Last data update: Apr 22, 2024. (Total: 46599 publications since 2009)
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Query Trace: Ray C [original query] |
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An urgent call to address work-related psychosocial hazards and improve worker well-being
Schulte PA , Sauter SL , Pandalai SP , Tiesman HM , Chosewood LC , Cunningham TR , Wurzelbacher SJ , Pana-Cryan R , Swanson NG , Chang CC , Nigam JAS , Reissman DB , Ray TK , Howard J . Am J Ind Med 2024 Work-related psychosocial hazards are on the verge of surpassing many other occupational hazards in their contribution to ill-health, injury, disability, direct and indirect costs, and impact on business and national productivity. The risks associated with exposure to psychosocial hazards at work are compounded by the increasing background prevalence of mental health disorders in the working-age population. The extensive and cumulative impacts of these exposures represent an alarming public health problem that merits immediate, increased attention. In this paper, we review the linkage between work-related psychosocial hazards and adverse effects, their economic burden, and interventions to prevent and control these hazards. We identify six crucial societal actions: (1) increase awareness of this critical issue through a comprehensive public campaign; (2) increase etiologic, intervention, and implementation research; (3) initiate or augment surveillance efforts; (4) increase translation of research findings into guidance for employers and workers; (5) increase the number and diversity of professionals skilled in preventing and addressing psychosocial hazards; and (6) develop a national regulatory or consensus standard to prevent and control work-related psychosocial hazards. |
Risk of COVID-19 hospitalization and protection associated with mRNA vaccination among US adults with psychiatric disorders
Levy ME , Yang DH , Dunne MM , Miley K , Irving SA , Grannis SJ , Weber ZA , Griggs EP , Spark TL , Bassett E , Embi PJ , Gaglani M , Natarajan K , Valvi NR , Ong TC , Naleway AL , Stenehjem E , Klein NP , Link-Gelles R , DeSilva MB , Kharbanda AB , Raiyani C , Beaton MA , Dixon BE , Rao S , Dascomb K , Patel P , Mamawala M , Han J , Fadel WF , Barron MA , Grisel N , Dickerson M , Liao IC , Arndorfer J , Najdowski M , Murthy K , Ray C , Tenforde MW , Ball SW . Influenza Other Respir Viruses 2024 18 (3) e13269 BACKGROUND: Although psychiatric disorders have been associated with reduced immune responses to other vaccines, it remains unknown whether they influence COVID-19 vaccine effectiveness (VE). This study evaluated risk of COVID-19 hospitalization and estimated mRNA VE stratified by psychiatric disorder status. METHODS: In a retrospective cohort analysis of the VISION Network in four US states, the rate of laboratory-confirmed COVID-19-associated hospitalization between December 2021 and August 2022 was compared across psychiatric diagnoses and by monovalent mRNA COVID-19 vaccination status using Cox proportional hazards regression. RESULTS: Among 2,436,999 adults, 22.1% had ≥1 psychiatric disorder. The incidence of COVID-19-associated hospitalization was higher among patients with any versus no psychiatric disorder (394 vs. 156 per 100,000 person-years, p < 0.001). Any psychiatric disorder (adjusted hazard ratio [aHR], 1.27; 95% CI, 1.18-1.37) and mood (aHR, 1.25; 95% CI, 1.15-1.36), anxiety (aHR, 1.33, 95% CI, 1.22-1.45), and psychotic (aHR, 1.41; 95% CI, 1.14-1.74) disorders were each significant independent predictors of hospitalization. Among patients with any psychiatric disorder, aHRs for the association between vaccination and hospitalization were 0.35 (95% CI, 0.25-0.49) after a recent second dose, 0.08 (95% CI, 0.06-0.11) after a recent third dose, and 0.33 (95% CI, 0.17-0.66) after a recent fourth dose, compared to unvaccinated patients. Corresponding VE estimates were 65%, 92%, and 67%, respectively, and were similar among patients with no psychiatric disorder (68%, 92%, and 79%). CONCLUSION: Psychiatric disorders were associated with increased risk of COVID-19-associated hospitalization. However, mRNA vaccination provided similar protection regardless of psychiatric disorder status, highlighting its benefit for individuals with psychiatric disorders. |
High school follow-up of the Dating Matters® RCT: Effects on teen dating violence and relationship behaviors
Niolon PH , Estefan LF , DeGue S , Le VD , Tracy AJ , Ray C , Bontempo D , Little TD , Vivolo-Kantor AM , Latzman N , Taylor B , Tharp A . Prev Sci 2024 Teen dating violence (TDV) is a significant public health problem that can have lifelong consequences. Using a longitudinal, cluster randomized controlled trial (RCT), this study examines whether the Dating Matters comprehensive prevention model, implemented in middle school, prevented TDV and negative relationship behaviors and promoted positive relationship behaviors in high school (9th-11th grades), when compared with a standard of care intervention. Dating Matters includes programs for sixth to eighth grade youth and their parents, training for school staff, a youth communications program, and policy and data activities implemented in the community. Self-report survey data were collected from students in 46 middle schools that were randomly assigned to condition within site. Students completed two surveys (fall and spring) in each middle school grade and a single survey in the spring of each high school grade. This study examined self-reported TDV perpetration and victimization, use of negative conflict resolution strategies, and positive relationship skills in the high school follow-up. While varying patterns emerged, latent panel models demonstrated significant program effects for all outcomes. Dating Matters students reported 19% reduced risk for TDV perpetration, 24% reduced risk for TDV victimization, 7% reduced risk for use of negative conflict strategies, and 3% more use of positive relationship skills, on average across time and cohort, than standard of care students. On average, Dating Matters, implemented in middle school, continued to be more effective at reducing TDV perpetration, TDV victimization, and use of negative conflict resolution strategies in high school than an evidence-based comparison program.Trial Registration: clinicaltrials.gov Identifier: NCT01672541. |
PTSD symptoms among college students: Linkages with familial risk, borderline personality, and sexual assault
Tyler KA , Ray CM . J Child Sex Abus 2024 1-19 College students have high rates of post-traumatic stress disorder (PTSD) symptoms as well as high rates of sexual assault. What is less clear, however, is whether different sexual assault types (e.g. coercive, physically forced, and incapacitation) are associated with greater PTSD symptoms. Moreover, understanding early familial and mental health histories of college students is important for explaining PTSD symptoms. As such, we use a social stress framework to examine the relationships between early familial risk (i.e. child abuse, perceived maternal rejection), borderline personality (BP) symptoms, and three sexual assault types with PTSD symptoms among college students. A total of 783 undergraduate students (65.4% female) completed paper and pencil surveys in fall 2019 and spring 2020 at a large public university. Results revealed that females were more likely to experience child sexual abuse and all three forms of sexual assault, while males experienced higher rates of child physical abuse. OLS regression results showed positive associations between child sexual abuse, perceived maternal rejection, BP symptoms and all three types of sexual assault with PTSD symptoms. Females also experienced more PTSD symptoms compared to males. Findings have implications for targeted interventions to improve mental health outcomes. |
Genetics and genomics for the prevention and treatment of cardiovascular disease: update: a scientific statement from the American Heart Association.
