BACKGROUND: Serology (the detection of antibodies formed by the host against an infecting pathogen) is frequently used to assess current infections and past exposure to specific pathogens. However, the presence of cross-reactivity among host antibodies in serological data makes it challenging to interpret the patterns and draw reliable conclusions about the infecting pathogen or strain. METHODOLOGY/PRINCIPAL FINDINGS: In our study, we use microscopic agglutination test (MAT) serological data from three host species [California sea lion (Zalophus californianus), island fox (Urocyon littoralis), and island spotted skunk (Spilogale gracilis)] with confirmed infections to assess differences in cross-reactivity by host species and diagnostic laboratory. All host species are known to be infected with the same serovar of Leptospira interrogans. We find that absolute and relative antibody titer magnitudes vary systematically across host species and diagnostic laboratories. Despite being infected by the same Leptospira serovar, three host species exhibit different cross-reactivity profiles to a 5-serovar diagnostic panel. We also observe that the cross-reactive antibody titer against a non-infecting serovar can remain detectable after the antibody titer against the infecting serovar declines below detectable levels. CONCLUSIONS/SIGNIFICANCE: Cross-reactivity in serological data makes interpretation difficult and can lead to common pitfalls. Our results show that the highest antibody titer is not a reliable indicator of infecting serovar and highlight an intriguing role of host species in shaping reactivity patterns. On the other side, seronegativity against a given serovar does not rule out that serovar as the cause of infection. We show that titer magnitudes can be influenced by both host species and diagnostic laboratory, indicating that efforts to interpret absolute titers (e.g., as indicators of recent infection) must be calibrated to the system under study. Thus, we implore scientists and health officials using serological data for surveillance to interpret the data with caution.

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.

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.

On July 2, 2021, MMWR published “Symptoms of Depression, Anxiety, Post-Traumatic Stress Disorder, and Suicidal Ideation Among State, Tribal, Local, and Territorial Public Health Workers During the COVID-19 Pandemic — United States, March–April 2021” (1). On October 12, 2021, the authors informed MMWR that some data were inaccurate because 420 incomplete participant responses were incorrectly assigned scores for depression. This error resulted in a change in overall depression prevalence from 32.0% to 30.8%, and other similar changes in stratified prevalences of depression, prevalence ratios of depression, and the overall proportion of respondents who reported at least one mental health condition. The authors have corrected the MMWR report by excluding the 420 records from the depression analysis and confirmed that the interpretation and the conclusions of the original report were not affected by these corrections. MMWR has republished the report (2), which includes the original report with clearly marked corrections in supplementary materials.

New developments in the treatment and management of phenylketonuria (PKU) as well as advances in molecular testing have emerged since the National Institutes of Health 2000 PKU Consensus Statement was released. An NIH State-of-the-Science Conference was convened in 2012 to address new findings, particularly the use of the medication sapropterin to treat some individuals with PKU, and to develop a research agenda. Prior to the 2012 conference, five working groups of experts and public members met over a 1-year period. The working groups addressed the following: long-term outcomes and management across the lifespan; PKU and pregnancy; diet control and management; pharmacologic interventions; and molecular testing, new technologies, and epidemiologic considerations. In a parallel and independent activity, an Evidence-based Practice Center supported by the Agency for Healthcare Research and Quality conducted a systematic review of adjuvant treatments for PKU; its conclusions were presented at the conference. The conference included the findings of the working groups, panel discussions from industry and international perspectives, and presentations on topics such as emerging treatments for PKU, transitioning to adult care, and the U.S. Food and Drug Administration regulatory perspective. Over 85 experts participated in the conference through information gathering and/or as presenters during the conference, and they reached several important conclusions. The most serious neurological impairments in PKU are preventable with current dietary treatment approaches. However, a variety of more subtle physical, cognitive, and behavioral consequences of even well-controlled PKU are now recognized. The best outcomes in maternal PKU occur when blood phenylalanine (Phe) concentrations are maintained between 120 and 360 μmol/L before and during pregnancy. The dietary management treatment goal for individuals with PKU is a blood Phe concentration between 120 and 360 μmol/L. The use of genotype information in the newborn period may yield valuable insights about the severity of the condition for infants diagnosed before maximal Phe levels are achieved. While emerging and established genotype-phenotype correlations may transform our understanding of PKU, establishing correlations with intellectual outcomes is more challenging. Regarding the use of sapropterin in PKU, there are significant gaps in predicting response to treatment; at least half of those with PKU will have either minimal or no response. A coordinated approach to PKU treatment improves long-term outcomes for those with PKU and facilitates the conduct of research to improve diagnosis and treatment. New drugs that are safe, efficacious, and impact a larger proportion of individuals with PKU are needed. However, it is imperative that treatment guidelines and the decision processes for determining access to treatments be tied to a solid evidence base with rigorous standards for robust and consistent data collection. The process that preceded the PKU State-of-the-Science Conference, the conference itself, and the identification of a research agenda have facilitated the development of clinical practice guidelines by professional organizations and serve as a model for other inborn errors of metabolism.

