health behaviors. Social norms for posts about four health behaviors (smoking tobacco, drinking alcohol, physical activity, eating food) on Twitter/X were evaluated. MethodsThis was a randomized experiment delivered via web-based survey to adult, English-speaking Twitter/X users in three Michigan, USA, counties from 2020-2022 (n=560). Each participant viewed 24 posts presenting experimental manipulations regarding four health behaviors and answered questions about each post's social acceptability. Principal component analysis was used to combine survey responses into one perceived social acceptability measure. Linear mixed models with the Benjamini-Hochberg correction were implemented to test seven study hypotheses in 2023. ResultsSupporting six hypotheses, posts presenting healthier (CI:0.028,0.454), less stigmatized behaviors (CI 0.552,0.157) were more socially acceptable than posts regarding unhealthier, stigmatized behaviors. Unhealthy (CI:-0.268,-0.109) and stigmatized behavior (CI:-0.261,-0.103) posts were less acceptable for more educated participants. Posts about collocated activities (CI:0.410,0.573) and accompanied by expressions of liking (CI:0.906,1.11) were more acceptable than activities undertaken alone or disliked. Contrary to one hypothesis, posts reporting unusual activities were less acceptable than usual ones (CI:-0.472,0.312). ConclusionsPerceived social acceptability may be associated with the frequency and content of health behavior posts. Users of Twitter/X and other social media platform posts to estimate health behavior prevalence should account for potential estimation biases from perceived social acceptability of posts.

Bioinformatic investigation of discordant sequence data for SARS-CoV-2: insights for robust genomic analysis during pandemic surveillance.

The COVID-19 pandemic has necessitated the rapid development and implementation of whole-genome sequencing (WGS) and bioinformatic methods for managing the pandemic. However, variability in methods and capabilities between laboratories has posed challenges in ensuring data accuracy. A national working group comprising 18 laboratory scientists and bioinformaticians from Australia and New Zealand was formed to improve data concordance across public health laboratories (PHLs). One effort, presented in this study, sought to understand the impact of the methodology on consensus genome concordance and interpretation. SARS-CoV-2 WGS proficiency testing programme (PTP) data were retrospectively obtained from the 2021 Royal College of Pathologists of Australasia Quality Assurance Programmes (RCPAQAP), which included 11 participating Australian laboratories. The submitted consensus genomes and reads from eight contrived specimens were investigated, focusing on discordant sequence data and findings were presented to the working group to inform best practices. Despite using a variety of laboratory and bioinformatic methods for SARS-CoV-2 WGS, participants largely produced concordant genomes. Two participants returned five discordant sites in a high-Cτ replicate, which could be resolved with reasonable bioinformatic quality thresholds. We noted ten discrepancies in genome assessment that arose from nucleotide heterogeneity at three different sites in three cell-culture-derived control specimens. While these sites were ultimately accurate after considering the participants' bioinformatic parameters, it presented an interesting challenge for developing standards to account for intrahost single nucleotide variation (iSNV). Observed differences had little to no impact on key surveillance metrics, lineage assignment and phylogenetic clustering, while genome coverage <90 % affected both. We recommend PHLs bioinformatically generate two consensus genomes with and without ambiguity thresholds for quality control and downstream analysis, respectively, and adhere to a minimum 90 % genome coverage threshold for inclusion in surveillance interpretations. We also suggest additional PTP assessment criteria, including primer efficiency, detection of iSNVs and minimum genome coverage of 90 %. This study underscores the importance of multidisciplinary national working groups in informing guidelines in real time for bioinformatic quality acceptance criteria. It demonstrates the potential for enhancing public health responses through improved data concordance and quality control in SARS-CoV-2 genomic analysis during pandemic surveillance.