Ganesh SK , Arnett DK , Assimes TL , Basson CT , Chakravarti A , Ellinor PT , Engler MB , Goldmuntz E , Herrington DM , Hershberger RE , Hong Y , Johnson JA , Kittner SJ , McDermott DA , Meschia JF , Mestroni L , O'Donnell CJ , Psaty BM , Vasan RS , Ruel M , Shen WK , Terzic A , Waldman SA . Circulation 2013 128 (25) 2813-51 Cardiovascular diseases (CVDs) are a major source of morbidity and mortality worldwide. Despite a decline of ≈30% over the past decade, heart disease remains the leading killer of Americans.1 For rare and familial forms of CVD, we are increasingly recognizing single-gene mutations that impart relatively large effects on individual phenotype. Examples include inherited forms of cardiomyopathy, arrhythmias, and aortic diseases. However, the prevalence of monogenic disorders typically accounts for a small proportion of the total CVD observed in the population. CVDs in the general population are complex diseases, with several contributing genetic and environmental factors. Although recent progress in monogenic disorders has occurred, we have seen a period of intense investigation to identify the genetic architecture of more common forms of CVD and related traits. | | Genomics serves several roles in cardiovascular health and disease, including disease prediction, discovery of genetic loci influencing CVD, functional evaluation of these genetic loci to understand mechanisms, and identification of therapeutic targets. For single-gene CVDs, progress has led to several clinically useful diagnostic tests, extending our ability to inform the management of afflicted patients and their family members. However, there has been little progress in developing genetic testing for complex CVD because individual common variants have only a modest impact on risk. The study of the genomics of complex CVDs is further challenged by the influence of environmental variables, phenotypic heterogeneity, and pathogenic complexity. Characterization of the clinical phenotype requires consideration of the clinical details of the diseases and traits under study. |
Lactic acid salts of nicotine potentiate the transfer of toxic metals into electronic cigarette aerosols
Pappas RS , Gray N , Halstead M , Watson CH . Toxics 2024 12 (1) The designs and liquid formulations of Electronic Nicotine Delivery System (ENDS) devices continue to rapidly evolve. Thus, it is important to monitor and characterize ENDS aerosols for changes in toxic constituents. Many ENDS liquid formulations now include the addition of organic acids in a 1 to 1 molar ratio with nicotine. Metal concentrations in aerosols produced by ENDS devices with different nicotine salt formulations were analyzed. Aerosols from devices containing lactic acid had higher nickel, zinc, copper, and chromium concentrations than aerosols produced by devices containing benzoic acid or levulinic acid. Our scanning electron microscope with energy dispersive X-ray analytical findings showed that the metals determined in the inductively coupled plasma-mass spectrometry analytical results were consistent with the metal compositions of the ENDS device components that were exposed to the liquids and that nickel is a major constituent in many ENDS internal components. As a result of the exposure of the nickel-containing components to the ENDS liquids, resulting aerosol nickel concentrations per puff were higher from devices that contained lactic acid in comparison to devices with benzoic or levulinic acid. The aerosol nickel concentrations in 10 puffs from ENDS-containing lactic acid were, in some cases, hundreds of times higher than cigarette mainstream smoke nickel deliveries. Thus, the design of an ENDS device in terms of both physical construction components and the liquid chemical formulations could directly impact potential exposures to toxic constituents such as metals. |
Respirable coal mine dust in the vicinity of a roof bolter: an inter-laboratory study to compare wet versus dry dust collection systems
Animah F , Greth A , Afrouz S , Keles C , Akinseye T , Pan L , Reed WR , Sarver E . Min Metall Explor null [Epub ahead of print] Among underground coal miners, roof bolter operators are generally considered to have some of the highest risks for hazardous respirable dust exposure. This is because bolting requires drilling into roof strata that can often be a source of silica and silicate dust, which are associated with occupational lung diseases. However, little is known about the variability of dust characteristics (e.g., mineralogy constituents, particle size) in the vicinity of the bolter-or when specific dust controls are applied. As part of a prior NIOSH study, respirable dust samples were collected during several different events in standardized locations around an active roof bolter, and personal samples were also collected from the operator during the cleanout of the bolter's dust collection system when it was equipped with a novel wet dust box versus a traditional dry box. Those samples were made available for follow-up analysis by scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), as well as direct-on-filter Fourier transform infrared spectroscopy (FTIR). Results showed variability in dust constituents and particle sizes at locations around the roof bolter, and indicated some event-to-event differences in dust sources. Additionally, compared to the dry dust box, the wet dust box appeared to reduce (by 41-82%) the relative silica and silicate content in the respirable dust to which the operator was exposed during cleanout. Furthermore, an inter-laboratory comparison demonstrated the reproducibility of a standardized direct-on-filter FTIR method for estimating quartz mass (i.e., the predominant form of crystalline silica) in respirable coal mine dust samples. However, for constituent analysis by SEM-EDX, differences observed between results from two independent labs indicate that standardization of the analytical protocol is necessary to enable comparability of results. |
Value of rigorous review and evaluation to support implementation of effective sexual violence prevention programming
Coker Ann L , Ray Colleen M . J Adolesc Health 2024 74 (1) 210-210 The goal of identifying evidence-based programming that reduces sexual violence (SV) on college campuses and elsewhere is crucial given SV's high lifetime frequency, the range of mental and physical health consequences linked to SV, and its economic costs [1]. To reduce SV on college campuses, the US Campus Sexual Assault Violence Elimination (SaVE) Act of 2013 (www.campussaveact.org) mandated institutions of higher learning to provide primary prevention and awareness programming to reduce SV. Sexual Assault Violence Elimination (SaVE) now acts as an impetus for novel SV prevention programming development and evaluation. Yet when SaVE was enacted, few SV prevention programs had been rigorously evaluated for their efficacy to prevent or reduce SV, including in which settings and with which students. Systematic reviews are strategic approaches to establish the effectiveness of SV programming to prevent SV or mitigate the, often life-long, trauma associated with SV [2,3] and are used to inform resources that can be used by communities for action. The Centers for Disease Control and Prevention's STOP SV resource for action [4] provides a summary of the best available evidence needed to establish an evidence base for selecting SV prevention programming. While important, the STOP SV resource for action was published in 2016, and an update is needed to reflect the recent evaluations as well an expanded range of settings and persons that could benefit from SV prevention intervention programming. |
Influenza vaccine effectiveness against influenza-A-associated emergency department, urgent care, and hospitalization encounters among U.S. adults, 2022-2023
Tenforde MW , Weber ZA , Yang DH , DeSilva MB , Dascomb K , Irving SA , Naleway AL , Gaglani M , Fireman B , Lewis N , Zerbo O , Goddard K , Timbol J , Hansen JR , Grisel N , Arndorfer J , McEvoy CE , Essien IJ , Rao S , Grannis SJ , Kharbanda AB , Natarajan K , Ong TC , Embi PJ , Ball SW , Dunne MM , Kirshner L , Wiegand RE , Dickerson M , Patel P , Ray C , Flannery B , Garg S , Adams K , Klein NP . J Infect Dis 2023 BACKGROUND: The 2022-2023 United States influenza season had unusually early influenza activity with high hospitalization rates. Vaccine-matched A(H3N2) viruses predominated, with lower levels of A(H1N1)pdm09 activity also observed. METHODS: Using the test-negative design, we evaluated influenza vaccine effectiveness (VE) during the 2022-2023 season against influenza-A-associated emergency department/urgent care (ED/UC) visits and hospitalizations from October 2022-March 2023 among adults (age ≥18 years) with acute respiratory illness (ARI). VE was estimated by comparing odds of seasonal influenza vaccination among case-patients (influenza A test-positive by molecular assay) and controls (influenza test-negative), applying inverse-propensity-to-be-vaccinated weights. RESULTS: The analysis included 85,389 ED/UC ARI encounters (17.0% influenza-A-positive; 37.8% vaccinated overall) and 19,751 hospitalizations (9.5% influenza-A-positive; 52.8% vaccinated overall). VE against influenza-A-associated ED/UC encounters was 44% (95% confidence interval [95%CI]: 40-47%) overall and 45% and 41% among adults aged 18-64 and ≥65 years, respectively. VE against influenza-A-associated hospitalizations was 35% (95%CI: 27-43%) overall and 23% and 41% among adults aged 18-64 and ≥65 years, respectively. CONCLUSIONS: VE was moderate during the 2022-2023 influenza season, a season characterized with increased burden of influenza and co-circulation with other respiratory viruses. Vaccination is likely to substantially reduce morbidity, mortality, and strain on healthcare resources. |