BACKGROUND: Housing is a major social determinant of health that affects health status and outcomes across the lifespan. OBJECTIVES: An interagency portfolio analysis assessed the level of funding invested in "health and housing research" from fiscal years (FY) 2016-2020 across the National Institutes of Health (NIH), the United States Department of Housing and Urban Development (HUD), and the Centers for Disease Control and Prevention (CDC) to characterize the existing health and housing portfolio and identify potential areas for additional research and collaboration. METHODS/RESULTS: We identified NIH, HUD, and CDC research projects that were relevant to both health and housing and characterized them by housing theme, health topic, population, and study design. We organized the assessment of the individual housing themes by four overarching housing-to-health pathways. From FY 2016-2020, NIH, HUD, and CDC funded 565 health and housing projects combined. The Neighborhood pathway was most common, followed by studies of the Safety and Quality pathway. Studies of the Affordability and Stability pathways were least common. Health topics such as substance use, mental health, and cardiovascular disease were most often studied. Most studies were observational (66%); only a little over one fourth (27%) were intervention studies. DISCUSSION: This review of the research grant portfolios of three major federal funders of health and housing research in the United States describes the diversity and substantial investment in research at the intersection between housing and health. Analysis of the combined portfolio points to gaps in studies on causal pathways linking housing to health outcomes. The findings highlight the need for research to better understand the causal pathways from housing to health and prevention intervention research, including rigorous evaluation of housing interventions and policies to improve health and well-being.

IMPORTANCE: Preterm birth is a leading cause of preventable neonatal morbidity and mortality. Preterm birth rates at the national level may mask important geographic variation in rates and trends at the county level. OBJECTIVE: To estimate age-standardized preterm birth rates by US county from 2007 to 2019. DESIGN, SETTING, AND PARTICIPANTS: This serial cross-sectional study used data from the National Center for Health Statistics composed of all live births in the US between 2007 and 2019. Data analyses were performed between March 22, 2022, and September 29, 2022. MAIN OUTCOMES AND MEASURES: Age-standardized preterm birth (<37 weeks' gestation) and secondarily early preterm birth (<34 weeks' gestation) rates by county and year calculated with a validated small area estimation model (hierarchical bayesian spatiotemporal model) and percent change in preterm birth rates using log-linear regression models. RESULTS: Between 2007 and 2019, there were 51 044 482 live births in 2383 counties. In 2007, the national age-standardized preterm birth rate was 12.6 (95% CI, 12.6-12.7) per 100 live births. Preterm birth rates varied significantly among counties, with an absolute difference between the 90th and 10th percentile counties of 6.4 (95% CI, 6.2-6.7). The gap between the highest and lowest counties for preterm births was 20.7 per 100 live births in 2007. Several counties in the Southeast consistently had the highest preterm birth rates compared with counties in California and New England, which had the lowest preterm birth rates. Although there was no statistically significant change in preterm birth rates between 2007 and 2019 at the national level (percent change, -5.0%; 95% CI, -10.7% to 0.9%), increases occurred in 15.4% (95% CI, 14.1%-16.9%) of counties. The absolute and relative geographic inequalities were similar across all maternal age groups. Higher quartile of the Social Vulnerability Index was associated with higher preterm birth rates (quartile 4 vs quartile 1 risk ratio, 1.34; 95% CI, 1.31-1.36), which persisted across the study period. Similar patterns were observed for early preterm birth rates. CONCLUSIONS AND RELEVANCE: In this serial cross-sectional study of county-level preterm and early preterm birth rates, substantial geographic disparities were observed, which were associated with place-based social disadvantage. Stability in aggregated rates of preterm birth at the national level masked increases in nearly 1 in 6 counties between 2007 and 2019.