Home testing for SARS-CoV-2 and impact on surveillance in New York State

PurposeTo determine the distribution of diagnosed SARS-CoV-2 infections by testing modality (at-home rapid antigen [home tests] versus laboratory-based tests in clinical settings [clinical tests]), assess factors associated with clinical testing, and estimate the true total number of diagnosed infections in New York State (NYS). MethodsWe conducted an online survey among NYS residents and analyzed data from 1012 adults and 246 children with diagnosed infection July 13-December 7, 2022. Weighted descriptive and logistic regression model analyses were conducted. Weighted percentages and prevalence ratios by testing modality were generated. The percent of infections diagnosed by clinical tests via survey data were synthesized with daily lab-reported results to estimate the total number of diagnosed SARS-CoV-2 infections in NYS July 1-December 31, 2022. ResultsOver 70% of SARS-CoV-2 infections in NYS during the study period were diagnosed exclusively with home tests. Diagnosis with a clinical test was associated with age, race/ethnicity, and region among adults, and sex, age, and education among children. We estimate 4.1 million NYS residents had diagnosed SARS-CoV-2 infection July 1-December 31, 2022, compared to 1.1 million infections reported over the same period. ConclusionsMost SARS-CoV-2 infections in NYS were diagnosed exclusively with home tests. Surveillance metrics using laboratory-based reporting data underestimate diagnosed infections.

Canadian Surveillance Metrics and History of the COVID-19 Pandemic: Update of Epidemiological Assessment.

This study provides an update to the status of the COVID-19 pandemic in Canada building upon our initial analysis conducted in 2020 by incorporating an additional two years of data. First, we aim to summarize the status of the pandemic in Canada when the World Health Organization (WHO) declared the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in Canada and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in Canada. This longitudinal study analyzed trends in traditional surveillance data and dynamic panel estimates for COVID-19 transmissions and deaths in Canada from June 2020 to May 2023. We also used sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. For these sequences, we used Nextclade nomenclature to collect clade designations and Pangolin nomenclature for lineage designations of SARS-CoV-2. We used t-tests of dynamic panel regression coefficients to measure the persistence of COVID-19 transmissions around the WHO declaration. Finally, we conducted a one-sided t-test for whether provincial and territorial weekly speed was greater than an outbreak threshold of ten. We ran the test iteratively with six months of data across the sample period. Canada's speed remained below the outbreak threshold for eight months by the time of the WHO declaration ending the COVID-19 emergency of international concern. Acceleration and jerk were also low and stable. While the 1-day persistence coefficient remained statistically significant and positive (1.074, P-value <.001), the 7-day coefficient was negative and small in magnitude (-0.080, P-value .02). Furthermore, shift parameters for either of the two most recent weeks around May 5, 2023, were negligible (0.003 and 0.018, respectively, with P-values of .75 and .31), meaning the clustering effect of new COVID-19 cases had remained stable in the two weeks around the WHO declaration. From December of 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to ten became entirely insignificant from mid-October 2022 onward. While COVID-19 continues to circulate in Canada, the rate of transmission remained well below the threshold of an outbreak for eight months ahead of the WHO declaration. Both standard and enhanced surveillance metrics confirm that the pandemic had largely ended in Canada by the time of the WHO declaration. These results can inform future public health interventions and strategies in Canada, as well as contribute to the global understanding of the trajectory of the COVID-19 pandemic.

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Europe: Longitudinal Trend Analysis.

In this study, we built upon our initial research published in 2020 by incorporating an additional 2 years of data for Europe. We assessed whether COVID-19 had shifted from the pandemic to endemic phase in the region when the World Health Organization (WHO) declared the end of the public health emergency of international concern on May 5, 2023. We first aimed to measure whether there was an expansion or contraction in the pandemic in Europe at the time of the WHO declaration. Second, we used dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we provided the historical context for the course of the pandemic in Europe in terms of policy and disease burden at the country and region levels. In addition to the updates of traditional surveillance data and dynamic panel estimates from the original study, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-tailed t test for whether regional weekly speed was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the sample period. Speed for the region had remained below the outbreak threshold for 4 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. While the 1-day and 7-day persistence coefficients remained statistically significant, the coefficients were moderate in magnitude (0.404 and 0.547, respectively; P<.001 for both). The shift parameters for the 2 weeks around the WHO declaration were small and insignificant, suggesting little change in the clustering effect of cases on future cases at the time. From December 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of speed equal to 10 became insignificant for the first time in April 2023. While COVID-19 continues to circulate in Europe, the rate of transmission remained below the threshold of an outbreak for 4 months ahead of the WHO declaration. The region had previously been in a nearly continuous state of outbreak. The more recent trend suggested that COVID-19 was endemic in the region and no longer reached the threshold of the pandemic definition. However, several countries remained in a state of outbreak, and the conclusion that COVID-19 was no longer a pandemic in Europe at the time is unclear.