Effectiveness of the original monovalent coronavirus disease 2019 vaccines in preventing emergency department or urgent care encounters and hospitalizations among adults with disabilities: VISION Network, June 2021-September 2022
Patel P , Schrader KE , Rice CE , Rowley E , Cree RA , DeSilva MB , Embi PJ , Gaglani M , Grannis SJ , Ong TC , Stenehjem E , Naleway AL , Ball S , Natarajan K , Klein NP , Adams K , Kharbanda A , Ray C , Link-Gelles R , Tenforde MW . Open Forum Infect Dis 2023 10 (11) ofad474 Adults with disabilities are at increased risk for severe coronavirus disease 2019 (COVID-19). Using data across 9 states during Delta- and Omicron-predominant periods (June 2021-September 2022), we evaluated the effectiveness of the original monovalent COVID-19 messenger RNA vaccines among 521 206 emergency department/urgent care encounters (11 471 [2%] in patients with a documented disability) and 139 548 hospitalizations (16 569 [12%] in patients with a disability) for laboratory-confirmed COVID-19 illness in adults (aged ≥18 years). Across variant periods and for the primary series or booster doses, vaccine effectiveness was similar in those with and those without a disability. These findings highlight the importance of adults with disabilities staying up to date with COVID-19 vaccinations. |
Prevalence of violence victimization and perpetration during middle and high school in under-resourced, urban communities
DeGue S , Ray CM , Bontempo D , Niolon PH , Tracy AJ , Estefan LF , Le VD , Little TD . Violence Vict 2023 38 (6) 839-857 This study describes rates of violence victimization, perpetration, and witnessing in 6th-11th grade for a multisite sample (N = 3,466) of predominantly Black and Hispanic middle- and high-school students from urban areas with high rates of crime and economic disadvantage. Students completed surveys in middle and high school assessing teen dating violence, stalking, sexual violence and harassment, bullying, cyberbullying, and physical violence perpetration and victimization, as well as witnessing violence. The highest prevalence rates are observed most often in 8th or 9th grade. Youth reported high rates of witnessing serious assault and severe community violence throughout adolescence. These findings suggest that efforts to prevent violence among youth living in under-resourced communities need to start early and address community-level socioeconomic disparities. |
Time-specific impact of mono-benzyl phthalate (MBzP) and perfluorooctanoic acid (PFOA) on breast density of a Chilean adolescent cohort
Kim CE , Binder AM , Corvalan C , Pereira A , Shepherd J , Calafat AM , Botelho JC , Hampton JM , Trentham-Dietz A , Michels KB . Environ Int 2023 181 108241 INTRODUCTION: High mammographic density is among the strongest and most established predictors for breast cancer risk. Puberty, the period during which breasts undergo exponential mammary growth, is considered one of the critical stages of breast development for environmental exposures. Benzylbutyl phthalate (BBP) and perfluorooctanoic acid (PFOA) are pervasive endocrine disrupting chemicals that may increase hormone-sensitive cancers. Evaluating the potential impact of BBP and PFOA exposure on pubertal breast density is important to our understanding of early-life environmental influences on breast cancer etiology. OBJECTIVE: To prospectively assess the effect of biomarker concentrations of monobenzyl phthalate (MBzP) and PFOA at specific pubertal window of susceptibility (WOS) on adolescent breast density. METHOD: This study included 376 Chilean girls from the Growth and Obesity Cohort Study with data collection at four timepoints: Tanner breast stages 1 (B1) and 4 (B4), 1- year post- menarche (1YPM) and 2-years post-menarche (2YPM). Dual-energy X-ray absorptiometry was used to assess the absolute fibroglandular volume (FGV) and percent breast density (%FGV) at 2YPM. We used concentrations of PFOA in serum and MBzP in urine as an index of exposure to PFOA and BBP, respectively. Parametric G-formula was used to estimate the time-specific effects of MBzP and PFOA on breast density. The models included body fat percentage as a time-varying confounder and age, birthweight, age at menarche, and maternal education as fixed covariates. RESULTS: A doubling of serum PFOA concentration at B4 resulted in a non-significant increase in absolute FGV (β:11.25, 95% confidence interval (CI): -0.28, 23.49)), while a doubling of PFOA concentration at 1YPM resulted in a decrease in % FGV (β:-4.61, 95% CI: -7.45, -1.78). We observed no associations between urine MBzP and breast density measures. CONCLUSION: In this cohort of Latina girls, PFOA serum concentrations corresponded to a decrease in % FGV. No effect was observed between MBzP and breast density measures across pubertal WOS. |
Clinical outcomes of patients with nontyphoidal salmonella infections by isolate resistance- Foodborne Diseases Active Surveillance Network, 10 U.S. Sites, 2004-2018
Watkins LKF , Luna S , Bruce BB , Medalla F , Reynolds J , Ray LC , Wilson EL , Caidi H , Griffin PM . Clin Infect Dis 2023 BACKGROUND: Nontyphoidal Salmonella causes an estimated 1.35 million U.S. infections annually. Antimicrobial-resistant strains are a serious public health threat. We examined the association between resistance and the clinical outcomes of hospitalization, length-of-stay ≥3 days, and death. METHODS: We linked epidemiologic data from the Foodborne Diseases Active Surveillance Network with antimicrobial resistance data from the National Antimicrobial Resistance Monitoring System (NARMS) for nontyphoidal Salmonella infections from 2004-2018. We defined any resistance as resistance to ≥1 antimicrobial and clinical resistance as resistance to ampicillin, azithromycin, ceftriaxone, ciprofloxacin, or trimethoprim-sulfamethoxazole (for the subset of isolates tested for all five agents). We compared outcomes before and after adjusting for age, state, race/ethnicity, international travel, outbreak association, and isolate serotype and source. RESULTS: Twenty percent of isolates (1,105/5,549) had any resistance and 16% (469/2,969) had clinical resistance. Persons whose isolates had any resistance were more likely to be hospitalized (31% vs. 28%, P=0.01) or have length-of-stay ≥3 days (20% vs. 16%, P=0.01). Deaths were rare, but more common among those with any than no resistance (1.0% vs. 0.4%, P=0.01). Outcomes for patients whose isolates had clinical resistance did not differ significantly from those with no resistance. After adjustment, any resistance (adjusted odds ratio 1.23, 95% confidence interval 1.04-1.46) remained significantly associated with hospitalization. CONCLUSIONS: We observed a significant association between nontyphoidal Salmonella infections caused by resistant pathogens and likelihood of hospitalization. Clinical resistance was not associated with poorer outcomes, suggesting that factors other than treatment failure (e.g., strain virulence, strain source, host factors) may be important. |
Modelling counterfactual incidence during the transition towards culture-independent diagnostic testing
Healy JM , Ray L , Tack DM , Eikmeier D , Tobin-D'Angelo M , Wilson E , Hurd S , Lathrop S , McGuire SM , Bruce BB . Int J Epidemiol 2023 BACKGROUND: Culture-independent diagnostic testing (CIDT) provides rapid results to clinicians and is quickly displacing traditional detection methods. Increased CIDT use and sensitivity likely result in higher case detection but might also obscure infection trends. Severe illness outcomes, such as hospitalization and death, are likely less affected by changes in testing practices and can be used as indicators of the expected case incidence trend had testing methods not changed. METHODS: Using US Foodborne Diseases Active Surveillance Network data during 1996-2019 and mixed effects quasi-Poisson regression, we estimated the expected yearly incidence for nine enteric pathogens. RESULTS: Removing the effect of CIDT use, CIDT panel testing and culture-confirmation of CIDT testing, the modelled incidence in all but three pathogens (Salmonella, Shigella, STEC O157) was significantly lower than the observed and the upward trend in Campylobacter was reversed from an observed 2.8% yearly increase to a modelled -2.8% yearly decrease (95% credible interval: -4.0, -1.4). CONCLUSIONS: Severe outcomes may be useful indicators in evaluating trends in surveillance systems that have undergone a marked change. |