Objective: Age is the strongest contributor to 10-year predicted atherosclerotic cardiovascular disease (ASCVD) risk. Some older adults have a predicted ASCVD risk ≥7.5 %, without established risk factors. We sought to compare ASCVD incidence among adults with predicted ASCVD risk ≥7.5 %, with and without established ASCVD risk factors, to adults with predicted risk <7.5 %. Methods: We analyzed data from REasons for Geographic and Racial Differences in Stroke study participants, 45–79 years old, without ASCVD or diabetes, not taking statins and with low-density lipoprotein cholesterol 70–189 mg/dL. Participants were categorized into 3 groups based on their 10-year predicted ASCVD risk and presence of established risk factors: <7.5 %, ≥7.5 % with established risk factors and ≥7.5 % without established risk factors. Established risk factors included smoking, systolic blood pressure ≥130 mmHg or antihypertensive medication use, total cholesterol ≥200 mg/dL, or high-density lipoprotein cholesterol <50 mg/dL for women (<40 mg/dL for men). Participants were followed for ASCVD events. Results: Among 11,115 participants, 911 incident ASCVD events occurred over a median of 11.1 years. ASCVD incidence rates were 3.6, 12.8, and 9.8 per 1,000 person-years for participants with predicted risk <7.5 %, predicted risk ≥7.5 % with established risk factors and predicted risk ≥7.5 % without established risk factors, respectively. Compared to adults with predicted risk <7.5 %, hazard ratios for incident ASCVD in participants with risk ≥7.5 % with and without established risk factors were 3.58 (95 %CI 3.03 – 4.21) and 2.72 (95 %CI 1.91–3.88), respectively. Conclusions: Adults with a 10-year predicted ASCVD risk ≥7.5 % but without established risk factors had a high ASCVD incidence. © 2023

In early 2022, a cluster of monkeypox virus (MPXV) infection (mpox) cases were identified within the UK with no prior travel history to MPXV-endemic regions. Subsequently, case numbers exceeding 80,000 were reported worldwide, primarily affecting gay, bisexual, and other men who have sex with men (GBMSM). Public health agencies worldwide have offered the IMVANEX Smallpox vaccination to these individuals at high-risk to provide protection and limit the spread of MPXV. We have developed a comprehensive array of ELISAs to study poxvirus-induced antibodies, utilising 24 MPXV and 3 Vaccinia virus (VACV) recombinant antigens. Panels of serum samples from individuals with differing Smallpox-vaccine doses and those with prior MPXV infection were tested on these assays, where we observed that one dose of Smallpox vaccination induces a low number of antibodies to a limited number of MPXV antigens but increasing with further vaccination doses. MPXV infection induced similar antibody responses to diverse poxvirus antigens observed in Smallpox-vaccinated individuals. We identify MPXV A27 as a serological marker of MPXV-infection, whilst MPXV M1 (VACV L1) is likely IMVANEX-specific. Here, we demonstrate analogous humoral antigen recognition between both MPXV-infected or Smallpox-vaccinated individuals, with binding to diverse yet core set of poxvirus antigens, providing opportunities for future vaccine (e.g., mRNA) and therapeutic (e.g., mAbs) design.

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.

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.

This study describes the evolution of knockdown resistance (kdr) haplotypes in Aedes aegypti in response to pyrethroid insecticide use over the course of 18 years in Iquitos, Peru. Based on the duration and intensiveness of sampling (∼10,000 samples), this is the most thorough study of kdr population genetics in Ae. aegypti to date within a city. We provide evidence for the direct connection between programmatic citywide pyrethroid spraying and the increase in frequency of specific kdr haplotypes by identifying two evolutionary events in the population. The relatively high selection coefficients, even under infrequent insecticide pressure, emphasizes how quickly populations can evolve. The observed rapid increase in frequency of resistance alleles might have been aided by the incomplete dominance of resistance-conferring alleles over corresponding susceptibility alleles. In addition to dramatic temporal shifts, spatial suppression experiments reveal that genetic heterogeneity existed not only at the citywide scale, but also on a very fine scale within the city.Competing Interest StatementThe authors have declared no competing interest.