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Sub-Saharan Africa: Longitudinal Trend Analysis.

This study updates the initial COVID-19 pandemic surveillance in sub-Saharan Africa (SSA) from 2020 by providing 2 additional years of data for the region. First, we aimed to measure whether there was an expansion or contraction in the pandemic in SSA when the World Health Organization (WHO) declared an end to the public health emergency for the COVID-19 pandemic on May 5, 2023. Second, we used dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aimed to provide historical context for the course of the pandemic in SSA. In addition to updates of traditional surveillance data and dynamic panel estimates from the original study by Post et al (2021), this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and used Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t-test to assess whether regional weekly speed was greater than an outbreak threshold of 10. We ran the test iteratively with a rolling 6-month window of data across the sample period. Speed for the region remained well below the outbreak threshold before and after the WHO declaration. Acceleration and jerk were also low and stable. The 7-day persistence coefficient remained somewhat large (1.11) and statistically significant. However, both shift parameters for the weeks around the WHO declaration were negative, meaning the clustering effect of new COVID-19 cases had become recently smaller. From November 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to 10 was insignificant for the entire sample period. While COVID-19 continues to circulate in SSA, the region never reached outbreak status, and the weekly transmission rate remained below 1 case per 100,000 population for well over 1 year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold for its classification as a pandemic. Both standard and enhanced surveillance metrics confirm that the pandemic ended in SSA by the time the WHO made its declaration.

South Asia's COVID-19 History and Surveillance: Updated Epidemiological Assessment.

This study updates our findings from the COVID-19 pandemic surveillance we first conducted in South Asia in 2020 with 2 additional years of data for the region. We assess whether COVID-19 had transitioned from pandemic to endemic at the point the World Health Organization (WHO) ended the public health emergency status for COVID-19 on May 5, 2023. First, we aim to measure whether there was an expansion or contraction in the pandemic in South Asia around the WHO declaration. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in South Asia. In addition to updating the traditional surveillance data and dynamic panel estimates from our original study, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t test to determine whether regional weekly speed or transmission rate per 100,000 population was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the sample period. Speed for the region had remained below the outbreak threshold for over a year by the time of the WHO declaration. Acceleration and jerk were also low and stable. While the 1-day persistence coefficients remained statistically significant and positive (1.168), the 7-day persistence coefficient was negative (-0.185), suggesting limited cluster effects in which cases on a given day predict cases 7 days forward. Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any overall change in the persistence measure around the time of the WHO declaration. From December of 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of speed equal to 10 was statistically insignificant across the entire pandemic. While COVID-19 continued to circulate in South Asia, the rate of transmission had remained below the outbreak threshold for well over a year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had ended by the time of the WHO declaration. Prevention policies should be a focus ahead of future pandemics. On that point, policy should emphasize an epidemiological task force with widespread testing and a contact-tracing system.

The status of person-centered contraceptive care in the United States: Results from a nationally representative sample.

The Person-Centered Contraceptive Care measure (PCCC) evaluates patient experience of contraceptive counseling, a construct not represented within United States surveillance metrics of contraceptive care. We explore use of PCCC in a national probability sample and examine predictors of person-centered contraceptive care. Among 2228 women from the 2017-2019 National Survey of Family Growth who reported receiving contraceptive care in the last year, we conducted univariate and multivariable linear regression to identify associations between individual characteristics and PCCC scores. PCCC scores were high ( : 17.84, CI: 17.59-18.08 on a 4-20 scale), yet varied across characteristics. In adjusted analyses, Hispanic identity with Spanish language primacy and non-Hispanic other or multiple racial identities were significantly associated with lower average PCCC scores compared to those of non-Hispanic white identity (B = -1.232 [-1.970, -0.493]; B = -0.792 [-1.411, -0.173]). Gay, lesbian, or bisexual identity was associated with lower average PCCC scores compared to heterosexual (B = -0.673 [-1.243, -0.103]). PCCC scores had a positive association with incomes of 150%-299% and ≥300% of the federal poverty level compared to those of income <150% (150%-299%: B = 0.669 [0.198, 1.141]; ≥300%: B = 0.892 [0.412, 1.372]). Cannabis use in the past year was associated with lower PCCC scores (B = -0.542 [-0.971, -0.113]). The PCCC can capture differential experiences of contraceptive care to monitor patient experience and to motivate and track care quality over time. Differences in reported quality of care have implications for informing national priorities for contraceptive care improvements.