Barriers to COVID-19 prevention measures among people experiencing homelessness with substance use disorder or serious mental illness
Meehan AA , Jeffers A , Barker J , Ray CM , Laws RL , Fields VL , Miedema SS , Cha S , Cassell CH , DiPietro B , Cary M , Yang M , McLendon H , Marcus R , Mosites E . J Prev (2022) 2023 44 (6) 663-678 People experiencing homelessness (PEH) are at disproportionate risk of becoming infected and having severe illness from coronavirus disease 2019 (COVID-19), especially when residing in congregate settings like homeless shelters. Behavioral health problems related to substance use disorder (SUD) and severe mental illness (SMI) may have created additional challenges for PEH to practice prevention measures like mask wearing, physical distancing, handwashing, and quarantine and isolation. The study objective was to understand the perceived barriers PEH face regarding COVID-19 non-pharmaceutical prevention strategies and identify recommendations for overcoming barriers. From August-October 2020, qualitative phone interviews with 50 purposively selected behavioral health professionals across the United States serving PEH with SUD or SMI were conducted. Professionals described that PEH faced barriers to prevention that were structural (e.g., access to necessary resources), behavioral (related to SUD or SMI), or related to the priority of other needs. Recommendations to overcome these barriers included providing free prevention resources (e.g., masks and hand sanitizer), providing education about importance of prevention strategies, and prioritizing access to stable housing. Interviews took place before COVID-19 vaccines were available, so barriers to vaccination are not included in this paper. Findings can help support tailored approaches during COVID-19 and future public health threats. |
Global diversity and antimicrobial resistance of typhoid fever pathogens: Insights from a meta-analysis of 13,000 Salmonella Typhi genomes
Carey ME , Dyson ZA , Ingle DJ , Amir A , Aworh MK , Chattaway MA , Chew KL , Crump JA , Feasey NA , Howden BP , Keddy KH , Maes M , Parry CM , Van Puyvelde S , Webb HE , Afolayan AO , Alexander AP , Anandan S , Andrews JR , Ashton PM , Basnyat B , Bavdekar A , Bogoch II , Clemens JD , da Silva KE , De A , de Ligt J , Diaz Guevara PL , Dolecek C , Dutta S , Ehlers MM , Francois Watkins L , Garrett DO , Godbole G , Gordon MA , Greenhill AR , Griffin C , Gupta M , Hendriksen RS , Heyderman RS , Hooda Y , Hormazabal JC , Ikhimiukor OO , Iqbal J , Jacob JJ , Jenkins C , Jinka DR , John J , Kang G , Kanteh A , Kapil A , Karkey A , Kariuki S , Kingsley RA , Koshy RM , Lauer AC , Levine MM , Lingegowda RK , Luby SP , Mackenzie GA , Mashe T , Msefula C , Mutreja A , Nagaraj G , Nagaraj S , Nair S , Naseri TK , Nimarota-Brown S , Njamkepo E , Okeke IN , Perumal SPB , Pollard AJ , Pragasam AK , Qadri F , Qamar FN , Rahman SIA , Rambocus SD , Rasko DA , Ray P , Robins-Browne R , Rongsen-Chandola T , Rutanga JP , Saha SK , Saha S , Saigal K , Sajib MSI , Seidman JC , Shakya J , Shamanna V , Shastri J , Shrestha R , Sia S , Sikorski MJ , Singh A , Smith AM , Tagg KA , Tamrakar D , Tanmoy AM , Thomas M , Thomas MS , Thomsen R , Thomson NR , Tupua S , Vaidya K , Valcanis M , Veeraraghavan B , Weill FX , Wright J , Dougan G , Argimón S , Keane JA , Aanensen DM , Baker S , Holt KE . Elife 2023 12 BACKGROUND: The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). METHODS: This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. RESULTS: Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal 'sentinel' surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. CONCLUSIONS: The consortium's aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies. FUNDING: No specific funding was awarded for this meta-analysis. Coordinators were supported by fellowships from the European Union (ZAD received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 845681), the Wellcome Trust (SB, Wellcome Trust Senior Fellowship), and the National Health and Medical Research Council (DJI is supported by an NHMRC Investigator Grant [GNT1195210]). | Salmonella Typhi (Typhi) is a type of bacteria that causes typhoid fever. More than 110,000 people die from this disease each year, predominantly in areas of sub-Saharan Africa and South Asia with limited access to safe water and sanitation. Clinicians use antibiotics to treat typhoid fever, but scientists worry that the spread of antimicrobial-resistant Typhi could render the drugs ineffective, leading to increased typhoid fever mortality. The World Health Organization has prequalified two vaccines that are highly effective in preventing typhoid fever and may also help limit the emergence and spread of resistant Typhi. In low resource settings, public health officials must make difficult trade-off decisions about which new vaccines to introduce into already crowded immunization schedules. Understanding the local burden of antimicrobial-resistant Typhi and how it is spreading could help inform their actions. The Global Typhoid Genomics Consortium analyzed 13,000 Typhi genomes from 110 countries to provide a global overview of genetic diversity and antimicrobial-resistant patterns. The analysis showed great genetic diversity of the different strains between countries and regions. For example, the H58 Typhi variant, which is often drug-resistant, has spread rapidly through Asia and Eastern and Southern Africa, but is less common in other regions. However, distinct strains of other drug-resistant Typhi have emerged in other parts of the world. Resistance to the antibiotic ciprofloxacin was widespread and accounted for over 85% of cases in South Africa. Around 70% of Typhi from Pakistan were extensively drug-resistant in 2020, but these hard-to-treat variants have not yet become established elsewhere. Variants that are resistant to both ciprofloxacin and ceftriaxone have been identified, and azithromycin resistance has also appeared in several different variants across South Asia. The Consortium’s analyses provide valuable insights into the global distribution and transmission patterns of drug-resistant Typhi. Limited genetic data were available fromseveral regions, but data from travel-associated cases helped fill some regional gaps. These findings may help serve as a starting point for collective sharing and analyses of genetic data to inform local public health action. Funders need to provide ongoing supportto help fill global surveillance data gaps. | eng |
Epidemiology and antimicrobial resistance of Campylobacter infections in the United States, 2005-2018
Ford L , Healy JM , Cui Z , Ahart L , Medalla F , Ray LC , Reynolds J , Laughlin ME , Vugia DJ , Hanna S , Bennett C , Chen J , Rose EB , Bruce BB , Payne DC , Francois Watkins LK . Open Forum Infect Dis 2023 10 (8) ofad378 BACKGROUND: Campylobacter is the most common cause of bacterial diarrhea in the United States; resistance to macrolides and fluoroquinolones limits treatment options. We examined the epidemiology of US Campylobacter infections and changes in resistance over time. METHODS: The Foodborne Diseases Active Surveillance Network receives information on laboratory-confirmed Campylobacter cases from 10 US sites, and the National Antimicrobial Resistance Monitoring System receives a subset of isolates from these cases for antimicrobial susceptibility testing. We estimated trends in incidence of Campylobacter infection, adjusting for sex, age, and surveillance changes attributable to culture-independent diagnostic tests. We compared percentages of isolates resistant to erythromycin or ciprofloxacin during 2005-2016 with 2017-2018 and used multivariable logistic regression to examine the association of international travel with resistance. RESULTS: Adjusted Campylobacter incidence remained stable or decreased for all groups analyzed since 2012. Among 2449 linked records in 2017-2018, the median patient age was 40.2 years (interquartile range, 21.6-57.8 years), 54.8% of patients were male, 17.2% were hospitalized, and 0.2% died. The percentage of resistant infections increased from 24.5% in 2005-2016 to 29.7% in 2017-2018 for ciprofloxacin (P < .001) and from 2.6% to 3.3% for erythromycin (P = .04). Persons with recent international travel had higher odds than nontravelers of having isolates resistant to ciprofloxacin (adjusted odds ratio [aOR] varied from 1.7 to 10.6 by race/ethnicity) and erythromycin (aOR = 1.7; 95% confidence interval, 1.3-2.1). CONCLUSIONS: Campylobacter incidence has remained stable or decreased, whereas resistance to antimicrobials recommended for treatment has increased. Recent international travel increased the risk of resistance. |