While many transmission models have been developed for community spread of respiratory pathogens, less attention has been given to modeling the interdependence of disease introduction and spread seen in congregate settings, such as prisons or nursing homes. As demonstrated by the explosive outbreaks of COVID-19 seen in congregate settings, the need for effective outbreak prevention and mitigation strategies for these settings is critical. Here we consider how interventions that decrease the size of the susceptible populations, such as vaccination or depopulation, impact the expected number of infections due to outbreaks. Introduction of disease into the resident population from the community is modeled as a branching process, while spread between residents is modeled via a compartmental model. Control is modeled as a proportional decrease in both the number of susceptible residents and the reproduction number. We find that vaccination or depopulation can have a greater than linear effect on anticipated infections. For example, assuming a reproduction number of 3.0 for density-dependent COVID-19 transmission, we find that reducing the size of the susceptible population by 20% reduced overall disease burden by 47%. We highlight the California state prison system as an example for how these findings provide a quantitative framework for implementing infection control in congregate settings. Additional applications of our modeling framework include optimizing the distribution of residents into independent residential units, and comparison of preemptive versus reactive vaccination strategies.

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.

Increases in mental health conditions have been documented among the general population and health care workers since the start of the COVID-19 pandemic (1-3). Public health workers might be at similar risk for negative mental health consequences because of the prolonged demand for responding to the pandemic and for implementing an unprecedented vaccination campaign. The extent of mental health conditions among public health workers during the COVID-19 pandemic, however, is uncertain. A 2014 survey estimated that there were nearly 250,000 state and local public health workers in the United States (4). To evaluate mental health conditions among these workers, a nonprobability-based online survey was conducted during March 29-April 16, 2021, to assess symptoms of depression, anxiety, post-traumatic stress disorder (PTSD), and suicidal ideation among public health workers in state, tribal, local, and territorial public health departments. Among 26,174 respondents, 52.8% reported symptoms of at least one mental health condition in the preceding 2 weeks, including depression (30.8%), anxiety (30.3%), PTSD (36.8%), or suicidal ideation (8.4%). The highest prevalence of symptoms of a mental health condition was among respondents aged ≤29 years (range = 13.6%-47.4%) and transgender or nonbinary persons (i.e., those who identified as neither male nor female) of all ages (range = 30.4%-65.5%). Public health workers who reported being unable to take time off from work were more likely to report adverse mental health symptoms. Severity of symptoms increased with increasing weekly work hours and percentage of work time dedicated to COVID-19 response activities. Implementing prevention and control practices that eliminate, reduce, and manage factors that cause or contribute to public health workers' poor mental health might improve mental health outcomes during emergencies.

A novel human coronavirus, now named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, referred to as HCoV-19 here) that emerged in Wuhan, China in late 2019 is now causing a pandemic1. Here, we analyze the aerosol and surface stability of HCoV-19 and compare it with SARS-CoV-1, the most closely related human coronavirus.2 We evaluated the stability of HCoV-19 and SARS-CoV-1 in aerosols and on different surfaces and estimated their decay rates using a Bayesian regression model (see Supplementary Appendix). All experimental measurements are reported as mean across 3 replicates.

INTRODUCTION: We assessed progress in HIV viral load (VL) scale up across seven sub-Saharan African (SSA) countries and discussed challenges and strategies for improving VL coverage among patients on anti-retroviral therapy (ART). METHODS: A retrospective review of VL testing was conducted in Côte d'Ivoire, Kenya, Lesotho, Malawi, Namibia, Tanzania, and Uganda from January 2016 through June 2018. Data were collected and included the cumulative number of ART patients, number of patients with ≥ 1 VL test result (within the preceding 12 months), the percent of VL test results indicating viral suppression, and the mean turnaround time for VL testing. RESULTS: Between 2016 and 2018, the proportion of PLHIV on ART in all 7 countries increased (range 5.7%-50.2%). During the same time period, the cumulative number of patients with one or more VL test increased from 22,996 to 917,980. Overall, viral suppression rates exceeded 85% for all countries except for Côte d'Ivoire at 78% by June 2018. Reported turnaround times for VL testing results improved in 5 out of 7 countries by between 5.4 days and 27.5 days. CONCLUSIONS: These data demonstrate that remarkable progress has been made in the scale-up of HIV VL testing in the seven SSA countries.