Barriers and facilitators to implementation of musculoskeletal injury mitigation programmes for military service members around the world: a scoping review

IntroductionMusculoskeletal injury (MSK-I) mitigation and prevention programmes (MSK-IMPPs) have been developed and implemented across militaries worldwide. Although programme efficacy is often reported, development and implementation details are often overlooked, limiting...

Comparison of acarological risk metrics derived from active and passive surveillance and their concordance with tick-borne disease incidence

Tick-borne diseases continue to threaten human health across the United States. Both active and passive tick surveillance can complement human case surveillance, providing spatio-temporal information on when and where humans are at risk for encounters with ticks and tick-borne pathogens. However, little work has been done to assess the concordance of the acarological risk metrics from each surveillance method. We used data on Ixodes scapularis and its associated human pathogens from Connecticut (2019–2021) collected through active collections (drag sampling) or passive submissions from the public to compare county estimates of tick and pathogen presence, infection prevalence, and tick abundance by life stage. Between the surveillance strategies, we found complete agreement in estimates of tick and pathogen presence, high concordance in infection prevalence estimates for Anaplasma phagocytophilum, Borrelia burgdorferi sensu stricto, and Babesia microti, but no consistent relationships between actively and passively derived estimates of tick abundance or abundance of infected ticks by life stage. We also compared nymphal metrics (i.e., pathogen prevalence in nymphs, nymphal abundance, and abundance of infected nymphs) with reported incidence of Lyme disease, anaplasmosis, and babesiosis, but did not find any consistent relationships with any of these metrics. The small spatial and temporal scale for which we had consistently collected active and passive data limited our ability to find significant relationships. Findings are likely to differ if examined across a broader spatial or temporal coverage with greater variation in acarological and epidemiological outcomes. Our results indicate similar outcomes between some actively and passively derived tick surveillance metrics (tick and pathogen presence, pathogen prevalence), but comparisons were variable for abundance estimates.

Online Help-Seeking Among Youth Victims of Sexual Violence Before and During COVID-19 (2016-2021): Analysis of Hotline Use Trends.

Three years since the onset of COVID-19, pandemic-related trends in child sexual abuse (CSA) remain poorly understood. Common administrative surveillance metrics may have underestimated abuse during the pandemic, given youths' limited access to mandatory reporters. Research using anonymous service-use data showed increased violence-related online help-seeking but overlooked youth-specific help-seeking for CSA during COVID-19. Understanding pandemic-related trends in CSA can inform abuse detection practices and mental health service provision for youth victims. The purpose of this study was to harness anonymous help-seeking data from the National Sexual Assault Online Hotline (NSAOH) to glean insights about CSA occurrence in the United States during the COVID-19 pandemic. We used an archival sample of victims who contacted NSAOH from 2016 to 2021 (n=41,561). We examined differences in the proportion of youth and adult victims contacting NSAOH during the first COVID-19 year (March 2020 to February 2021) compared to the prior year (March 2019 to February 2020; n=11,719). Further, we compared key characteristics of hotline interactions among youth victims during the first COVID-19 year to the prior year (n=5913). Using joinpoint regression analysis, we examined linear trends in the number of monthly sampled youth and adult victims (excluding victims of unknown age) from 2016 to 2021 who discussed any victimization event (n=26,904) and who discussed recent events (ie, events occurring during the pandemic; n=9932). Most youth victims were abused by family members prior to (1013/1677, 60.4%) and after (2658/3661, 72.6%) the onset of COVID-19. The number of youth victims contacting NSAOH spiked in March 2020 and peaked in November 2020 for all youth (slope=28.2, 95% CI 18.7-37.7) and those discussing recent events (slope=17.4, 95% CI 11.1-23.6). We observed a decline in youth victims into spring 2021 for all youth (slope=-56.9, 95% CI -91.4 to -22.3) and those discussing recent events (slope=-33.7, 95% 47.3 to -20.0). The number of adult victims discussing any victimization event increased steadily from January 2018 through May 2021 (slope=3.6; 95% CI 2.9-4.2) and then declined (slope=-13.8, 95% CI -22.8 to -4.7). Trends were stable for adults discussing recent events. This study extends the use of hotline data to understand the implications of the pandemic on CSA. We observed increased youth help-seeking through the NSAOH coinciding with the onset of COVID-19. Trends persisted when limiting analyses to recent victimization events, suggesting increased help-seeking reflected increased CSA during COVID-19. These findings underscore the utility of anonymous online services for youth currently experiencing abuse. Further, the findings support calls for increased youth mental health services and efforts to incorporate online chat into youth-targeted services.

