BACKGROUND: The second phase of the U.S. President's Emergency Plan for AIDS Relief (PEPFAR) transitioned from scaling up HIV prevention and treatment to promoting sustainability and capacity building for programs monitoring performance and evaluating key program indicators. We assessed the success of a monitoring and evaluation (M&E) curriculum designed to build capacity in three PEPFAR-supported countries. METHODS: We customized M&E trainings based on country-specific epidemic control priorities in Ethiopia, Guatemala, and Cameroon. The M&E curriculum included five modules and three evaluation activities to assess impact: (i) in-person pre-post confidence assessment surveys (CAS), (ii) in-person pre-post knowledge tests (PPKT), and (iii) electronic 6-12 months post-training translating knowledge into practice (TKP) surveys. Pre- and post-training results were compared within and across countries and triangulation with the qualitative data evaluated overall success. RESULTS: Among 188 participants attending M&E trainings, 154 (82 %) responded to CAS and 165 (88 %) participants from Ethiopia and Cameroon completed PPKT. Overall CAS scores between pre- and post-test improved [Score mean difference:1.5-1.9]. PPKT indicated statistically significant knowledge gained. One out of five TKP respondents provided direct application examples from the M&E training. CONCLUSION: While feedback was predominantly positive overall, revisions were recommended for three of the five modules. Developing a customizable and adaptable M&E curriculum may sustain countries' ability to monitor their progress towards epidemic control.

Leptospirosis, an acute bacterial zoonotic disease, is endemic in Puerto Rico. Infection in approximately 10%-15% of patients with clinical disease progresses to severe, potentially fatal illness. Increased incidence has been associated with flooding in endemic areas around the world. In 2022, Hurricane Fiona, a Category 1 hurricane, made landfall and inundated Puerto Rico with heavy rainfall and severe flooding, increasing the risk for a leptospirosis outbreak. In response, the Puerto Rico Department of Health (PRDH) changed guidelines to make leptospirosis cases reportable within 24 hours, centralized the case investigation management system, and provided training and messaging to health care providers. To evaluate changes in risk for leptospirosis after Hurricane Fiona to that before the storm, the increase in cases was quantified, and patient characteristics and geographic distribution were compared. During the 15 weeks after Hurricane Fiona, 156 patients experienced signs and symptoms of leptospirosis and had a specimen with a positive laboratory result reported to PRDH. The mean weekly number of cases during this period was 10.4, which is 3.6 as high as the weekly number of cases during the previous 37 weeks (2.9). After Hurricane Fiona, the proportion of cases indicating exposure to potentially contaminated water increased from 11% to 35%, and the number of persons receiving testing increased; these factors likely led to the resulting overall surge in reported cases. Robust surveillance combined with outreach to health care providers after flooding events can improve leptospirosis case identification, inform clinicians considering early initiation of treatment, and guide public messaging to avoid wading, swimming, or any contact with potentially contaminated floodwaters.

INTRODUCTION: Chlamydia trachomatis (Ct) and Neisseria gonorrhoeae (Ng) infections are often asymptomatic; screening increases early detection and prevents disease, sequelae and further spread. To increase Ct and Ng testing, several countries have implemented specimen self-collection outside a clinical setting. While specimen self-collection at home is highly acceptable to patients and as accurate as specimens collected by healthcare providers, this strategy is new or not being used in some countries. To understand how offering at home specimen self-collection will affect testing uptake, test results, diagnosis and linkage to care, when compared with collection in clinical settings, we conducted a systematic literature review and meta-analysis of peer-reviewed studies. METHODS: We searched Medline, Embase, Global Health, Cochrane Library, CINAHL (EBSCOHost), Scopus and Clinical Trials. Studies were included if they directly compared specimens self-collected at home or in other non-clinical settings to specimen collection at a healthcare facility (self or clinician) for Ct and/or Ng testing and evaluated the following outcomes: uptake in testing, linkage to care, and concordance (agreement) between the two settings for the same individuals. Risk of bias (RoB) was assessed using Cochrane Risk of Bias (RoB2) tool for randomised control trials (RCTs). RESULTS: 19 studies, from 1998 to 2024, comprising 15 RCTs with a total of 62 369 participants and four concordance studies with 906 participants were included. Uptake of Ct or Ng testing was 2.61 times higher at home compared with clinical settings. There was a high concordance between specimens collected at home and in clinical settings, and linkage to care was not significantly different between the two settings (prevalence ratio 0.96 (95% CI 0.91-1.01)). CONCLUSION: Our meta-analysis and systematic literature review show that offering self-collection of specimens at home or in other non-clinical settings could be used as an additional strategy to increase sexually transmitted infection testing in countries that have not yet widely adopted this collection method.