INTRODUCTION: The potential disruption in antiretroviral therapy (ART) services in Africa at the start of the COVID-19 pandemic raised concern for increased morbidity and mortality among people living with HIV (PLHIV). We describe HIV treatment trends before and during the pandemic and interventions implemented to mitigate COVID-19 impact among countries supported by the US Centers for Disease Control and Prevention (CDC) through the President's Emergency Plan for AIDS Relief (PEPFAR). METHODS: We analysed quantitative and qualitative data reported by 10,387 PEPFAR-CDC-supported ART sites in 19 African countries between October 2019 and March 2021. Trends in PLHIV on ART, new ART initiations and treatment interruptions were assessed. Viral load coverage (testing of eligible PLHIV) and viral suppression were calculated at select time points. Qualitative data were analysed to summarize facility- and community-based interventions implemented to mitigate COVID-19. RESULTS: The total number of PLHIV on ART increased quarterly from October 2019 (n = 7,540,592) to March 2021 (n = 8,513,572). The adult population (≥15 years) on ART increased by 14.0% (7,005,959-7,983,793), while the paediatric population (<15 years) on ART declined by 2.6% (333,178-324,441). However, the number of new ART initiations dropped between March 2020 and June 2020 by 23.4% for adults and 26.1% for children, with more rapid recovery in adults than children from September 2020 onwards. Viral load coverage increased slightly from April 2020 to March 2021 (75-78%) and viral load suppression increased from October 2019 to March 2021 (91-94%) among adults and children combined. The most reported interventions included multi-month dispensing (MMD) of ART, community service delivery expansion, and technology and virtual platforms use for client engagement and site-level monitoring. MMD of ≥3 months increased from 52% in October 2019 to 78% of PLHIV ≥ age 15 on ART in March 2021. CONCLUSIONS: With an overall increase in the number of people on ART, HIV programmes proved to be resilient, mitigating the impact of COVID-19. However, the decline in the number of children on ART warrants urgent investigation and interventions to prevent further losses experienced during the COVID-19 pandemic and future public health emergencies.

Aedes aegypti (Linnaeus) is an invasive mosquito species and notable vector of several pathogens in the USA. Their cryptic and anthropophilic nature puts this species in close association with humans, where they can also be a nuisance. Mosquito control programs are the front line of defense for protecting the community from nuisance-biting and disease. However, the occurrence and prevalence of insecticide resistance in mosquitoes is a well-documented phenomenon that directly impacts the efficacy of insecticide applications. In Florida specifically, widespread resistance in Ae. aegypti has created a need for operational strategies that combat and, ideally, reverse resistance. Laboratory studies and the association between fitness costs and insecticide resistance indicate that this reversion is possible under the right conditions. For a 2.5-year period, the impact of varying operational treatment regimens on insecticide resistance in Ae. aegypti is evaluated using kdr genotyping and the CDC bottle bioassay. In an organophosphate treatment area, a decrease in frequency of a double homozygous resistant genotype was observed. CDC bottle bioassays did not reveal any clear trends in the data to indicate a reversion to insecticide susceptibility. However, the changes in genotype could indicate the first step back to insecticide susceptibility. This study provides preliminary data that has implications for resistance management in mosquito control operations. Article Highlights: Presented study represents the first field study to evaluate how changing insecticide pressures on resistant mosquitoes affects insecticide resistance.A decrease in the double homozygous resistance genotype was observed in Ae. aegypti from the organophosphate treatment area after a change in use patterns.Identifiable trends in phenotypic resistance as a result of the treatment regimens were not observed. © 2022, The Author(s).

The explosive outbreaks of COVID-19 seen in congregate settings such as prisons and nursing homes, has highlighted a critical need for effective outbreak prevention and mitigation strategies for these settings. Here we consider how different types of control interventions impact the expected number of symptomatic infections due to outbreaks. Introduction of disease into the resident population from the community is modeled as a stochastic point process coupled to a branching process, while spread between residents is modeled via a deterministic compartmental model that accounts for depletion of susceptible individuals. Control is modeled as a proportional decrease in the number of susceptible residents, the reproduction number, and/or the proportion of symptomatic infections. This permits a range of assumptions about the density dependence of transmission and modes of protection by vaccination, depopulation and other types of control. We find that vaccination or depopulation can have a greater than linear effect on the expected number of cases. For example, assuming a reproduction number of 3.0 with density-dependent transmission, we find that preemptively reducing the size of the susceptible population by 20% reduced overall disease burden by 47%. In some circumstances, it may be possible to reduce the risk and burden of disease outbreaks by optimizing the way a group of residents are apportioned into distinct residential units. The optimal apportionment may be different depending on whether the goal is to reduce the probability of an outbreak occurring, or the expected number of cases from outbreak dynamics. In other circumstances there may be an opportunity to implement reactive disease control measures in which the number of susceptible individuals is rapidly reduced once an outbreak has been detected to occur. Reactive control is most effective when the reproduction number is not too high, and there is minimal delay in implementing control. We highlight the California state prison system as an example for how these findings provide a quantitative framework for understanding disease transmission in congregate settings. Our approach and accompanying interactive website (https://phoebelu.shinyapps.io/DepopulationModels/) provides a quantitative framework to evaluate the potential impact of policy decisions governing infection control in outbreak settings.