Evaluation of Bayesian spatiotemporal infectious disease models for prospective surveillance analysis

BackgroundCOVID-19 brought enormous challenges to public health surveillance and underscored the importance of developing and maintaining robust systems for accurate surveillance. As public health data collection efforts expand, there is a critical need for infectious disease modeling researchers to continue to develop prospective surveillance metrics and statistical models to accommodate the modeling of large disease counts and variability. This paper evaluated different likelihoods for the disease count model and various spatiotemporal mean models for prospective surveillance.MethodsWe evaluated Bayesian spatiotemporal models, which are the foundation for model-based infectious disease surveillance metrics. Bayesian spatiotemporal mean models based on the Poisson and the negative binomial likelihoods were evaluated with the different lengths of past data usage. We compared their goodness of fit and short-term prediction performance with both simulated epidemic data and real data from the COVID-19 pandemic.ResultsThe simulation results show that the negative binomial likelihood-based models show better goodness of fit results than Poisson likelihood-based models as deemed by smaller deviance information criteria (DIC) values. However, Poisson models yield smaller mean square error (MSE) and mean absolute one-step prediction error (MAOSPE) results when we use a shorter length of the past data such as 7 and 3 time periods. Real COVID-19 data analysis of New Jersey and South Carolina shows similar results for the goodness of fit and short-term prediction results. Negative binomial-based mean models showed better performance when we used the past data of 52 time periods. Poisson-based mean models showed comparable goodness of fit performance and smaller MSE and MAOSPE results when we used the past data of 7 and 3 time periods.ConclusionWe evaluate these models and provide future infectious disease outbreak modeling guidelines for Bayesian spatiotemporal analysis. Our choice of the likelihood and spatiotemporal mean models was influenced by both historical data length and variability. With a longer length of past data usage and more over-dispersed data, the negative binomial likelihood shows a better model fit than the Poisson likelihood. However, as we use a shorter length of the past data for our surveillance analysis, the difference between the Poisson and the negative binomial models becomes smaller. In this case, the Poisson likelihood shows robust posterior mean estimate and short-term prediction results.

Assessing trends in breast care surveillance metrics after implementing surgeon-specific tracking and performance reporting in a large, integrated cancer network.

There are few quality metrics and benchmarks specific to surgical oncology. Development of a surgeon-level performance metrics system based on peer comparisons is hypothesized to positively influence surgical decision-making. This study established a tracking and reporting system comprised of evidence and consensus-based metrics to assess breast care delivered by individual surgeons. Surgeons' performance is assessed by a surveillance tracking system of metrics pertaining to referrals and surgical elements. This retrospective analysis of prospectively collected breast care data reports on recurring 6-month and cumulative data from nine care locations from 2015 to 2021. Breast care was provided to 6659 patients by 41 surgeons. A total of 27 breast care metrics were evaluated over 7 years. Metrics with consistent, proficient results were retired after 18 months, including the rate of core biopsy, specimen orientation, and referrals to medical oncology, genetics, and fertility, among others. In clinically node-negative, hormone receptor-positive patients 70 years of age or older, the cumulative rate of sentinel lymph node (SLN) biopsy significantly decreased by 40% over 5.5 years (p<.001). The overall breast conservation rate for T0-T2 cancer increased 10% over 7 years. At the surgeon level, improvements were made in the median number of SLNs removed and in operative note documentation. Implementation of a surgeon-specific, peer comparison-based metric and tracking system has yielded substantive changes in breast care management. This process and governance structure can serve as a model for quantification of breast care at other institutions and for other disease sites.