INTRODUCTION: There is no licensed vaccine against gonorrhea but Neisseria meningitidis serogroup B outer membrane vesicle-based vaccines, like MenB-4C, may offer cross-protection against gonorrhea. This systematic review and meta-analysis synthesized the published literature on MenB-4C vaccine effectiveness against gonorrhea. METHODS: We conducted a literature search of electronic databases (PubMed, Medline, Embase, Global Health, Scopus, Google Scholar, CINAHL, and Cochrane Library) to identify peer-reviewed papers, published in English, from 1/1/2013-7/12/2024 that reported MenB-4C vaccine effectiveness estimates against gonorrhea and gonorrhea/chlamydia co-infection, and the duration of MenB-4C vaccine-induced protection. We estimated pooled MenB-4C vaccine effectiveness (≥1 dose) against gonorrhea using the DerSimonian-Laird random effects model. RESULTS: Eight papers met our eligibility criteria. Receipt of ≥1 dose of MenB-4C vaccine was 23%-47% effective against gonorrhea. Two doses of MenB-4C vaccine were 33-40% effective against gonorrhea and one dose of MenB-4C vaccine was 26% effective. MenB-4C vaccine effectiveness against gonorrhea/chlamydia co-infection was mixed with two studies reporting effectiveness estimates of 32% and 44%, and two other studies showing no protective effect. MenB-4C vaccine effectiveness against gonorrhea was comparable in people living with HIV (44%) and people not living with HIV (23%-47%). Pooled MenB-4C vaccine effectiveness (≥1 dose) against gonorrhea was 32.4%. One study concluded that MenB-4C vaccine effectiveness against gonorrhea may wane approximately 36 months post-vaccination. CONCLUSION: MenB-4C vaccine is moderately effective against gonorrhea in various populations. Prospective clinical trials that assess the efficacy of MenB-4C against gonorrhea, gonorrhea/chlamydia co-infection, and duration of protection are warranted to strengthen this evidence.

Bacterial zoonoses are established causes of severe febrile illness in East Africa. Within a fever etiology study, we applied a high-throughput 16S rRNA metagenomic assay validated for detecting bacterial zoonotic pathogens. We enrolled febrile patients admitted to 2 referral hospitals in Moshi, Tanzania, during September 2007-April 2009. Among 788 participants, median age was 20 (interquartile range 2-38) years. We performed PCR amplification of V1-V2 variable region 16S rRNA on cell pellet DNA, then metagenomic deep-sequencing and pathogenic taxonomic identification. We detected bacterial zoonotic pathogens in 10 (1.3%) samples: 3 with Rickettsia typhi, 1 R. conorii, 2 Bartonella quintana, 2 pathogenic Leptospira spp., and 1 Coxiella burnetii. One other sample had reads matching a Neoerhlichia spp. previously identified in a patient from South Africa. Our findings indicate that targeted 16S metagenomics can identify bacterial zoonotic pathogens causing severe febrile illness in humans, including potential novel agents.

BACKGROUND: Pathogenic Leptospira species are globally important zoonotic pathogens capable of infecting a wide range of host species. In marine mammals, reports of Leptospira have predominantly been in pinnipeds, with isolated reports of infections in cetaceans. CASE PRESENTATION: On 28 June 2021, a 150.5 cm long female, short-beaked common dolphin (Delphinus delphis delphis) stranded alive on the coast of southern California and subsequently died. Gross necropsy revealed multifocal cortical pallor within the reniculi of the kidney, and lymphoplasmacytic tubulointerstitial nephritis was observed histologically. Immunohistochemistry confirmed Leptospira infection, and PCR followed by lfb1 gene amplicon sequencing suggested that the infecting organism was L.kirschneri. Leptospira DNA capture and enrichment allowed for whole-genome sequencing to be conducted. Phylogenetic analyses confirmed the causative agent was a previously undescribed, divergent lineage of L.kirschneri. CONCLUSIONS: We report the first detection of pathogenic Leptospira in a short-beaked common dolphin, and the first detection in any cetacean in the northeastern Pacific Ocean. Renal lesions were consistent with leptospirosis in other host species, including marine mammals, and were the most significant lesions detected overall, suggesting leptospirosis as the likely cause of death. We identified the cause of the infection as L.kirschneri, a species detected only once before in a marine mammal - a northern elephant seal (Mirounga angustirostris) of the northeastern Pacific. These findings raise questions about the mechanism of transmission, given the obligate marine lifestyle of cetaceans (in contrast to pinnipeds, which spend time on land) and the commonly accepted view that Leptospira are quickly killed by salt water. They also raise important questions regarding the source of infection, and whether it arose from transmission among marine mammals or from terrestrial-to-marine spillover. Moving forward, surveillance and sampling must be expanded to better understand the extent to which Leptospira infections occur in the marine ecosystem and possible epidemiological linkages between and among marine and terrestrial host species. Generating Leptospira genomes from different host species will yield crucial information about possible transmission links, and our study highlights the power of new techniques such as DNA enrichment to illuminate the complex ecology of this important zoonotic pathogen.