The United States COVID-19 Forecast Hub dataset (preprint)
Cramer EY , Huang Y , Wang Y , Ray EL , Cornell M , Bracher J , Brennen A , Rivadeneira AJC , Gerding A , House K , Jayawardena D , Kanji AH , Khandelwal A , Le K , Mody V , Mody V , Niemi J , Stark A , Shah A , Wattanchit N , Zorn MW , Reich NG , US COVID-19 Forecast Hub Consortium , Lopez VK , Walker JW , Slayton RB , Johansson MA , Biggerstaff M . medRxiv 2021 2021.11.04.21265886 Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work. Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below: AIpert-pwllnod: Natural Sciences and Engineering Research Council of Canada; Caltech-CS156: Gary Clinard Innovation Fund; CEID-Walk: University of Georgia; CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook; COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health; Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information & Data Science Pilot Project; Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation; CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation; DDS-NBDS: NSF III-1812699; epiforecasts-ensemble1: Wellcome Trust (210758/Z/18/Z) FDANIHASU: supported by the Intramural Research Program of the NIH/NIDDK; GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowment, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. & Charlene Zalesky, and Claudia & Paul Raines, CDC MInD-Healthcare U01CK000531-Supplement; IHME: This work was supported by the Bill & Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096); Imperial-ensemble1: SB acknowledges funding from the Wellcome Trust (219415); Institute of Business Forecasting: IBF; IowaStateLW-STEM: NSF DMS-1916204, Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics; IUPUI CIS: NSF; JHU_CSSE-DECOM: JHU CSSE: National Science Foundation (NSF) RAPID Real-time Forecasting of COVID-19 risk in the USA. 2021-2022. Award ID: 2108526. National Science Foundation (NSF) RAPID Development of an interactive web-based dashboard to track COVID-19 in real-time. 2020. Award ID: 2028604; JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers for Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, & Infectious Disease Initiative (26798 Seed Grant); JHU_UNC_GAS-StatMechP ol: NIH NIGMS: R01GM140564; JHUAPL-Bucky: US Dept of Health and Human Services; KITmetricslab-select_ensemble: Daniel Wolffram gratefully acknowledges support by the Klaus Tschira Foundation; LANL-GrowthRate: LANL LDRD 20200700ER; MIT-Cassandra: MIT Quest for Intelligence; MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01; CA NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE); NotreDame-FRED: NSF RAPID DEB 2027718; NotreDame-mobility: NSF RAPID DEB 2027718; PSI-DRAFT: NSF RAPID Grant # 2031536; QJHong-Encounter: NSF DMR-2001411 and DMR-1835939; SDSC_ISG-TrendModel: The development of the dashboard was partly funded by the Fondation Privee des Hopitaux Universitaires de Geneve; UA-EpiCovDA: NSF RAPID Grant # 2028401; UChicagoCHATTOPADHYAY-UnIT: Defense Advanced Research Projects Agency (DARPA) #HR00111890043/P00004 (I. Chattopadhyay, University of Chicago); UCSB-ACTS: NSF RAPID IIS 2029626; UCSD_NEU-DeepGLEAM: Google Faculty Award, W31P4Q-21-C-0014; UMass-MechBayes: NIGMS #R35GM119582, NSF #1749854, NIGMS #R35GM119582; UMich-RidgeTfReg: This project is funded by the University of Michigan Physics Department and the University of Michigan Office of Research; UVA-Ensemble: National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and Virginia Dept of Health Grant VDH-21-501-0141; Wadnwani_AI-BayesOpt: This study is made possible by the generous support of the American People through the United States Agency for International Development (USAID). The work described in this article was implemented under the TRACETB Project, managed by WIAI under the terms of Cooperative Agreement Number 72038620CA00006. The contents of this manuscript are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government; WalmartLabsML-LogForecasting: Team acknowledges Walmart to support this study Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced are available online at https://github.com/reichlab/covid19-forecast-hub https://github.com/reichlab/covid19-forecast-hub |
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US (preprint)
Cramer EY , Ray EL , Lopez VK , Bracher J , Brennen A , Castro Rivadeneira AJ , Gerding A , Gneiting T , House KH , Huang Y , Jayawardena D , Kanji AH , Khandelwal A , Le K , Mühlemann A , Niemi J , Shah A , Stark A , Wang Y , Wattanachit N , Zorn MW , Gu Y , Jain S , Bannur N , Deva A , Kulkarni M , Merugu S , Raval A , Shingi S , Tiwari A , White J , Abernethy NF , Woody S , Dahan M , Fox S , Gaither K , Lachmann M , Meyers LA , Scott JG , Tec M , Srivastava A , George GE , Cegan JC , Dettwiller ID , England WP , Farthing MW , Hunter RH , Lafferty B , Linkov I , Mayo ML , Parno MD , Rowland MA , Trump BD , Zhang-James Y , Chen S , Faraone SV , Hess J , Morley CP , Salekin A , Wang D , Corsetti SM , Baer TM , Eisenberg MC , Falb K , Huang Y , Martin ET , McCauley E , Myers RL , Schwarz T , Sheldon D , Gibson GC , Yu R , Gao L , Ma Y , Wu D , Yan X , Jin X , Wang YX , Chen Y , Guo L , Zhao Y , Gu Q , Chen J , Wang L , Xu P , Zhang W , Zou D , Biegel H , Lega J , McConnell S , Nagraj VP , Guertin SL , Hulme-Lowe C , Turner SD , Shi Y , Ban X , Walraven R , Hong QJ , Kong S , van de Walle A , Turtle JA , Ben-Nun M , Riley S , Riley P , Koyluoglu U , DesRoches D , Forli P , Hamory B , Kyriakides C , Leis H , Milliken J , Moloney M , Morgan J , Nirgudkar N , Ozcan G , Piwonka N , Ravi M , Schrader C , Shakhnovich E , Siegel D , Spatz R , Stiefeling C , Wilkinson B , Wong A , Cavany S , España G , Moore S , Oidtman R , Perkins A , Kraus D , Kraus A , Gao Z , Bian J , Cao W , Lavista Ferres J , Li C , Liu TY , Xie X , Zhang S , Zheng S , Vespignani A , Chinazzi M , Davis JT , Mu K , Pastore YPiontti A , Xiong X , Zheng A , Baek J , Farias V , Georgescu A , Levi R , Sinha D , Wilde J , Perakis G , Bennouna MA , Nze-Ndong D , Singhvi D , Spantidakis I , Thayaparan L , Tsiourvas A , Sarker A , Jadbabaie A , Shah D , Della Penna N , Celi LA , Sundar S , Wolfinger R , Osthus D , Castro L , Fairchild G , Michaud I , Karlen D , Kinsey M , Mullany LC , Rainwater-Lovett K , Shin L , Tallaksen K , Wilson S , Lee EC , Dent J , Grantz KH , Hill AL , Kaminsky J , Kaminsky K , Keegan LT , Lauer SA , Lemaitre JC , Lessler J , Meredith HR , Perez-Saez J , Shah S , Smith CP , Truelove SA , Wills J , Marshall M , Gardner L , Nixon K , Burant JC , Wang L , Gao L , Gu Z , Kim M , Li X , Wang G , Wang Y , Yu S , Reiner RC , Barber R , Gakidou E , Hay SI , Lim S , Murray C , Pigott D , Gurung HL , Baccam P , Stage SA , Suchoski BT , Prakash BA , Adhikari B , Cui J , Rodríguez A , Tabassum A , Xie J , Keskinocak P , Asplund J , Baxter A , Oruc BE , Serban N , Arik SO , Dusenberry M , Epshteyn A , Kanal E , Le LT , Li CL , Pfister T , Sava D , Sinha R , Tsai T , Yoder N , Yoon J , Zhang L , Abbott S , Bosse NI , Funk S , Hellewell J , Meakin SR , Sherratt K , Zhou M , Kalantari R , Yamana TK , Pei S , Shaman J , Li ML , Bertsimas D , Skali Lami O , Soni S , Tazi Bouardi H , Ayer T , Adee M , Chhatwal J , Dalgic OO , Ladd MA , Linas BP , Mueller P , Xiao J , Wang Y , Wang Q , Xie S , Zeng D , Green A , Bien J , Brooks L , Hu AJ , Jahja M , McDonald D , Narasimhan B , Politsch C , Rajanala S , Rumack A , Simon N , Tibshirani RJ , Tibshirani R , Ventura V , Wasserman L , O'Dea EB , Drake JM , Pagano R , Tran QT , Ho LST , Huynh H , Walker JW , Slayton RB , Johansson MA , Biggerstaff M , Reich NG . medRxiv 2021 2021.02.03.21250974 Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information& Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. & Charlene Zalesky, and Claudia & Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill & Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, & Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44 |
Evaluation of the durability of long-lasting insecticidal nets in Guatemala (preprint)