The aim of the US Centers for Disease Control and Prevention's (CDC) National Diabetes Prevention Program (National DPP) is to make an evidence-based lifestyle change program widely available to the more than 88 million American adults at risk for developing type 2 diabetes. The National DPP allows for program delivery using four delivery modes: in person, online, distance learning, and combination. The objective of this study was to analyze cumulative enrollment in the National DPP by delivery mode. We included all participants who enrolled in CDC-recognized organizations delivering the lifestyle change program between January 1, 2012, and December 31, 2019, and whose data were submitted to CDC's Diabetes Prevention Recognition Program. During this time, the number of participants who enrolled was 455,954. Enrollment, by delivery mode, was 166,691 for in-person; 269,004 for online; 4,786 for distance-learning; and 15,473 for combination. In-person organizations enrolled the lowest proportion of men (19.4%) and the highest proportions of non-Hispanic Black/African American (16.1%) and older (65+ years) participants (28.2%). Online organizations enrolled the highest proportions of men (27.1%), younger (18-44 years) participants (41.5%), and non-Hispanic White participants (70.3%). Distance-learning organizations enrolled the lowest proportion of Hispanic/Latino participants (9.0%). Combination organizations enrolled the highest proportions of Hispanic/Latino participants (37.3%) and participants who had obesity (84.1%). Most in-person participants enrolled in organizations classified as community-centered entities (41.4%) or medical providers (31.2%). Online and distance-learning participants were primarily enrolled (93.3% and 70.2%, respectively) in organizations classified as for-profit businesses or insurers. Participants in combination programs were enrolled almost exclusively in organizations classified as medical providers (89%). The National DPP has reached nearly half a million participants since its inception in 2012, but continued expansion is critical to stem the tide of type 2 diabetes among the many Americans at high risk.

This study describes the evolution of knockdown resistance (kdr) haplotypes in Aedes aegypti in response to pyrethroid insecticide use over the course of 18 years in Iquitos, Peru. Based on the duration and intensiveness of sampling (~10,000 samples), this is the most thorough study of kdr population genetics in Ae. aegypti to date within a city. We provide evidence for the direct connection between programmatic citywide pyrethroid spraying and the increase in frequency of specific kdr haplotypes by identifying two evolutionary events in the population. The relatively high selection coefficients, even under infrequent insecticide pressure, emphasize how quickly Ae. aegypti populations can evolve. In our examination of the literature on mosquitoes and other insect pests, we could find no cases where a pest evolved so quickly to so few exposures to low or nonresidual insecticide applications. The observed rapid increase in frequency of resistance alleles might have been aided by the incomplete dominance of resistance-conferring alleles over corresponding susceptibility alleles. In addition to dramatic temporal shifts, spatial suppression experiments reveal that genetic heterogeneity existed not only at the citywide scale, but also on a very fine scale within the city. © 2021 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd

Increases in mental health conditions have been documented among the general population and health care workers since the start of the COVID-19 pandemic (1-3). Public health workers might be at similar risk for negative mental health consequences because of the prolonged demand for responding to the pandemic and for implementing an unprecedented vaccination campaign. The extent of mental health conditions among public health workers during the COVID-19 pandemic, however, is uncertain. A 2014 survey estimated that there were nearly 250,000 state and local public health workers in the United States (4). To evaluate mental health conditions among these workers, a nonprobability-based online survey was conducted during March 29-April 16, 2021, to assess symptoms of depression, anxiety, post-traumatic stress disorder (PTSD), and suicidal ideation among public health workers in state, tribal, local, and territorial public health departments. Among 26,174 respondents, 53.0% reported symptoms of at least one mental health condition in the preceding 2 weeks, including depression (32.0%), anxiety (30.3%), PTSD (36.8%), or suicidal ideation (8.4%). The highest prevalence of symptoms of a mental health condition was among respondents aged ≤29 years (range = 13.6%-47.4%) and transgender or nonbinary persons (i.e., those who identified as neither male nor female) of all ages (range = 30.4%-65.5%). Public health workers who reported being unable to take time off from work were more likely to report adverse mental health symptoms. Severity of symptoms increased with increasing weekly work hours and percentage of work time dedicated to COVID-19 response activities. Implementing prevention and control practices that eliminate, reduce, and manage factors that cause or contribute to public health workers' poor mental health might improve mental health outcomes during emergencies.