Background: Bullying behaviors whether verbal, emotional, or physical impact nurses in several ways. Aim: The purpose of this study was to describe how newly licensed nurses managed the bullying behaviors they experienced. Methods: A qualitative descriptive design was used with 24 newly licensed nurses. Interviews followed an open-ended, semi-structured interview guide. Colaizzi's procedural steps for phenomenological analysis were used to analyze the transcript data. Results: Six themes emerged from the qualitative data: The Bullying, The Perception of the Event, How Bullying Affected Them, How They Dealt with Bullying, How They Wished Bullying Had Been Managed, and What the School Should Do. Conclusions: Organizational support, in the form of policies and procedures, could reduce bullying behaviors and improve nurse efficiency. Additionally, nursing schools can incorporate education about bullying into their curricula to both better prepare new nurses and break the cycle of bullying among nurses. © 2024 The Authors

OBJECTIVES: Leptospira, the spirochaete causing leptospirosis, can be classified into >250 antigenically distinct serovars. Although knowledge of the animal host species and geographic distribution of Leptospira serovars is critical to understand the human and animal epidemiology of leptospirosis, current data are fragmented. We aimed to systematically review, the literature on animal host species and geographic distribution of Leptospira serovars to examine associations between serovars with animal host species and regions and to identify geographic regions in need of study. METHODS: Nine library databases were searched from inception through 9 March 2023 using keywords including Leptospira, animal, and a list of serovars. We sought reports of detection of Leptospira, from any animal, characterised by cross agglutinin absorption test, monoclonal antibody typing, serum factor analysis, or pulsed-field gel electrophoresis to identify the serovar. RESULTS: We included 409 reports, published from 1927 through 2022, yielding data on 154 Leptospira serovars. The reports included data from 66 (26.5%) of 249 countries. Detections were from 144 animal host species including 135 (93.8%) from the class Mammalia, 5 (3.5%) from Amphibia, 3 (2.1%) from Reptilia, and 1 (0.7%) from Arachnida. Across the animal host species, Leptospira serovars that were detected in the largest number of animal species included Grippotyphosa (n = 39), Icterohaemorrhagiae (n = 29), Pomona (n = 28), Australis (n = 25), and Ballum (n = 25). Of serovars, 76 were detected in a single animal host species. We created an online database to identify animal host species for each serovar by country. CONCLUSIONS: We found that many countries have few or no Leptospira serovars detected from animal host species and that many serovars were detected from a single animal species. Our study highlights the importance of efforts to identify animal host species of leptospirosis, especially in places with a high incidence of human leptospirosis. We provide an updated resource for leptospirosis researchers.

Leptospirosis affects numerous animal species, including domestic dogs, but documented transmission to humans is rare. Here, we describe epidemiologically linked cases in a 12-year-old Minnesota boy and his pet dog. While human leptospirosis is often thought of as a disease of tropical locations, this case report describes a rare documented example of local transmission in the northern United States, a region historically not perceived to be at high risk of Leptospira species transmission to humans. This case highlights an unusual presentation, with facial nerve palsy, underappreciated epidemiological risks, and diagnostic challenges of this reemerging infection.

BACKGROUND: Leptospirosis is an important zoonotic infection worldwide. Diagnosis of leptospirosis is challenging given its nonspecific clinical symptoms that overlap with other acute febrile illnesses and limitations with conventional diagnostic testing. Alternative advanced diagnostics, such as microbial cell-free DNA (mcfDNA), are increasingly being used to aid in the diagnosis of infections and can be applied to pathogens with public health importance such as Leptospira, a nationally notifiable disease. METHODS: The Karius Test uses plasma mcfDNA sequencing to detect and quantify DNA-based pathogens. This test offered through the Karius lab detected 4 cases of Leptospira santarosai during a 5-month period across the United States in 2021 and were clinically reviewed. RESULTS: In our case series, 4 adolescents with recent travel to Central America (Costa Rica, n = 3 and Belize, n = 1) from April to August 2021 were diagnosed with leptospirosis. While a large workup was performed in all cases, mcfDNA testing was the first test to detect L. santarosai as the microbiological diagnosis in all cases. CONCLUSIONS: Results of the Karius Test enabled rapid, noninvasive diagnosis of leptospirosis allowing for targeted therapy. Use of mcfDNA can be utilized for diagnosis of pathogens where conventional testing is challenging or limited. This in turn can enable quick diagnosis for targeted treatment and potentially aid in supporting case definitions of reportable diseases of public health concern.