Castellanos ME , Rodas S , Juárez JG , Lol JC , Chanquin S , Morales Z , Vizcaino L , Smith SC , Vanden Eng J , Woldu HG , Lenhart A , Padilla N . medRxiv 2020 2020.07.30.20165316 Background Insecticide-treated bednets (ITNs) are widely used for the prevention and control of malaria. In Guatemala, since 2006, ITNs have been distributed free of charge in the highest risk malaria-endemic areas and constitute one of the primary vector control measures in the country. Despite relying on ITNs for almost 15 years, there is a lack of data to inform the timely replacement of ITNs whose effectiveness becomes diminished by routine use.Methods We assessed the survivorship, physical integrity, insecticide content and bio-efficacy of ITNs through cross-sectional surveys conducted at 18, 24 and 32 months after a 2012 distribution of PermaNet® 2.0 in a malaria focus in Guatemala. A total of 988 ITNs were analyzed (290 at 18 months, 349 at 24 months and 349 at 32 months).Results The functional survivorship of bednets decreased over time, from 92% at 18 months, to 81% at 24 months and 69% at 32 months. Independent of the time of the survey, less than 80% of the bednets that were still present in the household were reported to have been used the night before. Most of the bednets had been washed at least once (88% at 18 months, 92% at 24 months and 96% at 32 months). The proportion of bednets categorized as “in good condition” per WHO guidelines of the total hole surface area, diminished from 77% at 18 months to 58% at 32 months. The portion of ITNs with deltamethrin concentration less than 10mg/m2 increased over time (14% at 18 months, 23% at 24 months, and 35% at 32 months). Among the bednets for which bioassays were conducted, the percentage that met WHO criteria for efficacy dropped from 90% at 18 months to 52% at 32 months.Conclusion While our assessment demonstrated that nets were in relatively good physical condition over time, the combination of declining bio-efficacy over time and low use rates limited the overall effectiveness of the LLINs. Efforts to encourage the community to retain, use, and properly care for the LLINs may improve their impact. Durability assessments should be included in future campaigns.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThe funding for this study was provided by the United States Agency for International Development (USAID) via the Amazon Malaria Initiative (AMI), Centers for Disease Control and Prevention (CDC) of the United States of America, Guatemalan Ministry of Public Health and Social Welfare and Center for Health Studies and Universidad del Valle de Guatemala. The funding bodies had no role in the design of the study and collection, analysis, and interpretation of the data and in writing the manuscript.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Oral informed consent was obtained from all participants prior to study inclusion. This study was approved by the Ethics Committee of the Center for Health Studies at Universidad del Valle de Guatemala (Approval Number: 081-06-2013); CDC investigators were not considered to be engaged in human subjects research.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe data that support the findings of this study are availa le on request from the senior author, NP. The data are not publicly available due to containing information that could compromise the privacy of participants.GISgeographic information systemGISgeographic information systemGPSGlobal positioning systemIQRinterquartile rangeITNInsecticide-treated bednetLLINlong-lasting insecticide-treated bednetLOESSLocally Weighted Scatterplot SmoothingMoHMinistry of HealthPDApersonal digital assistantTHSAtotal hole surface areatmmedian survival timeWHOWorld Health OrganizationXRFx-ray fluorescence |
A Collaborative Multi-Model Ensemble for Real-Time Influenza Season Forecasting in the U.S (preprint)
Reich NG , McGowan CJ , Yamana TK , Tushar A , Ray EL , Osthus D , Kandula S , Brooks LC , Crawford-Crudell W , Gibson GC , Moore E , Silva R , Biggerstaff M , Johansson MA , Rosenfeld R , Shaman J . bioRxiv 2019 566604 Seasonal influenza results in substantial annual morbidity and mortality in the United States and worldwide. Accurate forecasts of key features of influenza epidemics, such as the timing and severity of the peak incidence in a given season, can inform public health response to outbreaks. As part of ongoing efforts to incorporate data and advanced analytical methods into public health decision-making, the United States Centers for Disease Control and Prevention (CDC) has organized seasonal influenza forecasting challenges since the 2013/2014 season. In the 2017/2018 season, 22 teams participated. A subset of four teams created a research consortium called the FluSight Network in early 2017. During the 2017/2018 season they worked together to produce a collaborative multi-model ensemble that combined 21 separate component models into a single model using a machine learning technique called stacking. This approach creates a weighted average of predictive densities where the weight for each component is based on that component’s forecast accuracy in past seasons. In the 2017/2018 influenza season, one of the largest seasonal outbreaks in the last 15 years, this multi-model ensemble performed better on average than all individual component models and placed second overall in the CDC challenge. It also outperformed the baseline multi-model ensemble created by the CDC that took a simple average of all models submitted to the forecasting challenge. This project shows that collaborative efforts between research teams to develop ensemble forecasting approaches can bring measurable improvements in forecast accuracy and important reductions in the variability of performance from year to year. Efforts such as this, that emphasize real-time testing and evaluation of forecasting models and facilitate the close collaboration between public health officials and modeling researchers, are essential to improving our understanding of how best to use forecasts to improve public health response to seasonal and emerging epidemic threats. |
Forecasting seasonal influenza in the U.S.: A collaborative multi-year, multi-model assessment of forecast performance (preprint)
Reich NG , Brooks LC , Fox SJ , Kandula S , McGowan CJ , Moore E , Osthus D , Ray EL , Tushar A , Yamana TK , Biggerstaff M , Johansson MA , Rosenfeld R , Shaman J . bioRxiv 2018 397190 Influenza infects an estimated 9 to 35 million individuals each year in the United States and is a contributing cause for between 12,000 and 56,000 deaths annually. Seasonal outbreaks of influenza are common in temperate regions of the world, with highest incidence typically occurring in colder and drier months of the year. Real-time forecasts of influenza transmission can inform public health response to outbreaks. We present the results of a multi-institution collaborative effort to standardize the collection and evaluation of forecasting models for influenza in the US for the 2010/2011 through 2016/2017 influenza seasons. For these seven seasons, we assembled weekly real-time forecasts of 7 targets of public health interest from 22 different models. We compared forecast accuracy of each model relative to a historical baseline seasonal average. Across all regions of the US, over half of the models showed consistently better performance than the historical baseline when forecasting incidence of influenza-like illness 1, 2 and 3 weeks ahead of available data and when forecasting the timing and magnitude of the seasonal peak. In some regions, delays in data reporting were strongly and negatively associated with forecast accuracy. More timely reporting and an improved overall accessibility to novel and traditional data sources are needed to improve forecasting accuracy and its integration with real-time public health decision-making. |
An enhanced method for calculating trends in infections caused by pathogens transmitted commonly through food (preprint)
Weller DL , Ray LC , Payne DC , Griffin PM , Hoekstra RM , Rose EB , Bruce BB . medRxiv 2022 17 This brief methods paper is being published concomitantly with "Preliminary Incidence and Trends of Infections Caused by Pathogens Transmitted Commonly Through Food- Foodborne Diseases Active Surveillance Network, 10 U.S. Sites, 2016-2021" in Morbidity and Mortality Weekly Reports (MMWR). That article describes the application of the new model described here to analyze trends and evaluate progress towards the prevention of infection from enteric pathogens in the United States. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license. |
Diagnostic accuracy of three computer-aided detection systems for detecting pulmonary tuberculosis on chest radiography when used for screening: Analysis of an international, multicenter migrants screening study