One component of the Joint United Nations Programme on HIV/AIDS (UNAIDS) goal to end the HIV/AIDS epidemic by 2030, is that 95% of all persons receiving antiretroviral therapy (ART) achieve viral suppression.(†) Thus, testing all HIV-positive persons for viral load (number of copies of viral RNA per mL) is a global health priority (1). CDC and other U.S. government agencies, as part of the U.S. President's Emergency Plan for AIDS Relief (PEPFAR), together with other stakeholders, have provided technical assistance and supported the cost for multiple countries in sub-Saharan Africa to expand viral load testing as the preferred monitoring strategy for clinical response to ART. The individual and population-level benefits of ART are well understood (2). Persons receiving ART who achieve and sustain an undetectable viral load do not transmit HIV to their sex partners, thereby disrupting onward transmission (2,3). Viral load testing is a cost-effective and sustainable programmatic approach for monitoring treatment success, allowing reduced frequency of health care visits for patients who are virally suppressed (4). Viral load monitoring enables early and accurate detection of treatment failure before immunologic decline. This report describes progress on the scale-up of viral load testing in eight sub-Saharan African countries from 2013 to 2018 and examines the trajectory of improvement with viral load testing scale-up that has paralleled government commitments, sustained technical assistance, and financial resources from international donors. Viral load testing in low- and middle-income countries enables monitoring of viral load suppression at the individual and population level, which is necessary to achieve global epidemic control. Although there has been substantial achievement in improving viral load coverage for all patients receiving ART, continued engagement is needed to reach global targets.

The effect of HIV infection on COVID-19 outcomes is unclear. Studies in South Africa (1) and the United Kingdom (2) found an independent association between HIV infection and COVID-19 mortality; however, other studies have not found an association between poor COVID-19 outcomes and either HIV status among hospitalized patients (3-5) or HIV-associated factors such as CD4 count, viral load, or type of antiretroviral therapy (ART) (6). The effect of HIV infection on COVID-19 outcomes remains an urgent question in sub-Saharan Africa, where many countries are experiencing dual HIV and COVID-19 epidemics, and capacity to treat severe COVID-19 is limited. Using data from patients with probable or confirmed COVID-19 admitted to specialized treatment centers during March-December 2020 in Zambia, the Zambian Ministry of Health and CDC assessed the relationship between HIV infection and severe COVID-19 and COVID-19-associated death. Among 443 patients included in the study, 122 (28%) were HIV-positive, and of these, 91 (89%) were receiving ART at the time of hospitalization. HIV status alone was not significantly associated with severe COVID-19 at admission or during hospitalization or with COVID-19-associated death. However, among HIV-positive persons, those with severe HIV disease were more likely to develop severe COVID-19 and were at increased risk for COVID-19-associated death. Ensuring that persons maintain HIV disease control, including maintaining ART continuity and adherence, achieving viral suppression, and addressing and managing underlying medical conditions, could help reduce COVID-19-associated morbidity and mortality in sub-Saharan Africa.

INTRODUCTION: Healthcare workers (HCWs) in Zambia have become infected with SARS-CoV-2, the virus that causes coronavirus disease (COVID-19). However, SARS-CoV-2 prevalence among HCWs is not known in Zambia. METHODS: We conducted a cross-sectional SARS-CoV-2 prevalence survey among Zambian HCWs in twenty health facilities in six districts in July 2020. Participants were tested for SARS-CoV-2 infection using polymerase chain reaction (PCR) and for SARS-CoV-2 antibodies using enzyme-linked immunosorbent assay (ELISA). Prevalence estimates and 95% confidence intervals (CIs), adjusted for health facility clustering, were calculated for each test separately and a combined measure for those who had PCR and ELISA performed. RESULTS: In total, 660 HCWs participated in the study, with 450 (68.2%) providing nasopharyngeal swab for PCR and 575 (87.1%) providing a blood specimen for ELISA. Sixty-six percent of participants were females and the median age was 31.5 years (interquartile range 26.2-39.8 years). The overall prevalence of the combined measure was 9.3% (95% CI 3.8%-14.7%). PCR-positive prevalence of SARS-CoV-2 was 6.6% (95% CI 2.0%-11.1%) and ELISA-positive prevalence was 2.2% (95% CI 0.5%-3.9%). CONCLUSIONS: SARS-CoV-2 prevalence among HCWs was similar to a population-based estimate (10.6%) during a period of community transmission in Zambia. Public health measures such as establishing COVID-19 treatment centers before the first cases, screening for COVID-19 symptoms among patients accessing health facilities, infection prevention and control trainings, and targeted distribution of personal protective equipment based on exposure risk might have prevented increased SARS-CoV-2 transmission among Zambian HCWs.