BACKGROUND: Leptospirosis is suspected to be a major cause of illness in rural Tanzania associated with close contact with livestock. We sought to determine leptospirosis prevalence, identify infecting Leptospira serogroups, and investigate risk factors for leptospirosis in a rural area of Tanzania where pastoralist animal husbandry practices and sustained livestock contact are common. METHODS: We enrolled participants at Endulen Hospital, Tanzania. Patients with a history of fever within 72 hours, or a tympanic temperature of ≥38.0°C were eligible. Serum samples were collected at presentation and 4-6 weeks later. Sera were tested using microscopic agglutination testing with 20 Leptospira serovars from 17 serogroups. Acute leptospirosis cases were defined by a ≥four-fold rise in antibody titre between acute and convalescent serum samples or a reciprocal titre ≥400 in either sample. Leptospira seropositivity was defined by a single reciprocal antibody titre ≥100 in either sample. We defined the predominant reactive serogroup as that with the highest titre. We explored risk factors for acute leptospirosis and Leptospira seropositivity using logistic regression modelling. RESULTS: Of 229 participants, 99 (43.2%) were male and the median (range) age was 27 (0, 78) years. Participation in at least one animal husbandry practice was reported by 160 (69.9%). We identified 18 (7.9%) cases of acute leptospirosis, with Djasiman 8 (44.4%) and Australis 7 (38.9%) the most common predominant reactive serogroups. Overall, 69 (31.1%) participants were Leptospira seropositive and the most common predominant reactive serogroups were Icterohaemorrhagiae (n = 21, 30.0%), Djasiman (n = 19, 27.1%), and Australis (n = 17, 24.3%). Milking cattle (OR 6.27, 95% CI 2.24-7.52) was a risk factor for acute leptospirosis, and milking goats (OR 2.35, 95% CI 1.07-5.16) was a risk factor for Leptospira seropositivity. CONCLUSIONS: We identified leptospirosis in approximately one in twelve patients attending hospital with fever from this rural community. Interventions that reduce risks associated with milking livestock may reduce human infections.

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

BACKGROUND: In 2015, the World Health Organization recommended that all people living with HIV begin antiretroviral treatment (ART) regardless of immune status, a policy known as 'Treat-All to end AIDS', commonly referred to as Treat-All. Almost all low- and middle-income countries adopted this policy by 2019. This study describes how linkage to treatment of newly diagnosed persons changed between 2015 and 2018 and how complementary policies may have similarly increased linkage for 13 African countries. These countries adopted and implemented Treat-All policies between 2015 and 2018 and were supported by the U.S. Government's President's Emergency Plan for AIDS Relief (PEPFAR). The focuses of this research were to understand 1) linkage rates to ART initiation before and after the adoption of Treat-All in each country; 2) how Treat-All implementation differed across these countries; and 3) whether complementary policies (including same-day treatment initiation, task-shifting, reduced ART visits, and reduced ART pickups) implemented around the same time may have increased ART linkage. METHODS: HIV testing and treatment data were collected by PEPFAR country programs in 13 African countries from 2015 to 2018. These countries were chosen based on the completeness of policy data and availability of program data during the study period. Program data were used to calculate proxy linkage rates. These rates were compared relative to the Treat All adoption period and the adoption of complementary policies. RESULTS: The 13 countries experienced an average increase in ART linkage of 29.3% over the entire study period. In examining individual countries, all but two showed increases in linkage to treatment immediately after Treat All adoption. Across all countries, those that had adopted four or more complementary policies showed an average increased linkage of 39.8% compared to 13.9% in countries with fewer than four complementary policies. CONCLUSIONS: Eleven of 13 country programs examined in this study demonstrated an increase in ART linkage after Treat-All policy adoption. Increases in linkage were associated with complementary policies. When exploring new public health policies, policymakers may consider which complementary policies might also help achieve the desired outcome of the public health policy.

Leptospirosis, the most widespread zoonotic disease in the world, is broadly understudied in multi-host wildlife systems. Knowledge gaps regarding Leptospira circulation in wildlife, particularly in densely populated areas, contribute to frequent misdiagnoses in humans and domestic animals. We assessed Leptospira prevalence levels and risk factors in five target wildlife species across the greater Los Angeles region: striped skunks (Mephitis mephitis), raccoons (Procyon lotor), coyotes (Canis latrans), Virginia opossums (Didelphis virginiana), and fox squirrels (Sciurus niger). We sampled more than 960 individual animals, including over 700 from target species in the greater Los Angeles region, and an additional 266 sampled opportunistically from other California regions and species. In the five target species seroprevalences ranged from 5 to 60%, and infection prevalences ranged from 0.8 to 15.2% in all except fox squirrels (0%). Leptospira phylogenomics and patterns of serologic reactivity suggest that mainland terrestrial wildlife, particularly mesocarnivores, could be the source of repeated observed introductions of Leptospira into local marine and island ecosystems. Overall, we found evidence of widespread Leptospira exposure in wildlife across Los Angeles and surrounding regions. This indicates exposure risk for humans and domestic animals and highlights that this pathogen can circulate endemically in many wildlife species even in densely populated urban areas.