Gelaw SM , Kik SV , Ruhwald M , Ongarello S , Egzertegegne TS , Gorbacheva O , Gilpin C , Marano N , Lee S , Phares CR , Medina V , Amatya B , Denkinger CM . PLOS Glob Public Health 2023 3 (7) e0000402 The aim of this study was to independently evaluate the diagnostic accuracy of three artificial intelligence (AI)-based computer aided detection (CAD) systems for detecting pulmonary tuberculosis (TB) on global migrants screening chest x-ray (CXR) cases when compared against both microbiological and radiological reference standards (MRS and RadRS, respectively). Retrospective clinical data and CXR images were collected from the International Organization for Migration (IOM) pre-migration health assessment TB screening global database for US-bound migrants. A total of 2,812 participants were included in the dataset used for analysis against RadRS, of which 1,769 (62.9%) had accompanying microbiological test results and were included against MRS. All CXRs were interpreted by three CAD systems (CAD4TB v6, Lunit INSIGHT v4.9.0, and qXR v2) in offline setting, and re-interpreted by two expert radiologists in a blinded fashion. The performance was evaluated using receiver operating characteristics curve (ROC), estimates of sensitivity and specificity at different CAD thresholds against both microbiological and radiological reference standards (MRS and RadRS, respectively), and was compared with that of the expert radiologists. The area under the curve against MRS was highest for Lunit (0.85; 95% CI 0.83-0.87), followed by qXR (0.75; 95% CI 0.72-0.77) and then CAD4TB (0.71; 95% CI 0.68-0.73). At a set specificity of 70%, Lunit had the highest sensitivity (81.4%; 95% CI 77.9-84.6); at a set sensitivity of 90%, specificity was also highest for Lunit (54.5%; 95% CI 51.7-57.3). The CAD systems performed comparable to the sensitivity (98.3%), and except CAD4TB, to specificity (13.7%) of the expert radiologists. Similar trends were observed when using RadRS. Area under the curve against RadRS was highest for CAD4TB (0.87; 95% CI 0.86-0.89) and Lunit (0.87; 95% CI 0.85-0.88) followed by qXR (0.81; 95% CI 0.80-0.83). At a set specificity of 70%, CAD4TB had highest sensitivity (84.1%; 95% CI 82.3-85.8) followed by Lunit (80.9%; 95% CI 78.9-82.7); and at a set sensitivity of 90%, specificity was also highest for CAD4TB (54.6%; 95% CI 51.3-57.8). In conclusion, the study demonstrated that the three CAD systems had broadly similar diagnostic accuracy with regard to TB screening and comparable accuracy to an expert radiologist against MRS. Compared with different reference standards, Lunit performed better than both qXR and CAD4TB against MRS, and CAD4TB and Lunit better than qXR against RadRS. Moreover, the performance of the CADs can be impacted by characteristics of subgroup of population. The main limitation was that our study relied on retrospective data and MRS was not routinely done in individuals with a low suspicion of TB and a normal CXR. Our findings suggest that CAD systems could be a useful tool for TB screening programs in remote, high TB prevalent places where access to expert radiologists may be limited. However, further large-scale prospective studies are needed to address outstanding questions around the operational performance and technical requirements of the CAD systems. |
Preliminary incidence and trends of infections caused by pathogens transmitted commonly through food - Foodborne Diseases Active Surveillance Network, 10 U.S. Sites, 2022
Delahoy MJ , Shah HJ , Weller DL , Ray LC , Smith K , McGuire S , Trevejo RT , Scallan Walter E , Wymore K , Rissman T , McMillian M , Lathrop S , LaClair B , Boyle MM , Harris S , Zablotsky-Kufel J , Houck K , Devine CJ , Lau CE , Tauxe RV , Bruce BB , Griffin PM , Payne DC . MMWR Morb Mortal Wkly Rep 2023 72 (26) 701-706 Each year, infections from major foodborne pathogens are responsible for an estimated 9.4 million illnesses, 56,000 hospitalizations, and 1,350 deaths in the United States (1). To evaluate progress toward prevention of enteric infections in the United States, the Foodborne Diseases Active Surveillance Network (FoodNet) conducts surveillance for laboratory-diagnosed infections caused by eight pathogens transmitted commonly through food at 10 U.S. sites. During 2020-2021, FoodNet detected decreases in many infections that were due to behavioral modifications, public health interventions, and changes in health care-seeking and testing practices during the COVID-19 pandemic. This report presents preliminary estimates of pathogen-specific annual incidences during 2022, compared with average annual incidences during 2016-2018, the reference period for the U.S. Department of Health and Human Services' Healthy People 2030 targets (2). Many pandemic interventions ended by 2022, resulting in a resumption of outbreaks, international travel, and other factors leading to enteric infections. During 2022, annual incidences of illnesses caused by the pathogens Campylobacter, Salmonella, Shigella, and Listeria were similar to average annual incidences during 2016-2018; however, incidences of Shiga toxin-producing Escherichia coli (STEC), Yersinia, Vibrio, and Cyclospora illnesses were higher. Increasing culture-independent diagnostic test (CIDT) usage likely contributed to increased detection by identifying infections that would have remained undetected before widespread CIDT usage. Reducing pathogen contamination during poultry slaughter and processing of leafy greens requires collaboration among food growers and processors, retail stores, restaurants, and regulators. |
Implementation of BPaL in the United States: Experience using a novel all-oral treatment regimen for treatment of rifampin-resistant or rifampin-intolerant TB disease
Haley CA , Schechter MC , Ashkin D , Peloquin CA , Cegielski JP , Andrino BB , Burgos M , Caloia LA , Chen L , Colon-Semidey A , DeSilva MB , Dhanireddy S , Dorman SE , Dworkin FF , Hammond-Epstein H , Easton AV , Gaensbauer JT , Ghassemieh B , Gomez ME , Horne D , Jasuja S , Jones BA , Kaplan LJ , Khan AE , Kracen E , Labuda S , Landers KM , Lardizabal AA , Lasley MT , Letzer DM , Lopes VK , Lubelchek RJ , Macias CP , Mihalyov A , Misch EA , Murray JA , Narita M , Nilsen DM , Ninneman MJ , Ogawa L , Oladele A , Overman M , Ray SM , Ritger KA , Rowlinson MC , Sabuwala N , Schiller TM , Schwartz LE , Spitters C , Thomson DB , Tresgallo RR , Valois P , Goswami ND . Clin Infect Dis 2023 77 (7) 1053-1062 BACKGROUND: Rifampin-resistant tuberculosis is a leading cause of morbidity worldwide; only one-third of persons initiate treatment and outcomes are often inadequate. Several trials demonstrate 90% efficacy using an all-oral, six-month regimen of bedaquiline, pretomanid, and linezolid (BPaL), but significant toxicity occurred using 1200 mg linezolid. After U.S. FDA approval in 2019, some U.S. clinicians rapidly implemented BPaL using an initial linezolid 600 mg dose adjusted by serum drug concentrations and clinical monitoring. METHODS: Data from U.S. patients treated with BPaL between 10/14/2019 and 4/30/2022 were compiled and analyzed by the BPaL Implementation Group (BIG), including baseline examination and laboratory, electrocardiographic, and clinical monitoring throughout treatment and follow-up. Linezolid dosing and clinical management was provider-driven, and most had linezolid adjusted by therapeutic drug monitoring (TDM). RESULTS: Of 70 patients starting BPaL, two changed to rifampin-based therapy, 68 (97.1%) completed BPaL, and two of these 68 (2.9%) patients relapsed after completion. Using an initial 600 mg linezolid dose daily adjusted by TDM and careful clinical and laboratory monitoring for side effects, supportive care, and expert consultation throughout BPaL treatment, three (4.4%) patients with hematologic toxicity and four (5.9%) with neurotoxicity required a change in linezolid dose or frequency. The median BPaL duration was 6 months. CONCLUSIONS: BPaL has transformed treatment for rifampin-resistant or intolerant tuberculosis. In this cohort, effective treatment required less than half the duration recommended in ATS/CDC/ERS/IDSA 2019 guidelines for drug-resistant tuberculosis. Use of individualized linezolid dosing and monitoring likely enhanced safety and treatment completion. The BIG cohort demonstrates that early implementation of new tuberculosis treatments in the U.S. is feasible. |
Estimates of bivalent mRNA vaccine durability in preventing COVID-19-associated hospitalization and critical illness among adults with and without immunocompromising conditions - VISION Network, September 2022-April 2023