School closures affected more than 55 million students across the United States when implemented as a strategy to prevent the transmission of SARS-CoV-2, the virus that causes COVID-19 (1). Reopening schools requires balancing the risks for SARS-CoV-2 infection to students and staff members against the benefits of in-person learning (2). During December 3, 2020-January 31, 2021, CDC investigated SARS-CoV-2 transmission in 20 elementary schools (kindergarten through grade 6) that had reopened in Salt Lake County, Utah. The 7-day cumulative number of new COVID-19 cases in Salt Lake County during this time ranged from 290 to 670 cases per 100,000 persons.(†) Susceptible(§) school contacts(¶) (students and staff members exposed to SARS-CoV-2 in school) of 51 index patients** (40 students and 11 staff members) were offered SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) testing. Among 1,041 susceptible school contacts, 735 (70.6%) were tested, and five of 12 cases identified were classified as school-associated; the secondary attack rate among tested susceptible school contacts was 0.7%. Mask use among students was high (86%), and the median distance between students' seats in classrooms was 3 ft. Despite high community incidence and an inability to maintain ≥6 ft of distance between students at all times, SARS-CoV-2 transmission was low in these elementary schools. The results from this investigation add to the increasing evidence that in-person learning can be achieved with minimal SARS-CoV-2 transmission risk when multiple measures to prevent transmission are implemented (3,4).

BACKGROUND: Between March and December, 2020, more than 20 000 laboratory-confirmed cases of SARS-CoV-2 infection were reported in Zambia. However, the number of SARS-CoV-2 infections is likely to be higher than the confirmed case counts because many infected people have mild or no symptoms, and limitations exist with regard to testing capacity and surveillance systems in Zambia. We aimed to estimate SARS-CoV-2 prevalence in six districts of Zambia in July, 2020, using a population-based household survey. METHODS: Between July 4 and July 27, 2020, we did a cross-sectional cluster-sample survey of households in six districts of Zambia. Within each district, 16 standardised enumeration areas were randomly selected as primary sampling units using probability proportional to size. 20 households from each standardised enumeration area were selected using simple random sampling. All members of selected households were eligible to participate. Consenting participants completed a questionnaire and were tested for SARS-CoV-2 infection using real-time PCR (rtPCR) and anti-SARS-CoV-2 antibodies using ELISA. Prevalence estimates, adjusted for the survey design, were calculated for each diagnostic test separately, and combined. We applied the prevalence estimates to census population projections for each district to derive the estimated number of SARS-CoV-2 infections. FINDINGS: Overall, 4258 people from 1866 households participated in the study. The median age of participants was 18·2 years (IQR 7·7-31·4) and 50·6% of participants were female. SARS-CoV-2 prevalence for the combined measure was 10·6% (95% CI 7·3-13·9). The rtPCR-positive prevalence was 7·6% (4·7-10·6) and ELISA-positive prevalence was 2·1% (1·1-3·1). An estimated 454 708 SARS-CoV-2 infections (95% CI 312 705-596 713) occurred in the six districts between March and July, 2020, compared with 4917 laboratory-confirmed cases reported in official statistics from the Zambia National Public Health Institute. INTERPRETATION: The estimated number of SARS-CoV-2 infections was much higher than the number of reported cases in six districts in Zambia. The high rtPCR-positive SARS-CoV-2 prevalence was consistent with observed community transmission during the study period. The low ELISA-positive SARS-CoV-2 prevalence might be associated with mitigation measures instituted after initial cases were reported in March, 2020. Zambia should monitor patterns of SARS-CoV-2 prevalence and promote measures that can reduce transmission. FUNDING: US Centers for Disease Control and Prevention.