OBJECTIVES: To measure the effectiveness of chlamydia control strategies, we must estimate infection incidence over time. Available data, including survey-based infection prevalence and case reports, have limitations as proxies for infection incidence. We therefore developed a novel method for estimating chlamydial incidence. METHODS: We linked a susceptible infectious mathematical model to serodynamics data from the National Health and Nutritional Examination Survey, as well as to annual case reports. We created four iterations of this model, varying assumptions about how the method of infection clearance (via treatment seeking, routine screening or natural clearance) relates to long-term seropositivity. Using these models, we estimated annual infection incidence for women aged 18-24 and 25-37 years in 2014. To assess model plausibility, we also estimated natural clearance for the same groups. RESULTS: Of the four models we analysed, the model that best explained the empirical data was the one in which longer-lasting infections, natural clearance and symptomatic infections all increased the probability of long-term seroconversion. Using this model, we estimated 5910 (quartile (Q)1, 5330; Q3, 6500) incident infections per 100 000 women aged 18-24 years and 2790 (Q1, 2500; Q3, 3090) incident infections per 100 000 women aged 25-37 years in 2014. Furthermore, we estimated that natural clearance rates increased with age. CONCLUSIONS: Our method can be used to estimate the number of chlamydia infections each year, and thus whether infection incidence increases or decreases over time and after policy changes. Furthermore, our results suggest that clearance via medical intervention may lead to short-term or no seroconversion, and the duration of untreated chlamydial infection may vary with age, underlining the complexity of chlamydial infection dynamics.

Studies of infectious disease ecology would benefit greatly from knowing when individuals were infected, but estimating this time of infection can be challenging, especially in wildlife. Time of infection can be estimated from various types of data, with antibody-level data being one of the most promising sources of information. The use of antibody levels to back-calculate infection time requires the development of a host-pathogen system-specific model of antibody dynamics, and a leading challenge in such quantitative serology approaches is how to model antibody dynamics in the absence of experimental infection data. We present a way to model antibody dynamics in a Bayesian framework that facilitates the incorporation of all available information about potential infection times and apply the model to estimate infection times of Channel Island foxes infected with Leptospira interrogans. Using simulated data, we show that the approach works well across a broad range of parameter settings and can lead to major improvements in infection time estimates that depend on system characteristics such as antibody decay rate and variation in peak antibody levels after exposure. When applied to field data we saw reductions up to 83% in the window of possible infection times. The method substantially simplifies the challenge of modelling antibody dynamics in the absence of individuals with known infection times, opens up new opportunities in wildlife disease ecology and can even be applied to cross-sectional data once the model is trained. © 2023 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Background Information on the etiology and age-specific burden of respiratory viral infections among school-aged children remains limited.Methods We conducted a cohort study to determine the etiology of ILI (influenza like illness) among 2,519 K–12 students during the 2012–13 influenza season. We obtained nasal swabs from students with ILI-related absences. Generalized linear mixed-effect regressions determined associations of outcomes, including ILI and laboratory-confirmed respiratory virus infection, with school grade and other covariates.Results Overall, 459 swabs were obtained from 552 ILI–related absences. Respiratory viruses were found in 292 (63.6%) samples. Influenza was found in 189 (41.2%) samples. with influenza B found in 134 (70.9%). Rates of influenza B were significantly higher in grades 1 (10.1%, 95% CI 6.8%–14.4%), 2 (9.7%, 6.6%–13.6%), 3 (9.3%, 6.3%–13.2%), and 4 (9.9%, 6.8%–13.8%) than in kindergarteners (3.2%, 1.5%–6.0%). After accounting for grade, sex and self-reported vaccination status, influenza B infection risk was lower among kindergarteners in half-day programs compared to kindergarteners in full-day programs (OR = 0.19; 95% CI 0.08–0.45).Conclusions ILI and influenza infection is concentrated in younger schoolchildren. Reduced infection by respiratory viruses is associated with a truncated school day for kindergarteners, but requires further investigation in other grades and populations.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis work was supported by Cooperative Agreement number [1U01CK00179] from the US Centers for Disease Control and Prevention (CDC, www.cdc.gov). The findings and conclusions in this study are solely the responsibility of the authors and do not necessarily represent the official position of CDC. JMR acknowledges additional support from the Engineering and Physical Sciences Research Council (EP/N014499/1).Author DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll 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.YesData for reproduction of major results and figures is made available through the DRYAD archive.

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.