Link-Gelles R , Weber ZA , Reese SE , Payne AB , Gaglani M , Adams K , Kharbanda AB , Natarajan K , DeSilva MB , Dascomb K , Irving SA , Klein NP , Grannis SJ , Ong TC , Embi PJ , Dunne MM , Dickerson M , McEvoy C , Arndorfer J , Naleway AL , Goddard K , Dixon BE , Griggs EP , Hansen J , Valvi N , Najdowski M , Timbol J , Rogerson C , Fireman B , Fadel WF , Patel P , Ray CS , Wiegand R , Ball S , Tenforde MW . MMWR Morb Mortal Wkly Rep 2023 72 (21) 579-588 On September 1, 2022, CDC's Advisory Committee on Immunization Practices (ACIP) recommended a single bivalent mRNA COVID-19 booster dose for persons aged ≥12 years who had completed at least a monovalent primary series. Early vaccine effectiveness (VE) estimates among adults aged ≥18 years showed receipt of a bivalent booster dose provided additional protection against COVID-19-associated emergency department and urgent care visits and hospitalizations compared with that in persons who had received only monovalent vaccine doses (1); however, insufficient time had elapsed since bivalent vaccine authorization to assess the durability of this protection. The VISION Network* assessed VE against COVID-19-associated hospitalizations by time since bivalent vaccine receipt during September 13, 2022-April 21, 2023, among adults aged ≥18 years with and without immunocompromising conditions. During the first 7-59 days after vaccination, compared with no vaccination, VE for receipt of a bivalent vaccine dose among adults aged ≥18 years was 62% (95% CI = 57%-67%) among adults without immunocompromising conditions and 28% (95% CI = 10%-42%) among adults with immunocompromising conditions. Among adults without immunocompromising conditions, VE declined to 24% (95% CI = 12%-33%) among those aged ≥18 years by 120-179 days after vaccination. VE was generally lower for adults with immunocompromising conditions. A bivalent booster dose provided the highest protection, and protection was sustained through at least 179 days against critical outcomes, including intensive care unit (ICU) admission or in-hospital death. These data support updated recommendations allowing additional optional bivalent COVID-19 vaccine doses for certain high-risk populations. All eligible persons should stay up to date with recommended COVID-19 vaccines. |
Epidemiology of sepsis in US children and young adults
Magill SS , Sapiano MRP , Gokhale R , Nadle J , Johnston H , Brousseau G , Maloney M , Ray SM , Wilson LE , Perlmutter R , Lynfield R , DeSilva M , Sievers M , Irizarry L , Dumyati G , Pierce R , Zhang A , Kainer M , Fiore AE , Dantes R , Epstein L . Open Forum Infect Dis 2023 10 (5) ofad218 BACKGROUND: Most multicenter studies of US pediatric sepsis epidemiology use administrative data or focus on pediatric intensive care units. We conducted a detailed medical record review to describe sepsis epidemiology in children and young adults. METHODS: In a convenience sample of hospitals in 10 states, patients aged 30 days-21 years, discharged during 1 October 2014-30 September 2015, with explicit diagnosis codes for severe sepsis or septic shock, were included. Medical records were reviewed for patients with documentation of sepsis, septic shock, or similar terms. We analyzed overall and age group-specific patient characteristics. RESULTS: Of 736 patients in 26 hospitals, 442 (60.1%) had underlying conditions. Most patients (613 [83.3%]) had community-onset sepsis, although most community-onset sepsis was healthcare associated (344 [56.1%]). Two hundred forty-one patients (32.7%) had outpatient visits 1-7 days before sepsis hospitalization, of whom 125 (51.9%) received antimicrobials ≤30 days before sepsis hospitalization. Age group-related differences included common underlying conditions (<5 years: prematurity vs 5-12 years: chronic pulmonary disease vs 13-21 years: chronic immunocompromise); medical device presence ≤30 days before sepsis hospitalization (1-4 years: 46.9% vs 30 days-11 months: 23.3%); percentage with hospital-onset sepsis (<5 years: 19.6% vs ≥5 years: 12.0%); and percentage with sepsis-associated pathogens (30 days-11 months: 65.6% vs 13-21 years: 49.3%). CONCLUSIONS: Our data suggest potential opportunities to raise sepsis awareness among outpatient providers to facilitate prevention, early recognition, and intervention in some patients. Consideration of age-specific differences may be important as approaches are developed to improve sepsis prevention, risk prediction, recognition, and management. |
Machine learning to predict bacteriologic confirmation of Mycobacterium tuberculosis in infants and very young children
Smith JP , Milligan K , McCarthy KD , McHembere W , Okeyo E , Musau SK , Okumu A , Song R , Click ES , Cain KP . PLOS Digit Health 2023 2 (5) e0000249 Diagnosis of tuberculosis (TB) among young children (<5 years) is challenging due to the paucibacillary nature of clinical disease and clinical similarities to other childhood diseases. We used machine learning to develop accurate prediction models of microbial confirmation with simply defined and easily obtainable clinical, demographic, and radiologic factors. We evaluated eleven supervised machine learning models (using stepwise regression, regularized regression, decision tree, and support vector machine approaches) to predict microbial confirmation in young children (<5 years) using samples from invasive (reference-standard) or noninvasive procedure. Models were trained and tested using data from a large prospective cohort of young children with symptoms suggestive of TB in Kenya. Model performance was evaluated using areas under the receiver operating curve (AUROC) and precision-recall curve (AUPRC), accuracy metrics. (i.e., sensitivity, specificity), F-beta scores, Cohen's Kappa, and Matthew's Correlation Coefficient. Among 262 included children, 29 (11%) were microbially confirmed using any sampling technique. Models were accurate at predicting microbial confirmation in samples obtained from invasive procedures (AUROC range: 0.84-0.90) and from noninvasive procedures (AUROC range: 0.83-0.89). History of household contact with a confirmed case of TB, immunological evidence of TB infection, and a chest x-ray consistent with TB disease were consistently influential across models. Our results suggest machine learning can accurately predict microbial confirmation of M. tuberculosis in young children using simply defined features and increase the bacteriologic yield in diagnostic cohorts. These findings may facilitate clinical decision making and guide clinical research into novel biomarkers of TB disease in young children. |
National tuberculosis prevalence surveys in Africa, 2008-2016: an overview of results and lessons learned
Law I , Floyd K , African TB Prevalence Survey Group , Bloss E , Ershova J , Moonan PK . Trop Med Int Health 2020 25 (11) 1308-1327 OBJECTIVE AND METHODS: Worldwide, tuberculosis (TB) is the leading cause of death from a single infectious agent. In many countries, national TB prevalence surveys are the only way to reliably measure the burden of TB disease and can also provide other evidence to inform national efforts to improve TB detection and treatment. Our objective was to synthesise the results and lessons learned from national surveys completed in Africa between 2008 and 2016, to complement a previous review for Asia. RESULTS: Twelve surveys completed in Africa were identified: Ethiopia (2010-2011), Gambia (2011-2013), Ghana (2013), Kenya (2015-2016), Malawi (2013-2014), Nigeria (2012), Rwanda (2012), Sudan (2013-2014), Tanzania (2011-2012), Uganda (2014-2015), Zambia (2013-2014) and Zimbabwe (2014). The eligible population in all surveys was people aged ≥15 years who met residency criteria. In total 588 105 individuals participated, equivalent to 82% (range 57-96%) of those eligible. The prevalence of bacteriologically confirmed pulmonary TB disease in those ≥15 years varied from 119 (95% CI 79-160) per 100 000 population in Rwanda and 638 (95% CI 502-774) per 100 000 population in Zambia. The male:female ratio was 2.0 overall, ranging from 1.2 (Ethiopia) to 4.1 (Uganda). Prevalence per 100 000 population generally increased with age, but the absolute number of cases was usually highest among those aged 35-44 years. Of identified TB cases, 44% (95% CI 40-49) did not report TB symptoms during screening and were only identified as eligible for diagnostic testing due to an abnormal chest X-ray. The overall ratio of prevalence to case notifications was 2.5 (95% CI 1.8-3.2) and was consistently higher for men than women. Many participants who did report TB symptoms had not sought care; those that had were more likely to seek care in a public health facility. HIV prevalence was systematically lower among prevalent cases than officially notified TB patients with an overall ratio of 0.5 (95% CI 0.3-0.7). The two main study limitations were that none of the surveys included people <15 years, and 5 of 12 surveys did not have data on HIV status. CONCLUSIONS: National TB prevalence surveys implemented in Africa between 2010 and 2016 have contributed substantial new evidence about the burden of TB disease, its distribution by age and sex, and gaps in TB detection and treatment. Policies and practices to improve access to health services and reduce under-reporting of detected TB cases are needed, especially among men. All surveys provide a valuable baseline for future assessment of trends in TB disease burden. |
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