Confronted with the challenge of understanding population-level processes, disease ecologists and epidemiologists often simplify quantitative data into distinct physiological states (e.g. susceptible, exposed, infected, recovered). However, data defining these states often fall along a spectrum rather than into clear categories. Hence, the host-pathogen relationship is more accurately defined using quantitative data, often integrating multiple diagnostic measures, just as clinicians do to assess their patients. We use quantitative data on a bacterial infection (Leptospira interrogans) in California sea lions (Zalophus californianus) to improve both our individual-level and population-level understanding of this host-pathogen system. We create a “host-pathogen space” by mapping multiple biomarkers of infection (e.g. serum antibodies, pathogen DNA) and disease state (e.g. serum chemistry values) from 13 longitudinally sampled, severely ill individuals to visualize and characterize changes in these values through time. We describe a clear, unidirectional trajectory of disease and recovery within this host-pathogen space. Remarkably, this trajectory also captures the broad patterns in larger cross-sectional datasets of 1456 wild sea lions in all states of health. This mapping framework enables us to determine an individual’s location in their time-course since initial infection, and to visualize the full range of clinical states and antibody responses induced by pathogen exposure, including severe acute disease, chronic subclinical infection, and recovery. We identify predictive relationships between biomarkers and outcomes such as survival and pathogen shedding, and in certain cases we can impute values for missing data, thus increasing the size of the useable dataset. Mapping the host-pathogen space and using quantitative biomarker data provides more nuanced approaches for understanding and modeling disease dynamics in a system, yielding benefits for the clinician who needs to triage patients and prevent transmission, and for the disease ecologist or epidemiologist wishing to develop appropriate risk management strategies and assess health impacts on a population scale.Author Summary A pathogen can cause a range of disease severity across different host individuals, and these presentations change over the time-course from infection to recovery. These facts complicate the work of epidemiologists and disease ecologists seeking to understand the factors governing disease spread, often working with cross-sectional data. Recognizing these facts also highlights the shortcomings of classical approaches to modeling infectious disease, which typically rely on discrete and well-defined disease states. Here we show that by analyzing multiple biomarkers of health and infection simultaneously, treating these values as quantitative rather than binary indicators, and including a modest amount of longitudinal sampling of hosts, we can create a map of the host-pathogen interaction that shows the full spectrum of disease presentations and opens doors for new insights and predictions. By accounting for individual variation and capturing changes through time since infection, this mapping framework enables more robust interpretation of cross-sectional data; e.g., to detect predictive relationships between biomarkers and key outcomes such as survival, or to assess whether observed disease is associated with the pathogen of interest. This approach can help epidemiologists, ecologists and clinicians to better study and manage the many infectious diseases that exhibit complex relationships with their hosts.

Leptospirosis is the most widespread zoonotic disease in the world, yet it is broadly understudied in multi-host wildlife systems. Knowledge gaps regarding Leptospira circulation in wildlife, particularly in densely populated areas, contribute to frequent misdiagnoses in humans and domestic animals. We assessed Leptospira prevalence levels and risk factors in five target wildlife species across the greater Los Angeles region: striped skunks (Mephitis mephitis), Northern raccoons (Procyon lotor), coyotes (Canis latrans), Virginia opossums (Didelphis virginiana), and fox squirrels (Sciurus niger). We sampled more than 960 individual animals, including over 700 from target species in the greater Los Angeles region, and an additional 260 sampled opportunistically from other regions and species. In the five target species, seroprevalences ranged from 5-60% and active infection prevalences ranged from 0.8-15.2% in all except fox squirrels (0%). Patterns of serologic reactivity suggest that mainland terrestrial wildlife, particularly mesocarnivores, could be the source of repeated observed introductions of Leptospira into local marine and island ecosystems. Overall, we found evidence of widespread Leptospira exposure in wildlife across Los Angeles and surrounding regions. This indicates exposure risk for humans and domestic animals and highlights that this pathogen can circulate endemically in many wildlife species even in densely populated urban areas. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

Studies of infectious disease ecology often rely heavily on knowing when individuals were infected, but estimating this time of infection can be challenging, especially in wildlife. Time of infection can be estimated from various types of data, with antibody level data being one of the most promising sources of information. The use of antibody levels to back-calculate infection time requires the development of a host-pathogen system-specific model of antibody dynamics, and a leading challenge in such quantitative serology approaches is how to model antibody dynamics in the absence of experimental infection data. Here, we present a way to do this in a Bayesian framework that facilitates the incorporation of all available information about potential infection times. We apply the model to estimate infection times of Channel Island foxes infected with Leptospira interrogans, leading to reductions of 51-92% in the window of possible infection times. Using simulated data, we show that the approach works well across a broad range of parameter settings and can lead to major improvements of infection time estimates that depend on system characteristics such as antibody decay rate and variation in peak antibody levels after exposure. The method substantially simplifies the challenge of modeling antibody dynamics in the absence of individuals with known infection times, opens up new opportunities in wildlife disease ecology, and can even be applied to cross-sectional data once the model is trained. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Background: Leptospirosis, caused by Leptospira bacteria, is a common zoonosis worldwide more prevalent in the tropics. Reservoir species and risk factors have been identified but surveys for environmental sources of leptospirosis are rare. Furthermore, understanding of environmental Leptospira containing pathogenic genes and possibly capable of causing disease is incomplete and could result in some pathogenic strains evading detection, thereby convoluting diagnosis, prevention, and epidemiology. Methodology/Principal Findings: We collected environmental samples from 22 sites in Puerto Rico during three sampling periods over 14-months (Dec 2018-Feb 2020); 10 water and 10 soil samples were collected at each site. Samples were screened for pathogenic Leptospira DNA using the lipL32 PCR assay and positive samples were sequenced to assess genetic diversity. One urban site in San Juan was sampled three times over 14 months to assess persistence in soil; live leptospires were obtained during the last sampling period. Isolates were whole genome sequenced and LipL32 expression was assessed in vitro. We detected pathogenic Leptospira DNA at 15/22 sites; both soil and water were positive at 5/15 sites. We recovered lipL32 sequences from 83/86 positive samples (15/15 positive sites) and secY sequences from 32/86 (10/15 sites); multiple genotypes were identified at 12 sites. These sequences revealed significant diversity across samples, including four novel lipL32 phylogenetic clades. Most samples from the serially sampled site were lipL32 positive at each time point. We sequenced the genomes of six saprophytic and two pathogenic Leptospira isolates; the latter represent a novel pathogenic Leptospira species likely belonging to a new serogroup. Conclusions/Significance: Diverse and novel pathogenic Leptospira are widespread in the environment in Puerto Rico. The disease potential of the novel lineages is unknown but several persisted for >1 year in soil, which could contaminate water. This work increases understanding of environmental Leptospira and should improve leptospirosis surveillance and diagnostics. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

Gender-based violence (GBV) is a complex issue deeply rooted in social structures, making its eradication challenging. GBV increases the risk of HIV transmission and is a barrier to HIV testing, care, and treatment. Quality clinical services for GBV, which includes the provision of HIV postexposure prophylaxis (PEP), vary, and service delivery data are lacking. We describe GBV clinical service delivery in 15 countries supported by the President's Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Centers for Disease Control and Prevention. Through a descriptive statistical analysis of PEPFAR Monitoring, Evaluation, and Reporting (MER) data, we found a 252% increase in individuals receiving GBV clinical services, from 158,691 in 2017 to 558,251 in 2021. PEP completion was lowest (15%) among 15-19-year-olds. Understanding GBV service delivery is important for policy makers, program managers, and providers to guide interventions to improve the quality of service delivery and contribute to HIV epidemic control.

Objectives. To identify promising practices for implementing COVID-19 vaccination sites. Methods. The Centers for Disease Control and Prevention (CDC) and Federal Emergency Management Agency (FEMA) assessed high-throughput COVID-19 vaccination sites across the United States, including Puerto Rico, after COVID-19 vaccinations began. Site assessors conducted site observations and interviews with site staff. Qualitative data were compiled and thematically analyzed. Results. CDC and FEMA conducted 134 assessments of high-throughput vaccination sites in 25 states and Puerto Rico from February 12 to May 28, 2021. Promising practices were identified across facility, clinical, and cross-cutting operational areas and related to 6 main themes: addressing health equity, leveraging partnerships, optimizing site design and flow, communicating through visual cues, using quick response codes, and prioritizing risk management and quality control. Conclusions. These practices might help planning and implementation of future vaccination operations for COVID-19, influenza, and other vaccine-preventable diseases. Public Health Implications. These practices can be considered by vaccination planners and providers to strengthen their vaccination site plans and implementation of future high-throughput vaccination sites. (Am J Public Health. 2023;113(8):909-918. https://doi.org/10.2105/AJPH.2023.307331).

BACKGROUND: Historically, malaria has been the predominant cause of acute febrile illness (AFI) in sub-Saharan Africa. However, during the last two decades, malaria incidence has declined due to concerted public health control efforts, including the widespread use of rapid diagnostic tests leading to increased recognition of non-malarial AFI etiologies. Our understanding of non-malarial AFI is limited due to lack of laboratory diagnostic capacity. We aimed to determine the etiology of AFI in three distinct regions of Uganda. METHODS: A prospective clinic-based study that enrolled participants from April 2011 to January 2013 using standard diagnostic tests. Participant recruitment was from St. Paul's Health Centre (HC) IV, Ndejje HC IV, and Adumi HC IV in the western, central and northern regions, which differ by climate, environment, and population density. A Pearson's chi-square test was used to evaluate categorical variables, while a two-sample t-test and Krukalis-Wallis test were used for continuous variables. RESULTS: Of the 1281 participants, 450 (35.1%), 382 (29.8%), and 449 (35.1%) were recruited from the western, central, and northern regions, respectively. The median age (range) was 18 (2-93) years; 717 (56%) of the participants were female. At least one AFI pathogen was identified in 1054 (82.3%) participants; one or more non-malarial AFI pathogens were identified in 894 (69.8%) participants. The non-malarial AFI pathogens identified were chikungunya virus, 716 (55.9%); Spotted Fever Group rickettsia (SFGR), 336 (26.2%) and Typhus Group rickettsia (TGR), 97 (7.6%); typhoid fever (TF), 74 (5.8%); West Nile virus, 7 (0.5%); dengue virus, 10 (0.8%) and leptospirosis, 2 (0.2%) cases. No cases of brucellosis were identified. Malaria was diagnosed either concurrently or alone in 404 (31.5%) and 160 (12.5%) participants, respectively. In 227 (17.7%) participants, no cause of infection was identified. There were statistically significant differences in the occurrence and distribution of TF, TGR and SFGR, with TF and TGR observed more frequently in the western region (p = 0.001; p < 0.001) while SFGR in the northern region (p < 0.001). CONCLUSION: Malaria, arboviral infections, and rickettsioses are major causes of AFI in Uganda. Development of a Multiplexed Point-of-Care test would help identify the etiology of non-malarial AFI in regions with high AFI rates.

Because they are difficult to culture, obtaining genomic information from Leptospira spp. is challenging, hindering the overall understanding of leptospirosis. We designed and validated a culture-independent DNA capture and enrichment system for obtaining Leptospira genomic information from complex human and animal samples. It can be utilized with a variety of complex sample types and diverse species as it was designed using the pan-genome of all known pathogenic Leptospira spp. This system significantly increases the proportion of Leptospira DNA contained within DNA extracts obtained from complex samples, oftentimes reaching >95% even when some estimated starting proportions were <1%. Sequencing enriched extracts results in genomic coverage similar to sequenced isolates, thereby enabling enriched complex extracts to be analyzed together with whole genome sequences from isolates, which facilitates robust species identification and high-resolution genotyping. The system is flexible and can be readily updated when new genomic information becomes available. Implementation of this DNA capture and enrichment system will improve efforts to obtain genomic data from unculturable Leptospira-positive human and animal samples. This, in turn, will lead to a better understanding of the overall genomic diversity and gene content of Leptospira spp. that cause leptospirosis, aiding epidemiology and the development of improved diagnostics and vaccines.

This study examines the extent to which data linkages between Indian Health Service, tribal data, and cancer registries affect cancer incidence rates among American Indians/Alaska Natives (AI/ANs) in Michigan. The incidence of tobacco- and alcohol-associated cancers for 1995-2012 was analyzed to compare rates of the Upper Peninsula (UP) and Lower Peninsula (LP) in Michigan and among AI/ANs and non-Hispanic Whites (NHWs). Complete linkage resulted in 1,352 additional AI/AN cases; 141 cases were linked via IHS records alone, while 373 were linked via tribal records alone; 838 were linked through both IHS and tribal records. Age-adjusted incidence rates for AI/ANs increased from 214.39 per 100,000 to 405.41 per 100,000, similar to that of NHWs after complete linkage (421.46 per 100,000). In the UP, AI/ANs had age-adjusted incidence rates 1.67 times higher than NHWs (596.69 per 100,000 vs. 356.32 per 100,000 respectively). This study indicates a substantial number of AI/AN cancer cases remain misclassified in Michigan.

The report “Genomic Surveillance for SARS-CoV-2 Variants: Predominance of the Delta (B.1.617.2) and Omicron (B.1.1.529) Variants — United States, June 2021–January 2022” contained several errors.

Mpox vaccination is recommended for persons exposed to or at risk for mpox. About 25% of an online sample of MSM with presumed mpox exposure were vaccinated (≥1 dose). Vaccination was higher among younger MSM and MSM concerned about mpox or reporting sexual risk behaviors. Incorporating mpox vaccination into routine sexual health care and increasing 2-dose vaccination uptake is essential to preventing mpox acquisition, improving MSM sexual health, and averting future mpox outbreaks.

Breakup (dispersion) and distribution of nanoparticles are the chief hurdles towards taking advantage of nanoparticles in polymer nanocomposites for reinforcement, flame retardancy, conductivity, chromaticity, and other properties. Microscopy is often used to quantify mixing, but it has a limited field of view, does not average over bulk samples, and fails to address nano-particle hierarchical structures. Ultra-small-angle X-ray scattering (USAXS) can provide a macroscopic statistical average of nanoscale dispersion (breakup) and emergent hierarchical structure, as well as the distribution on the nanoscale. This work compares several common mixer geometries for carbon black-polystyrene nanocomposites. Two twin-screw extruder geometries, typical for industrial processing of melt blends, are compared with a laboratory-scale single screw extruder and a Banbury mixer. It is found that for a given mixer, nanoscale distribution increases following a van der Waals function using accumulated strain as an analogue for temperature while macroscopic distribution/dispersion, using microscopy, does not follow this dependency. Breakup and aggregation in dispersive mixing follow expected behavior on the nanoscale. Across these drastically different mixing geometries an unexpected dependency is observed for nanoscale distributive mixing (both nano and macroscopic) as a function of accumulated strain that may reflect a transition from distributive turbulent to dispersive laminar mixing as the mixing gap is reduced. © 2023 Elsevier Ltd